New Approaches in Management and Marketing

Abstract Abstract The present study was conducted based on the paradigm of pragmatism and with a combined approach of induction and deduction. To achieve the study's objectives, a qualitative research design was used. This research is of an applicable-developmental type and aims to present a paradigmatic model for improving customers' mental image of Tehran chain stores. In terms of data collection, the research is classified as a non-experimental (descriptive) study conducted with a cross-sectional survey approach. The participants were managers of chain stores, and sampling was carried out using a theoretical method; meaning that individuals were selected based on their information adequacy and capacity to enrich the categories, and theoretical saturation was achieved by conducting 21 interviews. Data were collected through semi-structured interviews and a questionnaire. The indicators affecting customers' mental image of the store were extracted using the data-driven theory method and MaxQDA24 software and then prioritized using the fuzzy Savaray method. The results of the research model showed that causal conditions (customer experience management, co-creation of value with the customer, customer orientation and service quality) affect the central phenomenon (customers' mental image of the store). The mental image of the store, along with contextual conditions (marketing mix) and intervening conditions (store social responsibility), affects strategies and actions (internal branding and branding strategy). Ultimately, the aforementioned strategies lead to outcomes such as customer loyalty, satisfaction and trust, which reflect the dynamics and multidimensional function of mental image in promoting long-term customer relationships with the store. Introduction In recent years, chain stores with various brands have grown significantly in the country, and a fierce competitive arena has been created to attract and retain customers (Torkanloo et al., 2025). In such circumstances, customers' purchasing behavior is more influenced than ever by their perceptions and mental images of the stores. Therefore, branding and efforts to improve the store brand are a decisive factor in success (Solati et al., 2024). Sales managers and chain store owners have well understood that improving the store's mental image in the minds of customers can pave the way for improving the overall brand image and increasing the willingness to buy. By improving the store's image in the minds of customers, the likelihood of customer retention and return will increase (Sudirman & Muis, 2025). In this regard, understanding customers' mental perceptions and understanding how their attitudes towards the store are formed is considered a major prerequisite for developing effective marketing strategies and customer experience. Continuing to be present in such a dynamic market requires targeted investment in branding and creating differentiation in brand identity (Yuan & Yang, 2024). On the other hand, consumers' needs, preferences, and decision-making patterns have also undergone profound changes and have reached a more complex level than in the past. In response to these changes, large chain stores are trying to satisfy a diverse range of customers by offering a wide range of goods and brands (Jiang & Wu, 2023). However, this product variety alone does not guarantee success; because the main focus should be shifted from the brand of the goods to the store brand and the image that the customer has of the entire shopping experience. Therefore, in the current competitive conditions, retailers must improve their image among customers in order to defend their position in the market (Nakamori et al., 2024). In Iran, with the emergence of new structures and the use of new technologies in the retail sector, a fierce competitive environment has been formed between stores to attract the attention and trust of customers. Customers in this market, based on their mental impressions and associations, have a specific idea about each store, which creates a mental image of the store within their perception (Berah moghadam et al., 2024). According to this view, consumers keep a set of real or mental beliefs about each store in their memory and are confident in the accuracy of those beliefs. In such circumstances and given the increasing competition, it is necessary for the country's chain stores to adopt a customer-centric approach to marketing in order to recognize their current position and plan to achieve the desired situation (Raispour et al., 2025). Statistics show that customers play a key role in the continuation of competition and profitability of chain stores. Global studies indicate that an increase of only 5% in customer retention rates can increase company profits by 25 to 95% (Jones et al., 2025). Successful branding has caused a change of about 15% in customer retention. Also, consumers who are loyal to brands make up 65% of the company's business and spend 43% more on brands they are loyal to (Stephens et al., 2025). According to statistics from the National Chain Store Association, the turnover of the country's retail industry was estimated at about 920 trillion, of which the share of chain stores Chains accounted for 10 percent, and the rest belonged to small and traditional retailers (Bormeideh et al., 2024). Also, in the retail industry, which also includes chain stores, the average customer retention rate globally has been reported to be about 63 percent, while the overall average for other industries is about 75 percent (Aghakhani Bezdi Langari & Hassani, 2023). In such a situation, the gap between the actual perception of customers and the marketing approaches of chain stores increases, and the need for a scientific analysis of this gap and a solution to it is highlighted. Accordingly, the aim of the research is to identify the components affecting the mental image of customers, explain the cognitive and behavioral mechanisms that shape this image, and present a native paradigmatic model to improve the perception of customers of chain stores in Tehran. This aim has been formulated in order to answer a fundamental question: How is the pattern of improving the mental image of customers in chain stores in Tehran explained and what elements and relationships shape it?  Theoretical framework Brand image Brand image is a multidimensional concept that reflects the perceptions, feelings, and accumulated experiences of the audience of a brand. This image is the result of a continuous process of interaction between the customer and the brand and shows how people mentally perceive the identity, value, and reputation of the brand (Tahir et al,. 2024). Store Image The concept of "store image" was first introduced in the marketing management literature in 1958 by Martineau. He considered store image to be a set of customer perceptions formed by a combination of functional characteristics (such as the quality of goods and services, layout and price) and psychological characteristics (such as store atmosphere, employee behavior and customer emotions). Although this concept did not receive much attention in the early years, its importance has increased significantly in the last two decades with the rapid expansion of chain stores and changes in shopping patterns (Lang et al., 2023). Research Methodology This study was designed based on the paradigm of pragmatism and with a combined approach of induction and deductive and was conducted with the aim of providing a paradigmatic model for improving customers' mental image of chain stores in Tehran. In terms of methodology, it is classified as non-experimental and descriptive research and was implemented in the form of a qualitative design and cross-sectional survey. In the qualitative section, the participant population included theoretical experts in the field of marketing management and empirical experts including senior managers, marketing managers, and customer experience managers in chain stores in Tehran, and ultimately 21 interviews were used as the basis for analysis. Research findings The final result of the analysis was the identification of 6 selective codes, 12 central codes, and 63 open codes. The results of the research model showed that causal conditions (customer experience management, co-creation of value with customers, customer orientation and service quality) affect the central phenomenon (customers' mental image of the store). The mental image of the store, along with contextual conditions (marketing mix) and intervening conditions (store social responsibility), affects strategies and actions (internal branding and branding strategy). Ultimately, the aforementioned strategies lead to outcomes such as customer loyalty, satisfaction and trust, which reflect the dynamics and multidimensional function of the mental image in promoting long-term customer relationships with the store. It was also determined that the perceived risk index of purchasing from the store is in the first priority, the ethics index and adherence to ethical responsibility is in the second priority, the index of providing products and services based on customer needs is in the third priority, the index of establishing the possibility of mutual and reciprocal relationships with customers with a weight of 0.0864 is in the fourth priority, and the index of mental association of the store with customers is in the fifth priority. Conclusion The research results are in line with domestic and foreign studies, and in the form of an integrated model, it explains the mechanism of customer image formation. Causal factors including customer experience management, value co-creation, customer orientation and service quality, like the findings of Torkanloo et al. (2025), Yuan & Yang (2024), and Mousavi & Fadai (2023), confirm the determining role of customer experience, interaction and recognition of real customer needs. In the context of factors, the marketing mix and social responsibility are introduced in accordance with foreign research, guiding perception and strengthening positive mindset. Customer image as a multidimensional construct including perceived value, risk, ease of purchase, and brand associations is presented in this study in a more coherent way than previous studies. Internal branding strategies and brand strategy show that employee alignment and clear policy-making play a direct role in shaping image. The final outcomes including trust, satisfaction and loyalty are also consistent with the results of previous research and emphasize that positive image strengthens purchasing behavior and customer relationship continuity. The suggestions emphasize the importance of creating a lasting experience for customers through dynamic environmental design, targeted sensory stimuli, and professional employee behavior, and further consider it essential to provide a platform for two-way interaction for co-creation of value by utilizing behavioral data and customer participation in improving services. Also, strengthening the customer-centric approach by deeply understanding needs, providing personalized offers, and focusing on key customers is introduced as an effective factor in increasing loyalty. Improving the quality of services by improving physical standards, effective responsiveness, and strengthening empathetic behavior of employees, along with intelligent design of the marketing mix including product, price, promotion, and distribution, can create a coherent and attractive experience. Attention to social responsibility and institutionalization of ethical and environmental principles provide the basis for public trust and strengthening brand credibility, and ultimately focusing on improving the mental image of customers and developing internal and strategic branding strengthens organizational cohesion and a positive perception of the value and quality of Tehran chain stores.

Abstract Abstract This study aims to develop a native entrepreneurial marketing model for Iranian startups using a mixed heuristic approach. In this regard, the role of causal, contextual, and intervening factors in the formation and implementation of entrepreneurial marketing strategies was examined, and a model appropriate to the cultural and economic characteristics of Iran was designed. In the qualitative part of the research, using the grounded theory method and content analysis, 33 key categories were identified in the form of causal, contextual, intervening, strategies, and consequences conditions. Semi-structured interviews were conducted with 18 marketing and entrepreneurship experts. In the quantitative part, data from a researcher-made questionnaire was collected from 340 startup managers in Tehran, and the validity of the model was examined through structural equation modeling and SmartPLS software. The findings showed that innovation, customer orientation, and networking as causal factors; and factors such as technology infrastructure, government support, public culture, and employee behavior in contextual and intervention roles have a significant impact on entrepreneurial marketing strategies. These strategies include new marketing, training, digitalization, customization, and inter-organizational partnerships, which ultimately lead to outcomes such as organizational agility, enhanced customer engagement, opportunity discovery, and improved business performance. This indigenous model, emphasizing the specific characteristics of Iran’s entrepreneurial ecosystem, can be an effective tool for guiding government policymaking, accelerator support programs, and startup management decisions. The findings also indicate that a smart combination of contextual and strategic factors can lead to sustainable competitive advantage and improve the position of startups in domestic and international markets. Introduction This research aims to develop a native entrepreneurial marketing model for Iranian startups using a mixed heuristic approach. This study examines the causal, contextual, and intervening factors in the formulation and implementation of entrepreneurial marketing strategies and presents a model appropriate to the economic and cultural characteristics of Iran. The research approach consists of two qualitative and quantitative parts. In the qualitative part, grounded theory and content analysis were used to identify key factors affecting entrepreneurial marketing. In this stage, semi-structured interviews were conducted with 15 entrepreneurial marketing experts and an initial model was designed. In the quantitative part, data collected from 340 startup managers were analyzed and the proposed model was validated using structural equation modeling. To increase the accuracy of the analysis, SmartPLS software was used and the validity and reliability of the measurement tools were carefully examined. The findings showed that innovation, customer orientation, and networking play a key role in the development of entrepreneurial marketing strategies. Also, government support, economic infrastructure, and public culture as contextual factors, and digital technologies, organizational culture, and employee behavior as intervening factors have a significant impact on the implementation of this model. The results indicate that the interaction between these factors and the adopted strategies improves the performance of startups in challenging environments. Entrepreneurial marketing strategies enhance the financial and competitive growth of startups by increasing organizational agility, improving interaction with customers, and identifying new opportunities. This study provides recommendations for business managers and policymakers to optimize their marketing strategies by focusing on innovation, customer orientation, and networking. It is suggested that future studies examine the role of advanced technologies such as artificial intelligence, big data analytics, machine learning, and augmented reality in optimizing entrepreneurial marketing models to ensure the model's adaptability to future changes. Theoretical Framework Given the specific characteristics of today's world, including rapid change, increasing complexity, and increasing competition, as well as the inefficiency of traditional methods such as strategic planning and classic market forecasts, it has become necessary to pay attention to new methods to overcome these changes. In the world of modern businesses, startups are recognized as the main players in the innovative economy, which seek to create value and gain market share by utilizing new technologies and flexible business models. However, the survival and growth of these new companies in an environment characterized by economic uncertainty, rapid technological change, and intense competition is a serious challenge. In such circumstances, startups need innovative strategies that are adaptable to their environment to survive and grow in competitive markets. One of the most effective strategies for startup growth in uncertain times is entrepreneurial marketing, which, due to its flexible and opportunity-oriented nature, allows startups to be more agile in the face of environmental changes and challenges and to benefit from sustainable competitive advantages. Unlike traditional marketing, which emphasizes long-term planning and specific processes; entrepreneurial marketing, as a dynamic model, focuses on identifying new opportunities, taking targeted risks, innovating in service delivery, and creating value for customers. These characteristics are especially important for startups in the early stages of development, as limited financial and human resources and an uncertain market environment force them to adopt more flexible approaches. Entrepreneurial Marketing Entrepreneurial marketing refers to processes in which entrepreneurs use innovative methods to develop the market, establish effective relationships with customers, and achieve new business opportunities. Unlike traditional models that focus on exploiting existing resources, this approach emphasizes innovation, courage in facing risks, and flexibility in decision-making. Many studies have shown that the use of entrepreneurial marketing can improve financial performance, increase market share, and enhance the competitive position of companies. However, existing entrepreneurial marketing models are mainly designed based on data and conditions of developed countries, and their localization is challenging for countries like Iran that face their own economic, infrastructural, and cultural limitations. Therefore, the need to develop a local model for entrepreneurial marketing in Iranian startups is strongly felt; a model that, while taking into account the environmental characteristics of Iran, has modern research approaches for scientific and operational structuring. Startup Startups operate in highly variable and uncertain conditions as new businesses trying to meet market needs in a different way by offering new products or services. These companies usually face high risk, limited resources and ambitious goals. In fact, what distinguishes a startup from other businesses is its innovative, risk-taking and opportunistic nature. Successful startups usually operate on the basis of a creative human team, a collaborative culture and an approach based on experimentation and learning. On the other hand, marketing in startups does not simply mean advertising and sales, but has a deeper meaning that includes a precise understanding of customer needs, designing a differentiated value proposition, creating a unique customer experience and developing long-term relationships. In this direction, digital technologies, data analysis and new communication tools play an important role in enhancing the effectiveness of entrepreneurial marketing. Therefore, the present study is trying to identify the influential components in the Iranian space, to design a comprehensive model for entrepreneurial marketing in startups that not only has a strong theoretical support, but also can be used and implemented in practice by managers. Research Methodology In this regard, the present study has used a mixed heuristic methodology. In the qualitative part, data were collected using semi-structured interviews with 18 experts in the fields of marketing, entrepreneurship, and startup management. Data analysis was conducted using the grounded theory method in three stages of open, axial, and selective coding, as a result of which 33 key categories were identified in the form of five main components: causal conditions, contextual conditions, intervening factors, strategies, and consequences. Then, based on these components, an initial conceptual model was designed that served as the basis for the quantitative part of the research. In the quantitative part, in order to empirically evaluate the model, a researcher-made questionnaire was designed and distributed among 340 startup managers active in Tehran. The collected data were analyzed using SmartPLS software and structural equation modeling method. The results of data analysis confirmed the proposed model and showed that the identified dimensions have statistical validity and reliability. Research findings The findings indicated that the variables of innovation, customer orientation, and networking have the greatest impact in the causal dimension. In the contextual dimension, structural factors such as government support, information technology infrastructure, and general culture of society play an important role in shaping the entrepreneurial marketing context. Also, in the intervention dimension, organizational culture, leadership style, and employee behavior play a facilitating and reinforcing role in implementing strategies. The identified strategies also included innovative marketing, process digitization, service personalization, brand development, employee training, and creating strategic partnerships. These strategies ultimately led to outcomes such as increasing organizational agility, improving customer interaction, discovering market opportunities, and improving the financial and competitive performance of startups. In fact, this model is able to pave the way for the development of new businesses in volatile markets by considering the link between intra-organizational and environmental variables. On the other hand, the analysis of the research results showed that integrating innovative strategies with capable human resources and a learning organizational culture can increase the capacity for adaptation and innovation at different organizational levels. Conclusion This indigenous entrepreneurial marketing model is not only designed to suit the specific conditions and challenges of the Iranian entrepreneurial ecosystem, but also has the ability to be applied practically at different decision-making levels. From a theoretical perspective, the present study has contributed to the enrichment of the entrepreneurial marketing literature in the context of developing countries by providing a comprehensive framework. From a practical perspective, the research results can be used by policymakers, managers, and young entrepreneurs. Finally, the present study suggests that in future studies, the role of emerging technologies such as artificial intelligence, big data analysis, augmented reality, and blockchain in the design and implementation of entrepreneurial marketing strategies be examined. Also, conducting comparative research among developing countries can lead to the identification of common patterns or significant differences. Focusing on developing dynamic models that are adaptable to environmental and technology-driven changes will be valuable avenues for continuing this line of research.

Abstract Abstract
The present study aims to present a branding model for cooperative products in Ilam Province, in terms of its applicable-developmental purpose. In terms of the nature of the data, it is qualitative-quantitative with a data-based approach, and finally, in terms of the problem or research method, it is descriptive; therefore, this research is placed in the framework of applicable research in terms of orientation. In the qualitative part of this research, theoretical sampling was used according to the subject. The statistical sample in the qualitative part includes 20 professors, specialists, experts, marketers, entrepreneurs, and owners of production cooperative companies; studied by purposive sampling and snowball method. In the qualitative part of the research, the data theorizing approach was used in line with the emergence of the learned helplessness model. In the quantitative part, the statistical population includes 384 customers of production cooperatives in Ilam province using the Cochran formula in unlimited communities and simple random sampling method. The data obtained from the distribution of questionnaires were analyzed in two parts: descriptive and inferential findings. The research findings led to the identification of causal conditions (including intra-organizational and extra-organizational factors), contextual conditions (including technical and legal infrastructures), intervening conditions (including economic and cultural barriers), strategies (including marketing and brand development strategies), and consequences (including economic and social consequences). The final research model shows that successful branding of cooperative products in Ilam province requires attention to all these factors and appropriate interaction between them. The results of this research can help managers and policymakers in the cooperative sector to develop and strengthen the brand of cooperative products and provide the basis for increasing the competitiveness and sustainable development of cooperatives in Ilam province.
Introduction
Most of the products of cooperatives in Ilam province are marketed without a brand. In such a case, there is no name or symbol of Ilam province in the production and supply of cooperative products to the market, and the products of the province are marketed under the names of others. Therefore, the cooperative products of the province are easily exported under the names of other provinces of the country due to weakness in branding and inattention to marketing, so that the credit of producing these products goes to other provinces of the country. The audience and customers of each product have different views and opinions regarding existing brands. This situation is called brand image. The products of cooperatives in Ilam province are among the productions that, despite having a high volume of product, do not have a market share and remain unknown among customers. In such a case, despite the fact that Ilam province has cooperatives related to the production in the fields of agriculture, horticulture, dairy products, animal oil, etc., there is no name or address in the production and supply of cooperative products in domestic and international markets, and the province's products are marketed under others' names. Branding and brand management have long existed in different societies to identify individuals and services in various ways. The main motivation for branding is to introduce products to customers and differentiate these products from competitors' products; therefore, it can be said that the success of cooperative products depends on the success of the product brand (Jablipo, 2015). A brand with a well-known personality brings customers' perception of the brand, as well as customer loyalty, less vulnerability to competitor marketing efforts, higher profit margins, and fewer negative customer reactions, among other results of a strong brand (He et al., 2022). A strong brand can lead to numerous marketing benefits and increase the competitive power of the product (ShiYon et al., 2022). It is usually interpreted that a brand with a positive and well-known image causes consumers to respond more favorably to product marketing activities (Malarvizhi et al., 2022). A strong brand symbolizes quality, reliability, and distinctiveness, thus improving the product's position in the market (Khan et al., 2022). In this study, researchers seek to find out the question: how and by means of what model can the branding of Ilam province cooperatives' products be presented?
Theoretical Framework
The Concept of Brand
Product brand includes broad concepts that are examined from different perspectives of marketing, consumer psychology, and strategic management. A brand is defined as a name, word, sign, symbol, or a combination of these elements that is used to identify the goods and services of a seller or group of sellers. Instrumental brand is a value-creating concept for customers and businesses, and includes a set of shared emotional bonds (He, 2022). Brand attributes may be real or unreal, emotional or logical, tangible or intangible. A brand is formed by building trust in specific promises that demonstrate unique and meaningful benefits. These promises can be formed through various communications with customers, including Internet search, websites, social media, advertising, shopping experiences, and customer service.
Importance of Brand
The importance of brand is felt more than ever in today's economic societies. Brands have become symbols and main players in various sectors including economic, social, political, cultural, and sports. The importance of brand is in achieving profit, facilitating faster selection, creating awareness and increasing the chances of survival of products. Branding is used as a tool to create distinction between manufacturers' goods (Zhang, 2022).
Brand equity
Brand equity is one of the most important marketing concepts, which includes brand awareness, perceived quality, brand loyalty, and differences in consumer choice between products with a strong brand and products with similar characteristics without a brand. Brand equity includes brand assets, brand power and brand value. (Kimura, 2021) Brand characteristics include simplicity, brevity, ease of pronunciation, lack of negative components, quick placement in people's minds and memories, ability to be introduced in the media and ability to be printed on product packages.
History of Branding in Cooperatives in Ilam Province
With the passage of time and increasing competition in the market, cooperatives realized that branding is an essential tool for survival and growth. In recent years, some cooperatives in Ilam Province have gradually begun to formulate and implement branding strategies. These strategies include determining brand identity, designing attractive logos and packaging, and using various media for advertising and brand promotion. Research on branding in cooperatives shows that this process can help strengthen the competitive position and increase the performance of cooperatives. For example, a study in Ilam Province showed that cooperatives that have taken branding seriously have been more successful in attracting customers and increasing sales (Antunes et al., 2022).
Research Methodology
In terms of the nature of the data, this research is qualitative-quantitative with a data-based approach; and in terms of the problem or research method, it is descriptive; therefore, this research falls within the framework of applicable research in terms of orientation. In the qualitative part of this research, theoretical sampling was used according to the topic. The statistical sample in the qualitative part includes 20 professors, specialists, experts, marketers, entrepreneurs, and owners of production cooperatives, selected by purposive sampling and snowball method. In the qualitative part of the research, in line with the emergence of the learned helplessness model, the data theorizing approach was used. In the quantitative part, the statistical population includes 384 customers of production cooperatives in Ilam province using the Cochran formula in unlimited communities and simple random sampling method. The data obtained from the distribution of questionnaires were analyzed in two parts: descriptive and inferential findings. The research findings led to the identification of causal conditions (including internal and external factors), contextual conditions (including technical and legal infrastructure), intervening conditions (including economic and cultural barriers), strategies (including marketing and brand development strategies), and consequences (including economic and social consequences).
Research findings
SPSS and AMOS statistical software were used to analyze the data. Confirmatory factor analysis was used to confirm the questions related to each of the variables. The results of factor confirmation using AMOS software are listed, given that the factor loading of all questions is greater than 0.3 and the significance level values ​​are greater than 1.96; therefore, it can be said that the questionnaire questions for this variable were formulated correctly.
Conclusion
The findings of this study indicate that factors such as product quality, appropriate pricing, attractive packaging, and targeted advertising play a significant role in the success of branding cooperative products in Ilam Province. Also, the results of this study showed that the use of modern technologies in the production and marketing process can help promote the brand of cooperative products in Ilam Province. In summary, it can be said that branding cooperative products in Ilam Province requires a comprehensive and targeted approach that considers all factors affecting the success of the brand. By focusing on product quality, appropriate pricing, attractive packaging, targeted advertising, and the use of modern technologies, cooperatives in Ilam Province can take effective steps towards branding their products and, in this way, pave the way for the economic and social development of the province.

