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Grounding on relational view and contingent resource-based views, the authors investigate the conditional indirect effect of Supply Chain Relational Practices (SCRPs) on supply chain performance (SCP) through proactive and reactive supply chain resilience (SCRE) capabilities at different levels of network complexity (NC).

The authors adopt an “exploratory sequential mixed methods design” combining the qualitative and quantitative approaches under a positivist paradigm. The qualitative method is primarily used to contextualize and develop better measurements of the factors and variables using content analysis of the field studies. This then informs the quantitative phase which conducts a questionnaire survey among the apparel manufacturing firms in Bangladesh. The authors analyzed the quantitative data using Partial Least Square based Structural Equation Modelling. The authors also used PROCESS integrated regression analysis to test conditional indirect effects.

Our research findings indicate that the indirect effect of SCRPs on SCP through proactive and reactive SCRE is positive and significant. It also finds that the conditional indirect effect is high at higher NC.

The results have immense practical implications as it proposes to enhance relational practices in order to develop SCRE as a contingent resource to mitigate disruptions. This will also help the supply chain (SC) managers to work through smoothly at different levels of supply chain NC and improve SCP.

Extant literature does not provide a deeper understanding of the impact of SCRPs on SCP, while SCRE and NC influence the link. Therefore, investigation of the conditional direct and indirect effect of SCRPs on SCP through proactive and reactive SCRE at different levels of NC is novel in SC management literature.

This study aims to investigate the conditional direct and indirect effects of supply chain relational capital (RC) on supply chain sustainability via sustainability governance.

In line with the study’s aims, a quantitative survey-based approach was adopted. This study uses a random sample of 272 manufacturing firms from the apparel industry in Bangladesh. This study assesses the measurement model using partial least square-based structural equation modelling and test the proposed hypotheses using the Hayes PROCESS.

The results reveal that the indirect effect of supply chain RC on supply chain sustainability via sustainability governance is significant. While at low levels of network complexity (NC), the conditional indirect effect of supply chain RC on supply chain sustainability via sustainability governance is significant, this study finds that such indirect effects are insignificant at high levels of NC. This study further shows that NC positively moderates the relationship between supply chain RC and supply chain sustainability.

While previous studies have demonstrated the role of RC in adopting sustainability practice, this study explores this link further by investigating the conditional direct and indirect effects of supply chain relational capital on supply chain sustainability via sustainability governance.

This research aims to develop a decision support framework to determine the optimal strategies for mitigating supply chain sustainability (SCS) barriers.

To operationalize the research objectives, both qualitative and quantitative methods were adopted. The qualitative phase comprised a field study, while a quality function deployment approach and optimisation technique were used in the quantitative phase.

This study finds that a lack of support from top management and cost and utility supply problems are the primary barriers to SCS. This study also finds that incentives for suppliers to implement sustainability practices, awareness building among supply chain members and supplier development are the main strategies to mitigate the barriers.

The findings of this study will assist the supply chain managers in prioritizing sustainability barriers and implementing the optimal strategies to mitigate the barriers.

Founded on the stakeholder theory and dynamic capability view, this study developed a unique decision support framework to identify appropriate strategies for mitigating SCS barriers while optimizing the social, environmental and economic objectives of the supply chain.

Drawing on the dynamic capability view (DCV), this research determines the suitable configurations of resilience strategies for sustainable tourism supply chain performance amidst “extreme” disruptive events affecting the entire supply chain.

This research applies a multi-study and multi-method approach. Study 1 utilizes in-depth interviews to identify a list of tourism supply chain sustainability risks and resilience strategies. Study 2, using quality function deployment (QFD) technique, determines the most important resilience strategies corresponding to highly significant risks. Study 3, on the other hand, adopts a fuzzy set qualitative comparative analysis (fsQCA) to determine the best recipe of resilience strategies and risks to make the tourism supply chain performance sustainable.

