Purpose Although prior research has examined ownership-incentive relationships, the authors broaden the focus to firm-wide incentive architectures and draw on regulatory focus theory (RFT) as an interpretive lens to understand the underlying patterns in this relationship. Design/methodology/approach The authors first use data from Chinese listed companies and examine whether incentive schemes differ systematically across state-owned and private enterprises. Then, leveraging China’s capital-oriented reform as a quasi-natural experiment, the authors further use a staggered difference-in-differences approach to investigate how incentive schemes evolve following ownership transitions. Findings The findings reveal that firms with different ownership types are associated with distinct incentive patterns, which are consistent with differences implied by RFT. The authors also found that following capital-oriented reform, reformed firms exhibit incentive patterns that remain broadly consistent with their pre-reform structures. Practical implications This study offers actionable insights for multiple stakeholders involved in corporate governance and SOE reform. More broadly, the authors’ findings are relevant for boards, investors and senior managers operating in non-SOE or multinational contexts characterized by hybrid governance arrangements. Originality/value The results illustrate how RFT can motivate predictions about ownership-incentive associations and offer a coherent lens for interpreting both cross-sectional differences and reform dynamics in incentive architecture. The findings speak to ongoing debates about governance reform, internal pay equity and incentive alignment, with implications that are consistent with ownership-linked differences across institutional contexts.
Purpose Integration of artificial intelligence (AI) into omnichannel operations has revamped operations, enhanced efficiency, improved sustainability and improved the customer experience. However, AI adoption is subject to various complexities and risks that can dilute operational performance and sustainable aspects. Therefore, this study aims to explore the multiple risks that hinder the adoption of AI in a sustainable, resilient omnichannel supply chain. Design/methodology/approach Based on the technology–organization–environment–societal theoretical background, the identified risks were categorized. The research methodology is carried out in three phases: first, the Delphi technique was used to verify the risks identified through a literature review. Second, grey relational analysis was done to prioritize the risks. Third, this research establishes a dyadic relationship among anticipated risks using the grey DEMATEL technique. Findings This research results indicate that inaccurate multichannel demand forecasting and operational cost overruns are the top causal risks. Misaligned performance metrics and loss of human oversight are the most influential risks. Originality/value To the best of the authors’ knowledge, this research is the first of its kind, and the results are highly useful for managers and practitioners to successfully integrate AI into the omnichannel supply chain, thereby enhancing sustainability and achieving net-zero goals.
Purpose While safety knowledge management in high-hazard organizations has received significant attention, existing literature predominantly focuses on professionalized “elite” settings (e.g. nuclear power, aviation), often overlooking contexts characterized by significant workforce knowledge disparities. To address this deficit, this study aims to develop an integrated theoretical model of safety knowledge management specifically for “asymmetric high-hazard organizations.” Design/methodology/approach An in-depth single case study was conducted on H Blasting Technology Corporation, a representative firm in the civilian blasting industry. The firm is characterized by strict external regulation and a frontline workforce with relatively limited educational attainment and theoretical background. Findings This study reveals that safety knowledge management in high-hazard organizations comprises two interrelated and mutually reinforcing channels: a vertical channel and a horizontal channel. The vertical channel is further classified into vertical knowledge translation (top-down) and vertical information reflection (bottom-up). The horizontal channel is characterized as horizontal high-frequency iteration. Originality/value This study advances the field by shifting the research lens from “elite” to “asymmetric” high-hazard organizations. It provides a novel theoretical framework explaining how organizations can achieve high reliability despite workforce knowledge asymmetries. These findings offer significant theoretical and practical insights for optimizing safety performance under conditions marked by high external regulation and internal knowledge disparities.
