رویکرد‌های نوین در مدیریت و بازاریابی

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

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

Abstract The purpose of this study is to identify the dimensions and components of competitive advantage and innovation within the policy framework for creating and developing digital entrepreneurship in knowledge‑based companies. This research is applicable in terms of purpose, and qualitative in terms of methodology. The statistical population consists of 15 experts, including university faculty members in management and managers of knowledge‑based firms located in Kerman. Considering participants’ diversity (managers, faculty members, and employees), a purposive sampling method was employed, and interviews continued until theoretical saturation was reached. Data were collected through semi‑structured interviews and analyzed using coding and thematic analysis, facilitated by MAXQDA software. The findings reveal that the most significant themes in this domain include research and development, adoption of emerging technologies, creation of digital business models, data‑driven decision‑making, digital networking, cybersecurity, development of e‑commerce, digital management and online human‑resource systems, development of digital markets, digital investment, and attraction of digital financial resources. These results indicate that digital entrepreneurship in knowledge‑based firms encompasses multiple dimensions that can contribute to enhanced performance and competitiveness. Introduction With the expansion of digital technologies and their prominent role in the global economy, digital entrepreneurship has emerged as a key driver of economic and social development. In this context, knowledge‑based businesses—relying on innovation and competitive advantages—possess significant potential for value creation and sustainable development. However, the absence of a comprehensive and effective policy model for establishing and developing digital entrepreneurship in such firms represents a major challenge (Bagaini et al., 2022). As an emerging and rapidly evolving field, digital entrepreneurship requires specialized operational models tailored to the needs and characteristics of knowledge‑based enterprises. Many existing models have been designed in a general form and do not sufficiently address the specific context of digital entrepreneurship or the distinct nature of knowledge‑based firms. This lack of operational models often leads to confusion and difficulties in implementing digital entrepreneurship strategies (Merín‑Rodrigáñez et al., 2024). Innovation and competitive advantage are two critical factors in the success of knowledge‑based companies within the realm of digital entrepreneurship. Innovation is a key driver of growth for firms, enabling them to achieve future successes and providing a mechanism through which businesses can sustain their presence in the global economy (Sung & Kim, 2021). It helps companies secure competitive advantages in uncertain environments, outperform competitors; and ultimately influences long‑term organizational performance. Innovation is also the primary factor contributing to business growth (Eshkor Vakili & Nojabaei, 2022). The innovation process requires effective management and efficient use of resources and technologies. The lack of an effective model for managing and implementing innovation can diminish competitive capability and hinder the realization of a firm’s full potential. Competitive advantage refers to a firm’s ability to, compared to its competitors, deliver greater value to customers. Knowledge‑based businesses, particularly those engaged in technology and innovation, must identify and leverage their competitive advantages. However, many such firms face challenges in recognizing, analyzing, and operationalizing these advantages. These challenges often stem from the absence of an integrated and practical framework for analyzing and exploiting competitive advantages (Hoang & Böckel, 2024). Accordingly, the central question of this study is: How can the dimensions and components of competitive advantage and innovation be identified within the policy framework for creating and developing digital entrepreneurship in knowledge‑based companies? Theoretical Framework Digital Entrepreneurship Digital entrepreneurship refers to the process of creating and developing businesses that primarily focus on digital technologies and technology-based business models. This type of entrepreneurship involves utilizing the internet, digital software, online platforms, and emerging technologies to establish, launch, and grow new ventures (Sharma, 2022). Competitive Advantage Competitive advantage refers to an organization’s ability to create higher value than its competitors and achieve market superiority. This advantage enables organizations to differentiate themselves from rivals by leveraging unique resources and capabilities; thereby gaining a larger market share (Teece, 2020). Mir Jalali et al. (2025) investigated the design of a customer relationship management development model and the role of sustainable competitive advantage in sports clubs in Gilan province. The research findings indicated that 469 indicators could be effective in customer relationship management with an emphasis on sustainable competitive advantage in sports clubs in Gilan province. Subsequently, in the axial coding of indicators, they were categorized into 105 concepts and 41 categories. The data obtained from interviews were analyzed using the grounded theory approach. The results showed that seven main categories—Marketing, Organizational Environment, Infrastructure, Performance, Management and Planning, Service Quality, and Relationship Management—are important for optimizing the customer relationship management system to develop CRM with an emphasis on sustainable competitive advantage. Managers of sports clubs can utilize the identified indicators, concepts, and categories in their future planning for effective customer engagement. Abhkiz et al. (2024) examined the presentation of a competitive advantage model with a pioneering approach in Iran’s aviation industry. The results indicated that having an appropriate network and scope of air routes, flights, and airport services in the country; the possibility (capability) of technological sharing for producing modern aircraft; the technical and technological capabilities of the industry for pioneering; possessing strategic management vision and abilities for the industry to lead; having experience in joint cooperation with international consultants, companies, and governments; the willingness of statesmen and decision-makers in the industry to be pioneers; commitment to strategic plans by industry managers for pioneering; the aviation industry’s learning, adaptation, and future-gazing capabilities for pioneering; possessing skills and expertise among managers and human resources in the industry for pioneering; the number and composition of the air transport fleet; and having cohesive, integrated, and strategic marketing and branding plans in the industry have the most influence among variables on competitive advantage for pioneering. Research Methodology In terms of its objective, the research methodology is applicable; and in terms of execution, it is qualitative. The statistical population of the research includes 15 experts, university professors in management, and managers of knowledge-based companies in Kerman city. For sample selection, considering the diversity of experts (managers, professors, and staff), a purposive sampling method was used, and interviews continued until theoretical saturation was achieved. Semi-structured interviews were used for data collection. Research Findings For data analysis, coding and thematic analysis methods were employed, utilizing the Maxqda software. The results indicated that the most significant themes in this domain include Research and Development (R&D), utilization of new technologies, creation of digital business models, data-driven decision-making, digital networking, cybersecurity, e-commerce development, digital management and online human resources, digital market development, digital investment, and digital fundraising. These findings suggest that digital entrepreneurship in knowledge-based companies encompasses various dimensions that can contribute to improving the performance and competitiveness of these firms. Conclusion The present research was conducted with the aim of identifying the dimensions and components of competitive advantage and innovation in the policy-making for the creation and development of digital entrepreneurship in knowledge-based companies. These findings are consistent with the results of previous studies by Mir Jalali et al. (2025), Abhkiz et al. (2024), Hosseini et al. (2023), Masah Choolabi et al. (2023), Porter & Kramer (2023), Teece (2022), Snihur et al. (2022), Fartash (2022), Nambisan & Baron (2021), and Ciriello et al. (2021). Hosseini et al. (2023) have shown that challenges such as technological limitations and legal institutions, along with digital market opportunities, are considered the main barriers and opportunities for digital entrepreneurship in Iran. Based on the research findings, the following suggestions are provided: Establish digital infrastructures for online sales and customer acquisition through various platforms. These models should be designed to cover the specific needs of particular customers and markets. Create an online system for collecting, evaluating, and implementing suggestions. This system can assist companies in identifying new market needs and improving internal services and processes.

