European Journal of Information Systems

, Volume 23, Issue 6, pp 691–707

The longitudinal impact of enterprise system users’ pre-adoption expectations and organizational support on post-adoption proficient usage

  • John F Veiga
  • Marcus M Keupp
  • Steven W Floyd
  • Franz W Kellermanns
Empirical Research

Abstract

Although enterprise systems (ES) are ubiquitous, many firms report less than stellar payoffs from these costly investments, with underutilization often attributed to failures in the implementation process. Unfortunately, research has not provided sufficient insights into these failures, in part because it has focused on actual usage, as opposed to proficient usage, as the benchmark for successful implementation. Moreover, research has not generally examined how the adoption process unfolds over time, thus overlooking potential underlying mechanisms that may help explain how adopters achieve proficiency. To begin addressing these shortcomings, we study how adopters’ pre-adoption expectations, enacted over time, can influence their post-adoption proficiency, by shaping how and why they spend time using the system during the adoption period. We analyzed time-lagged survey data from 153 financial analysts, required to adopt new ES-based software, at a multinational bank. We found that adopters who hold pre-adoption expectations reflecting greater internal and external motives to adopt the system as well as systematically integrate it into their work routines are more apt to use the system in ways that enhance their cumulative knowledge of it, and subsequently develop higher levels of proficiency post-adoption. Moreover, greater organizational support enhanced the impact of adopters’ expectations on proficiency, except when their actual use is low in which case organizational support had an adverse effect.

Keywords

actual usage proficient usage intention to use intention to systematically integrate performance outcome expectations organizational support 

