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Journal of New Approaches in Management and Marketing is an open-access, double-blind, peer-reviewed publication published by the Research Center of Resource Management Studies and Knowledge-Based Business. 

JNAMM is a quarterly publication that publishes original research papers related to the journal's scope. This journal follows the Committee on Publication Ethics (COPE) and complies with the highest ethical standards by ethical laws. All submitted manuscripts are checked for similarity through SamimeNoor software to ensure their authenticity to be assured about its originality and then rigorously peer-reviewed by expert reviewers. (Read More...)


Main Features of the Journal:
  • Owner: Research Center for Management Studies and Knowledge-Based Business
  • Publication Frequency: Quarterly (The journal started quarterly publication from Spring 2024)
  • Article Types: Research and Review Articles
  • Language: Persian, with English Abstract
  • Peer Review: Double-blind
  • Specialization Areas: Marketing Management, Business, Entrepreneurship
  • Initial Review Time for Articles: 10 days
  • Publication Type: Electronic
  • Processing and Publication Fee: No
  • Start of Publication: October 2022
  • Access to Articles: Open Access
Original Article (Qualitative) Marketing Management

Digital technologies on the evolution of human resource management practices and its consequences on employee outcomes with a data-driven theory approach

Pages 1-20

https://doi.org/10.22034/jnamm.2025.559393.1208

Gholamreza Tizfahm Fard, MAHMOUD SAMADI, Sahar Molazeinali, Armin Rajabzadeh, sara dodangeh

Abstract Abstract The present study aimed to qualitatively analyze the impact of digital technologies on the transformation of human resource management practices and its consequences on employee outcomes. This applicable and qualitative study was designed with a data-based theory approach using MAXQDA software, and data was collected through semi-structured interviews with managers, human resource experts, and employees with experience interacting with digital technologies. Data analysis was conducted in three stages of open, axial, and selective coding. The findings showed that causal factors including technology-driven leadership, managerial support for innovation, and data-driven decision-making culture play a key role in facilitating human resource transformation. Contextual factors including organizational learning culture and employees' digital literacy level provide the necessary context for the successful implementation of digital processes, while limited financial resources, administrative rules, and employee resistance act as intervening factors. Strategies such as digital employee empowerment, cross-functional collaboration, and technological infrastructure development improve employee productivity, satisfaction, and commitment. The study provides a comprehensive theoretical-practical framework that organizations can use to effectively and sustainably implement human resource management practices using digital technologies. Introduction Technological developments in recent decades have transcended the traditional boundaries of organizations and shaped a new concept of the workplace and human resources. The emergence and spread of digital technologies such as artificial intelligence, big data, machine learning, the Internet of Things, digital platforms, smart human resource systems, and augmented reality have fundamentally transformed the structure and nature of human resource management (chepkemoi et al., 2025). In the past, human resource management focused more on administrative and executive processes such as recruitment, payroll, performance appraisal, and training; however, in the digital age, this field has become a strategic and technology-driven platform that aims to create added value through the use of data, technology and organizational intelligence (Chen et al., 2024). The transformation of HRM practices in the digital age is significantly influenced by gaps in digital technologies. Resistance to change is one of the main obstacles that many organizations face (Dabić et al., 2023). This resistance is often due to a lack of understanding or fear of the unknown and can hinder the adoption of new systems and processes. In addition, the digital skills gap among employees is a major challenge for organizations that intend to fully exploit digital tools in HRM. This lack of skills can lead to inefficiencies in recruitment, training and performance management processes (Puspita, 2024). Data security and privacy concerns are also major challenges in integrating digital technologies with HRM (Abdollahzadeh Namini et al., 2024). Organizations need to find effective solutions to protect sensitive employee information while implementing digital solutions. On the other hand, the lack of clear implementation strategies is another problem that organizations struggle with. The absence of a clear framework can lead to inefficient use of technology and missed opportunities to improve HRM processes (Dyakiv et al., 2024). Financial constraints also limit organizations’ ability to invest in digital technologies and training programs, exacerbating the challenges in modernizing HRM practices. In addition, cultural barriers play an important role in the successful adoption of digital technologies (Puspita et al., 2024). Organizational cultures that do not support innovation may become a barrier to digital transformation (Barišić et al., 2021). Consequently, although digital technologies offer valuable opportunities to improve HRM practices, gaps such as resistance to change, lack of digital skills, security concerns, lack of clear strategies, financial constraints, and cultural barriers need to be seriously addressed in order for digital transformation in HRM to be achieved effectively and sustainably (Fenech et al., 2019). Therefore, the research question is: what is the role of digital technologies on the transformation of HRM practices and its consequences on employee outcomes with a data-driven theory approach? Theoretical Framework Digital Technologies and the Transformation of Human Resource Management Practices As one of the key factors of organizational transformation, digital technologies play a prominent role in changing human resource management practices. These technologies include human resource automation systems, data analysis software, online training platforms, and digital communication tools that enable the implementation of human resource processes with greater speed, accuracy, and transparency (Bennet et al., 2021). The implementation of digital technologies enables traditional human resource processes such as recruitment, training, performance evaluation, and employee information management to be carried out automatically and intelligently. In addition to reducing human errors, the automation of these processes allows for accurate data analysis and monitoring, and managers can make their decisions based on real evidence and organizational data. This feature facilitates the transformation of traditional decision-making to a data-driven decision-making culture and increases the speed of the organization's response to environmental changes and employee needs (Blanka et al., 2022). Dowlatabadi (2025) studied “Analyzing the Impact of Digital Technologies on the Evolution of Human Resource Management Practices in the Digital Age”. The research method is applicable in terms of purpose and descriptive-survey in nature. The findings of the study show that digital technologies have an impact on the evolution of human resource management practices. Ramos et al., (2024) studied “Digital Transformation in Human Resources: A Comprehensive Bibliometric Analysis of Evolution”. This study conducted a systematic review of the literature using the methodology of Zupik and Chater (2015). This approach allows for tracking intellectual developments, identifying key contributors, and drawing conceptual frameworks in the field of digital transformation in the workplace, and as a result, provides a comprehensive overview of the subject. This research reveals key trends in the literature related to digital transformation and personnel management, identifies influential researchers, and outlines the intellectual structure of this field. Research Methodology This research is of an applicable type and qualitative in nature, with an exploratory-explanatory approach based on grounded theory. Its main goal is to identify and explain the relationships between digital technologies, the evolution of human resource management practices, and its consequences on employee outcomes. The statistical population of the research included managers, experts, and human resource employees of organizations that interact with digital human resource management systems. Purposive sampling was conducted to include individuals who have direct experience with digital technologies and new human resource management practices, and the number of participants reached 15 based on theoretical saturation. Data were collected through semi-structured interviews that included questions about employees' experience with digital technologies, human resource management practices, and their effects on employee performance, commitment, and satisfaction. This method allowed for free and detailed expression of views and was not limited to predetermined options. Data analysis was conducted using an open, axial, and selective coding process; first, the initial concepts were extracted, then the relationships between the main concepts and categories were identified, and finally the central phenomenon for the development of the theory was identified. To increase the validity and reliability of the data, the feedback of experts and participants was taken into account in verifying the results, and field notes were recorded accurately. Also, the use of qualitative analysis software such as MAXQDA helped to organize and systematically analyze the data. Research findings The research findings showed that digital technologies, by strengthening technology-driven leadership and data-driven decision-making, cause a significant transformation in human resource management practices. Organizational learning culture and employee digital literacy, as contextual factors, facilitate the successful implementation of digital processes, while structural limitations and employee resistance can play a deterrent role. Finally, digital empowerment strategies and the development of technological infrastructure lead to improved employee productivity, satisfaction, and commitment. Discussion and Conclusion The present study was designed to investigate the impact of digital technologies on the transformation of human resource management practices and its consequences on employee performance and satisfaction. This applicable and qualitative study was conducted using a grounded theory approach and MAXQDA software, and data was collected through semi-structured interviews with managers, human resource experts, and employees with experience interacting with digital technologies. The results show that technology-driven leadership, managerial support for innovation, and a culture of data-driven decision-making act as the main drivers of technology adoption and improvement of human resource processes. These factors motivate employees, increase technology adoption, and improve data-driven decision-making. The findings of the study are in line with the studies of Dowlatabadi (2025) and Gupta (2024); these studies also emphasize the vital role of management and support for innovation in facilitating the adoption of digital technologies and its direct impact on the success of digital transformation. Digital transformation and the integration of technology with HR processes form the core of this research and include the digitization of training, assessment, recruitment and automation of personnel processes. These findings are consistent with the studies of Ramos et al. (2024) and Nasiri et al. (2023), which show that digital transformation includes antecedents, processes and direct consequences on employee performance. Digitization of processes improves efficiency, reduces errors and increases accuracy in decision-making and creates significant added value for the organization. Contextual factors such as learning culture, organizational adaptability and the level of digital literacy of employees also play an effective role in the success of digital transformation. Organizations that have a learning and flexible culture accept digital changes more easily, and continuous training and support from colleagues reduce resistance to technology. These results are consistent with the studies of Goudarzi et al. (2023) and Puspita (2024) and show that developing digital skills and promoting a learning culture are critical prerequisites for the successful implementation of new technologies. However, intervening factors such as limited financial resources, administrative rules and regulations, and employee resistance can reduce the success of digital transformation. Budget constraints and lack of supportive policies slow down the implementation of digital processes; and employee resistance due to fear of job changes or reductions is a significant challenge. Smart management of these barriers by creating motivation, training, and organizational support is essential for the success of digital transformation, and the findings of Gupta (2024) are in line. Organizational strategies, including employee digital empowerment, cross-functional collaboration, and the development of technological infrastructure, provide the basis for the full exploitation of technologies. Implementing continuous training programs, creating joint technology and HR teams, and implementing intelligent decision-making systems increase the speed and accuracy of process execution, facilitate the adoption of new technologies, and improve employee experience. This is consistent with the findings of Gupta (2024) and Zisis & Polydoros (2024), which show that effective organizational strategies are a determining factor in the success of digital transformation. Finally, the consequences of transformation include increased productivity and speed of action, improved employee experience, and enhanced organizational satisfaction and commitment. Successful digitalization and the use of related strategies reduce the cost and time of processes, faster access to HR services, and increase employee motivation and belonging. The research findings confirm that integrating technology with HR practices creates significant added value, and, as in the studies of Nasiri et al. (2023) and Bagheri et al. (2023), digital transformation can have positive and sustainable effects on organizational performance and employee experience.

Original Article (Mixed) Entrepreneurship

Development and Validation of an Entrepreneurial Marketing Model with a Strategic Approach to Technological Innovation in Startup Companies

Pages 21-45

https://doi.org/10.22034/jnamm.2025.560823.1210

Bagher Bagherian Kasgari

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.

Original Article (Mixed) Other topics related to business management, entrepreneurship, and marketing

Analysis of the open innovation project management system in the organization

Pages 46-69

https://doi.org/10.22034/jnamm.2025.565370.1221

Mohammad Moradi, Aliakbar Hasani, Danial Bidgoli

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.

Original Article (Qualitative) Marketing and Brand Strategy

Analysis of factors affecting the prediction of future saffron prices on the Iranian Commodity Exchange

Pages 70-88

https://doi.org/10.22034/jnamm.2026.567709.1232

Souad Ramezani vanegah, Hamid Reza Mollaei, Amirhossein Taebi Noghondari

Abstract Abstract The aim of the present study is to analyze the factors affecting the forecast of future prices of saffron in the Iranian Commodity Exchange. This research is applicable in terms of its purpose, and post-event in terms of its nature. The statistical population includes 20 experts in the field of agricultural economics, commodity exchange managers, and agricultural derivatives market activists, selected using a purposive and snowball method, and this process continued until it reached theoretical saturation. The data collection tool is an interview and a questionnaire. The DEMETL method was used for analysis. The findings showed that variables such as the agricultural sector credit facility rate, exchange rate, inflation rate, export rate, and inventory are in the group of influential variables, while factors such as production rate, allocated subsidies, production costs, global demand, and customs laws are considered among the influential variables. In terms of prioritization, the importance of allocated subsidies and saffron production rate are of the highest importance; Saffron exports, inflation rate and exchange rate are of high importance; production costs and drought index are of medium importance, and temperature changes and producer price index are of lesser importance. Introduction Derivatives price evaluation in the Iranian Commodity Exchange is a subject that deals with the study and analysis of complex financial instruments known as derivatives. Derivatives are contracts whose value is derived from underlying assets such as commodities, stocks, currencies and interest rates (Kevin, 2024). In this regard, the Iranian Commodity Exchange, as one of the most important trading platforms in the country, provides the possibility of trading various derivatives such as futures contracts and options (Moradi et al., 2024). This is while the correct evaluation of the price of these derivatives plays a key role in risk management, improving market efficiency and increasing financial transparency (Fan & Sirignano, 2024). Extreme price fluctuations are a characteristic feature of the derivatives market, which can occur due to sudden changes in supply and demand, political and economic events, and global factors. These fluctuations make it very difficult to correctly assess the price of derivatives (Grodek-Szostak et al., 2019). In addition, in the derivatives market, several factors such as interest rates, exchange rates, commodity prices, and economic and political conditions affect pricing (Cheng et al., 2018). Uncertainty about the impact of these factors can lead to increased risk and reduced accuracy in pricing (Holzermann, 2022). In Iran, saffron, as a high-value-added commodity and a major contributor to non-oil exports, is of strategic importance in the country's agricultural economy. The launch of saffron futures on the Iran Commodity Exchange has been a step towards institutionalizing hedging instruments and discovering fair prices (Gholami Mehrabadi, 2014). However, the volatile behavior of saffron futures prices, influenced by exchange rate fluctuations, inflation, trade policy changes, and information asymmetry, has created a major challenge for analysts and policymakers. Previous studies have mainly attempted to explain saffron price behavior using statistical or econometric models such as GARCH, ARIMA, VER, and VACM, but these models are unable to represent the causal, feedback, and dynamic relationships between variables (Neufeld & Sester, 2022). On the other hand, existing studies have often focused on one or a few limited variables and have neglected a comprehensive and multidimensional approach to simultaneously analyze economic, policy, and behavioral effects. As a result, the need for an integrated framework that can model both the causal relationships between key variables and the behavioral dynamics of the market over time is seriously felt. Therefore, the main question of this research is: What are the factors affecting the prediction of saffron futures prices on the Iranian Commodity Exchange? Theoretical Framework Futures Markets Futures markets, as one of the important financial engineering tools, play a fundamental role in improving market efficiency and hedging risk (Raei & Saeedi, 2017). These markets allow economic actors to manage their risk against price fluctuations through standardized futures contracts. In countries like Iran, whose economies are faced with currency, inflation, and political shocks, the importance of derivatives is doubled, especially in the agricultural sector. Saffron, as a strategic product, is an example of a commodity whose price fluctuations have wide-ranging consequences on producers' income and export policies. (Gholami Mehrabadi, 2014). Gui (2025), examined stock market forecasting using a hybrid model and confirmed the superiority of hybrid models over single models in improving the accuracy of futures price forecasting. His results showed that using time series analysis alongside machine learning algorithms can increase the reliability of forecasts. Cohen (2024) also focused on consumption patterns in global markets, explaining the role of export policies and demand changes in determining the prices of agricultural commodities and concluded that changes in global demand, especially in emerging markets, are quickly reflected in futures prices.  Research Methodology This research is applicable in terms of purpose, and post-event in nature. The statistical population includes 20 experts in the field of agricultural economics, commodity exchange managers, and agricultural derivatives market activists, selected using a purposive and snowball method, and this process continued until theoretical saturation was reached. The data collection tool is an interview and a questionnaire. Research findings The DEMET method was used for analysis. The findings showed that variables such as agricultural credit facility rates, exchange rates, inflation rates, export rates and warehouse inventory are in the group of influential variables; while factors such as production rates, allocated subsidies, production costs, global demand, and customs laws are considered among the influential variables. In terms of prioritization, the importance of allocated subsidies and saffron production rates are of the highest importance; saffron exports, inflation rates and exchange rates are of high importance; production costs and drought index are of medium importance, and temperature changes and producer price index are of lesser importance. Conclusion The present study aimed to analyze the factors affecting the prediction of future saffron prices on the Iranian Commodity Exchange. The results of this study are consistent with the results of Gui (2025), Cohen (2024), Garg et al. (2023), Baamonde-Suárez et al. (2023). Bagheri & Doliskani (2023), Morales-Banuelos et al. (2022), Fengqian & Chao (2020), Miyamoto & Kubo (2022), Barakchian &Baghernejad (2022), Mahaverpour et al. (2021). Amiri et al. (2021), Miyamoto & Kubo (2021), Bernal-Penke et al. (2020), Rostami et al. (2019). Gholami Mehrabadi (2014), and Kozmina & Kuznetsova (2018). Comparing the findings with previous research reveals important similarities and differences. Globally, studies such as Cohen (2024) and Fengqian & Chao (2020) emphasize the impact of macro variables such as exchange rates and inflation on derivatives pricing, which is consistent with the high sensitivity of the saffron futures market in this study. However, these studies mainly focus on advanced markets with economic stability and have paid less attention to local factors such as subsidies or climatic conditions such as drought. The following suggestions were made based on the research results: - Specialized training of traders in nonlinear analysis: It is essential for commodity exchanges to hold workshops and training courses for traders, focusing on nonlinear analysis and advanced volatility. These trainings should include an introduction to nonlinear time series modeling methods, chaos detection tests, and their practical applications in derivatives trading. - Implementation of a price fluctuation alert system: Developing automated alert systems based on predictive models that issue automatic notifications to traders when prices cross predicted ranges can help manage risk and prevent losses from irrational behavior.