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

Abstract The purpose of this study is to design a model for enhancing knowledge management based on intellectual and professional capital in the banking industry based on thematic analysis. The research method is applicable–developmental in terms of purpose, and qualitative in terms of implementation. The statistical population includes 18 university professors, managers, and experts from Gharz‑al‑Hasna Mehr Iran Bank. The sample size was determined through purposive sampling, and interviews continued until theoretical saturation was reached. Semi‑structured interviews were used for data collection. Thematic analysis was applied for data analysis using Maxqda software. The findings of the study revealed that knowledge management in organizations consists of six main dimensions: intelligent knowledge infrastructures (flexible knowledge infrastructures, smart accessibility, simplicity of knowledge systems, and automated organizational knowledge storage), knowledge empowerment (individual knowledge sharing, voluntary participation, and collective knowledge sharing), internal value creation (practical use of employee knowledge, decision‑making, and analysis of employee knowledge), external value creation (acquisition of knowledge and learning from customer experiences), comprehensive knowledge support (managerial support, strategic guidance, and psychological safety and trust), and knowledge culture (learning on the job, valuing knowledge acquisition, sustainability of knowledge management, and internalization of knowledge‑based behavior). Introduction In today’s world, organizations—particularly banks—face a variety of challenges that require the optimal use of their resources and assets. One of the most important resources available to any organization is the intellectual and professional capital of its employees, which can play a fundamental role in competitiveness and long‑term success (Quezada et al., 2025). Knowledge management in this regard, as the process of identifying, collecting, storing, transferring, and utilizing knowledge and information within organizations, plays a vital role in enhancing performance and innovation. As one of the major financial institutions in the country, due to its social and economic activities, Gharz‑al‑Hasna Mehr Iran Bank requires continuous improvement of its processes and effective utilization of organizational knowledge (Sadiqi et al., 2016). Since banks—especially Gharz‑al‑Hasna banks—play a key role in serving diverse segments of society, the optimal use of employees’ intellectual and professional capital can improve service quality, increase customer satisfaction, and enhance competitiveness in the market (Nguyen, 2024). Aburub et al. (2024) define intellectual and professional capital as an organized set of professional knowledge, specialized skills, accumulated experience in delivering financial services, customer information, effective stakeholder relationships, and structural and technological infrastructures that enable value creation, innovation, and competitive advantage for the bank. These capitals include human capital (employees’ abilities, knowledge, and creativity), structural capital (processes, systems, information technology, and internal regulations), and relational or customer capital (relationships, trust, and customer loyalty). Together, they play a central role in improving service quality, reducing operational risk, increasing efficiency, and strengthening the bank’s competitive position. In other words, intellectual and professional capital represents the intangible yet influential essence of modern banking which, when managed effectively, can transform organizational knowledge into economic and social value (Mehdikhani & Valmohammadi, 2020). Knowledge management based on intellectual capital is considered one of the most transformative approaches in modern banking; however, in Iran’s banking system—particularly in Gharz‑al‑Hasna banks with their distinct social mission—it has received limited scientific and structured attention. This study addresses the existing knowledge gap regarding the role of human, structural, and relational capital in enhancing knowledge management and provides a localized framework tailored to the characteristics of Gharz‑al‑Hasna Mehr Iran Bank. Accordingly, the main research question is: How can a model for enhancing knowledge management based on intellectual and professional capital in banking be designed using thematic analysis? Theoretical Framework Knowledge Management Knowledge management is a process through which an organization collects, organizes, shares, and analyzes its knowledge in a manner that makes it easily accessible to employees. This knowledge may include technical resources, frequently asked questions, training documents, and other forms of information (Afshari et al., 2020). Intellectual Capital Intellectual capital refers to intellectual materials such as knowledge, information, intellectual property, and experience that generate wealth. It is also considered intellectual material that is collected and structured to create a more valuable asset (Ozgun et al., 2022). Baharvand et al. (2026) examined a model for enhancing knowledge management based on intellectual and professional capital in the banking industry. Their qualitative analysis showed that knowledge management in organizations comprises six main dimensions: intelligent knowledge infrastructures, knowledge empowerment, internal value creation, external value creation, comprehensive knowledge support, and knowledge culture. The results of confirmatory factor analysis indicated that the proposed model has appropriate structural validity and convergence for all dimensions, and the indicators have high and significant factor loadings. As a practical suggestion, it is recommended that organizations strengthen flexible knowledge infrastructures and foster a culture of continuous learning so that, in addition to improving employee knowledge management, they can make practical use of employees’ experiences and knowledge, thereby ensuring the sustainable development of the organization’s intellectual capital. Putra et al. (2025) investigated the effect of intellectual capital and the creditworthiness of micro, small, and medium‑sized enterprises on bank performance. The findings revealed that intellectual capital (including employee knowledge, skills, and experience) and the credit provided to micro, small, and medium businesses have a significant and positive impact on the performance of rural banks. The study concludes that investing in human resource development and effectively managing credit allocation to local businesses are key factors in enhancing the productivity and competitiveness of banks. Research Methodology The research method is applicable–developmental in term of its purpose, and qualitative in terms of execution. The statistical population consists of 18 university professors, managers, and experts from Gharz‑al‑Hasna Mehr Iran Bank. The sample size was determined via purposive sampling, and the interviews continued until theoretical saturation was reached. A semi‑structured interview was utilized for data collection. Research Findings Data were analyzed by thematic analysis with Maxqda software. The findings revealed that knowledge management in organizations comprises six main dimensions: intelligent knowledge infrastructures (flexible knowledge infrastructures, smart accessibility, simplicity of knowledge systems, and automated organizational knowledge storage), knowledge empowerment (individual knowledge sharing, voluntary participation, and collective knowledge sharing), internal value creation (practical use of employees’ knowledge, decision‑making, and analysis of employee knowledge), external value creation (acquisition of knowledge and learning from customer experiences), comprehensive knowledge support (managerial support, strategic guidance, and psychological safety and trust), and knowledge culture (on‑the‑job learning, valuing knowledge acquisition, sustainability of knowledge management, and internalization of knowledge‑based behavior). Conclusion The present study was conducted with the aim of designing a model for enhancing knowledge management based on intellectual and professional capital in the banking sector using thematic analysis. The results of this research are consistent with the findings of Baharvand et al. (2026), Putra et al. (2025), Kurniawan and Sasmaya (2025), Nejad Afshar et al. (2025), Wang et al. (2025), Firdaus et al. (2024), Bocoya‑Maline et al. (2024), Heydari (2024), Attar and Bitar (2024), Mousavifard (2024), Hidayat and Sensuse (2022), and Ardalan et al. (2022). Hidayat and Sensuse (2022) showed that knowledge management and big data represent the most prominent trends, followed by governance, people, and smart education. Information technology was identified as the highest‑priority component. Their proposed knowledge management model for smart campuses consists of five main layers grouped according to system cycle stages. This cycle describes the intellectual capability of organizations to adapt and achieve smart campus indicators. The knowledge cycle in higher education institutions focuses on teaching, research, and social services. Based on the findings of this study, the following recommendation is proposed: It is recommended that the bank design a simple and user‑friendly interface for its knowledge management systems. Most users engage with knowledge management systems only when they can easily navigate and interact with them. Designing clear and intuitive interfaces can enhance user engagement and reduce the time required to learn how to use these systems.

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

Abstract The aim of this study is to present and validate a sustainable consumer behavior model based on good digital governance in the banking industry (case study: Parsian Bank). The research method is developmental-applicable in terms of targer, mixed in terms of implementation method, and of descriptive-exploratory type. The statistical population in the qualitative section includes 9 experienced professors in the field of research and senior and knowledgeable managers in the banking industry and Parsian Bank across the country, selected purposefully (judgmentally); and in the quantitative section includes 358 branch managers across the country, 186 of whom were selected using the Cochran formula and simple random sampling method. The tool for collecting findings in the qualitative section is a semi-structured interview and in the quantitative section is a questionnaire. MAXQDA software was used to analyze the data in the qualitative section and SPSS, and PLS software in the quantitative section. After coding, 23 subcategories were identified, including organizational values ​​supporting the formation of responsible behavior, Parsian Bank's macro and strategic goals, the level of education of the community and the expansion of new digital technologies at the banking level, influential factors (causal factors), providing personalized services, continuous training and awareness, reviewing digital policies, creating secure digital banking channels, and managing digital assets in the bank (pivotal factors). Considering the extracted components, the final research model explains a way to create sustainable consumer behavior and determine strategies and operational plans for the sustainable development of the country and improving bank performance. Introduction Good digital governance is recognized as a key framework for aligning digital processes with sustainable development goals. Recent studies show that the effective integration of technologies such as artificial intelligence and data analytics into banking systems not only increases operational efficiency, but also plays a decisive role in shaping sustainable consumer behavior. In particular, the report (Wang & Zhang, 2025) emphasizes that the use of artificial intelligence in integrating ESG (environmental, social and governance) data with banking decision-making processes leads to improved transparency and accountability (Wang & Zhang, 2025). On the other hand, research of Stauropoulou et al. (2023) shows that online banking plays a pivotal role in increasing financial inclusion and empowering underserved communities through personalized financial management tools by reducing access barriers. These findings suggest that designing digital systems based on good governance principles can lead to building customer trust and loyalty. Another study by Khosrpour et al. (2024) emphasizes the need to adopt digital transformation governance frameworks in commercial banks and proposes the “self-empowerment” strategy as an efficient model for coordinating between centralized and decentralized structures. Also, changes in lifestyle and the emergence of new technologies have led to different needs of customers who demand personalized services. In this competitive industry, banks must have strategies to maintain their competitive position. Good digital governance can improve consumer behavior by communicating with customers in a two-way manner and conveying necessary information about sustainable financial solutions to customers (Lucas & Basuki, 2015). By using digital technologies, banks can provide faster services and more diverse products, which increases customer interaction with the bank. In this regard, there are theoretical gaps about the role of good digital governance in the banking industry and its impact on sustainable consumer behavior. Also, differences in the definition and interpretation of sustainable consumer behavior can lead to a variety of perceptions and theoretical gaps among researchers (Zulfikar et al. 2020). The present article, focusing on Parsian Bank as a case study, seeks to combine research findings in the field of digital governance and sustainable consumer behavior to present a new model that is capable of adapting to rapid technological developments and increasing stakeholder expectations. Accordingly, the present study seeks to answer the following question: How does the presentation and validation of a sustainable consumer behavior model based on good digital governance in the banking industry look like in Parsian Bank? Theoretical Framework Sustainable Consumer Behavior Sustainable consumer behavior refers to the conscious and intentional actions of individuals as consumers to minimize the negative environmental, social, and economic impacts associated with their purchasing decisions. This includes choices that support sustainable practices, products, and businesses with the aim of promoting environmental protection, social equity, and economic well-being. By adopting this behavior, individuals can contribute to positive changes that create a more sustainable and just society (Milfont & Markowitz, 2016). Digital Governance Digital governance includes strategies and methods for managing and optimizing advertising activities, content marketing, digital public relations, data analytics, and customer communications. These actions help businesses improve, strengthen customer relationships, and ultimately increase sales and profitability. For example, using data analytics to better understand business strengths and weaknesses, identify customer behavior patterns, and optimize marketing strategies is an important aspect of digital governance in the marketing space. In general, digital governance in the marketing space plays a fundamental role in customer engagement, advertising, and online sales, and provides businesses with enormous opportunities to improve performance and growth (Shmok, 2022). Mohammadi et al. (2024) examined the design of a regulatory model based on sustainable development governance. They believe that the governance-based monitoring model for sustainable development includes three overarching themes (contextual, content, and monitoring) and five organizing themes (policy-based factors, economic factors, social factors, audit and reporting factors, and environmental factors) and 28 basic themes (formulation and implementation of economic, environmental, and social development policies, annual GDP growth, full employment, transparency, fiscal discipline, economic stability, social justice, access to renewable energy, combating desertification, waste management, sustainable forest management, sustainable use of financial resources and terrestrial ecosystems, reducing air pollution, minimizing the release of hazardous chemicals, poverty alleviation, social responsibility, combating corruption, health, intergenerational commitments, education, participation, promoting security, public welfare, budget and analytical reports, and audit reports). Hael et al. (2024) examined the trends in the literature on consumer behavior and sustainability: insights from a bibliometric analysis approach. They concluded that the three components The main ones, namely attitude, mental norms and perceived behavioral control, together shape the behavioral intentions of the individual and behavioral intention is the closest determinant of human social behavior and can have a significant impact on prediction. Research Methodology The research method is developmental-applicable in terms of its purpose, mixed in terms of implementation method, and descriptive-exploratory. The statistical population in the qualitative section includes 9 experienced professors in the field of research and senior and knowledgeable managers in the banking industry and Parsian Bank nationwide, which were selected purposefully (judgmentally) and in the quantitative section includes 358 branch managers nationwide, 186 of whom were selected using the Cochran formula and simple random sampling method. The tool for collecting findings in the qualitative section is a semi-structured interview and in the quantitative section is a questionnaire. Research Findings MAXQDA software was used to analyze data in the qualitative section and SPSS and PLS software were used in the quantitative section. After coding, 23 subcategories were identified, including organizational values ​​supporting the formation of responsible behavior, Parsian Bank's macro and strategic goals, the level of education of the community and the expansion of new digital technologies at the banking level, influencing factors (causal factors), providing personalized services, continuous training and awareness, reviewing digital policies, creating secure digital banking channels, and managing digital assets in the bank (central factors). Considering the extracted components, the final research model explains a way to create sustainable consumer behavior and determine strategies and operational plans for the sustainable development of the country and improving bank performance. Conclusion The present study was conducted with the aim of presenting and validating a model of sustainable consumer behavior based on good digital governance in the banking industry (case study: Parsian Bank). These results are consistent with the results of Mohammadi et al. (2024), Hael et al. (2024), Akpan Obong et al. (2023), Rezaei Lori et al. (2022), Husta & Zabkar (2021), Al-Ansari et al. (2021), Velenduck et al. (2017), Wu et al. (2016). Rezaei Lori et al. (2022) stated that; holistic responsibility is a factor for the formation of good governance and along with it, knowledge linkage, innovation platforms and innovative actions lead to sustainable development in social, economic and environmental dimensions. According to the research results, the following suggestions were made: Parsian Bank should evaluate and continuously improve its integrated channels by receiving consumer feedback periodically with the aim of their participation in the digital service improvement processes. This can be done through surveys, online comments or in-app feedback systems.

