Business Strategy and Development最新文献

This study investigates the influential relationship among the key factors of sustainable supply chain performance (SCP), which are green supply chain (GSC), resilient supply chain (RSC), information sharing (INS), big data analytics (BDA), information quality (INQ), and SCP. This research employs a mixed-method approach, utilizing Grey-MICMAC and Grey-ISM techniques to explore the interrelationships among the six important factors. Data was collected from 10 domain experts and evaluated to ascertain the hierarchical relationships among these factors. The Grey-ISM assesses the interdependence and influence of these essential factors. The analysis indicated that INQ, RSC, and INS exhibit higher driving power, establishing them as essential facilitators in improving SCP. The Grey-ISM findings highlight that INQ, achieved by INS, is paramount in improving SCP. The Grey MICMAC analysis categorized these elements into four clusters: driving, linking, dependence, and autonomous variables. The findings offer pragmatic direction for managers to enhance supply chain resilience and bolster strategies while also advising policymakers on the necessity of regulatory frameworks that facilitate the integration of essential enablers and sophisticated technology. This study contributes to the literature by proposing an integrated analytical framework, Grey-ISM and Grey-MICMAC analysis, establishing a foundation for future research across many industries and regions to investigate the interrelationship among sustainability, technology, and SCP.

The growing emphasis on environmental, social, and governance (ESG) considerations reflects a shift in corporate responsibilities, stakeholders' expectations, and influencing stakeholder engagement, coupled with the growing environmental regulatory pressure for sustainability disclosure initiatives. Therefore, this study investigates how strategically configured board features impact ESG disclosure and how environmental regulation influences this relationship. Based on agency, stakeholder, resource-based theories and data analysis from 428 oil and gas firms within Latin America and the Caribbean region from 2012 to 2023 and by deploying econometric estimators like General Method of Moments (GMM), Pooled Mean Group (PMG), Common Correlated Effects Mean Group (CCEMG), and Two-Stage Least Squares (2SLS), the study revealed that gender diversity, board size, and board independence positively impact ESG disclosure, while foreign nationality and CEO duality exhibit negative impacts. Furthermore, the environmental regulation moderates the nexus between board features and ESG disclosure. The study offers actionable insights for policymakers and corporate leaders to enhance ESG disclosure through tailored governance reforms and robust regulatory policies.

The aim of this paper is to investigate how corporate liquidity influences firms' engagement with SDG 8, which is related to decent work and economic growth, within the European Union context. Using 5154 firm-year observations from 952 EU listed companies between 2010 and 2024, it uses a dynamic random-effects probit model with Mundlak correction and a control function approach in order to address endogeneity and persistence in SDG adoption. The results indicate that liquidity enhances short-term SDG 8 adoption by providing financial flexibility to invest in workforce and productivity, while sustained excess liquidity weakens long-term SDG 8 commitment. Furthermore, governance mechanisms, in particular, CSR committees, significantly strengthen the translation of financial capacity into sustainable outcomes. These findings emphasize the dual role of liquidity as an enabler and constraint, where governance quality decides whether financial resources are effectively mobilized toward achieving inclusive and sustainable economic growth.

This study examines the integrated impact of low-carbon management practices (LCMPs), Industry 4.0 (I4.0), and circular economy practices (CEPs) on the triple bottom line of manufacturing firms. A conceptual framework incorporating both direct and indirect relationships is developed and theoretically grounded in the resource-based view (RBV) and dynamic capabilities theory (DCT). Data were collected using a structured online survey administered to senior managers in production, procurement, operations, logistics, and supply chain functions, resulting in 286 valid responses. The hypothesized relationships were empirically tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that I4.0 technologies have a strong and significant positive effect on LCMPs, which subsequently enhance economic and social performance. CEPs are found to directly and positively influence environmental, economic, and social performance. However, the direct relationship between I4.0 and CEPs is not statistically significant, and CEPs do not mediate the relationship between I4.0 and sustainability outcomes. Further the findings highlight LCMPs as a critical mechanism through which digital transformation translates into sustainability performance, while revealing limited integration between I4.0 and circular economy initiatives. This study contributes theoretically to sustainability literature and provides practical guidance for managers seeking to align digital transformation with low-carbon and circular strategies.

