Journal of New Approaches in Management and Marketing

Abstract The present research aims to design a dynamic model for Green Human Resource Management (GHRM) within organizations. In terms of purpose, this study is applied-developmental, and methodologically, it is a qualitative-exploratory research. The study population consists of 15 academic experts and senior human resource managers, selected through snowball sampling. Data were collected via semi-structured interviews and analyzed using thematic analysis with MAXQDA software, following the process of open, axial, and selective coding. The findings revealed that the dynamic GHRM model comprises six key dimensions: “Green Competencies,” “Environmental Organizational Culture,” “Green Management Support,” “Green Job Engagement,” “Sustainable Performance Feedback,” and “Structural Flexibility.” The analysis of themes and the network of codes indicate that these dimensions operate as a continuous learning-interactive cycle rather than a linear progression; they enhance organizational sustainability through feedback mechanisms, adaptive processes, and cultural institutionalization. By providing a qualitative and contextualized model, this research fills the existing theoretical gap in GHRM literature and offers a conceptual roadmap for the systematic, adaptive, and sustainable implementation of this approach in organizations within developing contexts.

Abstract The objective of the present study is to identify and prioritize the factors influencing the success and failure of platform ecosystems in technology firms. The research method, in line with its purpose, is applied–developmental, and in terms of its nature, follows an exploratory mixed‑method design (qualitative–quantitative). The statistical population includes 15 industry and academic experts in the qualitative phase and 12 experts in the quantitative phase. A semi‑structured interview was used as the data collection instrument. For data analysis, thematic analysis was conducted in MAXQDA 2024 in the qualitative phase, and in the quantitative phase, the factors were prioritized using the fuzzy analytic hierarchy process (FAHP). Four‑scenario sensitivity analysis and Friedman and Spearman tests were employed to validate the robustness of the results.Findings from the qualitative phase indicate that 36 open codes, 12 sub‑themes, and ultimately 6 success factors and 6 failure factors were identified. The quantitative results show that the most important success factors are, respectively, “positive network effects” (weight = 0.382), “transparent and fair governance” (0.245), and “effective complementor management” (0.163). Conversely, the key failure factors consist of “multi‑homing migration” (0.351), “unsustainable revenue model” (0.228), and “negative network effects” (0.175). The consistency ratios of the matrices (CR = 0.05 for success and CR = 0.07 for failure) indicate acceptable reliability in the judgments.A three‑layer integrated framework was proposed comprising, for success: foundational prerequisites, core drivers, and sustaining mechanisms; and for failure: primary threat, structural threats, and contextual threats. Platform managers should prioritize strengthening positive network effects, enhancing governance transparency, and mitigating multi‑homing migration.

Abstract In today's highly competitive markets, managers are looking to make people aware of their products and improve their brand. One of these methods is social media, which has created a great transformation in the field of business and electronic marketing. Brand equity is a valuable but intangible asset of any company, understanding brand equity is a major task for many organizations. Therefore, the purpose of this research was to investigate the impact of social media communication on brand equity through the mediation of electronic verbal advertising and the moderation of product mental involvement. The statistical population of the current research were dairy products customers of Yazd province who have used its products for at least one year and are present on social media, whose exact number is not known. Therefore, the number of members is 384 and is considered available by sampling method. The data collection tool was a questionnaire taken from the research of Lin et al. (2023). Convergent and divergent validity and factor analysis were used to measure face validity according to experts and regarding construct validity. Cronbach's alpha and composite reliability were used to measure reliability. Data analysis was done with SmartPLS3 software. The results showed that the co Firm-generated content as well as the user has a significant impact on electronic word of mouth and brand equity. The effect of electronic word of mouth on brand equity was significant. The Firm-generated content and the user has been significant through the mediating role of electronic word of mouth on brand equity. Finally, the role of moderator of product involvement in the relationship between the Firm-generated content, and the user and the brand equity.