Abstract This study was conducted with the aim of examining the role of neuromarketing in digital marketing. The research methodology is applicable in terms of purpose; quantitative in terms of execution; and descriptive-correlational in terms of nature and method. The statistical population of the study consisted of customers of active online stores in Tehran province. Using a simple random sampling method and Cochran’s formula, 384 individuals were determined as the sample size. To collect research data, a standard questionnaire based on a 5-point Likert scale was used. The content validity of the instrument was confirmed by specialists and experts; and to measure the reliability of the instrument, Cronbach’s alpha and composite reliability methods were used. By distributing the questionnaire, the validity of the instrument was assessed using three methods: construct validity (outer model), convergent validity (AVE), and discriminant validity. The AVE value for all variables should be greater than 0.5. SPSS and PLS software were used for data analysis. The research findings indicate that the dimensions of neuromarketing (interest and engagement, knowledge and awareness, and ethics) influence digital marketing. Introduction Neuromarketing is an interdisciplinary science rapidly emerging in consumer cognition research worldwide. It is also considered a creative field in marketing research that challenges the traditional marketing model to improve the understanding of the process related to purchasing behavior. Neuromarketing is a method that examines the customer’s decision-making process for purchasing (Alkhudari et al., 2023). Based on the marketing concept regarding this process, customer purchasing decisions are presented as a two-system approach. System 1 is an automatic and fast process, while decisions made by System 2 are deliberate, with conscious reasoning, and slow. In the study of consumer behavior cognition, these processes constantly guide purchasing decisions. Furthermore, neuromarketing is a combination of at least three basic sciences, including neuroscience, behavioral economics, and social psychology (Salaripour, 2021). On the other hand, due to intense competitive pressures today, one of the most important strategies through which service organizations can achieve a sustainable competitive advantage is to improve communications and advertising through cyberspace (Bílková et al., 2021). Therefore, applying the digital marketing approach in market activities facilitates and expands the strategic behaviors of marketing managers of companies in cyberspace (Sattarii et al., 2022). Consequently, digital marketing is considered one of the important items of strategic assets and modern marketing tools. Gathering and evaluating information related to competing companies in developing a modern digital marketing approach plays a vital role. On the one hand, building capacity for the development of digital marketing requires providing the necessary training and skills with a digital approach and the growth of commercial enterprises based on societal needs at all levels. On the other hand, the development and growth of digital businesses require understanding and removing obstacles and creating suitable grounds for the development of service activities (Kaushik, 2021). Adopting digital approaches and social media has gradually become one of the most critical marketing strategies for organizations (Saruklai et al., 2022). Digital and social media are essential sources for expanding individuals’ social lives or understanding consumer behavior, especially for contemporary global trends, such as Industry 4.0, intelligence, and even the metaverse. Therefore, for marketers and those who want to stay at the edge of market trends, “digital marketing” has become an inevitable paradigm in the business field. While the high potential of digital marketing in various business areas has been proven, the approach to this technology in financial markets is slightly different. A significant challenge facing the marketing team of financial institutions is digital transformation. Cyberspace creates many opportunities for the financial services industry in terms of customer acquisition and retention. In every economic unit, there is a close relationship between the economic unit’s ability to generate operating cash flows and the capital needs required for the next period. Like other behavioral phenomena, the adoption trend of digital marketing in online companies can be analyzed using the principles stated in behavioral theories. Hence, the present study seeks to answer the question: What is the role of neuromarketing in digital marketing? Theoretical Foundations Neuromarketing Neuromarketing is an emerging field that examines customer behavior using neuroscience tools and has rapidly become a topic of interest for marketing researchers. Neuromarketing is not a replacement for traditional marketing; rather, it is considered a complement to improve it. In fact, the relationship between neuromarketing and traditional marketing can be likened to the relationship between neuro-psychology and psychology (González-Mena et al.,2022). Digital Marketing Marketing is an essential activity for generating revenue from key customers and other ones. Therefore, companies facing budget cuts must exercise sufficient caution in identifying essential and non-essential expenses. Digital marketing is a general term for any effort by a company to communicate with customers through electronic technology, including email, location and mobile marketing, social media, online communities, and other video-based content (Wang et al., 2021). Pirzada (2025) conducted a study titled “Neuromarketing in Digital Advertising: Insights and Case Studies from India.” By leveraging advanced neuroimaging techniques and biometric tools, businesses can create more effective advertising strategies that resonate with consumers at an unconscious level. This study identifies key neuromarketing strategies employed by Indian companies and examines their impact on consumer engagement and decision-making. Additionally, it discusses ethical considerations and potential challenges associated with implementing these techniques. Devi (2025) conducted a study titled “Decoding the Consumer Mind: Integrating Neuromarketing Principles into Digital Marketing Strategies.” This study, supported by current trends from 2023 to 2025 and emerging neuroscience research, invites students to identify key opportunities and ethical challenges that marketers may face in creating psychologically optimized, technology-driven campaigns. Furthermore, the urgency of these developments is amplified by the acceleration of digital engagement in the post-pandemic era and the growing presence of artificial intelligence technologies. Research Methodology This research is applicable in terms of its objective, and descriptive-correlational in terms of its method. The statistical population of the study consists of customers of active online stores in Tehran province. Due to the unlimited nature of this population, 384 individuals were determined as the sample size using simple random sampling and the Cochran formula. A researcher-made questionnaire on a five-point Likert scale was used to collect data. The findings from the Cronbach’s alpha and composite reliability tests to measure the reliability of the research instrument are reported in Table 2. Content validity (expert consultation) was used to assess the instrument’s validity, and its credibility was confirmed. Then, by distributing the questionnaire, the instrument’s validity was measured using three methods: construct validity (outer model), convergent validity (AVE), and discriminant validity. The AVE value for all research variables must be greater than 0.5. To test the research hypotheses, structural equation modeling was used in the SmartPLS2 statistical software environment. Findings Data analysis indicated that neuro-based marketing, with its components of knowledge and awareness, ethics, interest, and engagement, has a significant positive impact on digital marketing. The results suggest that neural triggers, by accessing the subconscious layer, reduce mental resistance and facilitate customer decision-making in the online space. Ultimately, the research model explained that adhering to ethical principles, alongside emotional engagement, leads to the sustainability of digital trust and loyalty in the target market. Discussion and Conclusion The present research was conducted with the aim of analyzing the role of neuro-based marketing dimensions in enhancing digital marketing among customers of online stores in Tehran province. The findings from data analysis using Structural Equation Modeling (SEM) with PLS showed that all formulated hypotheses were confirmed, and the conceptual model of the research has a good fit. Explaining the first hypothesis regarding the impact of “interest and engagement” in neuro-based marketing on digital marketing, the results of statistical analysis showed that this component, with a beta coefficient of 0.594 and a t-statistic of 5.421, played the strongest explanatory role in the model, and the hypothesis was confirmed with 99% confidence. This finding is very consistent with the results of Devi (2025) and Millagala (2023), as neuro-based marketing, by influencing subconscious layers, identifies stimuli that lead to deeper emotional engagement of the customer in the digital space. In fact, as Gohain (2024) also pointed out in his research, in the current era where capturing consumer attention is difficult, using neural techniques to evoke interest makes digital marketing strategies move beyond simple messages and become resonant experiences in the audience’s mind, leading to their active participation and loyalty on online platforms. The second hypothesis, which examines the role of “knowledge and awareness” in neuro-based marketing on digital marketing, yielded results supporting a significant positive effect of this variable with a beta coefficient of 0.411 and a t-statistic of 6.189, indicating a high stability of this relationship in the studied population. This result is consistent with the findings of Moradi ziba et al. (2023), who consider customer knowledge as one of the main reasons for success in digital strategies, as well as with the results of Zhang et al. (2023) regarding the importance of awareness in dynamic environments. In interpreting this effect, it can be argued that neuro-based marketing improves comprehensive decision-making by enhancing brand cognition and clarifying the message in the audience’s mind. In other words, when customer awareness is strengthened through optimal neural stimuli, digital tools such as websites and applications are perceived more effectively in their minds, and by reducing mental resistance, they pave the way for interaction with online stores. Finally, the third hypothesis of the research regarding the impact of “ethics” in neuro-based marketing on digital marketing was also confirmed with a beta coefficient of 0.419 and a t-statistic of 4.980, indicating the importance of value dimensions in the adoption of new marketing techniques. The confirmation of this relationship aligns with the emphases of Pirzada (2025) and Devi (2025) on the necessity of managing ethical challenges in the use of novel marketing technologies. This finding suggests that among the customers of online stores in Tehran, adherence to ethical principles acts as a strengthening and enabling factor (consistent with the model of Bagheri anilu et al., 2023). In fact, commitment to an ethical charter in the use of neural data and biometric tools leads to the creation of “digital trust” in customers and acts as a shield against potential distrust, which ultimately allows digital marketing techniques to influence purchase intention and consumer behavior more sustainably and effectively.

