Search Results (567)

As contemporary global supply chains have become interconnected and exposed to diverse escalating cyber threats, Cyber Supply Chain Risk Management (C-SCRM) has rapidly evolved as a managerial imperative to safeguard security, robustness, and resilience, and hence ensure organizational sustainability and growth. While the concept of C-SCRM has recently received much attention among scholars, practitioners, and policymakers as an emerging field of study, its conceptual utility and theoretical foundation remain undeveloped. To address this gap, this paper provides a systematic literature review of C-SCRM using a hybrid approach that integrates bibliometric and concept evaluation analysis to ensure the goodness of the concept. A total of 175 relevant peer-reviewed scholarly articles from the Web of Science (WOS) Core Collection were collected and analyzed. The review reveals that the concept has many strengths, in terms of its interdisciplinary conceptual foundation and growing managerial relevance, but it also suffers from conceptual diffusion, overlapping terminology, and limited construct operationalization that inhibits theory development, hinders empirical accumulation, and limits practitioners’ ability to operationalize C-SCRM as a strategic resource. This review contributes to the C-SCRM literature by providing (1) a historical overview and intellectual structure of C-SCRM; (2) a synthesis and comparative analysis of the existing definitions; (3) an evaluation of the conceptual adequacy and theoretical relevance that underpin C-SCRM research based on established criteria and (4) conceptual and empirical research directions as well as an integrative framework. Based on the insights, our review might facilitate the improvement of multidimensional construct clarity and validation in future empirical studies and could be a useful tool for managers to benchmark C-SCRM maturity in practice. Full article

The integration of electric vehicles into urban life is currently being implemented rapidly. However, the excessive integration of electric cars into urban environments creates several risks that impede their sustainable development. In this regard, it is relevant to systematize the integration processes of electric cars supported by smart city tools. This study proposes a methodology for the sustainable development ecosystem of smart cities, enabling the measurement of both positive and negative results from the integration of electric cars, which can inform rational managerial decisions. This study utilized scientific abstraction approaches to establish a management framework for integrating electric vehicles into the smart city ecosystem. Comparative analyses of the impact of counterbalancing factors were conducted, and based on this, methodological approaches for determining the boundaries of the use of electric vehicles in smart cities were proposed. Full article

The classic set covering problem (SCP) is an NP-hard binary integer optimization problem with diverse business and industrial applications. Its primary goal is to consolidate resources by selecting a minimal cost subset of columns in a matrix that covers all required rows. Traditionally, conflicts between selected resources were resolved after generating a solution, often adding managerial effort and inefficiency. Recently, two papers have tried to handle conflict constraints explicitly as part of the SCP solution generation process. This paper focuses on SCPs with soft conflict constraints (SCP-SCC), where violations are allowed but with penalties, and proposes a simple hybrid solution approach that combines a GRASP-based heuristic with Gurobi optimization. Using 360 test instances (160 from the literature and 200 new instances), this hybrid approach results in a 7.4% performance improvement over Gurobi, demonstrating the benefit of integrating heuristic and exact solution methods. In addition, classification tree analysis is applied as an attempt to identify problem features (such as conflict graph density and size) that can be used to predict when SCP-SCC instances will likely be difficult to solve to proven optimality efficiently using Gurobi. These insights provide practical guidance for operations research practitioners, enabling informed decisions among heuristic, exact, or hybrid solution approaches and improving efficiency in real-world applications. Full article

Against the backdrop of accelerating servitization transformation in the global manufacturing sector, how digital platform capability effectively drives improvements in innovation performance has become a critical issue. Existing research mainly focuses on the instrumental attributes of digital technologies, while relatively few studies examine their strategic role in servitization transformation, particularly the systematic explanation of the “capability–behavior–context–performance” transmission mechanism. To address this gap, this study integrates dynamic capability theory and the opportunity window theory to construct a moderated mediation model that uncovers the internal mechanisms and boundary conditions through which digital platform capability influences servitization innovation performance. Based on survey data from 237 manufacturing firms in Guangdong Province, the empirical results indicate that: (1) digital platform capability and value co-creation both exert significant positive effects on servitization innovation performance; (2) value co-creation mediates the relationship between digital platform capability and servitization innovation performance; and (3) although organizational distance was theoretically expected to function as an important contextual variable, this study does not find evidence supporting its inverted U-shaped moderating effect, suggesting that its role in digital contexts may be more complex. This study not only extends the application of dynamic capability theory and opportunity window theory in servitization innovation settings but also provides managerial insights for manufacturing firms to optimize digital platform strategies and build more resilient and sustainable innovation systems. Full article