Original Article (Qualitative) Human resource management

Developing a human resource sustainability scenario with a foresight approach

Pages 89-109

https://doi.org/10.22034/jnamm.2026.567498.1231

Hamed Hadian, Yosef Ahmadi, Alireza Fathizadeh

Abstract Abstract The present study aims to develop a human resource sustainability scenario with a foresight approach. The research method is qualitative and applicable. The statistical population of the study includes 18 academic experts and human resource managers of government departments in Sirjan, selected through purposive sampling. The data collection tool is a semi-structured interview. The MICMAC and Wizard Scenario methods were used to analyze the findings. The results showed that among the eight components of "changes in the labor market, changes in technology, changes in employee values, changes in organizational structure, changes in employee expectations, psychological factors, economic factors, organizational culture and work environment", and changes in employee values ​​have the most impact and organizational culture and work environment have the most impact than other factors. Also, a total of eight scenarios with high compatibility for the future of human resource sustainability in the government sector are ahead. However, two scenarios of human resource excellence and stability (optimal and ideal scenario) and successful organizational transformation with a high standard (possible scenario, but with the risk of bureaucracy and forced persistence) have been introduced as the most important and likely paths to achieving goals, which have higher priority than others. Introduction Human resource is considered one of the important and fundamental resources of organizations, and organizations need specialized and committed human resources to achieve their goals (Babaei Meybodi & Alirezaei, 2020). Today, retaining competent employees is the main problem of government organizations; a problem that, if solved, will lead to greater profitability and effectiveness in the organization. On the other hand, losing employees is costly for the organization. It should also be noted that most organizations spend significant amounts of money every year to attract and retain their employees, while each organization is able to attract a number of other active employees of the organizations if appropriate methods are adopted, in addition to maintaining existing human resources. Undoubtedly, the current world is a world of organizations and the custodians of these organizations are humans; who breathe life into the body of the organization, set it in motion, and manage it (Roth et al., 2022). Research shows that human resource retention is influenced by many factors such as career development opportunities, work stress, financial and non-financial rewards, independence and autonomy, flexibility in work schedules, work-life balance, appropriateness of job roles and responsibilities, creating more responsible teams, ensuring a balance of human resource expectations with realistic job characteristics, social capital and support, human resource management practices and leadership (Matongolo et al., 2018; Jadon & Upadhyay, 2017; Kossivi & Kalgora, 2016). Today, retaining and maintaining human resources is the most difficult challenge for organizations in the public and private sectors. Human resource turnover in various fields is increasing rapidly, and the shortage of human resources in this sector in developing countries has been predicted by the World Health Organization to be 12.9 million people, which is a very high figure. Due to the shortage of skilled labor, employees expect more financial and non-financial benefits and are not willing to work under any conditions (Bharath et al., 2023). This research, using a foresight approach, is an attempt to predict and design scenarios for the sustainability of human resources, considering the upcoming social, economic, technological and organizational trends. The scientific contribution of the research is in the development of a theoretical and analytical framework that combines human resource management and futures studies, and from a scientific perspective, it can provide a strategic decision-making model in government human resources policies. On the other hand, its practical contribution to managers and planners of government organizations is in identifying key factors for retaining and motivating employees in the future horizons and helping to formulate effective recruitment and retention policies in Sirjan County. Therefore, an attempt is made to answer the question: how to formulate a human resource retention scenario with a foresight approach? Theoretical Framework Human Resource Retention Human resource retention, especially active and specialized human resources, is one of the main and priority goals of organizations. Retaining and maintaining human resources means creating and maintaining a suitable and balanced work environment for employees, encouraging them to continue working with the organization, and improving their job satisfaction. This process includes measures such as providing financial and non-financial benefits, professional advancement, providing training and development opportunities, promoting positive organizational interactions and a healthy work culture, and solving problems and creating an organizational environment that is appropriate to the needs of employees (Adibzadeh et al., 2023). Karami Moghaddam & Vishlaghi (2025) investigated the identification and explanation of legal and administrative factors affecting human resource retention using a mixed approach in government organizations. The results of the study indicate that a fair payment system in laws, the right to legal promotion and advancement, job security based on the law, determining salaries and benefits based on the approved and unified government table, legal protections in crisis situations, and equality and prohibition of legal discrimination were raised as the most important legal factors. Hadian et al. (2025) investigated the identification of drivers affecting the retention of human resources in the government and non-government sectors of Sirjan city. The research findings showed that the drivers affecting the retention of human resources in the public and private sectors include: changes in the labor market (intense competition for talent, emergence of a new generation of workers, hybrid work), changes in technology (automation and artificial intelligence, need for new skills), changes in employee values ​​(meaningfulness of work, personal development, meritocracy, work-life balance), changes in organizational structure (flat organizations, teamwork, flexibility in job roles), changes in employee expectations (soft skills development, social responsibility, transparency and fairness), psychological factors (mental health, motivation and job satisfaction, sense of belonging), economic factors (salaries and benefits, job security), organizational culture and work environment (effective and positive leadership, transparent and open communication, supportive and positive culture, diversity management, balance between organizational culture and individual culture, fairness and equality). Research Methodology The research method is qualitative and applicable. The statistical population of the study includes 18 academic experts and human resource managers of government departments in Sirjan who were selected through purposive sampling. The data collection tool is a semi-structured interview. Research findings The MICMAC and Wizard Scenario methods were used to analyze the findings. The results showed that among the eight components of "changes in the labor market, changes in technology, changes in employee values, changes in organizational structure, changes in employee expectations, psychological factors, economic factors, organizational culture and work environment", changes in employee values ​​have the most impact and organizational culture and work environment have the most impact than other factors. Also, a total of eight scenarios with high adaptability are ahead for the future of human resource sustainability in the government sector. However, two scenarios of human resource excellence and stability (optimal and ideal scenario) and successful organizational transformation with high standards (possible scenario, but with the risk of bureaucracy and forced persistence) have been introduced as the most important and likely paths to achieving goals, which have higher priority than others. Conclusion The present study was conducted with the aim of developing a human resource persistence scenario with a foresight approach. The results showed that a fair payment system in laws, the right to legal promotion and advancement, job security based on the law, determining salaries and benefits based on the approved and unified government table, legal protections in critical situations, and equality and prohibition of legal discrimination were raised as the most important legal factors. The results of this study are consistent with the results of Karami Moghaddam & Vishlaghi (2025), Hadian et al. (2025), Isiaka (2025), Bamiri et al. (2025), Safarloo et al. (2024), Suryani & Syamsulbahri (2024), Butson et al. (2023), Bekhit et al. (2023), Adibzadeh & Roknabadi (2023), Karami Moghaddam & Vishlaghi (2025). According to the research results, the following suggestions were made: The organization should allocate a specific budget for training employees in new technologies (such as artificial intelligence, data analysis, and automation tools) and require employees to dedicate specific hours to this training to prevent skills from becoming obsolete. In goal-setting sessions, ensure that each employee understands how his or her daily work contributes to achieving the organization's macro, social, or value goals (sense of meaningful work).

Original Article (Qualitative) Business financial and economic management

Study of iron ore pricing prediction using dynamic neural network method and the trend of factors' effectiveness and impact.

Pages 110-130

https://doi.org/10.22034/jnamm.2026.547880.1155

Yusef Naji, Hamid Reza Mollaei, Ali Raeispour Rajabali, Mahdi Mohammad Bagheri

Abstract Abstract The aim of the present research is to study the iron ore pricing forecasting using dynamic neural network method and factors’ influence and effectiveness trend. The present study is applicable in terms of its purpose, and survey in terms of data. The statistical population includes daily iron ore stock prices for 2058 working days. Given that severe stock price fluctuations will affect the forecast; the statistical sample used in this study includes daily iron ore stock prices during the period of companies’ entry into the stock exchange from 21/03/2016 to 20/03/2023. Python programming language was used to model the dynamic neural network, and DEMATEL software was used for the influence and effectiveness of factors. The results showed that the dynamic neural network model (LSTM) with its high ability to model the nonlinear effects of macroeconomic variables showed the best performance in predicting iron ore prices. After optimizing the parameters (3 layers and 64 neurons), this model achieved the highest coefficient of determination (R2) of 0.985 and the lowest root mean square error (RMSE) of 0.051. Sensitivity analysis indicated that steel prices were the most important variables for predicting iron ore prices. The results of DEMETL also showed that interest rates were the strongest antecedent (influencing) factor in the economic system, while iron ore production was the strongest a posteriori (influencing) factor. These findings emphasize that iron ore prices are highly dependent on macroeconomic and financial conditions and that the dynamic neural network is a superior tool for predicting them. Introduction Today, the rate of economic growth and development depends on capital accumulation on the one hand, and on the productivity factor in economic activities on the other. These two basic factors depend on the nature of the investment process; therefore, one of the most important tasks of financial markets is to facilitate capital formation. Capital markets can well handle both of the aforementioned tasks of capital accumulation and increasing economic productivity (Farajian & Farajian, 2022). Given the key impact of mineral product prices on calculating the cut-off grade and net present value of mining projects, reliable forecasting of mineral product prices is an important and fundamental issue in economics and the design and planning of open-pit metal mining. Given the high volatility of iron ore prices, its accurate forecasting is one of the critical issues in the design of open-pit mines to increase decision-making certainty (Sadegh Beigi Aliayee et al., 2025). Iron ore is the main raw material for steel production. The iron ore market has always been affected by different and variable conditions. There are many large and small producers and exporters active in this industry (Jan Nesari & Aghajani Bazazi, 2023). Iron is one of the most useful metals in the world. The global price of iron ore is determined by supply and demand. There are several variables, including steel prices, steel production, oil prices, gold prices, interest rates, inflation rates, iron production, and aluminum prices, that affect the global price of iron ore (Mehrdanesh et al., 2021). Iron ore does not have a direct substitute, but steel produced from iron ore has substitutes such as aluminum. On the other hand, any planning for the future requires predicting the future situation. Manufacturing companies need product price forecasts to plan, produce economic analysis of projects, review new investments for development, and so on. Steel production and consumption is today one of the main branches of development of countries and societies. The presence of the steel industry in a region has a significant impact on the process of development of culture, knowledge level, employment generation, research, education and trade of that region. Human daily life is mixed with steel, and steel industries play an important role in the construction, reconstruction and development of the country. Considering that the difference between the consumption and production of crude steel in the country in 2009 was more than 8.9 million tons, investment and growth of the steel industry in the country seems economical and logical; provided that the location of the process, production, supply of natural resources and energy, and project management are selected correctly (Azimi & Afrogh, 2015). Accordingly, the present study seeks to answer the question: how to predict iron ore pricing using the dynamic neural network method and the process of influence and effectiveness of factors? Theoretical Framework Iron Ore Pricing The iron ore industry plays a key and influential role in the growth and development of a country. On the one hand, this industry is a fundamental industry in development, and on the other hand, this industry is considered a benchmark for the industrialization of countries. Therefore, its improvement and development is of particular importance. Basic industries such as transportation, construction, machinery manufacturing, mining and other industries related to the production and transmission of energy are dependent on products produced from iron ore. Therefore, the global demand for iron ore is high and will remain stable in the future, if not increase (Hao et al., 2018). Sadegh Beigi Aliayee et al. (2025) studied the optimization of global iron ore price forecasting using intelligent methods. The main features of the forecasting model were based on the analysis of the correlation coefficients of iron ore prices and the dependent variables of six parameters including price, copper, gold, silver, oil, crude, transportation cost and iron ore demand. They were limited and normalized to improve the performance of intelligent algorithms. Then, a multivariate linear regression model of iron ore price forecasting based on the features was obtained with a coefficient of determination of 0.85. Finally, the frog leap metaheuristic algorithm was used to optimize the model, which led to an increase in the value of R2 and a decrease in RMSE and MSE. Souza et al. (2024) presented a new approach to predicting iron ore prices using weighted fuzzy time series analysis. Given the large number of effective parameters and the complex relationships between them, artificial intelligence-based approaches can be used to predict iron ore prices.  Research Methodology The present study is applicable in terms of purpose, and survey in terms of data. The statistical population includes the daily price of iron ore stocks for 2058 working days. Given that the strong fluctuations in stock prices will affect the forecast; therefore, the statistical sample used in this study includes the daily prices of iron ore stocks in the period of companies entering the stock exchange from 21/03/2016 to 20/03/2023. Research findings For modeling the dynamic neural network, the Python programming language was used, and DEMATEL software was used for the effects and effectiveness of factors. The results showed that the dynamic neural network model (LSTM) with its high ability to model the nonlinear effects of macroeconomic variables showed the best performance in predicting iron ore prices. After optimizing the parameters (3 layers and 64 neurons), this model achieved the highest coefficient of determination (R2) equal to 0.985 and the lowest root mean square error (RMSE) equal to 0.051. Sensitivity analysis indicated that steel prices are the most important variable for predicting iron ore prices. The results of DEMETL also showed that the interest rate is the strongest antecedent factor in the economic system, while iron ore production is the strongest adversarial factor. These findings emphasize that iron ore prices are highly dependent on macroeconomic and financial conditions, and that the dynamic neural network is a superior tool for predicting them. Conclusion The present study aimed to investigate the prediction of iron ore pricing using the dynamic neural network method and the trend of factors’ effectiveness and effectiveness. The results of this study are consistent with the results of Karami Moghaddam & Vishlaghi (2025), Hadian et al. (2025), Isiaka (2025), Bamiri et al. (2025), Safarloo et al. (2024), Suryani & Syamsulbahri (2024), Butson et al. (2023), Bekhit et al. (2023), and Adibzadeh & Roknabadi (2023). Karami Moghaddam & Vishlaghi (2025) showed that a fair payment system in laws, the right to legal promotion and advancement, job security based on the law, determining salaries and benefits based on the approved and unified government table, legal protections in critical situations, and equality and prohibition of legal discrimination were raised as the most important legal factors. According to the results of the study, it is proposed to replace the core of traditional predictive models with deep learning architecture (LSTM), a review of risk management systems, focusing on key nonlinear drivers and implementing metaheuristic optimization methodologies and hybrid models should be implemented.

