Purpose: The purpose of this paper is to examine how firms can develop business risk resilience from supply chain disruption events, by developing big data analytics (BDA) capabilities within their organization. The authors test whether BDA mediates the impact of institutional response to supply chain disruption events, and information technology infrastructure capabilities (ITICs), on firm’s ability to develop risk resilience from supply chain disruption events.Design/methodology/approach: The study is based on survey data collected from 225 firms, spread across several sectors in the USA and Europe. The respondents are primarily senior and middle management professionals who have experience within the information technology (IT) and supply chain domain. Validity and reliability analyses were performed using SPSS and AMOS; and covariance-based structural equation modeling was used to test the hypothesis.Findings: The analysis reveals two significant findings. First, the authors observe that institutional experience with managing supply chain disruption events has a negative impact on firm’s ability to develop business risk resilience. However, if the organizations adopt BDA capabilities, it enables them to effectively utilize resident firm knowledge and develop supply chain risk resilience capacity. The results further suggest that BDA positively adds to an organization’s existing IT capabilities. The analysis shows that BDA mediates the impact of ITIC on the organization’s ability to develop risk resilience to supply chain disruption events.Originality/value: This study is one of the few works that empirically validate the important role that BDA capabilities play in enabling firms develop business risk resilience from supply chain disruption events. The study further provides a counterpoint to the existing perspective within the supply chain risk management literature that institutional experience of managing past supply chain disruption events prepares the organization to deal with future disruption events. This paper adds to our understanding of how, by adopting BDA capabilities, firms can develop supply chain risk resilience from disruption events.

Purpose: As organizations globalize, they are facing twin challenges of (1) how to develop actionable intelligence from the vast amount of data flowing into their organization and (2) how to effectively manage the increasing risks to their supply chain. Therefore, the purpose of this paper is to bring these two issues on a single platform to understand how firms can effectively predict supply chain risk by developing and using BDA capabilities, through an automated risk alert tool.Design/methodology/approach: The authors used a questionnaire-based survey methodology supported by secondary data to collect information related to managerial perceptions on how firms can develop a risk alert tool by improving BDA capabilities. A database of 213 senior and middle-level managers was developed and used to test the proposed hypothesis. Using econometric techniques, the authors identify the conditions necessary for such an automated risk management tool to be effective.Findings: The results suggest that if organizations focus on developing an effective IT infrastructure supported by a strong BDA capability, they will be able to leverage these capabilities to develop an effective risk management tool. Moderating influences of Upstream and Downstream Supply Chain IT Infrastructure capabilities were also observed on different types of BDA capabilities within a firm. In conclusion, it was argued that the effectiveness of a risk alert tool is dependent on how well firms harness big data analytics capability.Originality/value: The value of the research stems from the fact that it uses managerial surveys to identify specific BDA capabilities that can enable firms to develop risk resilience capabilities. In addition, the article is one of the few empirical studies that aims to identify how firms can use BDA capabilities within a supply chain context to develop an automated risk alert tool. The article, therefore, contributes to the literature that identifies the value of BDA capabilities within the context of supply chain risk management.

With increasing global exposure, organisations have started to witness supply chain risks that they traditionally were not exposed to. This article therefore attempts to answer the research question of how environmental uncertainty within a firm’s supply chain, impacts firm financial performance. We further evaluate the role of supply chain risk management practices in mitigating the negative impact of such disruption events. To answer the research question, we conduct a literature review and develop the corresponding hypothesis. We test our hypothesis using both primary and secondary data. The results show that environmental uncertainty has a negative impact on firm financial performance, with entrepreneurial managerial capitalism mediating the impact. However, organisations that adopt macro and network supply chain risk management practices are able to improve managerial decision making frame, and mitigate the negative impact of environmental uncertainty on firm financial performance. The article concludes with our findings, along with managerial and practitioner implications of the research.

This article evaluates how firms are able to enhance the effectiveness of their Risk Management Infrastructure (RMI) by using Big Data Analytics (BDA) to improve their risk resilience capability. A theoretical model is developed and the corresponding hypothesis is tested through a survey instrument and quantitative analysis. The results show that if firms adopt BDA capabilities then it positively moderates the impact of RMI on risk resilience, improving the effectiveness of a risk management infrastructure.

Within the last decade, research has focussed on corporate social responsibility (CSR) practices as a strategic tool that enables firms to improve stakeholder perception, brand image and corporate reputation. However, one area that remains understudied is the role played by CSR practices in managing corporate reputation under conditions of supply chain risk. To answer this research question, we conduct a literature review and develop the corresponding hypothesis. We test our hypothesis using quantitative analysis of both primary and secondary data collected from organizations dispersed globally. The results highlight that under conditions of supply chain network disruption risk, CSR practices play an important role in enabling firms to manage the negative impact of such risk drivers on corporate reputation. The study further suggests that CSR practices positively impact supply chain risk management (SCRM) practices and are a necessary condition for SCRM practices to be effective in improving corporate reputation of organizations.

This article presents a research model that defines how external drivers impact financial performance outcomes, and the role played by strategic practices (especially CSR) in reducing the negative impact of such external influences. Applying strategic orientation theory, risk management theory, and CSR theory as the encompassing theoretical rationale, the conceptual framework defines the research idea and the research model provides the empirically testable model that identifies key variables with valid instrument measures. The results indicate that although external supply chain risk drivers do negatively impact a firm’s financial performance, the influence of these risk events can be mitigated if firms adopt focused strategic practices. The results highlight the significant role played by CSR strategic practices in enabling firms to develop resilience from disruption events. In our research model, CSR, as an organizational linkage practice, is positioned in between upfront strategic flow and back-end performance flow. It suggests that CSR success is only possible when CSR is implemented broadly throughout organizational processes. Based on the empirical results, lessons and implications are presented for theoretical and managerial insights and future research.