The long-run stock performance following announcements of sustainable supply chain management initiatives

Thi Ha Trang Dang, Shao Chi Chang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Purpose: This study aims to examine and analyze the determinants of the stock market performance after firms announce sustainable supply chain management (SSCM) practices. Design/methodology/approach: The study focuses on the long-run stock performance of firms announcing SSCM investments. The authors collected a sample of 280 SSCM announcements from 2010 to 2017 and estimated the buy-and-hold abnormal stock returns up to three years following the announcements. Numerous analyses were conducted to analyze the effect of environmental and social sustainability on long-run stock returns. Findings: The findings show a significantly positive stock performance in the three-year period after announcements. Moreover, the evidence indicates that the post-announcement abnormal stock return has an inverted-U relationship with corporate environmental sustainability but not with corporate social sustainability. Finally, whether firms expand the firms' corporate sustainability strength to SSCM practices or not, firms secure long-run wealth as long as SSCM programs are carried out. Research limitations/implications: The research focuses on the stock performance of USA public firms to draw conclusions about firms' market performance. This research leaves out the private and born-sustainable firms. Practical implications: The findings offer firms incentives to invest in SSCM and suggest the magnitude of value provided by each sustainability type to help firms set firms' supply chain (SC) sustainable investment level. Originality/value: The study is the first to investigate the long-run stock performance of firms announcing SSCM practices and the contribution of different sustainability types to stock performance.

Original languageEnglish
Pages (from-to)738-759
Number of pages22
JournalInternational Journal of Operations and Production Management
Volume43
Issue number5
DOIs
Publication statusPublished - 2023 Apr 5

All Science Journal Classification (ASJC) codes

  • General Decision Sciences
  • Strategy and Management
  • Management of Technology and Innovation

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