Adaptation to Information Technology: A Holistic Nomological Network from Implementation to Job Outcomes

Published Online:https://doi.org/10.1287/mnsc.2014.2111

References

  • Aiken LS, West SG (1991) Multiple Regression: Testing and Interpreting Interactions (Sage, London).Google Scholar
  • Aiman-Smith L, Green S (2002) Implementing new manufacturing technology: The related effects of technology characteristics and user learning activities. Acad. Management J. 45(2):421–430.CrossrefGoogle Scholar
  • Ajzen I (1991) The theory of planned behavior. Organ. Behav. Human Decision Processes 50(2):179–211.CrossrefGoogle Scholar
  • Ang S, Slaughter SA (2001) Work outcomes and job design for contract versus permanent information systems professionals on software development teams. MIS Quart. 25(3):321–350.CrossrefGoogle Scholar
  • Ayyagari R, Grover V, Purvis R (2011) Technostress: Technological antecedents and implications. MIS Quart. 35(4):831–858.CrossrefGoogle Scholar
  • Bala H, Venkatesh V (2013) Changes in employees’ job characteristics during an enterprise system implementation: A latent growth modeling perspective. MIS Quart. 37(4):1113–1140.CrossrefGoogle Scholar
  • Barki H, Hartwick J (1994) Measuring user participation, user involvement, and user attitude. MIS Quart. 18(1):59–82.CrossrefGoogle Scholar
  • Barki H, Titah R, Boffo C (2007) Information system use-related activity: An expanded behavioral conceptualization of individual-level information system use. Inform. Systems Res. 18(2):173–192.LinkGoogle Scholar
  • Beaudry A, Pinsonneault A (2005) Understanding user responses to information technology: A coping model of user adaptation. MIS Quart. 29(3):493–525.CrossrefGoogle Scholar
  • Bendoly E, Cotteleer MJ (2008) Understanding behavioral sources of process variation following enterprise system deployment. J. Oper. Management 26(1):23–44.CrossrefGoogle Scholar
  • Boudreau M-C, Robey D (2005) Enacting integrated information technology: A human agency perspective. Organ. Sci. 16(1):3–18.LinkGoogle Scholar
  • Burton-Jones A, Straub DW (2006) Reconceptualizing system usage: An approach and empirical test. Inform. Systems Res. 17(3):228–246.LinkGoogle Scholar
  • Camman C, Fichman M, Jenkins JD, Klesh JR (1983) Assessing the attitudes and perceptions of organizational members. Seashore SS, Lawler EE, Mirvis PH, Cammann C, eds. Assessing Organizational Change: A Guide to Methods, Measures, Practices (Wiley, New York), 71–138.Google Scholar
  • Carver CS, Scheier MF, Weintraub JK (1989) Assessing coping strategies: A theoretically based approach. J. Personality Soc. Psych. 56(2):267–283.CrossrefGoogle Scholar
  • Chan D (2000) Conceptual and empirical gaps in research on individual adaptation at work. Internat. Rev. Indust. Organ. Psych. 15:143–164.Google Scholar
  • Chattopadhyay P, Glick WH, Huber GP (2001) Organizational actions in response to threats and opportunities. Acad. Management J. 44(5):937–955.CrossrefGoogle Scholar
  • DeSanctis G, Poole MS (1994) Capturing the complexity in advanced technology use: Adaptive structuration theory. Organ. Sci. 5(2):121–147.LinkGoogle Scholar
  • DeVellis RF (2003) Scale Development: Theory and Applications (Sage, Thousand Oaks, CA).Google Scholar
  • Drach-Zahavy A, Erez M (2002) Challenge versus threat effects on the goal–performance relationship. Organ. Behav. Human Decision Processes 88(2):667–682.CrossrefGoogle Scholar
  • Edmondson AC (1999) Psychological safety and learning behavior in work teams. Admin. Sci. Quart. 44(2):350–383.CrossrefGoogle Scholar
  • Edwards J, Lambert L (2007) Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psych. Methods 12(1):1–22.CrossrefGoogle Scholar
  • Folkman S, Lazarus RS, Gruen RJ, DeLongis A (1986) Appraisal, coping, health status and psychological symptoms. J. Personality Soc. Psych. 50(3):571–579.CrossrefGoogle Scholar
  • Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Marketing Res. 18(3):382–388.CrossrefGoogle Scholar
  • Fugate M, Kinicki AJ, Prussia GE (2008) Employee coping with organizational change: An examination of alternative theoretical perspectives and models. Personnel Psych. 61(1):1–36.CrossrefGoogle Scholar
  • Gartner Inc. (2013) Forecast alert: IT spending, worldwide, 4Q12 update. Report, Gartner, Stamford, CT.Google Scholar
  • Gupta AK, Smith KG, Shalley CE (2006) The interplay between exploration and exploitation. Acad. Management J. 49(4):693–706.CrossrefGoogle Scholar
  • Harrison DA, Newman DA, Roth PL (2006) How important are job attitudes? Meta-analytic comparisons for integrative behavioral outcomes and time sequences. Acad. Management J. 49(2):305–326.CrossrefGoogle Scholar
  • Janssen O, Van Yperen NW (2004) Employees’ goal orientations, the quality of leader-member exchange, and the outcomes of job performance and job satisfaction. Acad. Management J. 47(3):368–384.CrossrefGoogle Scholar
  • Jasperson J, Carter PE, Zmud RW (2005) A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quart. 29(3):525–557.CrossrefGoogle Scholar
  • Klein KJ, Conn AB, Sorra JS (2001) Implementing computerized technology: An organizational analysis. J. Appl. Psych. 86(5):811–824.CrossrefGoogle Scholar
  • Lapointe L, Rivard S (2005) A multilevel model of resistance to information technology implementation. MIS Quart. 29(3):461–491.CrossrefGoogle Scholar
  • Lazarus RS, Folkman S (1984) Stress, Appraisal, and Coping (Springer, New York).Google Scholar
  • Liang H, Xue Y (2009) Avoidance of information technology threats: A theoretical perspective. MIS Quart. 33(1):71–90.CrossrefGoogle Scholar
  • Major B, Richards MC, Cooper ML, Cozzarelli C, Zubek J (1998) Personal resilience, cognitive appraisals, and coping: An integrative model of adjustment to abortion. J. Personality Soc. Psych. 74(3):735–752.CrossrefGoogle Scholar
  • Mishra AN, Agarwal R (2010) Technological frames, organizational capabilities and post-adoption IT use: An empirical investigation of electronic procurement. Inform. Systems Res. 21(2):249–270.LinkGoogle Scholar
  • Mithas S, Tafti AR, Bardhan IR, Goh JM (2012) Information technology and firm profitability: Mechanisms and empirical evidence. MIS Quart. 36(1):205–224.CrossrefGoogle Scholar
  • Moon H, Hollenbeck JR, Humphrey SE, Ilgen DR, West B, Ellis APJ, Porter COLH (2004) Asymmetrical adaptability: Dynamic team structures as one-way streets. Acad. Management J. 47(5):681–696.CrossrefGoogle Scholar
  • Morris MG, Venkatesh V (2010) Job characteristics and job satisfaction: Understanding the role of enterprise resource planning system implementation. MIS Quart. 34(1):143–161.CrossrefGoogle Scholar
  • Nan N (2011) Capturing bottom-up information technology use processes: A complex adaptive systems model. MIS Quart. 35(2):505–532.CrossrefGoogle Scholar
  • Parker SK, Chmiel N, Wall TD (1997) Work characteristics and employee well-being within a context of strategic downsizing. J. Occupational Health Psych. 2(4):289–303.CrossrefGoogle Scholar
  • Petter S, Straub D, Rai A (2007) Specifying formative constructs in information systems research. MIS Quart. 31(4):623–656.CrossrefGoogle Scholar
  • Podsakoff PM, Mackenzie SB, Lee J, Podsakoff NP (2003) Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psych. 88(5):879–903.CrossrefGoogle Scholar
  • Purvis RL, Sambamurthy V, Zmud RW (2001) The assimilation of knowledge platforms in organizations: An empirical investigation. Organ. Sci. 12(2):117–135.LinkGoogle Scholar
  • Rai A, Tang X (2014) Information technology-enabled business models: A conceptual framework and a coevolution perspective for future research. Inform. Systems Res. 25(1):1–14.LinkGoogle Scholar