Abstract The purpose of this study is to examine the relationship between office automation and organizational agility and health, considering the mediating role of organizational structure dimensions. This research is applicable in terms of purpose, and descriptive‑correlational in terms of method. The statistical population consisted of 600 employees of the Ports and Maritime Organization of Bushehr Province in 2025, of whom 234 individuals were selected as the sample through proportionate simple random sampling and Cochran’s formula. For data collection, four questionnaires were used: Ahangar‑Pour’s Office Automation Questionnaire (2008), Zhang and Sharifi’s Organizational Agility Questionnaire (2000), Hoy and Feldman’s Organizational Health Questionnaire (1996), and Robbins’ Organizational Structure Questionnaire (1979). The office automation questionnaire consisted of 30 items with validity and reliability coefficients of 0.90 and 0.93, respectively. The organizational agility questionnaire contained 28 items with validity and reliability of 0.88 and 0.86, respectively. The organizational health questionnaire included 44 items with validity and reliability of 0.91 and 0.85, and the organizational structure questionnaire consisted of 24 items with validity and reliability of 0.87 and 0.93. SPSS and LISREL software were applied to analyze the data. The results of data analysis indicate that there is a significant relationship between office automation and organizational agility and health, considering the mediating role of organizational structure dimensions in the Ports and Maritime Organization of Bushehr Province. Introduction According to numerous experts, the business world has undergone significant transformation, and the main drivers of these changes include increasing market competition, diverse customer expectations, globalization, rapid technological advancements, cultural and social issues, shortages of skilled labor, and the growing influence of information technology. In today’s dynamic environments, organizations can no longer be managed by traditional approaches. To cope with emerging challenges, production‑oriented organizations must revise their production processes and systems. Achieving organizational agility is essential for responding effectively to change and leveraging resulting opportunities to gain competitive advantage (Derani et al., 2016). Agile manufacturing in today’s competitive landscape equips organizations with the ability to respond quickly to market fluctuations (Lengnick‑Hall & Beck, 2016). Therefore, companies and organizations are inevitably moving toward agile production, which requires attention to multiple key factors—including the use of efficient office automation systems, achieving organizational health, and establishing a coherent and strong organizational structure (Civi, 2018). Today, optimal utilization of human resources and the delivery of customer‑oriented services as sources of competitive advantage depend on maintaining organizational health. Major consequences of low organizational health include decreased employee satisfaction, workforce fragmentation, increased conflicts, reduced innovation, diminished cooperation, and lower work quality (Beikzad, 2023). An office automation system facilitates internal organizational communication as well as communication with external entities, contributing to improved coordination and enhanced work quality. Consequently, the Ports and Maritime Organization can leverage an effective office automation system to evolve into an agile organization, maintain a healthy organizational environment, and establish a strong structural foundation among competing organizations (Behnamfar, 2023). Furthermore, the complexity of modern organizations presents significant challenges to organizational growth and development. Addressing these challenges requires flexibility and readiness to adapt to new conditions—an unavoidable necessity for today’s managers. Accordingly, this study seeks to answer the following question: Is there a significant relationship between office automation and organizational agility and health, considering the mediating role of organizational structure dimensions? Theoretical Framework Office Automation Office automation encompasses all electronic systems that establish or facilitate various forms of internal and external organizational communication (Kim, 2016). Organizational Agility Organizational agility refers to an organization’s ability to respond quickly and effectively to environmental changes and internal challenges (Baraei & Mirzaei, 2019). Organizational Health Organizational health is the capability of an organization to function effectively, adapt adequately, undergo appropriate change, and grow. Similar to individual health, it can vary across different levels, ranging from minimal to optimal (Sarmasti & Shah Taheri, 2021). Organizational Structure Organizational structure is the framework that governs the relationships among jobs, systems, operational processes, individuals, and groups working toward achieving organizational goals. It represents the set of mechanisms through which work is divided into specific tasks and coordinated among them (Rahimi et al., 2017). Emamdoust Haredasht et al. (2025) examined the modeling of human capital strategies in Bank Sepah of Iran with an emphasis on organizational structure modification. The findings showed that in the training and development subsystem, attention must be paid to training needs, training effectiveness, and career advancement pathways. In the compensation and reward subsystem, emphasis should be placed on strategies and policies related to payment and welfare plans, innovative reward and compensation methods, and rewards aligned with organizational goals. In the employee relations subsystem, focus should be directed toward employee relations strategies, employee interaction and participation, and effective design of structural change. Quantitative results demonstrated that the most important components were competence in the training and development subsystem (standard coefficient = 0.82), innovative compensation and reward strategies in the compensation subsystem (standard coefficient = 0.94), and employee relations strategies in the employee relations subsystem (standard coefficient = 0.84). Kadivar Zinkanloo et al. (2024) investigated the design of a model for developing organizational resilience based on components of organizational agility (case study: Bank Sepah branches in North Khorasan Province). The findings indicated several categories of causal factors, central phenomena, strategies, intervening conditions, contextual conditions, and consequences. Causal factors included flexible organizational culture; central phenomena involved developing organizational resilience based on agility components; strategic factors included strategy development; intervening conditions were related to the change process; contextual factors included process improvement and communication within the organization; and the main consequence identified was organizational agility. Research Methodology This study is applicable in terms of purpose, and descriptive–correlational in terms of research design. The statistical population consisted of 600 employees of the General Directorate of Ports and Maritime Affairs of Bushehr Province in 2025. 234 individuals out of this population were selected as the sample through proportionate simple random sampling and based on Cochran’s formula. To collect data, four questionnaires were used: Ahangar‑Pour’s Office Automation Questionnaire (2008), Zhang and Sharifi’s Organizational Agility Questionnaire (2000), Hoy and Feldman’s Organizational Health Questionnaire (1996), and Robbins’ Organizational Structure Questionnaire (1979). The office automation questionnaire consisted of 30 items with validity and reliability coefficients of 0.90 and 0.93, respectively. The organizational agility questionnaire contained 28 items with validity and reliability coefficients of 0.88 and 0.86, respectively. The organizational health questionnaire included 44 items with validity and reliability coefficients of 0.91 and 0.85, while the organizational structure questionnaire consisted of 24 items with validity and reliability coefficients of 0.87 and 0.93. Research Findings SPSS and LISREL software were used to analyze the research data. The results indicate that there is a significant relationship between office automation and organizational agility and health, considering the mediating role of organizational structure dimensions in the General Directorate of Ports and Maritime Affairs of Bushehr Province. Conclusion The present study aimed to examine the relationship between office automation and organizational agility and health, considering the mediating role of organizational structure dimensions. The results are consistent with the findings of Emamdoust Haredasht et al. (2025), Kadivar Zinkanloo et al. (2024), Zafari et al. (2019), Hoseini Pozveh et al. (2021), Ameri (2021), and Asgarpour and Matrudi (2023). Given that environmental changes affect many aspects of organizations; appropriate strategies must be employed to dynamically adapt to these changes in order to ensure their survival. One of the most effective approaches for addressing environmental changes is directing organizations toward agility. The most essential tool for achieving this goal is the office automation system, which must receive continuous and serious attention from decision‑makers to safeguard the future of organizations and companies—particularly the General Directorate of Ports and Maritime Affairs of Bushehr Province. Based on the findings, it is recommended that organizations utilize office automation systems effectively to enhance decision‑making quality, improve the analysis of organizational information, benefit from innovative ideas, increase responsiveness to clients, accelerate work processes, and streamline workflow procedures. Such measures can significantly contribute to improving organizational agility and health, thereby strengthening organizational structures.

