Management Research in Iran

Abstract The appointment of managers to new positions in Iranian public organizations is invariably accompanied by multiple challenges due to complex bureaucracy, frequent political changes, and diverse stakeholder expectations. This qualitative study, employing an interpretive phenomenological approach, aimed to explore the lived experiences of newly appointed senior managers and to identify their proactive strategies for effective adaptation to new job positions. The participants were 19 senior managers from public headquarters in Mashhad, selected through purposive sampling until theoretical saturation was achieved. Data were collected via in‑depth semi‑structured interviews conducted between August and October 2023 and were coded and analyzed using MAXQDA software. The findings revealed that successful adaptation of newly appointed managers is a self‑initiated and proactive process. Data analysis led to the extraction of seven main themes: (1) organizational environment assessment and analysis, (2) organizational communication and interactions, (3) strategy planning and implementation, (4) personal and organizational development, (5) challenge and risk management, (6) performance and productivity improvement, and (7) external and inter‑organizational networking, along with 21 sub‑themes. Since the proactive strategies of newly appointed managers serve as the key to successful organizational adaptation in the public sector context, they enable managers to reduce role ambiguity, gain social legitimacy, manage internal resistances, and implement constructive changes within bureaucratic government structures. The findings of this study extend organizational socialization from a passive framework toward proactive agency, offering an indigenous model for designing managerial training programs, role transition policies, and leadership empowerment initiatives in the public sector.

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 The aim of this study was to identify the dimensions and assessment models of professional qualifications in digital marketing jobs. This research employed a systematic review method, focusing on studies published in international databases between 2016 and 2025. Ultimately, eight selected articles were approved, analyzed, and synthesized. findings revealed that assessing soft skills—such as analytical thinking and problem-solving, communication skills, teamwork, management skills, personal attributes, and interpersonal abilities—plays a significant role in evaluating the professional qualifications of individuals in digital marketing roles. another key finding was that integrated models like DigComp are recognized as some of the most comprehensive frameworks for assessment in this field. In addition to general qualifications, DigComp covers five core areas: information and data literacy, communication, content creation, safety, and problem-solving. Furthermore, the 21st Century Skills Model, which includes learning skills, digital literacies, and life and career skills, along with performance-based situational questionnaires and assessments, can serve as effective, multidimensional tools for evaluating individuals’ qualifications in these occupations.

Abstract Development of key personnel, as one of the basic components of human resource management, plays a pivotal role in improving the efficiency, effectiveness, and learning of organizations. The aim of the present study is to design a talent development model in the Court of Accounts of the country. This study was conducted with an interpretive paradigm, a qualitative approach, a case study strategy, and a content analysis method. The research population included organizational experts in key positions who were identified and clustered based on the experts' opinions. To collect data, semi-structured interviews were conducted with 19 experts selected through purposive sampling, and the data were analyzed until theoretical saturation was reached. The findings showed that the talent development model in the Court of Accounts consists of four main parts: (1) goals and strategies, (2) what and areas of development, (3) how and mechanisms of development, and (4) individual and organizational results. The studies showed that key forces have been developed in some areas, such as personal and technical competencies, but for the future they also need to pay attention to other areas. Also, the experts emphasized the difference in mechanisms, level and implementation between key forces and other employees. The identified talent development mechanisms fall into four main categories: job-based, relationship-based, formal program-based and informal/informal mechanisms. This model can be used as a practical basis for designing and improving talent management programs in the Court of Accounts and similar organizations.

Abstract Product design in complex and dynamic environments requires an understanding of the simultaneous interactions among the problem, solution, knowledge, and stakeholders, while linear design models lack the capacity to explain such dynamics. Despite the development of the co-evolutionary design literature, there remains a gap in terms of an integrated framework for identifying and analyzing the relationships among the drivers affecting this process. Therefore, the present study was conducted with the aim of identifying, classifying, and modeling the key drivers of co-evolutionary product design. The research adopted a qualitative-developmental approach and was carried out in two stages. In the first stage, the key drivers were extracted and organized from the relevant literature using systematic meta-synthesis; in the second stage, the causal relationships and dynamics among them were modeled and analyzed using fuzzy cognitive mapping. The findings showed that co-evolutionary product design is grounded in the networked interaction of cognitive, adaptive, technological, and social drivers. Among these, the co-evolutionary process, adaptive mechanisms, and learning play the most significant role in the dynamics and performance of the system. Scenario analysis further demonstrated that the proposed model possesses an appropriate level of stability and resilience under different environmental conditions. By providing an integrated framework and dynamic modeling of the relationships among the drivers of co-evolutionary design, this study contributes to the advancement of the product design literature in complex and uncertain conditions and can serve as an analytical tool to support decision-making and innovation management in the design process.

