Search Results (141)

Big data analytics (BDA) has emerged as a crucial strategic asset for organizations aiming to enhance their sustainable company performance; nevertheless, empirical information elucidating the correlation between analytics and sustainability results is scarce, especially in developing nations. This study examines the influence of big data analytics (BDA) on sustainable firm performance (SFP) within the Libyan telecommunications sector, focusing on the mediating roles of organizational learning (OL) and process-oriented dynamic capabilities (PODCs), utilizing dynamic capability and organizational learning theories. A quantitative, cross-sectional research design was utilized. A systematic questionnaire was used to collect data from personnel at five different managerial and functional levels in the Libyan telecoms sector. There were 354 valid replies from a group of 5400 professionals who worked in the managerial, technical, and strategic areas. We used Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS 4.0 to look at the proposed research model. We used measurement scales from previous investigations. The findings demonstrate that BDA exerts a positive and statistically significant influence on SFP. Nonetheless, this direct effect is quite minor when juxtaposed with the indirect effects conveyed by OL and PODCs. Both organizational learning and process-oriented dynamic capabilities significantly and partially mediate the relationship between big data analytics (BDA) and sustainable performance. This shows that analytics-driven sustainability outcomes depend heavily on a company’s ability to learn from data and change how it does things. This study enhances the Business and Management literature by elucidating the inadequacy of analytics investments in producing robust sustainability outcomes. It emphasizes the essential function of supplementary organizational capabilities in converting data-driven insights into enduring economic, environmental, and social value. From a practical standpoint, the findings indicate that managers and policymakers in developing economies ought to prioritize learning systems and adaptive process capabilities in conjunction with digital investments to fully harness the sustainability potential of big data analytics. Full article

Despite the rapid expansion of AI and machine-learning techniques in bankruptcy prediction, classical statistical methods such as discriminant analysis and logistic regression remain relevant because of their transparency and interpretability. These characteristics are crucial for stakeholders who require understandable decision-making tools, especially in NACE Rev. 2 Section I—Accommodation and Food Service Activities, a sector characterized by high operating leverage, vulnerability to economic shocks, and strong macroeconomic importance. The study aims to evaluate and compare the predictive performance of discriminant analysis and logistic regression for bankruptcy prediction and to identify key predictors that can serve as managerial early-warning signals for companies in crisis across B9 countries. The sample of 4395 companies was used. The classification ability of all models is assessed using multiple performance metrics, including overall accuracy, sensitivity, specificity, precision, the F1-score, the F2-score, the Matthews correlation coefficient, and the area under the receiver operating characteristic curve. The results show that both approaches achieve consistently high predictive performance, with all major metrics exceeding 0.92 on the test sample of prosperous and non-prosperous enterprises. Six significant bankruptcy predictors are identified for each method, with three common indicators: financial leverage, total liabilities to assets, and return on costs. The comparative analysis results in a methodological “draw,” confirming comparable predictive power. These findings reaffirm the relevance of classical prediction models and identify key financial indicators that can be used as practical early-warning signals by managers in the sector. Full article

The sustainability of experience-intensive wellness tourism services increasingly depends on managers’ ability to understand heterogeneous and implicit tourist preferences that are rarely captured through traditional survey-based approaches. In the context of Korean Templestay tourism, this study develops a data-driven decision-support framework that leverages large-scale unstructured review data to address managerial challenges such as choice overload, inefficient resource allocation, and cold-start conditions. Using 74,015 user-generated reviews collected between 2020 and 2024, the framework integrates Optical Character Recognition (OCR) to extract image-embedded text, achieving a validated character-level accuracy of 96.8%. In addition, a weak supervision strategy is applied to identify latent tourist preferences in a cost-efficient and scalable manner. Preference classification is conducted using Random Forest models combined with SMOTE, followed by clustering and user-based collaborative filtering to support personalized recommendations. The findings indicate that the Templestay market is better understood as an interconnected preference network rather than a set of mutually exclusive segments. Across user groups, “rest” emerges as a shared foundational value, while differentiated sub-preferences coexist within the network. The proposed framework successfully generates recommendations for all users in the dataset, demonstrating strong applicability for mitigating cold-start risks and supporting adaptive and sustainable program design. Full article

