Return Abuse Detection

Return Abuse Detection is a methodological construct within returns management that identifies and distinguishes patterns of fraudulent or exploitative return behaviors by customers to prevent financial and operational losses.

3

Publications

154

Citations

8

Authors

6

Institutions

Publications per year

2017–2026

2

Authors

8

  1. MS
    Michele Samorani

    Santa Clara University, United States

    1 publications · 30 citations

    1

    h-index

  2. PR
    Paul R. Messinger

    University of Alberta, Canada

    1 publications · 30 citations

    1

    h-index

  3. JD
    James D. Abbey

    Texas A&M University, United States

    1 publications · 66 citations

    1

    h-index

  4. MK
    Michael Ketzenberg

    Texas A&M University, United States

    1 publications · 66 citations

    1

    h-index

  5. FM
    Franklin M. Fisher

    Massachusetts Institute of Technology, United States

    1 publications · 58 citations

    1

    h-index

1–5 of 8

Venues

  1. American Economic Review

    1 publications · 58 citations

    1

    h-index

  2. Service Science

    1 publications · 30 citations

    1

    h-index

  3. Journal of Operations Management

    1 publications · 66 citations

    1

    h-index

1–3