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While size asymmetry in buyer–supplier relationships has been studied in non-disruption contexts, this research explores how supplier size influences positive and negative supply chain disruptions. Anchoring on the commitment-trust theory (CTT), we explore buyer commitment as a mediating variable and examine how buying firms' mediated power usage depends on different supplier sizes and types of supplier-induced disruptions.

Through two scenario-based behavioral experiments, we discover different patterns in buyers' use of mediated power, contingent on the types of supplier-induced disruptions.

In negative disruptions, buyers prefer more mediated power with large suppliers to control uncertainties, using reward or coercive power strategies. In positive disruptions, we find opposite results, indicating different buyers' perceptions and actions are contingent on both the supplier size and the types of disruptions. These findings underscore the complex interplay between supplier size, buyer commitment and mediated power strategies, revealing that disruption type significantly shapes buyer responses.

This paper extends the CTT framework by considering new antecedents and outcomes. We also provide a more comprehensive understanding of buyer behavior when facing positive and negative supplier-induced disruptions. Our study has limitations. Through vignette-based behavioral experiments, there is a risk that scenarios may not accurately represent real-life situations and that decision-making dynamics could be oversimplified. Future research should incorporate nuanced measurements and conduct additional qualitative research for a comprehensive understanding.

This study enriches the understanding of the buyer-supplier relationship by expanding the CTT framework for a more comprehensive picture. We also offer nuanced insights into size dynamics and disruption types, emphasizing tailored strategies in supply chain management. The findings underscore the importance of understanding these nuances to employ tailored strategy in a business-to-business (B2B) context, as mediated power is contingent on multiple factors.

This study aimed to explore the institutional theory as a lens for investigating how construction firms adapt to supply chain disruptions. Specifically, the paper evaluates the interactions and interdependencies amongst various organizations, participants and institutions in the construction industry as a basis for a holistic, adaptive response strategy for managing supply chain disruptions.

Following the tenets of relativist philosophy and qualitative research methodology, this study explores the lived experiences of senior-level managers across major construction firms in New Zealand through in-depth semi-structured interviews, as a basis for understanding how their respective organizations adapt to supply chain disruptions.

The research findings suggest that aside from the formal rules that guide the conduct of construction firms as they adapt to supply chain disruptions, informal interactions that exist amongst various organizations and players in the construction industry could also enhance the development of innovative and practical response strategies to supply chain disruptions.

This study makes original empirical contributions to the supply chain management literature by providing insights into how construction firms demonstrate normative, coercive and mimetic isomorphic tendencies amidst the complexity of supply chain disruptions. Insights from this study could enhance the adaptive response of construction firms to supply chain disruptions while also improving the overall resilience of the built environment.

The present study investigates the impact of supply chain disruption orientation (SCDO) on four supply chain disruption (SCD) mitigation strategies: supply chain integration (SCI), supply chain agility (SCA), supply chain visibility (SCV) and supply chain redundancy (SCR). It also examines the impact of the four mitigation strategies on SCD. The impact of the latter on business performance (BP) is also explored.

This study employs an empirical approach through survey research methodology. It analyzes data collected from 304 managers from pharmaceutical distribution companies in Jordan. Appropriate validity and reliability tests were employed for the study constructs. Path analysis using AMOS software was performed to test the study hypotheses.

SCDO was found to positively affect all SCD mitigation strategies. Furthermore, among the four mitigation strategies examined, SCV exhibited the highest significant impact in reducing SCD, followed by SCA and then SCR. However, the results revealed that SCI did not significantly impact SCD. Additionally, SCD proved to be negatively and significantly related to BP.

The present study fills a gap in the literature regarding the management of SCDs in pharmaceutical supply chains (SCs) generally and SCs of pharmaceutical distribution companies specifically. It also addresses an under-investigated area in the literature concerning the role of SCDO in promoting the adoption of SCD mitigation strategies.

This study investigates the antecedents of supply chain resilience of small and medium-sized enterprises (SMEs) and the effects of government assistance and disruption intensity in long-term disruptions.

This study collected data from 626 SMEs in Australia in 2022 and analysed data using partial least squares structural equation modelling.

The study empirically confirms that digital capabilities, prior experience in disruptions, supplier proximity and relationships are antecedents of supply chain resilience of SMEs, with supply chain robustness as a mediator. It further confirms that SMEs' access to government assistance positively moderates the relationship between digital capabilities and supply chain robustness. The disruption intensity moderates the relationships between supplier proximity and supply chain robustness with supply chain resilience. Severe disruptions weaken the effects of prior disruption experiences and supplier relationships on supply chain resilience.

The findings inform SME practitioners of the importance of building supply chain robustness, leveraging their prior experience, supplier proximity and relationships and capabilities and flexibility for dynamic supply chain structures when disruptions are intense.