References

  1. Ackerman PL and Woltz DJ (1994) Determinants of learning and performance in an associative memory/substitution task: task constraints, individual differences, volition, and motivation. Journal of Educational Psychology 86 (5), 487–515.CrossRefGoogle Scholar
  2. Agarwal R and Karahanna E (2000) Time flies when you're having fun: cognitive absorption and beliefs about information technology usage. MIS Quarterly 24 (40), 665–694.CrossRefGoogle Scholar
  3. Allison CW and Hayes J (1996) The cognitive style index: a measure of intuition-analysis for organizational research. Journal of Management Studies 33 (1), 119–135.CrossRefGoogle Scholar
  4. Argote S, Beckman SL and Epple D (1990) T12he persistence and transfer of learning in industrial settings. Management Science 36 (2), 140–154.CrossRefGoogle Scholar
  5. Armstrong SJ (2000) The influence of cognitive style on performance in management education. Educational Psychology 20 (3), 323–339.CrossRefGoogle Scholar
  6. Bagozzi RP, Davis FD and Warshaw PR (1992) Development and test of a theory of technological learning and usage. Human Relations 45 (5), 659–686.CrossRefGoogle Scholar
  7. Bagozzi RP, Yi Y and Phillips LW (1991) Assessing construct validity in organizational research. Administrative Science Quarterly 36 (3), 421–458.CrossRefGoogle Scholar
  8. Bandura A (1986) Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice- Hall, Englewood Cliffs, NJ.Google Scholar
  9. Beaudry A and Pinsonneault A (2005) Understanding user responses to information technology: a coping model of user adaptation. MIS Quarterly 29 (3), 493–524.Google Scholar
  10. Bergeron F, Raymond L, Rivard S and Gara MF (1995) Determinants of EIS use: testing a behavioral model. Decision Support Systems 4 (2), 131–146.CrossRefGoogle Scholar
  11. Besson P and Rowe F (2012) Strategizing information systems-enabled organizational transformation: a transdisciplinary review and new directions. Journal of Strategic Information Systems 21 (2), 103–124.CrossRefGoogle Scholar
  12. Bollen KA (1989) Structural Equations with Latent Variables. John Wiley & Sons, New York.CrossRefGoogle Scholar
  13. Bollen KA (2011) Evaluating effect, composite, and causal indicators in structural equation models. MIS Quarterly 35 (2), 359–372.Google Scholar
  14. Boudreau M-C and Robey D (2005) Enacting integrated information technology: a human agency perspective. Organization Science 16 (1), 3–18.CrossRefGoogle Scholar
  15. Brown SA, Massey AP, Montoya-Weiss MM and Burkman JR (2002) Do I really have to? User acceptance of mandated technology. European Journal of Information Systems 11 (3), 283–295.CrossRefGoogle Scholar
  16. Burton-Jones A and Straub D (2006) Reconceptualizing system usage: an approach and empirical test. Information Systems Research 17 (3), 228–246.CrossRefGoogle Scholar
  17. Chau PYK (1996) An empirical assessment of a modified technology acceptance model. Journal of Management Information Systems 13 (2), 185–204.CrossRefGoogle Scholar
  18. Coetsee L (1999) From resistance to commitment. Public Administration Quarterly 23 (2), 204–222.Google Scholar
  19. Cohen J, Cohen P, West S and Aiken L (2003) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, 3rd edn, Lawrence Erlbaum Associates, Mahwah, NJ.Google Scholar
  20. Compeau DR and Higgins CA (1995) Computer self-efficacy: development of a measure and initial test. MIS Quarterly 19 (2), 189–211.CrossRefGoogle Scholar
  21. Compeau DR, Higgins CA and Huff S (1999) Social cognitive theory and individual reactions to computing technology: a longitudinal study. MIS Quarterly 23 (2), 145–158.CrossRefGoogle Scholar
  22. Cools E and Van den Broeck H (2007) Development and validation of the cognitive style indicator. The Journal of Psychology 141 (4), 359–387.CrossRefGoogle Scholar
  23. Cotteleer MJ and Bendoly E (2006) Order lead-time improvement following enterprise information technology implementation: an empirical study. MIS Quarterly 30 (3), 643–660.Google Scholar
  24. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13 (3), 319–340.CrossRefGoogle Scholar
  25. Davis FD, Baggozi RP and Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Management Science 35 (8), 982–1002.CrossRefGoogle Scholar
  26. Davis FD, Baggozi RP and Warshaw PR (1992) Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology 22 (4), 1111–1132.CrossRefGoogle Scholar
  27. DeLone WH and McLean ER (2003) The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems 19 (4), 9–30.Google Scholar
  28. DeSanctis D and Poole MS (1994) Capturing the complexity in advanced technology use: adaptive structuration theory. Organization Science 5 (2), 121–147.CrossRefGoogle Scholar
