https://www.jnamm.ir/ Journal of New Approaches in Management and Marketing en daily 1 Fri, 20 Feb 2026 00:00:00 +0330 Fri, 20 Feb 2026 00:00:00 +0330 https://www.jnamm.ir/article_237568.html 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. https://www.jnamm.ir/article_237569.html 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. https://www.jnamm.ir/article_237742.html 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. https://www.jnamm.ir/article_238081.html 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. https://www.jnamm.ir/article_238824.html 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). https://www.jnamm.ir/article_238921.html 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. https://www.jnamm.ir/article_241663.html The aim of the present study is to identify the most effective and efficient dimensions of the indigenous model of succession planning appropriate to the organizational culture in Barez Industrial Group. The research method is applied in terms of its purpose and quantitative in terms of its implementation method. The statistical population of the study consisted of 15 senior managers, human resources experts, and board members of Barez Industrial Group. Sampling was carried out purposively using the snowball technique. The data collection tool was a semi-structured interview, and the interviews continued until theoretical saturation was reached. The DEMATEL method was used for analysis. The results showed that ten effective factors, namely organizational values ​​and attitudes, learning and development culture, organizational interaction and cooperation, organizational processes and structure, skills and human resource development, motivational systems and participation, flexibility and knowledge management, individual and personality characteristics, professional and managerial skills, and flexibility and managerial ability, were confirmed by experts. The findings showed that the organizational interaction and cooperation index is the most effective index, as well as individual and personality characteristics. https://www.jnamm.ir/article_241859.html The aim of this research is to investigate the mental models of experts in the application of blockchain technology in government organizations using Q methodology. The present research is applied in terms of purpose and implementation using a mixed method. The statistical population of the research consists of managers of government organizations, 19 of whom were selected as a statistical sample using purposive sampling and based on the principle of theoretical adequacy. According to the research approach in the qualitative part, first, a discourse space was obtained with 19 interviews, and using their views and opinions, the sample, Q option, and finally the Q set were obtained. Then, in the quantitative part of the research, the data obtained from the qualitative part were analyzed and examined using SPSS. The findings show that transparency, increasing productivity, increasing agility, preventing corruption, improving trust, improving electronic voting, managing secure identity, and improving innovation are eight mental models of managers in line with blockchain technology in government organizations. https://www.jnamm.ir/article_242113.html This study was conducted with the aim of investigating the role of neuromarketing in digital marketing. The research method, considering its purpose, is applied, and in terms of execution, it is quantitative, and in terms of nature and method, it is descriptive-correlational. The statistical population of the research consisted of customers of active online stores in Tehran province. Using a simple random sampling method and Cochran’s formula, 384 individuals were determined as the sample size. A standard questionnaire based on a 5-point Likert scale was used to collect research data. The content validity of the instrument was confirmed by specialists and experts, and to measure the reliability of the instrument, Cronbach’s alpha and composite reliability methods were used. By distributing the questionnaire, the validity of the instrument was measured using three methods: construct validity (outer model), convergent validity (AVE), and discriminant validity. The AVE value for all variables should be greater than 0.5. SPSS and PLS software were used for data analysis. The research findings indicate that the dimensions of neuromarketing (interest and engagement, knowledge and awareness, and ethics) have an impact on digital marketing. https://www.jnamm.ir/article_242146.html The aim of this research is to explore the dimensions and components of digital transformation management based on artificial intelligence in the education system. This research was conducted in a qualitative manner using thematic analysis method. Data collection and extraction of related themes were carried out using in-depth semi-structured interviews with key experts in this field. Participants were selected using purposive sampling and theoretical saturation criteria, based on which 12 experts were selected. To obtain the credibility and validity of the data, two methods were used: participant review and review of experts not participating in the research. Max Quda statistical software was also used to analyze the data. The results of the present study indicated that AI-based digital transformation management was designed in the form of four overarching categories: "contextual requirements", "digital infrastructure", "digital transformation management process", "organizational capital", 12 organizing categories: "ethical requirements", "cultural requirements", "organizational requirements", "hard digital infrastructure", "soft digital infrastructure", "digital transformation management process", "digital transformation planning", "prototyping", "learning", "human capital", "process capital", "structural capital", "social capital" and 73 basic categories. https://www.jnamm.ir/article_242194.html The aim of this study is to identify the dimensions and components of competitive advantage and innovation in policies for the creation and development of digital entrepreneurship in knowledge-based companies. In terms of purpose, this research is applied, and in terms of implementation, it adopts a qualitative approach. The statistical population of the study consisted of 15 experts, including university professors in the field of management and managers of knowledge-based companies in the city of Kerman. To select the sample, purposive sampling was employed while considering the diversity of experts (managers, academics, and employees), and interviews continued until theoretical saturation was achieved.Data were collected through semi-structured interviews. Data analysis was conducted using coding and thematic analysis with the support of MAXQDA software. The results indicated that the most important themes in this area include research and development, the use of emerging technologies, the creation of digital business models, data-driven decision making, digital networking, cybersecurity, the development of e-commerce, digital management and online human resources, the development of digital markets, digital investment, and the attraction of digital financial resources.These findings suggest that digital entrepreneurship in knowledge-based companies encompasses multiple dimensions that can contribute to improving the performance and competitiveness of these firms. https://www.jnamm.ir/article_242207.html This study aims to design a model for enhancing employee performance effectiveness based on cultural components in the digital era at Melal E‑Commerce and Information