Abstract This study explores the place of ideology in management and organization studies by examining its conceptual, geographical, and temporal evolution from 1961 to 2024. Employing a scoping review methodology based on the PRISMA-ScR guidelines, the study systematically analyzes 111 scholarly sources, including journal articles, books, and theses, through qualitative content analysis. The findings identify nine dominant approaches to the study of ideology in management scholarship and demonstrate that ideology has evolved from a concept viewed primarily through a political lens in the first half of the twentieth century into a multidimensional construct within management research. These approaches encompass domination, legitimacy, interpretation, critique, social integration, normative logic, fantasy, grand strategy formulation, and social competitive advantage. Contrary to linear interpretations, the findings reveal that these perspectives have developed concurrently and exhibit substantial geographical diversity across different research contexts. A distinctive contribution of this study lies in highlighting the role of ideology in creating social competitive advantage and informing national grand strategies, thereby extending the boundaries of existing management scholarship. Adopting an interdisciplinary and critical perspective, the study further underscores the importance of advancing theory development in management and organization studies through greater attention to indigenous ideological foundations within diverse cultural and political contexts.

Abstract This article elucidates effective academia-industry linkage for developing technology-driven services. It proposes a comprehensive framework to enhance this interaction, positioning Business Intelligence (BI) as the core decision-making factor. In terms of classification, this study is applied and descriptive-survey, adopting a mixed-methods approach integrating qualitative and quantitative paradigms. During the qualitative phase, thematic analysis was employed, commencing with literature review and semi-structured interviews with subject-matter experts. Extracted data were categorized through open and selective coding. For the quantitative phase, a researcher-developed questionnaire was designed based on the identified components and distributed among 152 managers, specialists, and seasoned experts within the technology-focused industrial landscape. Instrument reliability was confirmed via Cronbach's alpha (0.93) and composite reliability, while convergent validity was demonstrated using Average Variance Extracted (AVE > 0.50). Quantitative data analysis was performed using Structural Equation Modeling with the Partial Least Squares approach (PLS-SEM) via Smart PLS 3.0. The empirical findings robustly indicate that six major determinants, at a significance level of 0.05 and with t-statistics exceeding 1.96, exert a very substantial influence on university-industry collaborations. These critical factors encompass Business Intelligence capabilities, Management Strategy, Structural elements, Cultural norms, Educational competencies, and Managerial-Financial resources. Collectively, they play an indispensable role in facilitating synergistic cooperation and accelerating the deployment of innovative technological services. The distinct innovation of this research resides in proposing a multidimensional model that places Business Intelligence at its conceptual core, while holistically encompassing six internal and external variables through an analytical-managerial lens to ultimately optimize strategic decision-making within the university-industry ecosystem.

Abstract This study aims to identify the factors influencing the implementation of sustainable development policies based on the Small Wins approach in Iran. In terms of purpose, the research is applied, while methodologically it adopts a descriptive qualitative design. The study was conducted using a qualitative approach based on Glaser's emergent grounded theory methodology. Data were collected through semi-structured interviews, the protocol for which was developed following a comprehensive review of the relevant literature. The interview data were subsequently analyzed through the coding procedures of Glaser's emergent grounded theory approach. The participants consisted of experts and practitioners with extensive experience in sustainable development policy implementation. Participants were selected using purposive and theoretical sampling, and data collection continued until theoretical saturation was achieved.The findings revealed that a wide range of factors influence the implementation of sustainable development policies. Drawing upon the concepts of Small Wins and sustainable development, 36 factors were identified through the coding process. These were subsequently classified into two overarching categories: driving factors and barrier factors. The results further indicated that each of these overarching factors comprises six dimensions, namely economic, social, cultural, strategic, environmental, and organizational, encompassing a total of 18 sub-factors. The analysis demonstrates that these factors constitute the key determinants of sustainable development and, within the proposed framework, represent the principal dimensions for the formulation and implementation of sustainable development policies. Furthermore, findings suggest that these factors provide a valuable analytical framework for designing and implementing sustainable development policies, particularly in developing countries such as Iran.

