Conceptualization
Bahar Ebrahimi; Hasan Danaeefard; Seyyed Hossein Kazemi; Seyyed Yagoub Hosseini
Abstract
IntroductionThe rapid development of information technology and digital transformation has transformed the role of human resource management (HRM) from a primarily administrative function into a more strategic component of organizational performance and value creation. In this context, data-driven human ...
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IntroductionThe rapid development of information technology and digital transformation has transformed the role of human resource management (HRM) from a primarily administrative function into a more strategic component of organizational performance and value creation. In this context, data-driven human resource management (DDHRM) has emerged as an approach that improves HR decision-making through the systematic collection, analysis, interpretation, and use of employee and organizational data. Unlike traditional approaches that rely heavily on managerial intuition and experience, DDHRM emphasizes evidence-based decision-making. The growing use of data in HR has also generated overlapping concepts, including HR analytics, people analytics, human capital analytics, workforce analytics, and data-driven HR decision-making. Although these concepts share common elements, their boundaries and relationships remain unclear. This conceptual ambiguity has limited theoretical development and created challenges for organizations seeking to implement data-driven HR practices. Therefore, this study aimed to clarify the concept of DDHRM by identifying its defining dimensions, antecedents, and consequences and by establishing a more coherent conceptual foundation for future research and organizational practice. MethodologyThis qualitative study employed Rodgers’ evolutionary concept analysis methodology, which is particularly appropriate for emerging concepts whose meanings evolve across time and contexts. The approach examines the defining characteristics of a concept, its antecedents and consequences, related concepts, and, where appropriate, empirical referents. The literature search was conducted in the Web of Science (WoS) and Scopus databases using a range of keywords associated with data-driven HRM and HR analytics. The search covered titles, abstracts, and keywords without imposing a publication-year restriction. The initial search yielded 480 publications, including 285 records from Scopus and 195 from Web of Science. After merging the databases, 95 duplicate records were removed. Screening of titles and abstracts resulted in the exclusion of 313 publications because of insufficient relevance. Consequently, 72 articles were selected for full-text analysis. The inclusion criteria consisted of English-language journal articles containing relevant keywords in the title, abstract, or keywords and providing access to the full text. Conference papers and books were excluded. The selected studies were systematically reviewed, and information concerning the characteristics, antecedents, and consequences of DDHRM was extracted and coded. Thematic analysis was conducted through iterative comparison and refinement of emerging themes, following the components of Rodgers’ evolutionary concept analysis. The resulting concepts, dimensions, and operational definitions were also reviewed by two experts involved in the analytical process to enhance the credibility of the findings. FindingsThe analysis identified five central dimensions of data-driven human resource management: data collection and analysis, data governance, data technology, data storytelling, and data-based decision-making.First, data collection and analysis constitutes the foundation of DDHRM. It involves systematically obtaining data from internal sources, such as HR management systems, employee surveys, and performance evaluations, as well as external labor-market and industry sources. Descriptive, predictive, and prescriptive analytics can then be applied to identify patterns and predict future developments.Second, data governance encompasses the policies, processes, responsibilities, standards, and structures required to ensure data quality, security, privacy, appropriate access, and regulatory compliance. Effective DDHRM therefore requires clear ownership and accountability for employee data and explicit rules governing its collection, storage, analysis, and use.Third, data technology refers to the technological infrastructure and analytical tools that enable organizations to store, integrate, process, visualize, and analyze HR data. Technology connects data resources with HR processes and provides the infrastructure necessary for transforming raw data into actionable information.Fourth, data storytelling represents the ability to translate analytical results into meaningful and understandable narratives for managers and organizational stakeholders. It serves as a bridge between technical analysis and managerial action, because analytical capabilities alone do not guarantee that insights will be incorporated into organizational decisions.Fifth, data-based decision-making represents the practical realization of DDHRM. It occurs when decisions concerning recruitment, performance management, employee development, and other HR functions are systematically informed by evidence and analytical results rather than relying solely on intuition, precedent, or personal experience. Together, these dimensions demonstrate that DDHRM is a socio-organizational process rather than an analytical activity.The study also identified several antecedents necessary for successful implementation, including information technology capability and infrastructure, skilled data analysts, data governance, a data-oriented organizational culture, organizational size and resources, managerial capabilities and support, and behavioral factors such as performance expectancy, social influence, and facilitating conditions. These findings indicate that successful adoption requires the simultaneous development of human, organizational, managerial, and behavioral capabilities.The identified consequences include improved HR decision-making, greater efficiency and effectiveness, stronger alignment between HR activities and organizational objectives, improved talent management, and enhanced organizational performance and competitiveness. Improved HR processes may also contribute to employee well-being. However, DDHRM can create challenges concerning employee privacy, data security, and the responsible use of personal information, which depend substantially on effective governance of employee data. Discussion and ConclusionThe findings provide a comprehensive conceptualization of DDHRM by integrating technological, analytical, organizational, and human dimensions. The five identified dimensions demonstrate that data-driven HRM extends beyond the technical application of HR analytics. In particular, data storytelling highlights the importance of transforming analytical outputs into managerial understanding and actionable knowledge. The findings further indicate that DDHRM should be understood as an integrated system in which technology, human expertise, organizational culture, governance, and managerial support interact. Consequently, investment in analytical technologies alone is unlikely to ensure successful adoption unless organizations simultaneously develop analytical capabilities, governance mechanisms, and an evidence-oriented culture. Conceptually, the study helps clarify the boundaries of DDHRM in relation to related constructs such as HR analytics, people analytics, and human capital analytics. Although these concepts overlap, DDHRM represents a broader process integrating data collection and analysis, governance, technology, interpretation, and evidence-based decision-making within HR practices. From a practical perspective, organizations should approach DDHRM as an organizational transformation rather than simply as the acquisition of analytical software. Developing technological infrastructure and storytelling competencies, data governance, a data-oriented culture, and managerial support are complementary requirements for effective implementation. At the same time, organizations must establish appropriate safeguards for data security and responsible data use. Overall, DDHRM is a multidimensional and evolving concept that can strengthen the strategic role of HRM when technological and analytical capabilities are combined with effective governance, human expertise, organizational readiness, and responsible decision-making.
Other
hamed dehghanan; Zahra Pouramini
Abstract
Introduction In the past decade, the expansion of artificial intelligence (AI) and large language ...
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Introduction In the past decade, the expansion of artificial intelligence (AI) and large language models (LLMs) has brought a fundamental transformation to qualitative research methods and expert-based decision-making processes. The Delphi method, traditionally grounded in the collective judgments of human experts, has entered a new phase of evolution with the advent of AI. The present study aimed to design and validate an AI-based Delphi method while leveraging the imitation game, or Turing test, as a tool to assess the credibility of its outputs. The central question guiding this research was:"How can the Turing test be utilized as a novel approach to evaluate the validity and similarity of AI-based Delphi results compared to traditional human-based Delphi?"This question is particularly significant because researchers engaging with modern language models face a fundamental challenge: whether AI-generated responses can be considered as reliable as human judgments in terms of logic, reasoning, and coherence. This study seeks to provide a well-grounded answer and establish a methodological framework for the combined use of Delphi and AI in applied research contexts. MothodologyThis research is of an applied-developmental nature and was conducted with the objective of validating the AI-based Delphi method through the Turing test. The study population consisted of 30 purposively selected participants, including human resources experts, AI specialists, and independent evaluators, ensuring the data could be examined from human, technical, and impartial judgment perspectives.In prior studies, the AI-based Delphi methodology was comprehensively designed and explained, and in a separate study, it was applied to prioritize the developmental needs of human resources managers in the context of coaching. In the current study, the method is only briefly introduced, and the data derived from previous research serve as input for the Turing test.In the AI-based Delphi process, large language models (ChatGPT, Copilot, and Gemini) acted as virtual experts, responding to research questions and presenting their reasoning explicitly through structured prompts. Subsequently, the outputs of these models were validated using the Turing test. Evaluators engaged in brief dialogues without knowing the source of the responses (human or AI) and were required to determine the nature of the respondent. Responses that could not be confidently distinguished were considered “successful” in the Turing test.Thus, this study represents a continuation of prior research, examining the similarity, coherence, and credibility of AI-based Delphi outputs in a real-world research setting using actual data and the Turing test. FindingsFindings indicated that 56% of participants were female and 44% male, with a mean age of 36 years (range: 27–52) and approximately 72% holding a master’s degree or higher. This diversity of expertise and experience provided a robust basis for analyzing AI model behavior in comparison with human responses. The data employed were secondary sources, comprising results from three rounds of traditional and AI-based Delphi in previous studies by the authors, focused on identifying developmental priorities for human resources managers. These datasets included competency ratings, comparisons between traditional and AI-based approaches, and reliability and validity matrices, with over 85% of the data confirmed as reliable and valid.During the study, key questions were collected from both human and AI sources at each Delphi stage, and evaluators were tasked with distinguishing between human and machine responses, in line with the Turing test framework. Qualitative analysis revealed that AI-generated responses were often so similar to human answers that evaluators struggled to distinguish them, with an overall Turing test success rate of only 23%, indicating that over two-thirds of responses could not be correctly classified. This finding highlights the strong ability of the models to simulate human behavior.Content analysis showed that evaluators primarily relied on cues such as grammatical and stylistic errors, vocabulary diversity, interactive responsiveness, display of emotion and empathy, variation in tone, and references to personal experience—features more prevalent in human responses. In contrast, AI responses were characterized by high linguistic precision, formal structure, uniform tone, accurate and error-free answers, consistent response speed, and absence of personal narratives or experiential examples. Behavioral and linguistic patterns further revealed that participants expected human responses to be more dynamic, personal, and occasionally non-linear, whereas machine responses were predominantly formal, precise, and structured. Discussion and ConclusionThese findings not only confirm the capability of large language models to emulate human-like behavior and response style but also underscore the significance of linguistic, behavioral, and emotional cues in distinguishing between humans and AI. Furthermore, integrating human and AI Delphi data and analyzing evaluator judgments demonstrated that AI models could produce highly coherent responses, logically consistent themes, and alignment with management literature, establishing their effectiveness as tools for analyzing developmental needs of human resources managers.Overall, the results indicate that the AI-based Delphi method, combined with the Turing test, can effectively evaluate the validity and similarity of machine-generated responses to human ones, enabling the production of reliable and credible data in real-world research settings.As the first study to employ the Turing test for evaluating a research methodology, this study demonstrates that AI-based Delphi can generate data that are reliable and highly similar to human responses. The findings show that large language models successfully emulate human behavior and response style, making it challenging for participants to distinguish human from machine responses. This evidence strengthens the credibility of the AI-based Delphi method, suggesting it can serve as an effective research tool without compromising the quality of human-like analysis.Based on the findings, practical recommendations include optimizing the design of Turing test scenarios and criteria to more accurately assess the capabilities of language models, integrating the Delphi method with the Turing test for practical validation of outputs, fully documenting the process and managing potential biases, attending to ethical considerations and data confidentiality, and developing and standardizing prompt-engineering skills for effective interaction with language models. Additionally, potential limitations—such as the influence of participants’ attitudes and experiences, ethical and confidentiality constraints, sensitivity of results to prompt design and model characteristics, limitations in sample diversity and size, and the inability to fully control the knowledge and biases embedded in language models—should be considered in the design and analysis of future studies.These findings provide practical guidance for researchers employing AI-based Delphi methods, enabling the combined use of human and AI collective intelligence with higher accuracy and reliability.