  29. Devadoss P and Pan S (2007) Enterprise systems use: towards a structurational analysis of enterprise systems’ induced organizational transformation. Communications of the AIS 19 (4), 352–385.Google Scholar
  30. Diamantopoulos A (2011) Incorporating formative measures into covariance-based structural equation models. MIS Quarterly 35 (2), 335–358.Google Scholar
  31. Dreyfus HL and Dreyfus SE (1986) Mind over Machine: The Power of Human Intuition and Expertise in the Era of the Computer. Free Press, New York.Google Scholar
  32. Due RT (1994) The productivity paradox revisited. Information Systems Management 11 (1), 74–76.CrossRefGoogle Scholar
  33. Ein-Dor P and Segev E (1978) Organizational context and the success of management information systems. Management Science 24 (10), 1067–1077.CrossRefGoogle Scholar
  34. Eisenberger R, Stinglhamber F, Vandenberghe C, Sucharski IL and Rhoades L (2002) Perceived supervisor support: contributions to perceived organizational support and employee retention. Journal of Applied Psychology 87 (3), 565–573.CrossRefGoogle Scholar
  35. Ferneley E and Sobreperez P (2006) Resist, comply or workaround? An examination of different facets of user engagement with information systems. European Journal of Information Systems 15 (4), 345–356.CrossRefGoogle Scholar
  36. Fichman RG and Kemerer CF (1997) The assimilation of software process innovations: an organizational learning perspective. Management Science 43 (10), 1345–1363.CrossRefGoogle Scholar
  37. Fishbein M and Ajzen I (1975) Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Addison-Wesley, Boston.Google Scholar
  38. Fiss PC (2007) A set-theoretic approach to organizational configurations. Academy of Management Review 32 (4), 1180–1198.CrossRefGoogle Scholar
  39. Gandhi J and Sauser B (2008) Knowledge networks: how independence and subject matter experts can influence project reviews. Engineering Management Journal 20 (1), 19–28.CrossRefGoogle Scholar
  40. Ginzberg MJ (1981) Early diagnosis of MIS implementation failure. Management Science 27 (4), 459–478.CrossRefGoogle Scholar
  41. Gonzalez-Padron TL, Chabowski BR, Hult G, Tomas M and Ketchen DJ (2010) Knowledge management and balanced scorecard outcomes: exploring the importance of interpretation, learning and internationality. British Journal of Management 21 (4), 967–982.CrossRefGoogle Scholar
  42. Grigorenko EL and Sternberg RJ (1995) International handbook of personality and intelligence. In Thinking Styles (Saklofske DH and Zeidner M, Eds), Plenum Press, New York, pp 205–230.Google Scholar
  43. Grimley M and Banner G (2008) Working memory, cognitive style, and behavioral predictors of GCSE exam success. Educational Psychology 28 (3), 341–351.CrossRefGoogle Scholar
  44. Grover V (1993) An empirically derived model for the adoption of customer-based interorganizational systems. Decision Sciences 24 (5), 603–640.CrossRefGoogle Scholar
  45. Harper G and Kember D (1986) Approaches to study of distance education students. British Journal of Educational Technology 17 (2), 212–222.CrossRefGoogle Scholar
  46. Hayes AF (2008) SPSS moderation mediation macro version 2.1. [WWW document] http://www.comm.ohio-state.edu/ahayes/SPSS%20programs/modmed.htm (accessed 10 May 2010).Google Scholar
  47. Hayes J and Allinson CW (1994) Cognitive style and its relevance for management practice. British Journal of Management 5 (1), 53–71.CrossRefGoogle Scholar
  48. Heinstrom J (2006) Broad exploration or precise specificity: two basic information seeking patterns among students. Journal of the American Society for Information Science and Technology 57 (7), 1440–1450.CrossRefGoogle Scholar
  49. Hestermann C, Anderson RP and Pang C (2009) Magic quadrant for midmarket and tier 2-oriented ERP for product-centric companies. Gartner Research, [WWW document] www.gartner.com/technology/mediaproducts/reprints/microsoft/vol14/ article12.html (accessed 1 July 2009).Google Scholar
  50. Holland CP and Light B (1999) A critical success factors model for ERP implementation. IEEE Software 16 (1), 30–36.CrossRefGoogle Scholar
  51. Hollenbeck JR, Beersma B and Schouten ME (2012) Beyond team types and taxonomies: a dimensional scaling conceptualization for team description. Academy of Management Review 37 (1), 82–106.Google Scholar
  52. Hunt RG, Krzystofiak FJ, Meindl JR and Yousry AM (1989) Cognitive style and decision making. Organizational Behavior and Human Decision Processes 44 (3), 436–453.CrossRefGoogle Scholar
  53. Igbaria M (1990) End-user computing effectiveness: a structural equation model. Omega 18 (6), 637–652.CrossRefGoogle Scholar
  54. Igbaria M, Iivari J and Maragah H (1995) Why do individuals use computer technology? A Finnish case study. Information and Management 5 (1), 7–38.Google Scholar