Abstract The purpose of this study is to analyze the dimensions and components of digital transformation management based on artificial intelligence. This research was conducted qualitatively using the thematic analysis method. The statistical population consisted of 12 experts and specialists in the fields of human resource management and information technology management across the country (including university faculty members in HRM and IT management, as well as general directors of provincial education departments). Participants were selected using purposive sampling. The data collection instrument was semi‑structured interviews. Data analysis was performed through thematic analysis using MAXQDA software. The findings revealed that AI‑based digital transformation management includes four overarching themes—contextual requirements, digital infrastructure, digital transformation management process, and organizational capital; twelve organizing themes—ethical requirements, cultural requirements, organizational requirements, hard digital infrastructure, soft digital infrastructure, digital transformation management process, digital transformation planning, prototyping, learning, human capital, process capital, structural capital, and social capital; and a total of 73 basic themes. Introduction The rapid advancements in new technologies in the current era, particularly in the fields of artificial intelligence, machine learning, big data, and smart technologies, have caused fundamental changes in the structures and operations of organizations. These transformations are not limited to economic and industrial sectors but also significantly impact educational and cultural institutions (Mostafaei et al., 2024). Many experts believe that the future of organizations depends on their ability to manage digital transformation. Digital transformation is a process that goes beyond equipping organizations with IT infrastructure; it involves rethinking missions, structures, governance methods, and even organizational culture (Wang et al., 2025). In this context, the education system, as the most fundamental social institution responsible for nurturing human capital, requires a reinvention and transformation of its processes more than ever before. In Iran, the education sector faces challenges such as centralization, inefficiency in some administrative procedures, underutilization of educational data, and a significant gap compared to global standards in digital transformation (Azimi et al., 2024). In many educational systems, including Iran’s, the adoption of new technologies has largely remained at the level of tools and infrastructure, with less attention paid to its strategic and forward-looking dimensions. Domestic studies indicate that most digitalization projects in education are implemented in isolation and sporadically, lacking necessary coherence (Golestani, 2024). In the Gilan province specifically, field evidence suggests that although some administrative and educational processes have been digitized, these changes often face resistance from employees, a lack of digital skills, and weaknesses in macro-level policymaking. Consequently, the potential capabilities of artificial intelligence for organizational transformation have not yet been utilized effectively or operationally. Therefore, in pursuit of this goal, the main research question is: What are the dimensions and components of artificial intelligence-based digital transformation management in the education system? Theoretical Framework Digital Transformation Digital transformation is a profound, multidimensional, and strategic process through which organizations systematically and purposefully leverage digital technologies to fundamentally alter their structures, processes, business models, organizational culture, and service delivery methods. This transformation aims to enable them to achieve more effective, agile, and value-driven performance in today’s complex, dynamic, and competitive environment (Asad Amraji et al., 2020). AI-Based Digital Transformation Artificial intelligence can bring about a fundamental transformation in the analysis of the performance of educational personnel, shifting it from a subjective, periodic, and guesswork-based process to an objective, continuous, data-driven, and development-oriented one (Agrawal et al., 2018). Chen & Zhang (2025) in their examination of the impact of AI applications on the environmental, social, and governance (ESG) performance of companies, demonstrated that digital transformation can enhance the sustainable development of organizations by increasing coordination and collaboration, the demand for specialized digital knowledge, the ability to manage virtual systems, and by changing the roles and styles of managers. Mohsen et al. (2025) in a study on financial institutions, found that the integration of artificial intelligence into organizational structures can significantly improve the managerial performance and operational efficiency of these organizations. Research Methodology This research was conducted qualitatively using the thematic analysis method. The statistical population of the study included 12 experts in the fields of human resource management and information technology management at the national level. This group comprised university faculty members in the fields of human resource management and information technology, as well as general directors of provincial education departments. They were selected using a purposive sampling method. The data collection tool used was semi-structured interviews. Research Findings Data analysis was performed using the thematic analysis method with the MAXQDA software. The findings of the present study indicate that AI-based digital transformation management has been designed in the form of four overarching categories: “Contextual Requirements,” “Digital Infrastructure,” “Digital Transformation Management Process,” and “Organizational Capital.” These are further broken down into 12 organizing categories: “Ethical Requirements,” “Cultural Requirements,” “Organizational Requirements,” “Hardware Digital Infrastructure,” “Software Digital Infrastructure,” “Digital Transformation Management Process,” “Digital Transformation Planning,” “Prototyping,” “Learning,” “Human Capital,” “Process Capital,” “Structural Capital,” and “Social Capital,” along with 73 basic categories. Conclusion The present research was conducted with the aim of exploring the dimensions and components of AI-based digital transformation management. These findings are consistent with the results of previous studies, including those by Brock & Von Wangenheim (2019), Chen & Zhang (2025), Mohsen et al. (2025), Rosemary (2025), Malik et al. (2022), Alemi Pasand & Farahani (2024), Tavakoli-Rad & Zargaran-Khozani (2022), and Kitsios & Kamariotou (2021). In their research, they acknowledged that indicators such as individual prerequisites, organizational culture, organizational digital culture, data, digital ethics and privacy, hardware and software, and policy-making play a significant role in improving organizational digital leadership. Furthermore, Mohsen et al. (2025) asserted that attention to the structural dimensions of an organization can play a crucial role in improving organizational performance. Chen & Zhang (2025) also stated that focusing on changes in organizational structure and regulations significantly contributes to the development of organizational practices. Based on the research findings, it is recommended that the Education Departments of Gilan Province develop and issue a special ethical charter for artificial intelligence. This charter should explicitly include principles such as algorithmic transparency, data privacy protection, prevention of discriminatory biases, and the necessity of human oversight in decision-making processes.

Abstract This research aims to design a model for enhancing employee performance effectiveness based on cultural components in the digital age within the Mellal E-commerce and Information Technology Company. The current study adopts a qualitative approach, framed within an interpretive paradigm, utilizing the strategy of thematic analysis. The statistical population comprises 10 experts, including university management professors with at least ten years of relevant experience and profound knowledge of enhancing employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. These experts were selected through purposive sampling. The data collection instrument employed was semi-structured interviews. Thematic analysis was utilized for analyzing the findings. The research findings revealed 6 main themes (Digital Acceptance Culture, Ethical Leadership Style, Organizational Culture, Cultural Competence of Employees and Managers, Cultural and Managerial Accountability, and Cultural and Psychological Empowerment), and 33 organizing themes that influence the enhancement of employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. This study provides a framework for designing a qualitative model to enhance employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. Introduction Human capital is increasingly emphasized for growth, and enhancing the quality of the workforce is a fundamental way to improve productivity and accelerate economic growth. In other words, human resources are the most crucial factor influencing productivity. Humans play a significant role as the basic foundation for organizational development by participating in group and organizational activities. Today, the growth and development of organizations depend on the effective utilization of human resources. Management theorists consider human to be complex phenomenon and a powerful tool for organizational change (Torabi et al., 2022). Organizations, regardless of their mission, must dedicate the most significant portion of their capital, time, and planning to human resource development, ensuring all employees are prepared in various dimensions to create, nurture, and apply individual, group, and organizational productivity. Therefore, an organization’s success in achieving its goals depends on an effective blend of human and material resources. In recent decades, human resources have been paid substantial attention as the largest and most important capital and asset of an organization (Maroufi & Alimoradi, 2015). One of the company’s strategies to increase employee productivity and achieve maximum performance is by offering incentives, including financial ones. Incentives are a form of monetary appreciation by company leaders, aimed at motivating employees to excel (Ichdan et al., 2021). Productivity is the relationship between the output achieved and the resources used in performing a specific activity. Employee work productivity is not achieved automatically; rather, employees must strive to meet the company’s expectations for the work performed, and fulfill what is received from them. In the past, it was believed that physical and material assets were the primary drivers of national progress, and the scarcity of these resources was considered the cause of underdevelopment in developing countries. Consequently, these nations pursued material capital, leading to increased dependency and the degradation of their economic, political, and cultural foundations. It is now understood that sustainable development hinges on the existence of strong and efficient administrative institutions possessing specialized human capital. In this context, the present research seeks to present a qualitative model for enhancing employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. Therefore, an attempt will be made to answer the question: How can the predictive model of the impact of human resource innovations on organizational performance be analyzed from a futures studies perspective? Theoretical Framework Enhancing Employee Performance Effectiveness An organization requires human resource management as a performance system to achieve its objectives. This transforms human resource performance management into one of the critical indicators for effectively and efficiently reaching organizational goals (Kertiriasih et al., 2018). Human resource management plays a vital role in shaping intended policies within any organization and must guide employees toward organizational objectives (Shaban, 2019). Several reasons contribute to performance effectiveness, benefiting organizations, managers, and employees alike. Employees are encouraged and motivated when their good work is recognized. This boosts their morale, leading them to perform better, and employees desire to be authenticate and feel valued. This fulfills a fundamental human need and motivates them (Govender & Bussin, 2020). The Digital Age Digital transformation has become a critical component in the national sustainable development of many countries in the third millennium. Governments are striving to establish e-governance and reform traditional bureaucracies. E-governance, by improving efficiency and effectiveness in public services, creates the conditions for expanding services to citizens, increasing public participation, and strengthening democracy. Therefore, digital governance holds significant importance at the macro level for governments. Leading organizations have also prioritized technology-based reforms, with a special focus on the digital community within the organizational sector. Digital transformation is a complex, multifaceted process that involves fundamental changes in how organizations and society work, think, and utilize technology (Kivanc Bozkus, 2023). Bagheri (2025) examined the relationship between organizational culture and inspection effectiveness in municipal devices. The findings indicated that strengthening an appropriate organizational culture through continuous training, enhancing team spirit, and establishing incentive mechanisms can serve as an effective strategy for improving inspection effectiveness and complaint response. Mirtajadini et al. (2025) investigated the provision of a model for employee job performance quality based on factors of job attachment and positive behavior. The results showed a significant relationship between job attachment and positive behavior with the manner and quality of job task execution by employees. There is a significant relationship between job attachment and positive behavior with the level of employee commitment to work and responsibility. Furthermore, there is a significant relationship between job attachment and positive behavior with the extent of employees’ efforts towards achieving organizational goals. Research Methodology The present research adopts a qualitative approach, operating within the interpretive paradigm and utilizing the strategy of thematic analysis. The statistical population of this study comprises 10 experts, including university management professors with at least ten years of relevant experience and a deep understanding of enhancing employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. These participants were selected using purposeful sampling. The data collection instrument employed is semi-structured interviews. Research Findings Thematic analysis was employed to analyze the findings. The results of the present research revealed six main themes: (Digital Acceptance Culture, Ethical Leadership Style, Organizational Culture, Cultural Competence of Employees and Managers, Cultural and Managerial Responsibility, and Cultural and Psychological Empowerment). Additionally, 33 organizing themes were identified, all of which influence the enhancement of employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. This research aims to contribute by presenting a framework for designing a qualitative model for improving employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. Conclusion The present research was conducted with the aim of designing a model for enhancing employee performance effectiveness based on cultural components in the digital age at Mellal E-commerce and Information Technology Company. The results of this study are consistent with the findings of the following research: Bagheri (2025), Mirtajadini et al. (2025), Namvar Hamzanloui et al. (2025), Pourhassan Harzandi et al. (2025), Stoudeh (2024), Abidi et al. (2024), Hassanvand et al. (2024), Abdollahzadeh Namini et al. (2024), Karimi (2024), Sokura (2024), Jou et al. (2024), Sana (2023), Hosseini Rad (2023), Raisi Nafchi & Zal (2023), and Khalil et al. (2022). Bagheri (2025) demonstrated that strengthening an appropriate organizational culture through continuous training, enhancing team spirit, and establishing incentive mechanisms can be an effective strategy for improving inspection effectiveness and responding to complaints. Based on the research findings, the following suggestions are presented: Updating organizational culture with a focus on trust, learning, and digital participation will increase employee motivation and effectiveness. Therefore, it is recommended that digital communication skills, including respect, active listening, and effective messaging, be taught to prevent misunderstandings. Additionally, formal and informal channels for open dialogue with management should be established.