Abstract The present research aims to systematically identify and refine the components of audience-centricity in the field of art. This study, employing a sequential exploratory mixed-methods approach, was executed in two main stages. In the qualitative stage, using the qualitative content analysis method and purposeful sampling, 19 credible scientific articles were deeply reviewed. The coding process, utilizing NVIVO software, resulted in the extraction of 39 open codes, 9 axial categories, and 4 core components. In the quantitative stage, to refine these components within the specialized context of art, the fuzzy screening technique was employed, utilizing the opinions of 12 experts. Data were collected and analyzed using a researcher-made questionnaire. The research findings indicated that out of the initial 39 indicators, 11 were confirmed as the final components of audience-centricity in art. Among these, three indicators—“Investing in Continuous Learning and Capability Development,” “Respecting Privacy and Ethics in Data Usage,” and “Transparency in Actions and Communications”—received the highest importance scores. This framework, by transitioning from “production-centric art” to “trust-centric art,” opens a new horizon for sustainable and meaningful interaction between artists, cultural managers, and audiences in the face of future uncertainties and complexities.
Introduction
In today’s hyper-competitive world, brands strive to increase their share of their target customers’ minds, their share of customers’ wallets, and ultimately, a larger percentage of customer lifetime value (Faraji et al., 2025). Within the marketing toolkit of these brands, audience-centricity and the precise and deep identification of the needs, desires, and behaviors of target customers are considered among the most important effective tools for achieving these brand objectives. Target audiences in different industries possess distinct and unique characteristics. Due to the special nature of artistic products and considering artists as personal brands, the target audience in art differs significantly from that of non-artistic brands. This includes brands active in the art scene such as gallerists, curators, or art exhibition organizers. Understanding these audiences and meeting their needs and desires requires a different perspective.
On the other hand, in the contemporary world, art, as a dynamic and multidimensional phenomenon, is constantly evolving in interaction with social, cultural, and technological contexts. One of the key pillars of this transformation is the shift in the “audience’s” position from a passive element to an active agent, interpreter, and participant in the process of creating and perceiving the artwork (Wald-Fuhrmann et al., 2026). The main issue here is that the prevailing paradigm in the scientific examination of audience behaviors, attitudes, desires, and needs is still influenced by the paradigms governing marketing science in conventional manufacturing or service industries, and it does not precisely consider the fundamental differences within the art domain. This is while traditional survey methods and static analyses are no longer sufficient for the needs of brands active in the field of art. The necessity of revising the indicators of audience-centricity is increasingly felt due to the diversity in message reception and the mismatch between source encoding and receiver decoding within the context of art (Sampah et al., 2025). Accordingly, the present paper seeks to answer two main questions: First, what are the components of audience-centricity through in-depth exploration and content analysis of credible scientific texts and articles? And second, which of these components hold greater importance by employing the fuzzy screening technique and expert opinions in the field of art?
Theoretical Foundations
Ontological Transformation of the Concept of Audience; From Mass Passivity to Active Subjectivity
The concept of the audience, throughout the history of communication theories, has transformed from a mere receiver to a central actor (Ghorbannezhad et al., 2024). In classical and linear perspectives, the audience was positioned at the end of the communication chain, playing a passive role in message reception. However, with the emergence of new paradigms, the audience is considered an active subject who selects and interprets the work based on their needs, cultural backgrounds, and lived experiences (Abdou, 2025).
Audience-Centricity as a Strategic Paradigm in the Communications Age
Audience-centricity, in its broadest sense, is not merely a marketing technique; rather, it is a philosophical paradigm whose core is the transition from “production-centricity” to “human-centricity.” This approach is based on the principle that true value lies not in the commodity or message itself, but in the experience and meaning created for the end-receiver (Hegen, 2017).
Audience-Centricity in the Specialized Arena of Art; Aesthetic and Economic Layers
In the realm of art, audience-centricity acquires deeper dimensions that distinguish it from other fields. This concept in art is analyzed at three levels: the aesthetic-philosophical level, which emphasizes the “semantic openness” of the work, allowing the audience to complete the work through their own interpretation (James, 2024); the communicative-experiential level, which focuses on the quality of interaction and the creation of inclusive pathways for understanding art, where participatory and interactive art transforms the audience’s presence into an essential element of the work (Kasiyan, 2019); and the economic-organizational level, which is shaped by new models such as “crowdfunding” and the “sharing economy,” turning the audience into a creative and material stakeholder of the work (Ersöz, 2015)
Research Methodology
The present research is philosophically based on the pragmatism paradigm, emphasizing the applicability of knowledge. This research is developmental in terms of its objective and exploratory-analytical in nature, conducted with a mixed-methods approach of the exploratory sequential type. In the first step, dedicated to identifying components (qualitative part), the qualitative content analysis method with an inductive approach was used to extract the components of audience-centricity. The statistical population for this section included all documents, scientific records, and research articles published in reputable domestic and international databases within the timeframe of 2015 to the present, addressing topics of audience and art. The sample consisted of 19 articles selected using purposive sampling. Data analysis was performed using NVIVO software through three stages of open, axial, and selective coding. In the second step, component screening (quantitative part), the aim was to refine the components identified within the specialized context of art, utilizing the fuzzy screening technique. The statistical population for this step comprised art experts, including university faculty members, distinguished artists, and senior cultural managers. A sample of 12 individuals was selected using snowball purposive sampling and analyzed via a researcher-made fuzzy screening questionnaire. The content validity of the questionnaire was reviewed by professors and 5 prominent experts (outside the main sample). Furthermore, for reliability in the fuzzy section, instead of Cronbach’s alpha, the method of agreement and consensus among expert groups was used.
Research Findings
A qualitative content analysis, through an in-depth study of 19 articles, resulted in the extraction of 39 initial open codes. These codes were key sentences, concepts, or phrases that directly or indirectly referred to dimensions of audience, interaction, technology, economy, or the future of art. In the axial coding stage, these 39 codes were categorized into 9 general themes based on semantic and conceptual similarities. The results of the fuzzy screening indicated that out of the initial 39 indicators, 11 components were selected as the “golden components” of audience-centricity in art. The three components “Investing in continuous learning and capability development,” “Respecting privacy and ethics in data usage,” and “Transparency in actions and communications” received the highest degree of importance from the experts. Additionally, the component “Personalization of product features” received the lowest level of importance, suggesting a different approach to audience-centricity in art compared to other fields.
Discussion and Conclusion
The findings of this study, beyond merely presenting a refined list of indicators, propose a profound paradigm shift in the philosophy of contemporary art: a transition from an instrumental view of the audience toward an “ontological co‑creation.” Within this emerging framework, the audience is neither a “target” for marketing nor even a simple “participant,” but becomes an inseparable component of the very being of the artwork.
The fuzzy refinement of the initial 39 indicators into 11 golden indicators—ultimately distilled into three core criteria (“investment in continuous learning,” “data ethics and privacy,” and “transparency”)—outlines a roadmap in which the future of art is fundamentally tied to trust as its most valuable intangible asset. This implies that, in the artistic ecosystems of tomorrow, the success of an artwork will not be measured by the number of viewers or sales, but by the depth of the existential bond formed between the artwork and its audience within an ethical and transparent environment.
While the results of this study reinforce and validate previous research, they also open new theoretical horizons. The alignment between the final fuzzy‑filtered components and the existing literature can be analyzed at three levels:

First, the confirmation of foundational theories such as market orientation (Wut et al., 2026) and value co‑creation (Ranjan & Upadhyay, 2025). Indicators such as “understanding the needs and preferences of the target audience” and “designing for multisensory and immersive experiences” directly emphasize the need for systematic information gathering and the creation of unique experiences—fully consistent with Ersöz (2015) regarding participatory arts and the stimulation of the five senses.
Second, the extension of these theories within the domain of art. For example, the finding of Bruen et al. (2025) regarding the influence of audience awareness of AI technologies on the valuation of artworks appears in this study as the highly significant indicator of “utilizing digital platforms and social media”—reflecting the acceptance of technology not merely as a tool, but as a component of the artwork’s ontology.
Third, and most importantly, the study introduces innovative ethical‑strategic indicators. While domestic research (e.g., Fallah et al., 2023) emphasized “message source credibility” and “avoiding biased perspectives,” fuzzy screening in this research highlights indicators such as “investment in continuous learning,” “respect for privacy and ethical data use,” and “transparency in actions and communications” as golden priorities. These findings not only bridge gaps in previous fragmented case studies (such as Leow & Ch’ng, 2021 in virtual reality, or Mokhtari Dehkordi, 2023 in multimedia art), but—drawing on theories of the experience economy (Esagala & Ntale, 2026) and relationship marketing (Madruga et al., 2024)—provide a comprehensive and integrative framework applicable across all artistic fields.

A key point is the strong alignment with Wald‑Fuhrmann et al. (2026) regarding the influence of performance formats on audience experience, as well as Zuo & Au’s (2026) theory of “media richness,” where the highly significant indicator “offering products/services through multiple channels (physical, online, hybrid)” reinforces the necessity of multi‑modal artistic engagement in the digital era.
Thus, by combining qualitative content analysis with fuzzy logic, this study not only consolidates previously scattered elements into a coherent system but also advances beyond existing theories by introducing data‑driven ethics and continuous learning as foundational pillars of audience‑centricity—thereby offering a roadmap for transitioning from mass‑oriented art to trust‑oriented art in the future.

Abstract The aim of the present study is to identify and prioritize the challenges of implementing digital marketing in knowledge-based companies located in Qom and Markazi provinces. The research follows a mixed-methods approach, utilizing both qualitative and quantitative techniques. Qualitative data were collected through a literature review and interviews with fourteen managers of knowledge-based companies, selected via snowball sampling until the stage of theoretical saturation. These data were analyzed by the thematic analysis method to identify and categorize the issues. For qualitative data organization, coding, and analysis, MAXQDA 2020 software was employed. Initially, 42 issues were identified and classified into six general categories: cognitive and behavioral issues of managers, financial and funding issues, content-related issues, human resource issues, marketing-oriented issues, and issues related to changes in social platforms and networks. In the second stage, the issues were screened by the Fuzzy Delphi technique in Excel. The screening resulted in 22 final factors, which were then prioritized by the MARCOS technique. The prioritization results indicate that “weakness in retaining expert and specialized human resources” and “lack of marketing research tailored to the digital environment” held the highest priority.
Introduction
The market is a dynamic, living, and evolving phenomenon (Azizi et al., 2020, p. 4). As the science of responding to human needs within a turbulent market environment, this academic discipline must maintain flexibility and alignment with environmental changes to address corporate requirements. One of the most significant transformations is the remarkable progress and expansion of cyberspace. Given the substantial growth of information and communications technology, which has influenced all aspects of social life and induced extensive changes in various work methods, it can be stated that digital communication tools have encompassed nearly all facets of modern human life (Iran Aghideh, 2021, p. 121; Farzinmehr et al., 2025, p. 102).
The widespread use of the Internet and digital tools presents a unique commercial opportunity for managers. The integration of social life with the digital sphere has led to the emergence of a new concept termed digital marketing (Iran Aghideh, 2021, p. 121). As a branch of marketing management and advertising, digital marketing encompasses all tools and activities related to the supply and promotion of products across digital platforms (Gholipour et al., 2016, p. 8; Mohseni et al., 2023, p. 229). This form of marketing refers to the utilization of the Internet and digital technologies such as computers, websites, mobile devices, applications, and email (Ayush et al., 2020, p. 225). Digital marketing, as a new paradigm, has revolutionized the marketing system and marketing knowledge. Given that it is conducted within the context of the Internet and through its associated techniques, it can be considered the most effective way to introduce products and improve the performance of knowledge-based companies. Consequently, the introduction and marketing of products via digital marketing are decoupled from their place of production; customers can be found from any point in Iran or even the world, and they, in turn, can establish connections with various manufacturers (Shirdel et al., 2022, p. 3).
On the other hand, knowledge-based businesses are on the rise and are considered vital to the economy; the knowledge-based economy accounts for a large share of the economy in many developed countries (Hayes, 2021). Therefore, knowledge-based companies can be viewed as the core and driving force of the knowledge-based economy. These companies, which often seek to generate wealth through high technologies, are critical drivers of growth.
These firms, like any other, require marketing functions, and specifically, the position of digital marketing is vital and essential in advancing their objectives. Digital marketing can bring numerous benefits to knowledge-based companies that produce and provide high-value-added goods and services based on knowledge and technology (Center for the Growth of Knowledge-Based Companies and Institutions, 2024).
Thus, the implementation of digital marketing in knowledge-based companies can significantly contribute to their progress. However, the use of digital marketing in these companies faces challenges and problems that have not been adequately addressed in previous research. Given the necessity of market development and increasing sales for knowledge-based companies, it is imperative to conduct precise and effective research to achieve these goals; identifying these challenges will pave the way for their resolution. Therefore, the present study seeks to address the issue of identifying the obstacles and problems hindering the use and implementation of digital marketing in knowledge-based companies. The research question is: What are the challenges and issues of implementing digital marketing in knowledge-based companies, and which of these hold higher priority?
Theoretical Framework
Digital Marketing
Since the emergence of buying and selling in human relations, the concept of marketing has existed (Mohseni et al., 2023, p. 227). Having transitioned through eras such as hunting, agriculture, and the first to third industrial revolutions, we are now witnessing the Fourth Industrial Revolution. This revolution is essentially considered a revolution in communications, linked to internet technologies that have transformed the world; thus, organizational agility in responding appropriately to changes can be regarded as the key to their success (Petrosian, 2023). Some believe that the emergence of digital marketing coincided with the advent of radio. In 1990, only a few individuals had access to the internet, a number that gradually increased until there were approximately 18 million internet users by 1995. In 1999, the Salesforce website introduced the first customer management system for storing user information, tracking their behavior on the site, and monitoring campaigns; this software is recognized as the core foundation for the formation of digital marketing (Mohseni et al., 2023, p. 228).
In simple terms, digital marketing can be defined as the execution of marketing plans and strategies through the internet and other related digital platforms. In fact, it can be defined as a marketing approach that primarily relies on the internet to communicate with target audiences through various digital media channels and platforms. In digital marketing, marketers utilize the internet, mobile devices, email, social media, search engines, video streaming platforms, and other channels to reach customers. At the same time, some marketing experts argue that digital marketing should be viewed as an entirely different and new endeavor that requires novel and distinct methods for approaching, communicating with, and understanding customers. Since digital technology lies at the heart of all companies, digital marketing serves as an essential tool for brands and marketers ydigital marketing provides organizations with the opportunity and space to strive for success in utilizing local and domestic markets (Nejati, 2022, p. 25).
Research Methodology
The present study adopts an inductive approach and falls within the category of exploratory and applicable research. Its strategy is survey-based, and in terms of implementation, it was conducted by a mixed-methods design. Data collection instruments included documents and semi-structured interviews in the qualitative phase, and a questionnaire in the quantitative phase. The theoretical population consisted of knowledge-based companies located in the Science and Technology Parks of Qom and Arak. Fifteen companies were selected as the sample for interviews, and data collection continued until theoretical saturation was achieved.
Research Findings
The thematic analysis method and MAXQDA 2020 software were employed for data analysis. The findings revealed 150 initial codes which, through consolidation, resulted in 42 basic themes. these were categorized into six organizing themes: cognitive and behavioral issues of managers, financial and funding issues, content-related issues, human resource issues, marketing-oriented issues, and changes in social platforms and networks. In the second step, due to the high number of basic themes, the Fuzzy Delphi method was applied to screen the issues. A questionnaire containing 42 issues was sent to 10 experts; ultimately, 22 issues with a defuzzified value greater than 0.5 were selected as the final challenges. For the final ranking, the MARCOS method was utilized.
Conclusion
The present study aimed to identify and prioritize the dimensions and components of implementing digital marketing in knowledge-based companies. The results of this study are consistent with the findings of previous studies of Shiri & Moradnejadi (2024); Gholipour et al. (2016); Papi et al. (2022); and Farast (2020). Based on the prioritization results, factors such as weakness in retaining expert and specialized human resources, lack of marketing research aligned with the digital environment, the lack of up-to-date digital marketing education in universities in line with the latest scientific and technological developments, and insufficient attention to the long-term outcomes of digital marketing were identified as the most significant issues. As noted by Shiri and Moradnejadi (2024), efficient human resources equipped with sufficient knowledge, who can address societal needs—including those of knowledge-based companies—through their expertise and contribute to national development, are of great importance.
As long as there is no adequate and accurate understanding of the market and competitors, the application of marketing knowledge will face challenges. Excessive focus on innovation and product uniqueness (without attention to the needs of online customers), along with insufficient awareness of marketing and digital marketing and the failure to conduct marketing research appropriate to the digital environment, will collectively lead to difficult and costly outcomes for businesses.
Based on the research findings, the following practical recommendations are proposed:

Designing a comprehensive system for the retention and development of digital human capital
Institutionalizing data-driven digital marketing research
Redesigning the university education system with a skills-oriented approach
Enhancing managers’ strategic literacy regarding digital marketing
Reforming organizational structures and consolidating the position of digital marketing
Diversifying digital channels and managing platform-related risks
Improving infrastructures related to trust, security, and digital financial transparency

Abstract The purpose of this study is to present a performance evaluation management model for the internal supply chain applying a hybrid approach of DEMATEL and the Analytic Network Process (ANP). In terms of purpose, the research is applicable, and regarding data collection it is descriptive–survey in nature. The statistical population of the study consisted of 12 experts, including 5 members from the hospital’s internal logistics unit and 7 managers from Namazi Hospital. To determine the relationships among 13 indicators within the five main components of the hospital’s internal supply chain, the DEMATEL method was employed. These relationships were subsequently incorporated into the Analytic Network Process model, and the weights of the 13 indicators were calculated by Super Decisions software. The indicators were ranked as follows: performance of completing patient treatment through access to comprehensive treatment resources, delay‑free patient treatment performance, patient waiting time, service provider supply time, professional value‑added productivity, error‑free performance in patient safety, continuity of the clinical treatment supply process, reliability and accessibility of suppliers of healthcare service resources, communication with patients, overall logistics cost management in the clinical treatment supply chain, reliability of investment and growth and revenue of the clinical treatment process, improvement of hospital staff skills to prevent errors, and development of organizational culture. The results of this study indicated that the hospital’s internal supply chain has a positive, direct, and significant impact on improving hospital performance. The findings of this research can be highly useful for optimizing managerial practices and supporting effective decision‑making among hospital managers and administrators.
Introduction
Supply chain management refers to the coordination and management of a complex network of activities aimed at delivering the final product to the end consumer or customer. It is a critical function in business operations and includes processes such as the procurement of raw materials, manufacturing and assembly of products, order registration and tracking, distribution through various channels, and ultimately delivery to customers. The structure of a company’s supply chain consists of external suppliers, internal organizational operations, external distributors, and customers (Glavas et al., 2018).
Compared with traditional management approaches that focus on managing individual members separately, supply chain management emphasizes managing relationships and seeks solutions to reduce supply, production, and distribution cycles while increasing flexibility and responsiveness. This approach aims to improve existing processes and facilitate the development of new products capable of meeting continuously changing customer demands. To achieve this, organizations need to adopt and implement supply chain technologies and information systems in order to reduce supply chain cycles and integrate their operational processes (Talaei & Ziaian, 2022).
Christmann and Taylor (2012) state that exporting and selling to international customers are two primary drivers for improving firms’ environmental performance. When companies export their products, they often face environmental or “green” requirements, which can motivate manufacturing firms to implement supply chain management practices. In many countries, exporting products requires obtaining specific certifications demonstrating that the use of these products does not harm the sustainable development of the destination country. In addition, consumer pressure also encourages organizations to adopt supply chain management practices. The effects of drivers for implementing supply chain management can be evaluated through three dimensions of firm performance: environmental performance, operational performance, and economic performance (Zoogah, 2011).
Environmental performance has become increasingly important for managers of manufacturing companies due to regulatory requirements, public awareness, and the pursuit of competitive advantage. Recent studies have provided insights into potential patterns of supply chain relationships that can enhance environmental performance. However, investment in such programs can be substantial, and the pressure for environmental investment may be high, while improvements in environmental performance resulting from the adoption of these practices are not always guaranteed (Kim et al., 2019).
Therefore, considering the growing importance of environmental supply chains and the performance of internal supply chains, as well as the increasing attention these topics have received in recent years and their associated benefits, this study investigates the indicators affecting internal supply chain performance. Accordingly, the main research question addressed in this study is: **What is the model for managing the performance evaluation of the internal supply chain using a hybrid approach of DEMATEL and the Analytic Network Process (ANP)?
Theoretical Framework
The supply chain is an essential network within the business infrastructure significantly facilitating production and distribution processes in companies that market their products. This network plays a vital role in creating numerous employment and professional opportunities for many individuals (Zinati et al., 2025).
Nouri et al. (2025) examined the impact of supply chain integration dimensions on new product innovation performance through supply chain agility in Pegah Pasteurized Milk Company in the northwest region of the country. The results of the study, using path analysis techniques, indicate that internal integration, customer integration, and supply chain integration have a significant effect on supply chain agility. Furthermore, supply chain agility, market knowledge, and product development significantly influence product innovation capability. In addition, internal integration, customer integration, and supply chain integration significantly affect product innovation capability through the mediating role of supply chain agility.
Zinati et al. (2025) also investigated the design of a maturity model for the Fourth Industrial Revolution in the banking service supply chain and the development of digital banking using a grounded theory approach. According to the findings, the identified categories included ten categories in the causal conditions, seven categories as components of the core phenomenon, four categories related to contextual conditions, eleven categories in the strategies section, seven categories representing intervening conditions, and finally eight categories in the outcome section of the model.
Research Methodology
In terms of its objective, this research is applicable, and in terms of data collection, it is descriptive–survey in nature. The statistical population of the study consisted of 12 experts, including five specialists from the internal logistics unit of the hospital and seven managers from Namazi Hospital.
Research Findings
To determine the relationships among the 13 indicators of the five main components of the hospital’s internal supply chain, the DEMATEL method was employed. The identified relationships were then incorporated into the Analytic Network Process (ANP) model, and the weights of the 13 indicators were calculated by Super Decisions software.
The ranking of the 13 indicators, in order of priority, was as follows: completion of patient treatment through full access to medical resources; on-time treatment performance without delay; patient waiting time; service provision time; professional value-added productivity; error-free performance in patient safety; continuity of the clinical treatment supply process; reliability and accessibility of medical service resources; communication with patients; overall logistics cost management in the clinical treatment supply chain; reliability of investment, growth, and revenue of the clinical treatment process; enhancement of hospital staff skills to prevent errors; and development of organizational culture.
The results of this study indicate that the hospital’s internal supply chain has a positive, direct, and significant impact on improving hospital performance. The findings provide valuable insights for hospital managers and decision-makers in optimizing management practices and enhancing overall operational effectiveness.
Conclusion
The present study was conducted with the aim of proposing a model for performance evaluation management of the internal supply chain employing a hybrid approach of DEMATEL and the Analytic Network Process (ANP). The findings of this research are consistent with the results of previous studies conducted by Nouri et al. (2025), Zinati et al. (2025), Mirshekar et al. (2024), Alizadeh (2024), Mousavi (2023), Samiei et al. (2023), Amozadeh et al. (2023), Davoodi and Sazgari (2022), Haddadzadeh and Motwalian-Bafeghi (2022), Zhang et al. (2022), Jetton (2022), and Dachyar and Mahendra (2020).
Nouri et al. (2025) investigated the impact of supply chain integration dimensions on new product innovation performance through supply chain agility in Pegah Pasteurized Milk Company in the northwest region of the country. The results, obtained using path analysis techniques, showed that internal integration, customer integration, and supply chain integration have significant effects on supply chain agility. Furthermore, supply chain agility, market knowledge, and product development significantly influence product innovation capability. In addition, internal integration, customer integration, and supply chain integration significantly affect product innovation capability through the mediating role of supply chain agility.
Based on the findings of the present study, several recommendations are proposed. Since hospital supply chain processes must be aligned with clinical care processes and supporting processes, it is necessary to consider all these aspects of performance simultaneously within clinical care processes, process efficiency support, and patient safety. Priorities should be determined according to the calculated weights of the indicators. Identifying key performance aspects enables supply chain managers to focus on the most critical factors when seeking to improve hospital performance.

