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Information Technology Determinants of Organizational Performance in the Context of a Cameroonian Electricity Company

  • Francis Dany Balie Djong
  • Jean Robert Kala Kamdjoug
  • Samuel Fosso Wamba
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)

Abstract

Increased organizational dependence on information technology (IT) drives management attention towards improving information system quality. Given that IT quality is a multidimensional measure, it is important to determine which of its aspects are critical to organization’s performance so that chief information officers (CIOs) may make more informed choices when selecting technologies for their organizations. This research investigates the relationship between system quality (SQ) and organizational performance, system quality and system use, user satisfaction system use and organizational performance, and finally, user satisfaction and organizational performance. A total of 140 responses were collected through a questionnaire-based survey with an electrical company, and the data were analyzed using the structural equation modelling partial least square (SEM-PLS) method. Our results show that system quality influences user satisfaction significantly, which in turn influences organizational performance. Thus, this paper highlights the importance of user satisfaction in organizational performance.

Keywords

System quality System use User satisfaction Organizational performance 

References

  1. 1.
    Kanaracus, C.: Gartner: Global IT spending growth stable. InfoWorld (2017)Google Scholar
  2. 2.
    Petter, S., McLean, E.R.: A meta-analytic assessment of the DeLone and McLean IS success model: an examination of IS success at the individual level. Inf. Manage. 46(3), 159–166 (2009)CrossRefGoogle Scholar
  3. 3.
    Delone, W.H., McLean, E.R.: Information systems success: the quest for the dependent variable. Inf. Syst. Res. 3(1), 60–95 (1992)CrossRefGoogle Scholar
  4. 4.
    Delone, W.H., McLean, E.R.: The DeLone and McLean model of information systems success: a ten-year update. J. Manage. Inf. Syst. 19(4), 9–30 (2003)CrossRefGoogle Scholar
  5. 5.
    Gorla, N., Somers, T.M., Wong, B.: Organizational impact of system quality, information quality, and service quality. J. Strateg. Inf. Syst. 19(3), 207–228 (2010)CrossRefGoogle Scholar
  6. 6.
    Ives, B., Olson, M.H., Baroudi, J.J.: The measurement of user information satisfaction. Commun. ACM 26(10), 785–793 (1983)CrossRefGoogle Scholar
  7. 7.
    Cyert, R.M., March, J.G.: A Behavioral Theory of the Firm. Prentice-Hall, Englewood Cliffs (1963)Google Scholar
  8. 8.
    Godin, G., Gagné, C., Université Laval: Groupe de recherche sur les aspects psychosociaux de la santé, Les théories sociales cognitives: guide pour la mesure des variables et le développement de questionnaire. Groupe de recherche sur les aspects psychosociaux de la santé, École des sciences infirmières, Université Laval (1999)Google Scholar
  9. 9.
    Hair, J.F., Hult, G.T.M., Ringle, C., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications, Thousand Oaks (2016)zbMATHGoogle Scholar
  10. 10.
    Kefi, H., Mlaiki, A., Kalika, M.: Shy people and Facebook continuance of usage: does gender matter? In: 16th Americas Conference on Information Systems, Sustainable IT Collaboration Around the Globe, AMCIS 2010, Lima, Peru, 12–15 August 2010, p. 27 (2010)Google Scholar
  11. 11.
    Malhotra, N.K.: Marketing Research: An Applied Orientation. Prentice Hall, Upper Saddle River (1999)Google Scholar
  12. 12.
    Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39–50 (1981)CrossRefGoogle Scholar
  13. 13.
    Gefen, D., Straub, D.W.: A practical guide to factorial validity using PLS-graph: tutorial and annotated example. CAIS 16, 5 (2005)Google Scholar
  14. 14.
    Straub, D.W., Boudreau, M.-C., Gefen, D.: Validation guidelines for IS positivist research. CAIS 13, 24 (2004)Google Scholar
  15. 15.
    Bradley, R.V., Pridmore, J.L., Byrd, T.A.: Information systems success in the context of different corporate cultural types: an empirical investigation. J. Manage. Inf. Syst. 23(2), 267–294 (2006)CrossRefGoogle Scholar
  16. 16.
    Gefen, D., Straub, D.: A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Commun. AIS 16, 91–109 (2005)Google Scholar
  17. 17.
    Fornell, C., Larcker, D.: A second generation of multivariate analysis: classification of methods and implications for marketing research. Rev. Mark. 1, 407–450 (1987)Google Scholar
  18. 18.
    Mooney, J.G., Gurbaxani, V., Kraeme, K.L.: A process oriented framework for assessing the business value of information technology. SIGMIS Database 27(2), 68–81 (1996)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Francis Dany Balie Djong
    • 1
  • Jean Robert Kala Kamdjoug
    • 1
  • Samuel Fosso Wamba
    • 2
  1. 1.FSSG, GRIAGESUniversité Catholique d’Afrique CentraleYaoundéCameroon
  2. 2.Toulouse Business SchoolUniversité Fédérale de Toulouse Midi-PyrénéesToulouseFrance

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