Examining an extended duality perspective regarding success conditions of IT service

Bongsik Shin, Sanghoon Lee, Ho Geun Lee

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


IS research predominantly presumes that the success factors of IT service have one-dimensional influences: the higher (or lower), the better. Sporadic arguments, however, have been made that, depending on the antecedent, such a monolithic premise may not sustainable. Despite the rich evidence of the dichotomous role of success factors on measured consequences in non-IS fields, especially in the marketing discipline, theoretical and empirical efforts to examine this duality have received limited attention in IS research. Especially, no previous IS study took the extended duality position in which the role of success conditions can be any of pure enabler, pure inhibitor, asymmetric bi-directional influencer or symmetric bi-directional influencer. The extended duality becomes the theoretical thesis of this research, setting it apart from the scant IS research that viewed duality through the rather simplified lens of statistical significance in each direction. To test the validity of the extended duality theory in the IT service context, cross-sectional survey data were gathered on post-adoption usage of mobile data services (or MDS), the most prevalent form of IT service. Frequently used success conditions of IT service - system quality, information quality, economic value and self-efficacy - are chosen as the explanatory variables. The analysis suggests that success conditions of IT service can have a highly divergent and diversified form of duality effects on measured outcomes. The findings have important practical and theoretical implications to practitioners and researchers.

Original languageEnglish
Pages (from-to)226-239
Number of pages14
JournalInternational Journal of Information Management
Issue number2
Publication statusPublished - 2016 Apr 1

Bibliographical note

Publisher Copyright:
© 2015 Elsevier Ltd. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Marketing
  • Library and Information Sciences
  • Artificial Intelligence


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