Abstract This study aimed to identify and analyze the key drivers influencing the adoption of gamification in the human resource management of Tejarat Bank in Birjand County. Employing a qualitative approach and thematic analysis based on Braun and Clarke’s (2006) framework, data were collected during the first half of 2025 through semi-structured interviews with 18 managers, experts, and employees until thematic saturation was achieved. Participants were selected purposefully and complementarily using the snowball sampling technique, and data analysis was carried out in MAXQDA 2020. To ensure validity and reliability, member checking, source triangulation, and Cohen’s Kappa coefficient (0.79) were utilized. The analysis revealed eight main themes and fifty six subthemes, including: organizational motivation and commitment toward gamification; fairness and transparency in gamification processes; alignment of the gamified environment with organizational structures; training, empowerment, and cultural development; organizational participation and interaction; support mechanisms and resource management; enhancement of employee experience and job satisfaction; and sustainability and coherence of gamification processes. Overall, the results indicate that a well designed multidimensional motivational system characterized by transparency, interactive organizational dynamics, and structural support plays a significant role in strengthening employees’ job satisfaction and productivity, thereby improving the effectiveness of gamification initiatives within human resource management.

Abstract Objective: In a complex, ambiguous and highly uncertain environment, technology megaprojects require new and combined tools, methods and approaches for optimal and efficient management. Roadmaping as a strategic, efficient and forward-looking tool, along with lean thinking, are the latest management versions that are growing rapidly in the world; their increasing applications are supplementing the knowledge of these two fields. The aim of this thesis is to design an integrated lean roadmapping conceptual framework that can be used in technology megaprojects.
Method: The method of this research is a combination of descriptive research methods, content analysis, and meta-analysis.
Findings: The conceptual framework combining the principles of lean thinking and roadmapping provides the opportunity to improve productivity and reduce risks in projects. This framework allows managers to optimally allocate resources and achieve strategic goals by reducing waste and continuous improvement. The key components of the framework include Preparation, Integrated roadmapping development, roadmapping validation, Integrated roadmapping implementation, Pilot project, Stakeholder engagement, Value/end-user focus, Value stream mapping, Continuous flow, Pull system/demand pull, Waste elimination, Continuous improvement (Kaizen)/evolution.
Conclusion: The results of the research show that using this framework can lead to improved performance of technology megaprojects, better alignment with organizational goals, and effective resource management. It is suggested that in future research this framework be examined and analyzed in different industries to make further improvements.

Abstract Deprivation, defined as the lack of access to resources to meet basic needs, is one of the persistent challenges of contemporary societies, intertwined with economic, social, and cultural dimensions, and structural and environmental factors contribute to its perpetuation. In Iran, despite extensive efforts in deprivation reduction, evidence indicates that policies in this area have not enjoyed adequate efficiency and effectiveness. This study aims to analyze the coherence of deprivation reduction policies in Iran and propose solutions for its improvement within the framework of public policymaking. The research employs a qualitative approach, combining two strategies: content analysis and thematic analysis. In the content analysis phase, relevant legal and policy documents from 1948 to 2024 were examined using Behardaj's model and four key indicators (institutional multiplicity, coverage of deprivation dimensions, legal contradictions, and alignment with higher-level documents). In the thematic analysis phase, data from semi-structured interviews with 15 experts in policymaking and deprivation reduction were analyzed based on Braun and Clarke's (2006) model. Findings reveal that deprivation reduction policies in Iran lack sufficient structural and functional coherence, with this incoherence identifiable at three levels: horizontal, vertical, and internal. Based on the results, policy solutions such as designating a single responsible institution, establishing a comprehensive database, redesigning the resource allocation system, and revising laws have been proposed. By emphasizing the necessity of enhancing coherence in deprivation reduction policies, this study provides an operational framework for improving the quality of policymaking and increasing the effectiveness of government interventions in this area.