Modeling
Masoud Eslami; Nader Bohlooli; Abbasgholi Sangi Nour Pour; Hosein Emari
Abstract
Introduction Digital transformation has become a fundamental organizational imperative, reshaping ...
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Introduction Digital transformation has become a fundamental organizational imperative, reshaping value creation, human resource management, decision-making, and organizational responses to technological change. The rapid development of technologies such as artificial intelligence, big data, the Internet of Things, cloud computing, blockchain, and extended and virtual reality has increased the need for new forms of leadership. Accordingly, digital transformation leadership extends beyond technology adoption and requires the integration of technology, human resources, organizational culture, processes, and strategic objectives.Human resource management plays a central role in this process because employees are the primary organizational resource through which digital capabilities are developed and implemented. Therefore, human resource managers need to move beyond traditional administrative roles and develop digital competencies, foster innovation and organizational learning, manage resistance to change, and align human capital with digital strategies. Although previous studies have identified digital competencies, strategic vision, digital culture, organizational learning, technological intelligence, customer orientation, and adaptability as important elements of digital leadership, an integrated model specifically addressing digital transformation leadership in human resource management and its relationship with economic productivity in government organizations remains necessary. Accordingly, this study aimed to design a comprehensive model of digital transformation leadership for human resource managers in government organizations and identify its dimensions, components, and indicators.MethodologyThe study was applied in terms of purpose and qualitative in terms of data and employed the systematic/Paradigmatic grounded theory approach. The statistical population in the qualitative phase consisted of experts in management and planning, technology, strategic and economic management, and human resource management who possessed doctoral-level qualifications as well as academic, research, or practical expertise in the field. Using purposive theoretical sampling, 15 experts were selected and interviewed until theoretical saturation was achieved.Semi-structured interviews constituted the principal data-collection instrument. The research process was conducted through several interconnected stages. First, relevant national and international theoretical and empirical studies on digital transformation leadership were extensively reviewed. Subsequently, open coding was conducted to identify the initial concepts and indicators emerging from the literature and expert interviews. Axial coding was then employed to organize and categorize the identified indicators into broader dimensions and components. Selective coding was subsequently conducted to establish relationships among the emerging categories within the paradigmatic grounded theory framework. Additional expert consultation, including in-depth interviews, the Delphi technique, and brainstorming, was used to refine and prioritize the dimensions, components, and indicators until theoretical saturation was reached. The qualitative data were managed using MAXQDA 2020.The validity and credibility of the resulting model were strengthened through triangulation, member checking, prolonged engagement with the data, and conscious control of researcher assumptions and biases. The data were collected over a four-month period, from February to May 2024, and the final model was presented to experts for validation. The dimensions, components, and indicators were subsequently prioritized and revalidated by the experts to ensure the theoretical and practical credibility of the proposed framework. FindingsThe findings resulted in the identification of five major dimensions, 24 components, and 102 indicators constituting the digital transformation leadership model for human resource managers. The model was organized according to the paradigmatic grounded theory structure into causal conditions, contextual conditions, intervening conditions, strategies, and consequences.The causal dimension comprised human capital, digital value capital, digital economy, and digital transformation. Human capital emphasized employees’ skills and expertise, training and development, work experience, motivation and commitment, creativity and innovation, employee well-being, job satisfaction, and turnover. Digital value capital included digital assets, digital knowledge and skills, digital innovation culture, technological infrastructure, and the adoption and use of emerging technologies. The digital economy dimension incorporated e-commerce, digital financial services, sharing-economy platforms, and digital platforms. Digital transformation focused on digital change management, digital learning and development, and digital customer orientation.The contextual dimension consisted of digital culture, digital governance, change management, and leadership styles. These components emphasized the acceptance and adaptation of new technologies, knowledge sharing, transparency and open communication, customer experience, digital policies and regulations, data security and protection, digital risk management, technology governance structures, change-management strategies, employee participation, resistance management, and transformational, servant, participative, and transformational leadership approaches.The intervening dimension included digital communication, digital literacy, foresight, soft skills, and performance indicators. Digital communication incorporated digital communication tools, communication strategies, multichannel communication management, communication analysis, and digital communication culture. Digital literacy encompassed information, media, security and privacy, technological, and analytical literacy. Foresight involved forecasting technological trends, analyzing future scenarios, and strategic planning capabilities. Soft skills included effective communication, critical thinking and problem solving, time management, organization, collaboration, and teamwork. Performance indicators focused on process efficiency, customer satisfaction, product and service quality, and financial returns.The strategic dimension comprised digital roadmapping, talent management, knowledge orientation, meritocracy, organizational transparency, and systems thinking. These components emphasized strategic digital objectives, technology implementation plans, employee training and empowerment, digital talent attraction and development, performance management, knowledge management and sharing, innovation, fair and transparent promotion and decision-making processes, accountability, system integration, digital platform development, stakeholder integration, advanced data analytics, and responsiveness to market and technological changes.Finally, the consequences dimension consisted of organizational and workplace success, smart organization, organizational sustainability, stakeholder experience, and return on investment. These outcomes included employee satisfaction, workplace quality, organizational stability and growth, advanced data analytics, process automation, data-driven decision-making, predictive modeling, machine learning and artificial intelligence, sustainable resource management, social responsibility, financial and economic stability, sustainable innovation, human capital development, customer and employee experience, supplier interaction, direct financial returns, increased productivity, reduced operating costs, and customer value creation. Discussion and ConclusionThe findings demonstrate that digital transformation leadership in human resource management is a multidimensional phenomenon that cannot be reduced to technological competence alone. The proposed model establishes an integrated relationship between human capital, digital capabilities, organizational context, leadership practices, strategic mechanisms, and organizational outcomes. The identification of five dimensions, 24 components, and 102 indicators provides a comprehensive framework for understanding how human resource managers can contribute to digital transformation and, ultimately, organizational productivity.The findings highlight human capital, digital value capital, and the digital economy as fundamental causal conditions. This indicates that successful digital transformation begins with the development and effective utilization of human and digital resources. At the contextual level, digital culture, digital governance, and change management provide the organizational environment required for technological adoption and transformation. Digital communication, digital literacy, and foresight operate as important intervening mechanisms by enabling employees and managers to use digital technologies effectively, communicate across organizational boundaries, and anticipate emerging technological developments. The strategic dimension further demonstrates that digital transformation requires more than technology acquisition. Digital roadmaps, talent management, knowledge orientation, meritocracy, organizational transparency, and systems thinking provide mechanisms through which digital objectives can be translated into organizational practices. These findings are consistent with previous studies cited in the article, particularly regarding the importance of teamwork, technological and human-resource alignment, digital vision, change-management readiness, digital literacy, customer orientation, talent orientation, digital communication, digital strategy, digital infrastructure, digital culture, and organizational structure.The consequences identified in the model also demonstrate the potential contribution of digital transformation leadership to organizational and economic performance. Organizational and workplace success, smart organizational capabilities, sustainability, stakeholder experience, and return on investment represent the principal outcomes of the proposed framework. In particular, increased productivity, reduced operating costs, financial returns, improved employee satisfaction, enhanced workplace quality, sustainable innovation, and improved stakeholder experience indicate how digital transformation leadership can contribute to economic productivity in government organizations.The study therefore concludes that effective digital transformation in government organizations requires human resource managers to assume an integrated leadership role combining technological awareness, strategic thinking, change management, human capital development, digital communication, organizational learning, and foresight. The proposed model provides a structured framework through which government organizations can align human resource practices with digital transformation objectives and create conditions for improved organizational effectiveness and economic productivity. Its principal contribution lies in integrating human-resource leadership with digital transformation and economic productivity within a single grounded framework derived from expert knowledge and validated through an iterative qualitative process.
Other
Zeinab Bakhtiari; Abbas Nargesian; Aryan Gholipor; Alireza Fouladi
Abstract
IntroductionConflict is an inevitable interactive phenomenon in organizations, arising from differences in ideas, values, and emotions among individuals or groups. When unmanaged, conflict can lead to detrimental outcomes such as reduced morale, productivity, job satisfaction, organizational commitment, ...
