Journal of New Approaches in Management and Marketing

Abstract The purpose of this article is to develop a coherent conceptual framework for the typology of consumer behavior during the processing of packaging information, with a particular focus on the cultural and social characteristics of the Iraqi market. Using a theoretical‑analysis and literature‑synthesis approach, this study addresses the existing gap in the classification of message‑processing patterns.

The proposed framework is built on two key dimensions—“depth of information processing” (shallow vs. deep) and “focus domain” (cognitive vs. affective)—resulting in the identification of four distinct behavioral types: the Cautious Analyst, the Committed Evaluator, the Minimal Seeker, and the Environmental Scanner.

Drawing on cultural theories (such as high‑context culture and collectivism), conceptual hypotheses are formulated suggesting that the prevalence and behavior of each type in Iraq are strongly shaped by social trust (source credibility) and group‑identity requirements, rather than solely by explicit textual messages on packaging.

The findings offer essential managerial insights for designing effective packaging that aligns with the region’s cultural norms.

Abstract The banking sector is undergoing a fundamental transformation driven by the integration of artificial intelligence into financial service processes. AI enhances operational efficiency, risk management, and customer interaction. Accordingly, the present study was conducted with the aim of developing an AI‑based model for Rafidain Bank, supported by the assurance of strengthened marketing capabilities, using an emergent grounded‑theory strategy.

The study population consisted of fifteen Rafidain Bank managers and experts, along with academic elites in Iraq, who were selected through snowball sampling and participated in semi‑structured interviews. The collected data were analyzed through three stages of open, axial, and selective coding, using MAXQDA 2024 and relying on latent content analysis techniques.

The findings led to the development of conceptual categories including AI adaptability, AI sustainability, AI user experience, AI capability, the bank’s future‑orientation, AI knowledge, and effective bank performance, resulting in ten novel core hypotheses among these constructs.

The results demonstrate that AI‑driven marketing capabilities are becoming increasingly prominent and serve as the primary antecedents of effective performance for Rafidain Bank in this study.

Abstract At the dawn of the twenty‑first century, the rapid surge in information and communication technologies and Industry 4.0 digital innovations led to the widespread adoption of smart home technologies across societies, creating a major transformation in the housing sector. Accordingly, the present study sought to develop a grounded theory model of the social acceptance of smart home technology among Iraqi consumers, based on an interpretivist paradigm.

The study’s statistical population consisted of fifteen experts in smart home technology and university faculty members specializing in marketing. Participants were selected using the snowball sampling method and took part in semi‑structured interviews. The collected data were analyzed using the latent content analysis technique in MAXQDA 2024 through three stages of open, axial, and selective coding.

The findings led to the emergence of several key conceptual categories: smart home technology acceptance, perceived trust and security, lifestyle‑integration behaviors, economic decision‑making, and responses to social influence. Based on these categories, seven new core hypotheses were formulated. The results demonstrated that the central category, “social acceptance of smart home technology,” represents a multidimensional construct shaped by cognitive, social, and innovation‑related factors.