Abstract The main objective of this research is to identify and prioritize factors affecting the development of Internet of Things (IoT)-based businesses in Iran. This research is applicable in terms of purpose, and descriptive and survey in terms of methodology. It was conducted using content analysis method and in two qualitative and quantitative stages. In the qualitative stage, the required data were collected and analyzed by using semi-structured interviews with 8 experts in the field of information technology in Kermanshah science and technology parks and professors working in related universities. In this stage, 6 main factor categories were identified, including financial-economic, technological, cultural-social, political-legal, human, and managerial factors, as well as 22 sub-criteria. In the quantitative stage, the factors were prioritized using the Analytic Hierarchy Process (AHP) technique and Expert Choice software. The research findings showed that among the factors affecting the development of IoT-based businesses, the financial-economic factor has the highest priority, and the managerial factor has the lowest.
Introduction
The evolution of the Internet began with the connection of computers. Later, many computers were connected to each other, creating the World Wide Web. Then, mobile devices were able to connect to the Internet, which led to the mobile Internet technique. People began to use the Internet through social networks. Finally, the idea of ​​connecting everyday objects to the Internet was proposed, which led to IoT technology (Internet of Things). When the concept of such a connection emerged, various companies focused on it and tried to recognize its importance and began to identify its role and future aspects related to it. Then these companies began to invest in this area in different periods but at certain intervals (Korade et al., 2019). From an economic perspective, the Internet of Things can transform business models and provide new solutions for creating added value. Using data generated by IoT devices, digital businesses can better understand customer needs and optimize their products and services (Manyika et al., 2015). Due to the increased productivity resulting from IoT, many advanced countries such as the United States and Japan have developed special strategies for the development of this technology (Lee et al., 2019). According to research, the market size of IoT equipment in 2018 was nearly $2 billion, which is expected to reach more than $11 billion by 2026 (Wang et al., 2021). In Iran, several studies have examined the capabilities of the Internet of Things in various fields and emphasized its importance in economic development and improving productivity (Razavi et al., 2019). Given the increasing importance of the Internet of Things in the future of the digital economy, it is necessary to identify and analyze the key factors affecting the development of businesses related to this technology in a scientific and systematic manner in order to provide a basis for effective planning and policymaking. Despite the efforts made, a review of the research background shows that previous studies have had a limited focus on identifying the factors affecting the development of these types of businesses or have not conducted a comprehensive and structured study of them. The present study seeks to fill this gap and was designed and presented with the aim of providing a scientific framework for it; therefore, this study seeks to answer the question from a perspective different from previous studies: what are the factors affecting the development of IoT-based businesses and what is their priority?
Theoretical Framework
The Internet of Things is a conceptual paradigm that connects billions of Internet-enabled devices to exchange data between themselves and their environment and enable intelligent interactions. This paradigm is a digital-physical infrastructure that establishes a connection between the physical environment and digital systems (Whitmore, 2015).
Ajalli et al., (2023) examined how the Internet of Things affects human resource management in the Fourth Industrial Revolution. This study states that the Internet of Things, as a paradigm in which objects equipped with sensors, actuators, and processors communicate with each other, enables the creation of digital workflows and the simplification of human resource management processes. These findings are important for the development of IoT-based businesses, because using this technology to simplify processes and increase efficiency can help improve organizational performance, including in the field of human resource management.
Rezaei et al., (2022) examined the role of artificial intelligence in optimizing IoT data and its impact on Iranian businesses. The results of this study showed that integrating IoT and artificial intelligence can create a significant competitive advantage for businesses. This study used the Big Data analysis method to examine the effects.
Khan et al., (2024) in a study titled IoT Adoption in the Fourth Industrial Revolution showed that success in implementing IoT requires combining it with complementary technologies such as AI, big data, and cloud computing; and factors such as digital infrastructure, human resource skills, and cybersecurity are influential.
Prasetyo et al., (2023) studied the key success factors in implementing the Internet of Things in Indonesian automotive companies, and the results showed that factors such as strategic alignment with organizational goals, top management support, technology readiness, employee training, supply chain digitization, and the use of smart products play a decisive role in the success of implementing the Internet of Things.
Research Method
This research is applicable in terms of purpose, and descriptive and survey in terms of methodology. It was conducted using the content analysis method. The statistical population of this study included experts and specialists in the field of information and communication technology who were working in companies present in science and technology parks and university growth centers. The statistical sample in the qualitative section included 8 experts and specialists selected from the Kermanshah Science and Technology Park, Kermanshah Innovation Factory, and professors at Razi University of Kermanshah. The sampling method was snowball sampling. The statistical sample in the quantitative part consisted of 15 people, 6 of whom were the same participants in the interview and 9 others were selected from among the experts and specialists and added to them.
Research findings
After a careful and meticulous review of the interviews and content analysis, the main codes and concepts were extracted. The extracted codes were analyzed in the first coding stage and evaluated several times to extract categories from it. After identifying; 6 main factor categories and 22 sub-criteria was obtained, and in the next stage, the Analytic Hierarchy Process (AHP) method was used for quantitative analysis. 15 questionnaires were distributed among the experts, and pairwise comparisons were made with the Expert Choice software.
Conclusion
The results of this study are consistent with the findings of many previous studies. Specifically, the role of economic investment, the importance of technological infrastructure, and the effect of education and awareness on the adoption of the Internet of Things has also been confirmed in the studies of Hossain et al. (2015), Zhang et al. (2021), Li et al. (2020), and Khan et al. (2019). Also, the impact of sanctions and legal problems on the development of this technology in Iran is consistent with the results of Wang et al. (2020). Studies such as Camarinha-Matos et al. (2009) and Sadeghi et al. (2020) also consider the role of organizational cooperation in the success of IoT-based businesses to be similar to the findings of this study.
According to the results of this study, one of the solutions used in the world in the field of IoT businesses and their development is the use of venture capitalists. Despite economic and political problems at the international level prevent the introduction of new technologies and the country's synchronization with them, a country like Iran, which has a large workforce of experts in various fields of information technology; however, needs to find new ways to improve its economy and its position in the international arena; therefore, the importance of the Internet of Things for a country like Iran is obvious and can play a role in all fields. On the other hand, West Asia and North Africa are currently the second largest Internet of Things market, which the UAE, Saudi Arabia and Turkey have taken over. While Iran can be a developer and play a decisive role in the heart of this region and earn significant profits and thereby bypass sanctions.
Iran also has the largest number of metropolises in the Middle East, in which cities such as Tehran, Mashhad, Isfahan, etc. are always struggling with optimal urban management. Becoming smart cities, using smart cars and home appliances connected to the Internet of Things can play a significant role in improving and preventing the problems caused by them.
One of the most important reasons given for the incorrect and late functioning of Internet-connected objects is the slowness in sending them in these fields. By developing smart networks based on the Internet of Things, such problems can be overcome.
Businesses and stakeholders should pay special attention to investing in information and communication technology infrastructure to be able to benefit from the benefits of the Internet of Things. Businesses themselves should pay attention to continuous research and development in the field of the Internet of Things to be able to keep up with rapid technological changes. Designing and implementing training programs for employees and users can help improve their awareness and capabilities in using the Internet of Things.
Creating and strengthening cooperation networks between businesses and different organizations can help exchange information and resources. Businesses should also pay special attention to collecting and analyzing customer feedback to be able to better identify their needs and improve their services. Acknowledgments The authors gratefully acknowledge all individuals, institutions, and organizations that provided scientific, technical, administrative, or advisory support throughout this research and the preparation of this manuscript. Conflicts of Interest The authors declare that they have no financial or non-financial, personal, professional, or institutional conflicts of interest relevant to this work. Data Availability Statement The data supporting the findings of this study are available from the corresponding author upon reasonable request. AI Use Statement The authors declare that no generative artificial intelligence (AI) or AI-assisted technologies were used in the preparation, writing, or editing of this manuscript. Funding The authors declare that no funds, grants, or other financial support were received during the conduct of this research or the preparation of this manuscript. Ethics Approval All procedures performed in this study were conducted in accordance with the ethical standards of the responsible institutional and national research committee.

Abstract The aim of this study is to present a career and organizational promotion model for middle managers with a meritocracy strategies approach. The research method is applicable in terms of purpose, and of descriptive-exploratory research type. The statistical population of the study includes 12 experts and specialists of Bushehr Petrochemical Company, and the sampling method is purposive. Based on the summary of previous studies and the data obtained from the implementation of the Delphi technique among Bushehr Petrochemical experts, four criteria of meritocracy strategy were identified for career and organizational promotion, meritocracy thinking, organization qualification, and talent management; and by a hierarchical approach, a hierarchy tree was first formed through this method, and then the criteria were ranked by Expert Choice software. The results of this study showed that meritocracy in managers and employees in Bushehr Petrochemical is as follows: meritocracy strategy for career and organizational promotion has a value of 0.362, meritocracy thinking for career and organizational promotion has a value of 0.384, organization qualification has a value of 0.152, and finally talent management has a value of 0.102, and the compatibility rate of 0.004 is also in the acceptable range. These results can transform managers' decisions and cause changes in their attitudes.
Introduction
Today, given the extremely intense and complex competition, unstable environment, lightning-fast technological advances, the increasing development of information and communications, and... almost no organization can survive without knowledge-based components, which are specialized and experienced managers and employees. The era of information technology and the digital revolution has also doubled the need to pay attention to the value of these precious elements in the life cycle of companies and organizations, and perhaps it can be safely claimed that the progress and excellence of any organization is due to the unique abilities and competencies of its human resources. An organization is a social environment whose cultures and values ​​provide space for the creativity and ingenuity of its employees. Without creating this creative environment, the hope for the growth and flourishing of elites and the emergence of their talents will be an illusion (Rastgar, 2024).
On the other hand, the competence of managers in an organization causes the emergence of organizational competence. Therefore, the competence relationship between the individual and the organization is a two-way relationship, which, due to the major benefit from the organization, must naturally grow from the whole to the part, that is, from the organization to the individual. In simpler terms, organizations need to create a suitable space for the activities of competent individuals and the emergence of their competencies (Hajili, 2022). One of the main solutions to get rid of the inefficiency of Iranian organizations is to value competent managers and make appropriate use of their competencies by appointing them to appropriate jobs. However, to establish this system, there is a need to make fundamental changes in the values ​​and culture of organizations, but the role of the government in promoting this thinking correctly and in a principled manner is undeniable (Vahidi Rad et al. 2026). To develop and promote this thinking, it is also necessary to be well acquainted with its obstacles and try to overcome them. On the other hand, the need to establish this system in organizations must become a widespread belief and senior organizational managers must accept it as the only model for saving their troubled organizations. In addition, familiarity with the requirements for implementing this system provides them with more operational solutions and helps them in the correct and comprehensive implementation of this thinking in organizations (Daniyali Deh Hoz et al. 2018).
In meritocracy, the latent talents of individuals are usually identified and then cultivated through the creation of a talent base and made available to the organization's goals. Meritocracy begins with the production of competence in employees and managers, then evolves in the context of opportunity creation. In meritocracy, criteria such as commitment, expertise, skill, ability, experience, and compassion are the criteria for selecting and promoting individuals in the organization. The degree of excellence, popularity, attachment, and the use of components in planning, decision-making, and their implementation are in line with the achievement of the organization's goals (Wade & Obwegeser, 2019). When a company helps employees in career promotion, employees are less willing to leave the company. Career promotion can increase employee morale, also increase productivity, and on the other hand help the company become more efficient (Rastiani, 2024). Considering the above, it can be said that the main purpose of conducting the research is to answer the main question: what is the career and organizational promotion pattern of middle managers with the approach of meritocracy strategies?
Theoretical Framework
Meritocracy
Meritocracy is a social system in which the highest power and social status are entrusted to those with the most ability. Meritocracy is a social system in which progress in society is based on individual abilities and competencies, not derived from family wealth or social background (Nasiri & Jafari, 2026).
Vahidi Rad et al. (2026) studied the design and presentation of a sustainable human resource management model with a meritocracy promotion approach in seven education districts of Mashhad. The findings in the sustainable human resource management model with a meritocracy promotion approach include 5 dimensions and 24 components, which include merit-based recruitment, sustainable human resource competency development-based improvement, human resource retention with a merit-based approach, sustainable and merit-based human resource performance evaluation, and a performance-based payment system. In the quantitative section, the results showed that the aforementioned model has the necessary validity. According to the results of the research, managers of the seven education districts of Mashhad can promote meritocracy in the organization by developing and strengthening sustainable human resource management.
Nasiri & Jafari (2026) studied the identification of the underlying factors and challenges in irresponsible appointments and away from meritocracy in education. The results of data analysis led to the identification of 47 basic themes and 7 organizing themes in the context of the underlying factors in irresponsible appointments and away from meritocracy in education, which were classified into 4 comprehensive themes: management in the shadow of politics; organizational affiliation bottlenecks; conflict between economy and educational strategy; and fundamental structural faults. Also, 105 basic themes and 9 organizing themes were identified in the context of the challenges in irresponsible appointments and away from meritocracy in education, which were classified into 4 comprehensive themes: managerial and organizational crises in the education system; social and cultural crisis in education; inequality crisis in education; and qualitative crisis in education were classified. Considering the identification of the underlying factors and challenges in irresponsible and meritocratic appointments in education in this research, implementing the solutions presented in it can facilitate and bring about the realization of the appointment of competent people in education.
Research Methodology
Regarding its purpose, the research method is applicable based on its objective, and a descriptive-exploratory research type. The statistical population of the research includes 12 experts and specialists of Bushehr Petrochemical Company, and the sampling method is purposive.
Research findings
Based on the summary of previous studies and the data obtained from the implementation of the Delphi technique among experts in Bushehr Petrochemical, four criteria of meritocracy strategy for career and organizational promotion, meritocracy thinking, organization competency, and talent management were identified. Through a hierarchical approach, a hierarchy tree was first formed by this method, and then the criteria were ranked by Expert Choice software. The results of this study showed that meritocracy in managers and employees in Bushehr Petrochemical is as follows: meritocracy strategy for career and organizational promotion has a value of 0.362, meritocracy thinking for career and organizational promotion has a value of 0.384, organization competency has a value of 0.152, and finally talent management has a value of 0.102. The compatibility rate of 0.004 is also within the acceptable range. These results can transform managers' decisions and cause changes in their attitudes.
Conclusion
The present study aimed to present a career and organizational promotion model for middle managers with a meritocracy strategies approach. The results of this study are consistent with the results of Baffour Gyau et al. (2024), Wang et al. (2023), Eskandarany (2024), Alotaibi (2024), Byambaa et al. (2025), Svoboda (2024), Lin et al. (2024), McKinsey (2020), Abdulsalam & Tajudeen (2024), Deloitte (2024), and Khan et al. (2024). The results of Baffour Gyau et al, (2024) study on the dynamic relationship between AI technology innovation in banking and finance and financial performance of banks in 20 countries show that AI technology innovation in banking and finance positively affects the return on assets of banks and highlights its role in increasing financial performance. The interaction term between AI innovation and economic growth emphasizes their joint positive effect on financial performance. Mediation analysis highlights the role of information and communication technology development in transforming AI innovation into improved financial results.
According to the results of the study, the following suggestions were made:
Training comprehensive AI literacy to bank employees: the findings showed that the bank should shift its focus from training skills in simple tools to training comprehensive AI literacy and enable its workforce to transform from passive users to active participants in the AI ​​ecosystem.

Abstract The purpose of this research is to present a localized model for brand authenticity in the healthcare industry. Initially, through a systematic literature review and qualitative content analysis using NVIVO software, 15 main factors of brand authenticity were identified in this study. In the next step, these components were localized for the Iranian healthcare services context using the Delphi method and surveying academic and industry experts (including 12 individuals), resulting in the extraction of 12 final factors (including transparency and honesty, brand heritage, existential authenticity, and brand social responsibility). The findings indicate that consistency between the stated values and the actual performance of healthcare organizations is the primary basis for the perception of authenticity in the minds of patients. This research, by focusing on the localized components, provides a scientific framework for managers of organizations active in the health sector to foster patient network trust and enhance the quality of the treatment experience by fundamentally shifting decision-making from an intuitive state.
Introduction
In the last decade, the healthcare industry has faced fundamental changes in how it interacts with stakeholders. Today’s patient is no longer a passive consumer; rather, through digital media and online feedback, they actively participate in evaluating healthcare services (Araújo et al., 2025). This transformation has paved the way for the emergence of “brand authenticity,” a construct referring to the patient’s perception of the healthcare organization’s honesty, transparency, and alignment between its stated values and reality (Apriyana et al., 2024). The necessity of studying brands active in the healthcare industry stems from the fact that brand authenticity in this sector is shaped by factors that are objective, behavioral, and observable. These factors rely more on the brand’s actual conduct, credible backing, and direct interaction with patients rather than on symbolism, claims, or historical narratives (Farzinmehr et al., 2025). Such a model indicates that patient trust is formed when a brand can demonstrate its authenticity in practice, not merely in discourse or mental imagery. Furthermore, in high-risk service environments like healthcare, patient trust is not only a prerequisite for treatment but also a key variable in the quality of the patient experience (Ghaffar et al., 2025). Despite the importance of this construct, scientific research on the precise role of brand authenticity in the healthcare industry is limited and scattered. Many managers, due to the lack of a localized framework, operate based on intuitive perceptions. This research seeks to answer the main questions: What are the scientifically-based factors of brand authenticity? And which of these factors, with an emphasis on trust-building, should be prioritized in the healthcare industry?
Theoretical Foundations
Brand Authenticity
In contemporary marketing literature, brand authenticity is defined as a psychological and strategic construct that extends beyond the technical quality of services. This concept pertains to stakeholders’ perceptions of the alignment between the brand’s declared values and the organization’s actual behaviors (Hyun et al., 2024). Authenticity, in its true sense, means being genuine, honest, and avoiding hypocrisy. It is achieved when a brand exhibits consistent performance over time and adheres to its promises. This characteristic imbues brands with a unique identity that is inimitable (Dedeoğlu et al., 2019; Crisci, 2024).
Customer Trust
Trust, as a key construct in relationship marketing, reflects the sense of security a consumer experiences when interacting with a product or service (Bae & Kim, 2023). This construct is formed on the perception that the brand is reliable and responsible for the customer’s interests and well-being. In essence, trust is a form of consumer belief and reassurance that they will be served in the long term to meet their needs and interests, acting as a lever of credibility for repeat purchases (Bhattacharjee, 2025).
In a study by Deng et al. (2025) titled “Exploring the Role of Brand Authenticity on Customer Loyalty in Sport Brands,” it was found that all dimensions of brand authenticity (real-to-ideal, real-to-reality, and real-to-self) have significant positive effects on brand attachment, trust, and loyalty.
In research conducted by Anubha & Roy (2025) titled “Explaining the Role of Consumer-Perceived Brand Authenticity in the Context of Masstige Brands,” findings indicated that all three dimensions of authenticity (including brand heritage, commitment to quality, and sincerity) influence customer purchase intention through the mediating variable of trust.
In a study by Kim et al. (2021) titled “Examining Consumer-Based Brand Authenticity in the South Korean Coffee Shop Market,” it was found that the dimensions of commitment to quality, heritage, and sincerity have significant impacts on brand credibility, ultimately leading to strengthened brand loyalty.
Another study titled “Investigating the Impact of Green Brand Storytelling on Authenticity and Trust” was conducted by Huang & Guo (2021). The results showed that rhetorical strategies (such as symbolism) enhance narrative immersion, which in turn positively influences perceived brand authenticity and trust in the brand.
Research Methodology
Regarding its research philosophy, this study is situated within the pragmatic paradigm, which relies on a subjectivist approach. In terms of objectives, this research is developmental with an inductive approach; and in its nature, it is considered an exploratory-analytical study. From a methodological perspective, this paper employs a mixed-methods research design, utilizing a qualitative content analysis strategy to identify factors, and the Delphi technique for the localization of these components.
The statistical population for this study is defined in two parts. The first part comprises articles related to brand authenticity. For the second part, intended for localization, the population included industry experts and academic faculty members with over 15 years of experience, possessing expertise in the core concepts of the research, as well as a history of publishing interdisciplinary research in business and healthcare; 12 of whom were selected by purposive sampling. Qualitative content analysis was conducted using open and axial coding in NVIVO 12 software, while the Delphi data analysis, including the calculation of means and the assessment of consensus, was performed using Excel.
Research Findings
The findings of this study led to the identification of 15 initial factors, which were ultimately localized and finalized into 12 key factors influencing brand authenticity within the context of Iran’s healthcare industry. These factors include transparency and sincerity, uniqueness, brand authenticity protection, adherence and commitment to customers, brand distinctiveness, alignment with brand identity, existential authenticity, sustainability and corporate social responsibility (CSR), enduring brand heritage, core brand values, rich background and history, and strategic participation and engagement with customers.
Discussion and Conclusion
The results indicate that in the healthcare industry, brand authenticity is not merely a marketing construct, but an ethical and strategic foundation for building networked trust and improving the treatment experience. Organizations that successfully embed these components into their identity and operations can, under current complex conditions (including sanctions and international limitations), foster domestic trust, serve as an effective substitute for foreign brands, and achieve a sustainable competitive advantage. This is consistent with studies by Anubha & Roy (2025), and the brand heritage component is also emphasized in the study by Kim et al. (2021). Furthermore, the results of this research underscore the importance of transparency as a dimension of brand authenticity in building patient trust; the study by Dehghan et al. (2022), consistent with our findings, emphasizes the role of transparency and brand storytelling in strengthening authenticity.
The path of this study—redefining the position of brand authenticity and establishing it as the cornerstone of patient trust—elevates the trust-oriented perspective from the level of individual interactions (physician-patient) to the level of identity and macro-behavior of healthcare organizations. Specifically, this research highlights components such as uniqueness, commitment to customers, brand distinctiveness, and customer engagement, which have received less attention in other studies, as constituent elements of brand authenticity in this industry. Existential authenticity refers to the internal authenticity of a brand, reflecting a commitment to its unique essence and origin. This factor is vital in creating deep and lasting trust in patients, as the brand must consistently and genuinely demonstrate and defend its values. Behavioral consistency, another component emphasized in this study, refers to the degree of harmony, continuity, and integrity of a brand’s behaviors, decisions, and actions over time and across all touchpoints with stakeholders. This concept indicates the extent to which a brand acts in accordance with its stated identity, values, and promises without experiencing fluctuations or behavioral contradictions. This factor serves as a powerful tool for increasing brand credibility in patients’ minds, particularly in therapeutic contexts where a high level of patient trust is required.
Based on these findings, the following recommendations are provided to managers of organizations active in the healthcare industry:

Developing a Charter of Transparency and Sincerity: Healthcare organizations should formalize and implement an official charter based on transparency in treatment, financial, and communication processes. Publishing periodic performance reports and patient feedback can be an effective step toward increasing public trust.
Developing Brand Identity Based on Authentic Values: Managers should institutionalize brand authenticity in patients’ minds by redefining their brand identity based on core values (e.g., social responsibility, commitment to quality, and organizational heritage) and aligning all communications and services with this identity.
Creating Strategic Engagement Mechanisms with Patients: Designing digital and in-person platforms for active patient participation in treatment decisions and service improvement can increase the sense of belonging and trust.
Training and Empowering Human Resources: As brand ambassadors, employees must receive continuous training in professional ethics, transparent communication, and behavior based on authenticity.
Utilizing Authentic Narrative and Storytelling: Utilizing real, human-centric narratives regarding the organization’s history, treatment successes, and social initiatives can strengthen the perception of brand authenticity.
Continuous Monitoring and Evaluation of Authenticity Indicators: Establishing a periodic monitoring system based on the 12 identified factors and gathering feedback from patients and stakeholders will assist managers in continuous improvement.
Turning Brand Authenticity into a National Competitive Advantage: At the macro level, policymakers can help differentiate and elevate the status of domestic providers by introducing authenticity-based accreditation marks (e.g., “Authentic Health Brand”).