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IntroductionConflict is an inevitable interactive phenomenon in organizations, arising from differences in ideas, values, and emotions among individuals or groups. When unmanaged, conflict can lead to detrimental outcomes such as reduced morale, productivity, job satisfaction, organizational commitment, and employee well-being. Therefore, conflict management is not merely about avoidance or termination, but rather about designing effective strategies to minimize destructive effects while enhancing the constructive functions of conflict for organizational learning and effectiveness. In this context, humor, as a key leadership characteristic and communication tool, plays a vital role in fostering a positive organizational culture, improving group cohesion, enhancing self-efficacy, and reducing stress, anxiety, and burnout. Given these multifaceted benefits, this study aims to systematically review the literature on the role of humor in managing and reducing organizational conflict. MethodologyThis study was conducted with the aim of systematically reviewing published literature on the application of humor in conflict management. To achieve this objective, a systematic review methodology was employed, and a comprehensive search was carried out in the reputable scientific databases Scopus and Web of Science. Ultimately, 40 articles that were fully aligned with the research objectives were selected and analyzed. The systematic review process followed standard stages, including: Step 1: Formulation of the Research ProblemResearch questions determine the overall direction of the review process and serve as a guide for subsequent stages. Like other types of research, review studies require clearly defined and well-formulated research questions. Step 2: Article Search ProtocolKeyword searching is the most common method for identifying relevant literature. Accordingly, keywords must be carefully examined to ensure the selection of terms that generate relevant data. To identify synonyms related to the research keywords, the Thesaurus website was used. In addition, the Connected Papers platform was employed to identify networks of articles relevant to the research topic. Final refinements to the search terms were made based on expert opinions and reviewers’ feedback. Step 3: Search for Scientific SourcesThe quality of a literature review is highly dependent on the quality of the sources collected—“garbage in, garbage out.” A systematic review therefore requires a structured and comprehensive literature search.In this study, the Web of Science and Scopus databases were used to collect relevant sources. The criteria for article selection included topical relevance, year of publication, and indexing in the aforementioned databases. The findings of this study were extracted exclusively from these sources. Step 4: Selection and Screening of SourcesIn this study, the search and selection process was conducted in several stages. Initially, 3,643 potentially relevant articles were retrieved from the databases. In the first screening stage, 97 records were identified as eligible based on title, abstract, and keywords. After full-text review, 51 articles were excluded due to lack of relevance to the topic of “the application of humor in conflict management,” and 6 articles were removed due to duplication. Ultimately, 40 articles that directly addressed the research questions and were closely aligned with the study’s focus were retained for final analysis. Step 5: Quality Assessment of Final Articles (Concise Version)To evaluate the quality of the selected studies, the standardized CASP checklist was used. This tool includes 10 key criteria, and each article was scored on a scale from 0 to 20. A score above 14 was considered the threshold for inclusion. The results indicated that all 40 final articles met the required quality standards and were deemed suitable for the study. Step 6: Data ExtractionThe information required to answer the research questions was collected during this stage. Data extraction was carried out using a structured data extraction form that included general characteristics of each article—such as title, objectives, methodology, and key findings. In addition, variables directly related to the research questions were carefully extracted from the selected studies. Step 7: Data AnalysisFollowing initial coding and data compilation, higher-level analysis was conducted. During this phase, codes were examined and integrated to identify overarching themes. Some codes were excluded if they did not fit into any theme. Through iterative review and refinement, themes were developed to be sufficiently precise, distinct, non-overlapping, and comprehensive, enabling them to capture a broad range of ideas across the data. This process resulted in the reduction of data into a manageable set of core themes that represent the essence of the original texts. Finally, themes were grouped based on data content and, where appropriate, theoretical foundations. Step 8: Reporting the FindingsIn this final stage, the findings derived from the systematic review of the selected articles are presented. First, descriptive results of the literature review are reported, followed by a coherent presentation of the findings obtained through thematic analysis. FindingsThe findings indicate that the application of humor in conflict management is influenced by a set of contextual factors, including individual characteristics of actors, organizational structure and culture, and the nature of the conflict situation. Moreover, different types of humor (constructive and destructive), speaker–listener positioning, and intervention mechanisms such as discursive and behavioral techniques as well as face management play a decisive role in shaping the organizational outcomes of this strategy, which are discussed below. Context and Background FactorsCharacteristics of the actors: Age, work experience, gender, and racial similarity or employees’ backgrounds influence the perception and effectiveness of humor. Individual differences can lead to divergent interpretations of humor in conflict management. Organizational structure and culture: Organizational climate, leadership style, culture, power distance, workplace norms, repetition of jokes in inappropriate situations, initiating humor with powerful individuals, power relations, social power dynamics, humor as a tool for challenging authority, Confucian values of harmony and hierarchy, and leader–member exchange quality all determine how humor is received, interpreted, and how it affects conflict management. Characteristics of the conflict situation: The intensity and seriousness of the conflict play a crucial role in determining the effectiveness of humor in conflict management. Anatomy of Humorous BehaviorConstructive forms of humor: These include affiliative, tension-relieving, self-enhancing, and self-deprecating humor. Such forms of humor can manage conflicts constructively by reducing tension, improving the quality of work relationships, increasing cooperation and team cohesion, creating a democratic communicative climate, strengthening positive interactions, and reducing employee silence. Destructive forms of humor: These include aggressive, controlling, and biased humor, which can escalate conflict and create feelings of superiority. Speaker–Listener Situational AwarenessThe speaker’s intention and the listener’s response determine how humor is perceived and interpreted. The speaker’s intent, the listener’s reaction and interpretation, attention to hierarchy, and sensitivity to face needs in interpersonal encounters can turn humor into a tool for reducing tension and fostering positive relationships. Mechanisms of Intervention and TransformationDiscursive techniques: The use and imitation of pre-scripted conversational patterns, as well as parody and inversion of dialogues, can contribute to conflict management. Behavioral techniques: The ambivalence–shift model and the interaction between body language and verbal language enhance humorous expression and coping laughter. Face management: Coping laughter reduces face threat, conceals face loss, renders serious situations less serious, facilitates topic shifts, and helps reduce conflict. Organizational OutcomesPositive functions: These include preventing and reducing conflict, improving interpersonal relationships, reducing tension, facilitating learning and interaction, increasing team cohesion, effectively managing stress and pressure, and improving job satisfaction and human communication. Humor can also enhance employees’ autonomy and spontaneous creativity, regulate emotions, and create a greater sense of calm and flexibility.Negative functions: These include silencing minority voices, failure to challenge gender norms, escalation of conflict, employee resistance to organizational tasks, suppressing discussions of exclusion and harassment, and the perpetuation of racial stereotypes. Discussion and ConclusionThe results indicate that humor, when applied consciously, ethically, and in alignment with the conflict context, can serve as an effective tool for managing interpersonal and organizational conflicts. The effectiveness of humor is significantly influenced by individual, cultural, and power-related differences, as well as by its content, context, and mode of delivery. Evidence suggests that constructive humor reduces face-threatening situations, regulates negative emotions, facilitates communication, strengthens double-loop learning, and creates shared meaning, thereby preventing conflict escalation and enhancing relationship quality, collaboration, and team cohesion. Conversely, inappropriate or destructive use of humor may lead to misinterpretation, weakened professional relationships, and intensified conflict. Overall, the findings emphasize the need for systematic attention by managers and human resource professionals to communication skills training and the purposeful use of humor as a complementary strategy in effective organizational conflict management.
Pathology
Ali Parvin; Behzad Souki; Tohfeh GHobadi Lamooki; Kambiz Hamidi
Abstract
IntroductionThe current research is based on the assumption that political appointments in the Iranian public sector are phenomena beyond a managerial challenge and result in the systematic erosion of human capital. The main problem of the research is the existence of an analytical gap in the existing ...
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IntroductionThe current research is based on the assumption that political appointments in the Iranian public sector are phenomena beyond a managerial challenge and result in the systematic erosion of human capital. The main problem of the research is the existence of an analytical gap in the existing literature; previous research has mainly described the correlation between variables, but it has remained silent in explaining “the underlying process” through which an organizational event (political appointment) turns into a multidimensional pathologic cascade at the personal level. Accordingly, the main aim of this research is to fill this gap by designing and validating a “human-centered process Pattern” for the pathology of this phenomenon. Theoretical Foundations Political AppointmentsPolitical appointments refer to the process by which the selection and appointment of individuals to public positions, especially in the middle and technical levels, takes precedence over technical competence and professional competence based on political criteria such as party loyalty, factional affiliation, or personal relationships (Peters & Pierre, 2020; Gallo & Lewis, 2022). Political control and agency theory introduces this action as a rational tool by politicians (the employer) to align the bureaucracy and manage the risks of information asymmetry and conflicts of interest with bureaucrats (agents) (Eisenhardt, 1989; Peters & Pierre, 2019). Network theories and social capital have revealed the practical mechanism of these choices and show how informal relationships and networks based on ethno-factional trust block the path to merit (Burt, 2005). Finally, institutional theory seeks the most fundamental cause in the conflict between “political logic” (based on power and loyalty) and “professional logic” (based on expertise) (North, 1990; Friedland & Alford, 1991). Transition from Organizational Analysis to Person-Centered PathologyPathology focuses on explaining the “causes and ways” of injury formation (Scott & Davis, 2016). Classical Patterns of organizational pathology (such as those of Nadler-Tashman, Weisbord, or Techie) are fundamentally “organization-centered” and are powerful at detecting macro disorders (such as lack of coherence of structure and strategy) (Rahimi,2020), but they are facing a serious analytical gap in explaining how a particular employee personally “experiences” these disorders and how this experience “is narrated” in the form of biopsychosocial suffering.Personal vulnerabilities can be classified into three main categories: (1) psychological vulnerability, (2) social vulnerability, and (3) physical (biological) vulnerability. Processing Pathology Narrative: From Perception to IncarnationBy combining the above theories, pathos can be narrated not as an event, but as a multi-stage process that transforms an organizational phenomenon into an individual debilitating experience:1) Perception and emotional response, 2) Resource erosion, and 3) manifestation of chronic pathos (Maslach et al., 2001). Empirical Background of the ResearchThe research literature shows that political appointments lead to negative behavioral reactions such as intensification of organizational silence by directly undermining the principle of meritocracy (Sarvari-Lak & Amirpour, 2024). This atmosphere is associated with a significant increase in psychological and professional stress among employees (Mohammad-Rezaei, Rezaei-Manesh, Vaezi, & Ghorbanzadeh, 2023). Bedi and Schat’s (2013) comprehensive meta-analysis showed that perception of organizational policy is associated with a sharp decline in positive variables such as trust, fairness, job satisfaction, and emotional commitment. Narrative Conceptual FrameworkInspired by Engel’s (1977) Biopsychosocial Pattern (BPS), this research challenges the reductionist and variable-oriented approach. Engel argued that human pathology cannot be reduced to physical disorders alone, but should be seen as the product of the dynamic and intertwined interaction of the three biological, psychological, and social dimensions. This call for a paradigm shift from “harm-centered” to “human-centered” forms the conceptual basis of this research in order to explain the pathological narrative of an organizational phenomenon in the lived experience of employees. Accordingly, the present conceptual framework considers political appointment as a “triggering event” that activates three parallel and intertwined paths of harm: Psychological path: This path begins with a cognitive rupture in the form of a perception of injustice and violation of the psychological contract (Bedi & Shat, 2013), and leads to negative reactions such as stress, anxiety, and erosion of motivation (Mohammad-Rezaei, Rezaei-Manesh, Vaezi & Ghorbanzadeh, 2023). Social path: Political appointment leads to the polarization of the workplace (“insider” and “outsider”) by creating a crisis of legitimacy, erodes social capital, and leads to the formation of destructive norms such as organizational silence (Danaeifard, Sadeghi, & Mostafazadeh, 2015). Biological path: This path, which is the main innovation of the framework, explains the “embodiment” process of stress. Continuous perception of threat leads to the exhaustion of the body’s physiological systems and eventually manifests itself in the form of physical exhaustion, chronic fatigue, and psychosomatic symptoms. Conceptual Framework Synthesis: Narrative Plot of PathologyTo integrate these paths, a “narrative plot” structure is used, which depicts the pathos as a “trajectory map” in three-stage time. This plot, which forms the conceptual skeleton of the research and will be used as the main analytical tool in the data analysis, can be described as follows:Input pathos (beginning of the narrative): This stage includes the triggering event (political appointment) and the initial cognitive-emotional processes.Mediating pathos (Development of narrative): In this stage, the pathos is processed and deepened. Chronic mistrust and hopelessness arise.Output pathos (Temporary end of the narrative): Pessimism, apathy, and destructive work behaviors, breakdown of the relationship network, and physical exhaustion. Methodology This research uses a two-stage exploratory-interpretive qualitative design developed to answer the research questions systematically. In the first stage (Patterning), the narrative data obtained from 13 in-depth interviews with government employees were analyzed using Reflexive Thematic Analysis (RTA). The purpose of this stage was to develop a conceptual Pattern based on the lived experiences and meaning-making of the participants. In the second stage i.e., validation and refining, the Pattern extracted by the researcher was subjected to the judgment and consensus of 10 executive experts through the “Delphi Technique” to be refined and finalized with a pragmatic goal to ensure its content validity and practicality. Content validity using Content Validity Index (CVI), Construct Validity using Lauchet’s Content Validity Ratio (CVR), and Inter-Coder Reliability using Cronbach’s alpha were measured after conducting interviews, which were (S-CVI/Ave=0.93), (CVR=0.85), and (α = 0.87), respectively.The data were analyzed using the reflective thematic analysis method based on the six-step approach of Brown and Clark (2021) and with the help of Atlas.ti software, the output of which was the initial conceptual Pattern of PSB. Quantitative data analysis of Delphi was performed using SPSS 27 software. FindingsThe data analysis and validation process led to a final 12-component Pattern that explains pathology as a three-dimensional, process narrative. This Pattern demonstrates that the pathos begins with a psychological dimension, which includes the “perception of injustice” the subsequent emotional, attitudinal, and motivational reactions. Then, this pathos spreads to the social dimension and manifests itself in the form of “undermining shared trust, norms and values” and the destruction of the organization’s social network. Ultimately, this process leads to the biological dimension, where chronic stress and exhaustion “materialize” in the individual and manifest themselves in the form of psychosomatic and physical consequences. Discussion and ConclusionThe main purpose of this study was to validate and refine the conceptual Pattern of “psychosocial-biological pathology” (PSB). The empirical findings confirmed the core of this Pattern and turned it into a 12-component operational and validated Pattern that depicts the dynamic and cascading pathos from initial perception to its multidimensional consequences.The pathos begins with a “initial psychological trigger” i.e., the perception of injustice (T1), quickly leads to emotional (T2), attitudinal (T3), and behavioral (T4) reactions, and serves as a bridge to the transfer of pathos from the individual to the social level. Next, “social contagion” occurs. The dominance of political logic (T5) leads to mistrust and polarization of the space between “insider” and “outsider” groups (T6), which destroys organizational cohesion and leads to the destruction of social capital and the emergence of group conflicts (T9) by promoting negative norms (T7) and erosion of morality (T8). The main innovation of the Pattern is in validating the third dimension, i.e., “bioembodiment”. Chronic psychosocial stress “materializes” in the employees in the form of physical symptoms (T10) and physical burnout (T11). The findings confirmed the moderating role of “contextual factors” (T12) such as individual resilience and organizational support in intensifying or weakening this process.Research innovation includes the presentation and empirical validation of the “Psychological-Social-Biological Pathology” Pattern of Employees of Political Appointments (PSB) that covers several key gaps in the literature such as addressing the gap of an integrated and process approach, eliminating the gap of person-centered Patterns, and presenting a native and testable Pattern.The limitations of this research include dependence on the cultural context of Iran, the qualitative nature of the data, and the cross-sectional nature of the data.