Abstract Abstract
This study aims to examine the experiences and influential factors shaping young people’s transitions from traditional employment to freelancing. The statistical population consists of 28 Iranian experts in the field of freelancing. Data were collected through semi‑structured interviews using purposive sampling and continued until theoretical saturation was reached. The qualitative method applied in this study was thematic analysis based on Braun and Clarke’s standard framework, and coding and analysis were conducted using Atlas.ti software.
The analysis of findings revealed four strategic dimensions that provide a comprehensive perspective for understanding freelancing:
(1) push factors and decision‑making in career transition;
(2) significant economic and financial challenges during the transition process;
(3) skill development and professional networking; and
(4) economic empowerment outcomes for youth.
The results indicate that transitioning from traditional employment to freelancing is a complex and multilayered process requiring precise and purposeful planning, strong social and professional network development, and the establishment of supportive governmental and political environments. The comprehensive strategic framework presented in this study can serve as a practical and evidence‑based guide for policymakers, entrepreneurs, and stakeholder organizations—including chambers of commerce and labor unions—to more effectively support young individuals during this career transition and to improve conditions for the development of freelancing.
Introduction
Over the past decade, a transformative shift—both morphological and structural—has emerged in the global labor market, placing independent entrepreneurship and freelancing at the forefront as key solutions. In Iran, as the knowledge‑based economy, modern digital technologies, and internet‑driven economic infrastructures rapidly expand and evolve (Khodaparast & Emadi, 2025), young people are increasingly and noticeably gravitating toward freelancing, autonomous work, and self‑directed employment, considering these pathways as preferred career choices.
These new forms of employment and career transitions, despite offering advantages such as flexibility and autonomy, are accompanied by complex and profound challenges that pose difficulties both for young individuals and for the global economy (Yang et al., 2024). Income instability, lack of access to conventional employment benefits such as health insurance and unemployment insurance, high levels of economic vulnerability, and the absence of formal support structures are among the most significant challenges (Lu et al., 2024).
Accordingly, the central research question is formulated as follows: How does the transition of Iranian youth from traditional employment to freelancing lead to economic empowerment?
Theoretical Foundations
Independent Entrepreneurship
Independent entrepreneurship, or freelancing, refers to a modern approach to business and autonomous work in which an individual, as an independent entrepreneur, undertakes various projects for multiple clients. In this model, the individual operates as a self‑directed professional, performing diverse tasks for different and numerous clients (Baitenizov et al., 2025; Öberg, 2018).
Career Path
Various perspectives exist regarding career paths, each emphasizing one or several dimensions of occupational development. Holland’s Theory of Career Choice highlights the alignment between an individual’s personality and their work environment, proposing that people are naturally drawn to occupations that match their personality types—such as realistic, investigative, artistic, social, enterprising, or conventional. This theory conceptualizes career choice primarily as a voluntary and individually driven process based on person‑environment fit; however, it pays limited attention to external pressures and involuntary career transitions.
Economic Empowerment
Economic empowerment is a broad and multi-layered concept that refers to the process by which individuals acquire and activate the ability, authority, and capacity to plan, make independent decisions, and control their own economic resources (Golara et al., 2025; Saffari Darberazi et al., 2025).
Research Methodology
This qualitative study employed the thematic analysis method within the standard framework developed by Braun and Clarke (2006), utilizing the Atlas.ti software. A qualitative approach was selected for this research to gain an in-depth, internal understanding of the lived experiences, motivations, emotions, and meanings held by participants (Clarke & Braun, 2021). This established framework for thematic analysis has garnered over 20,000 academic citations to date and represents a scientific and systematic method for identifying semantic patterns and latent themes within qualitative data (Foroozanfar et al., 2025).
The study utilized purposive sampling. The statistical population comprised individuals holding at least a bachelor’s degree and currently engaged in freelance work. In this research, the criterion for concluding the sampling process was the achievement of theoretical saturation, as defined within Braun and Clarke’s (2006) thematic analysis framework. The sampling process unfolded iteratively and in parallel with the coding phase. Following approximately 22 initial interviews, no significant new codes were added to the initial coding structure, and the primary themes began to repeat. Subsequently, conducting 6 additional interviews provided richer data and new contextual examples but did not yield any novel conceptual codes or themes, indicating theoretical saturation at the level of the main themes.
Research Findings