Technology Company. The research adopts a qualitative approach within an interpretive paradigm and is conducted using a thematic analysis strategy.The statistical population consisted of 10 experts, including university professors in the field of management with at least ten years of relevant professional and academic experience and a deep understanding of the concept of enhancing employee performance effectiveness based on cultural components in the digital era at Melal E‑Commerce and Information Technology Company. The participants were selected through purposive sampling. Data were collected using semi‑structured interviews. The collected data were analyzed using thematic analysis.The findings of the study revealed six main themes: digital acceptance culture, ethical leadership style, organizational culture, cultural competence of employees and managers, cultural accountability of employees and managers, and cultural and psychological empowerment. In addition, 33 organizing themes were identified that influence the enhancement of employee performance effectiveness based on cultural components in the digital era at Melal E‑Commerce and Information Technology Company.The study provides a conceptual framework for developing a qualitative model to enhance employee performance effectiveness grounded in cultural components in the digital era within Melal E‑Commerce and Information Technology Company. https://www.jnamm.ir/article_242224.html This study aims to systematically identify and refine the components of audience-centricity in the arts, . Employing an exploratory sequential mixed-methods approach, the research was conducted in two main phases. In the qualitative phase, using purposive sampling, 19 authoritative scientific articles were subjected to in-depth analysis through qualitative content analysis facilitated by NVIVO software yielded 39 initial codes, nine axial categories, and ultimately four core components. In the quantitative phase, fuzzy screening technique was employed to refine the components within the specialized context of the arts, utilizing the opinions of 12 experts . Data were collected using a researcher-developed questionnaire .The findings revealed that out of the 39 initial indicators, 11 were confirmed as the final components of audience-centricity in the arts, with three indicators—"investment in continuous learning and capability development," "adherence to privacy and data ethics," and "transparency in actions and communications"—attaining the highest level of importance. The alignment of the findings with the theoretical background not only confirms foundational theories such as market orientation and value co-creation but also demonstrates the study's innovation in introducing an "ethical-strategic framework" as the core of audience-centricity in the age of digital art. https://www.jnamm.ir/article_242238.html The purpose of this research is analyzing and localizing brand authenticity components in the healthcare industry. Aiming to propose a localized model, this study first identified 15 primary brand authenticity factors through a systematic literature review and qualitative content analysis utilizing NVIVO software. Subsequently, these factors were localized for the Iranian healthcare context through the Delphi method involving 12 academic and industry experts, resulting in 12 final validated factors, including transparency and honesty, strong brand legacy, existential originality, and brand sustainability and social responsibility. The findings indicate that the alignment between a healthcare organization's declared values and its actual performance serves as the fundamental basis for patients' perceptions of authenticity. By focusing on localized dimensions, this research offers a scientific framework for healthcare managers and policy makings to fundamentally transition from intuitive to evidence-based decision-making, thereby facilitating the strengthening of patients' networked trust and the enhancement of the therapeutic experience quality. https://www.jnamm.ir/article_242319.html This study aimed to investigate the relationship between administrative automation, organizational agility, and organizational health, considering organizational structure dimensions as a mediating variable in the General Department of Ports and Maritime Affairs of Bushehr Province. The current research is a descriptive-correlational study conducted cross-sectionally in the year 2025 among all employees of the General Department of Ports and Maritime Affairs of Bushehr Province. The total number of employees is 600, and from this number, 234 were selected as the sample size based on simple random sampling proportional to the population size and according to Cochran’s formula. To collect data, four questionnaires were used: Administrative Automation Questionnaire (Ahangarpour, 2008), Organizational Agility Questionnaire (Zhang & Sharifi, 2000), Organizational Health Questionnaire (Hoy & Feldman, 1996), and Organizational Structure Questionnaire (Robbins, 1979). The administrative automation questionnaire has 30 questions with validity and reliability of 0.90 and 0.93, respectively. The organizational agility questionnaire has 28 questions with validity and reliability of 0.88 and 0.86, respectively. The organizational health questionnaire has 44 questions with validity and reliability of 0.91 and 0.85, respectively. The organizational structure questionnaire has 24 questions with validity and reliability of 0.87 and 0.93, respectively. All statistical analyses were performed using SPSS and LISREL computer software. The results of data analysis indicate a significant relationship between administrative automation, organizational agility, and organizational health, considering the mediating variable of organizational structure dimensions in the General Department of Ports and Maritime Affairs of Bushehr Province. Conclusion: The organizational structure plays a very important role in achieving the organization’s goals, especially organizational health and agility, due to the type of service the organization provides. https://www.jnamm.ir/article_242348.html The aim of this study is to examine the modeling of psychological characteristics of the founders of small and medium-sized enterprises (SMEs) in the industrial cooperatives of Mazandaran Province. The present research is applied in terms of purpose and quantitative in terms of methodology. The statistical population consists of 893 business founders across the province, based on the definition provided by the Global Entrepreneurship Monitor (GEM). Using Cochran’s formula, a sample size of 186 individuals was selected through simple random sampling. The data collection instrument was a questionnaire developed by Kiggundo (2002). SPSS and LISREL software were employed for data analysis.The findings indicate that the overall psychological construct under investigation—analyzed within a path analysis measurement model (structural equation modeling)—explains the process of business start-up both directly, indirectly, and interactively. Among the examined variables, the sub-variable of internal locus of control demonstrated the greatest overall influence. Other variables, including tolerance of ambiguity, autonomy at work, need for achievement, motivation, and risk-taking, ranked respectively in subsequent levels of importance.The study concludes by recommending that policymakers and relevant authorities, in addition to considering other contextual factors, should also pay careful attention to these psychological variables in order to enhance the business start-up process and promote productive employment.