  55. Ilgen DR and Feldman JM (1983) Performance appraisal: a process focus. Research in Organizational Behavior 5 (2), 141–197.Google Scholar
  56. Jarvis CB, MacKenzie SB, Podsakoff PM, Mick D and Bearden W (2003) A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research 30 (2), 199–218.CrossRefGoogle Scholar
  57. Jelinek R, Ahearne M, Mathieu J and Schillewaert N (2006) A longitudinal examination of individual, organizational, and contextual factors on sales technology adoption and job performance. Journal of Marketing Theory and Practice 14 (1), 7–22.CrossRefGoogle Scholar
  58. Jeyaraj A, Rottman J and Lacity M (2006) A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology 21 (1), 1–23.CrossRefGoogle Scholar
  59. Jurison J (1996) The temporal nature of IS benefits: a longitudinal study. Information and Management 30 (2), 75–79.CrossRefGoogle Scholar
  60. Kaplan RS and Norton DP (1996) Using the balanced scorecard as a strategic management system. Harvard Business Review 74 (1), 75–85.Google Scholar
  61. Keeping LM and Levy PE (2000) Performance appraisal reactions: measurement, modeling, and method bias. Journal of Applied Psychology 85 (5), 708–723.CrossRefGoogle Scholar
  62. Kember D, Jamieson QW, Pomfret M and Wong ETT (1995) Learning approaches, study time and academic performance. Higher Education 29 (3), 329–343.CrossRefGoogle Scholar
  63. Kenny DA, Kashy DA and Bolger N (1998) Data analysis in social psychology. In The Handbook of Social Psychology (Gilbert DT, Fiske ST and Lindzey G, Eds), 4th edn, Vol. 1, pp 1233–1265, Oxford University Press, New York.Google Scholar
  64. Kirkman BL, Rosen B, Tesluk PE and Gibson CB (2004) The impact of team empowerment on virtual team performance: the moderating role of face-to-face interaction. Academy of Management Journal 47 (2), 175–192.CrossRefGoogle Scholar
  65. Kline RB (1998) Principles and Practice of Structural Equation Modeling. Guildford Press, New York.Google Scholar
  66. Kraiger K, Ford JK and Salas E (1993) Application of cognitive, skill-based and affective theories of learning outcomes to new methods of training evaluation. Journal of Applied Psychology 78 (2), 311–328.CrossRefGoogle Scholar
  67. Kwahk K (2006) ERP acceptance: organizational change perspective. In Proceedings of the International Conference on Systems Sciences (Nunamaker JF, Ed), Poipu Kauai, Hawaii, pp 1–10.Google Scholar
  68. Kwahk K and Kim H (2008) Managing readiness in enterprise systems-driven organizational change. Behavior & Information Technology 27 (1), 79–87.CrossRefGoogle Scholar
  69. Lassila KS and Brancheau JC (1999) Adoption and utilization of commercial software packages: exploring utilization equilibria, transitions, triggers, and tracks. Journal of Management Information Systems 16 (1), 63–90.CrossRefGoogle Scholar
  70. LeRouge C, Hevner A and Collins R (2007) It's more than just use: an exploration of telemedicine use quality. Decision Support Systems 43 (4), 1287–1304.CrossRefGoogle Scholar
  71. Lewin AY, Massini S and Peeters C (2011) Microfoundations of internal and external absorptive capacity routines. Organization Science 22 (1), 81–98.CrossRefGoogle Scholar
  72. Liang H, Saraf N, Hu Q and Xue Y (2007) Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Quarterly 31 (1), 59–87.Google Scholar
  73. Lucas HC (1978) Empirical evidence for a descriptive model of implementation. MIS Quarterly 2 (1), 27–41.CrossRefGoogle Scholar
  74. Lodewyka KR, Winneb PH and Jamieson-Noel DL (2009) Implications of task structure on self-regulated learning and achievement. Educational Psychology 29 (1), 1–25.CrossRefGoogle Scholar
  75. MacKinnon DP, Lockwood CM, Hoffman JM, West SG and Sheets V (2002) A comparison of methods to test mediation and other intervening variable effects. Psychological Methods 7 (1), 83–104.CrossRefGoogle Scholar
  76. MacKinnon DP, Lockwood CM and Williams J (2004) Confidence limits for the indirect effect: distribution of the product and resampling methods. Multivariate Behavioral Research 39 (1), 99–128.CrossRefGoogle Scholar
  77. Maish A (1979) A user's behavior towards his MIS. MIS Quarterly 3 (1), 39–52.CrossRefGoogle Scholar
  78. Marchand DA (2000) Information orientation: people, technology and the bottom line. Sloan Management Review 10 (3), 69–80.Google Scholar
  79. Marcolin BL, Compeau DR, Munro MC and Huff SL (2000) Assessing user competence: conceptualization and measurement. Information Systems Research 11 (1), 37–60.CrossRefGoogle Scholar
  80. Markus ML and Tanis C (2000) The enterprise system experience – from adoption to success. In Framing the Domains of IT Research: Projecting the Future Through the Past (Zmud RW, Ed), pp 173–207, Pinnaflex Educational Resources, Inc, Cincinnati.Google Scholar