Through the analysis of 28 interviews conducted with the target population and audience, followed by a textual analysis of the interview transcripts, 11 initial themes were identified. In aggregate, these sub-themes represent four main dimensions, illustrating that the transition from traditional employment to freelancing among Iranian youth is not a simple linear process. Instead, it is a chain of transitions where push factors and liberating motivations, in conjunction with economic and institutional challenges, are navigated through skill and network development. This ultimately leads to outcomes of relative empowerment or [outcome not specified in text]. Consequently, freelancing in this study is understood not merely as an opportunity nor solely as a threat, but as a dynamic and conditional field whose quality of experience is contingent upon a specific combination of individual, network, and structural circumstances.
Discussion and Conclusion
The results of this research indicate that the transition from traditional, conventional employment to freelancing for Iranian youth is a complex, multi-layered, and arduous process that demands considerable attention, meticulous and purposeful planning, and substantial support. The key findings are as follows: Firstly, diverse and varying push factors are significant—negative push factors (fear of instability, dissatisfaction) are as important as positive ones (freedom, income). Secondly, considerable economic challenges, such as income instability and the lack of benefits, represent fundamental dilemmas requiring innovative solutions. Thirdly, essential social capital, along with strong professional and social networks are crucial for success and economic empowerment. Fourthly, balanced economic empowerment and genuine self-sufficiency necessitate a combination of financial independence, a sense of control, and economic security.
In comparison to previous research, the findings of this study regarding the importance of networking underscore the vital and fundamental role of social capital in freelancing. These results corroborate Golara’s (2025) research on the role of “weak ties” and professional networks in job seeking. Furthermore, our findings concerning the essential role of social and professional networks, the importance of continuous skill development and learning, and the fear and concern regarding income instability show significant similarities with studies conducted in other countries (Baitenizov et al., 2019; Morris et al., 2025). However, fundamental differences also exist. It can be argued that in Iran, negative push factors are stronger, whereas in developed countries, positive factors are more prevalent.
The findings of this research have important implications for policymakers and support organizations, presented below based on the study’s outcomes:
Based on the findings and themes from the push factors and decision-making dimension, a significant portion of youth transitioning to freelancing stems from dissatisfaction with the rigid structures and bureaucracy of traditional employment. Therefore, it is recommended that governmental and private organizations revise their human resource policies. By developing flexible work models (remote work, flextime, project-based work) and reducing unnecessary procedures, they can mitigate some of the push pressures. This would help transform freelancing from an option often driven by compulsion or escape from structure into a conscious and strategic choice.
Based on the themes from the economic challenges dimension, considering the fundamental role of income instability and the lack of benefits in undermining the economic empowerment of freelancers, it is proposed that policymaking institutions such as the Ministry of Labor, the Social Security Organization, and the Chamber of Commerce move towards designing insurance and support mechanisms tailored for freelancers. This includes flexible health and retirement insurance and adaptable premiums based on actual income, thereby partially reducing the gap between occupational freedom and social security.
Furthermore, findings based on the skill development and networking dimension indicated that success in freelancing depends on a package of technical, soft, and business skills, as well as robust professional networks. Consequently, it is recommended that universities, skill training centers, and science and technology parks design and implement comprehensive freelancing preparation courses, including training in negotiation, project management, personal marketing, and professional networking skills. They should also foster the development of social capital for freelancers by creating networking spaces, such as internal events and platforms.
Also, based on the themes from the economic empowerment outcomes, given that economic empowerment is experienced as relative and conditional by participants, it is suggested that policymakers and freelancing platforms develop indicators to monitor the quality of freelance livelihoods, including relative income stability and access to social support. Based on these indicators, programs to enhance the welfare and job security of freelancers should be designed, ensuring that the transition to freelancing systematically leads to improved well-being rather than merely a change in the form of insecure work.
Based on the results of this research, suggestions for other researchers interested in the field of freelancing are presented as follows: conducting longitudinal studies to track the career paths of youth over longer periods; examining the potential of freelancing for women and conducting specific research on the unique barriers faced by female freelancers; analyzing the role of new technologies, artificial intelligence, and automation on the future of freelancing; investigating public sector support policies; conducting cross-country comparative studies to benchmark and assess efficient and diverse freelancing methods; and examining the social effects of freelancing on family and social relationships.