Purpose With the prosperity of the worldwide B2B electronic market, the purpose of this study is to explore the role of users' behavior, not only the effect of the user base, on its sustainable competitiveness. The quality of users' behavior, which is indicated by the activity of two-sided users, is critically important for B2B electronic market makers (or platform companies) as there is a "chicken and egg problem."Design/methodology/approach In the context of B2B electronic markets, the authors examine the dynamic relationship of two-sided users' activity and platform performance using a VAR model. Furthermore, the authors investigate how advertising strategies improve the active degree of different users' behaviorsFindings The results show that the sellers' activity improves the platform sustainable competitiveness more effectively than buyers' activity. Moreover, the authors find that the external customers who are attracted by advertising (search advertising and event marketing in this paper) can significantly influence the internal users' activity.Originality/value These findings emphasize that more exploration should be paid to the quality of users' behavior in two-sided markets, and provide guidance related to advertising strategy.
Purpose This study aims to examine how generative artificial intelligence (AI) chatbots influence tourists' purchase intention (TPI) in Iran's tourism sector. Iran is a developing economy with distinct socio-cultural and technological features. The study uses the Stimulus-Organism-Response (S-O-R) framework. It explores technological stimuli: prompt quality (PQ), personal innovativeness (INN), personalization (PER) and interactivity (INT). These shape psychological responses: tourist attitude (TATT), tourist trust (TT) and tourist engagement (TE). The responses drive TPI. Digital literacy (DL) moderates these relationships. Design/methodology/approach This study used a quantitative approach. Data came from 400 Iranian tourists who used ChatGPT for travel activities. An online survey was conducted in November-December 2024. The authors applied partial least squares structural equation modeling (PLS-SEM) to test the hypotheses. Findings PQ, INN, PER and INT positively affect TATT, TT and TE (with one exception for PQ-TE). These psychological factors mediate the path to TPI. TT is the strongest driver of TPI. This highlights its importance in low-trust contexts. DL strengthens the link between TATT and TPI. Its effect on TT and TE is limited. The model shows strong explanatory and predictive power. Originality/value This study extends the S-O-R framework to generative AI chatbots in a developing tourism market. It introduces PQ and DL as key elements. It addresses literature gaps by considering socio-cultural nuances. The study provides theoretical insights and practical recommendations for chatbot design. These can boost engagement, trust and sustainable tourism in similar economies.
Purpose Based on the theoretical foundation of social exchange theory and social learning theory, this study aims to investigate the impact of leaders' ethical role modelling on employees' time theft behaviour, with the mediating role of felt obligation and the moderating role of trust.Design/methodology/approach In this study, data were gathered from 205 respondents who were working in service sector companies in Sargodha, Punjab, Pakistan via multistage sampling. Hayes' PROCESS models 1, 4 and 7 were used for mediation, moderation and moderated mediation analysis.Findings Ethical role modelling has a significant impact on reducing time theft behaviour of employees. Felt obligation significantly mediates this relationship, while trust significantly moderates and strengthens the indirect relationship. The results confirm a moderated mediation model.Originality/value This study extends existing literature on workplace unethical behaviours by focusing on time theft in the Pakistani service sector based on the ethical reciprocity aspect of social exchange theory along with social learning theory. In contrast to the much-examined construct of ethical leadership, this research has examined the unique nature of ethical role modelling rather than the broad focus on leadership styles in general.
PurposeThis study aims to use the springboard perspective (SP) and institution-based view (IBV) to explore how company size and state ownership together affect the choice of full acquisitions and how some institutional factors moderate this effect.Design/methodology/approachEmploying a Chinese sample and the logit model, this study empirically tested these interactive effects.FindingsThis study finds that company size and state ownership together can affect the choice of full acquisitions. Marketization, industry inward FDI, host technology and market growth each can moderate this interactive effect.Originality/valueBy applying the SP and IBV, it develops new theoretical mechanisms to help us understand the state ownership-firm internationalization relationship. It applies the IBV and SP to explain some moderating effects that are difficult to be explained by the SP or IBV alone. It explains why full acquisition is a kind of springboard internationalization mode (SIM) and why Chinese large SOEs are a kind of springboard multinational enterprise (SMNE). It proposes that researchers should adequately identify SMNEs and SIMs and build relationships between them.
