Abstract Ecosystems have been popularized as a tool for organizing and managing a wide range of businesses due to their advantages and benefits required by today's markets. Energy markets, as development infrastructures in societies, can also benefit from the capacities of ecosystems for optimal efficiency due to their strategic and complex nature. Lack of understanding of the nature, dimensions, prerequisites, and most important factors affecting the energy ecosystem has limited the opportunity to benefit from it for many managers, decision makers, and markets, and in practice, this efficient management tool is not used optimally in business. This research has attempted to present the framework of a platform-based ecosystem that has not been considered by researchers. This research is a qualitative, applied, and exploratory study. The research population consisted of market management experts and energy industry activists, and with a grounded theory approach, it has identified the categories that have an impact on the research topic. Data collection was carried out using purposive sampling and snowball method, and semi-structured interviews using a protocol prepared with the help of scientific and practical experts. Finally, the B2B platform ecosystem framework of the electricity energy market was identified and extracted.

Abstract Humans are inherently altruistic beings. This innate altruism leads them to forego self-interest for others and engage in charitable giving. Today, as charity and NGO,s are facing a shortages in government support and financial resources, they have been inteseted in using cost-effective marketing methods. This research investigates one of the most affordable charity marketing methods: Fundraising Letters and Campaigns. The study aims to help charities attract more donations by determining the framework of Fundraising texts and their effective elements.
The mixed-methods study conducted in qualitative and quantitative phases. Initially, 26 campaigns from 8 charity websites and 18 letters from 5 charity organizations were examined using Genre Analysis. In the quantitative phase, two charity texts were studied by subjects. Ultimately, 7 moves and 21 steps were identified in the letters, and 8 moves and 17 steps were identified in the charity campaigns.
Furthermore, eye-tracking results revealed that the "Soliciting help " move in charity letters and the "introducing charity" move in campaigns have been indentified as Pont of Gaze; thus they are the most important moves in each text. According to the results, the middle paragraph of charity fundraising texts receive more attention than other parts; therefore, it is recommended that important elements be placed in the middle paragraphs of fundraising texts.

Abstract Considering the many challenges that petrochemical industries are facing today, including new technologies, sanctions and production issues, strategic planning has become one of the key tools to strengthen these industries in the field of national, regional and international competition. The competence and ability of senior managers in designing and implementing strategic plans plays a vital role in the success of organizations. This research was conducted with the aim of identifying the strategic competencies of senior managers and employees of Nouri Petrochemical Company in order to achieve strategic goals in the petrochemical industry. By using the theme analysis method, the aforementioned competencies were identified in five dimensions, including knowledge, skills, experience, attitude and personality traits, and categorized into 10 main components and 53 sub-components. Then these components were evaluated using five-point Likert scale. The results of the research showed that it was ranked 5 in many of these components, which is a confirmation of the successes of Nouri Petrochemical Company and its capable strategic management. Hence, this company can serve as a model for other petrochemical complexes in Iran and even the world. Also, using the experience and knowledge of these capable managers in the form of training sessions can help increase productivity in other petrochemical complexes of the country

Abstract Recently, with the penetration of artificial intelligence, the marketing environment of small and medium enterprises has experienced significant developments. The aim of this research is to identify the most influential contributors, current trends, and future research directions in the field of artificial intelligence in digital marketing in small and medium enterprises. For this purpose, bibliometric data of 100 documents between 2000 and 2025 in the field of artificial intelligence in marketing research were extracted from the Scopus database. VOSviewer version 1.6.20.0 software was used for the analysis. The results and publication trends indicate the annual growth in artificial intelligence in marketing research. In addition, keyword co-occurrence analysis uncovered four main thematic clusters: Cluster 1 - Digitalization of SMEs, Cluster 2 - Marketing Opportunities of AI in Industry, Cluster 3 - Data Analytics and Advanced Decision Making, and Cluster 4 - Marketing Strategies and Social Media. By identifying current thematic clusters, this study identifies future research areas. It also has practical implications for marketers in SMEs and shows how AI can be used to improve business operations.

Abstract This research, with the aim of providing more accurate and effective solutions, has used the Delphi method based on artificial intelligence and expert opinions to identify and prioritize the needs and personal development skills of human resource managers. This research is applied in terms of its purpose, which seeks to combine the human-based Delphi method (traditional) and artificial intelligence (modern), to provide an innovative approach in the field of research methods and data analysis that can be classified as fundamental research. The statistical population of the research is 15 experts in the fields of human resources, coaching and personal development and three types of language models such as Microsoft Copilot, Chat GPT and Gemini. The data collection tool in this research was the Delphi method, and the angle method was also used to examine the validity of the data. The findings showed that the Delphi method based on artificial intelligence analyzes the components with high speed and accuracy and provides access to rotational data. This method consists of 5 stages that begin with precise prompt writing. This method is best used as a complementary method along with human methods.