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.

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.

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.

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. 

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 

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.

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).

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.

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

Abstract Abstract The aim of the present study was to design an influencer marketing model based on the behavior of mountaineering product consumers with a data-based approach. The research method was qualitative and based on grounded theory. The statistical population included experts in the field of influencer marketing evaluation, faculty members, marketers, and manufacturers of mountaineering products. Sampling was purposefully conducted using the data saturation technique, and 12 people were selected for in-depth semi-structured interviews. Data analysis was conducted using the grounded theory method. The findings showed that 46 initial codes were extracted in the form of 15 main categories, which are: perceived credibility and expertise, value alignment, content quality and honesty, characteristics of the mountaineering community, nature of mountaineering products, advertising saturation in social networks, previous consumer experience, level of personal knowledge and expertise, perceived risk, mutual verification, direct communication and observation, use of established influencers, increase or decrease in trust in the influencer, change in attitude towards the brand, and decision to buy or not to buy. The results showed that the impact of influencers on consumer behavior is very deep and fundamental, depending on the characteristics of the target population such as children, adolescents, women and men. The findings can help brands and marketers to create more effective interaction with audiences and improve influencer-based marketing strategies by identifying effective criteria. Introduction Today, social media is known as the turbulent helm of the Internet; media that are based on web technology and play a fundamental role in the world's media equations by virtual sociality (Karimi et al., 2025). Based on Matthews' theory (2012), in the article Guide to Identifying Influencer Goals, it has been determined that consumers trust third-party recommendations (influential person) on a blog or Instagram or all social networks more than their paying attention to a brand (Duh et al., 2021). Social media influencers can be connected as friends or consumers in order to achieve the marketing goals of a brand and, due to their reputation, they can bring together not only fans of their specific field of activity but also a wide network of followers in their virtual space and, by taking advantage of their influence, direct people to the website or product of the related brand and increase the volume of social media exposure and introduce and promote the company's product through their recommendation or story according to their experience with the product or the manufacturer (Masoumi et al., 2023). On the other hand, sport has entered the field of economic science and art by introducing its new social values. The obvious and hidden attractions resulting from this development have aroused feelings and created certain tendencies among all societies towards sporting events (Zeithaml & Bitner, 2023). In order to effectively achieve global trade, sports and non-sports marketing organizations (including mountaineering disciplines) have greatly benefited from marketing opportunities such as sponsors of sports competitions, broadcasting rights and product endorsements by athletes and "social media influencers" in the field of marketing mix and consumer behavior (Alidoost Zoghi et al., 2021). When a product is noticed and supported by a famous sports star, effective conditions will be provided for persuading fans and others to buy that product through psychological connection with fans. In other words, a product based on the advertising or emphasis of a social media sports influencer will have two characteristics: uniqueness and value among his fans and followers in the online space. Accordingly, marketers and stores of sports products such as mountaineering products are seeking to improve marketing programs in order to increase sales of their products, control consumer behavior and have greater coordination between the consumer and the products produced by their brand, which is being formed and developed by influencers on social media (Khosravi et al., 2023). A review of research conducted in this field indicates that despite the increasing use of the effective capacities and capabilities of "social media influencer marketing on consumer behavior", there are no precise criteria for measuring this type of marketing, and due to the new emergence of this phenomenon in the field of sports products, especially mountaineering products, deep and extensive research has not been conducted (Anggraheni & Haryanto, 2023). Accordingly, the researcher aims to design and explain the influencer marketing evaluation model based on the consumer behavior of mountaineering product users, taking into account the aforementioned issues and based on issues such as the fundamental challenge of marketers and researchers in identifying influencer marketing criteria and indicators and the lack of specialized knowledge in this field, and the measurement and evaluation model for social media influencer marketing in the field of mountaineering and sports products using the data-based method to show what the influencer marketing evaluation model is based on the consumer behavior of mountaineering product users; and how the causal conditions, background conditions, intervening conditions, strategies, and consequences of the influencer marketing evaluation model based on the consumer behavior of mountaineering product users will be explained. Theoretical Basis Influencer Marketing Influencer marketing is a marketing strategy in which businesses collaborate with influential people on social networks or other platforms to introduce and sell their products, services, or brands to the influencer's audience (emad et al., 2024). Influencer marketing is not limited to a specific medium