Search Results (136)

In the context of global decarbonization and digital transformation, this study investigates whether and how the adoption of artificial intelligence (AI) promotes corporate energy transition, as measured by firms’ total energy consumption, energy intensity, and carbon emission intensity. Drawing on the theories of general-purpose technology (GPT), the resource-based view (RBV), and dynamic capabilities, the paper conceptualizes AI as a production-embedded technological capability that enhances intelligent automation, energy monitoring, and resource coordination within firms. Using panel data on Chinese A-share listed firms from 2012 to 2024, and capturing AI adoption through observable changes in firms’ production-related capital intensity, the analysis employs firm- and year-fixed effects, instrumental variables, and a dynamic event-study design to address endogeneity and temporal dynamics. The results show that AI adoption reduces firms’ energy consumption by approximately 2.0%, energy intensity by 1.8%, and carbon emission intensity by 2.3% within two to three years after adoption. Mechanism tests indicate that green innovation, operational efficiency, and resource allocation efficiency mediate this effect. Heterogeneity analyses reveal more substantial effects among non-state, large-scale, and technology-intensive firms operating in highly marketized regions. The findings broaden understanding of AI as a strategic sustainability technology and provide actionable implications for policymakers to align digital and energy governance to achieve carbon neutrality goals. Full article

Artificial Intelligence (AI) will drastically change the way entrepreneurs operate within their respective fields toward sustainable performance. However, although we have some data about how companies will adopt AI and how it is implemented, it is still an under-studied area of research. The goal of this study was to examine the antecedents and consequences of AI Adoption using the Technology–Organization–Environment (TOE) model and Unified Theory of Acceptance and Use of Technology (UTAUT). The researchers collected data from 207 entrepreneurial businesses (including SMEs, startups, and knowledge-based businesses) using a structured questionnaire and analyzed the data using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3. The study’s findings suggest that facilitating conditions, social influences, and competitive pressures are all important positive factors contributing to the firm’s decision on AI Adoption. On the other hand, the data indicate that performance expectancy is a negative factor related to the company’s decision to adopt because of the “reality check” influence of the initial implementation challenges diminishing ease of use. It is also important to mention that several internal factors including effort expectancy and top management support do not have a direct influence. Most importantly, however, the results show that AI Adoption provides companies with an opportunity for strategic renewal (opportunities) and sustainable business models (holistic sustainability). Also, this research provides insight into the Resource-Based View (RBV) and Dynamic Capabilities (DC) theory by showing that AI Adoption creates a significant competitive advantage for companies, making them more successful at creating entrepreneurial and technology-based firms, while providing them increased economic, environmental, and social performance. In conclusion, AI Adoption is a major game-changer for entrepreneurs interested in sustainable practices and the ability to achieve successful, holistic, and sustainable business performance. Full article

The shift toward a circular economy (CE) holds a central position in solving, globally, the long-standing environmental degradation and resource scarcity. Innovative sustainable processes and products lie at the core of such a shift, but they often face challenges associated with technological, organizational, financial, and regulatory paradigms. To date, two leading facilitators have been identified: sophisticated digital technologies, such as Artificial Intelligence, the Internet of Things, and Big Data, together with the collaborative creation of value among diverse stakeholders. Although the implications of each of these enablers on sustainability are known to some extent, little is understood about how their interrelatedness can counteract implementation barriers and drive innovation. The systematic thematic literature review examines how organizations utilize digital technologies and stakeholder engagement to facilitate green innovation in Circular Economy (CE) systems. Based on Stakeholder Theory, the Technology-Organization-Environment (TOE) framework, and the Resource-Based View (RBV), this review examines how organizations leverage digital technologies and stakeholder engagement to foster green innovation within circular economy systems. Following the PRISMA 2020 guidelines, a structured search was conducted in Scopus and Web of Science, covering peer-reviewed journal articles published in English between 2013 and 2024. Using predefined inclusion and exclusion criteria, 84 studies were retained for analysis from an initial pool of 850 records. The review integrates findings from five thematic areas: collaborative innovation among stakeholders, the use of digital technology to advance sustainability, challenges associated with adopting circular-economy values, linkages between technology and stakeholders, and the consequences of innovation. The findings suggest that collaboration between diverse stakeholders, combined with integration with digital technologies, provides a synergistic approach to maximizing innovation outcomes, overcoming implementation challenges, and diffusing circular practice. Skillfully crafted initiatives augment organizational capacities, foster collaborative actions, and advance sustainability initiatives. Despite providing a comprehensive synthesis of existing research, this review is limited by its reliance on secondary data. A qualitative quality appraisal was conducted to support the interpretation of findings. This review was not registered and received no external funding. Future research should conduct empirical analyses of these relationships and develop inclusive frameworks to guide initiatives emerging from collaborative and digital platforms across a wide range of sectors within the circular economy. Full article

