The role of congruence between exploitative and exploratory knowledge sharing in enterprise systems project: Polynomial modeling and response surface analysis

Yang Liu, Zhao Cai, Hefu Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

In enterprise system (ES) project, knowledge sharing between client and ES vendor is a pivotal practice to ensure its success. However, it is a tradeoff for managers to balance two forms of knowledge sharing - exploitative and exploratory knowledge sharing. This study provides a preliminary insight by investigating the effects of congruence and incongruence of knowledge sharing on the success of ES project. Using data collected from 112 clients of an ES vendor, we apply polynomial modeling and response surface methodology for an in depth analysis. Our findings point out the importance of congruence between the two forms of knowledge sharing and we also find that exploratory knowledge sharing between client and ES vendor is a prerequisite to the success of ES project. In future research, we aim to examine how to balance the two forms of knowledge sharing and find out which kind of knowledge should be necessarily shared.

Original languageEnglish
Title of host publicationInternational Conference on Information Systems 2018, ICIS 2018
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683173
Publication statusPublished - 2018
Event39th International Conference on Information Systems, ICIS 2018 - San Francisco, United States
Duration: 13 Dec 201816 Dec 2018

Publication series

NameInternational Conference on Information Systems 2018, ICIS 2018

Conference

Conference39th International Conference on Information Systems, ICIS 2018
Country/TerritoryUnited States
CitySan Francisco
Period13/12/1816/12/18

Keywords

  • Congruence
  • Enterprise systems
  • Knowledge sharing
  • Polynomial modeling
  • Response surface methodology

ASJC Scopus subject areas

  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences
  • Applied Mathematics

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