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

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

Abstract The purpose of this study is to model the psychological characteristics of founders of small and medium‑sized enterprises (SMEs) within the industrial cooperatives of Mazandaran Province. This research is applicable in terms of purpose, and quantitative in terms of methodology. The statistical population consists of 893 business founders across the province, as defined by the Global Entrepreneurship Monitor (GEM). Using Cochran’s formula, a sample of 186 individuals was selected through simple random sampling. The data collection instrument was the Kiggundu (2002) questionnaire. Data analysis was performed by SPSS and LISREL software. The findings indicate that the overall psychological construct under examination, within a measurement model and path analysis framework (structural equation modeling), explains the process of business start‑up. Each psychological variable exerts both direct and indirect (interactive) effects on this process. Among these, the highest overall influence belongs to the sub‑variable of internal locus of control, followed respectively by tolerance of ambiguity, job autonomy, need for achievement, motivation, and risk‑taking. The study concludes by recommending that policymakers and relevant authorities, in order to enhance business start‑up processes and foster productive employment, pay attention to these psychological variables in addition to other environmental and structural conditions. Introduction Entrepreneurs play a critical role in economic growth through leadership, management, innovation, efficiency, job creation, competition, productivity, and the establishment of new firms. It is widely believed that societies today require an “entrepreneurial revolution,” one whose significance in the current century surpasses even that of the Industrial Revolution. Business start‑ups are considered a driving force behind economic development, employment generation, and social improvement (Jeanneaux et al., 2025). Entrepreneurship education focuses on equipping trainees with the knowledge and skills necessary to initiate and manage new ventures. In recent years, a notable shift has occurred, with increasing emphasis on developing broader entrepreneurial competencies such as creativity, problem‑solving, opportunity recognition, and adaptability (Kallas & Parts, 2021). Given the crucial role of business creation and the successful track record of entrepreneurs in the development of many countries—and considering the economic challenges faced by our own nation in both the private and public sectors—promoting and institutionalizing the concept of entrepreneurship, as well as establishing supportive cultural conditions and developing assessment models for identifying and supporting entrepreneurs, are of vital importance. The country’s young demographic structure and the urgent need for job creation, along with the necessity of reducing dependence on primary raw materials and moving beyond a single‑product economy, combined with the dynamics of the information society, compel national policymakers to seek reliable alternative resources. Undoubtedly, in line with the requirements of the information society, such a resource is nothing other than creativity, innovation, and entrepreneurial business creation (Masoudi & Asgari, 2024). In social network theory, business start‑up is viewed as a process embedded within dynamic networks of social relationships—relationships that may either restrict or facilitate the entrepreneur’s access to resources and opportunities. Therefore, entrepreneurs as a group are both unique and diverse. Their similarities distinguish them from non‑entrepreneurs, while their differences create a heterogeneous group, making the study of entrepreneurial characteristics inherently complex (Chauhan et al., 2024). Accordingly, based on the above discussions, the present study seeks to answer the following question: How can the psychological characteristics of founders of small and medium‑sized enterprises in the industrial cooperatives of Mazandaran be modeled? Theoretical Foundations Business Start‑Up Business start‑up is an interdisciplinary subject shaped by the cumulative contributions of various fields such as economics, psychology, anthropology, sociology, and management (Vajdi Vahid et al., 2024). Shams et al. (2025) examined the relationship between brand dependence and business performance through inter‑organizational relationships and interactions within supply chain management environments. Their findings revealed that buyer–supplier interactive relationships and buyer–supplier commitment act as key mediators between brand dependence—specifically brand affordability, brand equity, and brand loyalty—and buyer–supplier communication, as well as between brand dependence and business performance. This study contributes to the branding literature by introducing the concept of brand dependence within the context of small and medium‑sized enterprises (SMEs). In another study, Rezaei Sadrabadi et al. (2025) explored the role of open innovation, social capital, co‑created knowledge, and collaboration with external partners in enhancing organizational agility amid the turbulence of today’s dynamic environment. Their research proposed a new framework for applying open‑agility enablers in selected SMEs located in the Yazd industrial zone. The findings indicate that organizational agility is significantly influenced by open innovation, and subsequently by collaboration with external partners and co‑created knowledge. Moreover, social capital has a strong and positive impact on the development of co‑created knowledge within these selected SMEs. Research Methodology This study is applicable in terms of purpose, and quantitative in its method of implementation. The statistical population consists of 893 business founders across the province, identified according to the Global Entrepreneurship Monitor (GEM) definition of business start‑ups. Using Cochran’s formula, a sample size of 186 individuals was determined and selected through simple random sampling. The data collection instrument used in this study was the questionnaire developed by Kiggundu (2002). Research Findings The data were analyzed by SPSS and LISREL software. The results indicate that the overall psychological construct examined in this study, assessed through a path‑analysis measurement model (structural equation modeling), significantly explains the business start‑up process. Each of the psychological dimensions demonstrated both direct and indirect (interactive) effects on this process. Among these variables, the strongest overall effect belonged to internal locus of control, followed by tolerance for ambiguity, work independence, need for achievement, motivation, and risk‑taking, respectively. The findings suggest that policymakers and relevant authorities should, in addition to other structural and economic conditions, pay close attention to these psychological characteristics in order to improve the business start‑up process and promote productive employment.S Conclusion The present study was conducted to investigate the modeling of the psychological characteristics of founders of small and medium‑sized enterprises (SMEs) within the industrial cooperatives of Mazandaran Province. The results of it align with the results of Shams et al. (2025), Jeanneaux et al. (2025), Omidi (2025), Monaisen et al. (2025), Rezaei Sadrabadi et al. (2025), Vahabi Abyaneh & Mobini Dehkordi (2025), Anne Magro et al, (2022), Baizhou et al. (2023), Mohtadi (2023), Bauwens et al. (2024), Chauhan et al. (2024), Farmahini Farahani et al. (2025), and Kallas & Parts (2021). Anne Magro et al. (2022) concluded that the prevailing viewpoints and perceptions toward entrepreneurship and its effects in France is not such positive. This study has also presented viewpoints about the factors effecting the success and failure of educational programmes, and investigated that how the business faculty of George Meissen University injects the free training approach into the business education, and utilizes a combination of effective methods such as primary year’s seminars, shared thinking experiences, learning societies, cooperative assignments, specialized researches, society-based learning, training, final courses and projects, and global diversity and learning. The Meissen experience demonstrates the possibility and advantages of this integration. According to the results, the following suggestions are presented: In order to improve the entrepreneurship in the statistical population under study according to the entrepreneur’s personal characteristics, it might be attempted by paying attention to the six personal variables which defines it in the real world. Therefore, it is necessary, at the first step, the most attention paid to the inner control locus variable, following the rest varables according to their respective importance.