Original Article (Quantified) Human resource management in business management

Identifying the most effective and influential dimensions of the indigenous succession model appropriate to the organizational culture in Barez Industrial Group

https://doi.org/10.22034/jnamm.2026.533752.1105

Mohammad Ziaei Abkenar, Sanjar Salajeghe, Mohammad Jalal kamali

Abstract The aim of the present study is to identify the most effective and efficient dimensions of the indigenous model of succession planning appropriate to the organizational culture in Barez Industrial Group. The research method is applied in terms of its purpose and quantitative in terms of its implementation method. The statistical population of the study consisted of 15 senior managers, human resources experts, and board members of Barez Industrial Group. Sampling was carried out purposively using the snowball technique. The data collection tool was a semi-structured interview, and the interviews continued until theoretical saturation was reached. The DEMATEL method was used for analysis. The results showed that ten effective factors, namely organizational values ​​and attitudes, learning and development culture, organizational interaction and cooperation, organizational processes and structure, skills and human resource development, motivational systems and participation, flexibility and knowledge management, individual and personality characteristics, professional and managerial skills, and flexibility and managerial ability, were confirmed by experts. The findings showed that the organizational interaction and cooperation index is the most effective index, as well as individual and personality characteristics.

Original Article (Mixed) Human resource management in business management

Exploring Experts’ Mental Models in the Adoption of Blockchain Technology in Public Sector Organizations Using Q Methodology

https://doi.org/10.22034/jnamm.2026.559255.1201

zahra mohemmi, mohammad ghasemi, baqer kord, Ali asghar Tabavar, Abdolmajid Imani

Abstract The aim of this research is to investigate the mental models of experts in the application of blockchain technology in government organizations using Q methodology. The present research is applied in terms of purpose and implementation using a mixed method. The statistical population of the research consists of managers of government organizations, 19 of whom were selected as a statistical sample using purposive sampling and based on the principle of theoretical adequacy. According to the research approach in the qualitative part, first, a discourse space was obtained with 19 interviews, and using their views and opinions, the sample, Q option, and finally the Q set were obtained. Then, in the quantitative part of the research, the data obtained from the qualitative part were analyzed and examined using SPSS. The findings show that transparency, increasing productivity, increasing agility, preventing corruption, improving trust, improving electronic voting, managing secure identity, and improving innovation are eight mental models of managers in line with blockchain technology in government organizations.

Original Article (Quantified) Marketing Management

The role of neuromarketing in digital marketing

https://doi.org/10.22034/jnamm.2026.573144.1245

Ehsan Alitanloo, Ali Naziri Firouzsalari, Hakimeh Niky Esfahlan

Abstract This study was conducted with the aim of investigating the role of neuromarketing in digital marketing. The research method, considering its purpose, is applied, and in terms of execution, it is quantitative, and in terms of nature and method, it is descriptive-correlational. The statistical population of the research consisted of customers of active online stores in Tehran province. Using a simple random sampling method and Cochran’s formula, 384 individuals were determined as the sample size. A standard questionnaire based on a 5-point Likert scale was used to collect research data. The content validity of the instrument was confirmed by specialists and experts, and to measure the reliability of the instrument, Cronbach’s alpha and composite reliability methods were used. By distributing the questionnaire, the validity of the instrument was measured using three methods: construct validity (outer model), convergent validity (AVE), and discriminant validity. The AVE value for all variables should be greater than 0.5. SPSS and PLS software were used for data analysis. The research findings indicate that the dimensions of neuromarketing (interest and engagement, knowledge and awareness, and ethics) have an impact on digital marketing.

Original Article (Qualitative) Human resource management in business management

Analysis of the Dimensions and Components of AI‑Based Digital Transformation Management

https://doi.org/10.22034/jnamm.2026.550414.1173

Kolsoum Ahmadi alinoudehi, Haideh Ashouri, Zohreh S hakibaei

Abstract The aim of this research is to explore the dimensions and components of digital transformation management based on artificial intelligence in the education system. This research was conducted in a qualitative manner using thematic analysis method. Data collection and extraction of related themes were carried out using in-depth semi-structured interviews with key experts in this field. Participants were selected using purposive sampling and theoretical saturation criteria, based on which 12 experts were selected. To obtain the credibility and validity of the data, two methods were used: participant review and review of experts not participating in the research. Max Quda statistical software was also used to analyze the data. The results of the present study indicated that AI-based digital transformation management was designed in the form of four overarching categories: "contextual requirements", "digital infrastructure", "digital transformation management process", "organizational capital", 12 organizing categories: "ethical requirements", "cultural requirements", "organizational requirements", "hard digital infrastructure", "soft digital infrastructure", "digital transformation management process", "digital transformation planning", "prototyping", "learning", "human capital", "process capital", "structural capital", "social capital" and 73 basic categories.

Original Article (Qualitative) Entrepreneurship

Identifying the Dimensions and Components of Competitive Advantage and Innovation in the Policy Framework for the Creation and Development of Digital Entrepreneurship in Knowledge‑Based Companies

https://doi.org/10.22034/jnamm.2026.539554.1112

mahdi jazinizadeh, Mehdi Mohammad Bagheri, zahra shokooh, Sanjar Salajegheh

Abstract The aim of this study is to identify the dimensions and components of competitive advantage and innovation in policies for the creation and development of digital entrepreneurship in knowledge-based companies. In terms of purpose, this research is applied, and in terms of implementation, it adopts a qualitative approach. The statistical population of the study consisted of 15 experts, including university professors in the field of management and managers of knowledge-based companies in the city of Kerman. To select the sample, purposive sampling was employed while considering the diversity of experts (managers, academics, and employees), and interviews continued until theoretical saturation was achieved.Data were collected through semi-structured interviews. Data analysis was conducted using coding and thematic analysis with the support of MAXQDA software. The results indicated that the most important themes in this area include research and development, the use of emerging technologies, the creation of digital business models, data-driven decision making, digital networking, cybersecurity, the development of e-commerce, digital management and online human resources, the development of digital markets, digital investment, and the attraction of digital financial resources.These findings suggest that digital entrepreneurship in knowledge-based companies encompasses multiple dimensions that can contribute to improving the performance and competitiveness of these firms.

Original Article (Qualitative) Other topics related to business management, entrepreneurship, and marketing

Designing a qualitative model for improving employee performance effectiveness based on cultural components in the digital age

https://doi.org/10.22034/jnamm.2026.549403.1163

Samin Haji Fathali, Amirmohsen Madani, Esmaeil Kavousi, Vida Goudarzi

Abstract This study aims to design a model for enhancing employee performance effectiveness based on cultural components in the digital era at Melal E‑Commerce and Information Technology Company. The research adopts a qualitative approach within an interpretive paradigm and is conducted using a thematic analysis strategy.The statistical population consisted of 10 experts, including university professors in the field of management with at least ten years of relevant professional and academic experience and a deep understanding of the concept of enhancing employee performance effectiveness based on cultural components in the digital era at Melal E‑Commerce and Information Technology Company. The participants were selected through purposive sampling. Data were collected using semi‑structured interviews. The collected data were analyzed using thematic analysis.The findings of the study revealed six main themes: digital acceptance culture, ethical leadership style, organizational culture, cultural competence of employees and managers, cultural accountability of employees and managers, and cultural and psychological empowerment. In addition, 33 organizing themes were identified that influence the enhancement of employee performance effectiveness based on cultural components in the digital era at Melal E‑Commerce and Information Technology Company.The study provides a conceptual framework for developing a qualitative model to enhance employee performance effectiveness grounded in cultural components in the digital era within Melal E‑Commerce and Information Technology Company.

Original Article (Mixed) Marketing and Brand Strategy

Decoding the Components of Audience-Centricity in Art; A Novel Approach to Identifying and Refining Indicators Using Fuzzy Logic

Articles in Press, Accepted Manuscript, Available Online from 20 June 2026

https://doi.org/10.22034/jnamm.2026.576649.1255

Azadeh Sahebazamani, Abolfazl Davodi Roknabadi, Nayeresadat Mobinipour, Nooshin Safiyari

Abstract This study aims to systematically identify and refine the components of audience-centricity in the arts, . Employing an exploratory sequential mixed-methods approach, the research was conducted in two main phases. In the qualitative phase, using purposive sampling, 19 authoritative scientific articles were subjected to in-depth analysis through qualitative content analysis facilitated by NVIVO software yielded 39 initial codes, nine axial categories, and ultimately four core components. In the quantitative phase, fuzzy screening technique was employed to refine the components within the specialized context of the arts, utilizing the opinions of 12 experts . Data were collected using a researcher-developed questionnaire .The findings revealed that out of the 39 initial indicators, 11 were confirmed as the final components of audience-centricity in the arts, with three indicators—"investment in continuous learning and capability development," "adherence to privacy and data ethics," and "transparency in actions and communications"—attaining the highest level of importance. The alignment of the findings with the theoretical background not only confirms foundational theories such as market orientation and value co-creation but also demonstrates the study's innovation in introducing an "ethical-strategic framework" as the core of audience-centricity in the age of digital art.

Original Article (Mixed) Marketing and Brand Strategy

Analyzing and Localizing Brand Authenticity Components in the Healthcare Industry

Articles in Press, Accepted Manuscript, Available Online from 20 June 2026

https://doi.org/10.22034/jnamm.2026.569720.1251

Parisa Imani, Shahnaz Nayebzadeh, Seyed Hasan Hatami Nesab

Abstract The purpose of this research is analyzing and localizing brand authenticity components in the healthcare industry. Aiming to propose a localized model, this study first identified 15 primary brand authenticity factors through a systematic literature review and qualitative content analysis utilizing NVIVO software. Subsequently, these factors were localized for the Iranian healthcare context through the Delphi method involving 12 academic and industry experts, resulting in 12 final validated factors, including transparency and honesty, strong brand legacy, existential originality, and brand sustainability and social responsibility. The findings indicate that the alignment between a healthcare organization's declared values and its actual performance serves as the fundamental basis for patients' perceptions of authenticity. By focusing on localized dimensions, this research offers a scientific framework for healthcare managers and policy makings to fundamentally transition from intuitive to evidence-based decision-making, thereby facilitating the strengthening of patients' networked trust and the enhancement of the therapeutic experience quality.

Original Article (Quantified) Human resource management

Investigating the relationship between administrative automation with organizational agility and health, considering the mediating role of organizational structure dimensions

Articles in Press, Accepted Manuscript, Available Online from 11 March 2026

https://doi.org/10.22034/jnamm.2026.523442.1092

Mohammadali Nikbakhsh, Behzad Sahraei, Ali Elaminezhad

Abstract This study aimed to investigate the relationship between administrative automation, organizational agility, and organizational health, considering organizational structure dimensions as a mediating variable in the General Department of Ports and Maritime Affairs of Bushehr Province. The current research is a descriptive-correlational study conducted cross-sectionally in the year 2025 among all employees of the General Department of Ports and Maritime Affairs of Bushehr Province. The total number of employees is 600, and from this number, 234 were selected as the sample size based on simple random sampling proportional to the population size and according to Cochran’s formula. To collect data, four questionnaires were used: Administrative Automation Questionnaire (Ahangarpour, 2008), Organizational Agility Questionnaire (Zhang & Sharifi, 2000), Organizational Health Questionnaire (Hoy & Feldman, 1996), and Organizational Structure Questionnaire (Robbins, 1979). The administrative automation questionnaire has 30 questions with validity and reliability of 0.90 and 0.93, respectively. The organizational agility questionnaire has 28 questions with validity and reliability of 0.88 and 0.86, respectively. The organizational health questionnaire has 44 questions with validity and reliability of 0.91 and 0.85, respectively. The organizational structure questionnaire has 24 questions with validity and reliability of 0.87 and 0.93, respectively. All statistical analyses were performed using SPSS and LISREL computer software. The results of data analysis indicate a significant relationship between administrative automation, organizational agility, and organizational health, considering the mediating variable of organizational structure dimensions in the General Department of Ports and Maritime Affairs of Bushehr Province. Conclusion: The organizational structure plays a very important role in achieving the organization’s goals, especially organizational health and agility, due to the type of service the organization provides.

Original Article (Quantified) business management

Modeling the psychological characteristics of founders of industrial small and medium enterprises in Mazandaran

Articles in Press, Accepted Manuscript, Available Online from 11 March 2026

https://doi.org/10.22034/jnamm.2026.573755.1247

Seyd kamal Tourang, Mohammad Hossein Hashemi Nasab

Abstract The aim of this study is to examine the modeling of psychological characteristics of the founders of small and medium-sized enterprises (SMEs) in the industrial cooperatives of Mazandaran Province. The present research is applied in terms of purpose and quantitative in terms of methodology. The statistical population consists of 893 business founders across the province, based on the definition provided by the Global Entrepreneurship Monitor (GEM). Using Cochran’s formula, a sample size of 186 individuals was selected through simple random sampling. The data collection instrument was a questionnaire developed by Kiggundo (2002). SPSS and LISREL software were employed for data analysis.The findings indicate that the overall psychological construct under investigation—analyzed within a path analysis measurement model (structural equation modeling)—explains the process of business start-up both directly, indirectly, and interactively. Among the examined variables, the sub-variable of internal locus of control demonstrated the greatest overall influence. Other variables, including tolerance of ambiguity, autonomy at work, need for achievement, motivation, and risk-taking, ranked respectively in subsequent levels of importance.The study concludes by recommending that policymakers and relevant authorities, in addition to considering other contextual factors, should also pay careful attention to these psychological variables in order to enhance the business start-up process and promote productive employment.

A review of supply chain performance evaluation models - case study: Iranian auto parts supply chain

Volume 1, Issue 1, March 2023, Pages 99-108

https://doi.org/10.22034/jnamm.2023.423043.1020

Fatemeh saghafi, Massoud Rezaei, Mohammad Mehdi Rezaei

Abstract In the current competitive conditions, the proper performance of the supply chain plays a key role in the success of an organization and the achievement of its goals, especially its profitability, therefore, in recent years, the management and measurement of supply chain performance has attracted the attention of a large number of managers and researchers in this study. In line with supply chain performance evaluation, various performance evaluation methods have been introduced and the characteristics of the most famous methods and studies conducted in this field have been collected. In this article, a framework for choosing the best method of evaluation of supply chain performance, improvement and continuous evaluation is proposed, which can facilitate the evaluation process in a targeted manner. It is suggested that in the next works, a review study on each of the used supply chain performance evaluation methods is done separately and also a conceptual framework of the application of these methods for different environments is prepared.