The findings reveal that sustainable tourism performance during an extreme disruptive event (e.g. COVID-19 health crisis) depends on the combined effect of tourism resilience strategies and risks instead of their individual effect.

The research findings offer significant managerial implications. Managers may experiment with multiple causal conditions of risks and resilience strategies to engender the expected outcome.

This research extends current knowledge on tourism supply chain and offers insights for managers to mitigate the risks and ensures sustainable performance in the context of extreme disruptive events.

Fake news on social media about COVID-19 pandemic and its associated issues (e.g. lockdown) caused public panic that lead to supply chain (SC) disruptions, which eventually affect firm performance. The purpose of this study is to understand how social media fake news effects firm performance, and how to mitigate such effects.

Grounded on dynamic capability view (DCV), this study suggests that social media fake news effects firm performance via SC disruption (SCD) and SC resilience (SCR). Moreover, the relation between SCD and SCR is contingent upon SC learning (SCL) – a moderated mediation effect. To validate this complex model, the authors suggest effectiveness of using partial least squares structural equation modeling (PLS-SEM). Using an online survey, the results support the authors’ hypotheses.

The results suggest that social media fake news does not affect firm performance directly. However, the authors’ serial mediation test confirms that SCD and SCR sequentially mediate the relationship between social media fake news and firm performance. In addition, a moderated serial mediation test confirms that a higher level of SCL strengthens the SCD–SCR relationship.

This work offers a new theoretical and managerial perspective to understand the effect of fake news on firm performance, in the context of crises, e.g. COVID-19. In addition, this study offers the advancement of PLS as more robust for real-world applications and more advantageous when models are complex.

Prior studies in the SC and marketing domain suggest different effects of social media fake news on consumer behavior (e.g. panic buying) and SCD, respectively. This current study is a unique effort that investigates the ultimate effect of fake news on firm performance with complex causal relationships via SCD, SCR and SCL.

Drawing on a dynamic capability view, this study develops a decision support model that determines the most suitable configuration of strategies and challenges to adopt additive manufacturing (AM) to expedite digital transformation and performance improvement of the surgical and medical device (SMD) supply chain.

To investigate the research objective, a multi-method and multi-study research design was deployed using quality function deployment and fuzzy set qualitative comparative analysis.

The study finds that only resilience strategies or negation (i.e. minimisation) of challenges are not enough; instead, a configuration of resilience strategies and negation of challenges is highly significant in enhancing performance.

SMD supply chain decision-makers will find the decision support model presented in this study as beneficial to be resilient against various challenges in the digital transformation of service delivery process.

This study builds new knowledge of the adoption of AM technology in the SMD supply chain. The decision support model developed in this study is unique and highly effective for fostering digital transformation and enhancing SMD supply chain performance.

Following a contingent resource-based view (CRBV) perspective, this paper aims to explore the operating context in which supply chain resilience (SCRE) is likely to enhance the supply chain performance (SCP) of organizations. More specifically, the authors developed the ‘Supply Chain Resilience’ model wherein we considered two important exogenous context variables (supply chain relational practices [SCRPs] and network complexities [NCs]) and studied their moderating roles on the relationship between SCRE and SCP. The authors also investigated the conditional effect of SCRE on SCP at different levels of SCRPs and NCs.

This study used both qualitative and quantitative approaches. For the qualitative approach, a field study was undertaken, while the quantitative study was conducted via the use of a survey questionnaire of 274 apparel manufacturers and their suppliers in Bangladesh. The authors applied Hayes PROCESS enabled multiple regression analysis and structural equation modelling to statistically test the proposed research models.

The research findings revealed that SCRP and NC individually moderated the link between SCRE and SCP. The link between SCRE and SCP was strengthened via the interaction effect of SCRP and NC, even if the NC value was high.

The findings will assist supply chain managers in managing supply chain performance during uncertainties by strengthening resilience capability at different levels of NCs and SCRPs.