Abstract The aim of this research is to develop a model of the consequences of digital tourism memorable experience in selected Iranian tourism destinations through destination appeal. The present study is applied in terms of purpose and mixed in terms of method. In the qualitative part, semi-structured interviews were used to collect data. The statistical population of this part consists of university professors, experts, and managers in the tourism industry. Judgmental and accessible sampling was used to identify experts, and the sample size was determined through theoretical saturation of 18 people. The results obtained from theme analysis and Max Quda software led to the identification of 135 codes that were classified into 18 categories. Also, in the quantitative part, 420 questionnaires were distributed among tourists who experienced the tourism destination through the digital platform, and the data were analyzed using SmartPLS and SPSS software. The results of the research led to the creation of a framework for the consequences of digital tourism memorable experience. Destination appeal is one of the most important antecedents of a memorable digital tourism experience, which can help tourism planning and tourism policy development, and has consequences for the tourist and the destination.

Abstract The main objective of this research is to "improve production performance" in the spinning and single-ply yarn production section in the textile industry by leveraging artificial intelligence (AI) and appropriate machine learning algorithms, while identifying an optimal algorithm for advancing intelligent manufacturing in textile production. Production data were analyzed using regression-based machine learning models to enhance yarn production performance in the worsted spinning system, minimize machine downtime and material waste, and ultimately improve overall production efficiency. The results demonstrate that machine learning models can effectively predict key production performance indicators in the textile industry, enabling reductions in material waste and unplanned downtime and thereby enhancing production efficiency during the single-ply yarn manufacturing stage on ring spinning machines at Guilan Spinning Company. Among the evaluated models, the Gradient Boosting Regressor achieved the highest predictive accuracy and overall performance, with an R² score of 0.938 and an RMSE of 22.182, making it the most effective model for data analysis and production performance prediction. Compared with the other models, the Gradient Boosting Regressor offers several advantages, including a lower risk of overfitting, the ability to efficiently process structured datasets with minimal preprocessing, high predictive accuracy, faster computational performance, and shorter training time. Furthermore, SHAP (SHapley Additive exPlanations) analysis revealed that the most influential factors affecting production performance, ranked by their contribution to the model's predictions, are yarn count, primary cause of machine stoppage, amount of material waste, downtime duration, and description of the primary cause of machine stoppage.

Abstract This study aimed to understand the lived meaning of managerial error from the perspective of managers in an Iranian public university. While existing literature has mostly treated error as a quantitative variable and examined it through typologies and individual, group, and organizational antecedents, less attention has been paid to how managers experience and make sense of error within specific historical–cultural contexts. Using a qualitative design and Gadamerian hermeneutic phenomenology, we conducted in-depth semi-structured interviews with managers of various units at Vali-Asr University and analyzed the data through the hermeneutic circle and interpretive thematic analysis. The findings showed that managerial error, in the participants’ horizon of understanding, is not an exception but a normal part of organizational life, emerging at the intersection of a patronage-based appointment structure, a culture of “Roodarbaisti” (face-saving), relational considerations, and weak evaluation and documentation systems. Managers simultaneously perceived error as a threat to reputation and trust, and as a potential opportunity for learning; however, in the absence of an error management culture, this positive potential largely remains at the level of individual experience and fails to translate into formal policies and procedures. This research demonstrates that the meaning of error in this context is the product of the interweaving of managers' interpretive horizons with the specific cultural and institutional contexts of the university under study. Accordingly, recommendations are offered for revising appointment procedures, establishing evidence-based evaluation systems, and creating institutional platforms for dialogue around error.

Abstract In recent years, alongside fundamental changes in the nature of the work environment at both international and domestic levels, as well as the rapid pace of change in employees' skills, the concept of "skill intelligence" has emerged as a data-driven and technology-oriented approach in scientific literature and organizational applications. However, existing studies have largely been conducted in a fragmented, siloed manner, focusing on specific aspects of skills, human resources, or technology, and this emerging topic still lacks a comprehensive, integrated, and organization-centered framework. This study aims to propose a comprehensive framework for skill intelligence systems in organizations by employing a systematic literature review method. To this end, scientific studies related to skill intelligence, skill management, skills analytics, and data-driven and AI-based systems in the field of talent management were systematically identified, screened, and analyzed. In the analysis phase, the extracted components were clustered using a structured approach, and the conceptual relationships among them were examined.