With the rapid acceleration of technological revolutions and industrial upgrading, firms are increasingly exposed to environmental uncertainty, intensified competition, and continuous technological disruption. Under such conditions, sustainable corporate development depends not only on innovation performance, but on the ability to sustain innovation activities over time. Innovation resilience, defined as the capacity to withstand shocks, reconfigure resources, and maintain innovation momentum, therefore represents a critical foundation of corporate sustainability. Using panel data from Chinese A-share listed firms from 2009 to 2024, this study examines how CEO power shapes sustainable innovation resilience. Drawing on upper echelons theory and signaling theory, we investigate the direct effect of CEO power, the mediating role of corporate reputation, and the moderating role of artificial intelligence adoption. Fixed-effects regression results indicate that CEO power is positively associated with sustainable innovation resilience, and this relationship is partially mediated by corporate reputation. Furthermore, artificial intelligence adoption strengthens the positive association between CEO power and innovation resilience. By linking executive governance, reputational mechanisms, and digital transformation to sustained innovation capacity, this study advances understanding of the organizational foundations of corporate sustainability under uncertainty. The findings provide theoretical insights and managerial implications for designing governance structures that support long-term sustainable development. Full article

Urban metro systems are highly sensitive to seismic disturbances, and the ability of metro stations to manage emergencies effectively has become an increasingly important component of urban resilience. This study develops a resilience-oriented evaluation framework that conceptualizes emergency management as a sequential managerial process encompassing preparedness, response, and recovery. A multi-dimensional indicator system was constructed based on the four resilience capacities—absorptive, maintaining, recovery, and adaptive—and operationalized through a multi-stage Data Envelopment Analysis (DEA) model. The framework enables both overall efficiency assessment and stage-specific diagnosis of managerial weaknesses. Methodologically, the study demonstrates how resilience theory can be operationalized into a network efficiency structure suitable for process-level diagnosis rather than aggregate scoring. A case study of a representative metro station demonstrates the applicability of the proposed method. The results reveal that while preparedness practices are relatively mature, notable inefficiencies exist in real-time response and post-event recovery due primarily to managerial factors such as communication reliability, personnel coordination, and restoration planning. Improvement simulations confirm that targeted enhancements in these management processes can substantially increase overall emergency efficiency. The findings highlight that seismic resilience is not solely determined by physical infrastructure but is heavily dependent on managerial effectiveness across the emergency cycle. The proposed framework contributes a process-oriented, data-driven tool for evaluating and improving emergency management performance and offers practical guidance for metro operators seeking to strengthen resilience under earthquake scenarios. Full article

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

This study aims to explore the relationship between a company manager’s activities and their impact on business performance. Networking is considered a worthy factor in professional and organizational success, providing access to important research, industry insights and future partnerships. Through the analysis of the data used in the study, this paper adopts a methodological approach to examine how managerial networking influences business results, with a particular focus on French small and medium-sized enterprises (SMEs). The findings indicate a strong and positive correlation between the manager’s ability to build and maintain professional relationships and the entire performance of their business. In fact, managers who actively engage in networking often gain access to better business opportunities, funding sources and strategic collaborations that increase growth and competitiveness. Additionally, strong networks facilitate the exchange of knowledge, best practices and innovative ideas, thereby improving decision making and operational efficiency. The review further highlights that networking is not just about expanding contacts, but also about attending meaningful and beneficial affairs that contribute to long-term success. These results underline its importance as a strategic tool for business leaders, sustaining the idea that well-connected managers are better equipped to navigate challenges, catch opportunities and drive sustainable business prosperity in an increasingly competitive market. 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