Purpose-This study aims to investigate the legitimacy challenges faced by emerging market digital platforms internationalizing under geopolitical salience, focusing on ByteDance as a case study. It also aims to reconceptualize the Liability of Origin (LOR) and liability of outsidership (LOO) concept in the context of digital platforms, identify specific challenges these enterprises encounter during internationalization amid digital economic globalization and explore strategic mechanisms that enable firms to maintain competitive advantages while overcoming inherent disadvantages in host countries. Design/methodology/approach-The research uses an exploratory case study methodology with high contextualization, analyzing ByteDance's international expansion. Data was collected from multiple sources including mainstream media coverage in host countries (USA, UK, Australia and India), editorial papers and publicly available corporate resources. The analysis systematically maps the manifestations of LOR and LOO for digital platforms and examines corresponding strategic responses, offering insights into how emerging market digital platforms navigate legitimacy challenges in developed markets within the context of escalating geopolitical tensions. Findings-For emerging market digital platforms, the Liability of Origin (LOR) fundamentally shifts from traditional capability-based deficits to "governance-based trust deficits" centered on data sovereignty and algorithmic ideology. Under geopolitical salience, this origin-based stigma functions as an antecedent trigger that actively precipitates systemic network exclusion (liability of outsidership), manifesting as institutional severance and ecosystem decoupling rather than simple relational barriers. Furthermore, traditional compliance strategies face a "legitimacy trap," where localization efforts paradoxically amplify scrutiny of the platform's internalized core. Practical implications-This research offers strategic guidance for digital platform enterprises seeking international expansion. It recommends strengthening institutional isomorphism through appropriate organizational design to establish legitimacy while preserving competitive advantages. Building rapid market response mechanisms, pursuing deep localization strategies and maintaining continuous innovation helps enterprises transcend origin-based limitations. It offers a context-sensitive framework for understanding digital globalization amidst "Great Power Competition." Originality/value-This study systematically distinguishes digital platforms from traditional multinational enterprises to reconceptualize their unique internationalization challenges. First, regarding Liability of Origin (LOR), the authors identify a qualitative shift in manifestations: from traditional "capability deficits" (e.g. product quality) to "governance-based trust deficits" (e.g. data sovereignty and algorithmic ideology), driven by geopolitical salience rather than institutional voids. Second, regarding liability of outsidership (LOO), the authors reveal that due to platforms' high externalization, LOO manifests as "ecosystem decoupling" and "institutional severance" rather than simple relationship barriers. Finally, the authors uncover a dynamic interaction where origin-based stigma functions as a trigger that precipitates this systemic network exclusion, offering a nuanced framework for digital globalization.
Purpose-Generative artificial intelligence (GenAI) presents unprecedented challenges and opportunities for entrepreneurship instructors. This conceptual paper aims to pair insights from the entrepreneurial cognition literature with current research on GenAI to propose a dynamic role-based framework and actionable pedagogic strategies for integrating GenAI into business planning assignments, a central facet of contemporary entrepreneurship education. Design/methodology/approach-The study begins by reviewing the history of business planning in entrepreneurship education, then analyzes GenAI's strengths and weaknesses across the common stages involved in producing a quality business plan: problem discovery and definition, and solution discovery and definition. Drawing on recent research, the study posits that GenAI is particularly advantageous in the divergent stages of this process (problem and solution discovery). Still, it has limitations in assimilating the complex ethical and situational understandings required to arrive at the "best" and actionable outcomes produced in the convergent stages (problem and solution definition). Findings-The study outlines a holistic pedagogical approach that integrates current and future GenAI alongside cognitive processes typical to business planning and the "soft" and "hard" skills required for successful business planning. This approach ensures that GenAI serves as a complement, not a substitute, for students' entrepreneurial education by maintaining opportunities for aspiring entrepreneurs to develop the critical thinking and failure-informed resilience necessary to cultivate their entrepreneurial mindsets and competencies. Originality/value-In this paper, the authors introduce a series of differentiated and dynamic roles that instructors, students and GenAI might adopt during the business planning process. Adopting this roles-based approach to the use of GenAI in business planning pedagogy can enable educators to enhance the quality of new venture assignments without depriving students of the opportunity to experience small failures and develop the critical thinking skills that are antecedents of their future personal growth and entrepreneurial success.