Food loss and waste (FLW) in agricultural perishable food supply chains (APFSCs) remains a persistent barrier to food security, environmental sustainability and rural economic development, particularly in emerging economies. Prior studies have documented various operational, technological, and infrastructural bottlenecks and this limited empirical work clarifies the specific capabilities that are necessary, which are sufficient, and the ones which exert their influence only in specific combinations to reduce FLW in business-to-business (B2B) APFSCs. Grounded in the contingent resource-based view (CRBV), this study examines how capability deficits, contextual constraints and inter-organisational dynamics jointly shape FLW outcomes in India's rural APFSCs. To address the inherent causal complexity of FLW, the study adopts an integrated tri-method approach combining partial least squares structural equation modelling (PLS-SEM), necessary condition analysis (NCA), and fuzzy-set qualitative comparative analysis (fsQCA). Data from 333 valid responses across diverse APFSC actors, including farmers, wholesalers, processors, distributors and cold storage operators. PLS-SEM is used to construct and validate latent constructs while minimising measurement error. Latent scores feed into NCA to identify bottleneck conditions, and into fsQCA to uncover non-linear, equifinal capability configurations associated with high FLW. The findings reveal that FLW emerges not from isolated deficiencies but from interdependent, context-contingent capability gaps, including inadequate cold-chain infrastructure, weak digital information systems, insufficient training, limited coordination mechanisms and fragmented marketing linkages. Several capabilities function as necessary but not sufficient, while others act as sufficient only within particular configurations, highlighting the asymmetric and complementary nature of capability effects. These insights extend CRBV by demonstrating that capability value depends on institutional conditions, actor interdependencies and minimum resource thresholds. The study contributes a nuanced causal explanation of FLW reduction and offers actionable guidance for managers and policymakers regarding the prioritisation and orchestration of operational, technological and relational capabilities in emerging rural B2B agri-food systems.

This study empirically investigates whether and how mergers and acquisitions (M&As) facilitate shared value creation. Using a sample of Chinese A-share listed enterprises from 2008 to 2023, we construct a novel shared value creation indicator that integrates ESG performance and return on assets within a two-dimensional evaluation framework. Employing multiple measures of M&A activity, we find robust evidence that M&As significantly enhance shared value creation. Mechanism analyses reveal that M&As promote shared value creation through three key channels: stimulating new product development, improving production efficiency, and strengthening cluster-level collaboration. Further heterogeneity analyses show that the positive effects of M&As on shared value creation are more pronounced in firms operating in less competitive market environments, firms with stronger stakeholder engagement, and firms with weaker dynamic capabilities. This study contributes to sustainable strategic management literature by demonstrating M&As' role in balancing shareholder and stakeholder interests, offering practical insights for firms to leverage M&As for shared value creation through innovation-driven strategies, operational synergies, and cluster engagement.

As global attention increasingly shifts toward sustainable business practices, understanding how technological innovation fosters responsible environmental behavior has become essential particularly in emerging economies. In this context, Artificial Intelligence (AI) is viewed as a transformative tool for sustainability reporting. Yet, empirical evidence on its influence on Carbon Performance (CP) in the manufacturing sector of the Middle East and North Africa (MENA) remains limited. This study examines the effect of AI adoption on CP and investigates the moderating roles of Responsible Innovation (RI) and Regulatory Quality (RQ). Using an unbalanced panel dataset comprising 3834 firm-year observations from 426 manufacturing firms between 2016 and 2024, the study employs panel quantile regression to capture heterogeneous effects across different performance levels while addressing potential endogeneity through robust econometric controls. The findings reveal that AI adoption significantly enhances CP, with the effect being more pronounced among firms with higher sustainability reporting levels. Moreover, both RI and RQ positively moderate this relationship, suggesting that stakeholder engagement and strong institutional frameworks amplify the sustainability benefits of AI adoption. These results extend the literature on corporate governance, digital transformation, and environmental sustainability by highlighting the complementary roles of technology, stakeholder inclusivity, and regulatory quality. Practically, the study underscores the need for firms and policymakers to align AI-driven innovation with responsible and transparent sustainability strategies to achieve long-term industrial resilience and climate accountability in the MENA region.

This study examines whether audit committee (AC) effectiveness, captured by independence, size, gender diversity, meeting frequency, and financial qualification, influences corporate social responsibility disclosure (CSRD), and whether audit quality (AQ) moderates this link in an emerging market. Using 1043 firm-year observations from 149 non-financial firms listed on the Amman Stock Exchange (ASE) during 2017–2023, we find that AC size and gender diversity are positively associated with CSRD, highlighting the importance of inclusive and diverse governance structures. High-quality auditors strengthen the influence of AC independence and size, suggesting that internal and external monitoring mechanisms operate in a complementary manner. Post-COVID-19, firms appear to rely more on internal governance to buffer uncertainty, reinforcing the strategic role of ACs during crises. These findings offer practical insights for regulators, nomination committees, and investors: strengthening AC composition, particularly in size, gender inclusion, and independence, alongside securing high AQ can function as a dual assurance mechanism to promote credible and consistent CSR reporting in emerging markets.