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

Abstract The present study was conducted with the aim of investigating the effect of knowledge management strategies for reducing organizational trauma with respect to the mediating variable of emotional intelligence in small and medium businesses in Anar County. This research is applicable in terms of its purpose, and descriptive in terms of its type and nature. The statistical population of this study includes 250 employees of small and medium businesses in Anar County. Due to the relative limitation of the statistical population, all its members were selected as a sample, and questionnaires were distributed and collected among them using the census method. To determine the validity of the questionnaires, the content validity ratio (CVR) and content validity index (CVI) were used. Finally, Cronbach's alpha coefficient was used to determine the reliability of the questionnaires. In order to examine the research hypotheses, structural equation modeling (SEM) through Smart PLS software was used. Based on the results, knowledge management strategy has a significant effect on reducing organizational trauma with respect to the mediator variable of emotional intelligence in small and medium-sized businesses. Introduction In organizations, knowledge management strategy and emotional intelligence are key factors for reducing organizational trauma. Organizational trauma refers to the negative effects of traumatic events on individual and organizational performance, which can lead to a decrease in employee trust and motivation. Knowledge management includes the processes of creating, collecting, and sharing knowledge that can lead to competitive advantage, and is divided into two types of explicit and tacit knowledge. Emotional intelligence is related to the ability to understand and manage one's own and others' emotions and can facilitate the improvement of personal relationships and employee resilience. Combining knowledge management strategies and strengthening emotional intelligence can create a healthier work environment and make employees more resilient to traumatic events (Moallemian & et al., 2021). In today's world, especially in small and medium-sized businesses, psychological pressures and organizational crises have increased, and organizational trauma can lead to reduced productivity and burnout. Knowledge management as a strategic approach can help reduce organizational trauma by facilitating the flow of information and enhancing learning. Also, emotional intelligence as a mediating factor can strengthen the effectiveness of knowledge management in reducing organizational trauma. This research focuses on small and medium-sized businesses and identifies effective mechanisms in reducing psychological harm, while also paying attention to the lack of studies in this field (ILO, 2023). The results of this research will not only help improve mental health and increase productivity in SMEs, but can also be a model for other organizations in dealing with crises and human knowledge management; in other words, researchers seek to answer the question: does knowledge management strategy have a significant effect on reducing organizational trauma with respect to the mediator variable of emotional intelligence in small and medium-sized businesses? Theoretical foundations Knowledge management Today, human life is influenced by cyberspace and new concepts such as knowledge-based society and knowledge management. The emergence of knowledge management as a response to organizational changes and knowledge-based jobs has led to flatter structures and reduced bureaucracy. These changes have necessitated the need for innovation and increased learning in organizations and have exacerbated the uncertainty of the business environment. Knowledge management is divided into two types of knowledge: Explicit knowledge: objective and expressible knowledge available in information systems, documents, and databases. Implicit knowledge: informal and experiential knowledge that is in the minds of individuals and is difficult to transfer (Behboudi & Sohrabi, 2019). Organizational trauma Organizational trauma theory addresses the trauma and emotional trauma that organizations experience. Similar to individual psychological trauma, this theory refers to the negative effects of frightening experiences on organizational performance and behavior (Abbasikhah & Behboudi, 2016). Spiegel (2008) defines trauma as a disorder in an individual’s control, and Corsini (2002) considers it the result of painful events that have lasting effects on the individual’s personality. Trauma can reduce an individual’s ability to cope with adverse situations and can lead to symptoms such as desensitization and decreased immunity (Kelly, 2014). Horman and Vivan (2017) define organizational trauma as dysfunctional changes in organizational behavioral patterns that can have negative effects on the development and identity of the organization (Venugopal, 2016). Failure to pay attention to this phenomenon can reduce the organization’s ability to deal with crises (Kleinberg, 2016). Organizational trauma theory is known as a framework for understanding stressors and providing effective solutions for their management (Rozensky et al., 2016). This phenomenon is especially common in service organizations and can create an atmosphere of despair and hopelessness in the organization. Employees in these organizations are affected by the situation, and their skills and motivation may be affected (Jirek, 2020). Emotional Intelligence As one of the key topics in psychology, intelligence includes traits and talents that are not directly observable. In 1958, Gardner proposed the theory of multiple intelligences, one of which is emotional intelligence (Kelishami et al., 2016). Mayer and Salovey defined emotional intelligence as the ability to recognize and manage one’s own and others’ emotions (Rezaei Dizgah et al., 2018). Research shows that emotional intelligence can predict mental health and lead to a positive outlook, optimism, and more stable social relationships (Dakal, 2016). Research Background Zhang and Zheng (2023) conducted a study entitled “Investigating how emotional intelligence affects knowledge management strategies and its impact on organizational resilience.” The results show that emotional intelligence can act as a mediator in improving knowledge management strategies. Mohammad and Ali (2022) conducted a study entitled Investigating the Effect of Knowledge Management Strategies on Reducing Organizational Trauma and the Mediating Role of Emotional Intelligence. The results indicate the importance of emotional intelligence in improving the positive effects of knowledge management. Research Methodology This study is "applicable" in terms of its purpose, and "descriptive" in terms of the method of data collection. The statistical population of this study included 250 employees of small and medium-sized businesses in Anar County. Given the relative limitations of the statistical population, all its members were selected as a sample and a questionnaire was distributed and collected among them using the census method. 8 items and 2 components (written knowledge management strategy, personal knowledge management strategy) were extracted from the Knowledge Management Strategy Questionnaire by Lopez-Nicolas and Merono-Cardin (2011);, 22 items and 5 components (goals, structure, technology, people, environment) from Organizational Trauma Questionnaire (Dihim and Dolati, 2017); and 28 items and 4 components (self-awareness, self-management, social awareness, relationship management) from Bradbury and Graves' (2004) Emotional Intelligence Questionnaire. Also, the Content Validity Ratio (CVR) and Content Validity Index (CVI) were utilized to determine the validity of the questionnaires. Finally, Cronbach's alpha coefficient was used to determine the reliability of the questionnaires. Structural equations were used to analyze the data and examine the relationships between variables. This method allows us to examine the direct and indirect effects of variables and identify more complex structures. The use of structural equations in this study helps to comprehensively and accurately analyze the relationships between knowledge management strategy, emotional intelligence, and organizational trauma. Findings There is a significant effect between knowledge management strategy on reducing organizational trauma with respect to the mediator variable of emotional intelligence in small and medium-sized businesses. The path coefficient of the variable between knowledge management strategy and organizational trauma in small and medium-sized businesses is -0.520, and the t-statistic is -4.902. The path coefficient of the variable between knowledge management strategy and emotional intelligence in small and medium-sized businesses is -0.968, and the t-statistic is -13.768. The path coefficient of the variable between emotional intelligence and organizational trauma in small and medium-sized businesses is -0.751, and the t-statistic is -6.445. Therefore, there is a significant effect between knowledge management strategy on reducing organizational trauma with respect to the mediating variable of emotional intelligence in small and medium-sized businesses. Discussion and Conclusion The main objective of this study was to investigate the effect of knowledge management strategies on reducing organizational trauma with respect to the mediating role of emotional intelligence in small and medium-sized businesses. The results of the main hypothesis showed that knowledge management strategies lead to an increase in the emotional intelligence of employees and, as a result, organizational trauma is reduced. These findings are consistent with the results of previous research of Moallemian et al. (2021) and Karimian Eqbal (2019), and emphasize the importance of knowledge management and emotional intelligence in reducing organizational trauma. Based on the studies conducted, it can be concluded that knowledge management strategies not only help reduce organizational trauma, but also play a positive role in strengthening the emotional intelligence of employees. These communications can help small and medium-sized business managers to improve organizational conditions and prevent the occurrence of organizational trauma by effectively applying these strategies. Knowledge management strategies include collecting, storing, and sharing information and knowledge in organizations. These strategies can help reduce organizational trauma because they increase the sense of security and trust in employees by creating a learning culture and improving internal communications. The results of this study are consistent with the results of Morris et al. (2021) and Johnson et al. (2021). Knowledge management strategies can help develop emotional intelligence in employees. By providing learning opportunities and sharing experiences, employees can strengthen their social and emotional skills. The results of this study are consistent with the results of Smith et al. (2020) and Nicholas et al. (2019). Emotional intelligence is known as a key factor in managing stress and coping with challenges. People with high emotional intelligence are better able to cope with organizational pressures and prevent organizational trauma. The results of this study are consistent with the research of Harris et al. (2020) and Garcia et al. (2019).

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

Abstract The aim of this research is to test the digital marketing model for the internationalization of small and medium-sized dairy companies. The present research is applicable in terms of its purpose, and descriptive-survey in terms of its nature and method. The statistical population of the present research includes 289 managers and experts of the dairy industries of Mazandaran province. The Cochran formula was used to determine the sample size and 165 people were selected as samples using stratified random sampling. The collection tool in the present research includes a researcher-made questionnaire. SPSS and PLS software were used to analyze the findings. According to the results, the main themes include digital marketing content, digital marketing tools, digital advertising, digital sales development, and digital customer relationship management. Among them, the theme of a strong presence in the digital space is of first importance, and the theme of analyzing and understanding international markets is of second importance, the theme of using innovative international digital marketing models is of third importance, the theme of creating a global brand is of fourth priority and importance, the theme of complying with international laws and standards is of fifth importance, and finally, the theme of cooperating with international business partners is of sixth importance. Also, the adaptation and adaptation of the obtained digital marketing model for the internationalization of small and medium-sized dairy companies in Mazandaran province has been assessed as appropriate. Introduction The extensive growth of technology and the increase in people's access to the Internet have paved the way for the transition to digital marketing. Evidence indicates that digital marketing has gradually replaced conventional marketing, meaning that its effects on customers' lives have become more important. This is a reality that current businesses must accept and embrace digital marketing (Rahmani et al., 2023). Industries and companies use digital marketing not only to carry out marketing activities within their borders and geographical areas, but digital marketing is also considered a suitable model for cross-border activities and exports (Zahoor & Lew, 2023). In recent years, the dairy industry has faced a reduction in the scope of export markets and sinusoidal exports for various reasons, which requires a solution to completely overcome such conditions. The potential capabilities of the country's dairy companies, as well as the existence of potential and diverse markets for exporting dairy products in the Middle East, Asia and Eurasia, provide the conditions for reclaiming past markets and even expanding markets along with improving and increasing continuous and sustainable exports (Dadashi Jokandan et al., 2022). Now, producers and customers have become more aware of the transparency, health and environmental impacts of product production and service provision activities. Changes in customer and market demands have forced producers to abandon short-term gains and consider long-term development of dairy production, distribution, and sales using digital marketing. It seems that companies active in the dairy industry are also forced to use digital marketing (Ikramov et al., 2021). The dairy industry is important in the economy of Mazandaran province and its importance is expected to increase in the next few years. Therefore, dairy industry marketing, which takes into account all current technology-based tools and facilities, is very important for growth in international and domestic markets. Despite valuable efforts to develop exports in the dairy sector for easy and correct management, no practical model has been presented so far for developing dairy product exports in this province. Therefore, the main question of the present study is: how to test the digital marketing model for the internationalization of small and medium-sized dairy companies? Theoretical Framework Digital Marketing Digital marketing means achieving marketing goals using the methods and tools of the digital technology world. In this method, all possible capacities and channels available in the digital world are used to deliver information to the customer or consumer. The use of digital tools (to introduce a product, attract customers, build a brand, and sell) is called digital marketing. In other words, the business owner introduces his product to customers through digital marketing tools and tries to increase sales (Diss & Henberry, 2020). Internationalization of Small and Medium-sized Businesses A small and medium-sized enterprise (SME) is a business with fewer than a certain number of employees. This limit varies in different countries and economies, but in many societies, including the European Union, it is considered 250 people. Small and medium-sized enterprises have an important place in the literature on organization and management. When talking about such companies, they mostly refer to companies that were formed based on entrepreneurship. Various types of spin-offs, startups, science and technology park companies, knowledge-based companies, and companies operating in industrial parks fall into this category (Amini & Fatahi, 2018). Beigloo et al. (2025) studied the provision of an appropriate digital marketing model for Iranian small and medium-sized industries. The research findings indicate 6 dimensions (including: marketing strategy, digital content marketing, appropriate digital tools, customer engagement, visitor conversion, interaction with target customers), 18 components and 54 indicators that determine the digital marketing model in Iranian small and medium-sized industries. The research results show that the dimensions, components and indicators extracted from the meta-synthesis method (research model) were approved by the target community. Also, in the ranking of digital marketing dimensions for small and medium-sized industries, among the 6 dimensions; “Reaching the target customer and interacting with them” and “Customer engagement” are in first place and “Visitor conversion”, “Digital content marketing”, “appropriate digital tools” are in second place and finally “Marketing strategy” is in third place. Zarei & Mohammad Khani (2024) stated in a study entitled A Model for Improving Digital Marketing Capabilities with Emphasis on Digital Marketing Usage Indicators in Industrial Companies that the convergence of information, media, and communication technologies has changed consumer behavior in terms of searching, obtaining, processing, and responding to company information or services. And the model for improving marketing capabilities has been designed with an emphasis on digital marketing usage indicators in industrial companies. Research Methodology The purpose of the present study is to test the digital marketing model for the internationalization of small and medium-sized dairy companies. This research is applicable in terms of purpose, and descriptive-survey in terms of nature and method. The statistical population of the present study includes 289 managers and experts in the dairy industries of Mazandaran province. The Cochran formula was used to determine the sample size, and 165 people were selected as samples using stratified random sampling. The collection tool in the present study includes a researcher-made questionnaire. Research findings SPSS and PLS software were used to analyze the findings. According to the results, the main themes include digital marketing content, digital marketing tools, digital advertising, digital sales development, and digital customer relationship management. Among them, the theme of a strong presence in the digital space is of first importance, and the theme of analyzing and understanding international markets is of second importance, the theme of using innovative international digital marketing models is of third importance, the theme of creating a global brand is of fourth priority and importance, the theme of complying with international laws and standards is of fifth importance, and finally, the theme of cooperating with international business partners is of sixth importance. Also, the consistency and fit of the obtained digital marketing model for the internationalization of small and medium-sized dairy companies in Mazandaran province has been assessed as appropriate. Conclusion The present study was conducted with the aim of testing the digital marketing model for the internationalization of small and medium-sized dairy companies. The results of this research are somewhat similar to the results of Beigloo et al. (2025), Zarei & Mohammad khani (2024), Dalili et al. (2024), Moradi ziba et al. (2023), Jahandideh & Bahramzadeh (2023), Rahmani et al. (2023), Javid et al. (2023), Raja (2023), Jadhav et al. (2023), Thaha et al. (2021), Quirós-Gómez & Arce-Gutiérrez (2020), Pakparvar et al. (2020), Jadhav et al. (2023), Khaerani et al. (2023), Klapkiv et al. (2023), Borhani et al. (2023), Bulegoda & Fernando (2023), Asgarnezhad (2023), and Nouri et al. (2020). Jadhav et al. (2023) stated the various benefits received by SMEs due to digital marketing in different capacities that can help organizations to improve their productivity. The mind map presents the idea of ​​the impact of SMEs on their various functions in rural as well as urban areas. According to the results of the study, the following suggestions were made: Creation of target market database: Creation of a comprehensive database for information related to the needs, preferences and behavior of customers in target markets. Precise targeting of digital advertising: Use market information to create targeted advertising campaigns on social networks and search engines.