PurposeEco-labels have evolved into pivotal factors shaping consumer preferences toward sustainable product selections, previous studies indicate that the effectiveness of eco-labels is closely intertwined with consumers' personal characteristics and situational factors. This necessitates attention to specific content and presentation of the eco-label as well as a deep understanding of consumer motivations. In this context, the study aims to address the question: how do eco-labels and their various types align with consumers' appeal to influence their green purchase behavior?Design/methodology/approachThrough three studies, a total of 1,150 participants were involved in this research to explore the relationship between eco-label and the purchase intention of green products.FindingsThe results show that: First, consumers exhibit a stronger intention to purchase green products with eco-labels compared to those without. Second, perceived green authenticity serves as a mediator in the relationship between eco-labels and consumers' purchase intentions for green products; it also mediates the effects of emotional eco-labels and numerical eco-labels on these intentions. Third, product type interacts with eco-label type in shaping consumers' willingness to buy green products; specifically, for altruistic green products, emotional eco-labels have a stronger positive effect than numerical eco-labels, whereas for egoistic green products, numerical eco-labels are more effective than emotional ones.Originality/valueThis research offers valuable insights for businesses seeking to leverage eco-labeling strategies effectively in their marketing efforts aimed at promoting sustainable consumption.
PurposeAs artificial intelligence (AI) capabilities advance, machine agents are increasingly integrated into financial markets, making it crucial to understand their influence on market dynamics. This study investigates how the presence and disclosure of machine agents influence return extrapolation, a key behavioral bias in financial decision-making, and subsequently explores which human-machine interaction (HCI) design paradigms may mitigate this bias.Design/methodology/approachHuman-machine hybrid Prediction Markets are used to extract and integrate beliefs from both human and machine agents. This work, through two empirical studies, aims to address two research questions: (1) To what extent does the introduction of machine agents and their presence disclosure affect the return extrapolation of the entire trader population, including both human and machine traders? (2) Which design paradigms of HCI may further mitigate return extrapolation?FindingsFirst, the introduction of machine agents significantly reduces return extrapolation. Second, disclosing the presence of machine agents weakens their effectiveness in reducing return extrapolation. Third, implementing a competitive goal structure between human and machine agents further reduces return extrapolation. Fourth, this competitive structure proves most effective when machine agents share profits based on human performance.Originality/valueThe findings offer valuable insights into the role of AI in financial markets and provide guidance for the design and governance of financial trading and prediction platforms.
PurposeCorporate environmental responsibility (CER) has become a global focus for businesses. While existing research has predominantly emphasized CER's institutional and environmental outcomes, its psychological mechanisms in shaping employee perceptions remain underexplored. Drawing on the instrumental-symbolic framework of organizational attractiveness, this study aims to investigate how CER influences organizational attractiveness through two psychological pathways - specifically, fostering organizational pride (as a symbolic attribute) and improving perceived treatment (as an instrumental attribute) - and to examine the moderating role of corporate ability.Design/methodology/approachThis study adopts a multi-method design. It includes two studies: Study 1 is an experiment with 200 potential employees, and Study 2 is a multi-wave survey of 423 current employees.FindingsThe results indicate that CER positively influences organizational attractiveness. Organizational pride and perceived treatment serve as parallel mediators, jointly explaining the relationship between CER and organizational attractiveness. Additionally, corporate ability negatively moderates these relationships: CER exerts stronger effects in organizations with lower corporate ability.Originality/valueThis study centers on employees' psychological responses to further understand how CER functions as a micro-level strategy to enhance organizational attractiveness. These findings not only expand the literature on corporate environmental management but also provide practical insights for integrating environmental initiatives into workforce strategies.
