Deploying Kaizen events in the manufacturing industry: an investigation into managerial factors

Jose Arturo Garza-Reyes, Christos Christopoulos, Anil Kumar, Sunil Luthra, Fernando González-Aleu, Vikas Kumar, Bernardo Villarreal

Research output: Contribution to conferencePaperpeer-review

Abstract

Despite the extensive research on Continuous Improvement (CI), limited reflection has been reported regarding the managerial factors needed to successfully deploy Kaizen Events (KEs). This study investigates various managerial aspects that affect the implementation of KEs. After conducting a literature review and gathering experts’ inputs, the objectives of the study and six research questions were formulated. A survey questionnaire responded by 175 manufacturing organisations was designed and validated. A combined approach of descriptive statistics and one-way ANOVA tests were used to analyse the collected data. Besides other ‘soft’ aspects, the results determine: (1) the drivers and barriers in the pre-implementation stage of KEs; (2) the critical success factors and challenges related to the implementation stage of KEs; (3) the reasons that result in unsuccessful KEs; and (4) the reasons that stop organisations from running KEs. The study provides insights into an under-researched topic by looking at different phases of KEs implementation. The study contributes to the contingency and the RBV theories by offering an understanding of the importance of different contingencies and resources planning for KEs implementation. The findings are beneficial for industrialists who may aim at driving CIs in their organisations through the implementation of KEs.

Original languageEnglish
DOIs
Publication statusPublished - 2020

Bibliographical note

Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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