Abstract The aim of this study is to investigate the dynamics of brand value in the Iranian dairy market and analyze the effect of multi-channel advertising, market share, and competitive intensity on the persistence of leading brands. Panel data from five major dairy brands during the period 2021 to 2024 were used to model the effects of television and digital advertising, market share, and local competition intensity on perceived brand value. Two non-dynamic empirical models, FE-2SLS and dynamic System GMM, were used to analyze the short-term and long-term effects of these variables. The results showed that television and digital advertising have a positive and significant effect on brand value. Specifically, the coefficients of television advertising were 0.091 for milk and 0.081 for cheese, while digital advertising had coefficients of 0.054 and 0.059, respectively. Also, the negative effects of advertising saturation and neighborhood competition intensity were observed in reducing brand value; the advertising saturation coefficients for milk and cheese were -0.011 and -0.010, respectively. In addition, market share had a positive effect on brand value, with market share coefficients of 0.023 for milk and 0.0201 for cheese. Also, the market concentration index (HHI) showed a positive and significant effect on brand value in both products. These results indicate that brands with higher market share can exploit advertising more effectively. These findings are consistent with the relatively concentrated structure of the Iranian dairy market and consumer loyalty to leading brands. In general, balanced advertising and strategies based on market share and competition can help sustain and increase brand value in the short and long term. Introduction The aim of this research is to dynamically examine the perceived brand value in the Iranian dairy market and analyze the impact of multi-channel advertising, market share, and competition on the position of leading brands in this industry. Over recent decades, Iran's dairy industry has experienced significant changes, including increased production capacity, expanded distribution networks, and the digitization of communication channels with consumers. These transformations are particularly significant for milk and cheese, as these two products are staples in the food basket of Iranian households, and their repeated purchase plays an essential role in consumer behavior. The necessity of conducting this research has emerged from the intersection of three facts: the stagnation or decrease in domestic consumption despite the nutritional importance of dairy products (Aaker, 1991; Keller, 1993), the pressure caused by market concentration, and the need for evidence-based policy-making to maintain a balance between exports and consumer welfare (FAO, 2023; Tirole, 1988), and the rapid migration of advertising budgets to digital media, which has increased the risk of inefficiency (De Haan et al., 2016; Kannan & Li, 2017; Bagwell, 2007; Mishra et al., 2025). Meanwhile, recent studies have shown that several factors, such as brand sensory experience (Mohammadnezhad & Rezaei Dizgah, 2025), personalized advertising on social media (Doroudi & Babaei, 2025), and brand knowledge and perceived quality (De Haan et al., 2016; Kannan & Li, 2017; Bagwell, 2007; Mishra et al., 2025), can enhance customer loyalty and future purchases. These findings underline the importance of scientifically analyzing brand value in various industries, but the dynamic and simultaneous analysis of television and digital advertising along with competitive structures in the Iranian dairy industry remains overlooked. Therefore, the main research question is: In the Iranian dairy market, what impact do television and digital advertising, market share, market concentration, and local competition intensity have on perceived brand value, and how sustainable are these effects in both the short and long term? Theoretical Framework Brand value is a fundamental concept in marketing literature, defined and expanded by Keller (1993) and Aaker (1991). In this framework, brand value is shaped by components such as brand awareness, brand associations, and customer loyalty, and as an intangible asset, it enhances a firm's ability to maintain higher prices, attract customers, and reduce price sensitivity. In other words, the more consumers have awareness and positive attitudes toward a brand, the greater their willingness to buy and their long-term loyalty, thus increasing brand value. In this context, multi-channel advertising, especially the combination of television and digital media, plays a key role in strengthening brand value. Recent studies have shown that television advertising can build trust and offer broad coverage, while digital advertising provides the ability to target more precisely and interact directly with customers (De Haan et al., 2016; Kannan & Li, 2017). The effect of these two channels can either complement each other (especially in the early stages of the purchase funnel) or, in some cases, act as substitutes. Therefore, the simultaneous examination of television and digital advertising is essential and the focus of this research. Another key concept is local competition intensity (LCI). This concept suggests that the closer two brands are in terms of attributes like price, quality, packaging, and brand positioning, the more competitive pressure they exert on each other, which consequently reduces the effectiveness of their advertising. This idea is rooted in spatial competition literature (Hotelling, 1929; Hauser & Shugan, 1983) and becomes particularly relevant in markets like dairy, where products have similar characteristics. Moreover, the role of market share and concentration has also been emphasized in the theoretical literature. Evidence shows that larger brands, due to their extensive distribution networks, greater financial resources, and consumer loyalty, achieve higher returns from advertising (Sethuraman et al., 2011). On the other hand, the level of market concentration (usually measured by the Herfindahl-Hirschman Index - HHI) can determine how advertising will impact competition dynamics. In concentrated markets, advertising often strengthens the position of leading brands, while in fragmented markets, its effects are more evenly distributed among competitors. This research is based on the integration of three theoretical foundations in the fields of microeconomics, marketing, and competitive market analysis. The main goal of designing this framework is to explain consumer behavior in brand selection, clarify firms' pricing strategies under competitive conditions, and analyze the effect of market share on perceived brand value. The starting point of this framework is the definition of brand value in marketing literature, where Keller (1993) and Aaker (1991) explain brand value based on components like awareness, brand associations, and customer loyalty. Consequently, it is expected that stronger brands can reduce customer price sensitivity and establish a more sustainable position in the market. To model this situation, the classical Hotelling (1929) model has been used; a model that is one of the most recognized frameworks in spatial competition analysis. In this model, firms and consumers are assumed to be in a linear or multidimensional space, and each consumer chooses a brand based on the lowest "total cost." This total cost includes two components: the price of the product and the cost of distance, or the degree of mismatch between the product's attributes and the consumer's preferences. In this study, the Hotelling model is extended to a K-dimensional space, where each axis represents a distinct product attribute such as taste, durability, packaging, or price. The Iranian dairy market is an example of such a space, as brands are positioned relatively fixed and consumers are distributed in this space based on their preferences. Conceptual Model of the Research The conceptual model of this research is based on theoretical foundations and previous studies. The positive and negative relationships between variables have been extracted with reference to the spatial competition model of Hotelling (1929), brand value literature (Aaker, 1991; Keller, 1993), and recent studies in multimedia advertising and competition (De Haan et al., 2016; Bonfrer et al., 2008; Shahbazi, 2023). Research Methodology This research is applicable in terms of purpose, and descriptive-analytical in nature, and it follows a positivist paradigm with a quantitative approach. The statistical population of the research includes five major dairy brands in Iran (Kalleh, Mihan, Pegah, Ramak, and Sabah) and two highly consumed products: pasteurized milk and cheese. The study period is from 2021 to 2024. Data collection methods combine archival and field sources. Sales data and television advertising data were obtained from official reports, while the cost data for digital campaigns were extracted from platforms such as Dima, Yektanet, Aparat, and Instagram. Brand perception indicators (awareness, attitude, and consumer preference) were collected through field surveys among 350 households in Tehran. For data analysis, three-dimensional panel data (brand-product-time) were used. In the first step, the static FE-2SLS model was estimated to determine the short-term effects of advertising, market share, and market structure. In the second step, to account for brand value sustainability and cumulative advertising effects, the dynamic model and System GMM estimator were used. This approach was chosen to address the endogeneity problem of variables and provide reliable results. Research Findings The results showed that both television and digital advertising have a positive and significant impact on brand value. The coefficients for television advertising were 0.091 for milk and 0.081 for cheese, indicating a positive and significant impact on brand value in the short term. These effects are especially more noticeable in brands that are in the early stages of entering the market or during high-traffic advertising periods. On the other hand, the coefficients for digital advertising were 0.054 for milk and 0.059 for cheese, showing a positive effect, although it was generally lower than television advertising. These findings highlight the importance of both television and digital advertising in enhancing brand value in the Iranian dairy market. Alongside this, negative effects of advertising saturation and local competition intensity were observed in decreasing brand value. The advertising saturation coefficients for milk and cheese were -0.011 and -0.010, respectively, indicating that excessive advertising can negatively affect consumers' perception of the brand. This is especially true when the market reaches saturation, and consumers become indifferent to advertising. Additionally, market share had a positive and significant effect on brand value, with coefficients for market share of 0.023 for milk and 0.020 for cheese, indicating the direct impact of market share on strengthening brand value. These results are particularly evident in brands with larger market shares, as larger brands can utilize more resources for advertising and thus benefit from greater advantages. Discussion and Conclusion The findings of this research indicate that leading brands in the Iranian dairy market can effectively strengthen their position in consumers' minds through television and digital advertising. Brands with higher market shares, in particular, are able to leverage advertising more effectively. However, local competition and advertising saturation can have negative effects on brand value. These results are consistent with the relatively concentrated structure of the Iranian dairy market and consumer loyalty to leading brands. In general, balanced advertising and strategies based on market share and competition can contribute to the sustainability and growth of brand value in both the short and long term.