Conceptualization
Mohammad Reza Mohajernia; Gholam Ali Tabarsa; Maryam Akhavan Kharazian
Abstract
IntroductionIn the contemporary competitive business landscape, organizational success is increasingly dependent on employee performance and ethical conduct. However, a paradoxical phenomenon known as "Unethical Pro-Organizational Behavior" (UPB) has emerged as a critical area of concern in organizational ...
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IntroductionIn the contemporary competitive business landscape, organizational success is increasingly dependent on employee performance and ethical conduct. However, a paradoxical phenomenon known as "Unethical Pro-Organizational Behavior" (UPB) has emerged as a critical area of concern in organizational behavior and business ethics literature. Defined as acts intended to benefit the organization or its members but which violate core societal values, laws, or ethical standards(Umphress et al, 2010), UPB presents a unique challenge. Unlike traditional deviant workplace behaviors aimed at harming the organization, UPB is driven by a motivation to help the organization, creating a cognitive dissonance between altruistic intent and unethical means. High-profile scandals, such as the Volkswagen emissions scandal and Toshiba’s accounting fraud, illustrate how employees may engage in unethical acts under the belief that they are serving the organization’s best interests. Despite its prevalence, UPB remains less studied compared to other organizational citizenship behaviors or counterproductive work behaviors. The dual nature of UPB—simultaneously supportive of organizational goals yet destructive to ethical norms—requires a comprehensive synthesis of existing research to understand its antecedents, mechanisms, and consequences. This study aims to provide a bibliometric analysis of the UPB domain, mapping its intellectual structure, identifying key influential scholars and journals, tracing thematic evolution, and examining the social structure of research collaboration. By doing so, it seeks to bridge the gap between fragmented studies and offer a holistic view of the field’s development from its inception to 2026. MothodologyThis research employs a bibliometric approach, specifically utilizing the five-step method proposed by Zupic and Cater (2015), to systematically analyze the scientific literature on UPB. The study is descriptive-analytical in nature, aiming to quantify and visualize the structure and dynamics of the research field. Data were extracted from two major bibliographic databases: Web of Science (WoS) and Scopus. The search string included keywords related to "unethical pro-organizational behavior" across titles, abstracts, and keywords to ensure comprehensive coverage. Initially, 244 articles were retrieved from WoS and 299 from Scopus. After applying inclusion criteria—restricting the document type to peer-reviewed journal articles and review papers, and limiting the language to English and Persian (with subsequent focus on English for global analysis)—a final dataset of 290 high-quality articles published between 2010 and 2026 was compiled. The analysis was conducted using R software (version 4.4.2) and specialized bibliometric tools. Several analytical techniques were employed to address the research questions: descriptive statistics were used to assess publication trends and growth rates; citation analysis identified the most influential journals, authors, and documents based on h-index, g-index, and m-index; bibliographic coupling and co-word analysis were used to map thematic trends and conceptual structures; and co-authorship network analysis explored the social structure of collaboration among countries and researchers. The co-word analysis allowed for the identification of conceptual clusters based on keyword co-occurrence, while bibliographic coupling helped trace the intellectual flow of the field. This multi-method approach ensures a robust and multidimensional understanding of the UPB research landscape. FindingsThe bibliometric analysis reveals significant growth and maturation in the field of UPB. The dataset of 290 articles shows an annual growth rate of 13%, indicating sustained and increasing academic interest. The average age of the articles is approximately 3.5 years, with an average citation count of 26 per article, suggesting high impact and relevance. The Journal of Business Ethics emerged as the most influential journal, followed by the Journal of Applied Psychology and Organization Science, highlighting the interdisciplinary nature of the research, bridging ethics, psychology, and management. In terms of authorship, Elizabeth Eve Umphress, John B. Bingham, and Marie S. Mitchell are identified as foundational scholars, having established the theoretical frameworks in the early years. However, recent years have seen a surge in productivity from Chinese scholars, particularly Ying Zhang, Yu Wang, and Shuang Zhang, indicating a shift in the center of gravity towards Asian contexts. These scholars demonstrate high h-index and g-index values, reflecting both high productivity and consistent citation impact.Thematic analysis through co-word clustering identified six major research streams. The dominant stream, characterized by high centrality and density, focuses on "Organizational Identity and Foundational Ethics," linking UPB to social identity theory and moral justification. Another significant stream explores "Moral Psychology, Leadership, and Social Exchange," emphasizing factors like psychological entitlement, leader-member exchange, and ethical leadership. A third cluster highlights "Cognitive Mechanisms and Ethical Leadership," focusing on moral disengagement and the dual role of leadership in either mitigating or exacerbating UPB. Other clusters address "Business Ethics and Job Satisfaction," "Negative Consequences and Complex Leadership Styles," and "Ethical Climate and Psychological Resources." Conceptual mapping further revealed three core structures: organizational drivers and leadership styles, psychological foundations and moral identity, and consequences and conceptual expansion (including unethical pro-family behavior). Social network analysis of authorship and country collaboration depicted a bipolar global structure dominated by the United States and China. The US acts as the theoretical hub and global connector, while China serves as a major production center and field laboratory, often testing US-derived theories in specific cultural contexts. Emerging collaborations with countries in Southeast Asia, India, and Korea suggest a democratization and localization of the field. Discussion and ConclusionThe findings of this bibliometric study highlight the complex and evolving nature of Unethical Pro-Organizational Behavior (UPB) research. The field has progressed from early definitional debates toward more sophisticated investigations of psychological mechanisms and contextual factors. The prominence of Organizational Identity and Moral Disengagement underscores the central paradox of UPB: employees may rationalize unethical acts as necessary sacrifices for organizational benefit. This suggests that UPB is not simply a consequence of individual moral failure but may emerge from organizational pressures, leadership practices, and social exchange dynamics.The growing contribution of Chinese scholars reflects the increasing relevance of UPB in collectivist and high-context cultural settings, where group loyalty and face-saving may encourage pro-organizational misconduct. This trend highlights the need for future research to incorporate cultural differences and move beyond predominantly Western theoretical perspectives. The prominence of Ethical Leadership and Bottom-line Mentality further emphasizes the role of management in shaping ethical climates. In particular, strong pressure for performance outcomes combined with inadequate ethical oversight may increase employees’ tendency to justify unethical behavior in the organization’s interest.The emergence of Unethical Pro-Family Behavior also indicates an expansion of UPB research toward broader forms of in-group favoritism, suggesting that prioritizing group interests over universal ethical standards may extend beyond organizational contexts. Moreover, findings such as emotional exhaustion reveal that UPB can impose psychological costs on employees in addition to reputational and organizational consequences.In conclusion, this study provides a comprehensive overview of the UPB research domain, identifying its major contributors, thematic evolution, and patterns of international collaboration. Overall, UPB appears to be a multifaceted phenomenon shaped by the interaction of individual psychology, organizational culture, and leadership. From a practical perspective, organizations should strengthen ethical climates, establish clear codes of conduct, and promote leadership approaches that prioritize integrity over short-term performance. Future research should address the limited evidence from longitudinal and cross-cultural studies, particularly in non-Western contexts, and examine the conditions and interventions that can reduce UPB while allowing organizations to benefit from employee commitment without compromising ethical standards.
Conceptualization
Ali Yasini
Abstract
IntroductionIn contemporary organizational research, increasing attention has been directed toward the subtle and often unregulated dynamics of informal power. Although formal hierarchies remain central to organizational theory, symbolic power, reputation, informal networks, and discretionary access ...