This study examines how Artificial Intelligence (AI) is reshaping the role of university teachers and transforming the foundations of academic work in the digital age. Building on the Dynamic Capabilities Theory (sensing–seizing–transforming), the article proposes a theoretical reframing of university teachers’ perceptions of AI. This approach allows us to bridge micro-level emotions with meso-level HR policies and macro-level sustainability goals (SDGs 4, 8, and 9). The empirical foundation includes a survey of 453 Ukrainian university teachers (2023–2025) and statistics, supplemented by a bibliometric analysis of 26,425 Scopus-indexed documents. The results indicate that teachers do not anticipate a large-scale replacement by AI within the next five years. However, their fear of losing control over AI technologies is stronger than the fear of job displacement. This divergence, interpreted through the lens of dynamic capabilities, reveals weak sensing signals regarding professional replacement but stronger signals requiring managerial seizing and institutional transformation. The bibliometric analysis further demonstrates a theoretical evolution of the university teacher’s role: from a technological adopter (2021–2022) to a mediator of ethics and integrity (2023–2024), and, finally, to a designer and architect of AI-enhanced learning environments (2025). The study contributes to theory by extending the application of Dynamic Capabilities Theory to higher education governance and by demonstrating that teachers’ perceptions of AI serve as indicators of institutional resilience. Based on Dynamic Capabilities Theory, the managerial recommendations are divided into three levels: government, institutional, and scientific-didactic (academic). Full article

Artificial intelligence (AI), a transformative force, has revolutionised various aspects of human life and business operations. This has led to a drastic mutation of the career landscape, embedded with vast opportunities as well as challenges, particularly concerning career sustainability (CS). Despite myriad studies on CS, the paradoxical interplay of AI and CS remains underexplored, particularly for expatriates (expats). To address the aforementioned gap, our study incorporates an affordance perspective (AFP), positioning AI as an object and CS as a user context. Specifically, this study investigates whether AI facilitates the orchestration of an enhanced sustainable career within the boundary conditions of knowledge sharing (KS), encompassing both tacit and explicit knowledge pertinent to AI, cultivated through managerial initiatives and employee-driven activities. The study conducted a quantitative survey among 490 expats working in AI-integrated environments in China. The results reveal a curvilinear (U-shaped) relationship between AI and CS, where AI affordance at a moderate level enhances career adaptability and skill development. However, digital affordances become complex beyond a certain threshold, creating several career concerns, such as job insecurity and role ambiguity. Furthermore, the moderating effect of tacit and explicit KS mitigates numerous career disruptions while fostering long-term career growth. The study framed AI as both a tool and a collaborator that illuminates the importance of AI–human intelligence (AI–HI) synergy and knowledge augmentation in navigating digital transitions. Moreover, implications for international career development and human-oriented digital transformation are also discussed. Full article

The transition to renewable energy technologies is one of the most important ways to achieve the sustainable development goals (SDGs) of affordable and clean energy (SDG7); industry, innovation and infrastructure (SDG9); responsible production and consumption (SDG12); and climate action (SDG13). The widespread use of renewable energy technologies in developing countries will reduce dependence on imported fossil resources, increase industrial competitiveness, and support low-carbon development. Despite all their advantages, the integration of renewable energy technologies into industrial and domestic systems in developing countries remains slow due to a number of barriers. Financial constraints, technical and technological deficiencies, political restrictions and uncertainties, and organizational and managerial inadequacies are some of the barriers to the widespread adoption of renewable energy technologies. This study aims to identify, classify, and prioritize the barriers to the implementation of renewable energy technologies by applying multi-criteria decision-making methods in a fuzzy environment, with Türkiye considered as a case study. The relative importance of the barriers identified using the Single-Valued Spherical Fuzzy SWARA method was assessed, and their interconnections and significance were systematically demonstrated. The findings will contribute to the development of policy and management strategies aligned with global sustainability goals, thereby facilitating a more effective and equitable transition to clean and resilient energy systems. Full article

A Security Operation Center (SOC) is a security control center for monitoring, detecting, analyzing, and responding to cybersecurity threats. PT (Perseroan Terbatas) Non-Bank Financial Company (NBFC) has implemented an SOC to secure its information systems, but challenges remain to be solved. These include the absence of impact analysis on financial and regulatory requirements, cost, and effort estimation for recovery; established Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs) for monitoring security controls; and an official program for insider threats. This study evaluates SOC effectiveness at PT NBFC using the ISO 27005:2018 and NIST SP 800-30 frameworks. The research results in a proposed SOC assessment framework, integrating risk assessment, risk treatment, risk acceptance, and monitoring. Additionally, a maturity level assessment was conducted for ISO 27005:2018, NIST SP 800-30, and the proposed framework. The proposed framework achieves good maturity, with two domains meeting the target maturity value and one domain reaching level 4 (Managed and Measurable). By incorporating domains from both ISO 27005:2018 and NIST SP 800-30, the new framework offers a more comprehensive risk management approach, covering strategic, managerial, and technical aspects. Full article

