research-article

IS Reappraisal and Technology Adaptation Behaviors: A Longitudinal Study During an IS Implementation

Authors:

Christoph Weinert,

Christian Maier,

Tim WeitzelAuthors Info & Claims

ACM SIGMIS Database: the DATABASE for Advances in Information Systems, Volume 51, Issue 4

Pages 11 - 39

https://doi.org/10.1145/3433148.3433151

Published: 02 November 2020 Publication History

Abstract

Employees have to adapt to newly implemented information systems (IS) because they are often perceived as radical changes or disruptions. To understand such adaptation behavior, IS research suggests that employees first appraise the new IS and second perform technology adaptive behaviors. However, while the psychology literature indicates that adaptation is a continuous process unfolding over time, previous IS literature treats adaptation towards IS implementation as a rather singular, noniterative process. As firms continue to implement IS, an understanding of reappraisal and the influence of technology adaptation behavior is vital to ensure successful implementations. Therefore, the present paper investigates reappraisal and the influences of four different technology adaptation behaviors. We conducted a longitudinal study and used hierarchical linear modeling (HLM) to validate our research model. The findings reveal that employees reappraise the newly implemented IS over time regarding perceived opportunity, threat, and controllability and demonstrate that technology adaption behaviors influence such reappraisal. One specific finding is that employees might get into positive or negative reappraisal loops. We thereby contribute to research by extending the adaptation behavior literature and add a new piece of the puzzle to understand how employees adapt towards newly implemented IS over time.

References

[1]

Aguirre-Urreta, M. I., & Hu, J. (2019). Detecting common method bias. SIGMIS Database, 50(2), 45--70.

Digital Library

[2]

Ahuja, M. K., & Thatcher, J. B. (2005). Moving beyond intentions and toward the theory of trying: Effects of work environment and gender on post-adoption information technology use. MIS Quarterly, 29(3), 427--459.

Digital Library

[3]

Anderson, B. B., Vance, A., Kirwan, C. B., Jenkins, J. L., & Eargle, D. (2016). From warning to wallpaper: Why the brain habituates to security warnings and what can be done about it. Journal of Management Information Systems, 33(3), 713--743.

[4]

Association for Information and Image Management (2018). What is ECM enterprise content management, http://www.aiim.org/What-is-ECM-Enterprise-Content-Management. Accessed 5 March 2018.

[5]

Bala, H., & Venkatesh, V. (2013). Changes in employees' job characteristics during an enterprise system implementation: A latent growth modeling perspective. MIS Quarterly, 37(4), 1113-A7.

Digital Library

[6]

Bala, H., & Venkatesh, V. (2015). Adaptation to information technology: A holistic nomological network from implementation to job outcomes. Management Science, 62(1), 156--179.

[7]

Barki, H., Titah, R., & Boffo, C. (2007). Information system use-related activity: An expanded behavioral conceptualization of individual-level information system use. Information Systems Research, 18(2),173--192.

Digital Library

[8]

Baskerville, R., Rowe, F., & Wolff, F.-C. (2018). Integration of information systems and cybersecurity countermeasures. SIGMIS Database, 49(1), 33--52.

Digital Library

[9]

Beaudry, A., & Pinsonneault, A. (2005). Understanding user responses to information technology: A coping model of user adaptation. MIS Quarterly, 29(3), 493--524.

Digital Library

[10]

Beaudry, A., & Pinsonneault, A. (2010). The other side of acceptance: Studying the direct and indirect effects of emotions on information technology use. MIS Quarterly, 34(4), 689.

Digital Library

[11]

Bhattacherjee, A., Davis, C. J., Connolly, A. J., & Hikmet, N. (2017). User response to mandatory IT use: a coping theory perspective. European Journal of Information Systems, 9(2), 204.

[12]

Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1994). Time series analysis: Forecasting and control. Englewood Cliffs, NJ: Prentice-Hall.

Digital Library

[13]

Burton-Jones, A., & Straub, D. W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228--246.

Digital Library

[14]

Carmines, E. G., & Zeller, R. A. (2008). Reliability and validity assessment. Newbury Park, Calif: Sage.

[15]

Carver, C. S., Scheier, M. F., & Weintraub, J. K. (1989). Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56(2), 267--283.

[16]

Crossler, R., & Bélanger, F. (2014). An extended perspective on individual security behaviors. SIGMIS Database, 45(4), 51--71.