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IntroductionIn contemporary organizational research, increasing attention has been directed toward the subtle and often unregulated dynamics of informal power. Although formal hierarchies remain central to organizational theory, symbolic power, reputation, informal networks, and discretionary access to information can substantially shape employees’ everyday experiences. Within this context, the metaphor of the “organizational Bigfoot” describes influential actors whose power extends beyond formal organizational structures while remaining partly invisible. These individuals, often senior managers, tenured faculty, or long-established employees, may exercise disproportionate influence through social prestige, narrative control, informal alliances, and gatekeeping. Their presence can shape workplace culture, communication, and decision-making, while generating caution, emotional tension, and reduced employee agency even without explicit threats or coercion.Academic institutions provide a particularly relevant context for examining such invisible power. Despite universities’ emphasis on intellectual freedom, collegiality, and scholarly autonomy, academic environments are also influenced by hierarchies associated with academic rank, reputation, disciplinary networks, and access to scarce resources. Consequently, junior faculty and administrative staff may encounter powerful actors who influence career advancement, committee decisions, research opportunities, and acceptable forms of dissent. The organizational Bigfoot metaphor therefore offers a useful framework for understanding how symbolic authority becomes embedded in everyday organizational interactions and psychological experiences.Although previous research on toxic leadership, workplace bullying, abusive supervision, and organizational silence has established the consequences of negative power dynamics, much of this literature emphasizes observable behaviors or quantitative relationships and provides less insight into how individuals subjectively interpret and experience covert forms of influence. Addressing this gap, the present study adopts a phenomenological approach to explore the lived experiences of staff and faculty members working under the influence of organizational Bigfoots. Specifically, it examines how employees perceive covert authoritarianism, understand its effects on organizational functioning, and develop coping strategies. By doing so, the study seeks to advance understanding of informal domination and its implications for employee well-being, innovation, morale, and institutional vitality. MothodologyThis study was grounded in the interpretivist paradigm, viewing organizational phenomena as socially constructed through human interpretation. Given the aim of understanding participants’ lived experiences rather than measuring predefined variables, a qualitative design based on Interpretative Phenomenological Analysis (IPA) was adopted. This approach enabled an in-depth exploration of the psychological, relational, and symbolic dimensions of informal power and how individuals make sense of complex organizational experiences.Data were collected through in-depth semi-structured interviews with 25 purposively selected faculty members and administrative staff at Ilam University who had direct experience with powerful informal actors. Interviews were conducted privately and lasted 60–90 minutes. The interview guide addressed experiences of covert power and informal authority, emotional and cognitive responses, effects on communication and innovation, coping strategies, and perceptions of organizational culture and leadership.Data analysis followed Braun and Clarke’s (2021) six-phase thematic analysis. Interviews were transcribed verbatim and repeatedly reviewed, followed by initial coding, theme development, and iterative refinement of themes to establish conceptual clarity and coherence.Research rigor was assessed using Lincoln and Guba’s (1985) criteria. Credibility was enhanced through member checking with three participants and peer debriefing. Confirmability was supported through reflexivity and analytic memos, while transferability was strengthened through rich contextual descriptions. Dependability was addressed through a transparent audit trail documenting methodological procedures, coding decisions, and theme development. FingdingsData analysis revealed five overarching themes, each reflecting distinct dimensions of participants’ lived experiences under the influence of organizational Bigfoots. Fifteen subthemes supported these main categories The Heavy Shadow of Covert AuthoritarianismParticipants described these powerful actors as possessing an “aura of untouchability,” wielding authority beyond formal roles. Their presence was experienced as a constant, looming force shaping meetings, decisions, and informal conversations. Even in their absence, employees modified their behavior based on anticipated reactions. This shadow governance produced climates characterized by self-censorship, anticipatory compliance, and emotional vigilance. Organizational Ecosystem BlockageThe second theme captured the structural and procedural barriers created by these individuals. Participants described how powerful actors acted as gatekeepers, controlling access to resources, approval channels, collaborations, and information flows. Innovation and creative initiatives were often stalled, redirected, or dismissed unless aligned with the preferences of the dominant actor. This produced a sense of stagnation in which organizational processes became rigid, slow, and tightly filtered. Psychological–Emotional ErosionParticipants reported chronic emotional strain, including anxiety, frustration, anger, and diminished self-worth. Repeated exposure to subtle intimidation, dismissiveness, or exclusion eroded professional confidence. Many described emotional fatigue and a progressive withdrawal from organizational engagement. This erosion was not the result of overt hostility but of persistent micro-dynamics that undermined psychological security. Systematic BetrayalA strong subtheme centered on the failure of organizational structures to protect employees. Participants expressed pessimism toward formal complaint mechanisms, perceiving them as symbolic rather than functional. Some believed that institutional processes implicitly protected powerful individuals due to their prestige, long tenure, or political connections. This sense of institutional betrayal intensified feelings of vulnerability and mistrust. Survival and Camouflage StrategiesEmployees developed adaptive behaviors aimed at minimizing exposure to risk. These included strategic silence, impression management, limiting initiative, avoiding visibility, and “professional camouflage.” Although these strategies enabled short-term self-preservation, they simultaneously reinforced organizational stagnation. Participants noted that genuine creativity or constructive criticism became emotionally costly and professionally risky.Across all themes, participants repeatedly referenced two emergent collective phenomena: “graveyard silence”—a climate of pervasive quietude, avoidance, and conformity—and “innovation sterilization”, in which creative energies are redirected away from productivity and toward coping and self-protection. Together, these patterns illustrate how organizational Bigfoots reshape the entire institutional ecosystem, affecting not only individual experiences but also organizational outcomes. Discussion and ConclusionThe study provides a nuanced understanding of how informal power operates in organizational contexts through the metaphor of the organizational Bigfoot. Unlike formal authority, Bigfoot-style power is diffuse, symbolic, and often invisible—yet deeply consequential. The findings demonstrate that such actors influence not only interpersonal relationships but also institutional structures, communication norms, and psychological climates.One of the most significant theoretical insights concerns the invisible nature of dominance. The shadow cast by these powerful individuals does not require overt aggression; rather, it functions through perceived consequences, collective narratives, and internalized expectations. This aligns with emerging theories of symbolic violence and soft domination within organizations, where power operates through perception rather than explicit coercion.The identified phenomena of “graveyard silence” and “innovation sterilization” offer important contributions to understanding organizational dysfunction. When employees devote cognitive and emotional resources to managing uncertainty and navigating powerful informal actors, their capacity for creativity, collaboration, and risk-taking diminishes. Over time, this dynamic becomes self-reinforcing: reduced innovation weakens organizational vitality, which further concentrates power among dominant actors.Practical implications are equally significant. Organizations—especially universities—must recognize the limitations of formal structures in addressing informal power dynamics. Training programs that promote ethical leadership, emotional intelligence, and accountability are necessary but insufficient. More importantly, institutions need to introduce confidential reporting mechanisms, transparent decision-making processes, and distributed leadership models that reduce the likelihood of power monopolization.In conclusion, this study expands theoretical understanding of informal power by conceptualizing organizational Bigfoots and empirically examining their effects on employees’ lived experience. By revealing the emotional, relational, and structural consequences of shadow domination, the study underscores the importance of organizational cultures that promote psychological safety, transparency, and equitable access to influence. Addressing these issues is essential for fostering workplace environments where innovation, well-being, and organizational learning can thrive.
Pathology
Pantea Ghaffari; Seyyed Mehdi Alvani; Amirhesam Arabi
Abstract
IntroductionThe digital age has brought significant complexity to social, economic, and environmental spheres, driving a profound change in public policymaking. With the surge in digital data and rapid advancements in artificial intelligence (AI), traditional policy models based on qualitative methods ...
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IntroductionThe digital age has brought significant complexity to social, economic, and environmental spheres, driving a profound change in public policymaking. With the surge in digital data and rapid advancements in artificial intelligence (AI), traditional policy models based on qualitative methods and personal judgment are being replaced by adaptive, evidence-based, and data-driven approaches. AI and data science now play a pivotal role, expanding possibilities in knowledge production, supporting political decision-making, and improving government responsiveness. AI excels at analyzing vast amounts of both structured and unstructured data, uncovering patterns, forecasting scenarios, and offering actionable policy insights—making it an important aid to human policymakers. This change is also propelled by increasing demands to manage complex issues like environmental threats, demographic changes, and security risks. In countries such as Canada, Estonia, and Singapore, incorporating AI into policymaking has led to more transparency, better efficiency, and reduced corruption. Importantly, AI serves as a decision-support tool—enhancing multi-dimensional analysis for evidence-based and timely policy choices, rather than replacing human decision-makers. This has encouraged a move away from intuition-led governance toward predictive modeling and scenario-based planning. Recent research also highlights the value of developing locally relevant AI models for public policy, stressing that universal solutions risk ignoring each society’s unique cultural, social, and structural features, thereby reducing effectiveness and potentially increasing inequality. Integrating indigenous knowledge with advanced AI creates new opportunities for participatory governance that is sensitive to national context. MethodologyThis study employs a rigorous systematic review methodology, strictly adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. The analysis draws upon both qualitative content and comparative thematic analysis to synthesize insights from leading international examples and local requirements. The research design involved extensive searches of reputable scientific databases, including Web of Science, Scopus, IEEE Xplore, ScienceDirect, and SpringerLink. The search spanned from 2010 through 2024, capturing literature that reflects the evolution and contemporary challenges of AI in policy environments. A total of 632 articles were identified in the initial search. After applying predefined inclusion and exclusion criteria, 28 scholarly articles were selected for in-depth analysis. The inclusion criteria prioritized empirical studies, systematic reviews, and conceptual papers that directly addressed AI’s role at various stages of the public policy cycle. Exclusion criteria eliminated commentaries, opinion pieces, and studies lacking robust methodological foundations. The data extraction process emphasized key thematic areas such as algorithmic bias, model transparency, privacy implications, efficiency gains, and ethical frameworks.Subsequent qualitative content analysis identified recurrent themes, theoretical models, and cross-national comparative insights. The analysis also featured benchmarking against real-world case studies from Canada, Estonia, and Singapore to contextualize global best practices and challenges. Special attention was paid to frameworks integrating local knowledge, participatory governance models, and multi-level governance protocols, which were deemed critical for tailoring AI systems to Iran’s unique societal landscape. Additionally, the research incorporated expert interviews and policy analysis reports relevant to the Iranian context as supplementary sources, ensuring a comprehensive and multi-dimensional perspective. FindingsThe systematic review and qualitative analysis of the selected articles revealed several overarching patterns in the application of AI across the five key stages of the public policy cycle: problem identification, policy analysis, solution design, effective implementation, and continuous evaluation. In leading countries, AI contributes to more incisive issue detection and refined analysis by leveraging big data, machine learning algorithms, and advanced social network analytics. These technologies not only facilitate the identification of emergent societal trends and nuanced policy challenges but also enable anticipation of complex feedback loops resulting from policy actions. Effective deployment of AI supports evidence-based solution design by integrating predictive analytics and simulation models. For instance, in healthcare policymaking, AI-driven epidemic modeling enables early detection of outbreaks and optimizes resource allocation. In environmental governance, AI-enhanced monitoring systems contribute to more accurate assessments of ecosystem dynamics and support adaptive regulatory responses. In economic policy, AI enables sophisticated scenario forecasting, guiding