Enos Weswa

Academic Paper Title: Optimization of Sports Good Recycling Management System Based on Internet of Things

Authors: Panhong Ren, Mengjian Nie, and Hui Ming

Journal: Wireless Communications and Mobile Computing

Year: 2021

Introduction

This critique evaluates the article Optimization of Sports Good Recycling Management System Based on Internet of Things by Ren, Nie and Ming (2021), published in Wireless Communications and Mobile Computing. The purpose is to summarise the paper’s central argument and apply the Salford Business School “What the Papers Say – Analysis Pro Forma” to assess its research quality, methods and presentation. The critique distinguishes clearly between the authors’ claims and my analytical interpretation, ensuring the reader can understand the contribution and limitations without consulting the paper. 

Summary of the Paper

The article aims to design and optimise an IoT-enabled recycling management system for sports goods. The authors analyse the recycling logistics process, storage points, transportation nodes and operational bottlenecks, before proposing an IoT-driven information platform integrating sensing, data transmission, cloud processing and optimisation algorithms. The research objective is to improve traceability, reduce labour-intensive management, strengthen information flow and enhance logistics coordination across recycling nodes. The authors implement a prototype platform, including RFID sensing, vehicle scheduling optimisation and an image-based classification module using a simplified LeNet-5 model. Reported results show improvements in monitoring, sorting accuracy and route optimisation, leading the authors to conclude that IoT technologies are effective in addressing sports-goods recycling inefficiencies (Ren, Nie & Ming 2021). 

Quality of the Research

1. Clarity of the Research Question

The research question—how IoT can optimise sports-goods recycling management—is clearly stated throughout the introduction and framework description (Ren, Nie & Ming 2021). 

2. Importance and Relevance

The topic is relevant given global emphasis on circular-economy systems and increasing adoption of IoT in logistics. Prior work cited in the paper also highlights the importance of IoT-enabled waste management (e.g., Saha et al. 2017; Mahmood & Zubairi 2019).

3. Originality

The application to sports-goods recycling is novel. Although IoT in waste management is well documented, the sports-goods sub-sector remains under explored, lending originality to the authors’ contribution.

4. Background Research

The literature review covers IoT sensing, logistics, network modelling and resource recovery. While it demonstrates breadth, the review is descriptive and doesn’t critically synthesise the gaps the paper aims to address. There is limited engagement with sustainability theory, reverse-logistics frameworks or behavioural aspects of product return.

5. Ethical Considerations

The paper does not adequately address ethical issues such as data privacy, consumer tracking or the environmental cost of IoT hardware—an important omission for research involving sensor networks and cloud data.

The Research Method

Method Summary

The authors use a systems-design approach: mapping recycling processes, proposing an IoT architecture, building an information platform and testing modules such as image classification and path optimisation (Ren, Nie & Ming 2021). 

Appropriateness

The design-science approach suits the engineering nature of the question. However, the method lacks detail regarding sampling, testing environments, datasets, evaluation metrics and validation procedures.

Adequacy of Description

Technical components—RFID, cloud architecture, neural-network configuration—are thoroughly described. Yet the operational testing context (e.g., live trials, controlled simulations) is missing, making it difficult to confirm practical effectiveness.

Correctness of Analysis

Algorithm comparisons (e.g., genetic algorithm vs distance-first algorithm) are plausible, though results are presented without statistical justification.

Support for Conclusions

The conclusions are optimistic but not fully supported by rigorous empirical evidence. The prototype shows potential, but generalisability is limited.

Quality of Presentation

The paper is clearly structured and uses diagrams well (e.g., recycling network diagrams on pages 3–4, platform architecture on page 7). However, narrative flow is dense, and some sections—especially the optimisation algorithms—could benefit from clearer explanation and abstraction. Definitions of key terms such as “returned good flow” or “cloud model theory” are brief and require additional elaboration.

Conclusion

The article aligns with module themes such as IoT architectures, digital transformation of logistics, and circular-economy design. It would benefit from stronger integration with IS theories such as socio-technical systems or process-innovation models to extend its contribution beyond engineering design.

Reference.

Ren, P., Nie, M., & Ming, H. (2021). Optimization of Sports Good Recycling Management System Based on Internet of Things. Wireless Communications and Mobile Computing.

Basden, A. (2009). Critical Management Perspectives on Information Systems. Taylor & Francis. 

McKeown, N. & Durkin, M. (2017). The Seven Principles of Digital Business Strategy. Business Expert Press. 

McKeown, N. & Durkin, M. (2017). Digital Business Strategy (Chapter 1). Business Expert Press. 

Perkin, N. & Abraham, P. (2017). Building the Agile Business Through Digital Transformation. Kogan Page. 

Stahl, B. C. (2008). Information Systems: Critical Perspectives. Taylor & Francis.