Drawing on CRBV, the authors studied how the conditional effects of exogenous variables (SCRP and NC) moderated the relationship between SCRE and SCP in both two- and three-way interactions, which is a novel approach in the SCRE literature and also extends the theoretical perspective of CRBV.

This paper aims to investigate the conditional indirect effect of innovativeness on performance via supply chain agility (SCA) in the service industry at higher and lower collaborative relationships.

The hypothesised model is operationalised with survey data from 245 Australian service firms collected via LinkedIn and analysed using structural equation modelling and fuzzy set qualitative comparative analysis (fsQCA).

The analysis found that SCA significantly mediates the relationship between innovativeness and performance. Further, the conditional indirect effect of innovativeness on performance via SCA was significant when the collaborative relationship was high. Results also revealed that a configuration of both innovativeness and agility better predicts performance.

This study is an early attempt to investigate SCA in service industries by scrutinizing SCA from an innovative point of view. While previous studies have demonstrated the role of innovativeness in enhancing a firm's performance, this study explores this link further by investigating the conditional indirect effect of innovativeness on performance via SCA at different levels of collaborative relationships.

Sharing economy-based service platforms are a relatively new way of delivering services that have received increasing attention from both practitioners and researchers. However, current research in the area is still developing in terms of offering practical insight in conjunction with a decision model that may help to determine optimal strategies for efficient service design in the sharing economy from a service triad perspective. Exploring this gap in the literature, this paper aims to develop and apply a decision model that enables managers to identify and prioritise the efficiency attributes of sharing economy-based services. It also aids in designing optimal strategies to enhance efficiency over time based on the insights obtained from users (buyers and sellers) and platform providers.

This study adopts a mixed-methods approach. The qualitative approach comprised an extensive literature review followed by in-depth interviews, and the quantitative approach adopted the quality function deployment (QFD) integrated optimisation technique to design and prioritise the most optimal strategy emanating from the application of a decision model.

The findings revealed that establishing global distribution, continued technological research and development (R&D) and enhancing the transactional platform are the most important strategies in the context of sharing economy platform providers (e.g. accommodation-based-platform service providers). This study also revealed that as the importance weights of the efficiency attributes changed over time, so too did the portfolio of strategies used to attain an optimal efficiency level.

The decision model brings a richer conceptual understanding of the dynamic changes over time that occur in the business ecosystem. It also allows managers of sharing economy-based platforms to select optimal strategies and make astute decisions towards achieving efficient service design.

Sustainable development goals and the climate change agenda are becoming widely promoted topics of research for the 21st century. The role of cities is increasingly recognised as central to investigating these topics. Yet, the field of informal sector entrepreneurship which so many urban entrepreneurs in developing countries depend upon is seldom considered. To redress this imbalance, this study aims to develop a decision model in accordance with institutional theory (IT) and resource dependency theory (RDT) for city managers to deploy. The model identifies and prioritises optimal strategies to address the three areas of sustainability requirements environment society and economy within the study context of Bangladesh.

This study used a mixed methods research design. In the qualitative part, the authors identified the three areas of sustainability requirements (i.e. environment, society and economy) and their corresponding strategies involving the informal sector that operates within the urban environment. In the quantitative part, the authors applied fuzzy quality function deployment (QFD) integrated with the 0-1 non-linear optimisation technique to identify optimal strategies.

The findings show that strategies such as legitimate frameworks, waste management, allocation of urban public space and training programs contribute in important ways to the three areas of sustainability requirements.

The proposed decision model will assist policy-makers and city managers to prioritise sustainability requirements and implement optimal strategies to address those requirements.

Through the integration of IT and RDT, the decision model developed in this study is unique in its application to urban-based informal entrepreneurship in the context of developing countries. The effective application of the fuzzy QFD approach and the optimisation model in the context of urban-based informal entrepreneurship also offers unique contributions to the field of study.