macroeconomic stabilization and investment strategies. Implementation stages benefit from AI through real-time monitoring of policy outcomes, automated reporting systems, and decision support platforms. Machine learning models assist in tracking program performance, detecting anomalies, and generating alerts for corrective action. Beyond operational efficiencies, AI facilitates increased transparency by making policy processes and outcomes more accessible and auditable to citizens and oversight institutions. In Singapore, for example, AI-powered smart platforms have redefined public service delivery, while in Estonia, decentralized digital governance protocols have streamlined administrative procedures and reduced governmental friction. Evaluation and continuous improvement are bolstered by AI’s capacity to analyze large-scale feedback, perform sentiment analysis on citizen inputs, and identify persistent gaps in policy effectiveness. Social network analysis further elucidates community-level reactions and supports participatory assessment models, strengthening the feedback loop between policy designers and stakeholders. Despite these benefits, persistent challenges remain. Algorithmic bias, data silos, lack of model explainability, and privacy threats are cited as major risks in the reviewed literature. The risk of perpetuating inequities through unexamined algorithms is particularly acute in heterogeneous societies. Moreover, the opacity of AI models can undermine trust, especially when policy decisions have significant social impact. Privacy concerns are magnified with the expansion of surveillance capacities and the aggregation of sensitive personal data. The analysis of Iranian policy literature and expert interviews underscores that, while technical infrastructure and expertise are growing, systemic hurdles persist. Data fragmentation, lack of unified governance protocols, and insufficient legal frameworks hamper comprehensive AI adoption. Furthermore, the absence of robust digital literacy programs among civil servants and the public inhibits meaningful participation in AI-driven governance processes. The persistence of legacy administrative systems and cultural resistance to technological change are additional factors constraining the transformative potential of AI in Iran’s public sector. Discussion and ConclusionThe findings highlight both remarkable opportunities and critical gaps in AI implementation within Iranian public policymaking. While several operational advances have been achieved, the current landscape remains primarily concentrated on efficiency-driven applications, with less emphasis on transformative restructuring of policymaking processes. Most Iranian initiatives focus on automating administrative tasks, optimizing workflow management, and improving service delivery. However, the integration of AI into strategic policy design, legitimization, and evaluation is nascent. A major limitation identified in the literature is the insufficient localization of AI models. International examples demonstrate that successful AI-driven governance depends not only on technological sophistication but also on contextual adaptability. Standardized solutions, when imported without nuanced customization, risk incompatibility and even adverse societal consequences. In countries with complex socio-cultural fabrics such as Iran, effective AI adoption requires multidimensional customization, balancing technological advancement with cultural sensitivities, governance traditions, and legal norms. The absence of comprehensive ethical and regulatory frameworks in Iran poses additional barriers. International best practices advocate for the implementation of algorithmic transparency protocols, independent ethics councils, and regulatory sandboxes for testing novel policy models. However, Iran’s current legal and institutional arrangements do not adequately address challenges related to data ownership, privacy protection, and algorithmic accountability. This gap not only undermines public trust but also exposes the policy ecosystem to risks of misuse, bias propagation, and social disenfranchisement. The reviewed literature indicates that fostering a culture of digital literacy and inclusivity is vital for successful AI-driven governance. Participatory governance models, as adopted in Estonia and Singapore, underscore the importance of stakeholder engagement and cross-sectoral collaboration. In Iran, the segmentation of policymaking institutions and the predominance of hierarchical structures limit opportunities for dynamic interaction between technologists, policymakers, and civil society. Bridging this gap requires strategic investment in capacity-building initiatives, curriculum reform, and the promotion of cross-functional policy innovation teams. A three-layered conceptual framework is proposed to address these challenges and optimize AI integration in Iranian policymaking:Layer 1 – Technological Integrity: Establish robust national standards for data quality, security, and interoperability across government databases. Centralize critical data infrastructure and introduce mandatory bias and explainability testing for all public sector algorithmic models.Layer 2 – Institutional and Legal Governance: Develop a unified and adaptive national AI policy, including legal mandates for algorithmic transparency and the creation of an independent ethics and auditing council. Pilot regulatory sandboxes to enable careful experimentation with innovative policy mechanisms while upholding minimum standards for transparency and accountability.Layer 3 – Socio-Cultural and Strategic Capacity: Launch comprehensive public and civil servant digital literacy programs and promote strategic workforce planning to cultivate indigenous AI expertise. Encourage public discourse on data ethics, privacy, and algorithmic fairness to strengthen collective trust in AI-enabled governance. This research systematically maps the current state and future prospects of AI utilization in Iranian public policymaking, drawing upon in-depth analysis of 28 scholarly articles, global case studies, and local context assessments. The findings confirm that, while progress is being made in operational efficiency and administrative modernization, the full transformative potential of AI in Iranian policy remains largely untapped. Persistent technical, institutional, and cultural barriers must be addressed to enable a successful shift toward intelligent, data-driven governance. The proposed three-layered indigenous framework offers a comprehensive roadmap for aligning technological innovation with ethical imperatives and robust institutional structures. By addressing data integrity, regulatory oversight, and strategic capacity development in tandem, Iran can maximize the benefits of AI integration while mitigating associated risks. Looking forward, future research should prioritize quantitative impact assessment, pilot program evaluations, and longitudinal studies tracking the evolution of AI models within Iranian governance. Policymakers are encouraged to embrace collaborative and cross-sectoral approaches, harnessing both local expertise and international best practices. Ultimately, Iran’s journey toward intelligent governance will depend not only on acquiring advanced algorithms but also on embedding them within transparent, participatory, and ethically governed policy systems. Only through this holistic strategy can Iran unlock AI’s full potential to advance social welfare, economic resilience, and sustainable development.
Modeling
Zeinab Salehi Khalaf Badam; Naser Barkhordar; Rashid Zolfaghari Zaafarani
Abstract
Introduction
Transformational leadership is the ability to create and guide a meaningful and bold vision that not only separates people from the status quo, but also forces them to redefine their own identity, values, and abilities so that they voluntarily become agents of change. Even in situations ...
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Introduction
Transformational leadership is the ability to create and guide a meaningful and bold vision that not only separates people from the status quo, but also forces them to redefine their own identity, values, and abilities so that they voluntarily become agents of change. Even in situations of extreme uncertainty. Transformational leadership is known as a process in which leaders and followers push each other to a higher level of ethics and motivation. Municipalities generally have a strong hierarchical structure and a deep bureaucratic culture. This can be a major obstacle to transformational leadership, as it is difficult to shift decision-making power and encourage bottom-up participation from employees. Resistance from middle managers, who are accustomed to traditional command-and-control styles, can be a major obstacle. Tehran Municipality, as a large and complex organization, plays a vital role in providing public services and managing urban affairs. Sometimes, the lack of active participation of employees in decision-making processes can prevent the organization from fully realizing its potential and providing quality and innovative services to citizens. The purpose of this research was to design a transformational leadership model with a participatory approach for Tehran Municipality employees.
Methodology
The present research method is applied in terms of purpose, descriptive-survey in terms of nature and method, and mixed in terms of method. The statistical population of the research included managers with more than ten years of experience in the field of Tehran municipality management, professors and experts in management and urban services familiar with the subject of transformational leadership in the 22 districts of Tehran municipality. Sampling was carried out using purposive, theoretical, and snowball methods with a total of 15 people until the theoretical saturation stage of data collection. The data collection tool was semi-structured interviews and thematic analysis using structural-interpretive modeling. The qualitative data analysis method was a three-stage coding of basic themes, organizing themes, and overarching themes. Also, for quantitative data, the structural-interpretive modeling method was used with the MICMAC software. In this study, first, using the five initial stages of the content analysis strategy, the components and indicators in the theoretical foundations of transformational leadership are extracted, and after evaluating them using the interview technique and the content analysis method, qualitative analysis and coding of the extracted components and indicators are carried out, and the relevant questions are presented along with the proposed model. To ensure the validity and reliability of the research data, face and content validity were used, and Cronbach's alpha method was used to determine the reliability of the test.
Findings
The findings showed that the transformational leadership model, with an emphasis on the participation of Tehran Municipality employees, consists of 149 codes, 25 basic themes, and 8 organizing themes. The eight main components include creating a shared vision, inspiring motivation, empowering employees, effective interaction and communication, stimulating and influencing, collaborating and thinking together, organizational performance, and virtue ethics. Quantitative results showed that stimulation and influence, employee empowerment, moral and spiritual role models, and creating a shared vision are the most influential and are the underlying components, respectively. It is suggested that the municipality take a step towards achieving organizational goals by creating a fair and transparent recognition and encouragement system for employees.
Discussion and Conclusion
The relationships between the components of the model show that the components of inspirational motivation, effective interaction and communication, cooperation and collaboration, and organizational performance have a two-way relationship and mutual influence, but the relationship between the other components is one-way. On the other hand, according to the obtained model, it should be acknowledged that the components of inspirational motivation, effective interaction and communication, cooperation and collaboration, and organizational performance, which are located at the fifth level, have the greatest impact on other components, and also the component of stimulation and influence, which is located at the first level, receives the greatest impact from other components. The overall results of the research are as follows: Participatory leaders, by creating and promoting a clear and shared vision, define organizational direction and increase employee commitment and alignment. Inspirational leaders inspire employees to go beyond expectations by inspiring and motivating them. This motivation is created by communicating the organization's values, beliefs, and lofty goals to employees, as well as encouraging and appreciating their efforts. Participatory leaders empower employees by delegating authority, providing necessary training, and creating opportunities for growth and development. This empowerment increases the sense of ownership, responsibility, and active participation of employees in decision-making. Emphasis on ethical values and responsible behavior, justice, fairness, and integrity in all organizational dimensions leads to the promotion of professional ethics, public trust, and organizational sustainability. Virtuous leaders inspire others by modeling ethical behavior and human values and promote a virtue-based organizational culture. Research suggests that collaborative leaders, by creating and promoting a clear and shared vision, set organizational direction and increase employee commitment and alignment. Inspirational leaders inspire employees to go above and beyond expectations by inspiring and motivating them.
This motivation is created by communicating the organization's values, beliefs, and lofty goals to employees, as well as by encouraging and appreciating their efforts. Participatory leaders empower employees by delegating authority, providing necessary training, and creating opportunities for growth and development. This empowerment increases employees' sense of ownership, responsibility, and active participation in decision-making. Emphasizing ethical values and responsible behavior, justice, fairness, and integrity in all organizational dimensions promotes professional ethics, public trust, and organizational sustainability.
Virtuous leaders inspire others by modeling ethical behavior and human values and promote a virtue-based organizational culture. Research suggestions include holding brainstorming sessions, developing a vision document, recognizing and encouraging, creating growth and development opportunities, delegating authority, providing necessary training, creating communication channels, creating opportunities for exchanging ideas, supporting risk-taking, and forming work teams.
Causation
Azadeh Eftekhar; Kiumars Ahmadi; Reza salehi; Yaghoub aHMADI
Abstract
IntroductionKnowledge-based companies, as the main drivers of innovation, economic growth and added value creation, play a decisive role in the development of societies (Kapotzis, 2024). By focusing on emerging technologies and utilizing creative ideas, these organizations not only contribute to job ...
