Involvement in emergency supply chain for disaster management: A cognitive dissonance perspective

Yogesh K. Dwivedi*, Mahmud Akhter Shareef, Bhasker Mukerji, Nripendra P. Rana, Kawaljeet Kaur Kapoor

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

89 Scopus citations

Abstract

An integrated process, interlinked operation and interoperable communication network amongst operating agencies are critical for developing an effective disaster management supply chain. The traditional managerial problems observed across disaster management operations are: non-cooperation among members, disrupted chain of commands, misuse of relief items, lack of information sharing, mistrust and lack of coordination. This study aims to understand the issues affiliated with negative attitude towards disaster management operations using theory of cognitive dissonance. A qualitative investigation was undertaken across 64 districts in Bangladesh. Five constructs were examined for their influences on attitude and behavioural intention of members participating in government emergency supply chain for disaster management. The results indicate that administrative conflict, political biasness and professional growth have significant effects on attitude. Impact of insecurity is non-significant on attitude. This research offers substantial theoretical contribution to the cognitive dissonance theory in the context of disaster management supply chain.

Original languageEnglish
Pages (from-to)6758-6773
Number of pages16
JournalInternational Journal of Production Research
Volume56
Issue number21
DOIs
StatePublished - 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Administrative conflict
  • Attitude
  • Cognitive dissonance theory
  • Disaster management
  • Emergency supply chain
  • Organisational behaviour

ASJC Scopus subject areas

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

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