Although teacher identity and social–emotional learning (SEL) have been studied separately, little is known about how these constructs intersect in ways that explain why teachers’ social and emotional competence (SEC) does not always translate into classroom practice. This study introduces the construct of SEL identity (SEL-ID) as a potential missing piece in the current SEL frameworks by utilizing the teacher identity construct. This study seeks to describe SEL-ID, drawing on teachers’ reflections on lived experiences and their classroom practices. Using grounded theory, the data was collected through semi-structured interviews and classroom observations of 12 early childhood education teachers who were actively working with children aged from 3 to 5 in childcare centers established by a local municipality. As a result, the coding process revealed overlaps between teacher identity and SEL, as well as unique elements that go beyond the established SEL framework. Five interrelated components of SEL-ID resulted from the analysis process: (1) self-perception, (2) emotional literacy, (3) interpersonal relations, (4) participatory SEL, and (5) managerial expertise. These findings demonstrate that SEL-ID is not simply an extension of teacher identity or SEL but a construct that helps explain variations in teachers’ ability to enact SEL in practice. The researchers hope that this study will guide future studies to explore more into SEL-ID and its contribution to strengthening SEL practices in schools. Full article

Although the practice of linking Environmental, Social, and Governance (ESG) metrics to executive compensation (ESG compensation) has become increasingly common worldwide, consistent evidence of its economic consequences for corporate value remains limited. Drawing on agency theory and a sustainable governance perspective, this study examines how responsibility-oriented incentive mechanisms translate into corporate financial performance. Using textual data from a large sample of Chinese listed companies and employing the BERT deep learning model for empirical analysis, the results show that ESG compensation significantly improves subsequent financial performance. Further analysis reveals that this effect is primarily driven by incentives related to the environmental and social dimensions of compensation structures. In addition, ESG compensation enhances firms’ ESG rating performance and reduces rating divergence, thereby lowering stakeholders’ transaction costs. The moderating analysis indicates that managerial ability and financial slack both strengthen the positive effect of ESG compensation on financial performance. Overall, this study uncovers the internal mechanism through which ESG compensation promotes corporate value creation and clarifies its practical implications for sustainable corporate governance. Full article

This study exploits the promulgation of China’s E-commerce Law in 2009 as a quasi-natural experiment to construct a difference-in-differences (DID) model, examining the impact and mechanisms of digital economy governance on corporate cost stickiness. Using Chinese-listed manufacturing companies from 2013 to 2020 as research samples, we find that the implementation of the E-commerce Law significantly reduces corporate cost stickiness. Mechanism analysis reveals that the implementation of the E-Commerce Law promotes digital transformation in traditional manufacturing firms and strengthens their supply chain collaboration. These advancements lead to more efficient cost management decisions and reduce corporate cost stickiness. Heterogeneity analysis indicates that this effect is more significant for mature and declining enterprises and state-owned enterprises, as well as in regions with relatively developed economies and low reliance on foreign trade. Further research shows that the implementation of the E-Commerce Law curbs managerial opportunism and enhances managerial ability. Full article

This study focuses on exploring the nature of inter-organizational learning and the types of knowledge that are transferred/shared between foreign multinational companies (MNCs) and their local partner firms within international interfirm alliances in developing countries, particularly those operating in the Nigerian oil industry. The aim is to identify/examine the types/quality of knowledge transfer and the viability of interfirm knowledge transfer for boosting the knowledge base and innovation capacity of the alliance partner firms, particularly of the local partner firms, in such a distinctive type of international alliances. Using a qualitative case study research method, four cases of international interfirm collaborative arrangements between foreign and local companies in the Nigerian oil industry were studied. The findings of this study show that the local partner firms in the alliances were able to access and acquire mainly technological and international market knowledge through the collaborations, but not managerial knowledge. Contrary to the extant theory/literature, the foreign partner firms did not seek to acquire local market knowledge from the local firms but clearly demonstrated “knowledge transfer willingness” that facilitated the acquisition of knowledge by the local firms in the alliances. However, the technological and international market knowledge acquired by local firms were limited to mainly the explicit dimension of the knowledge. In effect, the local partners in this study mainly acquired explicit technological and international market knowledge with limited tacit knowledge. A key implication of this finding can be a reduced ability to develop innovation capacity through alliances. This paper, therefore, highlights the necessity for an increased focus on tacit knowledge acquisition by local partner firms and the importance of utilizing appropriate learning mechanisms to achieving tacit knowledge acquisition through the collaborations. Full article

