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Using organizational influence processes to overcome IS implementation barriers: lessons from a longitudinal case study of SPI implementation

  • Research Article
  • Published:
European Journal of Information Systems

Abstract

A fundamental tenet of the information systems (IS) discipline holds that: (a) a lack of formal power and influence over the organization targeted for change, (b) weak support from top management, and (c) organizational memories of prior failures are barriers to implementation success. Our research, informed by organization influence, compellingly illustrates that such conditions do not necessarily doom a project to failure. In this paper, we present an analysis of how an IS implementation team designed and enacted a coordinated strategy of organizational influence to achieve implementation success despite these barriers. Our empirical analysis also found that technology implementation and change is largely an organizational influence process (OIP), and thus technical-rational approaches alone are inadequate for achieving success. Our findings offer managers important insights into how they can design and enact OIPs to effectively manage IS implementation. Further, we show how the theory of organizational influence can enhance understanding of IS implementation dynamics and advance the development of a theory of effective IS change agentry.

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Notes

  1. For an extensive review of power and politics in IS literature, the reader is advised to consult Jasperson et al (2002).

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Authors and Affiliations

  1. Ted Rogers School of Management, Ryerson University, Toronto, , Ontario,, Canada

    Ojelanki Ngwenyama

  2. Faculty of Commerce, University of Cape Town, South Africa

    Ojelanki Ngwenyama

  3. Department of Computer Science, Aalborg University, Aalborg, Denmark

    Peter Axel Nielsen

  4. Department of Information Systems, University of Agder, Kristiansand, Norway

    Peter Axel Nielsen

Authors
  1. Ojelanki Ngwenyama
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  2. Peter Axel Nielsen
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Correspondence to Peter Axel Nielsen.

Appendix

Appendix

The iterative coding resulted in 112 quotations (refined from 142 initial quotations). Each quotation, q, is associated with at least one code, c (see Section ‘Research Methodology’ for details). The Table A1 shows the set of codes {c} along with their frequencies (F) and definitions.

Table A1

Table A1 Code used in the empirical analysis with their frequencies and definitions
Full size table

The Table A2 displays the number of co-occurrences of each pair of codes in all documents. Each cell represents a code pair and also displays a normalized coefficient along with the count, which should vary between 0 (codes do not co-occur) and 1 (codes co-occur wherever they are used). The co-occurrence index (Garcia, 2006) accounts for the occurrence count of each code,

where F is the frequency of a code occurring on quotations – F(a), for example, measures how often the code a occurs, and F(a and b) measures how often both a and b occur on the same quotation.

Table A2

Table A2 Co-occurences of each pair of codes in the empirical data
Full size table

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Ngwenyama, O., Nielsen, P. Using organizational influence processes to overcome IS implementation barriers: lessons from a longitudinal case study of SPI implementation. Eur J Inf Syst 23, 205–222 (2014). https://doi.org/10.1057/ejis.2012.56

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