Analyzing Barriers of Circular Food Supply Chains and Proposing Industry 4.0 Solutions

被引:78
作者
Ada, Nesrin [1 ]
Kazancoglu, Yigit [2 ]
Sezer, Muruvvet Deniz [3 ]
Ede-Senturk, Cigdem [3 ]
Ozer, Idil [3 ]
Ram, Mangey [4 ,5 ]
机构
[1] Ege Univ, Dept Business Adm, TR-35100 Izmir, Turkey
[2] Yasar Univ, Dept Logist Management, TR-35100 Izmir, Turkey
[3] Yasar Univ, Dept Business Adm, TR-35100 Izmir, Turkey
[4] Graph Era Deemed Be Univ, Dept Math Comp Sci & Engn, Dehra Dun 248002, Uttarakhand, India
[5] Peter Great St Petersburg Polytech Univ, Inst Adv Mfg Technol, St Petersburg 195251, Russia
关键词
circular economy; food supply chain; industry; 4.0; sustainability; BUSINESS MODELS; ECO-INNOVATION; SUSTAINABILITY PRACTICES; BIG DATA; ECONOMY; WASTE; MANAGEMENT; DRIVERS; IMPLEMENTATION; CHALLENGES;
D O I
10.3390/su13126812
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The concept of the circular economy (CE) has gained importance worldwide recently since it offers a wider perspective in terms of promoting sustainable production and consumption with limited resources. However, few studies have investigated the barriers to CE in circular food supply chains. Accordingly, this paper presents a systematic literature review of 136 papers from 2010 to 2020 from WOS and Scopus databases regarding these barriers to understand CE implementation in food supply chains. The barriers are classified under seven categories: "cultural", "business and business finance", "regulatory and governmental", "technological", "managerial", "supply-chain management", "knowledge and skills". The findings show the need to identify barriers preventing the transition to CE. The findings also indicate that these challenges to CE can be overcome through Industry 4.0, which includes a variety of technologies, such as the Internet of Things (IoT), cloud technologies, machine learning, and blockchain. Specifically, machine learning can offer support by making workflows more efficient through the forecasting and analytical capabilities of food supply chains. Blockchain and big data analytics can provide the necessary support to establish legal systems and improve environmental regulations since transparency is a crucial issue for taxation and incentives systems. Thus, CE can be promoted via adequate laws, policies, and innovative technologies.
引用
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页数:29
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