This study formulates and verifies a network-based evaluation methodology for appraising the sustainable competitiveness of community enterprises. Based on Social Capital Theory, the Resource-Based View (RBV), and Network Theory, the model defines high-quality networks as structural relational circumstances that facilitate resource sharing and knowledge sharing, serving as mediating mechanisms that improve competitive outcomes. A quantitative study approach was utilized, gathering survey data from 451 representatives of community enterprises around Thailand, and Structural Equation Modeling (SEM) was applied to assess both measurement features and structural relationships. The model demonstrates satisfactory internal reliability, convergent validity, and discriminant validity, affirming measurement adequacy. Empirical evidence indicates that high-quality networks are positively correlated with sustainable competitiveness, both directly and indirectly, with 49.2% of the overall effect conveyed through resource and knowledge exchange, emphasizing the practical value of network-based processes. The suggested model offers practical utility for policymakers and development agencies in search of evidence-based instruments to enhance competitiveness, network capacity, and long-term resilience in community enterprises. The cross-sectional methodology and lack of contextual control variables restrict causal inference and external generalizability, highlighting the necessity for longitudinal or quasi-experimental expansions. By emphasizing model creation and empirical validation, this study develops a systematic and reproducible methodological framework for assessment. Full article

Integrated control systems (Supervisory Control and Data Acquisition–SCADA and Manufacturing Execution Systems—MES) constitute the backbone of Industry 4.0; however, research on their implementation remains scarce. This study analyzes the opportunities and challenges of modernizing these systems within the context of the Brazilian industry. A survey of 101 experts was conducted, with results analyzed via Friedman and Holm–Sidak nonparametric tests to establish a clear hierarchy of factors. Findings reveal that while economic efficiency, productivity gains, and real-time remote access represent the most significant opportunities, they are countered by critical structural challenges: obsolete machinery and inadequate infrastructure. These challenges significantly inflate implementation costs and highlight the reality of technological obsolescence that is typical of emerging economies. By applying the Resource-Based View (RBV), this research frames digital integration as a strategic competitive capability rather than a mere technical upgrade. Practically, the study provides a roadmap for industrial leaders to balance digital agility expectations with pragmatic operational constraints. These insights offer a foundation for successful digital transformation, delivering actionable value for academics, industrial managers, and policymakers. Full article

In the era of digital transformation, organizations increasingly invest in Artificial Intelligence (AI) to enhance competitiveness, yet persistent evidence shows that AI investment does not automatically translate into superior firm performance. Drawing on the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), this study aims to explain this paradox by examining how AI-enabled dynamic capability (AIDC) is converted into performance outcomes through organizational mechanisms. Specifically, the study investigates the mediating roles of organizational data-driven culture (DDC) and organizational learning (OL). Data were collected from 254 senior managers and executives in U.S. firms actively employing AI technologies and analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that AIDC exerts a significant direct effect on firm performance as well as indirect effects through both DDC and OL. Serial mediation analysis reveals that AIDC enhances performance by first fostering a data-driven mindset and subsequently institutionalizing learning processes that translate AI-generated insights into actionable organizational routines. Moreover, DDC plays a contingent moderating role in the AIDC–performance relationship, revealing a nonlinear effect whereby excessive reliance on data weakens the marginal performance benefits of AIDC. Taken together, these findings demonstrate the dual role of data-driven culture: while DDC functions as an enabling mediator that facilitates AI value creation, beyond a threshold it constrains dynamic reconfiguration by limiting managerial discretion and strategic flexibility. This insight exposes the “dark side” of data-driven culture and extends the RBV and DCT by introducing a boundary condition to the performance effects of AI-enabled capabilities. From a managerial perspective, the study highlights the importance of balancing analytical discipline with adaptive learning to sustain digital efficiency and strategic agility. Full article

Critical mineral supply chains underpin electric mobility, power electronics, clean hydrogen, and advanced manufacturing. Drawing on the resource-based view (RBV), the relational view, and dynamic capabilities, we conceptualize advantage not as ownership of ore bodies but as orchestration of multi-tier resource systems: upstream access, midstream processing know-how, standards and permits, and durable inter-organizational ties. In a world of high concentration at key stages (refining, separation, engineered materials), full “decoupling” is economically costly and technologically constraining. We argue for structured cooperation among the United States, European Union, China, and other producers and consumers, combined with selective domestic capability building for bona fide security needs. Methodologically, we conduct a structured conceptual synthesis integrating RBV, relational view, dynamic capabilities, and network-of-network research, combined with a structured comparative policy analysis of U.S./EU/Chinese instruments anchored in official documents. We operationalize the argument via technology–material dependency maps that identify midstream bottlenecks and the policy/standard levers most likely to expand qualified, compliant capacity. Full article