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IntroductionKnowledge-based companies, as the main drivers of innovation, economic growth and added value creation, play a decisive role in the development of societies (Kapotzis, 2024). By focusing on emerging technologies and utilizing creative ideas, these organizations not only contribute to job creation and enhance national competitiveness, but also demonstrate high agility and flexibility in conditions of environmental uncertainty. However, the emerging nature of these companies, their small scale and limited human and financial resources, which have been repeatedly mentioned in various studies, have presented them with numerous challenges in the areas of organizational culture and effectiveness. A weak organizational culture can lead to reduced team collaboration, decreased employee motivation, increased internal conflicts and even failure to achieve organizational goals. On the other hand, low effectiveness threatens the ability of these companies to achieve sustainable goals and compete in dynamic markets (Boschgens, 2021).Organizational culture, as a set of shared values, beliefs, and norms that shape the path of employee behavior and decision-making (Shayne, 2010; Cameron and Quinn, 2011), forms the foundation of organizational behavior, decision-making, and performance. This concept is doubly important in knowledge-based companies, which are often composed of young, dynamic, and diverse teams. Organizational culture not only affects the way in which intra-organizational interactions occur, but also determines the organization's strategic direction and ability to innovate and adapt to environmental changes. Research shows that different types of organizational cultures have different effects on the performance and effectiveness of companies and economic and organizational institutions. For example, group and innovative organizational cultures that emphasize collaboration, creativity, and continuous learning have the greatest positive impact on the performance of economic-administrative institutions and enterprises; In contrast, market or hierarchical cultures that focus on competition or excessive control may have negative or weaker effects on organizational performance (Hartnell et al., 2011). In this regard, strengthening a culture that promotes values such as trust, commitment, and collaboration is crucial for the success and effectiveness of knowledge-based start-ups. Despite the high potential of coaching, and especially team building in institutions, a recent literature review (Grant, 2017; Farahani, 1400) shows that most of the research conducted in this area has focused on large and established organizations and has less addressed the specific context of knowledge-based and start-ups. This is while the dynamic nature, resource constraints, and the need for rapid learning in these companies require that mechanisms such as team building be examined more carefully. Especially in the context of Iran and in provinces such as Kurdistan, where knowledge-based companies are growing and developing, examining the effect of coaching-based team building on organizational culture and effectiveness can provide valuable findings for managers, policymakers, and activists in this field. In Iran, it is only in recent years that the importance and role of team building and coaching in general in facilitating and strengthening organizational processes and bureaucratic and associational relations has been emphasized, and today it is mentioned as an important issue and factor in strengthening organizational effectiveness. In Kurdistan, however, this issue still does not have a special place in analyses and research as it should, and there is not much focus on it.Team building, by strengthening interactions and synergies between members, can help transform and diversify the organizational culture and performance of various companies and institutions. This is particularly important in start-up knowledge-based companies that often work with small, multidisciplinary teams. Accordingly, this study aimed to explain the effect of team building as a subset of coaching on organizational culture and effectiveness in knowledge-based companies in Kurdistan and to examine the mediating role of team building. The main research question is: How does team building affect the organizational culture and effectiveness of these companies and what is the role of team building in these relationships? MothodologyThis study was designed and implemented with a qualitative approach based on the grounded theory method. The statistical population of the study included experts and elites in the fields of management, human resources, and knowledge-based businesses in Kurdistan Province. These individuals were selected based on criteria such as at least five years of management experience in knowledge-based companies, a history of relevant research activity, or a prominent executive role in this field to ensure that their perspectives were based on in-depth knowledge and practical experiences. Sampling was purposive and non-probability and continued until theoretical saturation was achieved, at which point new data did not add new information. Finally, 12 in-depth interviews were conducted with these experts, which was determined to be sufficient depth and data saturation based on qualitative methodological standards (such as those proposed by Creswell, 2013). The main data collection tool was in-depth semi-structured interviews. Data analysis was conducted according to Strauss and Corbin's (1998) three-step process: in the open coding stage, the interview transcripts were reviewed line by line and primary key concepts (such as "job commitment" or "organizational learning") were extracted; in the axial coding stage, the relationships between these concepts were identified and grouped into main categories (such as causal, contextual, and intervening conditions); and in the selective coding stage, the central phenomenon ("teambuilding as a basis for sustainable transformation through culture") was determined and a paradigmatic model of the relationships between the categories was drawn. To ensure the validity and reliability of the findings, several strategies were adopted: internal validity was strengthened through data triangulation (by comparing interviews and literature) and peer review (review of coding by a second researcher); reliability was ensured by careful documentation of the process (such as recording initial codes and changes); and transferability was provided through a rich description of the research context (start-up knowledge-based companies in Kurdistan). Also, researcher reflexivity (recording assumptions and their impact on the analysis) was applied to reduce bias. FingdingsThis section presents the results of the findings extracted from interviews with experts, including managers and specialists in this field, on the subject of team building, organizational culture, and effectiveness in start-up knowledge-based companies. The analysis of this situation is based on the analysis of field data collected based on the provisions of grounded theory. Thematic analysis of the collected data led to the extraction of 20 primary categories, 9 secondary categories, and one core category. Analysis of the data obtained from interviews with 12 managers and experts of start-up knowledge-based companies in Sanandaj showed that team building coaching is not simply an educational intervention, but a transformative process that leads to the improvement of organizational effectiveness by changing and redefining organizational culture. In other words, the central category of the research was identified as “Team Building as the Basis of Sustainable Transformation in Knowledge-Based Companies through Culture”.Central Phenomenon: Team Building as the Basis of Sustainable Transformation in Knowledge-Based Companies through CultureThe analysis of interview data showed that “team building” in new knowledge-based companies acts not simply as an educational intervention or a tool for improving individual skills, but as a central and comprehensive phenomenon that links other categories in the data-based theory model. This central category encompasses the idea that team building provides the necessary context for enhancing organizational effectiveness by shaping shared organizational values, norms, and beliefs. Based on the findings, team building can function at three levels: the individual level, by strengthening communication skills and self-awareness; the group level, by increasing synergy, empathy, and social learning; and the organizational level, by institutionalizing new cultural values and creating sustainability in organizational behavior. From this perspective, team building, in the eyes of the interviewees, is a pivotal phenomenon, a connecting link between organizational culture strategies and organizational effectiveness outcomes. Discussion and ConclusionThe purpose of this study was to identify, discover, and analyze the relationships between team building as one of the main components of the coaching process in organizations and institutions on organizational culture and, through it, on effectiveness in new knowledge-based companies in Kurdistan Province. The findings indicate the pivotal role of team building as a transformative process in redefining organizational culture and enhancing organizational effectiveness in knowledge-based companies. The central theme of the research, “Team Building as the Basis of Sustainable Transformation Through Culture,” emphasizes that coaching leads to the sustainability and growth of knowledge-based start-ups by changing shared organizational values, beliefs, and norms. The findings of this study showed that team building within the scope of coaching, beyond a training or personal development tool, acts as a transformative process that enhances the effectiveness of knowledge-based start-ups by redefining organizational culture. The findings of the present study, based on the opinions and themes extracted from the interviews, show that team building, by strengthening the dimensions of organizational culture (such as trust, commitment, and learning), can lead to increased effectiveness in knowledge-based companies, especially new and emerging types, as previously stated by Grant (2017) and Theobaum et al. (2014) by stating that "team building is a mechanism for promoting human and social capital.
Other
Ensiyeh Barkhordari Ahmadi; Mohammad Montazeri; Shams Al Sadat Zahedi
Abstract
IntroductionSustainable development is defined as a form of development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs. Achieving sustainable development is inherently dependent on human development, as it emphasizes addressing ...
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IntroductionSustainable development is defined as a form of development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs. Achieving sustainable development is inherently dependent on human development, as it emphasizes addressing current and future needs while reducing deprivation without exhausting vital resources. Community development, in this context, involves collective efforts by individuals to improve economic, social, cultural, and environmental conditions through participation, cooperation, and shared goals. Research consistently highlights human capital as the most valuable asset of any organization, indicating that sustainable development cannot be realized without investing in human capabilities, particularly among youth.One important indicator of challenges facing young people is the NEET index, which measures the proportion of youth who are not in employment, education, or training. This index provides a clearer picture of youth disengagement and underscores the urgency of policies aimed at youth empowerment and inclusion. Positive Youth Development (PYD) has emerged as both a research framework and a practical approach that draws from multiple disciplines, including psychology, sociology, public health, education, and social work. PYD emphasizes creating opportunities that foster competence, belonging, empowerment, and social participation among young people, aligning closely with the broader goals of sustainable development.In organizational and governmental contexts, strategic management and performance evaluation play a crucial role in ensuring effective implementation of development-oriented strategies. Modern organizations increasingly recognize that sustainable growth and competitiveness require systematic performance measurement and continuous improvement. Within this framework, youth-oriented management has gained attention as a key driver of innovation, flexibility, and efficiency, particularly in public sector organizations facing rapid social and technological change.Despite its importance, management in the public sector often remains traditional and experience-centered, limiting the participation of young professionals in decision-making processes. Research suggests that youth-oriented management can enhance organizational performance, improve decision-making, and increase public satisfaction. Key components for developing youth-oriented management include supportive policies, organizational culture change, clear career pathways, managerial skill development, effective incentive systems, structural reforms, and the use of modern technologies. Accordingly, this study aims to identify and evaluate the components of youth-oriented management in the public sector and to propose a comprehensive and practical model to guide policymakers and senior managers in fostering sustainable and dynamic governance through youth engagement. MethodologyThis study employed an applied–developmental research design and was conducted using an inductive and mixed-methods approach. The qualitative phase followed an exploratory strategy, while the quantitative phase was carried out using the Fuzzy Analytic Hierarchy Process (FAHP). The statistical population in the first stage corresponded to the qualitative phase of the research and consisted of experts, specialists, and senior managers in public sector organizations. Participants were required to hold a doctoral degree and have a minimum of five years of managerial experience in governmental organizations. Sampling was conducted through purposive sampling combined with the snowball technique, and participant selection continued until theoretical saturation was achieved. Ultimately, 18 experts participated in the study.In addition, because this research applied a multi-criteria decision-making technique, and according to Chang et al. (2008) the opinions of 10 to 30 experts are sufficient for forming a decision-making group, the same 18 participants from the qualitative phase were selected as the sample for the quantitative phase.Data collection instruments included semi-structured interviews in the qualitative phase and a researcher-developed pairwise comparison questionnaire in the quantitative phase, which was designed based on the findings of the qualitative stage. To ensure trustworthiness in the qualitative phase, the Lincoln and Guba criteria were applied. In the quantitative phase, the reliability of the pairwise comparison questionnaire was confirmed using the consistency ratio.For data analysis, grounded theory was employed in the qualitative phase to extract key categories and components. In the quantitative phase, multi-criteria decision-making techniques were used to prioritize the identified components of youth-oriented management. Specifically, the collected data were analyzed using the Fuzzy Analytic Hierarchy Process (FAHP), which enables the ranking of alternatives based on multiple criteria under conditions of uncertainty. FindingsAs shown by the results of the qualitative analysis, the experts participating in the 18 in-depth interviews referred to a wide and diverse range of factors in response to the research questions. At this stage, a large volume of raw interview data was extracted, resulting in numerous initial codes. Through an iterative and back-and-forth data analysis process, these codes were gradually refined, merged, and reduced. To avoid redundancy, conceptually similar or repetitive codes were grouped into unified sets, leading to the formation of broader concepts and categories. As a result of this systematic process, a total of 11 main categories were identified.To ensure the adequacy of category selection, a minimum frequency threshold of nine was considered, meaning that at least half of the interviewees had to mention a category for it to be retained. This criterion was applied based on Chang’s (2008) recommendation and served as a clear decision rule for including or excluding extracted categories. Following multiple rounds of screening and validation, the final categories were confirmed and used as the basis for the quantitative phase.In the next stage, the relative importance of the identified factors influencing youth-oriented management in the public sector was examined using the Fuzzy Analytic Hierarchy Process (FAHP). Based on the qualitative findings and expert validation, 11 key factors were finalized: sustainable justice, youth orientation in the Second Step Statement, high transformational spirit, elite circulation, youth dynamism and propulsion, managerial dashboard development, positive image building, meritocracy, belief and self-efficacy, initiation of a new era, and utilization of new capacities. These factors were compared pairwise using a fuzzy nine-point scale questionnaire.The results of the consistency analysis indicated that the fuzzy pairwise comparisons were reliable, as the inconsistency ratios were below the acceptable threshold of 0.1. Final weights were calculated through fuzzy synthesis and normalization procedures. The ranking results revealed that sustainable justice had the highest priority, followed by youth orientation in the Second Step Statement and transformational spirit. Factors such as elite circulation and youth dynamism ranked next, while utilization of new capacities received the lowest priority. Overall, the findings provide a structured and prioritized framework for understanding and promoting youth-oriented management in the public sector. Discussion and ConclusionThis study aimed to develop a comprehensive model for youth-oriented management in the public sector by identifying and prioritizing its key components through a mixed-methods approach. The findings highlight that youth-oriented management is a multidimensional concept that extends beyond the mere appointment of young individuals to managerial positions and instead requires structural, cultural, and strategic transformations within public organizations. The qualitative phase revealed 11 core factors that collectively shape the foundation of youth-oriented management, reflecting both individual and organizational dimensions.The quantitative results, obtained through the Fuzzy Analytic Hierarchy Process, demonstrated that sustainable justice is the most influential factor, emphasizing the importance of fairness, equal opportunities, and non-discriminatory practices in empowering young managers. Youth orientation in the Second Step Statement and a high transformational spirit were also ranked as top priorities, indicating the critical role of value-based leadership, long-term vision, and adaptive capacity in fostering effective youth participation in governance. Additionally, factors such as elite circulation and youth dynamism underscore the need for continuous renewal, innovation, and mobility within managerial systems.From a practical perspective, the proposed model offers a clear and actionable framework for policymakers and senior managers seeking to institutionalize youth-oriented management in public sector organizations. By focusing on justice, meritocracy, capacity building, and positive image creation, organizations can better harness the potential of young professionals. Overall, this research contributes to the literature by providing an empirically grounded and prioritized model that supports sustainable development, organizational renewal, and the long-term effectiveness of public sector management through meaningful youth engagement.