The effect of artificial intelligence technology on the development of entrepreneurship with the mediating role of entrepreneurship education

Volume 3, Issue 1, Spring 2024, Pages 86-105

https://doi.org/10.22034/jnamm.2024.454730.1052

rasol mohamadi, seyed reza mousavi fard, bijan rezaee, mahdi hosseinpour

Abstract Abstract The purpose of this research is to investigate the effect of artificial intelligence technology on the development of entrepreneurship with the mediating role of entrepreneurship education. The research is applicable in terms of purpose, descriptive- survey in terms of nature, and of casual type. The statistical population of the research was managers and employees of start-up business companies in Kermanshah province. The sample size is 193 people and sampling method is random cluster. The data collection method was field collection, and the tools used were entrepreneurial development questionnaires (Antonik and Hiserich, 2003), artificial intelligence technology (adapted from Rahimi and Akbari research, 1402), and entrepreneurship training (researcher-made). The method of data analysis was descriptive statistics and inferential statistics (structural equation modeling), using Spss26 and Amos24 software. Sobel's test (t-statistic) was used to investigate the mediator variable. The findings showed that artificial intelligence technology has a significant effect on entrepreneurship development by 86%; and on entrepreneurship education by 83%. Also, entrepreneurship education predicts 11% of the changes resulting from entrepreneurship development. The results indicate that artificial intelligence technology has an impact on the development of entrepreneurship with the mediating role of entrepreneurship education in the start-up businesses of Kermanshah province. Extended Abstract Introduction The development of entrepreneurship is a complex, long-term and inclusive process that plays a significant role in the economic growth and development of countries. Today, entrepreneurship has become the most important and strategic economic tool of advanced societies. In fact, economic growth and development of countries depends on entrepreneurs and entrepreneurial activities. Therefore, the need to achieve economic development and progress is to pay special attention to the development of entrepreneurship (Zali & Razavi, 2008). The development of entrepreneurship requires serious determination and necessary knowledge in businesses; many influential factors can be listed that may improve the development of entrepreneurship. One of these factors that has created a global revolution today is the use of artificial intelligence technology in start-up businesses and entrepreneurship. In today's world, technological advances are one of the most fundamental factors in shaping society's transformations in all economic, cultural, political and social fields. Human dependence on technology is such that some experts such as Max Tegmark say: "Without technology, the extinction of us humans, on a cosmic scale of tens of billions of years, will happen soon" (Tegmark, 2017). One of the factors that can increase the effect of artificial intelligence technology on the development of entrepreneurship as a mediator is entrepreneurship education. Today, it is accepted that the progress and survival of any society and business depends on the quality and efficiency of the education of that society; and educational courses have an important mission in producing knowledge and preparing new businesses to assume leadership and responsibility in a competitive, complex and changing world (Escorcia et al., 2022). According to the stated contents, this research tries to answer the question: what is the effect of artificial intelligence technology on the development of entrepreneurship with the mediating role of entrepreneurship education? Theoretical framework Artificial intelligence Artificial intelligence is a multidisciplinary and interdisciplinary field grown tremendously since the introduction of handheld computers in the 1950s. This field has the potential to transform various industries, and is defined as any theory, method, or approach that helps machines, especially computers, in analyzing, simulating, exploiting, and exploring human intellectual processes and behaviors (Lund et al, 2023). Entrepreneurship training Entrepreneurship education refers to all activities that aim to develop entrepreneurial mentality, attitude and skills in a range of cases such as idea generation, start-up, growth and innovation (Nvello et al, 2015). Entrepreneurship training is an activity that is used to transfer the knowledge and information needed to start and manage a business, and it will increase, improve, and develop the attitudes, skills, and abilities of non-entrepreneurs (Naeiji & Ebrahimi, 2017). From the viewpoint of literature, in the simplest definition, entrepreneurship can be considered as the use of skills to bring innovation to business or to develop new businesses (Shetty et al, 2021). The first issue raised in entrepreneurship research and start-up business development was the emphasis given to capacities, specific assets, and the unit of new economic activities. Ownership, capabilities and assets can be a sign of successful growth of a business. Intelligence in entrepreneurship is a technology-driven process for collecting, integrating, analyzing and presenting business information (Mehdi Sasan, Bakhshandeh, 2022). Therefore, the first emphasis is research on artificial intelligence as a technology-based software, and the use of this technology in the global economy is increasing day by day. The use of artificial intelligence allows start-up businesses to improve economic conditions and business growth (Dondapati et al, 2022). Yerevani et al, (2024) conducted a systematic review of the impact of artificial intelligence on the world's educational systems. This research has been done with a systematic review of 26 scientific research articles, 5 books and 13 reference sites. The results showed that artificial intelligence has a comprehensive role and importance in education systems. In the field of education by artificial intelligence, there are many successful projects and systems (GPT, etc.) that have facilitated the improvement of the teaching and learning process. Gofman & Jin (2024) in a study entitled Artificial Intelligence, Education and Entrepreneurship concluded that students of disadvantaged universities founded fewer AI startups and attracted less funding. Also, the departure of professors from universities reduces the knowledge of artificial intelligence of startups, which seems to be an important factor for the successful formation of startups and attracting capital. Research methodology The current research is applicable in terms of purpose, descriptive- survey in terms of nature, and of casual type. The method of collecting information is library-based, and the tool used is note-making. The statistical population of the research is managers and employees of start-up businesses in Kermanshah province. The population size was 385 people and the sample size was determined to be 193 people based on Cochran's formula. Also, the sampling method of this research was random cluster. The data collection method was field-collection, and the tools used are a) Entrepreneurship Development Questionnaire (Antonik & Hisrich, 2003), b) Artificial Intelligence Questionnaire (Rahimi & Akbari, 2023), and c) Entrepreneurship Education Questionnaire (researcher-made). Research findings Spss and Amos software were used in this section. The statistical findings showed that the research hypotheses were confirmed with a significance level of less than 0.05, and the effect of artificial intelligence technology on entrepreneurship development is 86% and on entrepreneurship education is 83%. Also, the effectiveness of entrepreneurship education on entrepreneurship development was calculated as 11%. The results of the general hypothesis of the research were done using the Sobel test (t statistic). The results of this test are significant with a coefficient of 2.258 at a level of 1.96 and a significance level of 0.001, and it shows that artificial intelligence technology with the mediating role of entrepreneurship education has an impact on the development of entrepreneurship in start-up companies in Kermanshah province. Conclusion Artificial intelligence technology can help greatly in the process of entrepreneurship education. Artificial intelligence makes entrepreneurship education learners use the updated information and resources in this field to make proper use of it in their business process. Therefore, it can be concluded that artificial intelligence is an effective and applicable factor in entrepreneurship education. The statistical results obtained indicate that artificial intelligence has an effect of 83% on the changes resulting from entrepreneurship education. The results of structural equation modeling and the obtained fit indices are proof of this claim. The results obtained are aligned with the results of Yerevani et al., (2024), Moradzadeh (2022), Gafman & Jane (2024), Chen et al., (2024) and Kissinger et al, (2021). Today, a business is successful if it has enough information and knowledge and can develop its entrepreneurship and business through education. Therefore, entrepreneurship training is essential for start-up businesses and entrepreneurship development. The development of entrepreneurship will be faster when the necessary trainings have been implemented and the entrepreneurs have learned these trainings well and implement them in their business. The statistical results obtained indicate that entrepreneurship education responds to 11% of the changes resulting from entrepreneurship development. The obtained results are consistent with the results of Dahdahjani (2019) and Agha Mohammadi and Abdulahi (2015). The results of the general hypothesis of the research regarding the effect of artificial intelligence technology on the development of entrepreneurship with the mediating role of entrepreneurship education were confirmed with the Sobel test. According to the results obtained for the first hypothesis, it is suggested to identify the advantages and disadvantages of artificial intelligence in the entrepreneurial system and pay special attention to its strengths. In line with the results of the second hypothesis, it is suggested that the threats resulting from the implementation of artificial intelligence in entrepreneurship education and entrepreneurship development should be reduced as much as possible. And finally, in line with the results of the third hypothesis, it is suggested that artificial intelligence be considered as one of the new and practical technologies in start-up businesses.

The Impact of Customer Experience of Artificial Intelligence on Customer E-satisfaction, Customer Trust in Online Shopping, and Customer Online Purchase Intention in the Insurance Industry

Volume 3, Issue 4, Winter 2025, Pages 1-21

https://doi.org/10.22034/jnamm.2025.490323.1062

seyyedmojtaba mirfazli, Haniyeh Taghizadeh Fashkche, Neda Mohammadpour Khabazi, hassan gharibi

Abstract Abstract The aim of this study is to investigate the impact of customer experience of artificial intelligence on customer electronic satisfaction, customer trust in online shopping, and customer online shopping intention. The statistical population of this study consists of customers of Alborz Insurance Company throughout Iran. The sampling method was non-randomly available and the electronic questionnaire was distributed among customers through social networks (Telegram, ETA, and Instagram) by the admin of Alborz Insurance agencies. After collecting 385 questionnaires, the distribution process was stopped. The data collection tool was a standard questionnaire with 18 customer-specific questions, the validity and reliability of which have been confirmed. The collected data were analyzed using descriptive statistics and inferential statistics. Frequency and frequency percentage indices were used at the descriptive statistics level; and Pearson correlation coefficient, structural equation model, and path analysis were used at the inferential statistics level. For this purpose, SPSS and LISREL software were used. The results of the analyses showed that customer experience of artificial intelligence has a positive and significant effect on all three research variables, namely electronic satisfaction, customer trust in online shopping, and online shopping intention. The highest effect, with a path coefficient of 0.81, was related to the effect of customer experience of artificial intelligence on online shopping intention. In general, artificial intelligence, while improving the quality of customer experience, has a significant effect on key variables in online consumer behavior. Introduction Today, with the spread of information technology in the world and its rapid entry into everyday life, e-business has replaced traditional methods. In the last few years, the growth of cyberspace and businesses that operate on the Internet has been reported to be multifold, which has also led to the expansion of Internet-based commercial activities. The Internet has become a key tool, which can be called a strategic weapon by anybody; a tool that can simultaneously increase consumer trust and answer their questions, given the current competitive environment (Scott, 2015). The Internet has created a wide horizon for business, especially electronic services worldwide. Retailer websites are an important interface between retailers (banks and insurers) and their customers (van de Ven, K., & Koenraadt, R, 2017). Internet and online businesses offer different products and services compared with traditional businesses. Because of the product choices available on the Internet, advertising on social networks is important in enabling customers to make purchasing decisions (Wang et al., 2016). Although the impact of AI in the insurance industry may not be as tangible as in agriculture, cancer diagnosis, military industries, automotive, construction, etc., it can be claimed that this technology has given speed, accuracy, and security to industries such as banking, information technology, insurance, etc. One of the biggest challenges in this field can be considered detecting complex frauds and discovering false claims in the insurance industry. These frauds include fake accidents, arson, false stolen property, multiple repair and medical bills, etc. By using AI in the insurance industry, operational efficiency can be improved, wrongly paid claims can be limited, total payments can be reduced, and the company's profits can be increased. By relying on AI, insurance companies can consider more competitive prices for their insurance products and offer more personalized services to their customers. In the past, insurers needed customer information to assess insurance risks, although in some cases, due to the dishonesty of individuals, incorrect risk assessment was not possible. But now, with the advancement of machine learning and artificial intelligence, insurers have access to more accurate information sources. For example, in the housing sector, insurance companies can use artificial intelligence to obtain information about the geographical location, marital status and the likelihood of claiming damages from individuals. Also, today, technological developments, especially in the field of telecommunications and information technology, have revolutionized the industry of providing online services such as mobile applications and smartphones. This has changed customer satisfaction from traditional satisfaction to electronic satisfaction, and companies should pay attention to electronic satisfaction in addition to physical satisfaction of customers when measuring customer satisfaction. In fact, the importance of customer satisfaction in an electronic and service environment has been confirmed by marketing studies (Al-dweeri et al., 2017). Satisfaction leads to strong repurchase behavior in the future and also leads to increased sales and profits of the organization and improves the market value for an organization. In the offline environment, customer satisfaction is defined as an emotional reaction in response to one or more cognitive service encounters (Gera, 2011). It is a reaction that occurs immediately after the point of purchase of products and services (Behjati et al., 2012). In the online context, e-customer satisfaction is defined as the consumer's perceptions of online convenience, commerce, website design, and financial security (Ilgaz, H., & Gülbahar, Y., 2015). Therefore, these days, customers are changing their behaviors dramatically in line with the technology and economic environment of the world. They are acquiring a large amount of information, are familiar with products, and are losing their trust in advertisements. They prefer customized products and services, and change their purchasing channels; therefore, businesses are forced to modify or even change their advertising strategies to cope with the changes, facts, and behaviors of their customers in order to survive (Cui et al., 2018). One of the most common beliefs that consumers have about online shopping is that this type of shopping saves time and money and helps them find products that better match their needs (Punj, 2011). Online shopping decisions are directly influenced by consumers' emotions and their online shopping beliefs about the attractiveness of the website or mobile applications and the style of communication with the e-commerce software with the customer. These emotions and beliefs are vital elements of the image of an online store or mobile application in the minds of customers and are thus able to be a stimulus for online shopping (Alnawas, I., & Aburub, F, 2016, gharibi et al., 2019). Therefore, it can be said that there is a need for research and study in the insurance industry so that insurance companies can study the impact of artificial intelligence on customer trust, attitude and behavior. Therefore, the question of the present research is: What is the impact of customer experience of artificial intelligence on customer e-satisfaction, customer trust in online shopping and customer online shopping intention in the insurance industry? Research literature Concept of artificial intelligence Artificial intelligence is a branch of computer science that attempts to understand the nature of intelligence and produce new intelligent machines that think, respond and perform tasks exactly like humans based on the data given to it. Some activities related to artificial intelligence, such as robotics, speech recognition, image recognition, natural language processing and problem solving, are very technical and specialized. Artificial intelligence refers to the intelligence and capabilities used by machines and computer systems to perform intelligent activities and make decisions. This metadata allows machines to recognize patterns, analyze data, and manage problems (Umamaheswari, S., & Valarmathi, A, 2023). Artificial intelligence is concerned with building computer systems and robots that can understand and learn from their observations. The goal of artificial intelligence is to make machines act like humans. The goal of artificial intelligence in general is to build a machine that can “think” (Al-Sayyed et al., 2021). Artificial intelligence includes a set of techniques and algorithms that enable machines to examine and analyze data, identify hidden patterns in them, and make decisions based on them. Artificial intelligence is a branch of computer science that, inspired by sciences such as cognitive psychology, philosophy, logic, statistics and mathematics, tries to simulate a type of human intelligence and does this through software development (Poole, D. L., & Mackworth, A. K, 2010). Electronic satisfaction  High electronic satisfaction is the key to the success of any retailer operating in the competitive global e-commerce environment. To overcome the barriers to global online shopping, companies must improve satisfaction with their electronic services. Most experienced and successful companies in e-commerce have understood that the success factors are not just the company's presence on the web or low prices, but the delivery of high-quality electronic service. Recent research shows that online customers are willing to pay even higher prices for high-quality electronic services offered by electronic retailers; therefore, online retailers should focus on high-quality e-services during and after the transaction rather than on the transaction itself, in order to build customer trust, loyalty, and retention (Navimipour, N. J., & Soltani, Z, 2016). Trust in online shopping Previous studies also show that lack of customer trust is a major barrier to using online shopping. Internet users do not have sufficient trust in sharing and exchanging information and communication with online sellers (Dwidienawati et al., 2020). Perceived ease of use by the customer plays an indirect role in individuals' intentions to adopt or continue to use e-banking. Another study also found that ease of use has an indirect effect on the use of e-banking as much as initial training (Guriting & Ndubisi, 2006). If a person is familiar with the Internet and uses it regularly, they are likely to have a higher level of organizational trust than someone who has not had previous experience using the Internet. As a result, the experience of using the Internet will increase organizational trust (Eastlick, M. A., & Lotz, S, 2011). Customer Online Shopping Behavior Online shopping environments are specific types of interactions that users turn to fulfill their shopping goals. Online shopping is an activity beyond making a mere purchase and includes skills such as searching for products, working with a computer, etc. (Demangeot, C., & Broderick, A. J, 2007). Online shopping intention, as the most important predictor of actual shopping behavior, refers to the outcome of customers' evaluation of criteria such as website quality, information search, and product evaluation (Martins et al., 2023). Conclusion and Discussion The present study, which was conducted among Alborz Insurance customers across Iran, examined the effect of customer experience of artificial intelligence on customer e-satisfaction, customer trust in online shopping, and customer online shopping intention in the insurance industry. The result of the first hypothesis of the study: Customer experience of artificial intelligence has an effect on customer e-satisfaction in the insurance industry. a) Using the Pearson test, the correlation coefficient of customer experience of artificial intelligence and customer e-satisfaction in the insurance industry is 0.75, which indicates a positive and significant effect of customer experience of artificial intelligence on customer e-satisfaction in the insurance industry. b) Considering the path coefficient of 0.78 and the t-statistic of 16.84, it can be said that at a 99% confidence level, customer experience of artificial intelligence has a positive and significant effect on customer e-satisfaction in the insurance industry. The results of this hypothesis are consistent with the studies of Chen et al., (2021); Prentice et al., (2020); Datt (2020); and Hudong (2023). The result of the second hypothesis of the research: Customer experience of artificial intelligence has an effect on customer trust in online shopping in the insurance industry. A) Using the Pearson test, the correlation coefficient between customer experience of artificial intelligence and customer trust in online shopping in the insurance industry is 0.73, which indicates a positive and significant effect of customer experience of artificial intelligence on customer trust in online shopping in the insurance industry. B) Considering the path coefficient of 0.72 and the t-statistic of 11.63, it can be said: At a 99% confidence level, customer experience of artificial intelligence has a positive and significant effect on customer trust in online shopping in the insurance industry. The results of this hypothesis are consistent with the studies of Chen et al., (2021); Prentice et al., (2020); Datt (2020); and Hudong (2023). The result of the third hypothesis of the research: Customer experience of artificial intelligence has an effect on customer online shopping behavior in the insurance industry. a) Using the Pearson test, the correlation coefficient between these two variables is 0.81, which indicates a positive and significant effect of customer experience from artificial intelligence on customer online shopping behavior in the insurance industry. b) Considering the path coefficient of 0.81 and the t-statistic of 19.00, it can be said that at a 99% confidence level, customer experience from artificial intelligence has a positive and significant effect on customer online shopping behavior in the insurance industry. The results of this hypothesis are consistent with the studies of Chen et al., (2021); Prentice et al., (2020); Datt (2020); and Hudong (2023). The result of the fourth hypothesis of the research: Customer e-satisfaction has an effect on customer trust in online shopping in the insurance industry. a) Using the Pearson test, the correlation coefficient between these two variables is 0.68, which indicates a positive and significant effect of customer e-satisfaction on customer trust in online shopping in the insurance industry. b) Considering the path coefficient of 0.69 and the t-statistic of 12.06, it can be said that: at a confidence level of 99 percent, electronic customer satisfaction has a positive and significant effect on customer trust in online shopping in the insurance industry. The results of this hypothesis are consistent with the studies of Chen et al., (2021); and Keshiri et al., (2024). The result of the fifth hypothesis of the research: Electronic customer satisfaction has an effect on customer online shopping behavior in the insurance industry. a) Using the Pearson test, the correlation coefficient between these two variables is 0.79, which indicates a positive and significant effect of electronic customer satisfaction on customer online shopping behavior in the insurance industry. b) Considering the path coefficient of 0.66 and the t-statistic of 41.52, it can be said that: at a confidence level of 99 percent, electronic customer satisfaction has a positive and significant effect on customer online shopping behavior in the insurance industry. The results of this hypothesis are consistent with the studies of Chen et al., (2021); and Keshiri et al., (2024). The result of the sixth hypothesis of the research: Customer trust in online shopping has an effect on customer online shopping behavior in the insurance industry. A) Using the Pearson test, the correlation coefficient between these two variables is 0.75, which indicates a positive and significant effect of customer trust in online shopping on customer online shopping behavior in the insurance industry. B) Considering the path coefficient of 0.64 and the t-statistic of 8.46, it can be said that at a 99% confidence level, customer trust in online shopping has a positive and significant effect on customer online shopping behavior in the insurance industry. The results of this hypothesis are consistent with the studies of Chen et al., (2021); Keshiri et al., (2024); Hemmadi (2023); and Rahmani & Nowzari Jadid (2023). Today, with the spread of internet services and service applications, people of all tastes can compare and purchase different insurance services and, depending on their personal tastes, be satisfied or dissatisfied with their purchase. This satisfaction or dissatisfaction in receiving insurance services is recorded in the form of ratings and comments on mobile applications and social networks, based on which other people purchase services from different insurance companies. Therefore, customer trust and satisfaction with receiving services and even the way in which services are received can affect the customer's intention to purchase online, as in the present study, electronic satisfaction with a path coefficient of 0.66 and online trust with a path coefficient of 0.64 had an effect on the intention to purchase online of Alborz Insurance customers. The time is over when company messages were only about services or products and information was published unilaterally by the company and only what the company wanted to share. With the increasing spread of the Internet in various aspects of life, much research has been conducted to support the encouragement of customers to shop in the electronic and online environment. Considering the characteristics of the electronic environment and the behavioral characteristics of customers, in order to facilitate the customer shopping process, the reasons that cause customer distrust or poor site design and, as a result, customers' lack of purchase in the electronic environment should be investigated and resolved. By relying on the features of challengeability, uninterrupted analysis, the possibility of receiving feedback in time, establishing system interaction, and creating mental images in the electronic and online environment, it is possible to direct the mental structure of customers towards shopping on the Internet and mobile phones and guide their purchase decision-making process. Therefore, considering the impact of customer experience with artificial intelligence on customer e-satisfaction, customer trust in online shopping, and customer online shopping intention in the insurance industry, Alborz Insurance Company offers the following solutions in this regard: Alborz Insurance Company should design a mobile application for itself with the necessary investment in innovation and quick access, and place accessible user guides as a guide to using self-service technology on its website; it is suggested that a section be set up as an online support on the Alborz Insurance website so that it can answer customer questions 24 hours a day, because some customers may work night shifts and use the Alborz Insurance website more often during these times.

