Knowledge Economy Studies

Abstract Organizations are rapidly adopting Generative Artificial Intelligence (GenAI) for significant productivity gains, yet they are often not ready for its serious negative impacts on the workforce. This creates a major challenge for management. There is a significant research gap regarding the paradoxical effect of GenAI, where technological advancement undermines the employee psychological safety. This study directly addressed this gap by investigating the overall effect of this dual impact on employee engagement. A mixed-methods design was employed, combining a PRISMA-compliant systematic review of 27 articles with the Best-Worst Method applied to the judgments of eight organizational experts. Findings revealed a clear contrast. While knowledge management, dynamic content generation, and workflow automation were confirmed as positive drivers of job engagement, their benefits were significantly offset by specific risks. Ethical concerns, privacy breaches, and widespread distrust emerged as significant negative factors that substantially weaken engagement, resulting in technostress, cognitive overload, and job insecurity. Based on these findings, we proposed a conceptual-empirical framework for human-centered GenAI integration. The study concluded that without implementing robust data governance and specific measures to manage technostress, the potential of GenAI will not be realized, leading to widespread and persistent employee disengagement.

Abstract Iranian knowledge-based firms operate under institutional and resource constraints that may limit their ability to translate digital capabilities into performance gains. This study aimed to explain the effect of digital leadership and organizational artificial intelligence (AI) usage intensity on the relative performance of Iranian knowledge-based firms, with an emphasis on the mediating role of business model innovation. Digital leadership was conceptualized as a second-order construct comprising innovative and supportive dimensions. Business model innovation was examined as a mechanism through which managerial and technological effects are transmitted to relative performance. In terms of purpose, this study was applied, and in terms of method, it followed a descriptive-survey design. Cross-sectional data were collected through using a structured questionnaire, and after data screening, 264 valid questionnaires were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicated that digital leadership had a positive and significant effect on organizational AI usage intensity, business model innovation, and relative performance. In addition, organizational AI usage intensity had a significant effect on business model innovation but no significant direct effect on relative performance, suggesting that its performance value may be realized primarily through business model innovation. Consistent with this interpretation, the business model innovation showed the strongest direct effect on relative performance and significantly mediated the main relationships. The findings suggested that managers of knowledge-based firms should integrate organizational AI usage with digital leadership and business model innovation, while policymakers should support capability-building initiatives that enable firms to convert AI use into firm-level value and performance gains.

Abstract In recent years, digital technologies have transformed people’s lifestyles and the way businesses operate. These changes have become increasingly evident in various industries, including the apparel industry, especially after the emergence of the Fourth Industrial Revolution. The apparel industry, which has traditionally relied on physical supply chains, traditional design, and face-to-face sales, is now being influenced by drivers of digital transformation such as emerging technologies, organizational restructuring, data analytics, artificial intelligence, digital platforms, and smart design and manufacturing technologies. In such circumstances, companies operating in this industry are forced to redesign their business models, processes, and structures in accordance with the requirements of the digital age in order to remain competitive. Accordingly, digital transformation has become an inevitable necessity for apparel industry players. One of the most important steps in this direction is to extract and integrate the drivers of digital transformation implementation and present them in a five-dimensional framework including strategic, organizational, environmental, operational, and competitive drivers. Using the meta-synthesis method, this study organized the scattered literature on digital transformation into a coherent framework with 139 codes, 25 concepts, and 5 categories, and by calculating the presence of each code in the selected studies, it determined the level of support between studies and the relative consensus of the literature on the drivers. Operational drivers with technology and infrastructure concepts, organizational drivers with diverse concepts at the organization level, and competitive drivers with customer, market, and sales channels concepts had the most scientific support.

