Mobilising information systems scholarship for a circular economy: Review, synthesis, and directions for future research

Enhancing Coherence and Diversity in Multi-class Slogan Generation Systems

Many problems related to natural language processing are solved by neural networks and big data. Researchers have previously focused on single-task supervised goals with limited data management to train slogan classification. A multi-task learning framework is used to learn jointly across several tasks related to generating multi-class slogan types. This study proposes a multi-task model named slogan generative adversarial network systems (Slo-GAN) to enhance coherence and diversity in slogan generation, utilizing generative adversarial networks and recurrent neural networks (RNN). Slo-GAN generates a new text slogan-type corpus, and the training generalization process is improved. We explored active learning (AL) and meta-learning (ML) for dataset labeling efficiency. AL reduced annotations by 10% compared to ML but still needed about 70% of the full dataset for baseline performance. The whole framework of Slo-GAN is supervised and trained together on all of these tasks. The text with the higher reporting score level is filtered by Slo-GAN, and a classification accuracy of 87.2% is achieved. We leveraged relevant datasets to perform a cross-domain experiment, reinforcing our assertions regarding both the distinctiveness of our dataset and the challenges of adapting bilingual dialects to one another.

Product Lifecycle Information Flow in E-waste Handling: a Means to Increase Circularity?

Electronic waste (e-waste) is a growing waste stream. In Europe, e-waste is regulated by the Waste Electrical and Electronic Equipment (WEEE) Directive. Each manufacturer or importer is responsible for the end-of-life (EoL) treatment of the equipment it handles, although this task is usually outsourced to producer responsibility organizations (PROs) that collect and treat the e-waste. The WEEE regime has been criticized for focusing on waste handling according to the traditional linear economy, while, in a circular economy, the goal is to eliminate waste. Information sharing helps improve circularity, and digital technology is seen as enabling information transparency and visibility in the supply chain. However, there is need for empirical studies demonstrating the use of information in supply chains to improve circularity. We conducted a case study of a manufacturer, including its subsidiaries and PROs in eight European countries, in which we investigated the product lifecycle information flow related to e-waste. Our findings indicate that product lifecycle information is available, but that it is provided for purposes other than e-waste handling. Actors are willing to share this information, but it is not regarded as useful for EoL treatment since the actors involved in EoL handling believe that using this information could lead to delays and poorer performance in e-waste handling. Our findings contradict the optimistic view of digital technology as improving circularity in circular supply chain management. The findings further give reason to question the implementation of digital technology to improve the product lifecycle information flow as long as the involved actors do not request this information.

Emerging Technologies Supporting the Transition to a Circular Economy in the Plastic Materials Value Chain

Plastic waste has come to the forefront of academic and political debates as a global problem that demands an urgent solution. Promoted by policymakers, academia, and corporations alike, the circular economy model presents a viable path to reach more sustainable levels of development. Emerging and disruptive technologies can catalyse the transition to a circular economy, but their application to the transition of the plastic materials realm is not fully understood. Based on a systematic review of the literature, this paper aims to understand the role of key emerging technologies in the transition towards a circular economy in the plastic materials value chain, their potential impact, as well as the barriers of adoption and diffusion. Employing the ReSOLVE framework, the analysis reveals that rather than individual technologies, four technology sets associated with Industry 4.0, distributed economies, bio-based systems, and chemical recycling stand as major enablers of this transition. The complementarity of technologies and the change needed from a systemic perspective are discussed along with a proposal for governance and practical implementation pathway to overcome barriers and resistance to the transition.

Purchase Intentions for Brazilian Recycled PET Products—Circular Economy Opportunities

Circular economy involves structural changes in traditional business models and consumers’ behavior toward recycled products. The recycling of PET products is increasing but there is still a gap between consumption and demand for PET packaging in Brazil. In this research, waste reduction was examined under a projective scenario to the current ecological purposes in Brazil for reducing environmental pollution. In that manner, this paper aimed to comprehend the intention to purchase recycled PET products of Brazilian consumers. With a non-probabilistic and convenience sample, the study counts 422 participants. The method employed was based on structural equation modelling and partial least Squares, used to test the hypotheses of causality among the variables. Results showed the perception of low quality about recycled products reduced consumers’ intention to purchase. Additionally, the sustainability of recycled products positively influenced the intention to purchase. In addition, recycled products presented a negative impact on the perceived safety, which could influence the purchase of recycled products in Brazil. We conclude that the image that Brazilian consumers have about recycled products positively affects the intention to purchase.

Circularity for Electric and Electronic Equipment (EEE), the Edge and Distributed Ledger (Edge&DL) Model

In the transition to a circular focus on electric and electronic products, manufacturers play a key role as the originators of both the products and the information about the products. While the waste electric and electronic equipment (WEEE) directive’s contemporary focus is on handling the product as waste after its end of life, the circular economy focuses on retaining the product’s value with a restorative system. The polluter-pays principle requires producers of pollution to bear the costs of handling the pollution, leading to the extended producer responsibility (EPR) principle. This requires manufacturers to change their focus from their current passive role of out-sourcing end-of-life treatment to taking explicit responsibility for product management over an extended period of time. This paper investigates how a manufacturer can assume its responsibility to achieve circularity for its products. Based on our findings, three fundamental circularity principles, the circular electric and electronic equipment (CEEE) principles, for manufactures of electronic and electrical equipment are defined: (1) Serialize product identifiers, (2) data controlled by their authoritative source at the edge, and (3) independent actors’ access to edge data via a distributer ledger are the foundation of the Edge and Distributed Ledger (Edge&DL) model. We demonstrate the model through a case study of how to achieve circularity for lighting equipment. The CEEE principles and the demonstrated model contribute to building new circularity systems for electronic and electric products that let manufacturers undertake their extended product responsibility.

Data for Sustainable Platform Economy: Connections between Platform Models and Sustainable Development Goals

In recent years, the platform economy has been recognised by researchers and governments around the world for its potential to contribute to the sustainable development of society. Yet, platform economy cases such as Uber, Airbnb, and Deliveroo have created a huge controversy over their socioeconomic impact, while other alternative models have been associated with a new form of cooperativism. In parallel, the United Nations are advocating global sustainable development by promoting Sustainable Development Goals (SDGs), considering elements such as decent work, inclusive and sustainable economic growth, and fostering innovation. In any case, the SDGs have been also criticised for the lack of digital perspective. This dataset draws from two 2020 European projects’ (DECODE and PLUS) data collections and presents the possibility to compare different platform economy models and their connections with the SDGs.