Knowledge Economy Studies

Abstract Organizations are rapidly adopting Generative Artificial Intelligence 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 and a significant research gap: the paradoxical effect of generative Artificial intelligence, where technological advancement undermines employee psychological safety, has been insufficiently studied. This study directly addresses 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 reveal a clear contrast: while knowledge management, dynamic content generation, and workflow automation are confirmed as positive drivers of job engagement, their benefits are significantly offset by specific risks. Ethical concerns, privacy breaches, and widespread distrust emerge as significant negative factors that substantially weaken engagement, resulting in technostress, cognitive overload, and job insecurity. Based on these findings, we propose a conceptual-empirical framework for human-centered generative Artificial intelligence integration. The study concludes that without implementing robust data governance and specific measures to manage technostress, the potential of generative Artificial intelligence will not be realized, leading to widespread and persistent employee disengagement.

Abstract This study aims to explain the effect of digital leadership and organizational 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 is conceptualized as a second-order construct comprising innovative and supportive dimensions, and business model innovation is examined as a mechanism through which managerial and technological effects are transmitted to relative performance. In terms of purpose, this study is applied, and in terms of method, it follows a descriptive-survey design. Cross-sectional data were collected through a structured questionnaire, and after data screening, 264 valid questionnaires were analyzed using partial least squares structural equation modeling and SmartPLS 3 software. The significance of the relationships was assessed through bootstrapping with 5,000 subsamples. The findings indicate that digital leadership has a positive and significant effect on organizational AI usage intensity, business model innovation, and relative performance. In addition, organizational AI usage intensity has a significant effect on business model innovation; however, its direct effect on relative performance is not significant. Business model innovation shows the strongest direct effect on relative performance and plays a significant mediating role in the main relationships. The results suggest that improving the performance of knowledge-based firms requires digital leadership and the transformation of AI capabilities into business model innovation.

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 The 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 aims to offer an exploratory review of the emerging literature on HRM in the context of the metaverse and its related technologies. To this end, a systematic review strategy was employed. 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 prevailing trends. Findings indicate that the metaverse entails significant implications for HRM across three dimensions: technical, human, and organizational. From a technical perspective, technologies such as artificial intelligence, 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 reveals a duality between increased productivity and the emergence of negative psychosocial outcomes for employees, including technostress and digital fatigue. At the organizational level, the 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.Content analysis shows 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.

Abstract Digital transformation and the development of smart cities offer significant potential for enhancing quality of life and improving public service delivery; however, in the absence of inclusive approaches, these technologies may inadvertently perpetuate existing inequalities and generate new forms of digital exclusion. Mothers of children with disabilities constitute a particularly vulnerable group in this context, as they encounter multi-layered environmental, socio-economic, and technological barriers when accessing urban services and participating in social life.
This research aims to elucidate the role of smart governance in promoting the citizenship rights of this group. Employing a descriptive-analytical methodology, the study utilizes thematic analysis of upstream documents, disability rights legislation, and interdisciplinary literature concerning smart cities, digital justice, and responsible artificial intelligence.
The findings indicate that the realization of inclusive smart governance requires four fundamental pillars: accessible digital infrastructure, data-driven decision-making, a robust legal-ethical framework for responsible artificial intelligence, 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 demonstrates the necessity of transitioning from “passive support” to “active empowerment.”
Ultimately, a “smart and inclusive governance” policy model is presented, in which technology is redefined as a vehicle 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, equitable access, and sustainable development.

Abstract The convergence of blockchain, the Internet of Things (IoT), and artificial intelligence (AI) is widely heralded as transformative for advancing the Sustainable Development Goals (SDGs) and reshaping responsible investment, yet the literature remains profoundly fragmented across technological, sustainability, and financial silos. This study addresses this gap through 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, dynamic capabilities, institutional, stakeholder, information asymmetry, and socio technical systems theories, our analysis delineates eight interconnected thematic categories and three core causal pathways transparency and trust infrastructures, real time sensing with operational optimization, and predictive and prescriptive intelligence. Critically, the synthesis uncovers four persistent paradoxes the energy throughput trade off, transparency obfuscation dynamics, governance accountability voids, and digital divide exclusion tensions that collectively qualify prevailing technology optimism narratives and position digital technologies as conditional enablers rather than panaceas. Building upon these insights, we advance 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 reveals 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 consolidates fragmented knowledge, explicates implementation paradoxes, and offers actionable guidance for policymakers, investors.