Abstract Metaverse, by providing interactive virtual environments, is redefining and creating new spaces for attracting, training, evaluating, and shaping employee experiences in Human Resource Management (HRM). Accordingly, the present study provided a structured review of the emerging literature on HRM in the context of Metaverse and its related technologies. To this end, the study was designed as a systematic search-based review with qualitative content analysis. Relevant studies were identified through searches in Scopus and Web of Science, while SpringerLink and ScienceDirect were additionally consulted. Retrieved studies were screened and selected for final analysis. Data were examined using qualitative content analysis, complemented by descriptive indicators to depict the prevailing trends. Findings indicated that metaverse entails significant implications for HRM across three dimensions of technical, human, and organizational. From a technical perspective, technologies such as Artificial Intelligence (AI), Blockchain, and Digital Twins have contributed to optimizing certain HR processes, while challenges related to cybersecurity and protection of organizational knowledge remain salient. From a human perspective, the literature revealed a duality between increased productivity and the emergence of negative psychosocial outcomes for employees including technostress and digital fatigue. At the organizational level, Metaverse has prompted a rethinking of HR strategies and business models. However, it is accompanied by challenges such as resistance to change and lack of coherent evaluation frameworks. The content analysis showed that the dominant focus of research has been on technical and economic dimensions, with comparatively limited attention to social, ethical, and cultural aspects—reflecting conceptual reductionism. Moreover, several research gaps were identified, including a lack of long-term empirical studies, insufficient consideration of contextual and cultural differences, and the absence of novel organizational models. By presenting an initial conceptual overview of the emerging literature on HRM in Metaverse, this study proposed directions for future research in this field.

Abstract Digital transformation and the development of smart cities have provided significant potential for enhancing the quality of life and improving the delivery of public services. However, in the absence of inclusive approaches, smart technologies may inadvertently lead to the reproduction of inequalities and the creation of new forms of digital exclusion. Mothers of children with disabilities constitute a particularly vulnerable group regarding these challenges, as they encounter multi-layered environmental, socio-economic, and technological barriers in accessing urban services and participating in social life. This study aimed at elucidating the role of smart governance in promoting the citizenship rights of this group. It has been conducted using a descriptive-analytical method through the thematic analysis of upstream documents, disability rights legislation, and interdisciplinary literature in the fields of smart cities, digital justice, and responsible artificial intelligence (AI). The research findings indicated that the realization of inclusive smart governance requires the establishment of four fundamental pillars: accessible digital infrastructure, data-driven decision-making, an appropriate legal-ethical framework for responsible AI, and the digital-economic empowerment of citizens. While identifying key obstacles such as algorithmic bias, the digital divide, privacy concerns, and institutional resistance, this study demonstrated the necessity of transitioning from “passive support” to “active empowerment”. Finally, a “smart and inclusive governance” policy model was presented, in which technology is redefined as a tool for social justice, individual autonomy, and active citizen participation. By bridging the discourse of the smart city with the social model of disability, this model provides a conceptual framework for urban policymakers, public institutions, and digital service designers to advance urban justice and sustainable development.

Abstract The convergence of Blockchain, the Internet of Things (IoT), and artificial intelligence (AI) is widely regarded as transformative for advancing the Sustainable Development Goals (SDGs) and reshaping responsible investment. Yet, the literature remains profoundly fragmented across technological, sustainability, and financial dimensions. This study addressed this gap through conducting a rigorous qualitative meta synthesis of 33 peer reviewed studies published between 2021 and 2026, deliberately prioritizing interpretive depth and thematic integration over Qualitative Meta-Synthesis quantification to extract causal mechanisms and contextual contingencies. Anchored in the Resource-Based View (RBV), Dynamic Capabilities Theory, Institutional Theory, Stakeholder Theory, Information Asymmetry Theory, and Socio-Technical Systems Theory, our analysis delineated eight interconnected thematic categories and identified three core causal pathways: (1) transparency and trust infrastructures, (2) real-time sensing and operational optimization, and (3) predictive and prescriptive intelligence. Critically, the synthesis uncovered four persistent paradoxes including the energy throughput trade off, transparency obfuscation dynamics, governance accountability voids, and digital divide exclusion tensions that collectively qualified the prevailing technology optimism narratives and positioned digital technologies as conditional enablers rather than panaceas. Building upon these insights, we advanced the Digital Integrated Mechanisms for Transformation (DIMT) Framework, positing that sustainability outcomes are not technologically determined but critically contingent upon data maturity, regulatory coherence, stakeholder literacy, and institutional readiness. Empirical evidence further revealed that synergistic integration of all three technologies remains empirically scarce, comprising merely 2.7% of the corpus, marking a paramount frontier for future inquiry. This review consolidated the fragmented knowledge, explicated the implementation paradoxes, and offered actionable guidance for policymakers, investors, and organizational strategists, underscoring that effective digital transformation for sustainability demands systemic integration, context sensitive governance, and calibrated implementation strategies.