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Research project

Forecasting and influencing product returns and fraud rates in a Covid-19 world

Project overview

Covid-19 has significantly aggravated the problem of high product returns rates, which have been increasing over the last few years. This is a significant challenge for retailers and society, causing economic, social and ecological harm. Returns lead to added complex processing, transportation and wasted resources, as many products cannot be resold and risk going to landfill.
Online shopping thrived during the lockdown, and many retailers extended their returns periods. A surge of product returns arrived when non-essential retailers reopened. Problems that are costly in normal periods (e.g. wardrobing, fraudulent refunds, serial returners) have become worse in this pandemic period. With recent research showing that many customers will retain their new online shopping habits, the problems will stay, too.

We conducted two consumer surveys, interviewed 9 retailers and 5 retail experts to improve our understanding of consumer behaviours in a pandemic. We then modelled this at micro and macro levels using explainable artificial intelligence (AI) techniques to forecast returns and fraud rates in a world dominated by Covid-19 conditions. To mitigate this, we developped a set of measures, indicating the expected effectiveness and environmental impact.
The ultimate goals are to help retailers operate efficiently and thrive in this challenging time, avoiding the need to cut jobs and thereby increasing the financial burden on welfare. This project will uniquely combine behavioural research with the development of explainable AI that retailers can use to mitigate the economic and ecological effects of product returns.

Staff

Lead researcher

Doctor Regina (Gina) Frei dipl.ing. Micro-Eng., MSc, PhD, FHEA, MIET, CEng

Assoc Prof Operatns & Supply Chain Mgmt

Research interests

  • Sustainable business and sustainable supply chains
  • Reverse supply chains

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Other researchers

Doctor Gary Wills PhD, CEng, FHEA, MIET

Research interests

  • Internet of Things (IoT),
  • Data Protection,

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Professor Enrico Gerding

Professor

Research interests

  • My main research focuses on applications where autonomous self-interested agents compete in markets and negotiate, and where designing appropriate incentives is important to ensure a well functioning and fair society. My research combines theory, mainly game theory and mechanism design, with practical applications. Specific applications include: autonomous vehicles, the smart grid, online advertising markets, cloud computing, algorithmic trading, ride sharing and data privacy.
  • I'm currently an investigator on the following projects:

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Doctor Steffen Bayer

Lecturer in Business Analytics

Research interests

  • Simulation Modelling
  • Health Systems Research

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Doctor PK Senyo

Associate Professor

Research interests

  • Artificial Intelligence (AI)
  • Digital Transformation and Innovation

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Collaborating research institutes, centres and groups

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