  81. Martin DC and Bartol KM (1998) Performance appraisal: maintaining system effectiveness. Public Personnel Management 27 (2), 223–230.CrossRefGoogle Scholar
  82. Mathieson K (1991) Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Information Systems Research 2 (3), 173–191.CrossRefGoogle Scholar
  83. Mathieu JE and Taylor SR (2006) Clarifying conditions and decision points for meditational type inferences in organizational behavior. Journal of Organizational Behavior 27 (8), 1031–1056.CrossRefGoogle Scholar
  84. Mayer RE (1992) Cognition and instruction: their historic meeting within educational psychology. Educational Psychology 84 (4), 405–412.CrossRefGoogle Scholar
  85. Meissonier R, Bourdon I, Amabile S and Boudrandi S (2012) Toward an enacted approach to understanding OSS developers motivations. International Journal of Technology and Human Interaction 8 (1), 38–54.CrossRefGoogle Scholar
  86. Mirvis PH, Sales AL and Hackett EJ (1991) The implementation and adoption of new technology in organizations: the impact on work, people, and culture. Human Resource Management 30 (2), 113–139.CrossRefGoogle Scholar
  87. Morris MG and Dillon A (1997) How user perceptions influence software use. IEEE Software 14 (1), 58–64.CrossRefGoogle Scholar
  88. Muchinsky PM (2012) Psychology Applied to Work, 10th edn, Hypergraphic Press, Summerfield, NC.Google Scholar
  89. Munro M, Huff S, Marcolin B and Compeau D (1997) Understanding and measuring user competence. Information and Management 33 (1), 45–57.CrossRefGoogle Scholar
  90. Nonaka I. (1994) A dynamic theory of organizational knowledge creation. Organization Science 5 (1), 14–37.CrossRefGoogle Scholar
  91. Orlikowski WJ (1993) CASE tools as organizational change: investigating incremental and radical changes in systems development. MIS Quarterly 17 (3), 309–341.CrossRefGoogle Scholar
  92. Pedhazur EJ (1982) Multiple Regression in Behavioral Research. Explanations and Predictions. 2nd edn, Hartcourt Brace College Publishers, Fort Worth, TX.Google Scholar
  93. Phan HP (2009) Relations between goals, self‐efficacy, critical thinking and deep processing strategies: a path analysis. Educational Psychology 29 (7), 777–799.CrossRefGoogle Scholar
  94. Phan HP (2010) Empirical model and analysis of mastery and performance‐approach goals: a developmental approach. Educational Psychology 30 (6), 547–564.CrossRefGoogle Scholar
  95. Podsakoff P, MacKenzie S, Lee J and Podsakoff N (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology 88 (5), 879–903.CrossRefGoogle Scholar
  96. Podsakoff NP, Shen W and Podsakoff PM (2006) The role of formative measurement models in strategic management research: review, critique, and implications for future research. Research Methodology in Strategy and Management 3 (3), 197–252.CrossRefGoogle Scholar
  97. Preacher KJ and Hayes AF (2004) SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers 36 (6), 717–731.CrossRefGoogle Scholar
  98. Preacher KJ, Rucker DD and Hayes AF (2007) Addressing moderated mediation hypotheses: theory, methods, and prescriptions. Multivariate Behavioral Research 42 (1), 185–227.CrossRefGoogle Scholar
  99. Purvis RL, Sambamurthy V and Zmud RW (2001) The assimilation of knowledge platforms in organizations: an empirical investigation. Organization Science 12 (2), 117–135.CrossRefGoogle Scholar
  100. Ragin CC (2000) Fuzzy Set Social Science. University of Chicago Press, Chicago.Google Scholar
  101. Ragin CC (2008) Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press, Chicago.CrossRefGoogle Scholar
  102. Rayner SG and Riding RJ (1997) Towards a categorization of cognitive styles and learning styles. Educational Psychology 17 (1), 5–27.CrossRefGoogle Scholar
  103. Rhoades L, Eisenberger R and Armeli S (2001) Affective commitment to the organization: the contribution of perceived organizational support. Journal of Applied Psychology 86 (5), 825–836.CrossRefGoogle Scholar
  104. Robey D (1979) User attitudes and MIS use. Academy of Management Journal 22 (3), 527–538.CrossRefGoogle Scholar
  105. Robey D, Ross JW and Boudreau M-C (2002) Learning to implement enterprise systems: an exploratory study of the dialectics of change. Journal of Management Information Systems 19 (1), 17–46.Google Scholar
  106. Rogers E (1995) Diffusion of Innovations. The Free Press, New York.Google Scholar
  107. Sabherwal R, Jeyaraj A and Chowa C (2006) Information system success: individual and organizational determinants. Management Science 52 (12), 1849–1864.CrossRefGoogle Scholar
  108. Saeed KA, Abdinnour S, Lengnick-Hall ML and Lengnick-Hall CA (2010) Examining the impact of pre-implementation expectations on post-implementation use of enterprise systems: a longitudinal study. Decision Sciences 41 (4), 659–688.CrossRefGoogle Scholar
