Linking inventory management performance and operational performance: An empirical analysis of U.S. fashion apparel and accessory industries

Fethi Çalışır, Gülşah Hançerlioğullari*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

Managing inventories is at the core of operational performance in fashion industries. Due to its importance in practice, inventory management has been a well-studied area of research in operations management. The purpose of this study is to examine the relationship between inventory management performance including inventory efficiency, productivity and responsive, and firm operational performance. We present and empirically test a performance model which inte- grates the various dimensions of a fashion industry’s inventory management exe- cution. The regression analysis is used to study the effect of various measures on inventory performance. We use financial data for 40 publicly listed U.S. fashion apparel and accessory industries for the 6-year period, 2010-2015, from “Com- pustat North America Annually Updated” available at Standard and Poor’s Com- pustat database using Wharton Research Data Services (WRDS). We discuss the implications of these empirical results on the study of inventory policy execution, and propose some guidance for further research.

Original languageEnglish
Title of host publicationLecture Notes in Electrical Engineering
EditorsRinaldo Rinaldi, Romeo Bandinelli
PublisherSpringer Verlag
Pages153-161
Number of pages9
ISBN (Print)9783319485102
DOIs
Publication statusPublished - 2017

Publication series

NameLecture Notes in Electrical Engineering
Volume413
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2017.

Keywords

  • Fashion apparel industry
  • Inventory efficiency
  • Inventory management
  • Inventory Productivity
  • Inventory responsiveness
  • Operational performance
  • Operations management

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