This study investigates the impact of Governance, Risk management, and Compliance (GRC) practices on operational efficiency and corporate reputation. Drawing on the Resource-Based View (RBV), Stakeholder Theory, and the signaling perspective, it conceptualizes GRC as a set of organizational capabilities that enhance operational efficiency and company reputation. It also examines the mediating role of operational efficiency in the GRC–reputation relationship, particularly within technologically advanced and regulated sectors. Data were collected through a structured questionnaire distributed to 126 professionals across various Saudi technology-driven organizations, and the analyses combined descriptive statistics, hierarchical regression, and bootstrapped mediation testing using PROCESS to assess direct and indirect effects. The results indicate that operational efficiency partially mediates the effects of governance and compliance on reputation, supporting the argument that strengthened internal processes enhance external stakeholder evaluations; meanwhile, no mediation was found for risk management. Although the study offers meaningful insights, its sample size and sectoral focus limit the generalizability of conclusions, suggesting the need for broader or longitudinal research. This study contributes by advancing the conceptualization of GRC as organizational capabilities and empirically demonstrating their roles in strengthening both efficiency and reputation within technology-driven firms where digital governance and compliance capabilities are increasingly central. Full article

This paper introduces flourishing circularity as a transformative approach to resource assessment that transcends both traditional Resource-Based View (RBV) theory and conventional circular economy concepts. We demonstrate RBV’s fundamental limitations in addressing the polycrisis of breached planetary boundaries and social inequities. Similarly, while the circular economy focuses on resource reuse and recycling, it often merely delays environmental degradation rather than reversing it. Flourishing circularity addresses these shortcomings by reconceptualizing natural and social capital not as externalities but as foundational sources of all value creation. We develop a comprehensive framework for assessing resources within an open systems perspective, where competitive advantage increasingly derives from a firm’s ability to regenerate the systems upon which all business depends. The paper introduces novel assessment tools that capture the dynamic interplay between organizational activities and coevolving social and ecological systems. We outline the core competencies required for flourishing circularity: regenerative approaches to social and natural capital, and systems thinking with cross-boundary collaboration capabilities. These competencies translate into competitive advantage as stakeholders increasingly favor organizations that enhance system health. The framework provides practical guidance for transforming resource assessment from extraction to regeneration, enabling business models that create value through system enhancement rather than depletion. Full article

This study examines how digital transformational leadership (DTL) drives superior and enduring organizational performance through the mediating roles of organizational agility (OA) and digital transformation (DT) while assessing the contingent moderating role of digital culture (DC). Anchored in the Resource-Based View (RBV), the study conceptualizes DTL as a strategic intangible capability that enables the orchestration of digital and agile resources into sustained performance outcomes in digitally turbulent environments. Data were collected from 284 senior and middle managers across 13 Palestinian commercial banks—a highly regulated sector undergoing intensive digital pressure in an emerging-economy context—using an online survey. The proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The results reveal that DTL significantly enhances both OA and DT, which in turn contribute positively to organizational performance. OA and DT operate as both independent and sequential mediators, uncovering a multistage capability-building pathway through which leadership fosters long-term adaptability and resilience. The findings further indicate that digital culture conditions the effectiveness of leadership-driven transformation, shaping how digital initiatives consolidate into enduring organizational routines rather than short-term efficiency gains. By reframing sustainable transformation as the continuity of organizational performance through agility, digital renewal, and cultural alignment—rather than as an ESG outcome alone—this study refines RBV boundary conditions in digital contexts. The study contributes theoretically by clarifying how leadership-enabled capabilities generate sustainable competitive advantage and offers actionable managerial insights for cultivating agility, embedding digital transformation, and strengthening cultural readiness to support long-term organizational resilience. Full article

The accelerating global transition toward low-carbon production and sustainable value chains has intensified interest in practices that enhance environmental performance, particularly green supply chain management (GSCM) and green innovation (GI). Although these practices are widely promoted, empirical findings regarding how GSCM influences GI and carbon-neutral supply chain performance (CNSCP) remain dispersed and context-dependent. This study aims to synthesize and clarify these relationships by conducting a systematic meta-analysis grounded in the Resource-Based View (RBV) and Natural Resource-Based View (NRBV). Analyzing 24 studies published between 2017 and 2025, the research investigates the direct effects of GSCM on GI and CNSCP and examines the moderating roles of key sustainability metrics—CO₂ emissions, renewable energy use, carbon tax, Frontier Technologies Index (FTI), and Global Sustainable Competitiveness Index (GSCI)—across low- and high-income countries. The findings reveal that GSCM significantly enhances both GI and CNSCP. Furthermore, strong sustainability infrastructures and stringent regulatory environments in high-income countries amplify these relationships, whereas infrastructure deficiencies and weaker regulatory systems in low-income countries limit their strength. These results demonstrate that sustainability metrics meaningfully condition the effectiveness of GSCM practices. Overall, this study highlights the strategic importance of GSCM in fostering CNSCP and provides theoretical insights and practical recommendations for policymakers, managers, and governments seeking to achieve long-term carbon neutrality goals. Full article