Purpose This study aims to examine blockchain technology’s transformative potential in advancing circular economy practices, specifically focusing on reverse logistics. This study investigates how supply chains may become more transparent, traceable and trustworthy by using blockchain’s secure and unchangeable data exchange capabilities. Design/methodology/approach This study identifies and validates important circular economy behaviors using the Delphi technique and Grey Influential Analysis (GIA). GIA analysis helps in identifying the most influential circular economy practices through blockchain technology in reverse logistics. Findings This study highlighted the GIA technique, indicating that a more holistic conceptual framework is necessary to capture the complex interactions between technological, organizational and social factors for enabling blockchain-enabled reverse logistics. This study further contributes to the literature that is growing daily on the role of “emerging technologies” in the management of sustainable supply chains by uniquely placing in context how blockchain addresses the key challenges related to reverse logistics and the implementation of the circular economy. Research limitations/implications This study’s limitations include potential bias in practice assessment, relying on literature and expert opinions. Practical implications This research will be very helpful and valuable to organizations that intend or seek to use blockchain technology in their circular economy and reverse logistics operations. The ranking of practices allows the business world to have a prioritized roadmap on which they can focus their efforts and resources on the most influential applications of blockchain technology. Originality/value Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in various industries, but very little in the circular economy, specifically in reverse logistics. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain in reverse logistics. The research would bridge the gap in identifying the gap and recognizing the prominent principles using the Delphi technique and GIA techniques.
PurposeLean and green (LG) principles provide ways for escalating the progress and ecological images of the manufacturing organisations (MO). LG strategies are effective for increasing performance and to build green environment solutions for improving the sustainability and operational outcomes in an industry. However, there are certain barriers towards implementing LG pathways in the manufacturing industry. The study demonstrated critical perspectives towards transforming supply chains based on integral LG manufacturing barriers for indeed Innovations and reinforcements. This study aims to determine these barriers by reviewing the literatures and evaluated grey-connections between them.Design/methodology/approachThe study highlights 40 barriers that hinder the implementation of LG approaches in MO. In study, a six-phase methodology is used to analyse the challenges of LG implementation. Here, DEMATEL technique is used and grey-connections are determined by plotting cause-and-effect relationship diagram to examine the impact of barriers. Additionally, modified best-worst method (MBWM) is used and integrated to define the priority importance of each barrier.FindingsIn study, 40 barriers are presented, where nine barriers are classified according for cause-and-effect relationship. The findings presented the grey-connections between nine barriers. Here, significant ratings are attained, which affirmed "lack of top management commitment", "Lack of human resources and technical expertise" and "High cost of disposing of harmful wastes" as the greatest barriers that hindered the implementation of LG approaches in MO.Practical implicationsThe findings will assist manufacturing firms in simplifying the most essential and the least significant barriers by mapping grey-connections between these barriers. The study will assist practitioners and allow administrators to raise awareness towards barriers to LG implementation in developed economics. Grey-connections highlighted the commitment of the top management along with technical expertise and availability of human resources critical for implementing LG practices in the manufacturing organisation.Originality/valueThe current study uses the integration of DEMATEL and MBWM model to evaluate the order of barriers towards LG deployment and presented a greater understandability about LG barriers. The study categorised the grey-connection between barriers based on cause-and-effect relationship to portray the drivers and influencing barriers. This study landmark its achievement by setting the way for future research in the area of removing barriers to LG practices implementation.