Modeling
Farhad Najafi Esfahani; Mohammadreza Mohammady; Mandan Momeni
Abstract
IntroductionThe convergence of digital transformation and urban governance is a critical imperative for contemporary metropolitan management, especially in developing economies aiming to enhance service efficiency and citizen satisfaction. Smart cities signify a paradigm shift from traditional management ...
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IntroductionThe convergence of digital transformation and urban governance is a critical imperative for contemporary metropolitan management, especially in developing economies aiming to enhance service efficiency and citizen satisfaction. Smart cities signify a paradigm shift from traditional management to data-driven, technology-enabled governance, leveraging digital infrastructure to optimize resource allocation and foster sustainable development. However, transitioning to such ecosystems requires a comprehensive architectural framework that integrates technical infrastructure, governance mechanisms, and value-creation processes.Digital Government Architecture (DGA) serves as the foundational blueprint for this transition. Despite growing global interest in smart city initiatives, a significant gap persists in understanding how DGA components interact within specific institutional and cultural contexts—particularly in Middle Eastern megacities like Tehran, where traditional governance structures coexist with rapid technological adoption.Existing literature frequently prioritizes technological dimensions (IoT, big data, cloud computing) while overlooking the governance and value-creation aspects essential for implementation. Furthermore, most conceptual models are derived from Western contexts, often failing to account for the unique regulatory and social landscapes of developing nations. This research addresses these gaps by developing a context-sensitive, Structural-Interpretive Model that explicates the hierarchical relationships and causal pathways of DGA components within the Tehran Municipality. This study moves beyond technology-centric approaches to offer a holistic perspective, providing actionable insights for policymakers and administrators through a causally structured hierarchy.MethodologyThis study adopts a pragmatic paradigm, utilizing a sequential mixed-methods design to analyze the complex socio-technical system of DGA.Phase 1: Qualitative ExplorationThe qualitative phase employed semi-structured interviews to elicit expert insights. Following an actor-protocol approach, 20 specialized managers and senior officials from key municipal divisions (e.g., IT, Urban Planning, Strategic Management) were purposively sampled. Theoretical saturation was achieved at the 20th interview. Transcripts were analyzed using Clarke’s (2006) reflexive thematic analysis in MAXQDA 2020. Inter-coder reliability was confirmed with a Cohen’s kappa of 0.82. The analysis identified 9 overarching themes, 27 organizing themes, and 68 basic themes, categorized into three meta-dimensions: Technical Infrastructure, Governance, and Value Creation.Phase 2: Structural ModelingTo transform qualitative findings into a causal hierarchy, Interpretive Structural Modeling (ISM) was employed. Fifteen senior municipal experts evaluated the pairwise directional influence of the 9 overarching themes using a four-point scale. The ISM procedure involved constructing a Structural Self-Interaction Matrix (SSIM), deriving a Final Reachability Matrix via Boolean logic, and partitioning elements into hierarchical levels based on driving power and dependence. The model was finalized using MATLAB and validated for content and construct coherence through expert review and theoretical alignment.FindingsThe integrated analysis yielded a four-level hierarchical structural model of DGA for smart urban services, revealing distinct causal layers from foundational drivers to ultimate outcomes.Level 4 (Foundational Drivers): Three themes emerged as the deepest structural elements with high driving power and low dependence, serving as the fundamental prerequisites for DGA implementation:1. Urban Digital Regulation: This theme encompasses the legal and regulatory frameworks governing data privacy, digital service standards, interoperability requirements, and accountability mechanisms. Findings indicate that absence of clear regulatory guidelines creates implementation paralysis, as municipal departments hesitate to launch digital services without legal certainty regarding data handling, citizen rights, and liability issues.2. Digital Transformation Governance: This theme captures the organizational structures, leadership commitment, strategic planning processes, and change management capabilities necessary for coordinating digital initiatives across municipal departments. Participants emphasized that fragmented governance—where each department pursues independent digital projects without coordination—leads to duplicated efforts, incompatible systems, and poor citizen experience.3. Urban Digital Technology Architecture: This theme represents the technical infrastructure foundation, including cloud computing platforms, data centers, network connectivity, cybersecurity systems, and integration middleware. Interviewees highlighted that inadequate technical architecture creates bottlenecks that prevent scaling of digital services and integration of data across municipal functions.These foundational drivers exhibit strong causal influence on all higher-level components but are themselves relatively independent of other factors, indicating they must be established early in DGA development and require sustained investment and policy attention.Level 3 (Enabling Mechanisms): Two themes function as critical linkage factors that translate foundational drivers into operational capabilities:1. Digital Participation and Citizen Interaction: This theme encompasses digital channels for citizen engagement (mobile apps, web portals, social media), participatory decision-making platforms, feedback mechanisms, and co-creation processes. Analysis revealed that effective citizen interaction depends on both technical infrastructure (Level 4) and regulatory clarity regarding data use, while simultaneously enabling improved service delivery (Level 2).2. Digital Security and Urban Protection: This theme addresses cybersecurity measures, data protection protocols, system resilience, and privacy safeguards. Participants identified security as a dual concern—both a technical requirement dependent on infrastructure quality and a governance issue requiring clear policies—that directly impacts citizen trust and service adoption rates.These enabling mechanisms exhibit moderate driving power and moderate dependence, serving as bridges between foundational elements and operational outcomes. Their intermediate position indicates they require simultaneous attention to both infrastructure development and service delivery optimization.Level 2 (Operational Outcomes): Two themes represent the direct service delivery results that citizens experience:1. Ease and Speed of Service Delivery: This theme captures service accessibility, transaction simplicity, processing time reduction, and multi-channel availability. Quantitative data from municipal records indicated that digital service implementation reduced average transaction times by 60-75% compared to traditional in-person processes, while citizen satisfaction scores increased by 40% for digitally-delivered services.2. Digital Urban Data Management*: This theme encompasses data collection, storage, analysis, and utilization for decision-making and service personalization. Participants noted that effective data management enables predictive service delivery, proactive problem identification, and evidence-based policy formulation.These operational outcomes exhibit low driving power but high dependence, indicating they result from effective implementation of lower-level components rather than driving further changes themselves.Level 1 (Ultimate Goals): Two themes emerged as the highest-level outcomes representing the ultimate objectives of DGA implementation:1. Sustainability and Continuous Improvement of Urban Services: This theme reflects long-term service quality enhancement, resource efficiency, environmental sustainability, and adaptive capacity. Participants emphasized that digital systems enable continuous monitoring and iterative improvement cycles that were impossible with traditional manual processes.2. Integrated Smart Urban Services Ecosystem: This theme represents the holistic integration of services across municipal functions, creating seamless citizen experiences and optimized resource allocation through data sharing and process coordination.These ultimate goals exhibit very low driving power and very high dependence, confirming their position as end-state outcomes that depend on successful implementation of all lower-level components.Cross-cutting Findings: Several important patterns emerged across the hierarchical structure. First, governance factors (regulation, organizational structures) proved equally important as technical infrastructure, contradicting technology-centric approaches that prioritize hardware and software over institutional arrangements. Second, citizen engagement emerged as a critical mediating factor rather than a final outcome, suggesting that participatory mechanisms must be built into DGA design rather than added after technical implementation. Third, security and privacy concerns pervade all levels, requiring integrated attention rather than treatment as isolated technical issues.Discussion and ConclusionThis research advances the discourse on Digital Government Architecture (DGA) by moving beyond technology-deterministic models. It establishes that governance and value-creation dimensions are as critical as technical infrastructure, offering a nuanced hierarchical structure that captures complex causal pathways and feedback loops-an improvement over traditional, linear taxonomies.The findings demonstrate that Urban Digital Regulation, Digital Transformation Governance, and Urban Digital Technology Architecture act as foundational drivers. Their identification explains the failure of many smart city initiatives that prioritize visible applications over underlying frameworks. Furthermore, the role of Digital Participation and Digital Security as intermediate “linkage factors” indicates that these elements must be developed concurrently with both foundational and operational components. Practically, the study offers a strategic roadmap for Tehran Municipality: prioritizing regulatory and governance reforms is a prerequisite for the successful implementation of citizen-engagement platforms and data-driven management.The study identifies three key drivers of DGA implementation: (1) Leadership commitment, essential for overcoming organizational inertia; (2) Interoperability standards, which prevent data fragmentation; and (3) Citizen trust, generated through transparency and reliable service delivery, which remains the ultimate determinant of value realization.While this model offers significant insights, its focus on Tehran limits its immediate generalizability to vastly different institutional environments. Additionally, the cross-sectional design captures a static snapshot of a dynamic transformation process. Future research should prioritize: (1) large-scale quantitative validation of the structural model, (2) comparative studies across diverse metropolitan contexts to isolate universal patterns, and (3) the integration of citizen-centric perspectives to complement the current expert-driven framework.Successful DGA for smart urban services requires a holistic integration of technical, governance, and value-creation dimensions. For Tehran and similar megacities, this research provides a diagnostic tool to assess architectural maturity and a prescriptive framework to prioritize investments. By establishing foundational drivers-regulation, governance, and infrastructure-before pursuing operational outcomes, municipal administrators can better navigate the transition toward truly smart, citizen-centered urban governance.