Abstract Abstract
The aim of this research was to present a competitive advantage model with a leadership approach in the Iranian aviation industry. The present research is a mixed exploratory research. In this research, data was collected and research questions were examined using interview and questionnaire tools. Given that the present research is in two stages (quantitative and qualitative), the relevant population in the qualitative dimension includes experts such as senior managers and consultants of the Civil Aviation Organization of Iran as well as university professors, selected to saturation. In the quantitative dimension, the statistical population includes executive managers, department heads, consultants and employees of the Civil Aviation Organization of Iran, 620 people altogether, of whom 237 were selected by the Morgan table using simple random sampling. Based on the interpretive structural technique (ISM), the results showed that having a suitable network and scope of air, flight and airport services in the country, the possibility of sharing technology for the production of modern aircraft, the technical and technological capabilities of the industry for leadership, having a strategic management attitude and capabilities for the industry for leadership, having experience in joint cooperation with international consultants, companies and governments, the desire to lead in government officials and industry decision-makers, commitment to strategic plans in industry managers for leadership, learning, ability to adapt and foresight in the aviation industry for leadership, having skills and expertise in managers and human resources in the industry for leadership, the number and composition of the air transport fleet and having coherent, integrated and strategic marketing and branding plans in the industry have the greatest influence on the competitive advantage for leadership among the variables.
Introduction
The aviation industry, as one of the vital pillars of the economic and social development of any country, plays a significant role in facilitating communications, trade, tourism, and the movement of people. In Iran, despite its geographical and strategic potential, this industry faces numerous challenges, including fleet obsolescence, international sanctions, and weak infrastructure. In the meantime, creating and maintaining a sustainable competitive advantage for domestic airlines, especially with a pioneering approach, seems essential (Alavi et al., 2020).
One of the prominent models in the field of competitive advantage is Porter's theory, which introduces three general strategies for gaining competitive advantage (butt et al., 2022): cost leadership, differentiation, and focus. In the meantime, the differentiation strategy by providing unique and high-quality services can be considered as a suitable approach for Iranian airlines. By focusing on the specific needs of customers and providing services that are different from competitors, this strategy can lead to creating a sustainable competitive advantage (Summerville et al., 2020).
On the other hand, according to the theory of first-mover advantage, in many industries, including the aviation industry, where there is the possibility of strategic management of organizational resources in order to be the best, providing innovative specialized services increases efficiency, that is, along with the increase in innovative services, the ability to obtain economies of scale also increases, leading to a reduction in the cost of providing services and, so to speak, being the best in the industry (lo et al., 2020).
One of the most important reasons for the backwardness of the Iranian aviation industry is the lack of development of commercial systems in transportation activities. The lack of a professional commercial aviation system in the aviation industry and the existence of the charter mafia and the black market are one of the major commercial problems in the field of air transportation. However, according to the 1990 diamond porter model, the proper design, application, and implementation of competitive advantage models can bring positive results to the industry, the most important of which are (Summerville et al., 2020): exceptional ability to obtain information from the organization's environment; exceptional ability to respond appropriately to environmental information and challenges; ability to learn quickly and discover new and potential customers; improving the level of business/marketing awareness - which mainly collects and analyzes information from customers, suppliers, etc.; improving the level of awareness of the situation of competitors - which focuses on issues such as pricing policies, substitute services, and competitor development policies; improving the level of technological and technical awareness - which deals with basic and applied research, processes, and norms, and the promotion of new technologies for providing services; improving the level of strategic and social awareness - which deals with issues such as laws, financial and tax issues, political and economic issues, and social aspects and human resources. Accordingly, the question arises: What is the competitive advantage model with a leadership approach in the Iranian aviation industry?
Theoretical Framework
Technical and Technological Capabilities and Infrastructure
Technical and technological capabilities are considered to be the main pillars of competitive advantage in the aviation industry. With rapid advances in technology, airlines can increase their productivity, reduce costs, and provide a better experience for passengers. The use of artificial intelligence and Internet of Things systems to optimize flight operations and predict maintenance needs increases efficiency and reduces costs (Awamleh et al., 2021).
Strategic Management and Leadership
Strategic management and leadership play a decisive role in industrial leadership. Strategic planning, optimal resource management, and the organization's ability to learn and adapt to environmental changes are key factors in creating sustainable competitive advantage (Hamadamin et al., 2019). Airlines that have clear and coherent strategies are able to manage costs, increase operational efficiency, and improve their performance in a competitive market.
Human Resources and Skills Development
Highly skilled and specialized human resources are one of the main pillars of industrial leadership. Developing human capital through education, research, and succession planning increases the organization's efficiency and ability to adapt to environmental changes (Alfawaire Alfawaire et al., 2021). Organizations that continuously develop their human resources are able to create sustainable competitive advantage and perform better in a competitive market (Torres et al., 2019).
International Networks, Markets, and Communications
International networks and communications are key factors in creating and maintaining competitive advantage. Active presence in international markets, establishing cooperation with foreign companies and institutions, and adopting internationally oriented approaches increase access to resources, technology, and new markets (Cavusgil et al., 2014). Organizations that have extensive and sustainable relationships with international partners are better able to respond to market changes and global competition.
Infrastructure and organizational resilience
Operational infrastructure and organizational resilience play an important role in maintaining and developing competitive advantage. Investment in modern equipment and technologies, optimal information management, and strategic planning increase organizational efficiency and reduce vulnerability to environmental changes. Organizations with strong infrastructure are able to maintain their performance in adverse conditions and exploit market opportunities (haseeb et al., 2019).
Research Background
Abdulwase et al. (2024) conducted a study titled “The Role of Business Strategy in Creating Competitive Advantage”. The findings showed that business strategy plays a vital role in creating competitive advantage and increasing market share. Also, the organization’s market was affected by a strategy with a desirable quality.
Kashefarzaagh et al. (2024) conducted a study titled “The Effect of the Brand of Islamic Azad University, Electronics Branch on Competitive Advantage with the Mediating Role of Positioning and Market Orientation”. The findings confirmed the effect of audience recognition of the brand on positioning and market orientation and the effect of these two variables on competitive advantage.
Research Methodology
This research is applicable in terms of purpose, and qualitative-quantitative approach. Considering that the present research is in two stages, (quantitative - qualitative), the research community is different in both dimensions; in the qualitative dimension, the relevant community includes experts such as senior managers and consultants of the Civil Aviation Organization of Iran and university professors, selected to saturation; and in the quantitative dimension, the statistical community includes executive managers, department heads, consultants and employees of the Civil Aviation Organization of Iran, totaling 620 people, of which 237 people were selected by the Morgan table using simple random sampling.
Research Findings
The findings of the present study showed that the capabilities of research and development and investment for leadership in the aviation industry, learning, ability to adapt and foresight of the aviation industry for leadership, the possibility (ability) of sharing technology for the production of modern aircraft, management of income and costs in the industry for leadership, having experience in joint cooperation with international consultants, companies and governments, having skills and expertise in managers and human resources in the industry for leadership, forming a comprehensive database (customer, product, service and market) with a high level of safety for the industry, the number and composition of the air transport fleet, the existence of educational and research centers in accordance with international standards for the development and replacement of technical and staff forces in the industry and having coherent, integrated and strategic marketing and branding programs in the industry are at the eighth level of the competitive advantage model with a leadership approach. Also, managerial stability in the industry is at the first level of this model, which interacts with political and economic stability in the country and restrictions on the transfer of specific technology and the import of new aircraft due to sanctions conditions.
Conclusion
The results of the study showed that leadership in the Iranian industry is mainly based on internal and organizational capabilities. Technical capabilities, human resources, strategic management and organizational infrastructure are the basis for creating and maintaining competitive advantage. Unlike some studies that highlight macro-political and economic factors, the present findings showed that long-term success depends more on innovation, organizational skills and the use of technology, which is in line with the research of Teece (2007), Porter (1985), and Awamleh et al. (2021).
The results showed that the breadth and quality of the domestic and international service network play an important role in industry leadership. Awamleh et al. (2021) and Santos et al. (2024) have also shown that an extensive operational network increases productivity and customer satisfaction. The results showed that a competitive position in the global market increases the organization's ability to exploit international opportunities and reduce environmental risks. Porter (1985) and Teece (2007) have also shown that a strong presence in global markets facilitates access to new resources and technologies, and the present findings are consistent with these studie.
The results showed that the development of technical and technological capabilities improves the operational performance and efficiency of the organization and provides the basis for creating competitive advantage. Awamleh et al. (2021) and Santos et al. (2024) have also emphasized that investment in technology and technological infrastructure provides the basis for competitive differentiation and increased productivity, and the present findings are consistent with these studies.
Studies by Hamadamin et al. (2019) and Mahdi et al. (2019) have also emphasized that effective strategic management increases productivity, resource coordination, and rapid response to environmental changes. The results showed that adopting an international approach increases access to new technologies and markets and strengthens the organization in global competition.
Cavusgil et al. (2014) have shown that companies that are internationally oriented have a better ability to exploit opportunities and reduce risks. The results showed that the desire and motivation of government officials and decision makers to lead facilitates the implementation of strategies and creates institutional support.
Research by Mahdi et al. (2019) has also stated that the support of key decision makers for strategic plans facilitates the successful implementation of strategies and the consolidation of competitive advantage. The results showed that the commitment of managers to the implementation of strategic plans causes the continuity of activities and strengthens competitive advantage.
Hamadamin et al. (2019) have shown that the commitment of managers to strategies reduces internal conflict, and increases resource coordination and productivity. The results showed that investment in R&D and innovative capabilities provides the basis for leadership and competitive advantage.
Awamleh et al. (2021) and Santos et al. (2024) have also emphasized that continuous investment in R&D leads to sustainable innovation and strengthening competitive position.

Abstract Abstract The aim of the present study is to design a sustainable business model based on circular economy in the Iranian oil industry. This study is applicable in terms of purpose, and mixed in terms of implementation (qualitative-quantitative). The research community in the qualitative section includes 12 experts, based on snowball sampling, and the statistical community in the quantitative section includes 220 experts, managers, and specialists active in subsidiaries of the National Iranian Oil Company, universities, and research centers related to the oil industry and the environment. Data collection was carried out using semi-structured interviews and questionnaires. Data analysis was performed using meta-synthesis in the qualitative section and PLS in the quantitative section. The results in the qualitative section showed that 142 basic themes were categorized into 34 organizing themes and 11 overarching themes. The overarching themes are: diversification strategy, smart production and operations, strategic collaboration and partnership, value creation, resource management, risk management and resilience, dynamic capabilities, sustainability culture, innovation and technology, flexibility and organizational, establishment of international standards and requirements. The results in the quantitative section showed that all the identified factors were confirmed and the desirability of the extracted model was also confirmed. According to the research findings, the general management suggestion is that policymakers and oil industry managers establish and institutionalize the principles of the circular economy in all parts of the oil value chain by developing a comprehensive strategic framework. Introduction Sustainability has increased significantly in recent years. To move towards sustainability, industries and companies need to look at everything from a holistic perspective and in order to understand the interplay between economic growth and environmental and social sustainability (Sari et al., 2024). The one-dimensional business approach to developing institutions and business units and increasing profits without considering their surrounding environment has led to negative environmental consequences such as climate pollution, global warming, reduction in animal and plant diversity, and others (Antony et al., 2023). Given the emergence of such issues, many researchers and experts believe that business units must consider measures that take into account not only the interests of shareholders, but also the interests of other stakeholders such as employees, suppliers, customers, government, non-governmental organizations, and even the environment, in order to ensure their survival in society. Such businesses are considered sustainable enterprises that, in addition to maintaining their activities at a profitable level, consider the limitations of the socio-ecological system of which they are a part (KHayatian Yazdi et al., 2016). The circular economy is a two-dimensional approach to the industrial economy that aims to recycle industrial waste to protect the environment and achieve a sustainable economy. The circular economy is more than recycling. The linear economy uses materials and ultimately throws them away. However, the circular economy seeks all the options available in this chain so that the least resources are used initially and these resources and materials have the greatest circulation in the economy, and as a result, the most added value is extracted from them during consumption, and finally the products are revived or recycled (Gomez et al., 2024). Circular business models can be defined as those that make the loops smaller, smaller, slower, denser, and dematerialized (raw materials) in order to minimize the input and output sources of waste and energy leakage. Replacing the current linear economic model with a circular economy model not only saves costs, but also significantly reduces the negative impacts of industries on the natural environment. This is why the circular economy has attracted increasing attention as one of the strongest and most recent steps towards a sustainable economy (Hengyu et al., 2019). Aiming to fill this gap, this research seeks to answer the main question: “How is a sustainable business model based on a circular economy designed in the Iranian oil industry?” Theoretical Framework Business Sustainability Business sustainability refers to the ability of an organization or company to continue its activities in the long term, while maintaining a balance between economic success, environmental protection and promotion of social welfare. In fact, business sustainability means continuing to be financially, environmentally and socially acceptable (Hina et al., 2024). Circular Economy A circular economy is an economic system that aims to minimize waste and maximize resource use. This regenerative approach contrasts with the traditional linear economy approach, in which the production model is “receipt of raw materials, production, and disposal.” In a circular system, input resource consumption, output waste, and energy loss are minimized by closing or shrinking material and energy loops. These goals can be achieved in the long term through design, maintenance, repair, reuse, reproduction, and recycling (Marina et al., 2019). Torabi et al. (2024) conducted a research. The results showed that the meta-synthesis method was obtained in the form of a comprehensive questionnaire, which was approved after screening by the fuzzy Delphi method in two stages, to provide the main research question, which is the circularization of the industrial innovation process in 4 stages and 12 dimensions based on the circular economy as an effective framework for expanding the results in line with the sustainable development goals in this research. The results of this study can be a basis for operationalizing circular economy strategies in the industrial innovation ecosystem and lead to new innovation opportunities in industrial organizations, especially start-ups. Colabi (2020) examined the modeling of factors affecting business model sustainability. It has been stated that the factors affecting business model sustainability are innovation, shared value creation, participatory leadership, economic factors, and corporate governance, respectively. Research Methodology This study is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of implementation. The research community in the qualitative section includes 12 experts, based on snowball sampling, and the research statistical community in the quantitative section includes 220 experts, managers, and specialists active in subsidiaries of the National Iranian Oil Company, universities, and research centers related to the oil industry and the environment. Data collection was carried out using semi-structured interviews and questionnaires. Research findings Data analysis in the qualitative part is meta-synthesis method, and in the quantitative part is PLS. The results in the qualitative part showed that 142 basic themes were categorized into 34 organizing themes and 11 overarching themes. Overarching themes include: diversification strategy, smart production and operations, strategic collaboration and partnership, value creation, resource management, risk management and resilience, dynamic capabilities, sustainability culture, innovation and technology, flexibility and organizational, establishment of international standards and requirements. The results in the quantitative part showed that all identified factors were confirmed and the desirability of the extracted model was also confirmed. According to the research findings, the general management suggestion is that policymakers and managers of the oil industry establish and institutionalize the principles of circular economy in all parts of the oil value chain by developing a comprehensive strategic framework. Conclusion The present study was conducted with the aim of designing a sustainable business model based on circular economy in the Iranian oil industry. The findings of this research are in line with studies such as Mattera et al. (2021), Leal et al. (2024), Torabi et al. (2024), Colabi (2020), Sharafi et al. (2019), Tunn et al. (2019), Meike et al. (2018), Angus&Nancy (2018), Maghsoudi (2017), Parsapour et al. (2017), KHayatian yazdi et al. (2016), Benzazoua et al. (2015), and Regasa (2015) that emphasize the role of strategic collaboration and sustainable innovation in circular business models. However, while Western studies mainly focus on technical recycling or supply chain optimization in open environments, this research shows that in the context of sanctions and the monopolistic structure of the Iranian oil industry, factors such as energy diversification and ethical value leadership become more important. This shows that the circular economy in sanctioned countries is not only a technical-environmental issue, but also a survival strategy. The presence of “risk management and resilience” as one of the key factors is a reflection of the structural instability of the Iranian business environment. 

Abstract The aim of this study was to design an optimization model for the coexistence of artificial intelligence and human capital in the provision of urban services in the municipalities of Sistan and Baluchestan Province. This research was conducted in two phases: qualitative and quantitative. In the qualitative phase, document analysis, interviews, and the Delphi technique were employed with the assistance of 20 experts to identify key dimensions and develop the initial model. The software used in this phase was MAXQDA. In the quantitative phase, data were collected from 300 employees of the municipalities of the province through a researcher-made questionnaire, the validity and reliability of which were tested and confirmed, and the data were analyzed through Structural Equation Modeling (SEM).
The findings indicated that the final research model demonstrated a satisfactory fit and comprised six main constructs, including contextual factors, artificial intelligence components, human capital components, mediating factors, coexistence strategies, and desirable outcomes. The strongest relationship in the model was observed between contextual factors and artificial intelligence components, with a path coefficient of 0.98. This study provides an indigenous model for optimizing the collaboration between humans and artificial intelligence in the municipalities of underprivileged regions.
Introduction
The rapid growth of artificial intelligence in the public sector has created unprecedented opportunities to improve the delivery of urban services. However, the successful implementation of artificial intelligence is not merely a technical challenge; rather, it represents a profound organizational transformation that critically depends on effective interaction with human capital (Wilson & Daugherty, 2018; Wirtz et al., 2019). In many developing regions, this challenge is intensified by infrastructural deficiencies, skill gaps, and unique socio‑cultural contexts.
Municipalities in Sistan and Baluchestan Province of Iran face specific difficulties, including dispersed populations, severe financial constraints, a shortage of digitally skilled personnel, and inadequate communication infrastructure (Jafarinia et al., 2021; Deputy for Management Development and Resources of the Governorship of Sistan and Baluchestan Province, 2022). Preliminary observations indicate that although there is willingness to adopt artificial intelligence, employees often fear job displacement, and the existing level of digital literacy is significantly lower than the national average (Planning and Budget Organization of Sistan and Baluchestan Province, 2023). Moreover, general artificial intelligence models developed for metropolitan areas are often unable to account for local knowledge, cultural nuances, and geographical dispersion.
Despite the growing body of literature on artificial intelligence in smart cities (Sun & Medaglia, 2019; Singh & Shah, 2025), most studies assume the presence of strong infrastructure and well‑prepared human capital, leaving a significant gap regarding context‑dependent and resource‑constrained environments. Therefore, the necessity of the present research lies in developing a localized model that promotes a symbiotic (co‑evolutionary) relationship, rather than a substitutive one, between artificial intelligence and human employees. The main objective is to design an optimal coexistence model that enables municipalities in a less‑developed province to benefit from artificial intelligence while simultaneously empowering their existing workforce.
Theoretical Framework
In this study, three complementary theoretical frameworks are integrated. First, Becker’s Human Capital Theory (Becker, 1964) posits that knowledge, skills, and experience are productive assets that generate economic and organizational returns. In urban management, human capital—including technical skills, creativity, organizational commitment, and awareness of local culture—constitutes a prerequisite for successful digital transformation (Pahlavani Rad, 202).
Second, the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003) explain technology adoption through the constructs of performance expectancy, effort expectancy, social influence, and facilitating conditions—factors highly relevant to the adoption of artificial intelligence in public services.
Third, the framework of Collaborative Intelligence proposed by Wilson and Daugherty (2018) moves beyond the notion of substitution toward coexistence, where artificial intelligence performs data‑driven tasks while human beings contribute ethical judgment, creativity, and contextual understanding. Recent empirical research confirms that trust, transparency, and algorithmic explainability are essential for such collaboration (Glikson & Woolley, 2020; Raftopoulos & Hamari, 20).
Taken together, these theories provide the foundation for a model composed of contextual factors, artificial intelligence components, human capital dimensions, mediating factors, coexistence strategies, and desirable outcomes.
Research Methodology
This study employed an exploratory sequential mixed-methods design. In the qualitative phase, following a systematic literature review, semi-structured interviews were conducted with 15 participants (senior managers, IT specialists, and AI experts) from the municipalities of Sistan and Baluchestan Province, selected through snowball sampling until theoretical saturation was reached. Subsequently, a three-round Delphi technique involving 20 experts was employed to reach a consensus on the model’s components. Thematic analysis by MAXQDA software led to the extraction of 127 primary codes, 6 main themes, and 18 sub-themes.
In the quantitative phase, a researcher-made questionnaire (using a five-point Likert scale) was administered to a simple random sample of 300 municipal employees (drawn from a population of approximately 1,200). The validity of the instrument was confirmed through content validity, convergent validity (AVE > 0.5), and discriminant validity (Fornell-Larcker criterion). Reliability was also verified by Cronbach’s alpha and composite reliability (CR > 0.7). Data were analyzed by SPSS software for descriptive statistics and Smart-PLS software for Structural Equation Modeling (SEM), including bootstrapping to test the significance of path coefficients.