Abstract This study examines the impact of the most prominent early warning signs and causes of out-of-sequence (OOS) work on the productivity of industrial construction projects. Relying on the opinions of 16 industrial construction professionals and using the fuzzy Delphi technique, the most relevant of these signs and causes were identified. Then, using Max-Max and Bayes rules, the impact of this signs and causes on the productivity of industrial construction projects was analyzed. The findings indicated a high level of agreement between the rankings of causes of OOS work and a moderate level of agreement between the rankings of early warning signs, as assessed using both the Bayes and Max-Max approaches. Combining the findings of the two approaches revealed that if any of the following six early warning signs are observed—regardless of which sign precedes the occurrence of any cause of OOS work—it can be expected to lead to substantial decreases in project productivity: increase in drawing revisions, Inexperience in key roles, trending away from baseline progress curve, inadequate transition planning from construction to commissioning, high percentage of rework, and float usage early in schedule. Additionally, among the most obvious causes of OOS work, lack of consideration of stakeholder requirements in project planning, change in design, poor communication between different project parties throughout the project, late delivery from vendors, unrealistic activities duration, and lack of access to full project, respectively, can cause the greatest damage to the productivity of construction projects.

Abstract Two primary approaches exist for empirical tests assessing the efficiency of options contract markets: the model-based approach and the arbitrage-based approach. Numerous empirical studies have examined model-based efficiency (comparing model-derived option prices with market prices). Still, they have yielded conflicting results regarding the efficiency of the options market, with some studies supporting market efficiency and others rejecting it. This study conducts a meta-analysis of options market efficiency under the model-based approach to reconcile these contradictions and identify their underlying causes. We selected 30 studies published between 2003 and 2022 in SCOPUS-indexed journals, extracting 6,409 test samples for hypothesis testing. The sample includes all reported tests in prior empirical studies (published in SCOPUS-indexed journals) on model-based options market efficiency. Our findings reject market efficiency, indicating a significant divergence between option contract prices and their intrinsic values. Robustness tests—including efficiency metrics, option pricing models, journal H index, analysis date, and moneyness depth—consistently confirm this conclusion.

Abstract Digital transformation, as one of the most important drivers of change in contemporary banking, has had profound impacts on banking structures, processes, and services. This paper aims to identify research areas and trends in digital transformation in banking, and conducts a comprehensive bibliometric analysis based on bibliographic data available in prominent academic databases. Using the VOSviewer tool, scientific mapping and visualization of relationships between keywords, authors, and publications are performed, and major clusters in the literature in this field are identified. The findings show that digital transformation research in banking is focused on areas such as artificial intelligence, cybersecurity, fintech, open banking, and customer experience. Emerging trends in digital banking, including the use of new technologies such as blockchain and cloud computing, are also examined. By analyzing patterns and research gaps, this paper suggests future directions for academic studies in this area and emphasizes the need to develop innovative strategies for banks to adapt to the challenges and opportunities of digital transformation. The results can help researchers, policymakers, and bank managers to better understand key trends and design data-driven solutions for the future of banking.

Abstract The developments of the last few decades in the economy, even capitalism and the crisis of 2007, show that it is impossible to talk about the withdrawal of the government in the development process. The level of government involvement in the development process is one of the important issues of the economy. The main goal of this research is to describe the way and scope of government intervention. The research method of this research is descriptive-analytical. Government production of goods and services, transfer payments, taxes and regulations are the four main channels of the government to influence economic activities. And the regulation of the government's optimal intervention based on investment, commercial and industrial policy has been investigated. Based on the results of the research, contrary to liberal beliefs that government intervention hinders development in East Asian countries, the conscious intervention of government agents is the main factor in the development of these countries, and the main focus in these countries is on the manner and scope of government intervention instead of interference or non-interference. In our country, the presence of the government should be comprehensive and focused on development. With the intervention of the government in the processes of development, regulation and guidance of the market mechanism, inadequacies can be eliminated and the economic system can be driven to a better situation in terms of resource allocation and economic capacity creation.