This study utilizes data from Chinese listed small- and medium-sized enterprises (SMEs) from 2010 to 2023. Based on dynamic capability theory and behavioral theory, we examine how corporate digital transformation influences new quality productivity and analyze the mediating role of managerial ability. The results indicate that digital transformation significantly and positively impacts the development of new quality productivity in SMEs, with managerial ability exerting a mediating effect. Furthermore, industry technological turbulence, ESG ratings, and digital intellectual property protection amplify the promotional effect of digital transformation on new quality productivity. Additionally, digital transformation plays a crucial role in enhancing new quality productivity for enterprises operating in more competitive industries, high-tech enterprises, and specialized, refined, distinctive, and innovative (SRDI) enterprises. This study extends the digital transformation literature by integrating managerial ability as a key internal mechanism linking digitalization to new quality productivity within SMEs, offering evidence derived from a large-scale longitudinal dataset. Full article

In the context of environmental challenges and digital transformation, artificial intelligence (AI) plays a key role in promoting sustainable development within Industry 4.0 and the emerging paradigm of Industry 5.0. This study systematically reviewed the literature (2015–2025) from Scopus and Web of Science on the connections between AI, circular economy, industrial paradigms, and the Sustainable Development Goals (SDGs), with a particular focus on supply chains and SDG 12—responsible consumption and production. The majority of research emphasizes managerial aspects, the application of machine learning and robotics, as well as waste reduction, resource optimization, and circular economy practices within supply chain and production–consumption systems. Geographical analysis shows that larger economies serve as central research hubs, while some countries that are not among the most populous often achieve the highest average citations per document. Temporal keyword trends indicate a shift in research focus from operational efficiency in traditional supply chains (optimization) toward supply chain digitalization (artificial intelligence) and sustainability (circular economy). Keyword trends reveal four thematic clusters: supply chain digitalization, agritech, smart industry, and sustainability. The study highlights future research directions, including integrating circular economy with managerial and technical approaches, linking Industry 5.0 with SDG 12, and applying advanced AI in sustainable industrial practices. The increasing attention to ethical and social dimensions underscores the need for AI solutions that are both technologically advanced and sustainability oriented. Full article

Municipal solid waste management (MSWM) remains a critical environmental governance challenge in rural and peri-urban regions of the Global South, where service delivery gaps exacerbate illegal dumping and public health risks. Geographic Information Systems (GIS) are increasingly promoted as decision-support tools to improve waste collection efficiency and environmental monitoring; however, their adoption in resource-constrained municipalities remains limited. This study investigates the institutional and policy barriers shaping GIS readiness in four rural municipalities within South Africa’s Vhembe District. Using a qualitative case-study design, semi-structured interviews were conducted with 29 municipal officials across managerial and operational levels, complemented by 399 community responses to an open-ended survey question. Thematic analysis, guided by Institutional Theory and the Technology Acceptance Model (TAM), identified five interrelated themes: waste production and disposal behaviours, collection and infrastructure constraints, institutional and operational challenges, policy and standardisation gaps, and technology readiness. The findings reveal that weak service reliability, fragmented governance structures, limited human and financial capacity, and inconsistent policy enforcement collectively undermine GIS adoption, despite its high perceived usefulness among officials. The study demonstrates that the effectiveness of GIS as an environmental management tool is contingent on institutional readiness rather than technological availability alone and highlights the need for integrated reforms in service delivery, institutional capacity, and policy implementation to enable GIS-supported sustainable waste management. Full article

Although green housing is widely regarded as an effective solution to energy and environmental challenges, its actual rate of adoption remains lower than expected. In the context of increasingly prominent sustainable development goals, promoting residents’ adoption of green housing has become a key issue in advancing sustainable transformation within the housing sector. Consequently, enhancing residents’ willingness to adopt green housing is critical to its broader diffusion. Drawing on diffusion of innovation theory, attitude theory, and perceived value theory, this study develops a multidimensional integrated model to identify factors influencing the adoption of green housing. The model examines how the innovation attributes of green housing and residents’ psychological evaluations jointly shape adoption intention. A questionnaire survey was conducted among 387 residents in Nanjing, China, and the data were analysed using partial least squares modelling. The results indicate that the five attributes derived from diffusion of innovation theory are significant antecedents of residents’ attitudes. Relative advantage, compatibility, trialability, and observability exert significant positive effects on residents’ attitudes toward adopting green housing, with relative advantage emerging as the most influential factor. Complexity has a negative, though comparatively weaker, effect on residents’ attitudes toward green housing adoption. Residents’ attitudes and perceived value are identified as significant predictors of green housing adoption intention. These findings contribute to a clearer understanding of residents’ green housing adoption intentions for both researchers and practitioners. More importantly, the study offers general policy and managerial implications for governments and developers seeking to enhance the uptake of green housing. Full article