Research Findings
The structural model demonstrated that all hypothesized paths were statistically significant (p < 0.05), confirming the multidimensional nature of human–AI coexistence in this context. The strongest relationship was observed between contextual factors—including hardware and software infrastructure, managerial support, adequate budget, and ethical considerations—and AI components (decision-making accuracy, reliability, and explainability), with a path coefficient of 0.986. This finding aligns with recent international studies emphasizing that foundational infrastructure and ethical governance are indispensable pillars for AI adoption in smart cities (Ben Dhaou et al., 2024; Thomas et al., 2025). Notably, without managerial commitment and sufficient funding, even well-designed AI systems are likely to fail.
Human capital components—particularly awareness of local culture (0.937), technology acceptance (0.797), and problem‑solving skills (0.923)—had strong direct effects on mediating factors (trust in system accuracy, equitable distribution of benefits, and a clear managerial vision) as well as on desirable outcomes. These results confirm previous domestic studies (Nikfarjam & Soleimani, 2023; Karimi & Naderi, 2023) while extending them by quantifying the relative importance of local knowledge, a factor often overlooked in general AI models. In underdeveloped regions, employees’ familiarity with geographical and cultural characteristics becomes a strategic asset that AI cannot easily replicate.
Furthermore, coexistence strategies—including intelligent task division, continuous training, and the use of decision-support systems—significantly improved outcomes such as service quality (0.873), citizen trust (0.894), crisis resilience (0.881), and reduced operational costs (0.877). These findings strongly support the collaborative intelligence model (Wilson & Daugherty, 2018) and recent empirical evidence from South Korea and Singapore (Yang & Lee, 2025; Singh & Shah, 2025), where human‑in‑the‑loop designs have enhanced both efficiency and public acceptance. However, this study uniquely demonstrates that in resource‑constrained environments, continuous training and intelligent task allocation are not optional enhancements but core drivers of effective coexistence.
Compared with earlier international studies that focused primarily on leading smart cities such as Barcelona and Singapore, this model reveals that contextual factors play a disproportionately larger role in less developed regions. While Ferreira dos Santos et al. (2025) identified inclusiveness and trust as key drivers, the present study adds that budget limitations and deficiencies in basic infrastructure can completely hinder AI initiatives unless they are explicitly addressed. Similarly, although ethical concerns (such as privacy and algorithmic bias) are global issues (Engstrom et al., 2020), in Sistan and Baluchestan Province, the absence of any formal ethical framework emerged as a primary concern raised by experts.
From a theoretical perspective, this study proposes a third model beyond the dominant views of “AI as replacement” or “AI as complement.” It provides empirical evidence for coexistence as a distinct, context‑dependent relationship in which AI and human capital co‑evolve through mutual adaptation. From a practical perspective, the final model—comprising six components and 21 indicators—offers an operational roadmap for municipalities facing similar structural and resource constraints.
Conclusion
Using a mixed-methods approach, this study designed and empirically tested a localized coexistence model for artificial intelligence and human capital in the municipalities of Sistan and Baluchestan Province, Iran. The final structural model demonstrated a good fit (SRMR = 0.07, NFI = 0.91) and confirmed that contextual factors, AI components, human capital, mediating factors, and coexistence strategies collectively generate desirable outcomes. The strongest effects were found, respectively, in the relationship between contextual factors and AI components, and between human capital and coexistence strategies. Accordingly, the model provides a practical and evidence-based framework for optimizing human–AI collaboration in under-resourced urban service environments.
The findings showed that achieving an optimal coexistence between artificial intelligence and human capital in the municipalities of Sistan and Baluchestan requires simultaneous attention to technical infrastructure, capable human capital, and cultural–organizational strategies. Domestic studies such as Zamani et al. (2024) and Naseri & Ahmadi (2023) emphasized the role of AI in improving the quality of urban services, including waste management and transportation. Consistent with those studies, the present research found that AI components—namely decision-making accuracy, reliability, and algorithmic transparency—have a direct effect on desirable outcomes. Likewise, the results are aligned with the studies of Nikfarjam & Soleimani (2023) and Karimi & Naderi (2023), which identified training, skills, and employees’ psychological readiness as prerequisites for successful digital transformation. In the present model, human capital, represented by indicators such as awareness of local culture and problem-solving skills, played a central role in technology acceptance.
At the international level, the findings are also consistent with Ferreira dos Santos et al. (2025), who identified inclusiveness and trust as major drivers of smart-city system adoption. Similarly, in the present model, trust in system accuracy and the perceived fair distribution of benefits emerged as key mediating factors. Furthermore, the results correspond with the findings of Singh & Shah (2025) and John et al. (2025) regarding the importance of collaborative and trust-based approaches to digital governance.

Abstract The aim of the present study is to analyze the organizational policy model based on social responsibility in the oil-rich areas company. The research method is fundamental-applicable in terms of its purpose, and mixed (qualitative-quantitative) in terms of implementation method and of exploratory type. The statistical population in the qualitative section includes 14 managers and experts in the field of social policy-making and social responsibility, faculty members, managers of the oil-rich areas company, selected purposefully; and in the quantitative section includes 191 managers and experts of the Iranian Copper Company who are experts in the field of corporate social responsibility and were selected by simple random sampling. The tool for collecting findings in the qualitative section is a semi-structured interview, and in the quantitative section is a researcher-made questionnaire. For data analysis in the qualitative section, based on the data-driven method, NVIVO version 11 software was applied; and in the quantitative section, SPSS and PLS software were applied. The results of the qualitative section showed that the extracted concepts included 89 open codes, 30 central codes, and 15 selected codes that constitute the model of social policies based on social responsibility in the National Iranian Copper Company. The results of the quantitative section show that the causal conditions of the model of implementing social policies based on social responsibility, the background factors affecting the model of implementing social policies based on social responsibility, the intervening conditions of social policies based on social responsibility, the consequences of the model of social policies based on social responsibility, and the strategies of social policies based on social responsibility are the central categories that constitute the model of social policies based on social responsibility.
Introduction
Given the progress made in recent decades regarding the implementation of social policies, its importance for policy analysts has been clarified to some extent. But it has not yet been able to achieve its true place in policy-making and is referred to as the “missing link” in many countries, especially third world countries (Faliza & et al., 2019). Many of these countries are trapped in the cycle of traditional bureaucracy and authoritarian management system that stems from the old thinking of separation of administration from politics, and the implementation of social policy remains an unsolvable issue for them. Accordingly, most government programs in these countries face failure and frustration in the implementation stage (Alvani & Shalviri, 2016). In our country, although the extensive changes and political development process that have attracted the attention of the authorities in the last few years have partially closed the gap between those who formulate social policies, implementers of the system, and the general public, and important steps have been taken to reform and transform the administrative system; many policies, guidelines, and laws are still formulated and approved in a vacuum and sometimes far from the realities of society, which naturally leads to numerous problems in implementation and in the practical stage (Zainivand Moghadam et al., 2021). Undoubtedly, part of these damages are due to the failure to consider appropriate social and cultural development for the industrialization of oil-rich regions in the country, such as Kerman Province. Although some companies have taken a few steps in recent years, the companies' actions to end this situation have been insufficient, irresponsible, and late, and some of them have only taken initial steps (Zare Behnimiri et al., 2022). In these areas, in addition to the construction and expansion of its phases, it has caused the loss of people's sense of place in the villages, as well as the arrival of countless immigrants from all over the country to the region and the undesirable reception and accommodation methods in labor camps, the lack of healthy recreation, the distance of workers from their family environment, the multiculturalization of the environment, and the lack of adequate social control and supervision. Such issues have caused great harm to the people of local communities, and with many social and cultural issues such as social insecurity, the risk of contracting various diseases caused by biological contamination, and the uncontrolled entry and exit of workers who have suspicious interactions (Salari-Eskari & Shafiei, 2022). Therefore, the main question of this research is: What is the model for implementing social policies based on social responsibility in the National Iranian Copper Industries Company?
Theoretical Framework
Social Policy
Social policy is a set of interrelated decisions made by groups or social and political actors of organizations with the aim of achieving specific goals (Maadani et al., 2018).
Social Responsibility Corporate
Social responsibility means that organizations, in addition to carrying out economic activities and producing goods or services, must act in a way that contributes to the well-being and development of society and prevents social and environmental harm. This responsibility includes complying with laws, respecting employee rights, producing safe and quality products, protecting the environment, and participating in public benefit activities (Por hoseini & Farahbakht Fomani, 2024).
Pazhouhan et al. (2026) analyzed the mediating role of organizational ambidexterity in the effect of corporate social responsibility and knowledge management infrastructure on sustainable corporate performance. The research findings showed that the path coefficient of corporate social responsibility on organizational ambidexterity was 0.417, the path coefficient of knowledge management infrastructure on organizational ambidexterity was 0.379, the path coefficient of social responsibility on sustainable performance was 0.513, the path coefficient of knowledge management infrastructure on sustainable performance was 0.439, and the path coefficient of organizational ambidexterity on sustainable performance was 0.571, which were significant at the 95% confidence level. The results also showed that organizational ambidexterity can mediate the effect of social responsibility on sustainable performance by 0.751. In addition, organizational ambidexterity can mediate the effect of knowledge management infrastructure on sustainable performance. Accordingly, promoting an organizational culture that strengthens social and environmental values ​​and encourages employees to participate in corporate social responsibility programs will lead to sustainable company performance.
Akbari et al. (2023) investigated the prediction of consumer loyalty through the role of flow experience, perceived value, and corporate social responsibility. The results showed that attention, focus, and the concept of time have a significant effect on flow experience. Other results showed that flow experience, perceived value, and corporate social responsibility have a significant effect on consumer loyalty.
Research Methodology
The research method is fundamental-applicable in terms of its purpose, and mixed (qualitative-quantitative) in terms of implementation method and of exploratory type. The statistical population in the qualitative section includes 14 managers and experts in the field of social policy-making and social responsibility, faculty members, managers of the oil-rich areas company, selected purposefully; and in the quantitative section includes 191 managers and experts of the Iranian Copper Company who are experts in the field of corporate social responsibility and were selected by simple random sampling. The tool for collecting findings in the qualitative section is a semi-structured interview, and in the quantitative section is a researcher-made questionnaire.
Research findings
For data analysis in the qualitative section, based on the data-driven method, NVIVO version 11 software was applied; and in the quantitative section, SPSS and PLS software were applied. The results of the qualitative section showed that the extracted concepts included 89 open codes, 30 central codes, and 15 selected codes that constitute the model of social policies based on social responsibility in the National Iranian Copper Company. The results of the quantitative section show that the causal conditions of the model of implementing social policies based on social responsibility, the background factors affecting the model of implementing social policies based on social responsibility, the intervening conditions of social policies based on social responsibility, the consequences of the model of social policies based on social responsibility, and the strategies of social policies based on social responsibility are the central categories that constitute the model of social policies based on social responsibility.
Conclusion
The present study was conducted with the aim of an organizational policy model based on social responsibility in the oil-rich areas company. The results of this study are consistent with the results of Pazhouhan et al. (2026), Akbari et al. (2023), Kashanipour & Ghorbani (2022), Mighi fard (2021), Barshad et al. (2021), Behnam et al. (2021), Ramzan et al. (2021), Liua et al. (2021), and Svetlana et al. (2020). Barshad et al. (2021) showed that there is a negative and significant relationship between social responsibility and information asymmetry. Social responsibility performance, according to organizational policy, can reduce information asymmetry when information related to this performance of companies is made available to the market in some way (through the preparation and publication of social and environmental performance reports or through the announcement and publication of the score or rank of corporate social responsibility by financial institutions, etc.).
Based on the results, the following suggestions were made:
- Strengthening civil and local institutions and involving them in the company's missions and viewing them as strategic partners in achieving a common goal
- In order to meet social expectations from organizations and reduce information inequality, necessary and effective policies related to corporate social responsibility should be examined.

Abstract Abstract
The aim of this research is to present a study and analysis of consumer behavior through social media analytical models to improve reverse logistics decisions. The research method is fundamental and applicable research in terms of its purpose, and descriptive-survey in terms of research method. The statistical population of the study is SAMSUNG mobile phone users. To analyze the findings, first programming for social media data through word labeling using LAD, word stemming with Porter STEMMER, data feature identification, and in the case of website and Instagram data; entity identification with NER, stop word removal, latent dirichlet thematic modeling, word classification based on determined keywords, and finally analyzing the sentiments of SAMSUNG mobile phone users with the Naive Bayes algorithm was carried out. The findings showed that sentiment analysis has a positive effect on reverse logistics decisions. By providing real-time insight into customer sentiment, it helps managers and decision makers identify potential issues and facilitate rapid resolution. In addition, sentiment analysis helps predict demand, increase resource allocation, and improve overall operational efficiency. By incorporating sentiment analysis into the reverse logistics decision-making process, organizations can gain a competitive advantage by understanding and responding appropriately to customer sentiment.
Introduction
Anything that allows users to participate, create, and share information from anywhere is a social media (Berthon et al., 2012). Looking at the breadth of research conducted in various sciences, the importance and role of social media in various product-oriented and service-oriented industries cannot be denied (Garant, 2017), because this platform directly and indirectly affects user behavior or the way they make decisions (Schivinski & Dabrowski, 2016). Today, users' interactive behaviors on social media have become an important source and influence on marketing activities in various businesses.
The availability of interactive tools such as mobile phones, tablets and personal computers, along with the wide variety of social media, has made it possible to make user experience and information available to others in the shortest possible time. Companies (or organizations) obtain this information through the most important competitive analysis techniques in social media, including text mining, trend analysis, sentiment analysis, opinion analysis and visualization techniques, which are used to discover hidden concepts and patterns in large volumes of data (Kim et al., 2016). Collecting data on social media and analyzing data to help decision makers address specific problems refers to social media analytics (Lee, 2019).
In the era of information and electronic communications, all mobile phone manufacturing companies are also subject to challenges such as changing customer expectations, expanding competition, technological advances, and extensive economic, social, demographic, cultural, etc. developments, and must choose strategies to continue their lives in turbulent markets. The huge popularity of social media, especially mobile phones, in recent years has attracted more attention from society and, with the large volume of user-generated content, including their opinions, feelings, and experiences, has become one of the most important and up-to-date sources of information for manufacturers, suppliers, consumers, and other active factors in the economy and industry, and has brought new opportunities and challenges to organizations (Kim et al., 2016; Zarco et al., 2019). Social network analysis and big data confront today's digital world with issues that it has not encountered before. The influx of information allows businesses to better understand customer behavior and purchasing patterns. However, the benefits of big data go beyond these issues and can help scientists solve global issues (Talón et al., 2018). With the growing world population and ever-increasing technologies, more electronic devices are being produced than ever before (Balde et al., 2017) and recently, more than 145,000 tons of natural resources - some of which are very scarce - are consumed each year to produce mobile phones (Statista, 2020). Considering the above, the main research question is as follows: How can consumer behavior analysis through social media analytics models improve reverse logistics decisions?
Theoretical Framework
Social Media
Social media are websites and services that shape users' social connections in the form of user-generated content; they are sharing their content in small and large groups (Marwick & Boyd, 2014).
Reverse Logistics
Reverse logistics is the process by which manufacturers receive their previously shipped products from end consumers or recipients for re-sending to another customer, recycling, remanufacturing, repair, or disposal. The principles of reverse logistics will increase customer service and loyalty, restore the value of assets faster, improve customers' mental image of the brand, better communication with shareholders, increase personal motivation, and ultimately achieve the organization's sustainable vision and goals (Eidi & Rezaei, 2017).
Mohades deilami et al. (2021) studied the presentation of an intelligent model for multi-faceted recognition of user personality using deep learning methods. They combined the sand convolutional neural network with the Adabost model for data classification so that they could classify the experimental data that were classified with errors in the second stage of classification with higher accuracy by assigning an alpha coefficient. The proposed model was tested on two datasets, ISIS and YouTube; and based on the results obtained, the proposed model has higher accuracy than other existing methods on both datasets.
Mohammadi & Khalaj (2021) studied the presentation of a model for opinion mining at the document feature level for hotel user reviews. The results showed that the proposed method performed better than the basic methods based on sentiment dictionaries on this dataset, and the accuracy, precision, recall, and F-criterion evaluation criteria using the proposed method were 65, 94, 53, 94, 89, 93, 17, and 95, respectively. The diversity of ways in which customers engage with brands through social networks has become a challenge for brand managers; such as how social networks are used with a strategic approach and how much content should be produced so that company-customer interactions lead to value creation for the organization.Research Methodology
The research method is fundamental and applicable in terms of research method, and descriptive-survey. The statistical population of the study is: SAMSUNG mobile phone users.
Research Findings
To analyze the findings; first, by programming for social media data through word tagging using LAD, word stemming with Porter STEMMER, data feature identification, and in the case of website and Instagram data; entity identification with NER, stop word removal, Latent Dirichlet thematic modeling, word classification based on determined keywords, and finally analyzing the sentiments of SAMSUNG mobile phone users with the Naive Bayes algorithm was carried out. The findings showed that sentiment analysis has a positive effect on reverse logistics decisions. By providing real-time insight into customer sentiments, it helps managers and decision makers identify potential issues and facilitate quick resolution. In addition, sentiment analysis helps to predict demand, increase resource allocation, and improve overall operational efficiency. By incorporating sentiment analysis into the reverse logistics decision-making process, organizations can gain a competitive advantage by understanding and responding appropriately to customer sentiment.
Conclusion
The present study aimed to provide a review and analysis of consumer behavior through social media analytical models to improve reverse logistics decisions. The results of this study are consistent with the results of Shahsavandi et al. (2025), Mashhadizadeh et al. (2024), Ghanbarian et al. (2023), Hahighhinia et al. (2021), Malekakhlagh et al. (2021), Mohades deilami et al. (2021), Mohammadi & Khalaj (2021), Ahmadia et al. (2020), Abdul Waheed et al. (2019), Zhang et al. (2019), and D. Xue et al. (2018). Hahighhinia et al. (2021) showed that a number of units were jointly efficient by implementing the CCR and BCC models at the levels of organizational activity and audience response; but other units were also identified as efficient by implementing the BCC model. Then, using hyperefficiency analysis, the efficient units were ranked. Finally, inefficient units in each of the social networks are identified and appropriate strategies are proposed to improve the performance of the inefficient units. This model will help media managers to identify their inefficiency compared to competitors and become an efficient unit.

Abstract This research aimed to predict the products required by e-commerce customers in Kaleh Meat Products Company using machine learning algorithms. The present research was conducted with an applicable and quantitative approach in terms of purpose. The data used included historical information on online purchases of Kaleh Company customers, which included the variables "product price", "past weight purchase volume", "product type", "past purchase frequency" and "past Rial purchase amount". To predict the "required product" as an output variable, four machine learning algorithms including artificial neural network, random forest, decision tree and K-nearest neighbor were implemented and evaluated with the criteria of Accuracy, Precision, Recall and F1-Score. The results of the model evaluation showed that the artificial neural network algorithm achieved the highest score in all evaluation criteria (Precision: 95.1%, Accuracy: 94.2%, Recall: 95.9% and F1-Score: 95.5%). The results showed that the artificial neural network has the best performance in predicting the products needed by customers; the research models were implemented and validated in the Python version 3.x programming environment and using the specialized libraries Scikit-learn and Keras based on TensorFlow. After that, the random forest, decision tree and K-nearest neighbor algorithms were used, respectively. Also, the analysis of the importance of the variables showed that "past weighted purchase volume" and "past purchase frequency" had the greatest impact on the model's prediction. The proposed model based on the artificial neural network has the ability to become an accurate and efficient product recommendation system for the Kale company. Implementing this model can lead to optimized inventory management, increased customer satisfaction, and ultimately sales growth by accurately predicting future customer demand.
Introduction
Accurately predicting customer purchasing behavior is recognized as one of the most central capabilities of market-oriented organizations in the era of digital transformation, because in order to achieve sustainable competitive advantage, companies must predict future customer needs and allocate their resources to the production and distribution of products that are most likely to be purchased; otherwise, they will face phenomena such as accumulation of low-demand inventories, increased holding costs, lost sales opportunities, and ultimately reduced profitability (Bhavishya et al., 2025). This challenge is even more critical in industries with perishable and time-sensitive products such as meat products, because any forecast error not only leads to direct financial losses, but also to damage to brand reputation and reduced customer trust (Satyanarayana et al., 2025; Jauhar et al., 2025). With the rapid expansion of e-commerce and the development of digital infrastructure, a huge amount of transactional big data including purchase records, order frequency, product type, prices, and purchase time has been generated, which has provided a suitable platform for the application of advanced data analysis methods (Wen & Liu, 2026; Jain, 2025). In the meantime, machine learning algorithms are known as powerful analytical tools in the field of demand forecasting and recommender systems due to their ability to identify hidden patterns and nonlinear relationships (Syamsuri et al., 2025). Despite the large volume of transaction data in the e-commerce system of Kale Meat Products Company, no data-driven model has been designed to predict the products needed by customers, and managers often face shortages of high-demand products or overproduction of low-demand products. Therefore, the main objective of this study is to design and evaluate a model based on machine learning algorithms to predict the products needed by customers in the e-commerce platform of Kale Company and to identify the best algorithm in terms of accuracy, precision, recall, and F1 score.
Theoretical Framework
The theoretical foundations of this study are based on the intersection of e-commerce, consumer behavior, and machine learning. Machine learning enables the extraction of complex patterns from large data and data-driven decision-making (Breiman, 2001). Algorithms such as support vector machines are used in the analysis of customer behavioral data due to their ability to model nonlinear relationships (Cortes & Vapnik, 1995).
Customer Buying Behavior in E-Commerce (Digital RFM Model)
E-commerce platforms are a huge source of customer behavioral data (Kechri et al., 2025). Past purchasing patterns are considered the strongest predictor of future behavior (Li & Hu, 2026). The RFM model analyzes customer behavior based on purchase recency, purchase frequency, and transaction value (Gupta & Agarwal, 2024). In this study, past purchase frequency and past purchase amount are adapted from this theoretical structure. Customers with higher purchase frequency have stronger behavioral attachment to the brand (Fang et al., 2025). The financial volume of transactions reflects the customer lifetime value (Akter et al., 2025). Combining these variables allows for dynamic personalization (Vuppala & Prasad, 2026).
Supply Chain: Demand Forecasting in Perishable Food Industries
Meat products face logistical challenges due to their high perishability (Jauhar et al., 2025). Maintaining a safe inventory is costly due to the risk of expiration (Padmanabhan et al., 2025). The imbalance between supply and demand creates the bullwhip effect (Letto & Orsini, 2025). Predictive logistics emphasizes the shift from push to pull mode based on actual demand (Thiel et al., 2023). In this study, past weighted purchase volume and product type are entered into the model as supply chain indicators.
Analytical Tools: Recommender Systems and Python Computing Platform Recommender systems play a key role in guiding customer choices (Koren et al., 2009). The entire data pipeline is developed in Python. Artificial neural networks extract hidden patterns of transactions (Hochreiter & Schmidhuber, 1997). Random forest is predicted using decision trees and criteria such as Gini impurity (Da, 2025). K-nearest neighbor algorithm also operates based on behavioral similarity.
Research methodology
The present study is applicable in terms of purpose, quantitative in nature, and based on a data mining approach. The statistical population includes all online customers of Kale Company, and a sample of 15 thousand purchase records (after cleaning and preprocessing) was extracted from the company's online shopping transaction database by simple random method. The dependent variable "customer's required product" was defined as binary (select/not select the target product) and the independent variables included product price, past purchase weight volume, product type, past purchase frequency and past purchase amount in Rials. Four classification algorithms including Artificial Neural Network (ANN), Random Forest, Decision Tree and K-Nearest Neighbor (KNN) were implemented using Python 3.x and Scikit-learn and Keras libraries (based on TensorFlow). The implementation process included data preprocessing (cleaning, normalization of quantitative variables and encoding of nominal variables), data splitting into training (80%) and test (20%) parts, training the models using cross-validation to avoid overfitting, and finally evaluating the performance of the models on the test data. The evaluation was performed using the criteria of accuracy (Accuracy = (TN+TP)/(TN+FP+TP+FN)), precision (Precision = TP/(FP+TP)), recall (Recall = TP/(FN+TP)) and F1 score (F1 = 2(PrecisionRecall)/(Precision+Recall)). In order to check the stability of the results, each algorithm was run in 15 consecutive iterations.
Research findings
The results of implementing four machine learning algorithms on the data of 15 thousand online customers of Kale Company are presented in Table 1. As can be seen, the artificial neural network algorithm obtained the highest values ​​in all four criteria of precision, accuracy, recall and F1 score; and is recognized as the superior algorithm. After that, random forest, decision tree and K-nearest neighbor are in the next ranks, respectively.