Purpose This study aims to develop and empirically test a three-dimensional framework integrating visibility, green logistics performance, and operational flexibility to explain freight logistics performance in the Indian context. The freight logistics sector serves as a critical driver of economic growth and competitiveness of nations across the globe. Yet, it faces significant operational inefficiencies, infrastructural constraints and environmental challenges. Despite ongoing reforms and policy interventions, logistics performance remains suboptimal compared to global benchmarks. Design/methodology/approach This study proposes an integrative framework encompassing three key dimensions: visibility, green logistics performance, and flexibility, as determinants of improved freight logistics performance. Drawing on data from logistics professionals across diverse organizational roles and sectors, the study applies fuzzy-set qualitative comparative analysis to identify necessary and sufficient conditions for high performance. Findings The study findings reveal that individual dimensions positively influence outcomes, digital visibility tools, green logistics practices and operational adaptability significantly enhance logistics effectiveness and resilience. Configurations involving Internet of Things integration, carbon footprint reduction initiatives and multimodal transport capabilities emerged as critical enablers. Practical implications By offering a context-specific, empirically grounded model, the study contributes to both theoretical understanding and practical decision-making. It also aligns with Indian national logistics goals such as the PM Gati Shakti initiative and broader global imperatives, including the UN Sustainable Development Goals. The research thus provides actionable insights for policymakers, logistics providers and supply chain strategists seeking to transform India’s freight logistics landscape in a sustainable and future-ready manner. Originality/value The research adds value by providing the organization’s unique strategic pathways to achieve high logistics performance.
Purpose The supply chain acts as a critical bridge connecting the global production network to consumer markets, playing an instrumental role in bolstering an enterprise’s international competitive edge. However, the existing research on the impact of the supply chain on an enterprise’s overseas investment is still unclear and needs to be solved urgently. This paper aims to explore the configuration effect of the supply chain and institutional gap on Chinese company’s overseas investment along the Belt and Road. Design/methodology/approach Based on 24 listed companies, this study adopts the fuzzy-set qualitative comparative analysis method and selects six antecedent conditions in the supply chain dimension, supply chain enterprise dimension and external environment dimension to explore the configuration effect. Findings It is found that supply chain and institutional gap are not necessary conditions to promote Chinese enterprises’ overseas investment in the countries along the Belt and Road. There are three configuration paths. First, green supply chain companies with low digital integration and high supply chain concentration can boost overseas Belt and Road investments through strong ESG performance, even without innovation policies. Second, companies with low supply chain concentration and digitalization can invest abroad with good institutional environments and high ESG performance, regardless of their green status or policy support. Third, nongreen companies with low ESG, digitalization and policy support can still invest in Belt and Road regions with unfavorable institutional environments if they have high supply chain concentration. Originality/value This paper enriches the study on the influencing factors of overseas investment in the Belt and Road from the perspective of configuration, holding significant relevance for enterprises engaging in overseas investments within Belt and Road countries.
PurposeThis paper aims to examine the optimal charging station construction cooperation strategy in promoting the use of electric vehicles (EVs) and achieve green and sustainable development, the government has provided subsidy incentives for the installation of charging stations by new energy vehicle manufacturers. At the same time, in practice, many competitive new energy vehicle manufacturers collaborate to jointly build charging stations. Therefore, understanding how the government's subsidies interact with the collaborative relationships between competing manufacturers is an important issue in the EVs field.Design/methodology/approachBy constructing a game theory model, this study explores the charging station construction cooperation strategies of competitive manufacturers, including non-cooperation and cooperation through revenue sharing or investment cost-sharing between both parties.FindingsThe findings suggest that independent construction suits smaller firms with limited investment capacity, while revenue-sharing collaboration is ideal for firms with diverse business types. Investment cost-sharing collaboration is better for firms with limited capabilities but growth ambitions. From a government perspective, to maximize charging station construction, larger subsidies and encouraging revenue-sharing collaboration among diverse firms are recommended. To prevent market monopolies, promoting investment cost-sharing collaboration between small and large firms is more effective.Originality/valueThis study provides a correct understanding of the feasibility of the new energy subsidy policies currently implemented in China, particularly offering a theoretical foundation for charging station cooperation strategies.
