Journal of System Management(JSM)

Today, electric energy is a strategic energy carrier in infrastructure, essential for sustainable growth and development in various dimensions of societies. Simultaneously, the scarcity of primary resources and the increasing demand for energy, while considering the rights of future generations, emphasizing the importance of enhancing performance excellence and promoting a spirit of responsibility. This research introduces a developed value-based performance excellence model with a sustainable electricity supply chain approach. In this model, theme analysis is utilized to extract indicators that represent effective components within the organization, categorized as organizational capabilities. Confirmatory factor analysis is employed to assess the validity and reliability of criteria and sub-criteria. To demonstrate the model's efficiency and explore the relationship between organizational capability criteria, organizational focus and the stability of the electricity supply chain, a comprehensive study was conducted in companies within the three sectors of electricity production, transmission and distribution in Iran. The findings underscore the significance of considering all three sectors' efficiency when examining the relationships between organizational capability, organizational focus and sustainable development.

The aim of this study was to design a model for identification and ranking of factors influencing the selection of suppliers of Iran's National Steel Industrial Group. In terms of the method, the current research is part of the descriptive research and based on its main purpose, it is an exploratory and confirmatory study, and in terms of the applied purpose. After filtering the criteria, based on the DEMATEL technique, the desired criteria affecting the evaluation and selection of suppliers will be determined and the relationship between them and the modeling of these relationships will be done. In the third step, the ANP method is used to weight the criteria. Finally, in the fourth stage, the questionnaire to determine structural modeling relationships is completed by the experts of the organization and using the data obtained from the questionnaires, the method of structural equations is used to confirm the exploratory model. The technique used in the current research was an in-depth interview-Delphi method, a statistical population of 10 knowledgeable experts on the subject of the research, and a non-probability chain sampling method. The results of the research showed that the factor of product authenticity and compliance with the standards and requested analysis of the product are in the first rank and the factors of authentic or exclusive representative of goods and after-sales services (guarantee and warranty) are in the second and third ranks, respectively.

Having a comprehensive view of digital marketing capabilities is essential for companies to survive in the revolutionized digital world. Specifically, in B2B commerce, is a game-changer, turning complex sales cycles into efficient that boost client engagement and drive rapid growth. Accordingly, the purpose of the present research is to design a model for developing digital marketing capabilities in B2B markets. Emphasizing B2B marketing, this research has adopted a qualitative approach. A model is developed through grounded - theory and in-depth semi-structured interviews with 12 experts of medical and industrial gases industry. The collected data has been analyzed with the three-step coding method and Nvivo10 software. The data has categorized into 6 main categories including; casual conditions (dominance of the Internet, development of international relations in B2B markets and digital marketing features), intervening conditions (manager's attitude and cooperation of different units of organization), contextual conditions (changing the way B2B customers choose suppliers and predominance of classic approach in B2Bmarkets), methods (e-mail marketing, website, etc.), consequences(customer retention and loyalty and increasing the growth rate of the organization) and main phenomenon (development of digital marketing capability in B2B market). This model provides a comprehensive mental framework for the managers of this field regarding the capabilities of digital marketing.

Today, considering that the growth and flourishing of any organization depend on the knowledge and capabilities of its leaders, the first and most important step in this path is to identify the level of knowledge and ability of the leaders within an organization. The most effective tool for understanding the awareness of managers is to recognize their competencies within the organization. The aim of the present research was to design a comprehensive leadership model. A qualitative case study research design was employed. Participants were selected using purposive sampling and theoretical saturation criteria, resulting in 27 elites and faculty members from Fars Province being chosen for interviews. To obtain the credibility and validity of the data, participant response review methods were used, and reliability was assessed using the Holistic coefficient, which was found to be 0.81. The findings of the research indicated that the comprehensive leadership competency model consists of four overarching themes: clear thinking, which includes future thinking, team thinking, conceptual thinking, and creative thinking; self-leadership, which encompasses self-management, accountability, flexibility, resilience, and continuous learning; guiding others, which includes empathy, perception and evaluation, multigenerational leadership, communication skills, writing skills, and diplomacy; and knowledge management, which involves negotiation, conflict management, coaching, customer orientation, problem-solving, and authenticity.