Table 1 Comparison of machine learning algorithms used in the present study





Algorithms


Accuracy


Precision


Recall


F1-Score




Decision Tree


0.94


0.92


0.958


0.938




random forest


0.946


0.932


0.958


0.945




artificial neural network


0.951


0.942


0.959


0.955




K-nearest neighbor


0.931


0.912


0.944


0.922






In addition to comparing the main performance, the stability of the results was checked in 15 consecutive repetitions. The results showed that the accuracy of all four algorithms had a slight and stable improvement process; so that the artificial neural network reached 94.3% accuracy in the first iteration to 95.1% in the 15th iteration, and the random forest improved from 93.9% to 94.6%, which indicates proper convergence and the lack of strong dependence of the results on the randomness of the data. The confusion matrix also showed that the artificial neural network and the random forest have the lowest type 1 and type 2 errors. In the ranking of the input variables based on the analysis of the importance of features in the artificial neural network algorithm, the variable "weight or weighted volume of purchase" had the greatest impact on the prediction with an approximate share of 35%, followed by "past purchase times" (28%), "product type" (18%), "product price" (12%) and "previous purchase amount in riyals" (7%). This ranking in random forest and decision tree algorithms was also observed to be almost the same, which indicates the high validity of the findings.
Conclusion
The findings of this research are consistent with previous research. Turatti (2025) showed that deep learning models have a high ability to analyze big data and predict online shopping behavior, which is confirmed by the accuracy of 1.95% of the artificial neural network in the current research. Iseal & Michael (2025) also considered analytical models based on behavioral data to be effective for estimating the probability of purchase. Mirasçı & Aksoy (2025) reported the use of machine learning models in the optimization of effective purchasing strategies, and the random forest in the current research showed a good performance with an accuracy of 94.6%. Esmeli & Gokce (2025) emphasized the importance of explainable models and the ranking of the input variables in the current research is considered a step towards clarifying the model. Also, Karimi & Mahmoodi Ranai (2025) confirmed the positive impact of artificial intelligence adoption on business performance, which reinforces the necessity of implementing the proposed model. Darvish et al. (2026) also introduced machine learning algorithms as key technologies. Due to the superior performance of the artificial neural network as well as the acceptable and stable performance of the random forest, these two algorithms are proposed as the main options for the implementation of the intelligent recommender system in Calais. Such a system can reduce perishable product waste, optimize warehouse inventory, increase sales conversion rates, and improve customer satisfaction. For future research, it is suggested to test the proposed model in similar companies, add new variables such as demographic characteristics and purchase time patterns to the model, use more advanced deep learning approaches (such as LSTM and attention-based models), and perform sensitivity analysis on the architecture of the artificial neural network (number of layers, neurons, activation functions) to increase the accuracy and stability of the model.

Abstract The aim of the present study was to provide a comprehensive model for international entrepreneurship in ECO member countries. A mixed research method was used: in the qualitative part, data were collected and analyzed using systematic data-based theory and interviews with 15 academic and executive experts (until theoretical saturation). In the quantitative part, 323 managers were selected from 2035 managers of knowledge-based companies in the Export Development and Technology Exchange Corridor by random sampling. The data collection tool included semi-structured interviews and a questionnaire based on qualitative findings. The validity of the tools was confirmed by experts and reliability was confirmed with Cronbach's alpha. Qualitative data were analyzed with MAXQDA software and three-stage coding, which resulted in the extraction of 356 primary codes, 79 open categories, 16 axial categories, and 5 selected categories. In the quantitative part, factor analysis and structural equations were conducted with AMOS. The findings showed that the international entrepreneurship model in ECO is based on multi-level convergence (macro, meso, and micro). Its main components include contextual factors (regional capacity building), causal factors (strategic context building), intervention factors (challenge management), strategies (operational framework), and consequences (sustainable development). This model can help policymakers, economic institutions, knowledge-based companies, and small, medium, and large companies enter global markets and pave the way for creating a sustainable competitive advantage and transforming ECO into an Asian innovation hub.
Introduction
International entrepreneurship, as the process of forming and expanding innovative economic activities across national borders and taking advantage of global opportunities, has become one of the main engines of economic growth in the world in recent decades (Chukwuka et al., 2024). The Economic Cooperation Organization (ECO), as a regional pact consisting of countries with common historical, cultural and geographical ties, has extensive capacities in the fields of trade, investment and knowledge transfer. With a population of over half a billion people and rich natural and human resources, these countries can provide an important platform for the expansion of international entrepreneurship. However, existing studies show that despite the existence of many opportunities, obstacles such as weak institutional coordination, limited access to capital, ineffective support policies, insufficient use of new technologies, and lack of regional entrepreneurial networks have prevented the full realization of the international entrepreneurial potential in the ECO region (khan, 2024). The ECO organization was initially founded in 1985 by Iran, Turkey, and Pakistan, and with the accession of seven other countries in 1992, it became a regional institution with the prospect of economic cooperation, infrastructure development, and facilitation of trade exchanges (abbas, 2024).
Despite such capabilities, the growth of international entrepreneurship in ECO has faced serious obstacles; Complex bureaucracy, financial constraints, difficulty in accessing global markets, and sanctions have prevented the full use of potential (Montiel, 2023). Past research also shows that factors such as a strong business environment, effective support policies, the use of new technologies, and the capabilities of entrepreneurs are essential conditions for success in this direction (Deakins et al., 2024). However, the role of local culture and values, the effect of national policies, and how to integrate new technologies in a regional framework have still received less attention (Nazari et al., 2024).
On the other hand, the geopolitical and economic conditions of these countries are such that entrepreneurial cooperation can not only improve the level of economic interactions in the region, but also play a role in increasing their economic resilience and socio-political convergence. Thus, providing a comprehensive and localized model for the development of international entrepreneurship in ECO member countries is an undeniable necessity; a model that can encompass both structural factors (such as policies, laws, and infrastructure) and behavioral factors (such as entrepreneurial culture, innovation, and risk-taking) and provide practical and efficient solutions by considering common characteristics and differences between member countries. Examining these obstacles and identifying key success factors can pave the way for providing a local and efficient model for the development of international entrepreneurship in the ECO region. Therefore, the research question is: What model can explain the key and effective dimensions of international entrepreneurship in ECO member countries and pave the way for the sustainable development of the region?
Theoretical foundations
Entrepreneurship and economic growth
Entrepreneurship is recognized in the economic development literature as one of the most important engines of growth and innovation. This phenomenon creates economic and social value by identifying new opportunities, organizing resources, and creating innovative businesses, and provides a platform for the dynamics of economic systems (Callegari, 2024). At the international level, entrepreneurship takes on more complex dimensions, because entrepreneurs are forced to face institutional, political, and cultural diversity in addition to economic factors. Accordingly, “international entrepreneurship” as an interdisciplinary field in management, economics, and social sciences, focuses on the process of identifying and exploiting cross-border business opportunities (Zahra & George, 2017). In other words, at the international level, this concept becomes important when entrepreneurs operate in diverse political, economic, and cultural environments and are forced to adapt to the institutional and structural differences of different markets (Zahra and George, 2017). Having its roots in internationalization discussions (Tolstoy, 2024), international entrepreneurship, is known as a tool for exploiting cross-border opportunities and creating competitive advantage. Doozandeh Ziabar et al., (2024) studied the presentation of a social entrepreneurship model in rural tourism development in a tourism target village in Guilan province. The statistical population of the study included 10 managers, experts, and university professors in the field of tourism, selected through purposive sampling. The results of the qualitative questionnaire and open interviews with sample members were analyzed after taking notes and transferring them to the system using the data-driven method and through coding and Max Quda software, and the output and final model were reported. The results showed that traditional tourism entrepreneurship follows a capitalist approach.
Shahzad et al. (2024) studied "International Entrepreneurship Antecedents and the Role of Emerging Technologies in Achieving Sustainable Development Goals". This research is applicable in terms of purpose, and quantitative in terms of approach; the data were analyzed using PLS-SEM techniques in SmartPLS 4 software. The findings showed that key antecedents of international entrepreneurship significantly affect sustainable development and emerging technologies play a mediating role between antecedents and sustainable development.
Research Methodology
This research was conducted with a mixed approach (modern hybrid) and in two qualitative and quantitative stages. In the qualitative part, systematic data-based theory was used and the statistical population included academic and non-academic experts in the field of international entrepreneurship. Purposive sampling continued until theoretical saturation was reached, and a total of 15 semi-structured interviews were conducted. Qualitative data were collected through in-depth interviews, observation, and review of scientific documents, and then analyzed. In the quantitative part, the data collection tool was a researcher-made questionnaire with a five-point Likert scale. The reliability of the questionnaire was confirmed by Cronbach's alpha test and its validity was confirmed through content validity and construct validity. Finally, structural equation modeling was used to test the research hypotheses using Amos software.
Research findings
By presenting a local model of "entrepreneurship development based on multi-level convergence", the present study showed that institutional coordination, regional networking, and empowerment of entrepreneurs at three macro, intermediate, and micro levels connect regional capacities in an integrated manner. Contextual factors such as policies, entrepreneurial culture, technological infrastructure and international cooperation provide the foundation for entrepreneurial development, while administrative barriers, legal restrictions and cultural differences pose challenges. Research innovations include the “interactional model of natural resources”, the “dual role of family relationships”, and the “multi-layer model of administrative barriers”. Proposed strategies target the development of infrastructure, cross-border cooperation networks, and the promotion of individual capabilities. The consequences include increased innovation, economic growth and the creation of job opportunities, and social welfare.
Conclusion
The present study, with the aim of analyzing the development of international entrepreneurship in the ECO region, has presented an indigenous model called “Entrepreneurship Development Based on Multilevel Convergence”. The findings show that multilevel convergence, including institutional coordination, regional networking and empowerment of entrepreneurs, plays a central role in strengthening international entrepreneurship and connects regional capacities in an integrated manner at three levels: macro (regional policy-making and governance), meso (inter-organizational networks) and micro (individual skills and capabilities). These results are consistent with the findings of Morris (2024) and O’Connor (2023), who have emphasized the importance of institutional frameworks and cooperation networks in the growth of regional entrepreneurship.
The analysis of the research context showed that contextual factors including supportive policies and laws, entrepreneurial culture, technological infrastructure and international cooperation are the foundation for the formation of international entrepreneurship in the ECO region. Cultural and historical commonalities, shared natural resources and economic diversity of countries, especially in the completion of the value chain, play both facilitating and challenging roles. Innovative findings of the research include the “interactive pattern of natural resources” and the “dual role of family relationships” that simultaneously act as an advantage and a constraint in the entrepreneurial process. These results are in line with the studies of Khan et al. (2024) and Zocchla (2024) that have highlighted the importance of contextual capacities in regional entrepreneurship. On the other hand, intervening conditions including administrative and bureaucratic challenges, legal and policy constraints and cultural and social barriers were identified. Lengthy company registration processes, lack of legal transparency, sudden policy changes, language differences, and limited role of women are examples of the main barriers. By introducing the “multi-layered model of administrative barriers” and providing an integrated framework for managing these challenges, this study has provided practical solutions to reduce their negative effects, and is consistent with the findings of Esmaeilpour et al. (2020), Khosravi (2023), and Navi (2025).
Entrepreneurship development strategies in the ECO region focus on three main axes: strengthening legal frameworks and supportive policies, developing common technological and economic infrastructure, and expanding cross-border cooperation networks. Tools such as tax exemptions, joint technology parks, digital platforms, and holding regional conferences facilitate entry into entrepreneurial activities and increase the capacity for synergy among entrepreneurs in member countries. Research innovations include the design of a “regional entrepreneurship policy model at three levels”, a framework for measuring the effectiveness of shared technological infrastructures, and the development of a “smart networking model among regional entrepreneurs.”
The consequences of international entrepreneurship development in the ECO region include two dimensions: economic and social. From an economic perspective; increased innovation, GDP growth, and technological export promotion are observed, and from a social perspective; the creation of job opportunities for youth and women and the improvement of general welfare indicators are significant. These results are in line with the findings of OECD (2023) and Economic Development Bank (2022), which have emphasized that regional entrepreneurship can lead to sustainable economic and social growth. Acknowledgments The authors gratefully acknowledge all individuals, institutions, and organizations that provided scientific, technical, administrative, or advisory support throughout this research and the preparation of this manuscript. Conflicts of Interest The authors declare that they have no financial or non-financial, personal, professional, or institutional conflicts of interest relevant to this work. Data Availability Statement The data supporting the findings of this study are available from the corresponding author upon reasonable request. AI Use Statement The authors declare that no generative artificial intelligence (AI) or AI-assisted technologies were used in the preparation, writing, or editing of this manuscript. Funding The authors declare that no funds, grants, or other financial support were received during the conduct of this research or the preparation of this manuscript. Ethics Approval All procedures performed in this study were conducted in accordance with the ethical standards of the responsible institutional and national research committee.

Abstract Abstract The aim of the present study is to classify the factors of identity commodification in light of the expansion of social networks in Iran with a futures research approach. The present study is applicable in terms of its purpose; descriptive in terms of its data collection method, and exploratory in nature. The statistical population of the study includes 21 prominent Iranian academics and experts in the field of social networks and communication sciences. These individuals have excellent academic knowledge and work backgrounds and experiences. The sampling method in this study is purposeful. The data collection tool is a semi-structured interview and a questionnaire. The MICMAC method was used to analyze the findings, and in line with futures research, interaction analysis and scenario building methods were used. After in-depth interviews with experts, 22 categories were identified in six dimensions; the cultural planning variable was identified as the most influential component or variable, followed by the education component in second place. The third place in terms of impact in the direct impact matrix is ​​related to the variable of improving social skills, while in the indirect impact matrix this position belongs to the variable of self-interest. In the scenario section, 7 scenarios were identified, which are: changes in lifestyle, strengthening communication, advertising, creating a new identity, personal and behavioral factors, educational-skill factors, cultural factors, international and political factors, technological factors, and social factors. Introduction The rapid development of digital technology has changed the lives of people in various fields (Prabowo et al., 2020). The emergence of information technology has created major changes in global markets. Information technology gives all people in the world the opportunity to engage in virtual business via the Internet, and also enables them to communicate with people around the world (Hosseini et al., 2022). New information and communication technologies have given individuals and societies new identities in new forms by enabling the emergence of a networked society (Sohrabi et al., 2021). The spread of new technologies has been accompanied by the formation of virtual spaces; with a different identity and function than the tangible spaces of the past, that rewrite the values, concepts, and beliefs of the past in a way (Moharbi et al., 2023). The concept of "identity" is not a new issue and has been preoccupying humans for a long time. However, not only has it not become outdated, but it is also considered the most important concern of modern humans. This concept is one of the most abstract and complex concepts; so that "it is difficult to find a common agreement on the formation of this concept" (Wibowo et al., 2021). Identity in today's societies is not a fixed and predetermined data, but rather has a fluid form that must be constructed and revised at different times. The processes of rationalization and disenchantment, which began in previous centuries, have led to the decline of traditional values, the weakening of traditional authorities, and the increasing multiplicity of value domains. The result is uncertainty and a kind of cultural abandonment that leads to the collapse of traditional foundations of identity. (Kohestani et al., 2024) But having a coherent and specific identity is a human need. This need is no longer given to the individual in advance, but the task of constructing it is the responsibility of the individual himself. In other words, personal identity in late modernity becomes a project that must be “constructed in a reflective way. But this task must be carried out in the midst of an astonishing diversity of choices and possibilities” (Sharifi et al., 2023). Social media are a new generation of social relations space and, although not very old, they have managed to find their place in people’s lives. People's alignment with social media has intensified in recent years; and this has continued to increase with the spread of the coronavirus. So much so that today it is very difficult to imagine life without virtual networks and virtual social communication tools, and this human dependence has caused some people to use these tools to offer their products, productions, and services (Sharifi et al., 2023). Therefore, the main question of the present study is: what is the leveling of the factors of commodification of identity in light of the expansion of social networks in Iran with a futures research approach? Theoretical Framework Social Identity Social identity refers to the characteristics that distinguish a society from others. This category, which has undergone major changes with the entry of virtual social networks, is more important in relation to young people than any other group; because youth is the stage of developing an independent identity and gaining independence. Social identity influences young consumers' actions towards brands in a two-way interaction with social media (Sharifi et al., 2023). Kohestani et al. (2024) conducted a study entitled “Fame on Social Networks: A Study on the Why and Consequences of Becoming Famous on Instagram” by conducting in-depth interviews with a qualitative approach. The findings from the interviews include 6 main themes and 12 sub-themes. The results of this study indicate that generating income and acquiring economic capital, a shortcut to success, and an opportunity to be seen and heard are among the main reasons for users to seek fame on Instagram, which lead to consequences such as standardization of taste, consumerization of daily life, and transformation of values ​​and norms in society. Zand et al. (2023) conducted a study entitled; The Effect of Using Social Networks on the Social Identity and Job Performance of Employees of the Tehran Municipality Sports Organization, which showed that the use of social networks has an effect on the social identity and job performance of employees of the Tehran Municipality Sports Organization.  Research Methodology The present study is applicable in terms of its purpose, descriptive of survey type in terms of data collection method, and exploratory in terms of nature. The statistical population of the study includes 21 prominent Iranian academics and experts in the field of social networks and communication sciences. These individuals have high-level academic knowledge and work experience. The sampling method in this study is purposive. The data collection tool is a semi-structured interview and a questionnaire.  Research findings The MICMAC method was used to analyze the findings, and in line with future research, interaction analysis and scenario building methods were used. After in-depth interviews with experts, 22 categories were identified in six dimensions; the cultural planning variable was identified as the most influential component or variable, followed by the education component in second place. The third place in terms of impact in the direct impact matrix is ​​related to the improvement of social skills variable, while in the indirect impact matrix this position belongs to the profit-seeking variable. In the scenario section, 7 scenarios were identified, which include: changes in lifestyle, strengthening communication, advertising, creating a new identity, personal and behavioral factors, educational-skill factors, cultural factors, international and political factors, technological factors, and social factors.  Conclusion The present study aimed to classify the factors of identity commodification in light of the expansion of social networks in Iran with a futures research approach. The results of this study are consistent with the results of Kohestani et al. (2024), Zand et al. (2023), Sharifi et al. (2023), Tavani et al. (2022), Asgharpourmasouleh & Davari (2022), Dwivedi et al. (2023), Nafees et al. (2021), Katherine Cao (2020), and Cirklová (2020). Tavani et al. (2022) showed that factors related to users' identity include: self-reflection and the growth of reflective thinking, interactions and communications on Telegram and Instagram, the experience of disorientation in time and space, the experience of anxiety and trust, the experience of freedom, individual independence and the power of idealism, the communicative transformation of controllability and insecurity. The main and final concept is the power of direction, which expresses the role-playing and power of action of the user in cyberspace compared to the real world, and the user can simultaneously experience diverse and sometimes contradictory roles and functions, which is due to the user's power of direction in the social network.

