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      Linking green supply chain management practices with competitiveness during covid 19: The role of big data analytics

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          Abstract

          Although the global green supply chain management (GSCM) practice has attracted considerable scholarly attention, its efficacy for environmental management systems (EMS) and market competitiveness during Covid-19 has not been fully capitalized. Therefore, the existing literature indicates that the important link between GSCM, EMS, and market competitiveness is missing as supply management is crucial to maintaining market competitiveness. To fill this research gap, the current study examines whether EMS affects the relationship between GSCM practices and market competitiveness. We also propose the moderating role of big data analytics and artificial intelligence (BDA-AI) and environmental visibility on these associations from a Covid-19 perspective. We tested a proposed model using the primary data ( N = 283) from regression-based structural equation modeling (SEM). The results provide empirical support for the impact of GSCM on ESM and market competitiveness. Furthermore, the results show that BDA-AI and environmental visibility strengthen the positive relationship between GSCM-EMS and EMS and market competitiveness, respectively. Current research provides thoughtful insights for supply chain practitioners, policymakers, managers, and academics that organizations should opt for formal EMS, BDA-AI, and environmental visibility to achieve market competitiveness, even in times of crisis such as Covid-19.

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          A new criterion for assessing discriminant validity in variance-based structural equation modeling

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            Sources of method bias in social science research and recommendations on how to control it.

            Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms "method" and "method bias" and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.
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              • Record: found
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              • Article: not found

              Responding to Covid-19 — A Once-in-a-Century Pandemic?

              Bill Gates (2020)
                Bookmark

                Author and article information

                Journal
                Technol Soc
                Technol Soc
                Technology in Society
                Elsevier Ltd.
                0160-791X
                0160-791X
                17 June 2022
                August 2022
                17 June 2022
                : 70
                : 102021
                Affiliations
                [1]Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Nanshan District, Shenzhen, 518060, Guandong, China
                Author notes
                []Corresponding author.
                [∗∗ ]Corresponding author.
                Article
                S0160-791X(22)00162-2 102021
                10.1016/j.techsoc.2022.102021
                9439874
                36090699
                c2b3b51a-960e-4d35-a70d-270ae22bef8a
                © 2022 Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 15 January 2022
                : 6 March 2022
                : 9 June 2022
                Categories
                Article

                green supply chain management practices,environmental visibility,environmental management system,market competitiveness,big data analytics-artificial intelligence

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