The supply chain resilience and data analytics capability has generated increased interest in academia and among practitioners. However, existing studies often treat these two streams of literature independently. Our study model reconciles two different streams of literature: data analytics capability as a means to improve information-processing capacity and supply chain resilience as a means to reduce a ripple effect in supply chain or quickly recover after disruptions in the supply chain. We have grounded our theoretical model in the organizational information processing theory (OIPT). The four research hypotheses are further tested using responses from 213 Indian manufacturing organizations collected via a survey-based pre-tested instrument. We further test our model using variance based structural equation modelling, popularly known as PLS-SEM. All of hypotheses were supported. The findings of our study offer a unique contribution to information systems (IS) and operations management (OM) literature. The findings further provide numerous directions to the supply chain managers. Finally, we note our study limitations and provide further research directions.
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Our study examines the relationship between information alignment (IA), collaboration (CO) and supply chain agility (SCAG) under the moderating effects of artificial intelligence driven big data analytics capability (AI-BDAC) and intergroup leadership (IGL). We have grounded our theoretical model in the resource based view (RBV) and contingency theory and further tested our research hypotheses using multi-informant data collected using a web-based pre-tested instrument from 613 individuals working in 193 humanitarian organisations drawn from 24 countries located on various continents across the globe. We tested our research hypotheses using variance based structural equation modelling (PLS-SEM). Our study offers interesting results which help to advance the theoretical debates surrounding technology-driven supply chain agility in the context of humanitarian settings. We further provide some directions to managers engaged in disaster relief operations, who are contemplating using emerging technologies to enhance collaboration and supply chain agility. Finally, we have outlined the limitations of our study and offer some future research directions.
Purpose
Worldwide, facing increasing resources pressure, more and more manufacturing firms aim to circular economy (CE), which is a system characterized by the application of remanufacturing principles and adoption of sustainable manufacturing practices. The purpose of this paper is to investigate the function of remanufacturing capability in influencing supply chain resilience in supply chain networks under the moderating effects of both flexible orientation and control orientation.
Design/methodology/approach
Data were gathered through a survey performed online in South Africa, and 150 participants completed the survey. Participants were mainly industry professionals holding senior administrative positions.
Findings
Results indicate that market factors, management factors and technical factors positively influence dynamic remanufacturing capability (DRC). More specifically, on one hand, market factors strongly influence DRC, whereas, on the other hand, both management and technical factors influence at lower level DRC. DRC has a positive influence on supply chain resilience. Flexible orientation is found to positively moderate the effect of DRC on supply chain resilience, whereas control orientation does not exert any moderating effect on DRC and supply chain resilience.
Originality/value
This is one of the first studies that explore research gaps between current vs desired remanufacturing capability requirements to achieve sustainability goals in CE.
Purpose
Cloud-based enterprise resource planning (ERP) enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure. The purpose of this paper is to empirically test the role of cloud-based ERP services on the performance of an organization. Here, the performance is categorized as supply chain performance and organizational performance that comprises of financial performance and marketing performance. Contingent resource-based view (RBV) theory was used to develop a theoretical framework in which supply base complexity (SBC) acts as a moderating variable on the relationship between cloud ERP and the performance.
Design/methodology/approach
Contingent RBV theory is used to explain the relationship between all identified variables in this paper. Partial least squares (PLS) based on structural equation modeling (SEM) is used to empirically test our theoretical framework.
Findings
The PLS-SEM analysis of 154 respondents supports the contingent RBV theory. Six hypotheses – out of the eight hypotheses formulated in this paper – are supported by data.
Research limitations/implications
Given this study was conducted in India where the potential of cloud ERP has not been fully implemented yet, the results may reflect more of perceived usefulness of this technology. The authors have attempted to understand the effect of SBC as a moderator in the relationship between cloud ERP and organizational performance which may not be the only moderator affecting this relationship among other potential moderators.
Originality/value
This paper empirically validates the theoretical framework based on the contingent RBV theory as it mitigates the static nature of the resource-based view approach suggested in the seminal article of Barney (1991).
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