PurposeAlthough big data may enhance the visibility, transparency, and responsiveness of supply chains, whether it is effective for improving supply chain performance in a turbulent environment, especially in mitigating the impact of COVID-19, is unclear. The research question the authors addressed is: How do logistics firms improve the supply chain performance in COVID-19 through big data and supply chain integration (SCI)?Design/methodology/approachThe authors used a mixed-method approach with four rounds of data collection. A three-round survey of 323 logistics firms in 26 countries in Europe, America, and Asia was first conducted. The authors then conducted in-depth interviews with 55 logistics firms.FindingsIn the first quantitative study, the authors find mediational mechanisms through which big data analytics technology capability (BDATC) and SCI influence supply chain performance. In particular, BDATC and SCI are two second-order capabilities that help firms develop three first-order capabilities (i.e. proactive capabilities, reactive capabilities, and resource reconfiguration) and eventually lead to innovation capability and disaster immunity that allow firms to survive in COVID-19 and improve supply chain performance. The results of the follow-up qualitative analysis not only confirm the inferences from the quantitative analysis but also provide complementary insights into organizational culture and the institutional environment.Originality/valueThe authors contribute to supply chain risk management by developing a three-level hierarchy of capabilities framework and finding a mechanism with the links between big data and big disaster. The authors also provide managerial implications for logistics firms to address the new management challenges posed by COVID-19.

PurposeThis study aims to explore how relational and contractual governance affect crowdsourcer satisfaction under boundary conditions, including internal (i.e. task complexity) or external (i.e. environmental complexity) factors.Design/methodology/approachWe empirically validate the hypotheses using survey data collected from 255 crowdsourcers on a leading platform (i.e. Zhubajie.com). Partial least squares technique and hierarchical regression analysis are used to test the research model.FindingsBoth forms of governance mechanisms positively affect crowdsourcer satisfaction. Task complexity negatively moderates the linkage of relational governance and crowdsourcer satisfaction. However, environmental complexity weakens the positive effect of contractual governance but enhances the effect of relational governance on satisfaction.Originality/valueThis study deepens the current understanding of governance mechanism in crowdsourcing by discovering the effectiveness of contractual and relational governance. We also contribute to the governance and crowdsourcing literature by revealing the mechanisms of how governance takes effect under task and environmental complexities.

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