This study examines how Green Human Resource Management (GHRM) is linked to sustainable organizational performance, encompassing environmental, economic, and social outcomes through the capability-building mechanisms of green innovation (GI) and green organizational culture (GOCL) in emerging manufacturing systems. Drawing on the Resource-Based View and capability-based sustainability perspectives, GHRM is conceptualized as a strategic organizational capability that enables firms in developing economies to beyond short-term regulatory compliance toward measurable and integrated sustainability performance outcomes. Survey data were collected from 446 managerial and technical respondents in Ethiopia’s garment and textile industrial parks, one of Africa’s fastest-growing industrial sectors facing significant sustainability challenges. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with bootstrapping-based mediation analysis, the results show that GHRM is positively associated with sustainable organizational performance, with GI and GOCL operating as key mediating mechanisms that translate HR-related practices into measurable sustainability outcomes. The findings highlight the role of GHRM in strengthening firms’ adaptive and developmental sustainability capabilities by fostering pro-sustainability mindsets and innovation-oriented behaviors, which are particularly critical in resource-constrained and weak-institutional contexts. The study contributes to sustainability and management literature by explicitly linking Green HRM to triple-bottom-line performance through a capability-building framework and by providing rare firm-level empirical evidence from a low-income emerging economy. Practically, the results provide guidance for managers and policy makers to design, monitor, and evaluate HRM systems that intentionally cultivate human, cultural, and innovative capabilities to support long-term organizational sustainability transitions. Full article

Digital cultural-heritage (DCH) platforms are integral to achieving UN SDG Target 11.4, yet their long-term sustainability is compromised by a systemic vulnerability: the rapid decay of user engagement once the initial “novelty effect” fades. To address the theoretical anomaly of the “null effect” regarding value perception found in prior studies, this paper develops a competitive dual-path model to determine whether information-centric or experience-centric strategies effectively foster sustainable continuance intention. Drawing on the stimulus–organism–response (S-O-R) framework, interactivity is modelled as a high-order managerial investment. A quantitative survey of 407 DCH users was analysed using covariance-based structural equation modelling (CB-SEM). The results resolve the strategic dilemma: while interactivity enhances both pathways, a chi-square difference test $\left(\Delta {\chi }^2\left(1\right)=26.207\right.$, p < 0.001) confirms that affective value exerts a significantly stronger impact on cultural identity than epistemic value, supporting the affective primacy hypothesis. Crucially, cultural identity serves as the essential mediator that translates user experience into “emotional stickiness.” By demonstrating that narrative-driven affective engagement is superior to mere information dissemination, this study provides a validated blueprint for virtual–real symbiosis. The findings offer actionable guidance for managers to build digital resilience and safeguard heritage transmission across generations. Full article

As corporate sustainability reporting evolves into a pivotal resource for investors, regulators, and stakeholders, the imperative to evaluate and elevate ESG disclosure quality intensifies amid persistent challenges like opacity, inconsistency, and greenwashing. This review synthesizes interdisciplinary insights from accounting, finance, and computational linguistics on artificial intelligence (AI), particularly natural language processing (NLP) and machine learning (ML), as a transformative force in this domain. We delineate ESG disclosure quality across four operational dimensions: readability, comparability, informativeness, and credibility. By integrating cutting-edge methodological innovations (e.g., transformer-based models for semantic analysis), empirical linkages between AI-extracted signals and market/governance outcomes, and normative discussions on AI’s auditing potential, we demonstrate AI’s efficacy in scaling measurement, harmonizing heterogeneous narratives, and prototyping greenwashing detection. Nonetheless, causal evidence linking managerial AI adoption to stakeholder-perceived enhancements remains limited, compounded by biases in multilingual applications and interpretability deficits. We propose a forward-looking agenda, prioritizing cross-lingual benchmarking, curated greenwashing datasets, AI-assurance pilots, and interpretability standards, to harness AI for substantive, equitable improvements in ESG reporting and accountability. Full article