Abstract The purpose of this research is to present a model for sustainable financial resource provision in Iran’s sports federations. This research was conducted qualitatively using a data-based theory approach. The statistical population of the research included 17 elites in the field of sports management and sports federation management. A semi-structured interview was used as the data collection tool. The grounded theory method was employed for data collection and analysis. Data analysis was carried out in three stages: open coding, axial coding, and selective coding. MAXQDA software version 24 was used for data analysis. The findings indicated that sustainable financial resource provision in Iran’s sports federations, as the core phenomenon, is shaped by factors such as dependence on government budgets, scarcity of sustainable financial resources, and the pressure of regional and global competitions, all within a context of economic limitations, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, adopting strategies such as diversifying financial resources, commercializing sports, and strengthening the branding of federations is essential. The successful implementation of these strategies leads to outcomes such as financial independence, infrastructure development, and increased competitiveness of sports federations, ultimately ensuring the sustainable growth of the country’s sports.
Introduction
The strong inclination of society towards sports and the demand for sports goods and services have led the sports industry to experience significant revenue generation and contribute substantially to the economies of nations. This industry, driven by major sporting events, creates opportunities for advertising across various media, thereby establishing the necessary platform for interaction between industry, commerce, and sports (Halkos & Tzeremes, 2013). The macroeconomic impact of sports, such as its contribution to Gross Domestic Product (GDP) and Gross National Product (GNP), as well as its role in job creation, compels countries to accurately and regularly assess sports' economic effects each year (Dimitropoulos & Alexopoulos, 2014). Professional clubs worldwide utilize various methods to secure financial resources and cover expenses, including attracting sponsors for commercial product advertising, player sales, ticket and merchandise sales, and offering ancillary services (Singh et al., 2016). One crucial method for funding sports activities, particularly championship sports, is attracting suitable sponsors by sports organizations and officials. In this regard, creating a healthy and conducive environment for investment by industrialists and the private sector in sports is essential and necessary. Capital owners are interested in establishing sports facilities, providing sports services, producing sportswear and equipment, and organizing profitable competitions because their fundamental goals include achieving global recognition through competitions, offering high-quality services and products, and most importantly, realizing profits through effective marketing (Andreopoulou et al., 2015). The significant presence of the government in professional sports has created challenges for both parties. On one hand, given the severe economic constraints in the country and intervening factors such as oppressive sanctions and threats to people's livelihoods, allocating substantial funds to professional sports is no longer justifiable for the government and the nation as it once was. On the other hand, professional sports, by relying on government and state budgets, has become a dependent phenomenon. Despite the abundant potential for revenue generation, sports clubs in Iran are not only unprofitable for governments and investors but also face fundamental challenges in meeting their own expenses. Therefore, the issue of financial provision, along with the existing tools, methods, and strategies for attracting capital to ensure the dynamic and efficient operation of professional sports, has become more critical than ever. Accordingly, the present research seeks to answer the question: How can a model for sustainable financial resource provision in Iran's sports federations be presented?
Theoretical Framework
Financial Resource Provision
The financial capacity of a profit organization is defined as the ability and potential to develop and deploy financial capital that can be converted into money: revenues, expenses, assets, and liabilities (Hall et al., 2003). From the perspective of sports financing, using the allocation of public resources in the Slovak Republic, according to the study by Kucera & Nemec (2021), four forms of financing can be discussed: assignment taxes; EU budget; budgets of state-owned companies; and budgets of central government, local government, and their parts are used to finance projects that also serve sports activities (indirect public resources).
Maleki et al. (2025) investigated the design of a model for innovative financing in the sports industry, focusing on the role of FinTechs. The research results indicated that the empowering drivers for sports startups are capital attraction through smart FinTech, novel revenue models with data analysis, smart contracts in transfers or sponsorships, and the application of blockchain in financial transparency, which are the five influential factors in this regard. The proposed policy recommendations focus on key influential drivers and include supporting infrastructure such as specialized accelerators in the sports and FinTech domain, access to seed capital, tax exemptions for innovators in the sports industry, and encouraging the use of artificial intelligence in sports data analysis. The results of this research can serve as a basis for policymaking to support sports startups, attract venture capital, and develop the digital sports economy.
Mokhlesi et al. (2024) examined the factors influencing financing in sports clubs and presented a model based on exploratory analysis. They stated that the increasing societal inclination towards sports and the demand for sports goods and services have led the sports industry to experience significant revenue generation and play a substantial role in the economy of any country. The results show that variables such as holding raffles among spectators, dedicated administrative buildings, financial support from fans, attracting foreign investors, ticket pricing in different tiers, advertising club products and services through media, receiving interest income from banks, using their own commercial licenses for business transactions, and dedicated stadiums are of higher importance.
Research Methodology
This research was conducted qualitatively using the grounded theory method. The statistical population of the study included 17 experts in the field of sports management and the management of sports federations. The data collection tool was semi-structured interviews. The grounded theory method was used for data collection and analysis.
Research Findings
Data analysis was performed in three stages: open coding, axial coding, and selective coding. The MAXQDA 24 software was used for data analysis. The findings indicated that the provision of sustainable financial resources in Iran's sports federations, as the core phenomenon, is shaped by factors such as dependence on government budgets, lack of stable financial resources, and the pressure of regional and global competitions; within a context of economic limitations, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, adopting strategies such as diversifying financial resources, commercializing sports, and strengthening federation branding is essential. The successful implementation of these strategies leads to outcomes such as financial independence, infrastructure development, and increased competitiveness of sports federations, ultimately ensuring the sustainable growth of the country's sports.
Conclusion
The present research was conducted with the aim of providing a model for sustainable financial resource provision in Iran's sports federations. The results of this research are aligned with the findings of Maleki et al. (2025), Mokhlesi et al. (2024), Varmus et al. (2023), Ahmadi (2022), Guevara et al. (2021), and Ghafouri Yazdi et al. (2021). Mokhlesi et al. (2024) stated that the increasing societal inclination towards sports and the demand for sports goods and services have led the sports industry to experience a significant revenue-generating trend, playing a crucial role in any country's economy. The results indicate that variables such as holding lotteries among spectators, having dedicated administrative buildings, fan financial support, attracting foreign investors, ticket pricing in different tiers, advertising club products and services through media, receiving bank deposit interest, using own commercial licenses for business transactions, and having dedicated stadiums are of higher importance.
As the core phenomenon, "The effort to provide sustainable financial resources in Iran's sports federations" is shaped by factors such as dependence on government budgets, lack of stable financial resources, and the pressure of regional and global competitions; within a context of economic limitations, managerial weaknesses, and infrastructural challenges. Factors such as government policies, the role of media, and organizational capabilities moderate the intensity and direction of these efforts. To overcome these challenges, adopting strategies such as diversifying financial resources, commercializing sports, and strengthening federation branding is essential.

Abstract The present research aims to identify and prioritize the factors affecting the success and failure of platform ecosystems in technology companies. The research method is applied-developmental in terms of its objective, and exploratory mixed-methods (qualitative-quantitative) in nature. The statistical population includes 15 industry and academic experts in the qualitative section and 12 experts in the quantitative section. The data collection instrument is semi-structured interviews. For data analysis in the qualitative section, thematic analysis was conducted using MAXQDA 2024 software, and in the quantitative section, the factors were prioritized using the fuzzy Analytic Hierarchy Process (AHP). Sensitivity analysis using a four-scenario approach, along with Friedman and Spearman tests, was employed to confirm the robustness of the results. The qualitative results identified 36 open codes, 12 sub-themes, and ultimately 6 success factors and 6 failure factors. The quantitative results showed that the most important success factors are, respectively, “positive network effects” (weight 0.382), “transparent and fair governance” (0.245), and “effective management of complementors” (0.163). In contrast, the most important failure factors are “multi-homing migration” (0.351), “unsustainable revenue model” (0.228), and “reverse network effects” (0.175). The inconsistency ratios of the matrices (CR = 0.05 for success and CR = 0.07 for failure) indicate satisfactory reliability of judgments. A proposed three-layer integrated framework for success (foundational prerequisites, core drivers, sustaining factors) and failure (greatest threat, structural threats, contextual threats) was presented. Platform managers should prioritize strengthening positive network effects, governance transparency, and countering multi-homing migration.
Introduction
In recent years, the emergence and expansion of digital platforms have fundamentally transformed the landscape of technology businesses. Platform ecosystems, formed through dynamic interactions among different groups of actors (developers, suppliers, customers, and complementors), have become one of the pillars of the digital economy (Alt, 2022). Despite the remarkable success of some global platforms, many platform ecosystems in technology companies face a high failure rate, and only a limited number of them are able to sustain and scale (Fan et al., 2021). This issue is of particular importance in Iran due to the rapid growth of platforms such as Snapp, Digikala, Torob, and Albatros, coinciding with challenges of survival and sustainable profitability. According to industry reports, the customer churn rate in Iranian platforms is estimated at over 40% annually on average, indicating structural problems in governance, revenue, and user interaction models. Previous research in the field of platform ecosystems has primarily focused on aspects of architecture, governance, and competitive strategy (Engert et al., 2022). Some studies have addressed the role of complementors (Blasco-Arcas et al., 2020; Deilen & Wiesche, 2021), while others have emphasized the importance of platform leadership (Leong et al., 2019). In this regard, recent studies published in reputable domestic journals have emphasized the need to localize success and failure models in digital contexts. For example, Torkanloo et al. (2025), in a study titled “Increasing Purchase Intention in Chain Retail Stores Using an Integrated Channel Strategy,” demonstrated that customer experience and perceived risk play a decisive role in the success of digital channels. Additionally, Aalami et al. (2025), in designing a customer experience model in the retail industry with an emphasis on Generation 4.0, highlighted the importance of bilateral interactions and co-creation of value as the primary drivers of success.
In this context, the main research question is formulated as follows: How can the factors affecting the success and failure of platform ecosystems in technology companies be identified and prioritized?
Theoretical Framework
Platform Ecosystem
A platform ecosystem refers to a set of independent and semi-independent actors organized around a shared technological core (the platform) who, through repeated interactions, exchanges, and mutual collaboration, create value beyond the sum of the individual components. Unlike traditional hierarchical organizations, which are based on ownership and direct control, platform ecosystems operate through indirect orchestration and network governance (Kretschmer et al., 2022).
Rong et al. (2025) examined the all-in-one platform strategy, focusing on building a multi-product ecosystem to lock in users. The results showed that features such as the integration of diverse services, inter-product synergies, and centralized data management influence platforms’ ability to create sustainable user dependence and strengthen their competitive position in multi-sided markets by increasing switching costs and enhancing a unified user experience.
Schreieck et al. (2022) investigated the governance of platform ecosystems through inward and outward governance in traditional companies, using SAP as a case study. The findings indicated that factors such as managing conflicts between internal units, designing open application programming interfaces (APIs), and creating reward mechanisms for business partners, through their influence on platform governance structure, affect the success of leading firms in building innovation ecosystems and maintaining competitiveness in digital markets.
Research Methodology
The research method, in terms of objective, is applied-developmental, and in terms of nature, it is exploratory mixed-methods (qualitative-quantitative). The statistical population in the qualitative section consisted of 15 industry and academic experts, while in the quantitative section it included 12 experts. The data collection tool was semi-structured interviews.
Research Findings
For data analysis, thematic analysis was employed in the qualitative section using MAXQDA 2024 software. In the quantitative section, factors were prioritized using the fuzzy Analytic Hierarchy Process (AHP). Four-scenario sensitivity analysis, along with Friedman and Spearman tests, were used to confirm the robustness of the results.
The qualitative analysis revealed 36 open codes, 12 sub-themes, and ultimately identified 6 success factors and 6 failure factors.
The quantitative analysis indicated that the most significant success factors, in order of importance, are: “Positive network effects” (weight 0.382), “Transparent and fair governance” (0.245), “Effective management of complementors” (0.163). Conversely, the most critical failure factors identified are: “Multi-homing migration” (0.351), “Unsustainable revenue model” (0.228), “Reverse network effects” (0.175).
The matrix inconsistency ratios (CR=0.05 for success and CR=0.07 for failure) suggest a favorable reliability of the judgments.
A proposed three-layer integrated framework for success (foundational prerequisites, core drivers, sustaining factors) and failure (greatest threat, structural threats, contextual threats) was presented. Platform managers should prioritize strengthening positive network effects, governance transparency, and countering multi-homing migration.
Conclusion
The present research was conducted with the aim of identifying and prioritizing the factors affecting the success and failure of platform ecosystems in technology companies. The findings are consistent with the results of Zeng et al. (2025), Bontems & Chaves (2025), Tiwana & Konsynski (2024), Schreieck et al. (2024), Busalim et al. (2024), Hao & Fan (2026), Rong et al. (2025), Schreieck et al. (2022), Marković et al. (2022), Gawer (2022), Mirzaee Azandariani & Arya (2022), Jalali (2021), Kretschmer et al. (2022), and Calabrese et al. (2021). Specifically, Rong et al. (2025) demonstrated that features such as the integration of diverse services, inter-product synergy, and centralized data management—by increasing switching costs and enhancing a unified user experience—influence the ability of platforms to create sustainable dependence and stabilize their competitive position in multi-sided markets.
Based on the research findings, the following recommendations are proposed:

Strengthening positive network effects alongside managing reverse effects: Utilize loyalty mechanisms, quality ranking, and supply-demand balancing to prevent value degradation caused by network congestion.
Transforming governance transparency into a competitive advantage: Publicly declare transparent commission rules, fair pricing, and dispute resolution procedures, and institutionalize adherence to these standards.

Abstract The present study aims to design a competitive model for streaming platforms, specifically subscription-based video and audio services, with an emphasis on the future of media management. In terms of objective, the research is applied, and in terms of implementation, it is mixed-methods (qualitative-quantitative) with a sequential exploratory design. The qualitative population consists of 15 experts in media management in Iran. The quantitative population includes 378 active users of streaming services in Iran (Filimo, Namava, Shadava, and Beeptunes), and the sampling method used in this study was convenience sampling. The data collection instruments were semi-structured interviews and questionnaires. For data analysis, coding was used in the qualitative section, including three stages of basic, organizing, and overarching themes, supported by MAXQDA software. In the quantitative section, structural equation modeling with the partial least squares approach (PLS-SEM) was employed. The findings showed that three dominant competitive models include local exclusive content production, bundling with mobile operators, and a hybrid advertising-subscription model. The phenomenon of multi-homing was observed in more than three-quarters of users and showed a positive and significant correlation with churn rate. The PLS results indicated that bundling with operators has the greatest effect on reducing churn. The qualitative analysis identified seven main categories. The most likely future scenarios are platform consolidation and alliances, or the stabilization of existing platforms. It is concluded that media managers should adopt a combination of retention strategies and prepare themselves for managing integrated and large-scale platforms.
Introduction
The rapid growth of internet communication technologies has transformed the traditional structure of various industries, including media. In this context, subscription-based video and audio streaming services, by offering on-demand and personalized content, have changed audience consumption patterns from linear viewing to non-linear viewing (Aalami et al., 2025). This transformation has not only altered media consumption habits, but also posed a serious challenge to traditional business models based on television advertising and linear broadcasting. Platforms such as Netflix, Amazon Prime, and Disney Plus globally, and Filimo, Namava, Shadava, and Beeptunes in Iran, are examples of this paradigm shift. In this new model, users pay a monthly or annual fee to access a large content library, and platforms, instead of generating momentary ad-based revenue, seek stable and predictable income streams through subscriptions (Koul & Suresh Ambekar, 2020). However, this very feature, namely the ease of canceling subscriptions and the low cost of switching between platforms, has confronted media managers with a new strategic challenge: churn rate.
From an academic perspective, the literature on media management and platform economics in Iran requires localized models that reflect the unique characteristics of the domestic market, including the role of mobile operators as gateways for payment and distribution, the high prevalence of VPNs as a hidden competitor, and centralized regulation by SATRA. International studies, such as Tang and Wei (2023), have shown that media management strategies in Western and Eastern contexts differ due to cultural and regulatory differences; Netflix emphasizes global content production and simultaneous release across countries, while Chinese platforms such as Tencent Video focus on local content and adaptation to domestic policy. Therefore, the main research question is: How can a competitive model for streaming platforms, specifically subscription-based video and audio services, be designed with an emphasis on the future of media management?
Theoretical Framework
Streaming Platforms and Subscription-Based Services
Streaming platforms refer to digital environments that provide video and audio content directly via the internet, bypassing traditional broadcasting networks (cable, satellite). By leveraging subscription business models, these platforms have successfully transformed media consumption patterns from “linear viewing” to “on-demand viewing” (Steffiani & Irwansyah, 2021).
The Evolution of Media Management in the Platform Era
The emergence of global streaming platforms has shifted media management from the traditional model of “linear broadcasting and content scheduling” toward “algorithmic ecosystem management and audience engagement” (Khalafi et al., 2019). In this new landscape, media managers must grapple with four primary challenges: changing audience consumption habits (shifting from TV channels to on-demand platforms), competing with cross-border giants, the need for massive investment in exclusive content, and the integration of data-driven marketing strategies (Pandey et al., 2020).
Sarbakhsh et al. (2025) conducted research titled “Explaining the Content of Popular Animations on Streaming Media (A Study of Netflix, Amazon Prime, and Disney+ Works).” Their findings indicated that most Netflix animations center on female protagonists or women, often progressing without reliance on male characters. Amazon Prime productions continue to focus on older high-audience content within the themes of adolescence and maturity, while the newcomer Disney+, relying on the productions of its parent company (Disney), offers fragmented content in the form of spin-offs.
Cheng et al. (2025) conducted a study titled “Advanced Customer Churn Prediction for a Music Streaming Service via Enhanced Deep Learning.” The results showed that user behavioral characteristics (such as decreased engagement and changes in listening patterns) and user-experience-related features—by influencing loyalty indicators and perceived satisfaction—significantly impact consumers’ churn intention (service abandonment) in online streaming environments.
Research Methodology
In terms of its objective, this research is applied, and in terms of its execution method, it is mixed-methods (qualitative-quantitative) using a sequential exploratory design. The qualitative statistical population includes 15 experts in the field of media management in Iran. The quantitative population consists of 378 active users of streaming services in Iran (Filimo, Namava, Shadava, and Beeptunes), selected through convenience sampling. The research data collection tools include semi-structured interviews and questionnaires. Data analysis was conducted using coding (comprising three stages: basic, organizing, and overarching themes) with MAXQDA software in the qualitative section, and structural equation modeling with a partial least squares approach (PLS-SEM) in the quantitative section.
Research Methodology
The research method, in terms of its objective, is applied. In terms of execution, it is a mixed-methods (qualitative-quantitative) approach with a sequential exploratory design. The qualitative population includes 15 experts in the field of media management in Iran. The quantitative population comprises 378 active users of streaming services in Iran (Filimo, Namava, Shadava, Beeptunes), and the sampling method used was convenience sampling. The research data collection instruments were semi-structured interviews and questionnaires.
Research Findings
Data analysis was performed using coding (including three stages: basic, organizing, and overarching themes) with MAXQDA software in the qualitative section. In the quantitative section, structural equation modeling with the partial least squares (PLS-SEM) approach was utilized. The findings revealed three dominant competitive models: Production of exclusive local content, Bundling with mobile operators, A hybrid model of advertising and subscription.
The phenomenon of multi-homing was observed in over three-quarters of users and showed a significant positive correlation with churn rate. The PLS modeling results indicated that bundling with operators has the greatest impact on reducing churn. The qualitative analysis identified seven main categories. The most probable future scenarios involve the merger and alliance of platforms or the consolidation of existing platforms.
It is concluded that media managers should employ a combination of retention strategies and prepare themselves for managing integrated and large-scale platforms.
Conclusion
The present study was conducted with the objective of designing a competitive model for streaming platforms (subscription-based video and audio services) with an emphasis on the future of media management. The results of this research are consistent with those of Sarbakhsh et al. (2025), Cheng et al. (2025), Wu (2025), Benesbordi & Khalili (2024), Mohammadi et al. (2024), and Yahya Zadeh et al. (2023).
Specifically, Sarbakhsh et al. (2025) demonstrated that the majority of Netflix animations center on female protagonists or women, often progressing without reliance on male characters. Amazon Prime’s productions continue to focus on previously popular content within the themes of adolescence and maturity, while the newcomer Disney+—relying on the productions of its parent company, Disney—offers fragmented content in the form of spin-offs.
Based on the findings, the following recommendations are proposed:
1. Strategic Bundling: Establishing long-term exclusive contracts with mobile operators to reduce payment friction.
2. Data-Driven Customization: Investing in recommendation systems tailored to indigenous behavioral data.

Abstract The present study aims to develop a model of the impact of artificial intelligence recommender systems on online impulse buying, with the mediating role of emotional arousal and the moderating role of self-regulation. In terms of purpose, this research is applied-developmental; in terms of implementation, it is a mixed-methods study (qualitative–quantitative); and in terms of nature, it follows a sequential exploratory design.In the qualitative phase, the statistical population consisted of 18 online shoppers, who were selected through purposeful sampling using a snowball strategy. In the quantitative phase, the statistical population included 378 internet users residing in Tehran, who were selected through purposive convenience sampling.Data collection was carried out through semi-structured interviews in the qualitative phase and through a questionnaire in the quantitative phase. For analyzing the qualitative data, the grounded theory method and MAXQDA 2024 software were used, while SPSS and SmartPLS 4 were employed for the quantitative analysis.The qualitative findings revealed 25 concepts and 6 main categories. Among these, perceived urgency and emotional personalization showed the highest frequency in participants’ impulse buying experiences. The quantitative results indicated that perceived urgency has a positive and significant effect on AI recommender systems. Furthermore, the three variables of perceived urgency, emotional personalization, and surprising novelty had a positive and significant effect on arousal. Arousal, in turn, had a positive and significant effect on impulse buying.The findings also showed that arousal plays an important mediating role in the relationship between perceived urgency, emotional personalization, and surprising novelty and impulse buying. Overall, recommender systems primarily generate positive arousal through creating a sense of urgency and emotional personalization, which in turn leads to impulse buying, while high self-regulation plays a protective role

Abstract The aim of this study is to present a model of factors affecting investors' intention to participate in crowdfunding projects and is mixed in terms of methodology. In the qualitative part, data were collected through interviews with 14 experts and specialists in the field under study and analyzed using the content analysis method and ATLAS.ti software, which resulted in the extraction of 14 main themes and 46 sub-themes. Next, in the quantitative part, by designing a questionnaire and collecting 200 samples of active investors, the proposed model was tested using structural equation modeling using Smart Pls software. The research findings showed that all identified factors, including motivation and desire, trust, risk perception, familiarity and recognition, altruism, financial and information resources available, shared values, network size, innovation and quality of the project, rate of return, geographical location, expertise and experience of the project owners, and product or service characteristics, have a positive and significant effect on investing in crowdfunding. The results also indicate that investor behavior in this area is influenced by a combination of economic, social, and psychological factors and is not limited to financial dimensions. Finally, the conceptual framework presented in this study can be used as a practical basis for improving the performance of crowdfunding platforms, enhancing investors' decision-making processes, and increasing the success of entrepreneurial projects.