  109. Schermerhorn JR, Gardner Jr. WL and Martin TN (1990) Management dialogues: turning on the marginal performer. Organizational Dynamics 18 (4), 47–59.CrossRefGoogle Scholar
  110. Schmeck, RR (Ed) (1988) Learning Strategies and Learning Styles. Plenum Press, New York.CrossRefGoogle Scholar
  111. Seddon P, Calvert C and Yang S (2010) A multi-project model of key factors affecting organizational benefits from enterprise systems. MIS Quarterly 34 (2), 305–328.Google Scholar
  112. Sproull LS and Hofmeister KR (1986) Thinking about implementation. Journal of Management 12 (1), 43–60.CrossRefGoogle Scholar
  113. Straub, D, Limayem M and Karahanna-Evaristo E (1995) Measuring systems usage: implications for IS theory testing. Management Science 41 (8), 1328–1342.CrossRefGoogle Scholar
  114. Swanson EB (1987) Information channel disposition and use. Decision Sciences 18 (2), 131–145.CrossRefGoogle Scholar
  115. Tabachnick BG and Fidell LS (1996) Using Multivariate Statistics. Harper-Collins College Publishers, New York.Google Scholar
  116. Tanni M. and Sormunen E (2008) A critical review of research on information behavior in assigned learning tasks. Journal of Documentation 64 (6), 893–914.CrossRefGoogle Scholar
  117. Tate W (1995) Developing Managerial Competence: A Critical Guide to Methods and Materials. Gower, London.Google Scholar
  118. Tennant M (1988) Psychology and Adult Learning. Routledge, London.CrossRefGoogle Scholar
  119. Thompson R, Higgins C and Howell J (1991) Personal computing: toward a conceptual model of utilization. MIS Quarterly 15 (1), 124–143.CrossRefGoogle Scholar
  120. Thompson RL, Higgin CA and Howell JM (1994) Influence of experience on personal computer utilization: testing a conceptual model. Journal of Management Information Systems 11 (1), 167–187.CrossRefGoogle Scholar
  121. Trice AW and Treacy M (1988) Utilization as a dependent variable in MIS research. Data Base 1 (1), 33–41.CrossRefGoogle Scholar
  122. Van Offenbeek BA and DongBack S (forthcoming) Towards integrating acceptance and resistance research: evidence from a telecare case study. European Journal of Information Systems.Google Scholar
  123. Venkatesh V (2006) Where to go from here? Thoughts on future directions for research on individual-level technology adoption with a focus on decision making. Decision Sciences 37 (4), 497–518.CrossRefGoogle Scholar
  124. Venkatesh V, Morris M and Ackerman P (2000) A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes 83 (1), 33–60.CrossRefGoogle Scholar
  125. Venkatesh V, Morris MG, Davis GB and Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Quarterly 27 (3), 425–478.Google Scholar
  126. Venkatesh V and Speier C (1999) Computer technology training in the workplace: a longitudinal investigation of the effect of the mood. Organizational Behavior and Human Decision Processes 79 (1), 1–28.CrossRefGoogle Scholar
  127. Vroom VH and Deci EL (1992) Management and Motivation. Penguin, London.Google Scholar
  128. Wagner EL and Newell S (2007) Exploring the importance of participation in the post-implementation period of an ES project: a neglected area. Journal of the Association for Information Systems 8 (10), 508–524.Google Scholar
  129. Walsham G (2001) Making a World of Difference: IT in a Global Context. Wiley, Chichester, U.K.Google Scholar
  130. Weick KE (1988) Enacted sensemaking in crisis situations. Journal of Management Studies 25 (4), 305–317.CrossRefGoogle Scholar
  131. Wixom BH and Todd PA (2005) A theoretical integration of user satisfaction and technology acceptance. Information Systems Research 16 (1), 85–102.CrossRefGoogle Scholar
  132. Wu J and Du H (2012) Toward a better understanding of behavioral intention and system usage constructs. European Journal of Information Systems 21 (6), 680–698.CrossRefGoogle Scholar

Copyright information

© Operational Research Society 2013

Authors and Affiliations

  • John F Veiga
    • 1
  • Marcus M Keupp
    • 2
  • Steven W Floyd
    • 3
  • Franz W Kellermanns
    • 4
    • 5
  1. 1.Department of ManagementSchool of Business, University of ConnecticutStorrsU.S.A.
  2. 2.Department of Military Business AdministrationMilitary Academy, Swiss Federal Institute of TechnologyZurichSwitzerland
  3. 3.Isenberg School of Management, University of Massachusetts – AmherstAmherst, MAU.S.A.
  4. 4.Department of ManagementBelk College of Business, The University of North Carolina-CharlotteCharlotte, NCU.S.A.
  5. 5.INTES Center for Family Enterprises, WHU, Düsseldorf, Germany Otto Beisheim School of ManagementVallendarGermany

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