The findings led to the identification of key components of skill intelligence systems and their organization into a five-layer reference architecture. Furthermore, the proposed framework can serve as a theoretical and practical foundation for researchers and organizational managers in designing, evaluating, and developing skill intelligence systems.

Abstract This study aims to identify the barriers to implementing corporate governance in Iranian state-owned enterprises (SOEs) using the three-pronged model. Given the strategic role of SOEs in achieving national macroeconomic and social goals, and ongoing challenges in transparency, accountability, and managerial independence, a detailed analysis of these inhibiting factors is increasingly essential. The research employs a qualitative approach with thematic analysis as the main method. Fifteen academic experts and senior SOE executives were purposively selected and interviewed through semi-structured interviews. Data were systematically coded and classified into basic, organizing, and global themes.The findings reveal that barriers fall into three major categories: contextual factors (e.g., weaknesses in legal and regulatory frameworks, political interference, institutional misalignment, and political economy constraints); structural factors (including inefficiencies in governance bodies and committees, and deficiencies in risk management and financial reporting); and behavioral factors (such as conflicts of interest, resistance to change, non-professional managerial culture, and managerial instability). The interaction among these levels creates a cycle of inefficiency that reduces governance effectiveness in SOEs. Addressing these barriers requires an integrated, cross-sectoral approach. By offering a context-specific understanding of corporate governance barriers in Iran, this study provides a foundation for policymaking, regulatory design, and improving supervisory mechanisms in Iranian SOEs.

Abstract Purpose: This study develops and validates a strategic human resource development model tailored to the requirements of Iran’s aviation industries. Methodology: An applied-developmental, exploratory-validation mixed-method design was used. Initial strategies were derived from a targeted literature review and an analysis of human, technological, and safety challenges, and were refined with 60 managers, senior experts, and specialists. Fifteen experts then assessed model comprehensiveness, structural logic, and implementability using a nine-item questionnaire and open-ended responses. The formative model was tested using partial least squares structural equation modeling. Findings: Mean scores for comprehensiveness, structure and relationships, implementability, and overall evaluation were 4.65, 4.40, 4.20, and 4.42 out of 5, respectively. Convergent validity was 0.78, variance inflation factors ranged from 1.85 to 2.95, and all formative weights were significant at the 95% confidence level. R2 was 0.68 and SRMR was 0.072. Digital skill development and technology localization had the largest relative weights; however, approximate pairwise Wald tests did not confirm statistically distinct weights. Conclusion: The final model organizes ten strategies into foundational drivers, organizational enablers, and strategic outcomes. It offers an actionable framework for competency development, talent retention, burnout reduction, and technological capability building under the resource and safety constraints of specialized aviation organizations.

Abstract The study attempted to identify key factors affecting the operational resilience of Iran's banking ecosystem, analyze the interrelationships between these factors, and present a systematic model for improving the resilience of banks in the face of cyber risks. The study is applied and mixed (qualitative-quantitative). In the qualitative part, data from semi-structured interviews analyzed using content analysis and coded with the MAXQDA tool. In the quantitative part, causal relationships between the identified factors analyzed using the Fuzzy Cognitive Mapping approach and modeled with the Mental Modeler tool. The statistical population of the study included digital banking experts, and sampling was purposeful and judgmental, and 20 people were interviewed until theoretical saturation was reached. The results of the present study showed that the operational resilience of Iran's banking ecosystem is subject to the complex interaction of technological, managerial, human, institutional, and cyber factors. Among them, cyber resilience, IT infrastructure, crisis management and organizational agility play the most important role in maintaining the sustainability and continuity of banking operations. The research also showed that the digital circular economy can play an important role in improving operational resilience by increasing the sustainability of infrastructure, optimizing resource consumption and improving the flexibility of systems. On the other hand, the findings indicate that operational resilience is not simply a technological issue, but human, managerial and institutional dimensions also play a fundamental role in it. Therefore, single-dimensional approaches to cyber risk management and banking resilience cannot respond to the complexities of the digital banking ecosystem.

