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The Influence of a Convergence in Understanding Between Technology Providers and Users on Information Technology Innovativeness

Author

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  • Mary R. Lind

    (School of Business and Economics, North Carolina A&T State University, 1915 Rosecrest Drive, Greensboro, NC 27408-6215)

  • Robert W. Zmud

    (College of Business, Florida State University, Tallahassee, FL 32306-1042)

Abstract

The objective of this research was to determine if a convergence in understanding between providers and users of a technology would result in greater innovativeness regarding that technology. Two mechanisms were proposed for achieving greater convergence: (1) more frequent communication and (2) the use of richer communication channels. Here, convergence represents the degree of mutual understanding between the technology providers and the other business personnel about the firm's business activities and the importance of the technology in supporting those activities.Frequency of communication indicated the degree to which the technology providers and the business personnel had communication contact, while richness of communication was determined by the type of communication channel used. These means of communication ranged from face to face, computer mediated, to written channels of communication. The convergence construct was operationalized in terms of the value chain framework where 14 business activities (primary and secondary to the value chain) were identified. Convergence thus represents the degree of mutual understanding between the technology providers and the business personnel regarding the importance of these business activities and the importance of the technology in supporting these activities. Innovativeness was determined through expert evaluation of information technology innovativeness.This research was conducted in two United States divisions of a large multinational firm. The units of analyses for the research constructs were the departments in these two divisions. The constructs were measured over five periods of data collection so that longitudinal, causal analysis techniques (cross-lagged correlations and path analysis) were used to investigate the research model.The following results were obtained: (1) convergence was found to be a predictor of innovativeness, (2) communication richness was a predictor of convergence, and (3) communication frequency was a predictor of both convergence and communication richness. This study provided two important extensions to the often-studied relationship between communication behaviors and innovativeness. First, this research showed empirically that the richness of communication influences innovativeness and, in fact, may be the more relevant predictor variable. Secondly, this research showed that convergence is an important intervening construct in the communication activity/innovativeness relationship. Interestingly, the research model only suggested a causal relationship for convergence on the importance of the primary business activities. Thus, the intent of this study to examine the proposition that frequent and rich communication exchanges produce a convergence in understanding among technology providers and users and, that this convergence directly promotes organizational innovativeness was supported.

Suggested Citation

  • Mary R. Lind & Robert W. Zmud, 1991. "The Influence of a Convergence in Understanding Between Technology Providers and Users on Information Technology Innovativeness," Organization Science, INFORMS, vol. 2(2), pages 195-217, May.
  • Handle: RePEc:inm:ororsc:v:2:y:1991:i:2:p:195-217
    DOI: 10.1287/orsc.2.2.195
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    File URL: http://dx.doi.org/10.1287/orsc.2.2.195
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    Cited by:

    1. Amit Kumar & Bala Krishnamoorthy, 2020. "Business Analytics Adoption in Firms: A Qualitative Study Elaborating TOE Framework in India," International Journal of Global Business and Competitiveness, Springer, vol. 15(2), pages 80-93, December.
    2. Veroniek Collewaert & Harry J. Sapienza, 2016. "How Does Angel Investor–Entrepreneur Conflict Affect Venture Innovation? It Depends," Entrepreneurship Theory and Practice, , vol. 40(3), pages 573-597, May.
    3. Yuecheng Yu & Alexander Pelaez & Karl R. Lang, 2016. "Designing and evaluating business process models: an experimental approach," Information Systems and e-Business Management, Springer, vol. 14(4), pages 767-789, November.
    4. Frédéric Delmar & Johan Wiklund, 2008. "The Effect of Small Business Managers’ Growth Motivation on Firm Growth: A Longitudinal Study," Entrepreneurship Theory and Practice, , vol. 32(3), pages 437-457, May.
    5. Terri L. Griffith & David A. Tansik & Lehman Benson, 2002. "Negotiating Technology Implementation: An Empirical Investigation of a Website Introduction," Group Decision and Negotiation, Springer, vol. 11(1), pages 1-22, January.
    6. Ana Ferreira & Ana Lúcia Teixeira & Ana Roque Dantas, 2015. "Non-technological innovation activities mediate the impacts of the intra- and extra-organizational contexts on technological innovation outputs," Enterprise and Work Innovation Studies, Universidade Nova de Lisboa, IET/CICS.NOVA-Interdisciplinary Centre on Social Sciences, Faculty of Science and Technology, vol. 11(11), pages 9-43, December.

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