The novelty of our study is the use of the Contingent Resource-Based View to understand the effects of firm and supply chain-level antecedents on supply chain robustness and resilience, considering the contextual contingencies of disruption intensity and government assistance. The focus on long-term disruptions extends the conventional supply chain resilience studies on supply and demand disruptions of small scale. We also explore the firm-level effects of government assistance, which extends the commonly tested economic-level effects. Furthermore, we investigate supply chain robustness and resilience as different but connected constructs, deviating from common approaches. The finding that the relationship between digital capabilities and supply chain robustness, not the relationship between digital capabilities and supply chain resilience, becomes stronger with higher access to government support shows the importance of this approach to investigating specific effects.

According to extant Supply Chain Risk Management (SCRM) literature, manufacturing firms must align their choice of SC bridging or buffering strategies with their operating environment to achieve high plant performance and minimize SC disruption impacts. However, very few empirical studies have examined the relative performance of these strategies in dynamic industry environments. This study aims to address this research gap. This study also seeks to supplement the limited empirical research that has examined the empirical relationships between a firm’s Supply Base Complexity (SBC), the likelihood of SC disruptions, and plant performance.

This study uses data from a cross-sectional survey of 202 manufacturing firms in India. The data is analyzed, and the study hypotheses are tested using PLS path modeling and SPSS PROCESS Macro.

The study shows that increased SBC leads to an increased frequency of SC disruptions with a negative impact on plant performance. The study also finds that the firm’s implementation of SC bridging or buffering strategies effectively moderates this performance impact. However, the study results do not support the hypothesis that industry dynamism moderates the relative effectiveness of SC bridging or buffering strategies in mitigating the negative impact of SC disruptions.

The study adds to the limited empirical research examining the SC disruption risk associated with SBC and the resulting performance impact. It addresses a gap in extant research by evaluating the efficacy of SC bridging and buffering strategies in mitigating this performance impact in dynamic industry environments.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.

The adverse interactions between disruptions can increase the supply chain's vulnerability. Accordingly, establishing supply chain resilience to deal with disruptions and employing business continuity planning to preserve risk management achievements is of considerable importance. The aforementioned idea is discussed in this study.

This study proposes a multi-objective optimization model for employing business continuity management and organizational resilience in a supply chain for responding to multiple interrelated disruptions. The improved augmented e-constraint and the scenario-based robust optimization methods are adopted for multi-objective programming and dealing with uncertainty, respectively. A case study of the automotive battery manufacturing industry is also considered to ensure real-world conformity of the model.

The results indicate that interactions between disruptions remarkably increase the supply chain's vulnerability. Choosing a higher fortification level for the supply chain and foreign suppliers reduces disruption impacts on resources and improves the supply chain's resilience and business continuity. Facilities dispersion, fortification of facilities, lateral transshipment, order deferral policy, dynamic capacity planning and direct transportation of products to markets are the most efficient resilience strategies in the under-study industry.

Applying resource allocation planning and portfolio selection to adopt preventive and reactive resilience strategies simultaneously to manage multiple interrelated disruptions in a real-world automotive battery manufacturing industry, maintaining the long-term achievements of supply chain resilience using business continuity management and dynamic capacity planning are the main contributions of the presented paper.

A variety of buffer allocation methods exist to distribute an aggregated time buffer among project activities. However, these methods do not pay simultaneous attention to two key attributes of disruptive events that may occur during the construction phase: probability and impact. This paper fills this research gap by developing a buffer allocation method that takes into account the synergistic impact of these two attributes on project activities.

This paper develops a three-step method, calculating the probability that project activities are disrupted in the first step, followed by measuring the potential impact of disruption on project activities, and then proposing a risk-informed buffer allocation index by simultaneously integrating probability and impact outputs from the first two steps.

The proposed method provides more accurate results by sidestepping the shortcomings of conventional fuzzy-based and simulation-based methods that are purely based on expert judgments or historical precedence. Further, the paper provides decision-makers with a buffer allocation method that helps in developing cost-effective buffering and backup strategies by prioritizing project activities and their required resources.

This paper develops a risk-informed buffer allocation method that differs from those already available. The simultaneous pursuit of the probability and impact of disruptions distinguishes our method from conventional buffer allocation methods. Further, this paper intertwines the research domains of complexity science and construction management by performing centrality analysis and incorporating a key attribute of project complexity (i.e. the interconnectedness between project activities) into the process for buffer allocation.

This study investigates the possible curvilinear relationship between operational interdependency and supply chain performance as well as the contingency effect of supply chain disruptions, in terms of disruption orientation and disruption impact.

Path analysis was employed to test the hypotheses using the data collected from Chinese manufacturers.

The results confirm an inverted U-shape effect of operational interdependency. As level of buyer-supplier operational dependency increase, the supply chain performance is enhanced. However, the benefits of operational interdependency diminish beyond a certain point. Additionally, the findings of this study show the disruption orientations positively moderate the relationship between interdependency and performance, whereas the effect of disruption impact is not significant.

The findings of this study provide an explanation to the theoretical gap about the equivocal results of the effect of dependency, which provide new insights into the literature regarding buyer-supplier relationships. Furthermore, this paper identifies the moderating role of supply chain disruption in the relationship between operational interdependency and supply chain performance, which provide further explanation about the mixed results of the effect of dependency. The results confirmed that supply chain disruption orientation positively moderate the relationship between operational interdependency and supply chain performance.