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

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

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 purpose of the present study is the Network Analysis Process (DANP) Sustainable Development Model Based on Quantum Management Approach. The research method is applicable-developmental in terms of its purpose, descriptive in terms of data collection, and quantitative in terms of implementation method. The statistical population of the study includes 10 municipal managers with at least 20 years of experience and their field of specialization is urban management, selected through purposive sampling. To collect data for the DEMETL section and the network analysis process for prioritizing variables, a standardized AHP paired comparison questionnaire was used and distributed to the statistical population of the study and, after completion, collected and analyzed. The DENP method (a combination of DEMETL and the Analytic Network Process (ANP)) was used to prioritize the effective factors. The results showed that urban infrastructure development, self-organization, urban governance and legislation, quantum knowledge, improving the quality of life, economic infrastructure development, social justice and participation, and improving environmental quality are in the first to eighth priority, respectively. Introduction The success of today's organizations depends on correct and efficient leadership that relies on influencing, guiding, directing, and streamlining the organization's activities, and the beliefs and convictions of employees. Quantum management, influenced by the quantum paradigm, has unique features that can meet the needs of leaders and organizations, especially government organizations, in today's ambiguous, uncertain, and rapidly changing conditions in order to achieve goals and organizational excellence (Madahiyan et al, 2021). The quantum perspective views the world as complex, living, highly interconnected, dynamic, describes as self-constructive and unpredictable, so that in this perspective, organizations must have a learning structure. Quantum management is a practice that, by creating human capacity, focuses more on the free and continuous interaction between the leader and employees, as well as the mutual influence of the internal dynamics of the organization with employees and vice versa; and by emphasizing the organization, it guides it towards a desirable future (Norouzzdeh et al., 2020). Following the development of cities, the speed of physical changes in the city, and the changing needs of citizens in various social and economic fields, comprehensive urban plans based on the principles of past years cannot meet the needs of cities; for this reason, such plans have been obsolete for decades and are not applicable, so their characteristics do not lead to improving the quality of living space in today's era (Ghadiri et al., 2021). The field of many urban researches is sustainable development, and the ideal attitude of urban planners and designers in designing sustainable cities is mainly on better living and reducing environmental crises (Bikdeli et al., 2018). Therefore, quantum management, which is a new management in line with the needs of the people and in harmony with the era of electronics and knowledge-based networks, can contribute significantly to sustainable development and a new approach to urban management. In this type of management, hierarchies and bureaucracies will be eliminated. Also, each person does what he specializes in, and the relationship is not the criterion for selecting individuals (Nazmfar et al., 2019). A quantum manager is a person who can make the best decision in the shortest time and has the power to resolve contradictions. In addition, he is a transparent and honest person and shares his decisions with the people and asks for their advice. Therefore, the solution to solving the current problems of urban management can be considered to be the use of strategic plans with the quantum management approach, and urban management should move towards creating small-scale structures with a wide scope of authority in the form of neighborhoods. Therefore, to prepare any plan for the development of the city, it is necessary to first of all gain knowledge. The knowledge in the urban planning system must be comprehensive and complete, so all dimensions of the city, including the city structure, uses, accesses, urban landscape, as well as the social, demographic, economic, managerial dimensions, etc., must be considered (Bahrini, 2022). Accordingly, the researcher addresses the main question: what is the network analysis process (DANP) of the sustainable development model based on the quantum management approach? Theoretical framework Sustainable development The concept of sustainable development means a process of change in which the exploitation of resources, the direction of investments, the orientation of technological development, and institutional changes are coordinated and increase the current and future potential to meet human needs. Sustainable development means the management and protection of basic resources and the introduction and application of technological advances and organizational structures through which human needs can be continuously and reasonably guaranteed for the present and future generations. (Roozbeh et al, 2023). Quantum Management Quantum management is a set of fully operational skills for managers appropriate for the characteristics of organizations in the last century. This metaphor for the behavior of managers is derived from quantum theory, which is derived from the field of physics. Quantum management increases the level of employee empowerment and at the same time provides the basis for consultation and synergy by employees and managers (Ali sofi & Salimi, 2023). Rasouli et al. (2024) examined the antecedents and consequences of professional competence of school administrators with an emphasis on environmental sustainability and sustainable development. The research findings showed that the professional competency model of managers includes the enablers of skill competency, management competency, and professional ethics and behavior competencies, manager development, social characteristics of managers, establishing work groups to improve performance and green competency, attitudinal competencies, knowledge competencies, educational competencies, knowledge-skill and technology commercialization competencies, high-work ethic, consumption pattern reform, participation in development, and movement toward national authority; which lead to the realization of the results of high-work ethic, consumption pattern reform, participation in development, movement toward national authority, diversity and pluralism management, and strengthening the relationship between humans and nature. Ali sofi & Salimi (2023) studied the effect of quantum management skills on readiness for change with the mediating role of organizational agility. The findings from the structural equation model showed that the standard coefficient between quantum management on readiness for change (0.19), quantum management on organizational agility (0.58), as well as readiness for change and organizational agility (0.64), and the indirect effect of quantum management on readiness for change (0.47) were significant.  Research Methodology The research method is applicable-developmental in terms of its purpose, descriptive in terms of data collection, and quantitative in terms of implementation method. The statistical population of the research includes 10 municipal managers with more than 20 years of experience and their field of specialization is urban management, selected through purposive sampling. A standardized AHP pairwise comparison questionnaire was used to collect data from the DEMETL section and the network analysis process to prioritize variables, and was distributed to the statistical population of the research and, after completion, collected and analyzed. Research findings The DANP method (a combination of DEMETL and the Analytical Network Process (ANP)) was used to prioritize the effective factors. The results showed that urban infrastructure development, self-organization, urban governance and legislation, quantum knowledge, improving the quality of life, economic infrastructure development, social justice and participation, and improving environmental quality are in the first to eighth priority, respectively. Conclusion The present study was conducted with the aim of the Analytical Network Process (DANP) model of sustainable development based on the quantum management approach. The results of this study are consistent with the results of Rasouli et al. (2024), Ali sofi & Salimi (2023), Roozbeh et al. (2023), Hajizadeh Majdi et al. (2023), Negahdarandeh & Anvari (2022), Nazarzadeh et al. (2021), Bahrini (2022), Shafiepour & Parhemat (2022), Dixon & Tewdwr-Jones (2021), and Rodríguez et al. (2019). Shafiepour & Parhemat (2022) showed that the characteristics of quantum management have a positive and direct impact on the three individual, social and organizational levels of human resource development, that is, by increasing quantum management techniques, the three individual, social and organizational levels of human resource development are improved. According to the results of the research, the following suggestion was made: -Reconstruction and modernization of worn-out water, electricity, gas and telecommunications networks to increase resilience to crises. -Creating comprehensive roadmaps for infrastructure development, taking into account population growth and future needs of the city. -Delegating more authority to local institutions and city councils to solve regional issues and encourage active citizen participation.