business management

Factors affecting the adoption of artificial intelligence in e-commerce by small and medium-sized enterprises

Volume 4, Issue 1, Spring 2025, Pages 62-83

https://doi.org/10.22034/jnamm.2025.500793.1067

Keyhaneh Karimi, Elaheh Mahmoodi Ranani

Abstract Abstract
The aim of this study is to evaluate the factors affecting the adoption of artificial intelligence in e-commerce by small and medium enterprises. This study is applicable in terms of its purpose, and is a quantitative research type. The present study proposes an integrated model based on the framework of dynamic capabilities, entrepreneurial orientation, and customer-centric systems. The empirical data of this study were collected through a digital survey using a purposive sampling method from small and medium enterprises in Iran. The analysis of the collected data was performed using structural equation modeling, and the results point to the role of dynamic capabilities and entrepreneurial orientation in facilitating the adoption of artificial intelligence in e-commerce. The data of this study were collected by distributing an online questionnaire to a sample of 183 decision-makers and managers in small and medium enterprises in Iran working in e-commerce. This study confirms the positive impact of AI adoption on the business performance of SMEs. The findings show that AI adoption in e-commerce is significantly associated with improved business performance of SMEs. Also, this study emphasizes the pivotal role of dynamic capabilities and entrepreneurial orientation in driving AI adoption in the e-commerce sector, which in turn can help improve business performance. These results emphasize the importance of developing technological capabilities and innovative approaches in SMEs to effectively utilize AI and achieve growth and success.
Introduction
Many companies are looking to leverage e-commerce to increase sales, improve services, and achieve greater customer satisfaction. If successful e-commerce strategies and tools are effectively implemented, this technology can significantly increase the revenue and profits of SMEs (Abbas et al., 2023; Ojha et al., 2023). However, the success of using these platforms depends on the level of commitment and trust of companies in smart technologies, which are effective in improving technical services and enhancing customer experience (Mishra et al., 2023). The adoption of artificial intelligence in e-commerce is considered one of the key factors for the success of businesses, as this technology uses existing data to identify opportunities and improve products and services (Liu et al., 2024).
While several studies have addressed the role of artificial intelligence in e-commerce, including customer service, sales facilitation, and information gathering, research related to the adoption and enhancement of artificial intelligence tools in maintaining e-commerce performance and supporting entrepreneurship in small and medium-sized enterprises is still scarce. Therefore, this article seeks to examine the factors affecting the adoption of artificial intelligence in e-commerce in small and medium-sized enterprises to promote entrepreneurship and strengthen the role of these companies in the country's economic progress and development. Insufficient understanding of how SMEs effectively use AI tools in e-commerce can negatively impact their ability to gain competitive advantage. Hence, there is a need for more in-depth research to identify challenges, exploit opportunities, and improve the effectiveness of using these technologies (Salah & Ayash, 2024(.
This paper identifies the benefits and opportunities for SMEs to adopt AI systems in e-commerce and suggests various ways to implement effective strategies for entrepreneurship development and selecting appropriate AI tools. The following key research question is formulated to guide the research and provide a structured approach to understanding the various factors involved: What factors influence SMEs’ ​​adoption of AI in e-commerce?
Theoretical literature
Artificial Intelligence
Artificial Intelligence is a branch of computer science that aims to design systems that can automatically and intelligently process information and perform various tasks. By imitating human intelligence and abilities such as learning, reasoning, problem solving, natural language understanding, and pattern recognition; this technology helps humans solve the most complex scientific, industrial, and social challenges. Artificial intelligence has been recognized as one of the most revolutionary technologies of the modern era since its early years and has now penetrated all aspects of human life (Simone, 2018.)
E-commerce
E-commerce is defined as the electronic buying and selling of items by consumers and businesses using computerized business exchanges. In this study, e-commerce is defined as the buying and selling of transactions over the Internet (Esare et al., 2012). E-commerce allows businesses to grow more easily in the global market and opens up new ways for companies to communicate information with consumers, suppliers, and other stakeholders (Tai, 2022).
Small and Medium Enterprises
In recent years, the importance and role of small and medium enterprises have been increasing, both in industrialized and developing countries. With the advent of new technologies, there have been transformations in production and the methods of it, distribution, and organizational structure of companies. It is essential for small and medium enterprises to use AI tools to obtain maximum value and competitive advantage, which includes reducing human errors, analyzing customer data, and providing highly efficient services. AI also helps in providing new and intelligent innovations that serve both institutions and customers, such as sales forecasting and attracting more customers (David at al., 2023).
Research Methodology
This study adopts a quantitative approach using a questionnaire to obtain data from officials in small and medium enterprises. It aims to investigate the factors associated with the adoption of AI in the field of e-commerce, while considering the relevant literature to improve the study results. Data for this study were collected by distributing an online questionnaire to a sample of 183 decision-makers and managers in small and medium-sized enterprises in Iran working in e-commerce. The sample focused on store owners and supervisors regarding their main occupations. The e-store owners were contacted through visits to the small and medium-sized enterprises, as well as through phone calls, WhatsApp, and email to encourage participation in the survey.
Research Findings
Structural equation modeling was used to analyze the data collected from the questionnaires and test the hypotheses. Based on the data analysis, the results of structural equation modeling showed that entrepreneurial orientation has a positive and significant effect on the adoption of AI-based e-commerce. The findings indicate that dynamic capabilities have a very positive and significant effect on the adoption of AI-based e-commerce. These findings emphasize that dynamic capabilities, such as the ability to learn quickly, adaptability, and continuous innovation in SMEs, can play a key role in the adoption and effective use of AI-based e-commerce. The results showed that the adoption of AI-based e-commerce has a positive and significant impact on the business performance of SMEs. This indicates a very strong and significant effect of this relationship. These findings emphasize that the adoption of new technologies such as AI can significantly improve the business performance of companies. In particular, companies that exploit AI-based e-commerce will be able to optimize their processes, reduce costs, and generally achieve economic advantages in competition with other companies.
Conclusion
This research shows that SMEs need to develop dynamic capabilities and strengthen entrepreneurial orientation to successfully adopt AI in e-commerce. Dynamic capabilities, as the ability of an organization to reconfigure resources, adapt to changes, and exploit new opportunities, are considered key factors in the adoption of new technologies. The results of the present study emphasize that companies with stronger dynamic capabilities are able to integrate AI into their business processes more effectively, which leads to improved organizational performance.
From a practical perspective, this research shows that in order to optimally utilize AI, small and medium-sized enterprises should focus on developing their dynamic capabilities and strengthening an entrepreneurial culture. Investing in employee training, developing agile strategies, and creating support structures for innovation can help to more effectively adopt this technology. From a theoretical perspective, this study highlights the role of dynamic capabilities and entrepreneurial orientation in the adoption of digital technologies and establishes a link between the strategic management, entrepreneurship, and digital transformation literature.
The present study aimed to provide a model to investigate the factors affecting the adoption of artificial intelligence in e-commerce by small and medium-sized enterprises in Iran. The results of this study are consistent with the results of Salah et al., (2024), Wei et al., (2022), Palataeka et al., (2023), Yang et al., (2024), Stalings et al., (2024), and Cabrit et al., (2024). The findings show that small and medium-sized enterprises need to develop dynamic capabilities and strengthen entrepreneurial orientation to successfully adopt artificial intelligence in e-commerce. Dynamic capabilities, as the ability of the organization to reconfigure resources, adapt to changes, and take advantage of new opportunities; are considered key factors in the adoption of new technologies.
Finally, this study suggests directions for future research; including examining the impact of other organizational and environmental factors on AI adoption, analyzing the role of government policies and financial support in the development of digital technologies, and studying the long-term impact of AI on the sustainability of small and medium-sized businesses. Also, conducting comparative research across industries can help to better understand the structural and strategic differences in the adoption of this technology. 

Marketing Management

Improving employee performance through internal marketing and organizational learning: The mediating role of organizational innovation