Abstract Recent changes in consumer behavior and advancements in communication technologies have given rise to the concept of consumer activism, which indicates that today’s consumers play an active role in the market, can influence purchasing decisions and brand policies, and act as effective players in the consumption environment. The present study is designed based on a mixed-method approach, utilizing both qualitative and quantitative methods. This study falls within the deductive-inductive paradigm and is applied in terms of purpose, while being classified as exploratory research. The statistical population of the study consists of Digikala consumers in the city of Khorramabad. Sampling was conducted randomly, and based on the principle of theoretical saturation, 20 individuals were selected as the sample members. For data analysis in the qualitative section, content analysis and coding methods were employed using Maxqda software.For data analysis in the qualitative section, content analysis and coding methods were employed using Maxqda software.

Abstract This study analyzes the heterogeneous impacts of the crisis induced by the military attack against Iran in February 2026 on the economic activities of firms. The objective of this research is to classify businesses based on two dimensions: “the criticality of the product/service from the consumer’s perspective during crises” and “operational risk and supply chain vulnerability,” thereby proposing tailored managerial and policy solutions for each scenario. Methodologically, this study is applied in terms of objective and employs a multi-stage design with a predominantly qualitative approach, supplemented by a descriptive survey stage. Data were gathered through structured questionnaires and semi-structured interviews with participants possessing relevant experience and expertise. The findings indicate that, from the participants’ perspective, firms supplying essential goods and services with lower dependency on complex supply chains are in a more favorable position to maintain business continuity. Conversely, firms facing declining demand, transportation disruptions, and infrastructural instability exhibit higher operational vulnerability. Based on this classification, managerial strategies were developed across four distinct quadrants within the framework of three interpretive logics: “dynamic adaptability,” “risk decentralization,” and “social capital.” Furthermore, policy recommendations aligned with operational continuity, market adaptation, and the prevention of business cessation are proposed. The proposed framework can assist policymakers in targeting support mechanisms more effectively and guide managers in selecting adaptation strategies to mitigate operational vulnerability.

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 Alliances can be a very effective way to achieve new strategic opportunities, but despite this, a high percentage of strategic alliances fail and end failure.. Therefore, the present study sought to identify the factors affecting the stability and stability of strategic alliances using a systematic review. The case of the study was all articles accepted from invalid databases after filtering in several stages, 44 articles were reviewed for final evaluation and analysis. In the coding process stage, the selected articles were performed and 30 sub-themes were divided into three main themes: Senior management team, structure, and business. In the individual section, the strategic ability of the leaders, the commitment of the senior management team, the coordination between the senior managers of the units, having interdisciplinary specializations, and having previous experience in the inter-company cooperation space were identified. In the structure section, module management process, continuous and short-term performance feedback, data output transparency, number of module partners, complementary resources, distinct goals, having an international perspective, intangible outputs, symmetric learning capabilities, clear division of labor, a form of governance, Type of contract, reward system, contract orientation and type of exchange were identified; For the business sector, cultural distance, market growth, partner reputation, partner size, partner experience, contract territory, type of partner activity, cash flow of each partner, a unique type of exchange, correct choice of key partner were selected. Finally, based on the five identified proportions (cultural, strategic, operational, organizational, and individual) at each level of sustainability, it can be significantly increased

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 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.

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 The automotive industry, as the forefront of the technological revolution, is undergoing a profound transformation with the integration of artificial intelligence (AI) technology. AI and its application in this industry have evolved into a complex technological ecosystem that encompasses numerous stakeholders. The objective of this research is to identify and analyze the position and role of stakeholders within the AI ecosystem in Iran's automotive industry. To this end, a list of stakeholders in the AI ecosystem was initially compiled. Subsequently, the position and role of these stakeholders were analyzed. Data regarding the stakeholders' positions were collected using an interest-power matrix, for which a questionnaire comprising 48 items was designed and completed by 36 experts and specialists. Based on the findings, the stakeholders in this ecosystem were categorized at both macro and micro levels and classified into four groups using the interest-power matrix: key stakeholders (with high interest and high power), contextual stakeholders (with high power and low interest), dependent stakeholders (with low power and high interest), and marginal stakeholders (with low power and low interest). The results indicate that governmental institutions, research centers, and automakers are among the key stakeholders, while financial institutions and some suppliers fall into the contextual stakeholder group. End-users, including consumers and drivers, are considered dependent stakeholders, whereas media and some regulatory organizations are categorized as marginal stakeholders. This classification can assist policymakers and industry players in optimizing interactions and fostering the sustainable development of the AI ecosystem in the automotive industry.

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.