PurposeThis study aims to explore how and when humble leadership evokes subordinate task proactivity. Integrating social information processing theory with the reflexivity literature, the study propose that task reflexivity mediates the relationship between humble leadership and task proactivity. Subordinate learning goal orientation moderates this indirect effect.Design/methodology/approachA scenario-based experiment and a two-wave field study were conducted to examine the proposed hypotheses. Descriptive statistics and hierarchical multiple regression techniques were applied to analyze the data.FindingsThe research found that 1) task reflexivity mediated the relationship between humble leadership and task proactivity; 2) subordinate learning goal orientation strengthened this indirect effect.Practical implicationsThe results suggest that organizations should emphasize the role of humility in leader selection and training to actively and flexibly cope with workplace uncertainty and complexity. In addition, organizations should adopt a flexible staffing system (i.e. allocating subordinates with high learning goal orientation to humble leaders) to optimize the effect of leader humility on proactivity.Originality/valueThis research provides insights into how humble leadership affects employee proactivity by fostering deep cognitive engagement. Employees with high learning goal orientation are more likely to perceive the developmental signals conveyed by humble leaders and thereby engage in targeted proactive behaviors by reflecting on past experiences and preparing for future actions.
PurposeChina, as a global manufacturing powerhouse, relies on labor-intensive entrepreneurship for economic growth. To protect workers' rights, China is tightening labor market regulations. The purpose of this study is to empirically examine how China's tightened labor market regulations impact manufacturing entrepreneurship.Design/methodology/approachScholars have divergent views on the effects of labor regulation on entrepreneurship. Using signaling theory and panel data from 2008 to 2020 across Chinese cities, the author applied a two-way fixed-effects model to examine the direct, indirect and varying impacts of labor regulation on manufacturing entrepreneurship.FindingsThe author found that frequent labor regulation promotes manufacturing entrepreneurship, with higher levels of regulation correlating with more entrepreneurship. Labor regulation also enhances AI innovation and digitalization, which both support entrepreneurship. Besides, the effects of labor regulation vary, decreasing as firm density and nonmanufacturing entrepreneurship rise.Originality/valueThe research extends signaling theory and clarifies the complex dynamics between labor regulation and entrepreneurship using Chinese city data.
Purpose This study aims to explore the interplay between supply chain collaboration and disruption and their joint impact on supply chain resilience. It also aims to identify the configurational conditions under which supply chain resilience is achieved, providing a holistic framework for enhancing supply chain management practices amidst disruptions. Design/methodology/approach This study uses a fuzzy-set qualitative comparative analysis (fsQCA) to investigate the complex causal mechanisms linking supply chain collaboration and disruption with supply chain resilience. The research integrates three dimensions of collaboration with three dimensions of disruption, offering a comprehensive understanding of supply chain resilience factors. Findings This study reveals that supply chain resilience is not solely dependent on individual elements but is shaped by unique configurations of collaboration and disruption factors. Information sharing emerges as a core factor in high resilience, while the absence of supply and facility disruptions significantly influences resilience outcomes. The research highlights the importance of multiple paths leading to supply chain resilience and the asymmetrical impact of collaboration and disruption. Research limitations/implications The study acknowledges limitations due to data sourced exclusively from China and the use of static data, suggesting the need for cross-temporal and international samples to enhance broader applicability. Future research should consider dynamic temporal changes and diverse theoretical perspectives to comprehensively examine the factors influencing supply chain resilience. Practical implications The research underscores the critical role of information sharing in bolstering supply chain resilience and advises firms to prioritize it in their strategies. It also highlights the importance of mitigating supply and facility disruptions through supplier diversification and robust contingency planning, offering actionable insights for enhancing operational efficiency and risk management in supply chain management. Social implications This research has significant social implications, particularly in the context of global supply chain disruptions. By identifying key factors that enhance supply chain resilience, it can help businesses better prepare for and respond to crises, thereby reducing economic instability and social disruption. Improved resilience can lead to more stable employment, maintain the flow of essential goods and services and contribute to overall societal well-being during times of supply chain stress. Originality/value This study offers original insights by applying fsQCA to explore the multifaceted relationship between supply chain collaboration, disruption and resilience. Its value lies in revealing the complex causal configurations that lead to high or low levels of supply chain resilience, challenging traditional linear perspectives and providing a nuanced understanding that can guide both academic research and practical supply chain management strategies.