This study investigates the barriers in adopting the Circular Economy (CE) in Saudi Banking under Vision 2030 and using the Resource-Based View and stakeholder theory. This study examined how customer engagement, process innovation, and dynamic capabilities limit the implementation of CE. A quantitative, cross-sectional survey collected 418 responses from bank employees in Riyadh and was collected from January to March 2024. A 29-item Likert scale was analyzed with SmartPLS 4; measurement quality was strong, and confirmatory factor analysis confirmed construct validity. Results highlight the main barriers as customer resistance regulatory constraints and lack of adequate employee training. The construct is highly interconnected (r = 0.758), showing that improvements in customer engagement and process innovation strengthen dynamic capabilities. The study provides practical guidance for banks and policymakers on designing circular finance products, targeted training, and supportive regulations to accelerate the CE transition and achieve measurable sustainability outcomes in financial sectors, aligning with SDG 3, good health and well-being, and SDG 7, affordable and clean energy. Full article

Background: The extraordinary disturbances faced by the hotel industry, ranging from worldwide health problems to political instability and climate change, have highlighted the insistent need for more resilient and agile supply chain (SC) systems. This study explored how artificial intelligence (AI) capabilities can generate competitive advantage (CA) through supply chain agility (SCA) and supply chain resilience (SCR) as mediators and competitive pressure (CP) as a moderator. Methods: Drawing on the resource-based view (RBV) framework, we suggested and empirically tested the study model. Using data collected from 432 hotel managers and analyzed using Partial Least Squares Structural Equation Modelling (SEM-PLS). Results: the results reveal that AI-driven SC can significantly strengthen SCA and SCR. Furthermore, SCA and SCR can act as powerful mediators, and CP can strengthen the tested relationships (the links from AI adoption and CA) as a moderator. Conclusions: The study made several theoretical and practical contributions by integrating AI capabilities into SCR and SCA frameworks in the hotel and tourism context, and by providing practical evidence for professionals aiming to leverage AI-driven SC tools to navigate uncertainty and create sustainable CA. Full article

The global shift toward a Circular Economy (CE) presents both significant challenges and opportunities for small and medium-sized enterprises (SMEs) in the logistics sector of emerging economies. This study aims to empirically identify and analyze the key drivers and barriers to the adoption of CE practices among logistics SMEs in Vietnam. Drawing on an integrated theoretical framework that combines the Technology—Organization—Environment (TOE) framework, the Resource-Based View (RBV), and Institutional Theory, a questionnaire survey was conducted with a sample of 160 logistics SMEs. Data were analyzed using multiple linear regression to test the proposed hypotheses. The findings reveal that external environmental factors exert the strongest influence, with supply chain partner support (β = 0.355) and competitive pressure (β = 0.331) emerging as the most significant predictors. Leadership commitment (β = 0.237) and regulatory pressure (β = 0.164) also have positive and statistically significant effects. Notably, the study found no significant impact from internal factors such as financial capacity or cognitive factors, suggesting that ecosystem pressures may play a dominant role for SMEs. Based on the findings, the paper offers valuable practical implications for both managers and policymakers. Full article

Although Generative Artificial Intelligence (GenAI) is one of the strategic choices for digital transformation in small and medium-sized enterprises (SMEs), its adoption remains constrained by leadership decision-making that must balance strategic aspirations with resource limitations and organizational inertia. Organizational leadership must face the dynamic and complex characteristics of digital transformation in the knowledge era. Drawing on Complexity Theory and integrating the Technology Acceptance Model (TAM), Temporal Motivation Theory (TMT), and the Resource-Based View (RBV), this study proposes a conceptual framework reflecting distinct strategic leadership orientations. Following a qualitative approach based on semi-structured interviews with SME leaders and an Interpretative Phenomenological Analysis (IPA) this conceptual framework contributes by reframing GenAI adoption as a complex, nonlinear process rather than a straightforward diffusion model, that includes four strategic profiles (Strategic Adopters, Aspiring Adopters, Opportunistic Adopters, and Operational Stabilizers) that affect a dynamic relationship between three key adoption dimensions: intention, motivation, and resource allocation. SME leaders can benefit from a delimitation of their strategic and operational goals while overcoming adoption barriers. Full article