Volume 4, Issue 1, Spring 2025, Pages 1-21

https://doi.org/10.22034/jnamm.2025.524617.1093

neda zarin negar, Mohsen Najafi, fattaneh Hosseinzadeh bajgiran

Abstract Abstract
The present study investigated improving employee performance through internal marketing and organizational learning: the mediating role of organizational innovation. This research is applicable in terms of purpose, quantitative in terms of method, and of descriptive-survey type. The statistical population in this study is 116 food exporting companies in Mashhad, and using the Cochran formula, the sample size was estimated to be 86 companies; for this purpose, a questionnaire was distributed among and completed by the managers of these companies using simple random sampling method. In order to analyze the data, structural equation modeling test and other statistical tests based on SPSS and Pls software were used. The validity of the research variables was measured through confirmatory factor analysis. Also, the reliability of the research variables has shown that Cronbach's alpha for research variables including internal marketing, performance, organizational innovation, and organizational learning has been obtained as 0.909, 0.935, 0.940, and 0.901 respectively, which indicates the desired reliability of the research tool. The research findings have shown that organizational learning and internal marketing are effective on employee performance and organizational innovation mediates its effect.
Introduction
In today's world, human resources are recognized as the most important resource of organizations and attracting and retaining efficient forces is considered a vital competitive advantage (Chaudhary & Sharma, 2024). With rapid environmental changes, traditional management tools have become ineffective and the need for flexible and learning structures to respond to changes is felt more than ever. Optimal human resource performance is a necessary condition for the success of organizations, as it allows managers to focus on macro strategies (Organ, 2020). Two key factors in improving employee performance are organizational learning and internal marketing. Organizational learning helps organizations survive in a competitive environment by producing knowledge and continuously reviewing methods. On the other hand, internal marketing, by looking at employees as internal customers, creates effective relationships and improves organizational performance by increasing job satisfaction and motivation (Ocharo & Kinyua, 2021). Also, organizational innovation, especially in times of crisis and intense competition, plays a decisive role in the success of organizations and helps managers allocate resources optimally (Quispe et al., 2024). This issue is doubly important in food trading companies that face export challenges and strict standards. Therefore, in today's dynamic and uncertain environment, organizations need a flexible, learning, and innovative structure to meet stakeholder expectations. Based on the above, this study examines the question: do internal marketing and organizational learning through innovation have a significant impact on employee performance?
Theoretical foundations
Innovation and organizational innovation
Leticia Santos et al., (2022) consideres innovation as the tendency of a company or organization to participate in and support new ideas, pioneer in technology, conduct research, development, and other creative activities aimed at developing new products, services, and processes. On the other hand, organizational innovation encompasses a wide range of actions and activities aimed at facilitating and achieving innovative results in the organization. This type of innovation can be related to a product, device, system, process, policy, program, or service (Chen & et al., 2019).
Internal Marketing
Internal marketing means that companies should seriously invest in the quality of performance and capabilities of their employees. This is especially important for people who are directly in contact with customers, and these people need to be trained effectively. Also, all support staff should work together and work as a team to satisfy customers (Corrin & et al., 2022).
Organizational Learning
Organizational learning is a dynamic process that enables an organization to adapt quickly to changes. This process involves the production of new knowledge, skills, and behaviors. Organizational learning is the main way to create knowledge work and improve the efficiency of the organization; therefore, a successful organization must be dynamic in learning (Okolie, 2024).
Research Background
Bikzadeh Abbasi & Kaneshloo (2024) conducted a study titled: Investigating the Effect of Marketing Research on Improving Organizational Innovation. The results obtained indicate that marketing research has a positive and significant effect on improving organizational innovation in the United Nations Credit Institution. Khajeh Saeed & Sattarii (2024) conducted a study titled: The Effect of Marketing Capabilities on the Financial Performance of Exporting Companies. The results of this study showed that financial resources, information resources, and relational resources have a significant effect on the financial performance of exporting companies. Patwary et al., (2022) conducted a study aimed at investigating the role of knowledge management (KM) practices on performance and innovation. The findings indicate that KM has a positive effect on innovation performance among Malaysian hospitality employees. This study also shows that organizational learning and organizational creativity significantly mediate the relationship between KM and innovation performance.
Research Methodology
The present study is applicable in terms of purpose, and descriptive-survey in terms of method. The statistical population in this study is 116 food exporting companies in Mashhad, and the sample size was estimated to be 86 companies using the Cochran formula; for this purpose, a questionnaire was distributed among the managers of these companies and completed by them, through a simple random sampling method. In order to collect data, a questionnaire with 36 items related to the research variables was used. Also, in order to analyze the data in this study, the structural equation modeling technique and other statistical tests were used through SPSS and Smart PLS software. Face validity was used to confirm validity and Cronbach's alpha coefficient criterion was used to confirm reliability.
Findings
The findings of this study are presented in the form of 7 hypotheses, all of which were confirmed.
 Internal marketing has a positive and significant effect on employee performance.
 Organizational learning has a positive and significant effect on employee performance.
 Organizational innovation has a positive and significant effect on employee performance.
 Internal marketing has a positive and significant effect on organizational innovation.
 Organizational learning has a positive and significant effect on organizational innovation.
 Internal marketing has a positive and significant effect on employee performance with the mediating role of organizational innovation.
 Organizational learning has a positive and significant effect on employee performance with the mediating role of organizational innovation.
Discussion and Conclusion
The present study aimed to improve employee performance through internal marketing and organizational learning: the mediating role of organizational innovation (case study: food exporting companies in Mashhad). The findings of this study are consistent with the research of Chaubey et al., (2024), Laksono (2023), Imani et al., (2015), Karimi et al., (2021), and Gholipour et al., (2021). In the following, and based on the research findings, the following suggestions are presented:
 Internal marketing

Designing motivational systems to increase job satisfaction
Improving organizational communications and clarifying processes
Paying attention to the needs of employees as internal customers

Organizational learning

Holding continuous training courses
Creating an organizational knowledge bank of successful and unsuccessful experiences
Encouraging employees to share knowledge

 Developing innovation

Creating a safe space for presenting new ideas
Forming cross-departmental innovation teams
Investing in new technologies

 Coordinating strategies

Integrating internal marketing with innovation programs
Facilitating knowledge exchange between different units
Practical support for innovative ideas

 Human resource management

Mapping a career path for employees
Promoting a culture of continuous learning
Linking individual and organizational goals 

Identifying factors affecting sustainable consumption: a hybrid approach

Volume 1, Issue 1, March 2023, Pages 1-19

https://doi.org/10.22034/jnamm.2023.383330.1001

Kobra Sadeghi Dezaki, Abdol-Qayyum Azmoodeh Rad, siyavosh alirezaei

Abstract Responsible and sustainable consumption is considered one of the important aspects of sustainable development, which depends on achieving long-term economic growth compatible with environmental and social needs. In fact, the level of people's awareness about the environment and their mental self-awareness is directly related to the amount and type of consumption by the consumer. The more consumers give importance to environmental issues, the more resistance they have in consuming products that are in conflict with it, and this point of view accurately shapes consumer perception and behavior, so a producer, in addition to paying attention to issues related to the category Sustainable consumption must also take into account the factors that affect consumer behavior. The purpose of this research was to analyze the factors influencing sustainable consumption with metacombination method in Shahrekord convenience stores. Due to the comprehensive approach of the concept of conscious consumption presented by Sheth and colleagues (2011) and Lim (2017), this research tries to expand and complete the presented concept with a review study. Therefore, by considering the two aspects of conscious mental structure and conscious behavior for conscious consumption, the dimensions of a conscious mental structure that can lead to the occurrence of conscious behavior in the field of consumption are identified.

Managing the Adoption of Business Intelligence in Human Resources Based on Soft Systems Methodologies and Systems Dynamics

Volume 2, Issue 2, March 2024, Pages 1-23

https://doi.org/10.22034/jnamm.2023.419498.1016

Maryam Ebrahimi, Behnoush Jovari, Sayyed Kamran Yeganegi

Abstract Abstract
The purpose of the present research is to investigate, analyze and predict the strategies governing the adoption of business intelligence in the decisions of the Iranian Electricity Network Management Company, to policy science, technology, and innovation based on business intelligence in this company. In the first step, the research is based on the theory of technology-organization-environment while identifying the barriers and facilitators of using business intelligence in the organizational decisions of the Iranian Electricity Network Management Company using the three-way method including study, observation, and semi-structured interviews with data collection experts. And it was done through the method of thematic analysis of the coding process. In the next step, by combining soft system methodology and system dynamics, and using Rapidminer and Vensim software, the acceptance and use of this technology has been predicted in five years. For this purpose, by using cause-and-effect relationships and in the form of a dynamics model, circular and flow diagrams were modeled, and based on the opinion of experts, the necessary corrections were made to the output at this stage. In the following, the simulation was carried out for five years using a developed model using dynamic systems thinking. According to the research findings, the research system is controllable and has observable effects. That is, the inputs of the system control the variables of the state and each of the variables of the state affects some of the outputs of the system. Based on this, scenarios were obtained with changes in individual factors, organizational factors, environmental factors, and extra-environmental factors. The result is that the inappropriate localization of technologies, the insularity of information systems, the contradiction of security instructions, and the resistance of human resources in front of security policies are among the factors with a negative impact on the establishment of the sub-system of optimal allocation of human resources., the establishment of an education sub-system, security policies, establishment of the steering committee, establishment of systems integration sub-system, and establishment of a knowledge-based companies sub-system were recognized as positive predictors for the adoption and application of business intelligence.

Advantages and Barriers of Virtual Businesses in Iran Using Domestic Messaging Platforms and Instagram

Volume 3, Issue 2, Summer 2024, Pages 1-28

https://doi.org/10.22034/jnamm.2024.480656.1057

Ebrahim Kafshdartousi

Abstract Abstract This research examines the barriers and advantages of using Instagram along with Eitaa or Rubika in virtual businesses. Employing a qualitative approach, data was collected from 12 virtual business owners through semi-structured interviews and purposeful sampling. The data analysis was conducted using thematic analysis, facilitated by MAXQDA software and coding methods. The results indicated that the advantages of utilizing Eitaa and Rubika include reduced internet consumption, the potential to attract governmental and religious clients, the ability to address issues related to accounts or channels, and financial support. The advantages of using Instagram primarily involve ease of building trust. Collectively, the benefits of all three messaging platforms encompass the ability to attract customers from various parts of the city and country, learning from the profiles/channels of successful individuals, gaining information, employing strategies to attract clientele, and the opportunity to connect with new collaborators. The general acceptance of Instagram among the audience and the user-friendliness of domestic messaging applications compared to Instagram are considered additional benefits of these platforms. However, businesses also face challenges, including restrictions and regulations on content creation and advertising, audience limitations, the impact of political and social crises, competition, warnings from authorities, governmental restrictions, unethical behavior from audiences and competitors, and systematic issues such as messaging app bugs, lack of financial support, insufficient features in domestic messaging applications, and ideological constraints. This study offers solutions to improve the utilization of these messaging platforms and to assist businesses in better leveraging the capabilities of Instagram, Eitaa, and Rubika. Introduction The advancement of human life from the era of mass production to the age of communications and information, as well as the movement of countries towards knowledge-based and informational societies, has transformed all aspects of economic, cultural, industrial, and social activities. Among these developments, virtual social networks have experienced significant growth (Talebpour et al., 2014), attracting many businesses due to their features such as constant access, removal of time and space limitations, global reach, flexibility, and multimedia capabilities (Karimian et al., 2017). This has led to changes in consumer buying behavior (Yang et al., 2024). One of the most popular social networks, Instagram, has more than 1.6 billion users worldwide (Kemp, 2023), with 46.89% of Iran's population using it (Statcounter, 2024). Given this popularity, many businesses have started their activities on this platform. However, alongside this, some online business owners have expanded their activities on local messaging platforms like Eitaa and Rubika, responding to audience needs and adapting to domestic conditions due to the larger user base compared to other local platforms. According to statistics from 2023, Rubika has about 40 million users and Eitaa has about 30 million users (Tasnim, 2023). Being present on local messaging platforms such as Eitaa and Rubika, in addition to international platforms like Instagram, offers businesses opportunities for growth and increased revenue. However, business owners also face challenges and barriers, and understanding these challenges and planning to optimize their use is essential. This study seeks to answer the question: What are the advantages and barriers for Iranian businesses in using local (Eitaa and Rubika) and foreign (Instagram) messaging platforms? Theoretical Framework The social marketing theory emphasizes building relationships based on shared values between businesses and customers and uses tools such as social media to improve customer experience and enhance interactions. Simultaneously using both local and international messaging platforms can increase fast feedback and communication, enhancing customer trust and sales volume (Baran & Davis, 2017; Kotler & Roberto, 1989). The Hierarchical Effects Model focuses on the customer acquisition process, from awareness to action, while McLuhan's Global Village concept highlights the role of social networks in reducing geographical borders and influencing user behavior. These networks, as tools for transmitting information and shaping culture and user behavior, provide businesses with opportunities to send targeted messages to both local and international audiences (Baran & Davis, 2017; Zolghadr & Ghasemzadeh-Araghi, 2012). Social Learning Theory emphasizes the importance of observing and modeling competitors. By analyzing competitors' activities on different messaging platforms, businesses learn new methods for brand and business development, and use these patterns to promote their own growth (Baran & Davis, 2017). Finally, the Technology Acceptance Model indicates that if businesses perceive the usefulness and ease of use of a messaging platform, they will be more likely to adopt it and encourage others to participate as well (Ningtyas & Kurniawan, 2024). Methodology In this study, data was collected through semi-structured interviews with 12 online business owners active on Instagram and Eitaa or Rubika. The interviews were conducted purposively via telephone contact, and after obtaining informed consent, the interviews were recorded for analysis. Data were coded and analyzed using thematic analysis (Braun & Clarke, 2006) and MAXQDA software (version 2018). Subsequently, main and subcategories were extracted and compiled into a comprehensive report. Findings The advantages of using the Instagram, Rubika, and Eitaa platforms include their usefulness and ease of use. Local messaging platforms like Eitaa and Rubika reduce costs by offering discounted internet rates and eliminating the need for VPNs, making access to businesses more convenient. Each platform targets a specific audience; for example, Eitaa is more appealing to government employees, while Rubika attracts a younger, teenage demographic. Instagram, with features such as global accessibility, algorithms, and advertising capabilities, helps businesses widely promote their products and utilize diverse ideas for growth. On Instagram, influencer marketing is more effective, while on Eitaa and Rubika, advertisements are mainly promoted through pinned sections and broader areas, where increased monitoring builds user trust. In addition to advertising, promotional exchanges and discounts are popular customer acquisition methods. In Rubika, businesses can receive financial rewards for increased activity, but Instagram does not offer such financial support. Due to its commercial nature, Instagram easily builds customer trust, whereas local messaging platforms require more effort in this regard. Addressing issues on local platforms is easier due to the presence of related organizations within the country, while on Instagram, the only solution is typically email, which is often ineffective. Additionally, the use of these platforms, due to their lack of dependence on VPNs and simpler designs for various age groups, makes it easier for businesses to operate. Ultimately, Instagram, with features like Explore, automatic post downloads, and continuous visibility by users, provides more opportunities for businesses to be seen. Alongside the advantages, there are also various social and systemic barriers on these three platforms. Social barriers include content production limitations across all three messaging platforms. In Eitaa and Rubika, there are restrictions on certain topics, including dress codes, specific terms, and social issues like gender identity, materialism, and consumerism. These restrictions are less common on Instagram, where the focus is more on violent and disturbing content that could lead to account suspension. Additionally, Eitaa and Rubika mainly attract specific age, professional, and religious groups, which limits the target audience for businesses and reduces their revenue potential. In contrast, Instagram’s broad audience diversity offers more opportunities to sell products to different age groups and professions. Another social barrier is the challenges caused by audience behavior, such as offensive comments or inappropriate suggestions. These issues are more prominent on Instagram, especially for women in business, whereas they are less frequent on local messaging platforms due to stricter monitoring. Furthermore, operating on Instagram requires understanding complex algorithms, necessitating that business owners take various training courses. Local platforms, on the other hand, are simpler to use and do not require special training. Finally, intense competition on Instagram often leads to the creation of meaningless content and the manipulation of audience emotions, adding to the challenges faced by business owners. Such competition is less visible on local messaging platforms. Moreover, governmental restrictions in Iran have made it difficult to use Instagram, as political and social events may disrupt access to the platform, requiring the use of VPNs. Systemic Barriers: From a systemic perspective, Instagram allows business owners to receive feedback through comments on posts, a feature that Eitaa lacks. Additionally, upload speed and content size limitations on Eitaa and Rubika can affect user activity, whereas Instagram does not impose content size restrictions. Due to the lack of content editing tools in Eitaa and Rubika, users typically edit their content on Instagram before uploading it to these platforms. Instagram also has ideological restrictions related to words and topics concerning crises and social issues in Iran. If these terms are used too frequently, user accounts may be suspended. In contrast, Rubika offers more financial support to businesses, providing them with funds to prevent their activities from being halted, while Instagram does not offer such financial backing and only provides a platform for activity. Conclusion This study examines the advantages and obstacles faced by online business owners on three messaging platforms: Instagram, Eitaa, and Rubika. In terms of advantages, Instagram provides a suitable platform for business growth with its sophisticated algorithms and diverse tools, allowing business owners to reach a wide range of audiences due to its extensive user base. Additionally, Instagram offers numerous educational resources on optimizing activities and expanding businesses, which can be valuable for business owners. On local messaging platforms (Eitaa and Rubika), advantages include the absence of the need for VPNs and easier access for Iranian audiences. Furthermore, these platforms are more cost-effective compared to Instagram, as business owners do not need to pay additional costs for advertising, training, or internet usage. However, in terms of social barriers, there are significant differences between these platforms. Local messaging platforms impose more content and advertising restrictions, particularly concerning issues such as dress code, consumerism, and topics related to gender identity. Moreover, cultural and religious restrictions specific to age groups on these platforms may hinder business growth. While Instagram has fewer advertising restrictions, issues related to violence, controversy, and intense competition can create challenges for business owners. In terms of systemic barriers, similar problems exist across all three platforms. Eitaa and Rubika face issues such as slow upload speeds and content size limitations, which often drive business owners to turn to Instagram due to its better editing tools and upload capabilities. Additionally, ideological restrictions on Instagram, especially regarding social issues in Iran, may lead to account suspensions. Finally, issues like the lack of financial support on Instagram and software problems across all platforms are fundamental obstacles in the growth of businesses. Overall, operating on Instagram and local messaging platforms each has its own advantages and disadvantages. Online business owners need to choose platforms based on their type of business and audience needs in order to achieve the greatest success with the fewest challenges.

