Smart circular supply chains to achieving SDGs for post-pandemic preparedness
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Date
2022
Authors
Yasanur Kayikci
Yigit Kazancoglu
Çisem Lafci
Nazlican Gozacan
Sachin Kumar Kumar Mangla
Journal Title
Journal ISSN
Volume Title
Publisher
Emerald Group Holdings Ltd.
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Purpose: The coronavirus disease 2019 (COVID-19) pandemic created heavy pressure on firms by increasing the challenges and disruptions that they have to deal with on being sustainable. For this purpose it is aimed to reveal the role of the smart circular supply chain (SCSC) and its enablers towards achieving Sustainable Development Goals (SDGs) for post-pandemic preparedness. Design/methodology/approach: Total interpretive structural modelling and Matrice d'Impacts Croises Multipication Applique' a un Classement (MICMAC) have been applied to analyse the SCSC enablers which are supported by the natural-based resource view in Turkey's food industry. In this context industry experts working in the food supply chain (meat sector) and academics came together to interpret the result and discuss the enablers that the supply chain experienced during the pandemic for creating a realistic framework for post-pandemic preparedness. Findings: The results of this study show that “governmental support” and “top management involvement” are the enablers that have the most driving power on other enablers however none of them depend on any other enablers. Originality/value: The identification of the impact and role of enablers in achieving SDGs by combining smart and circular capabilities in the supply chain for the post-pandemic. © 2022 Elsevier B.V. All rights reserved.
Description
Keywords
Circular Economy, Industry 4.0, Natural Resource-based Review, Smart Circular Supply Chain, Sustainable Development Goals, Total interpretive Structural Modelling, 0, Circular Economy, Smart Circular Supply Chain, Sustainable Development Goals, Industry 4.0, Industry 4, Total Interpretive Structural Modelling, Natural Resource-Based Review, Total Interpretive Structural Modelling
Fields of Science
0502 economics and business, 05 social sciences
Citation
WoS Q
Scopus Q

OpenCitations Citation Count
33
Source
Journal of Enterprise Information Management
Volume
35
Issue
1
Start Page
237
End Page
265
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Citations
CrossRef : 34
Scopus : 49
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Mendeley Readers : 244
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