  • Ringle CM, Wende S, Will A (2005) SmartPLS 2.0 M3 (beta). Hamburg, Germany.Google Scholar
  • Robey D, Ross JW, Boudreau M-C (2002) Learning to implement enterprise systems: An exploratory study of the dialectics of change. J. Management Inform. Systems 19(1):17–46.CrossrefGoogle Scholar
  • Sabherwal R, Jeyaraj A, Chowa C (2006) Information system success: Individual and organizational determinants. Management Sci. 52(12):1849–1864.LinkGoogle Scholar
  • Setia P, Venkatesh V, Joglekar S (2013) Leveraging digital technologies: How information quality leads to localized capabilities and customer service performance. MIS Quart. 37(2):565–590.CrossrefGoogle Scholar
  • Sharma R, Yetton P (2003) The contingent effects of management support and task interdependence on successful information systems implementation. MIS Quart. 27(4):533–556.CrossrefGoogle Scholar
  • Sharma R, Yetton P (2007) The contingent effects of training, technical complexity, and task interdependence on successful information systems implementation. MIS Quart. 31(2):219–238.CrossrefGoogle Scholar
  • Stewart DW, Shamdasani PN, Rook DW (2007) Focus Groups: Theory and Practice (Sage, Thousand Oaks, CA).CrossrefGoogle Scholar
  • Sun H (2012) Understanding user revisions when using information system features: Adaptive system use and triggers. MIS Quart. 36(2):453–478.CrossrefGoogle Scholar
  • Sykes TA (2015) Support structures and their impacts on employee outcomes: A longitudinal field study of an enterprise system implementation. MIS Quart. 39(2):437–495.CrossrefGoogle Scholar
  • Sykes TA, Venkatesh V (2015) Explaining post-implementation employee system use and friendship, advice and impeding social ties. MIS Quart. Forthcoming.Google Scholar
  • Sykes TA, Venkatesh V, Johnson JL (2014) Enterprise system implementation and employee job performance: Understanding the role of advice networks. MIS Quart. 38(1):51–72.CrossrefGoogle Scholar
  • Thatcher J, McKnight H, Arsal R, Baker E, Roberts N (2011) The role of trust in post-adoption IT exploration: An empirical examination of knowledge management systems. IEEE Trans. Eng. Management 58(1):56–70.CrossrefGoogle Scholar
  • Venkatesh V, Bala H (2008) Technology acceptance model 3 and a research agenda on interventions. Decision Sci. 39(2):273–315.CrossrefGoogle Scholar
  • Venkatesh V, Bala H, Sykes TA (2010) Impacts of information and communication technology implementations on employees’ jobs in India: A multi-method longitudinal field study. Production Oper. Management 19(5):591–613.CrossrefGoogle Scholar
  • Venkatesh V, Brown SA, Bala H (2013) Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS Quart. 37(1):21–54.CrossrefGoogle Scholar
  • Venkatesh V, Davis FD, Morris MG (2007) Dead or alive? The development, trajectory, and future of technology adoption research. J. Assoc. Inform. Systems 8(4):267–286.Google Scholar
  • Venkatesh V, Brown SA, Maruping LM, Bala H (2008) Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quart. 32(3):483–502.CrossrefGoogle Scholar
  • Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: Toward a unified view. MIS Quart. 27(3):425–478.CrossrefGoogle Scholar
  • Venkatesh V, Thong JYL, Chan FKY, Hu PJ-H, Brown SA (2011) Extending the two-stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Inform. Systems J. 21(6):527–555.CrossrefGoogle Scholar
  • Volkoff O, Strong DM, Elmes MB (2007) Technological embeddedness and organizational change. Organ. Sci. 18(5):832–848.LinkGoogle Scholar
  • Xue Y, Liang H, Wu L (2011) Punishment, justice, and compliance in mandatory IT settings. Inform. Systems Res. 22(2):400–414.LinkGoogle Scholar
  • Yuan F, Woodman RW (2010) Innovative behavior in the workplace: The role of performance and image outcome expectations. Acad. Management J. 53(2):323–342.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.