Exploring recommendations for circular supply chain management through interactive visualisation

作者:

Highlights:

• Industries transition towards circular supply chain management.

• Recommenders need more transparency, explanations and interaction.

• We propose a visual exploration approach for industrial symbiosis identification.

• The system incorporates interactive node-link visualisation to explore suggestions.

• The sector-based approach amplifies practitioners' supply network intelligence.

摘要

The new era of circular supply chain management (CSCM) produces a new complex decision area for process managers. Part of it can be attributed to green procurement, in which a large number of potential ideas need to be reviewed that can sustain business. Such a large amount of data can quickly lead to information overload, especially without the presence of appropriate decision support tools. While there exists a range of visualisation methods that can aid the exploration of recommendations, there is a lack of studies that illustrate how these exploration techniques can facilitate the identification of CSCM activities. This paper showcases a study on how to ease the identification of new sustainable business opportunities through visual data exploration. Following the design science methodology, we have designed and evaluated a recommender system prototype (the IS Identification App) that supports sector-based identification of industrial symbiosis. The interactive visualisation enhances users with more control over recommendations and makes the recommendation process more transparent. Our case study results indicate that the interactive visualisation technique is a viable, fast and effective approach for exploring recommendations that increase the sustainability of the supply chain.

论文关键词:Circular supply chain management,Circular economy,Industrial symbiosis,Recommender systems,Exploration,Set visualisation

论文评审过程:Received 7 February 2020, Revised 13 October 2020, Accepted 22 October 2020, Available online 28 October 2020, Version of Record 30 November 2020.

论文官网地址:https://doi.org/10.1016/j.dss.2020.113431