Marketing Management

Presenting a model of persuasion in social media messages in promoting green products

Volume 4, Issue 2, Summer 2025, Pages 1-19

https://doi.org/10.22034/jnamm.2025.546926.1150

Mosa mohsenpour, Nasser Fegh-hi Farahmand, Hossein Gharehbiglo, Hossein Bodaghi Khajeh Noubar

Abstract Abstract The present study sought to provide a model of persuasion in social media messages in promoting green products. The research method is applicable in terms of its purpose, quantitative in terms of implementation, and descriptive-correlational in terms of nature and method. A standard questionnaire based on a 5-point Likert scale was used to collect research data. The content validity of the tool was confirmed by specialists and experts, and Cronbach's alpha and composite reliability were used to measure the reliability of the tool. By distributing the questionnaire, the validity of the tool was measured with three methods: construct validity (external model), convergent validity (AVE), and divergent validity. The AVE value for all variables should be greater than 0.5. SPSS and PLS software were used to analyze the data. The results of structural equation modeling with SmartPL software showed that trust-building, audience interaction, narrative, and visual design all play an effective role in strengthening the audience's environmental attitude and behavior and supporting green products. Also, technical infrastructure and new technologies facilitate the path of persuasion and acceptance of a sustainable lifestyle. Introduction Today's world is constantly changing; changes that are mainly the result of scientific advances and emerging technologies and have a wide impact on the individual and social lives of humans. Communication and information technologies have grown significantly in recent years (Jafari et al., 2017). Since the 1970s, with the beginning of the communication and information technology revolution, tools such as satellites, the Internet, and mobile phones have entered the field, changing the level of expectations, norms, and social interactions (Bastani et al., 2017). At the same time, social networks have provided an efficient and low-cost space for communication and interaction, which has become more effective than other media due to the possibility of access at any time and active participation of users (Mahmoud et al., 2020). Today, citizens are able to receive and analyze information at the lowest cost and at the highest speed, and this can create appropriate or sometimes distorted perceptions (Lin et al., 2020; Hamidi Zadeh, 2019). Social networks have become large databases that increase the rapid circulation of information and decision-making power in various fields, including marketing. By producing attractive content, these media play an effective role in attracting and persuading audiences (Kim et al., 2016) and, as a low-cost platform, they provide the opportunity to reflect persuasive messages and influence customer beliefs, attitudes, and behavior (Labbafi et al., 2016). Since networks host diverse groups with different interests, the reflection of persuasive messages can promote the acceptance and support of green products. Marketing on social networks not only strengthens customer attitudes and satisfaction, but also affects their purchase intention and repeat purchase (Ghaforian Shagerdi et al., 2016). The development of green products through these messages can increase collective perceptions and social responsibility in environmental protection (Matthes et al., 2014). Attention to the environmental impacts of products has also become an important criterion in purchasing decisions, so that price is not the only determining factor (Joshi et al., 2015). The global and Iranian situation shows an increase in environmental pollution and waste, highlighting the necessity of developing green products (Du et al., 2020). Given the importance of environmental protection, this study seeks to investigate the role of persuasive messages on social networks in promoting support for green products, and its main goal is to explain the conceptual model of persuasion and its impact on the development of green products. In a situation where the global market is sensitive to customers' environmental demands and considerations, companies are forced to formulate their marketing strategy based on customer attitudes and perceptions and social expectations (Limk & Louizao, 2014). Creating customer-friendly values ​​and a coherent identity between the company, customers, and society are key principles for business survival and growth (Talari et al., 2018). The development of green products can increase social awareness and pave the way for positive behavioral changes in consumers (Wu et al., 2020). Despite previous research that has emphasized the importance of social awareness and persuasion in supporting green products (Ogbeibu et al., 2020), there is still a lack of research about the topic. Theoretical foundations Persuasion As a multidimensional process in human communication, persuasion deals with changing the audience's attitudes, emotions, and behavior, and its success requires understanding the audience's cognitive, emotional, and cultural backgrounds so that the message has the greatest impact (Lin et al., 2020). Trust-building and brand credibility Brand credibility and trust are key components of marketing and brand communications that shape consumers' attitudes and behaviors. Brand trust includes assurance of the truthfulness of promises and social responsibility, and brand credibility refers to the audience's perception of the brand's reliability (Kim et al., 2016; Huang et al., 2024). Research has shown that reputable brands can increase green behaviors and customer satisfaction, and strengthen individual motivations for sustainable consumption (Ogbeibu et al., 2020; Hu et al., 2024; Mahmoud et al., 2020). Persuasive and interactive tactics Interactive tactics invite the audience to actively participate and respond and include personalized content, Q&A, surveys, and creating a discussion space (Mahmoud et al., 2020). These tactics increase the level of attention, learning, and trust in the brand and, in green marketing, allow for better understanding of environmental messages (Lin et al., 2020; Ogbeibu et al., 2020). Environmental behavior and lifestyle Environmental behavior and lifestyle include purchasing green products, reducing energy consumption, waste management, and participating in environmental activities (Joshi & Rahman, 2015; Du et al., 2020). Positive attitudes towards the environment and external factors such as brand trust, social responsibility and social media messages can strengthen individual motivations to adopt a sustainable lifestyle (Huang et al., 2024; Mahmoud et al., 2020; Ogbeibu et al., 2020; Wu et al., 2020). Hu et al. (2024) investigated "The role of social media marketing on green product repurchase intention". The research method is descriptive correlational and the sample is 438 people. The results showed that social media marketing activities significantly increase green values, environmental concerns and brand image and positively affect brand involvement. Also, brand involvement mediated the relationship between green values, environmental concerns, brand image and repurchase intention. Huang et al. (2024) studied the "Effect of Green Marketing on Repurchase Intention and Positive Word of Mouth of Residential Platform Users". The research method is descriptive correlational and the sample size is 488 people. The results showed that consumers' perception of green marketing increased consumer trust and identification with the platform, and as a result, it affected repurchase intention and positive word of mouth. Consumer trust also mediated the relationship between green marketing and repurchase intention and positive word of mouth. Research Methodology This research is applicable in terms of purpose and descriptive-correlational in terms of method. The statistical population includes active users of social networks and experts in the field of green product marketing who play a practical role in the process of persuasion and acceptance of messages. Given that there is no information on the exact number of the statistical population; therefore, the population is considered indefinite and according to the Cochran formula sampling method for the indefinite population, the sample size is 384 people. The statistical sample of the research will be selected randomly and by simple sampling method. The findings from the Cronbach's alpha test and composite reliability to measure the reliability of the research tool are reported in Table 1. To examine the validity of the tool, content validity (expert opinion) was used and its validity was confirmed. Then, by distributing the questionnaire, the validity of the tool was measured with three methods: construct validity (external model), convergent validity (AVE), and divergent validity. The AVE value for all research variables must be greater than 0.5. In order to test the research hypotheses, structural equation modeling was used in the context of smart pls2 statistical software. Research findings The present study showed that building trust and brand credibility, along with the use of interactive tactics and emotional narratives, plays a fundamental role in improving the environmental behaviors and attitudes of the audience. Modern messaging infrastructures and technologies and visual design in harmony with green values ​​strengthen the persuasive power of messages and increase the acceptance of a sustainable lifestyle. The findings confirm the importance of integrating trust, interaction, narrative, visual design, and technology in developing green marketing and promoting brand social responsibility, and show that these factors can strengthen individual and collective motivations for sustainable consumption. Discussion and Conclusion The research findings showed that trust-building and brand credibility play a central role in shaping audiences’ environmental attitudes and behaviors, such that audiences who consider the brand to be credible and trustworthy are more likely to consume green, reduce energy consumption, and participate in environmental activities (Huang et al., 2024; Meysamizad et al., 2023). Also, persuasive and interactive tactics in messaging, along with narratives and emotional messages, increase active audience participation and pave the way for improving green messaging infrastructure and channels (Antoun et al., 2023; Khalaji et al., 2022). Other findings of the present study showed that persuasive strategies based on narrative and emotion, by enhancing interactive tactics, engage audiences more and increase their level of interaction with messages and the brand. This is consistent with the research of Antoun et al. (2023) and Meysamizad et al. (2023) who have confirmed the role of storytelling and emotional messages in increasing digital impact and participation. Also, the infrastructure and technical platforms of green messaging are of considerable importance in creating environmental behaviors of audiences and strengthening their understanding of the brand's social responsibility. This finding is consistent with the research of Khalaji et al. (2022) and Hu et al. (2024) and shows that digital tools and channels can strengthen individual motivations for green consumption and adoption of a sustainable lifestyle. Visual design aligned with green values ​​and the use of digital platform technologies and algorithms also enhance the persuasive power of messages and improve audience acceptance and commitment to sustainable consumption (Hu et al., 2024; Mahmoud et al., 2024).

the impact of the Islamic Azad University Electronics Branch's brand on its competitive advantage, considering the mediating role of positioning and market orientation

Volume 3, Issue 3, Autumn 2024, Pages 1-26

https://doi.org/10.22034/jnamm.2025.484881.1058

Mehri KashefArzanagh, Shahnaz Nayebzadeh

Abstract Abstract
The purpose of the present study is to investigate the effect of brand recognition of the Electronics Branch of Islamic Azad University on its competitive advantage with regard to the role of positioning and market orientation. In terms of purpose, this study is an applicable research conducted in a cross-sectional manner based on a survey approach (questionnaire) and using field studies and correlational research methods; data collection was carried out using a questionnaire among 194 students of this university unit who were selected by simple random method, and data analysis was performed using PLS software. The findings indicated the confirmation of the effect of brand recognition on positioning and market orientation and the effect of these two variables on competitive advantage; and the mediating effect of these two variables in the relationship between brand recognition and competitive advantage was also confirmed. Following the study of the Electronics Branch of Islamic Azad University, this study has also provided suggestions to improve the insight of managers of this university.
Introduction
With the onset of the post-industrial era, markets became highly competitive and learning faster and earlier than competitors became a competitive advantage, so the organization's focus was on awareness, knowledge, and information (Krakowski et al., 2023). The competitive market environment is such that future market trends, as well as competitors' activities, cannot be easily predicted and interpreted (Campagna et al., 2023). Businesses active in the education industry have also realized that gaining a competitive advantage in a market that has become complex and challenging with the increasing number of competitors and the diversity and breadth of services must pay more attention to the mindset of customers and target audiences; among the most key activities of managers and decision-makers, especially in highly competitive markets, is therefore investing in the brand (Permana, 2023). A review of the research literature indicates a research gap in the field of brand effects on competitive advantage in higher education, and in particular, the role of variables such as positioning and market orientation has received less attention in such studies, which indicates the necessity of the present study. Another important point is that the existence of numerous socio-economic and cultural problems has challenged the function and role of traditional universities and damaged people's mentality about their commitment to society. On the other hand, a society without efficient and effective higher education cannot progress and excel (Samani et al., 2022). This issue becomes more important in the case of the largest university system in the country, namely Islamic Azad University, with a significant number of students nationwide and its spread among target audiences with different characteristics, tastes and needs. Therefore, the present study seeks to answer the main question: how does brand recognition affect the competitive advantage of Islamic Azad University, Electronics Branch, with regard to the mediating role of positioning and market orientation??
Theoretical framework
Brand Recognition: The concept of brand awareness by the customer is essentially the customer's comprehensive understanding of how brand relationships with customers develop. Therefore, brands have realized that to enhance brand awareness among customers, they must invest in brand attributes such as credibility and differentiation, while also considering the attractiveness and impacts on perception, and giving importance to informing and enhancing the mental image of the audience (Gading et al., 2024).
Competitive Advantage: Competitiveness refers to how an organization aligns its internal capabilities and resources with external changes, and it can increase under conditions where resources are utilized in a way that directly or indirectly makes competition more challenging for other businesses (Beirami et al., 2024). Organizational competitiveness can be measured in various ways. To overcome the limitations of financial metrics, the use of marketing metrics such as brand reputation, customer loyalty, and employee loyalty has also been suggested for assessing competitiveness (Heydari et al., 2021).
Positioning: Positioning is a strategic concept that, over time, has entered other management discussions, such as marketing, and particularly strategic marketing. Business managers have realized that in today's highly turbulent environments, they must identify the environmental factors that contribute to their success in competing in an uncertain environment, given the presence of numerous competitors and rapid changes (Parhizgar et al., 2023).
Market Orientation: Market orientation is a type of behavioral norm that has spread throughout the business and responds to the current and future needs of target audiences and customers through innovation (Azimi et al., 2021). With the emergence of market orientation in recent years, market-based organizational culture has increasingly been considered a key element in the superior performance of businesses, emphasizing the positive relationship between market orientation and performance (O'Cass & Sok, 2013).
Research methodology
The research method of the present study is applicable in terms of purpose. From the perspective of execution, this research is a non-experimental study of the correlational type, and regarding the time frame for data collection, it is a cross-sectional study conducted in the field using a questionnaire. The statistical population of this research consists of 337 master's degree students in business management at the Islamic Azad University, Electronic Unit, who are currently studying. The sampling method used in this research is simple random sampling, and to determine the sample size, a pilot study and Cohen's formula for a finite population were utilized, resulting in 194 completed questionnaires being analyzed. The questionnaire of Rua & Santos (2022) included brand awareness with 5 items; brand positioning with 6 items; market orientation with 2 items; and competitive advantage with 3 items. The measurement scale for the questions was a five-point Likert scale, and face validity was used for validating the content validity, while reliability was confirmed using Cronbach's alpha coefficient. To examine the normality of the data distribution, the Kolmogorov-Smirnov test was employed. The relationships between variables and factors were confirmed through confirmatory factor analysis and structural equation modeling techniques using PLS3 Smart software, which is a variance-based path modeling method that allows for the simultaneous examination of theories and metrics.
Research findings
The internal model framework was examined, and the structural model path was evaluated. Considering the t-statistic value and P-values for all paths except for the brand awareness to competitive advantage path, the t-statistic is greater than 1.96 and the P-values are less than 0.05, indicating that at a 95% confidence level, all paths except for the brand awareness to competitive advantage path have a significant impact.
Conclusion:
Regarding the first hypothesis of the research, which states that brand awareness has a positive and significant impact on the competitive advantage of the Islamic Azad University, Electronic Unit; the data analysis indicated that the first hypothesis of the study was not confirmed. The findings of the present research regarding this hypothesis do not align with the results of the study by Rua & Santos (2022) and Umukoro et al., (2023), who examined and confirmed the same hypothesis in their research. Concerning the second hypothesis of the research, which suggests that brand awareness has a positive and significant impact on the positioning of the Islamic Azad University, Electronic Unit; the data analysis showed that the second hypothesis of the study is confirmed. The findings of the present research regarding this hypothesis are consistent with the results of the study by Rua & Santos (2022) and Umukoro et al., (2023), who also examined and confirmed this hypothesis in their research. Regarding the third hypothesis of the research, which states that brand awareness has a positive and significant impact on the market orientation of the Islamic Azad University, Electronic Unit; the data analysis indicated that the third hypothesis of the study is confirmed. The findings of the present research regarding this hypothesis align with the results of the study by Rua & Santos (2022), who examined and confirmed the same hypothesis, and the research by Mampaey et al., (2019), which also referred to successful market orientation as a result of increased audience awareness about the brand in their study on internal and external branding. Regarding the fourth hypothesis of the research, which suggests that positioning has a positive and significant impact on the competitive advantage of the Islamic Azad University, Electronic Unit; the data analysis indicated that the fourth hypothesis of the study is confirmed. The findings of the present research regarding this hypothesis are consistent with the results of the study by Rua & Santos (2022), who examined and confirmed this hypothesis in their research.
To practically benefit from the results of the present research, it can be suggested to the managers and decision-makers of the Islamic Azad University, Electronic Unit, that:
The growth and development of higher education institutions and universities depend on the effective utilization of marketing concepts, including brand awareness, positioning, and market orientation. Brands and businesses that play a vital role in the educational economy of the country and have been compelled to embrace transformation in the competitive arena due to changes in key environmental factors in the long term are guided in managing the perceptions of their audience.