Abstract Abstract The present study was conducted with the aim of developing and validating an entrepreneurial marketing model with a strategic approach to technological innovation in startup companies. In terms of purpose, it is an applicable-developmental research, and in terms of methodology, it is mixed with a sequential exploratory design implemented in two qualitative and quantitative parts. In the qualitative part, the population included marketing, entrepreneurship, and startup managers who were selected based on the purposive sampling method. In the nineteenth interview, the researcher encountered repetition of concepts and conducted two supplementary interviews to prevent false saturation; finally, 21 people participated in this stage. In the quantitative part, the statistical population included startup managers and experts, and the sample size was determined as 130 people using the Cohen power analysis method and simple random sampling was performed. The data collection tool was a semi-structured interview and a researcher-made questionnaire. Qualitative data analysis was conducted using the Strauss and Corbin data-driven method in three coding stages, and the results were presented in the form of a paradigmatic model. The findings showed that causal conditions (founders’ opportunity-driven motivation, competitive pressure in the innovation ecosystem, inadequacies of traditional marketing models, and startup technological capacities) affect the pivotal phenomenon of entrepreneurial marketing. The pivotal phenomenon, contextual conditions (flexible organizational structure and innovative organizational culture), and intervening conditions (institutional and infrastructural barriers of the innovation ecosystem) affect strategies and actions (technological innovation strategy). Based on these results, an appropriate policymaking approach should focus on strengthening institutional infrastructure, targeted support for technological innovation, and creating facilitating mechanisms for the development of entrepreneurial marketing at the national level to enable the creation of sustainable competitive advantage and scalability of startups. Introduction As competitive environments become more complex, startups are forced to go beyond relying solely on technology or business model to achieve sustainable competitive advantage and require approaches that simultaneously cover market understanding, customer engagement, and strategic agility (Pangilinan et al., 2025; Hong et al., 2024). In this regard, recent management literature suggests the formation of convergence between entrepreneurial marketing, technological innovation, and a strategic approach in the process of organizational value creation (Crick et al., 2025). However, most studies have examined each of these concepts independently and a coherent framework has not been provided to explain their interaction in the context of startups. Entrepreneurial marketing, as an opportunity-oriented, innovative and proactive approach, elevates marketing from a mere promotional function to a process for discovering and exploiting market opportunities (Morris et al., 2024; Javid et al., 2025). In contrast, technological innovation, focusing on the development of new products, services and processes, is considered the main driver of growth and competitiveness of organizations (Mokhtari et al., 2023; Li & Zhang, 2024). The connection between the two will be effective when, in the form of a strategic approach, it guides the organization's long-term orientation in resource allocation and market-oriented decisions (Barney, 2024). At the global and national levels, digital transformations and the expansion of the digital economy have made technological entrepreneurship one of the main engines of economic growth and innovation (Sun & Lee, 2025; Kumar et al., 2025). In Iran as well, despite the quantitative growth of the startup ecosystem and the improvement of its global position, the lack of integrated theoretical frameworks to explain the mechanisms of startup growth and sustainability is still evident (Heydarzadeh et al., 2021 Eghbal; Moghaddam et al., 2023). A review of the literature shows that entrepreneurial marketing, technological innovation, and strategic approach have often been examined at separate analytical levels, and their synergistic role in the formation of sustainable competitive advantage has received less attention (Ezanloo et al., 2022; Udekwe & Iwu, 2025). Accordingly, the present study answers the fundamental question: how does the entrepreneurial marketing model with the strategic approach of technological innovation work in startup companies and how valid is it? Theoretical Framework - Entrepreneurial Marketing The concept of entrepreneurial marketing was first proposed in 1982 during a scientific conference at the University of Illinois at Chicago, with the support of the International Council of Small Business and the American Marketing Association, and is known as the starting point of the systematic link between entrepreneurship and marketing (Deku et al., 2023). - Technological Innovation Technological innovation, as one of the main drivers of economic development and the evolution of business models, has a central position in the literature on innovation management and technological entrepreneurship. This concept refers to the application of new or improved technologies in the development of products, processes, services or business models that lead to the creation of new value for the organization and customers (Akhlaghi et al., 2024). - Startup companies Innovative startup companies are new and agile enterprises that rely on innovation to create value, respond quickly to market changes, and achieve sustainable competitive advantage (Mahmoudi Niloo et al., 2023). These companies are usually formed based on a new idea and a technology-based business model and have a flexible structure, multi-skilled teams and a risk-taking culture. Their high ability to generate, absorb, and apply new ideas, especially in areas such as digital product development, technology-based platforms, customer experience innovation, and new ways of interacting with the market, is one of the distinctive features of these firms (Kahrai & Shivaei, 2025(. Research Methodology This research is of an applicable-developmental and non-experimental type with a survey-cross-sectional design, conducted with a mixed exploratory approach. The qualitative part was conducted with the participation of theoretical and empirical experts and 21 interviews were conducted until theoretical saturation was reached. In the quantitative part, the statistical population included managers and owners of startup businesses, and the sample size was estimated to be 130 people using Cohen's power analysis and G*Power software. The qualitative part of the research was conducted with qualitative data analysis and validation of the paradigm model using the partial least squares method in SmartPLS software. Research findings The paradigmatic model of the research shows that causal conditions, by shaping the central phenomenon, create an explanatory chain that leads to strategies in interaction with contextual and intervening conditions. In this framework, opportunity-based motivation, competitive pressure, traditional marketing inadequacy, and technological capacities strengthen startups’ tendency toward entrepreneurial marketing. The realization of this phenomenon leads to a technological innovation strategy in the presence of a flexible structure and innovative culture, although institutional barriers can weaken this path. Accordingly, the policy orientation emphasizes reducing interventionist constraints and strengthening institutional infrastructures with the aim of supporting technological innovation and developing entrepreneurial marketing to achieve sustainable competitive advantage and scalability of startups. Discussion and Conclusion In the dimension of causal conditions, the findings show that entrepreneurial marketing in startup companies is formed by the simultaneous presence of four main components: opportunity-based motivation of founders, competitive pressure of the innovation ecosystem, inefficiency of traditional marketing models, and available technological capacities. This result, in contrast to studies such as Pangilinan et al. (2025) that have addressed the role of environmental pressures or entrepreneurial mindsets in isolation, suggests that the activation of entrepreneurial marketing is the result of the simultaneous interaction of individual, technological, and institutional forces, rather than the influence of an independent factor. The central phenomenon of the research, namely entrepreneurial marketing, was explained as an institutional phenomenon and the dominant logic of action in startups. This phenomenon is formed in a dynamic interaction with the organizational structure and institutional environment and goes beyond a set of marketing tactics or market-oriented behaviors. This explanation covers the gap in studies such as Samara & Galdolage (2024), whose main focus is on performance outcomes and has paid less attention to the institutional and contextual layers of the formation of this phenomenon. In the context dimension, flexible organizational structure and innovative organizational culture were identified as the main components. The findings show that these factors play an “active enabler” role in startups and pave the way for the transformation of technological ideas into market-oriented solutions. This perception, compared to studies such as Bafghi et al. (2024) and Mokhtari et al. (2023) that have analyzed structure and culture mainly as organizational constraints, indicates a redefinition of the role of these components in the context of start-ups. In contrast, intervening conditions, including institutional and infrastructural barriers of the innovation ecosystem, play a decisive role in the intensity and direction of the impact of the pivotal phenomenon on strategies. The results show that the lack of institutional support, weak technological infrastructure, and policy incoherence can undermine the process of transforming entrepreneurial marketing into effective strategies, even in the presence of high motivation and technological capacity. This finding, in comparison to studies such as Sun & Lee (2025) and Khan et al. (2025) that have marginalized these factors, highlights the importance of the institutional context as a central component of the model's explanatory logic and has clear local implications for the Iranian startup ecosystem. The strategies and actions identified in the study are explained in the form of a technological innovation strategy that is the result of the convergence of the central phenomenon with causal, contextual, and intervening conditions. This result has deeper theoretical coherence compared to studies such as Payandeh & Ansari Moghadam (2024) that have analyzed innovation and marketing in two relatively separate paths. In terms of consequences, the results show that the causal-strategic chain of the model leads to the creation of sustainable competitive advantage and the possibility of scalability. These consequences go beyond short-term performance improvements and are directly aligned with the logic of startup survival and growth in uncertain environments. This finding provides a broader analytical horizon compared to studies such as Giti Nejad & Hassan Pour ghroghchi (2024) that have limited the consequences of entrepreneurial marketing mainly to financial or behavioral indicators.

Abstract Abstract The main goal of this study is to examine how organizations can use the experience of implementing pioneering projects to create a systematic ability to manage open innovation projects. The innovation process and then their development and commercialization have in the past been dependent on internal organizational intellectual resources. Today, the open innovation paradigm invites companies to use external ideas and technologies in their business and allows others to benefit from their innovative ideas. In the present study, the case study is the Iranian Electronics Industries Organization, which operates in the field of open innovation. In other words, in the past, it has moved from a closed innovation mode to an open innovation mode through activities. In this study, the impact of open innovation on the field of project knowledge management will be examined, with an emphasis on aspects of project risk management, project time management, project human resource management, and project relationship management. In order to collect information from members of the statistical community, including organization experts in the field related to innovation management, 15 people were purposefully selected and a researcher-made questionnaire was used. The resulting data were structurally analyzed using the MiqMaq software. According to the effective and effected plan in the structural analysis method, the variables of shortening product development time, enriching project evaluations with different aspects, inefficiency in production and distribution, misuse of the organization's intellectual and physical assets, and coordination problems were identified as strategic research variables that affect slower product development, faster market entry, and risk diversification as research outputs. Introduction Rapid technological change, increasing innovation costs, increasing competition in introducing new products and services, and shortening technology life cycles have led to an increased need for organizations to interact with their environment and stakeholders by opening up organizational boundaries to exchange innovative ideas (Khabaz et al., 2024). Henry Chesbro defines open innovation as follows: “Open innovation is a model based on the assumption that if an organization seeks to improve its technology level, it can and should use external technological ideas as well as internal ideas and use a variety of internal and external routes to the market (Bertello et al., 2024). “Closed innovation is the opposite of open innovation and considers success to depend on exercising control over the innovation process (Kanan et al., 2023). In closed innovation, all innovation activities are carried out within the company's boundaries and exclusively with internal resources (Ríos et al., 2024). However, due to the limited internal resources and the complexity of technology, closed innovation exposes the organization to numerous risks (Felin & Zenger, 2014). This study attempts to present a systematic structure for managing open innovation projects, and for this purpose, a four-stage process including closed mode, open drive, leading project, and project to the organization will be used. Given that the Iranian Electronics Industries Organization, as the research case, has had extensive activities regarding the decision-making requirements for communicating with its external environment and has communicated with the external environment to receive resources and information, the four-stage open innovation process will begin with the third stage, namely the leading project. For this purpose, the company's experiences in the two stages of closed mode and open drive that are already available will be used. The research project in question is innovation in the knowledge domain of project management (project communication management, project human resource management, project risk management, project time management). Accordingly, the research question is: how does open innovation affect the knowledge domain of project management? Theoretical foundations Open innovation Open innovation, as a key driver for organizational change, represents an efficient method for knowledge transfer and innovation at the organizational level and a necessary process for exploring the aforementioned opportunity by moving from closed to open systems and requires the development of organizational capabilities through specific processes (Andriyani et al., 2024). To ensure joint efforts for product development processes, the organization chooses co-creation, which can be examined from three perspectives (Wlazlak et al., 2018): (1) external innovation, (2) inside-out innovation, and (3) a hybrid approach to innovation. The relationship of these approaches can be understood through the creation of a knowledge base. The organization pursues a strategy that engages stakeholders to gain knowledge (Wlazlak et al., 2018). By using open innovation, the organization is moving towards shared products, shifting from individual to collective efforts to improve performance, and addressing potential risks associated with product development processes (Chang, 2019). Research Background Rezaei Sadrabadi et al. (2025) in their research entitled “Investigating the Effect of Open Enablers on the Agility of Selected Small and Medium-sized Enterprises in Yazd Industrial Park” have examined the role of open innovation, social capital, collaborative knowledge creation, and cooperation with foreign partners to increase agility in today's turbulent world, and finally, they have presented a new model for applying open agility enablers in selected small and medium-sized enterprises in Yazd Industrial Park. Khabaz et al. (2024) in their research entitled “Providing Effective Innovative Strategies in the Development of the Cosmetics and Health Products Industry with an Emphasis on International Entrepreneurship”, considering the importance of adopting new innovation strategies at the organizational level and moving away from the closed innovator, they have examined the strategies of aggressive innovation, technology absorption, pioneering innovator, and risk-taking innovator using thematic analysis and decomposition method. The results of their analysis show that innovative strategies of technology absorption will be of higher priority and risk-taking strategies will be of lower priority for an organization. Andriyani et al. (2024) in their study titled "Designing an Adaptive Innovation Model: Integrating Agile and Open Innovation in Regional Innovation", examined the open innovation framework from the perspective of three key organizational capabilities of knowledge absorption, sharing, and creation to enable efficient open innovation as key dimensions. The results of their study indicate that a company's open innovation capability can be defined as a dynamic ability to manage the knowledge base using input and output information flows and to transform internal and external knowledge and ideas into new products, services, processes, structures, and business solutions. Kanan et al. (2023) in their research entitled "Identifying the Components of the Open Innovation Maturity Model in Iranian Defense Industries Based on the Metasynthesis Method", used the metasynthesis method to identify key dimensions and components based on the targeted use of knowledge flows, in the form of ideas, science, or technology, in order to create value. Bauj Khushmian et al. (2022) in their research entitled "Presenting a Basic and Strategic Innovation Model in Petrochemical Design and Manufacturing Companies", presented a hybrid innovation model using a mixed research method and emphasized components such as revolutionary technologies, market innovation, innovation in human resource development and planning, the component of the birth of new industries, innovation in organizational processes and organizational structure, product innovation, and operational capability. Research Methodology The present research is of the applicable research type based on its purpose; and the type of research in terms of data collection is descriptive and survey-type. Also, in terms of method, the present study is a narrative study using event structure analysis, which is a network consisting of closed-mode, open-drive, lead project, and project-to-organization stages. The research stages include observing and collecting documents, constructing a narrative, semi-structured credit interviews, and a questionnaire, and analyzing the event structure. The sample members are 15 organization experts in the field related to innovation management and with more than 10 years of work experience. Structural analysis also seeks to determine key variables and the relationships between them, the steps of which include extracting variables, determining relationships between variables, and identifying key variables. Research findings The key results of the study indicate that based on the method of identifying strategic variables in the effective and effected map, with the organization focusing on implementing open innovation, these activities lead to reducing organizational costs, improving knowledge management and organizational culture, and filling internal knowledge gaps by collaborating with outsiders in the field of project management knowledge. The classification of variables based on the structural analysis method is: • Dichotomous variables: Shortening the product development time is the only dichotomous variable identified, which is the strategic variable. • Influential variables: Improving the organization's knowledge management, collaborating with customers and benefiting from their opinions, knowledge and information available in the organization, lack of coordination between partners' behavior and their interests, conflicting goals of open innovation, innovation during the process, increasing job satisfaction, choosing the wrong partner, leaving knowledge workers and joining a partner, inefficient allocation of resources, limiting the development of internal skills, filling internal knowledge gaps with collaboration and absorbing information from outside, lack of clear information about the market and customer needs, and improving culture. Planners are unable to apply changes to influential variables (environmental variables). • Independent variables: Coordination problems, misuse of the organization's intellectual and physical assets, better forecasting of developments, inefficiencies in production and distribution, complexities of cooperation, and enriching project assessments with different aspects. Independent variables have little influence and cannot be strategic. • Dependent variables: faster market entry, risk diversification, and slower product development Conclusion From the perspective of the general dimension of project management knowledge, the results of the present study show that open innovation processes, especially with inter-organizational collaborations and the use of external resources and knowledge, significantly affect the management of risk, time, communication, and human resources of the project. These findings are in line with the results of Audretsch & Belitski (2023). From the perspective of the key dimension of dichotomous variables, the findings presented by Sikandar & Abdul Kohar (2022) show that shortening the product development time can be the beating heart and key connecting point of the open innovation system, or in other words, the same dichotomous variable that is consistent with the results of the present study. From the perspective of the key dimension of influential variables, the findings presented by Almeida (2024) warn that failure to properly manage open innovation processes can lead to problems such as the departure of knowledge workers and limitations in the development of internal skills, which is also clearly stated in the present study. From the perspective of the key dimension of independent variables, according to the study results of Livieratos et al. (2022), choosing appropriate strategic partners and using external knowledge have an impact on improving product development time, which is also consistent with the findings of this study. On the other hand, existing analyses show that if open innovation is not implemented properly, it may lead to problems such as conflicting goals, increased complexity, and reduced productivity, which is similar to the result of Lazarenko (2019). From the perspective of the dependent variable, the results of the study conducted by Farjam et al. (2023) indicate that open innovation can lead to reduced project risks and increased speed to market. The results of the research indicate that if the organization communicates with the external environment to carry out its projects, the following set of scientific recommendations are provided to the organization in the field of risk management, human resources, time, and project communication: • Integrated management of innovation goals: Although open innovation and communication with the environment and external resources such as human, intellectual, and physical resources shorten the product development time, the organization must be careful in selecting the right organization to jointly implement its innovative activities. The discrepancy between the organization's innovation goals with each other causes problems in creating the necessary interdepartmental coordination and will not only shorten the product development time and rapid market entry and reduce risk, but will also increase costs, inefficient allocation of resources, and even stakeholder dissatisfaction. • Integrated management of the partner network: If the organization carries out its activities in cooperation with external factors, the evaluations of a project will be richer in various aspects. At this stage, choosing the right partner for the organization to implement its activities is important. If this choice is not correct, there will be no change in the knowledge and information available in the organization and the organization's internal knowledge gaps will not be filled properly. Also, evaluations of open innovation projects will not be done properly.

Abstract Abstract The objective of this research is to investigate the mindsets of experts regarding the application of blockchain technology in government organizations using Q methodology. This study is applicable in its objective, and employs a mixed-methods approach for its execution. The statistical population of the research consists of managers in government organizations. Using purposive sampling and based on the principle of theoretical sufficiency, 19 individuals were selected as the statistical sample. With respect to the research approach, the qualitative phase initially involved 19 interviews to establish discourse; and the sample, Q-options, and finally the Q-set were derived through their perspectives and opinions. Subsequently, in the quantitative phase, the data obtained from the qualitative phase were analyzed and examined using SPSS. The findings indicate that transparency, increased productivity, enhanced agility, corruption prevention, elevated trust levels, improved electronic voting, secure identity management, and improved innovation are the eight mindsets of managers concerning blockchain technology in government organizations. Introduction The contemporary era of digitalization is placing significant pressure on administrative sectors, both in the private and public domains, to initiate and advance their digital transformation agendas (Hammad et al., 2023). Blockchain technology is one such technology that can be utilized within administrative systems (Cagigas et al., 2022; Seyedsayamdost & Vanderwal, 2020; Tandon et al., 2021). Some of the areas where blockchain is being tested for government services include: cryptocurrency/payments, land registration, identity management, document authentication, supply chain tracking, healthcare, education, company registration, data management, auditing, energy markets, taxation, voting, and the management of legal entities (Muafiq, 2024; Tan et al., 2022). The increasing adoption of blockchain in public sectors indicates that this technology possesses a broader capacity to enhance trust, accountability, and operational efficiency in governance functions. Particularly, the decentralized and immutable nature of blockchain offers a compelling solution to the long-standing challenges in these domains in areas such as digital identity management, adherence to requirements and regulations, and the provision of public services (Chen et al., 2026). It is claimed that blockchain will profoundly transform the process of producing and delivering public services (Rana et al., 2022). With key features such as decentralization, persistence, transparency, privacy and security, accuracy, and notably, cost and network savings, this technology significantly enhances the value in accessing data and minimizing intermediation in digital processes (Dowlatabadi, 2025; Hammad et al., 2023; Jamali, 2023; Rana et al., 2022). Furthermore, blockchain contributes to improving process efficiency through automation with smart contracts. These self-executing contracts can streamline administrative tasks, reducing the time and costs associated with manual processes. Moreover, the decentralized nature of blockchain technology enhances trust among participants by eliminating the need for intermediaries and providing a secure and transparent platform for transactions. Integrating blockchain into administrative processes can lead to increased trust through information transparency, predictability, and efficiency. By leveraging blockchain’s capabilities such as data aggregation through smart contracts and ensuring data security via cryptographic algorithms, administrative processes can be simplified and become a more reliable tool (Muafiq, 2024). Therefore, considering the perspectives of experts, this research seeks to answer the question: What are the mindsets of experts in the application of blockchain technology in government organizations, using Q methodology? Theoretical Framework Blockchain in Government Organizations Blockchain is a combination of existing technologies such as distributed ledgers, cryptography, hashing, and consensus protocols. All transaction records in a blockchain are stored in a chain of data packets (blocks) and distributed across a peer-to-peer network. All nodes in the network possess a copy of the blocks (Batubara & Janssen, 2018). This technology can resolve or mitigate issues related to transparency, trust, public policies, and service quality. The adoption, implementation, or integration of blockchain technologies by governments and public institutions can be beneficial for all stakeholders. For instance, blockchain can help optimize data management among public service provider organizations, not only in terms of interoperability, trust, and transparency; but also in terms of data accuracy, coordination, traceability, and integrity. It is also suggested that this technology can aid in preserving existing organizational and management structures. Therefore, blockchain is presented as a solution for governments to address significant public sector challenges such as transparency and fairness in processes and procedures (Fosso et al., 2024). Chen et al. (2026), in their research, conducted a comprehensive review of blockchain applications in government, demonstrating that blockchain can play a transformative role by enhancing transparency, efficiency, and security in public services (e.g., healthcare, e-voting, and registration systems). They also identified driving forces and barriers to adoption through force field analysis and emphasized the need for interdisciplinary research and regulation/collaboration for successful implementation. Murano et al. (2026), through their research, found that despite blockchain’s capacity to enhance transparency, efficiency, and trust in public services, its adoption remains slow due to organizational and technical barriers. They identified specific public sector challenges, such as interoperability and a lack of technical expertise, through a systematic review and proposed tailored strategies for effective implementation. Research Methodology This research is applicable in terms of its objective, and was conducted using a mixed-methods approach. The statistical population of the research consists of managers in government organizations. Using purposive sampling and based on the principle of theoretical saturation, 19 individuals were selected as the statistical sample. With respect to the research approach, the qualitative phase initially involved 19 interviews to establish discourse. Research Findings A sample, a Q-sort, and finally a Q-set were obtained using the experts’ insights and opinions. In the quantitative phase of the research, the data obtained from the qualitative section were analyzed using SPSS. The findings indicate that transparency, increased productivity, enhanced agility, corruption prevention, improved trust levels, better e-voting, secure identity management, and improved innovation are the eight mental models of managers regarding blockchain technology in government organizations. Conclusion The present research was conducted with the aim of examining the mental models of experts in the application of blockchain technology in government organizations, using the Q methodology. The results of this research are aligned with the findings of the studies by Chen et al. (2026), Murano et al. (2026), Hammad et al. (2026), Mueller et al. (2026), Rubino et al. (2026), Sánchez-obando et al. (2025), Fosso et al. (2024), Akhmetbek & Špaček (2021), Sung & Park (2021), Brauner & Janissek-muniz (2020), Reddic et al. (2019), Navadkar et al. (2018), and Qian et al. (2017). Reddic et al. (2019) state that blockchain prevents the excessive concentration of power in the hands of a few, possesses a more transparent legal framework, and provides citizens with more information. This higher level of transparency allows citizens to monitor public transactions. They emphasized that with a greater degree of transparency and security, undesirable behaviors can be quickly identified and curbed. Based on the research results, the following suggestions are presented: To enhance and empower government organizations in achieving their objectives, it is recommended that managers pay special attention and consideration to blockchain technology. Blockchain can minimize the risk of using unreliable systems and provide rapid access to information for stakeholders, thereby improving the performance of public sector institutions.