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.

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The Covid-19 pandemic has emerged as one of the most disquieting worldwide public health emergencies of the 21st century and has thrown into sharp relief, among other factors, the dire need for robust forecasting techniques for disease detection, alleviation as well as prevention. Forecasting has been one of the most powerful statistical methods employed the world over in various disciplines for detecting and analyzing trends and predicting future outcomes based on which timely and mitigating actions can be undertaken. To that end, several statistical methods and machine learning techniques have been harnessed depending upon the analysis desired and the availability of data. Historically speaking, most predictions thus arrived at have been short term and country-specific in nature. In this work, multimodel machine learning technique is called EAMA for forecasting Covid-19 related parameters in the long-term both within India and on a global scale have been proposed. This proposed EAMA hybrid model is well-suited to predictions based on past and present data. For this study, two datasets from the Ministry of Health & Family Welfare of India and Worldometers, respectively, have been exploited. Using these two datasets, long-term data predictions for both India and the world have been outlined, and observed that predicted data being very similar to real-time values. The experiment also conducted for statewise predictions of India and the countrywise predictions across the world and it has been included in the Appendix.

Purpose Differences in institutional environment and governance structures pave the way for heterogeneous nature of different businesses; this, in turn, shapes the way various sections of society act toward each other enacting their responsibilities. Taking into account the unique institutional environment and governance structures of firms in developing economies, this paper aims to build on the “stakeholder theory” to address the issue of the implementation of corporate social responsibilities (CSR) practices in these economies, particularly India. This paper also aims to uncover the saliency (legitimacy and power) of different stakeholder groups on different aspects of a firm’s CSR activities. Further, as most of the firms in developing economies are family-run firms, the paper examines role of organizational leadership in shaping firms’ CSR strategies. Design/methodology/approach Integrating literature on “stakeholder theory” and CSR, this paper examines the implementation of different CSR practices by family-run firms in India. This paper uses survey research to collect data from 80 privately held family firms operating in apparel and textiles industry in India. The data have been collected from respondents holding top leadership positions in the sample firms. Findings The findings indicate that pressure from primary stakeholders (i.e. customers, employees and shareholders) and CSR-oriented leadership belief significantly influence organizational implementation of CSR practices, whereas pressure from secondary stakeholder (i.e. community groups and non-governmental organizations) was found to be insignificant. Further, CSR-oriented leadership belief moderated the relationship between primary stakeholder pressure and organizational implementation of CSR practices. The findings equally highlighted lower saliency of secondary stakeholder’s legitimacy and power because of weak institutional mechanisms, while on the other hand, the primary stakeholders exert considerable power because of the direct nature of transactional legitimacy, further accentuated by the governance structure in family firms. Originality/value This paper is among the very few studies that address the issue of CSR among family-run businesses in developing economies. Existing frameworks on analyzing firm’s implementation of CSR practices does not recognize the inherent heterogeneity among different stakeholder groups. Recognizing that different stakeholders have different levels of influence over firms, this paper categorized the stakeholders’ groups into primary and secondary to analyze their differential impact over firms. Additionally, given the critical role of leadership belief in the implementation of CSR practices, this paper analyzed the moderated effect of CSR-oriented leadership belief toward developing a more robust model of CSR implementation.

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