Analysis of barriers to circularity for agricultural cooperatives in the digitalization era

Abstract

PurposeThis study aims to propose a novel framework for barriers to circularity within cooperative supply chains. The barriers in the adoption and implementation of circular economy principles are examined within a framework.Design/methodology/approachFuzzy best-worst method is used to calculate the weights of barriers and identify the prioritization of barriers to circularity within cooperative supply chain.Findings“Insufficient implementation of circular economy laws” was found as the most important barrier, followed by “Lack of information”, “Ineffective recycling policies”, “Lack of awareness for circular economy”, “Remanufacturing is a labor-intensive procedure”, “Inconsistent price policies in sources and products”, “Lack of environmental management system”, “Cost of implementation for green activities” and “Lack of R&D capability” barriers, respectively.Research limitations/implicationsThe number of participant professionals limits the conclusions of the study and reaching more general conclusions. A comprehensive research can be conducted by the participation of a greater number of professionals.Originality/valueSeveral studies analyzed the barriers to circularity; however, to the best of the authors' knowledge, no study has been taken an approach for barriers to circularity for cooperatives or cooperative supply chains.

Pushing Forward the Transition to a Circular Economy by Adopting an Actor Engagement Lens

“…In symbiotic ecosystems, third parties—like industrial associations and governmental bodies—often engage in relationally matching focal actors with other actors through orchestration (Ünal, Urbinati, and Chiaroni 2019), for instance, by organizing workshops (van Keulen and Kirchherr 2021), or fostering geographical proximity of different actors (Donner et al 2021). Finally, each and every actor in an ecosystem can contribute to establishing mutual understanding and trust when collaborating (Ada et al 2022; Agarwal, Tyagi, and Garg 2021). When actors perceive each other as understanding and trustworthy partners without experiencing power imbalances and/or conflicts of interest, they may engage in sharing operand (e.g., infrastructure) and operant resources (e.g., knowledge—Moggi and Dameri 2021).…”

“…This is, for instance, illustrated by partnerships between fashion-rental entrepreneurs and upcoming designers and luxury brands to give visibility to this CBM with effective product-service loops (Bodenheimer, Schuler, and Wilkening 2022) and partnerships to scale up reusable packaging models so that symbiotic ecosystems emerge (Bocken, Harsch, and Weissbrod 2022). In the aforementioned situations, actors may systematically select focal actors to collaborate with (Ada et al 2022), sign formal agreements like a “green deal” (Giorgi et al 2022), and/or set up initiatives to coordinate multi-actor collaborations across regions (Jaeger and Upadhyay 2020).…”

The Role of Digitalization in Facilitating Circular Economy

“…The key barriers that they identified from those studies are summarized in table 6. Ada et al (2020), focused on the impact of agricultural cooperatives in establishing circular systems in the digitalization era and proposed a new fuzzy Best Worst Method framework to identify the barriers against CE. The authors identified 51 barriers and found that these nine were the most important: (1) insufficient implementation of circular economy laws; (2) a lack of information; (3) ineffective recycling policies; (4) a lack of circular economy awareness; (5) remanufacturing is a labor-intensive procedure; (6) inconsistent price policies in sources and products; (7) a lack of an environmental management system; (8) the cost of green activity implementation; and 9) a lack of R&D capability.…”

A Platform Approach to Smart Farm Information Processing

“…Although data-driven solutions have provided various benefits in agriculture, data integration, processing, and usage processes and protocols are still prominent challenges that need to be addressed [13]. Some of these challenges are limited awareness and knowledge of digitalization [14], lack of standardization and suitable management to cope with fragmented and heterogeneous data [15], lack of high-quality data and proper analysis [16], privacy and security challenges in an entire smart farming ecosystem [17], and lack of compliance with uniform regulations and policies [18].…”