In the contemporary day, where digital technologies profoundly impact all facets of human existence, effective policymaking in digital media is crucial. Considering the substantial influence of these media on public opinion, political and social communications, as well as their profound effects on cultural and economic aspects of societies, the imperative for a meticulous and exhaustive assessment of the policies implemented in this area is more evident. Given the intricate and multifaceted characteristics of digital media policymaking, the application of soft operational research methodologies can provide more thorough and agreeable outcomes. This research investigates the methodologies of soft systems and cognitive mapping as analytical instruments for assessing digital media policymaking. This methodology enables the identification of current concerns and issues, while also assessing capacities and potential for enhancement, thereby offering a thorough and pragmatic framework for effective policymaking in this domain. The data necessary for constructing the conceptual model of this research were obtained by examining prior studies and conducting comprehensive interviews with experts and specialists in digital media. In analyzing the present condition of the media and communication sector, a significant observation, akin to various social and cultural domains, is the occurrence of cultural lag, wherein the rapid progression of communication technologies has surpassed the capacity of society and policymakers to adjust and formulate suitable content strategies. This research indicates that modifications in the "content" domain are crucial for effective policymaking in digital media.

Efficient management of liquidity and inventory is a critical challenge in production planning, especially for organizations aiming to optimize financial performance while mitigating risks. This study introduces a novel mathematical model that integrates accounts receivable financing into production planning. Unlike traditional models, our approach explicitly incorporates parameters such as cash inflows, advance payments, and bank discount rates, while addressing constraints related to liquidity, inventory balance, and credit limits. The objective function is designed to maximize liquidity at the end of the planning horizon, ensuring financial stability and operational efficiency. The model employs advanced optimization techniques, including linear and nonlinear programming, to provide actionable insights for decision-makers. Sensitivity analyses highlight its adaptability to dynamic market conditions, such as demand fluctuations and interest rate changes. The results demonstrate the model’s potential to reduce financial risks, improve cash flow, and optimize resource allocation across periods. This work serves as a practical framework for managers in diverse industries, offering a comprehensive solution to production planning challenges. Limitations and future research opportunities are also discussed to inspire further advancements

Oil and its derivatives are among the non-renewable natural resources that constitute a significant portion of the annual income of several countries. A critical question that arises in this context is whether oil revenues can foster economic growth and development in oil-producing nations or not. Additionally, given the increasing importance of domestic financial markets in recent years, it is essential to examine these markets to better understand the relationship between economic growth and oil revenues. This study investigates the oil revenues and economic growth, with a particular focus on domestic financial markets in crude oil-producing countries, using the Generalized Method of Moments (GMM) method in the period from 2000 to 2020. The results showed that the lagged variable of gross domestic product per capita, the variable of domestic credit to the private sector by banks, and the variable of private credit by monetary banks and other financial institutions to GDP influence GDP per capita. Furthermore, the coefficient for the share of oil revenues in total income is negative, though not statistically significant. In other term, in oil-producing countries, an increase in oil revenues is associated with a decrease in GDP per capita, indicating that oil revenues have not been able to play a substantial role in the economic growth of these nations.

The first and most important goal of investors in the stock market is to grow their investment portfolio. Meanwhile, behavioral factors emerge as one of the most important factors that prevent optimal decision-making. Many studies have identified and introduced these factors. However, prioritizing these factors and identifying causal relationships between these factors has been neglected. Therefore, this study was conducted to prioritize and explain causal relationships between the most important behavioral biases of retail investors in the Tehran Stock Exchange. Given the qualitative and quantitative nature of the data used in this study, a Fuzzy Cognitive Mapping Approach was used. Therefore, 30 behavioral biases were discussed and examined by 15 experts, and the causal relationships between them were explained and prioritized. Accordingly, the distribution effect biases, the Salience data Bias, and the Loss Aversion Bias were introduced as the most important, and the forgiveness biases, Evolutionary Bias, and Money Illusion Bias were introduced as the least important behavioral biases. Also, behavioral biases were grouped into four categories, which in order of importance are: perceptual, experiential/informational, personality, and emotional.