or platform, but many people recognize and apply the concept more in the social media space (pick et al., 2021). Consumer Behavior Consumer behavior refers to the actions of individuals or groups in acquiring, consuming, and disposing of economic goods and services, including the decision-making processes before and after these actions. Consumer behavior is the study of consumers and the processes they use to select, use (consume), and dispose of products and services, including consumers' emotional, mental, and behavioral responses. Consumer behavior includes ideas from several sciences, including psychology, biology, chemistry, and economics. Consumer behavior is the study of how individuals, groups, and organizations purchase, use, and consume ideas, goods, and services to satisfy needs and wants (Divandari et al., 2023). Kamali et al. (2025) investigated “Factors Affecting Intention to Purchase FMCG from Online Retailers (Case Study: Kale Dairy Products)”. This research was conducted using a descriptive-survey method and structural equation modeling. The results showed that situational variables such as system quality and product familiarity have a significant effect on perceived usefulness, but they had no effect on perceived hedonicity. It was also found that perceived usefulness and hedonicity mutually affect each other and both have a positive effect on consumers’ purchase intention. Abrood et al. (2024) investigated the “Effect of Social Media Marketing on Consumer Behavior with Respect to the Mediating Role of Brand Value”. The descriptive-correlational research method and data analysis were conducted using path analysis. The results showed that social media marketing has an effect on consumer behavior. However, entertainment did not have a significant effect on brand awareness and image, and favorable information only had a positive effect on brand image. Also, word-of-mouth marketing had a significant effect on brand awareness and image. Finally, both brand awareness and image had a positive and significant effect on brand preference and brand loyalty. Research Method The present study was qualitative and based on Grounded Theory. The statistical population included experts in the field of influencer marketing, faculty members, marketers, and manufacturers of mountaineering products. Twelve people were selected by purposive sampling and using the data saturation technique. Data were collected through semi-structured in-depth interviews and continued until information saturation was reached. Data analysis was conducted using the Strauss & Corbin (1998) method and three stages of open, axial, and selective coding. In open coding, interview phrases were transformed into abstract concepts; in axial coding, concepts similar to composition and components were formed; and in selective coding, final categories including causal, contextual, intervening factors, strategies, consequences, and central phenomenon were extracted. To increase the validity of the research, criteria of validity, reliability, verifiability, and transferability were used. The opinions of professors and colleagues were considered in reviewing the codes and analyses, and all stages of the research were documented to provide verification and replication.  Findings The research shows that influencer marketing plays an important role in shaping consumer behavior of mountaineering products. The effect of this marketing depends on the influencer's credibility and expertise, value alignment, content quality, customer experience and knowledge, and risk perception. Effective engagement and the provision of authentic content increase trust, change brand attitudes, and purchase decisions. Strategies such as direct observation, verification, and leveraging established influencers enhance marketing effectiveness. This research provides a practical and theoretical framework for designing and evaluating influencer-based marketing. Discussion and Conclusion The present study aimed to design an influencer marketing model based on the behavior of consumers of mountaineering products and was conducted with a grounded theory approach. The findings showed that in the field of specialized and high-risk products such as mountaineering equipment, the success of influencer marketing does not depend solely on their reputation or number of followers, but rather on the authenticity, honesty, and effectiveness of the content produced by the influencer. Experienced consumers make their purchase decisions based on their perception of the expertise and real credibility of influencers, and their trust in the experience and technical knowledge of these people plays a central role in the effectiveness of marketing messages. Data analysis showed that the three main factors of "perceived credibility and expertise", "value alignment", and "content quality and honesty" have the greatest impact on consumer behavior. Consumers respond positively to marketing messages when the influencer has practical experience in mountaineering, provides expert and honest content, and their ethical values ​​and lifestyle are consistent with their own. These findings are consistent with research by Anggraheni & Haryanto (2023), Yazdani Kachuei et al. (2022), and Masoumi et al. (2023), and confirm the importance of expert trust and value congruence in forming consumer loyalty and emotional attachment. Contextual factors, including characteristics of the mountaineering community, the nature of products, and advertising saturation on social networks, as well as intervening conditions such as personal experience and knowledge, and perceived risk, play an important role in evaluating advertising messages. Consumers make their purchase decisions using strategies such as verification, comparison of different sources, and actual observation. Finally, the final research model showed that the perception of authenticity and effectiveness of influencers’ messages is affected by causal, contextual, and intervening factors, and by adopting specific strategies, it leads to outcomes such as increased or decreased trust, changed brand attitude, and purchase decision. These results are consistent with the findings of Emad et al. (2024) and Divandari et al. (2023) and show a new dimension of trust in influencers’ experience and expertise in specialized sports markets.

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