Abstract Adopting a scientific approach to management and human resource management in Iran is less than a century old. This study has studied the evolution of "human resource management knowledge" in Iran using the qualitative research strategy of the Grounded Theory. The research data were obtained from interviews with a group of veteran professors of Iranian management knowledge, supplemented with data collected from written sources. The oral and written data of the research were then analyzed using open coding, central coding, and selective coding. The final theory based on the systematic model of the Strauss and Corbinchr('39')s Grounded theory categorizes the evolution of human resource management knowledge in Iran into four historical periods: "period of formation", "period of growth", "period of separation" and "period of re-creation" of human resources.

Abstract The global banking industry, driven by new technologies and changing customer behavior, has undergone major changes unprecedentedly all over its history. As banks contend with innovation challenges in their processes, fintech companies benefiting from digital capabilities, deliver innovative and customer-centric services. In the business world, the collaboration between these two institutions has taken many forms. This has also attracted the attention of the academic community, and several papers have been written in this field. The purpose of this article is to review these articles, and its main question is: What has the scientific literature contribute toward bank-fintech collaboration? To answer this question, a systematic literature review, based on PRISMA Checklist, has been utilized and various specific areas have been examined to understand the necessity, evolution, challenges, drivers, benefits, barriers, and types of bank-fintech collaboration in the scientific articles. The most significant achievements of the articles are discussed in the paper; furthermore, different types of bank-fintech collaboration in the scientific literature are listed, and a bank-fintech collaboration algorithm is presented. Ultimately, the gaps in the literature and suggestions for future research are expressed.

Abstract Customer relationship management provides the basis for customer optimal communication, customer loyalty and customer retention. This requires the design of customer-based strategies, the proper implementation and applying of technology, employee empowerment and increasing the level of customers knowledge. Given the advances in e-banking and the reduction of face-to-face contact points, the use of business intelligence tools to effectively use large volumes of customer information also seems necessary. The purpose of present study is to provide a conceptual framework for customer relationship management in electronic banking using business intelligence tools in Sepah Bank and merged banks. For this purpose, a qualitative research has been conducted and first, by reviewing the studies, the initial framework has been identified and then, Theme Analysis has been used for its development in electronic banking. The research population is 7 experts of case study. Semi-structured interviews were used to collect data and credibility and confirmability were used to assess the validity of the results. After analyzing the data, the customer relationship management framework in e-banking is classified into 6 dimensions, 16 components and 35 indicators. The main dimensions of which are Customer reach and acquisition, Customer identification, Customer attraction, Customer relationship development, Customer retention and customer relationship review.

Abstract Industrial groups have interactions within and outside groups. In this paper, twelve industrial groups of companies listed in Tehran Stock Exchange are reviewed in order to evaluate linear information dynamics. Conservatism measures of “ratio of sum of price to sum of book value” and “mean of price-to-book ratio” are considered. In sample periods, in order to remedy the effects of special factors in sample industries, later ratio is de-trended. For controlling effects of each industry, inflation, and some other factors on the various industry indices, two measures of “average annual difference between price and book value” and “each industry index” are considered. Industry analysis shows that "sum of price to sum of book value" criterion has a significant correlation with the average of market value to book value and the correlation would be stronger if using the de-trended criteriun. Finally, comparing scaled variables on the average annual difference between price and book value, it concluded that scaled variables based on the index of each industry led to a much stronger coefficient of valuation models. Therefore, for assessment and analysis of linear information dynamics in industrial groups (including environmental factors such as conservatism in accounting policies, industry, stock market indices, cost of capital rate, inflation, the policy of dividend distribution, past and present of book value and securities) can be used for developing residual income valuation models.

Abstract One of the main challenges constantly facing the majority of the organizations is planning to develop and improve processes and operations based on the adoption of new technologies, especially digital technologies, to react to the requirements of markets and competitive environments. Therefore, by using hybrid research approach (qualitative and quantitative), the present study explores the applications of digital technologies in terms of technical needs and business performances in the supply chain network of the bedding industry. The method includes developing an efficient measurement tool to evaluate the digitalization and automation specifications for integrated management of the supply chain operations and flows in manufacturing industries and validating it using the multi-criteria decision-making approach DANP (DEMATEL-based ANP), which is considered the study’s contribution to knowledge and the literature. Therefore, in the first step, the list of influential factors was determined as 6 process areas and a total of 22 related attributes using the desk-based research and Delphi method. Then, the weights and relationships among factors were evaluated using the DANP technique. According to the obtained results, the process area of inventory and warehouse management is considered the most critical factor with the highest weight. However, the process areas of sourcing and buy and business management were identified as the most effective factors in improving critical areas.