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

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

Abstract Abstract
The 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 objective of the current research is destination branding for health tourism in medical centers of Yazd province. The present study is based on the pragmatism paradigm with an exploratory orientation, conducted as developmental research in a cross-sectional manner using a survey approach (interviews) through field studies; the research strategy was projective technique, and data collection was performed using semi-structured, in-depth interviews with 12 experts in health tourism and destination branding who were selected through purposive sampling; at this stage, the sample size was determined based on the theoretical saturation rule, and after three-level coding (open, axial, and selective), this concept was developed; the research findings indicate the necessity of attention to infrastructure factors, cultural factors, and economic factors as variables of health tourism destination country, tourism factors and destination branding factors of the city, advertising, sales promotions, brand communities, and public relations as communication tools variables, as well as physicians and nurses, medical center staff, and managers as human resources variables, and medical equipment/facilities and services as product/service variables.
Introduction
In today's world, health tourism is recognized as one of the most prosperous global industries, attracting millions of people annually to various destinations for medical services (Patterson & Balderas-Cejudo, 2023). Within this context, health tourism destination branding has emerged as a critical factor in attracting both domestic and international patients while creating sustainable competitive advantages for medical centers. A primary concern for health and tourism policymakers is establishing medical destinations as preferred and trustworthy options in the minds of global audiences through effective branding strategies.
Despite Iran's significant potential, particularly in Yazd province, for attracting health tourists, limited research has systematically examined the factors influencing destination branding in this context. A review of existing literature reveals that cultural perspectives and elements - themselves influenced by environmental changes - significantly impact branding. As Wijaya (2024) demonstrated, successful branding strategies can create innovative, distinctive products that foster loyalty among target audiences. Similarly, Ailawadi & Keller (2004) investigated how branding strategies create unique positions for brands across various sectors, contributing to sustainable competitive advantage.
Theoretical Framework
Branding
The rapid changes and transformations at the end of the second millennium, coupled with the emergence of new global challenges, have revealed the limitations of traditional forecasting-based planning methods (Linkon et al., 2024). This constant evolution creates an ongoing need for individuals to adapt to environmental changes (Kindström et al., 2024).
Tourism Destination Branding
Destination branding focuses on creating perceptions or reputations that attract investors and tourists. A strong destination brand serves as an effective tool for differentiation and developing emotional connections with consumers (Darwish & Burns, 2019).
Health Tourism Destination Branding
Health tourism, defined as travel for physical and mental health purposes lasting between 24 hours and one year, represents a rapidly growing sector of the tourism industry (Sattari et al., 2020).
Research Methodology
This exploratory qualitative study adopts a developmental approach within the pragmatism paradigm. Utilizing inductive reasoning and taxonomic modeling, the research employed projective techniques and expert interviews to develop the concept of health tourism destination branding. The cross-sectional field study involved purposive sampling of 12 experts (following theoretical saturation principles) from academia and healthcare management in Yazd province (Table 1).

Credibility: Verified through member checking with participating experts
Transferability: Ensured through peer review by university professors
Dependability: Established through audit trails by two external reviewers
Inter-coder reliability: Achieved >0.7 agreement between independent coders

Findings and Discussion
Analysis of 60-90 minute interviews (recorded with participant consent) yielded 60 open codes, subsequently categorized into 14 axial and 5 selective categories (Table 2). The study identifies critical success factors including:

Infrastructure, cultural, and economic considerations
Tourism and destination branding elements
Communication tools (advertising, promotions, PR)
Human resources (medical staff, administrators)
Service quality and medical facilities

Conclusion
Yazd province - and Iran more broadly - possesses the medical expertise, competitive pricing, and cultural attractions to become a regional health tourism hub. However, realizing this potential requires:

Strategic destination branding
Infrastructure development
Health diplomacy initiatives

The study provides a comprehensive framework for policymakers and healthcare administrators to enhance Iran's position in the global health tourism market through systematic destination branding approaches. 

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.