Drivers of implementing big data analytics in food supply chains for transition to a circular economy and sustainable operations management

Kazancoglu, Yigit, Ozbiltekin Pala, Melisa, Deniz Sezer, Muruvvet, Luthra, Sunil and Kumar, Anil (2021) Drivers of implementing big data analytics in food supply chains for transition to a circular economy and sustainable operations management. Journal of Enterprise Information Management. ISSN 1741-0398 (In Press)

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Abstract / Description

Purpose:
The aim of this study is to evaluate Big Data Analytics (BDA) drivers in the context of food supply chains (FSC) for transition to a Circular Economy (CE) and Sustainable Operations Management (SOM).

Design/methodology/approach:
Ten different BDA drivers in FSC are examined for transition to CE; these are Supply Chains (SC) Visibility, Operations Efficiency, Information Management & Technology, Collaborations between SC partners, Data-driven innovation, Demand management & Production Planning, Talent Management, Organizational Commitment, Management Team Capability and Governmental Incentive. An interpretive structural modelling (ISM) methodology is used to indicate the relationships between identified drivers to stimulate transition to CE and SOM. Drivers and pair-wise interactions between these drivers are developed by semi-structured interviews with a number of experts from industry and academia.

Findings:
The results show that Information Management & Technology, Governmental Incentive and Management Team Capability drivers are classified as independent factors; Organizational Commitment and Operations Efficiency are categorized as dependent factors. SC Visibility, Data-driven innovation, Demand management & Production Planning, Talent Management and Collaborations between SC partners can be classified as linkage factors. It can be concluded that Governmental Incentive is the most fundamental driver to achieve BDA applications in FSC transition from linearity to CE and SOM. In addition, Operations Efficiency, Collaborations between SC partners and Organizational Commitment are key BDA drivers in FSC for transition to CE and SOM.

Originality/value:
The main contribution of the study is to analyse BDA drivers in the context of FSC for transition to CE and SOM. This study is unique in examining these BDA drivers based on FSC. We hope to find sustainable solutions to minimize losses or other negative impacts on these SC.

Research Implications:
The interactions between these drivers will provide benefits to both industry and academia in prioritising and understanding these drivers more thoroughly when implementing BDA based on a range of factors. This study will provide valuable insights. The results from this study will help in drawing up regulations to prevent food fraud, implementing laws concerning government incentives, reducing food loss and waste, increasing tracing and traceability, providing training activities to improve knowledge about BDA and focusing more on data analytics.

Item Type: Article
Uncontrolled Keywords: food supply chains; circular economy; sustainable operations management; big data analytics; drivers; interpretive structural modelling
Subjects: 600 Technology > 650 Management & auxiliary services
Department: Guildhall School of Business and Law
Depositing User: Anil Kumar
Date Deposited: 22 Mar 2021 11:47
Last Modified: 22 Mar 2021 11:50
URI: http://repository.londonmet.ac.uk/id/eprint/6419

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