Strategic Management

From Survival to Evolution: A Comprehensive and Dynamic Model of Organizational Resilience for Iranian SMEs in Permacrisis Ecosystem Using Meta-synthesis

Volume 4, Issue 3, Autumn 2025, Pages 43-73

https://doi.org/10.22034/jnamm.2025.561784.1215

Ehsan Mirzadeh, seyed morteza ghayour baghbani, Morteza Rojuee, Saeed Jafari titkanloo

Abstract Abstract This study aims to design a comprehensive and dynamic model to explain organizational resilience in Iranian small and medium-sized enterprises. Given that these companies operate in a unique ecosystem of permanent crisis, traditional resilience models based on cross-sectional shocks seem inadequate to explain their dynamics. This research is exploratory and theoretical in nature and is based on the interpretive paradigm. A mixed methodological approach including metasynthesis as the main method and bibliometric analysis as a complementary method was used, and bibliometric data were extracted from 953 articles in Scopus and analyzed with VOSviewer software. After a systematic search of reliable databases and screening, 67 key articles were selected and synthesized and integrated through a content analysis process. Qualitative data analysis led to the identification of 460 unique conceptual codes that were categorized into 15 organizing themes and 5 overarching themes including: “1. Drivers and enabling factors, 2. Multilevel capabilities (individual/entrepreneurial, organizational, network/institutional), 3. Dynamic process cycle (anticipation, exposure, learning), 4. Resilient strategies (defensive, adaptive, offensive), and 5. Heterogeneous outcomes”. The main finding of the research is “A dynamic and multilevel model of organizational resilience in a permanent crisis environment,” which conceptualizes resilience as an evolutionary meta-capability. This research presents the first comprehensive and dynamic theoretical framework to explain resilience in the Iranian perma-crisis ecosystem, and its main innovation lies in conceptualizing resilience as an evolutionary process for the strategic transition from survival to evolution and showing the mechanisms of this transition. Introduction The business landscape is witnessing a paradigm shift as it enters an era of constant turmoil and unpredictable disruptions. This environment, described as the “Woka world”, has seriously challenged the fundamental principles of traditional strategic management. In these circumstances, the survival and sustainable growth of organizations requires a capacity beyond short-term resistance, known in the literature as the concept of organizational resilience (Chi et al., 2025). The understanding of the concept of resilience has evolved from the traditional “go back” perspective to the new “leap forward” paradigm, emphasizing strategic learning and transformation (Hernes et al., 2025). However, the existing literature suffers from three gaps: theoretical fragmentation and lack of integrated models, a homogeneous view of resilience pathways, and a lack of sensitivity to context. Much of the research has examined resilience in response to episodic crises and has not been able to explain it in the context of a permanent crisis (permacrisis), a structural situation in which multiple and intertwined crises have become the norm (Maalouf et al., 2025). This concept accurately describes the unique nature of the Iranian business environment. Iranian companies, especially small and medium-sized enterprises, operate in a multi-crisis ecosystem shaped by a combination of factors such as economic and institutional instability, international sanctions, social unrest, geopolitical tensions, and infrastructure challenges (Shabani et al., 2025). Numerous pieces of evidence, including the National Business Environment Monitoring Reports and the unprecedented rise in the Uncertainty Index, confirm this turbulent ecosystem. These conditions render resilience models developed in more stable environments ineffective. At the heart of this ecosystem, SMEs, as the driving force of the economy, face a paradox: on one hand, they are more vulnerable due to resource constraints; and on the other hand, they have a higher potential for agility due to their flexibility (Koporcic et al., 2025). How this potential is activated in Iran’s high-risk context is a question that, despite valuable domestic research, still requires a comprehensive model based on systematic knowledge synthesis. Accordingly, this study aims to design and present a comprehensive, dynamic, and multi-level model of organizational resilience for SMEs in Iran’s perma-crisis ecosystem. This article conceptualizes resilience as an evolutionary meta-capability for the transition from survival to evolution, moving beyond a static perspective. To achieve this goal, this research uses meta-synthesis and bibliometric analysis to systematically synthesize previous researches to arrive at a new and context-sensitive theoretical framework and answer the fundamental question: "What are the dimensions and components of a comprehensive model of organizational resilience in Iranian small and medium-sized enterprises in a permanent crisis ecosystem?" The theoretical framework Organizational Resilience Hepfer & Lawrence (2022) defines resilience as “the ability of an organization to anticipate, respond to, recover from, and learn from adversity”. Organizational resilience is a multilevel phenomenon. The existing literature generally distinguishes three key levels of resilience: individual, organizational, and network/institutional (Hillmann & Guenther, 2021). 1. Individual level: This level focuses on the psychological resilience of employees, managers, and especially entrepreneurs (Hartmann et al., 2022). In the context of small and medium-sized enterprises, the individual resilience of the entrepreneur plays a vital and pivotal role in guiding the entire organization’s response to a crisis (Leonelli et al., 2024). 2. Organizational level: This level, which is the main focus of this research, addresses the resources, processes, capabilities, and structures that allow the entire organization to cope with disruptions (Barasa et al., 2018). 3. Network/Institutional Level: This level examines resilience beyond the boundaries of an organization and focuses on the quality of the institutional environment, supportive policies, and the organization’s relationships with external actors and stakeholders (Koporcic et al., 2025). Koporcic et al. (2025) in a comprehensive umbrella review, identified key barriers to resilience in SMEs as constraints related to firm size and greater vulnerability to shocks, financial constraints and ineffective leadership and lack of crisis management skills; and key coping strategies included business continuity planning, organizational culture, technology adoption, proactive manufacturing, and strategic cooperations. De Waal et al. (2025) identified four heterogeneous resilience paths (incomplete recovery and survival, performance recovery, leapfrogging, explosive leap) in a longitudinal study of Ukrainian companies in war conditions, which shows that survival in critical conditions is itself a form of resilience. Research Methodology This research is exploratory and theoretical in nature, based on an interpretive paradigm, and uses the meta-synthesis and bibliometric analysis methods. Research Findings Data analysis was conducted using the meta-synthesis method as the main method and bibliometric analysis as a complementary method. Also, bibliometric data were extracted from 953 articles in Scopus and analyzed with VOSviewer software. After a systematic search of reliable databases and screening, 67 key qualitative and conceptual studies were finally selected and synthesized and integrated through a content analysis process. The results showed that 460 conceptual codes were classified into 15 organizing themes and 5 overarching themes including “drivers and enabling factors, multilevel capabilities, dynamic process cycle, resilient strategies, and heterogeneous outcomes.” The main finding of the research is “A dynamic and multilevel model of organizational resilience in a permanent crisis environment”. This model conceptualizes resilience as an evolutionary meta-capability that emerges from the dynamic interaction between the reservoir of multilevel capabilities and the flow of a continuous learning cycle and includes the following elements: 1) drivers and enabling factors (permanent crisis context); 2) the core of resilience including multilevel capabilities (individual/entrepreneurial, organizational, and network/institutional) and a dynamic process cycle (anticipation, exposure, learning); and 3) heterogeneous outcomes (from survival to explosive mutation). This model operates through strategic choices (defensive, adaptive, offensive) and evolves over time with feedback loops and an “evolutionary learning spiral”. Conclusion The present study aimed to provide a comprehensive and dynamic model of organizational resilience in Iranian SMEs in a permanent crisis ecosystem using a meta-synthesis method. The findings of this study are fully consistent with studies that emphasize the pivotal role of the leader in SMEs (Leonelli et al., 2024; Branicki et al., 2018). However, this model goes further and shows that leader resilience (including strategic intelligence and managerial competencies) is not only a driver, but also the main catalyst for activating capabilities at other levels. At the organizational level, this model is consistent with the main literature by highlighting capabilities such as agility, learning culture and digital transformation (Georgescu et al., 2024; Dowlatabadi, 2025) and shows that organizational capabilities are a platform for institutionalizing individual-level experiences and intuitions and transforming individual learning into organizational memory. At the network level, this model is also consistent with the findings of researchers by emphasizing strategic partnerships and resource dependency management (Koporcic et al., 2025). In the Iranian context, where formal institutions are weak and unreliable, informal and trust-based networks (social capital) become an alternative infrastructure for business. At the macro level, the resilience of small and medium-sized enterprises affects the resilience indicators of society, and supportive government policies can lead to strengthening the country's business ecosystem. This research, by moving beyond simplistic models, attempted to open the black box of resilience in the unique context of Iran's permanent crisis.

The effect of green marketing on green repurchase intention (mediating and moderating role of green marketing strategies)

Volume 3, Issue 4, Winter 2025, Pages 44-66

https://doi.org/10.22034/jnamm.2025.521082.1089

Abbas Ghaedamini Harouni, Mahsan Hemtizadeh, Khatoon Hashemipour

Abstract Abstract The present study was conducted with the aim of investigating the effect of green marketing on green repurchase intention with the mediating role of green marketing strategies. The research is applicable in terms of its purpose, descriptive in terms of the nature of the data, and of the correlation type (structural equation modeling). The statistical population of this study consists of consumers of green products of HB Board Company. The desired information was collected from the study sample using an online questionnaire. Given that the number of statistical population in this study is large and uncertain, the Cochran formula for unlimited populations was used to determine the sample size, and the number of sample members was selected by considering the estimated number of 384 people as non-probability sampling, known as convenience sampling. The research tool was standard questionnaires, and the validity of the questionnaires was examined based on content, face and construct validity, and after the necessary terms, the validity was confirmed; on the other hand, the reliability of the questionnaires was estimated by Cronbach's alpha method; all variables above 0.7 Data analysis was performed at two descriptive and inferential levels, including structural equation modeling. The results showed that green marketing positively affected all green outcomes; and green advertising, brand loyalty, brand equity and brand innovation had a positive effect on repurchase intention. However, a significant moderating effect of green awareness on green brand equity and green repurchase intention was not found. Introduction Consumers' satisfaction with their green purchases is influenced by their level of satisfaction. As a contemporary approach, green marketing has important implications for consumers' perceptions and behavioral tendencies. The evolving strategies in green marketing emphasized its potential for sustainable branding. The impact of green marketing tools highlighted on purchasing behavior, reinforcing the effectiveness of green advertising in fostering positive consumer perceptions. In the case of brand loyalty, green advertising and brand innovation positively affect brand loyalty and encourage repeat purchases. They emphasized the critical role of green brand equity in shaping repurchase intention. They stated that green brand effects and trust significantly underlie green brand equity, which in turn, stimulates repurchase. Green brand innovation enhances loyalty, especially when consumers are well informed about environmental issues, and increases the chances of green repurchase. While there is a growing literature on green marketing and its impact on consumer behavior, several gaps still need to be addressed. First, the integrated effects of green marketing, advertising, brand loyalty, equity value, and innovation on consumer repurchase intention remain to be investigated (Chen et al., 2020). Second, the potential moderating role of green awareness in strengthening or weakening the relationship between green advertising, brand loyalty, equity, innovation, and repurchase intention needs further research (Alemsiyah et al., 2021). Third, while green satisfaction is known to be pivotal in influencing consumer behavior (Chen et al., 2020), its moderating effect requires further empirical research, especially on the relationship between green marketing and green loyalty. This research is conducted in Iran (HB Board Company) and specifically focuses on the construction products sector. This sector was appropriately selected due to its significant contribution to the Iranian economy and environmental degradation. Although the direct effect of green marketing on green advertising, green brand loyalty, green equity, green brand innovation, and consumer repurchase intention has been studied, the potential moderating effects of green awareness and green satisfaction on these relationships still need to be investigated. Understanding these moderating effects is crucial for businesses seeking to optimize their green marketing strategies and foster stronger consumer loyalty to environmentally responsible brands; therefore, the present study identified gaps in the moderating role of green awareness in the relationships among green advertising, green brand loyalty, green equity, green brand innovation, and consumer repurchase intention that need to be better understood. There is a need to examine how different levels of green awareness affect these links to inform marketing strategies to better target repurchase intentions. Furthermore, the effect of green satisfaction as a moderating factor in the relationship between green marketing and green loyalty has not yet been fully explored. Gaining insight into this relationship can help businesses understand how consumer satisfaction with environmentally friendly products or services enhances green loyalty; therefore, the present study aims to investigate the effects of green marketing on consumer repurchase intention with the mediating role of green marketing strategies. Theoretical Framework Green Marketing and Green Repurchase Intention According to Rahbar and Vahid (2011), eco-labeling is a powerful tool to reduce knowledge asymmetry between consumers and sellers. Secondly, an eco-brand is a name, symbol or design attached to products not harmful to the surrounding ecosystem. Consumers may find it easier to distinguish eco-brands from other types of goods by using features that distinguish eco-brands from other types of products. According to Chatterjee (2009), consumers will be more motivated to choose environmentally friendly alternatives to products with a high level of environmental impact than those with a low level of environmental impact. Based on a previous survey conducted by Rahbar and Vahid (2011), consumers in Malaysia consider the categories of products made of glass, household cleaning products, aerosols, chemicals and plastics as non-green product classes that are highly harmful to the environment. Advertising about the environment helps to form consumer values ​​and transforms those values ​​into purchasing environmentally friendly items. According to Pancić (2023), environmental signals in commercials and product labeling sometimes influence the purchase choices of 70% of respondents. Research Methodology The present study is applicable in terms of purpose, descriptive in terms of data analysis, and of the correlation type (structural equation modeling). The statistical population of this study, consumers of green products in Iran, was collected using an online survey distributed via Google Forms. The present study surveyed consumers of HB Board, a company that markets green products. HB Board offers environmentally friendly building materials and uses sustainable resources. The survey was shared through various channels such as social media platforms and email invitations to reach a diverse sample of respondents. In addition, a consent letter was attached to the survey to increase the response rate. This letter provided information about the purpose of the study and assured the respondents that their participation was voluntary and that their responses would be kept confidential and used exclusively for research purposes. Considering that the statistical population of the present study is unlimited, the statistical sample size of the study was 384 people based on Morgan's table. Therefore, the present study used a non-probability sampling method known as convenience sampling to select participants, where the survey link was shared through social media platforms, online forums, and email invitations. Research Findings Data analysis was conducted at both descriptive and inferential levels, including structural equation modeling. The results showed that green marketing positively affected all green outcomes, and green advertising, brand loyalty, brand equity, and brand innovation had a positive effect on repurchase intention. However, it did not find a significant moderating effect of green awareness on green brand equity and green repurchase intention. Conclusion The present study aimed to investigate the effect of green marketing on green repurchase intention. The findings of the present study are consistent with previous studies that show that companies engaging in green marketing have a positive impact on various aspects of green consumer behavior, including green repurchase intention, green advertising, green brand loyalty, green brand equity, green innovation, and green branding (Mahmoud et al., 2024; Ramadan et al., 2024; Hu et al., 2024; Huang et al., 2024; Molana and Haryadi, 2024). This suggests that companies can focus on something other than increasing green awareness to improve their brand and increase consumer intention to repurchase their products. These findings can help companies develop more effective green marketing strategies, enhance their brand, and increase consumer willingness to repurchase their products. Given the varying levels of green awareness and global perceptions, it will be interesting to see whether these findings are consistent across cultures and regions.

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