Standardization alliance networks serve as crucial channels for firms to sponsor standards and access external resources, exerting a substantial impact on their standard-setting competitiveness and their ability to foster a sustainable innovation ecosystem. The technology–organization–environment (TOE) framework offers an integrated theoretical perspective for studying the causal recipes of how the technological composition, the network structure, and the environment features of standardization alliance network affect firms’ capabilities to dominate and support technological standardization. Based on the data of 88 vehicle manufacturers with experience in participating in standardization alliances, the results of fuzzy-set Qualitative Comparative Analysis (fsQCA) show that: (1) large-scale networks with low density and high technological diversity can simultaneously explain firms’ high level capabilities to dominate and support standardization; (2) supporting standardization is highly dependent on network scale, as firms embedded in large-scale alliance networks with high technological diversity or proximity both enjoy advantages in supporting standardization; (3) dominating standardization shows relatively low dependence on network scale, a firm can enhance its standardization dominance by maintaining an alliance network with low technological proximity in institutional environment with high government intervention. Overall, this study contributes to the theoretical literature on cooperative standard-setting and provides managerial implications for firms looking to enhance capabilities to dominate and support standardization, thereby shaping sustainable technology trajectories and securing their long-term industrial competitiveness in a rapidly evolving technological environment. Full article

This study investigates how improvements in energy efficiency (EE) contribute to the sustainable growth rate (SGR) of manufacturing firms. Using panel data from Chinese A-share listed companies between 2012 and 2023, we provide empirical evidence that higher EE significantly enhances firms’ ability to maintain long-term and stable growth. Furthermore, the findings reveal that executives’ green perception (EGP) and environmental protection investment (EPI) strengthen this positive relationship, while an excessive green innovation bubble (GIB) weakens it. By integrating insights from corporate governance and sustainability research, this study highlights the critical roles of managerial orientation, resource allocation, and innovation quality in shaping the pathway from EE to sustainable growth. The results extend the understanding of how micro-level corporate actions support global sustainability goals and provide a nuanced perspective on balancing efficiency and innovation. Practically, the findings suggest that managers should embed EE into strategic decisions, while policymakers should strengthen financial and institutional support to facilitate corporate green transition. This research contributes to the literature by offering new evidence from an emerging market context and by demonstrating the multidimensional mechanisms through which EE fosters corporate sustainable development. Full article

This study develops a multi-agent evolutionary game model that incorporates both retailers and heterogeneous logistics providers, extending beyond prior dyadic models that typically isolate either channel choice or logistics competition. By comparing scenarios with and without the BOPS channel, the framework captures the dynamic interactions between retailers and logistics providers. The results show that introducing In-Store Pickup significantly increases market demand and retailer revenue by reducing consumer waiting time, but it also produces a revenue crowding effect for slow logistics providers. For fast providers, the impact depends on their ability to adjust service quality: lowering service levels helps retain market share, while efficiency improvement enhances profitability. Furthermore, consumer product valuation plays a critical role in driving retailers toward dual-provider or hybrid strategies. The methodological innovation lies in integrating heterogeneous logistics service differentiation with channel strategy selection into a unified evolutionary game framework. The study contributes by proposing a dynamic “efficiency threshold–channel selection” mechanism, offering both theoretical advancement in omnichannel retailing research and managerial insights for retailers and logistics providers seeking to optimize logistics capabilities and channel collaboration. Full article