Digital Library

[17]

Elie-Dit-Cosaque, C. M., & Straub, D. W. (2011). Opening the black box of system usage: User adaptation to disruptive IT. European Journal of Information Systems, 20(5), 589--607.

[18]

Folkman, S. (1982). An approach to the measurement of coping. Journal of Organizational Behavior, 3(1), 95--107.

[19]

Folkman, S., Lazarus, R. S., Gruen, R. J., & DeLongis, A. (1986). Appraisal, coping, health status, and psychological symptoms. Journal of Personality and Social Psychology, 50(3), 571--579.

[20]

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39--50.

[21]

Gartner (2019). Information technology (IT) implementation spending worldwide from 2014 to 2019 (in billion U.S. dollars), https://www.statista.com/statistics/505171/worldwide-it-implementation-spending/. Accessed 1 February 2019.

[22]

Groves, P. M., & Thompson, R. F. (1970). Habituation: A dual-process theory. Psychological Review, 77(5), 419--450.

[23]

Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405--431.

[24]

IBM Corp. Released (2016). IBM SPSS Statistics for Windows: Version 21.0. Armonk, NY: IBM Corp.

[25]

Jasperson, J., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525--557.

Digital Library

[26]

Kane, G. C., & Labianca, G. (2011). IS avoidance in health-care groups: A multilevel investigation. Information Systems Research, 22(3), 504--522.

Digital Library

[27]

Kher, H. V., & Serva, M. A. (2014). Changing the way we study change. SIGMIS Database, 45(2), 45--60.

Digital Library

[28]

Klein, K. J., & Kozlowski, S. W. J. (eds.) (2000). Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions. San Francisco, Great Britain: Jossey-Bass.

[29]

Ko, D.-G., & Dennis, A. R. (2011). Profiting from knowledge management: The impact of time and experience. Information Systems Research, 22(1), 134--152.

Digital Library

[30]

Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 29(3). 461--491.

Digital Library

[31]

Laumer, S., Beimborn, D., Maier, C., and Weinert, C. (2013). Enterprise content management. Business & Information Systems Engineering, 5(6), 449--452.

[32]

Laumer, S., Maier, C., Eckhardt, A., & Weitzel, T. (2016a). User personality and resistance to mandatory information systems in organizations: A theoretical model and empirical test of dispositional resistance to change. Journal of Information Technology, 31(1), 67--82.

[33]

Laumer, S., Maier, C., Eckhardt, A., & Weitzel, T. (2016b). Work routines as an object of resistance during information systems implementations: Theoretical foundation and empirical evidence. European Journal of Information Systems, 25(4), 317--343.

[34]

Laumer, S., Maier, C., & Weitzel, T. (2017). Information quality, user satisfaction, and the manifestation of workarounds: A qualitative and quantitative study of enterprise content management system users. European Journal of Information Systems, 26(4), 333--360.

[35]

Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer Pub. Co.

[36]

Li, X., Hsieh, J. J. P.-A., & Rai, A. (2013). Motivational differences across post-acceptance information system usage behaviors: An investigation in the business intelligence systems context. Information Systems Research, 24(3), 659--682.

[37]

Liang, H., Saraf, N., Hu, Q., & 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.

Digital Library

[38]

Liang, H., & Xue, Y. (2009). Avoidance of information technology threats: A theoretical perspective. MIS Quarterly, 33(1), 71--90.

Digital Library

[39]

Liang, H., & Xue, Y. (2010). Understanding security behaviors in personal computer usage: A threat avoidance perspective. Journal of the Association for Information Systems, 11(7), 394--413.

[40]

Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705--737.

Digital Library

[41]

Maier, C., Laumer, S., Weinert, C., & Weitzel, T. (2015). The effects of technostress and switching stress on discontinued use of social networking services: A study of Facebook use. Information Systems Journal, 25(3), 275--308.

Digital Library

[42]

Maier, C., Laumer, S., Wirth, J., & Weitzel, T. (2019). Technostress and the hierarchical levels of personality: A two-wave study with multiple data samples. European Journal of Information Systems, 62(1), 1--27.

[43]

Maier, C., Laumer, S., Thatcher, J.B., Sun, H., Weinert, C., & Weitzel, T. (2020). Social Networking Site Use Resumption: A Model of Return Migration. Forthcoming in: Journal of the Association for Information Systems

[44]

McCullagh, P., & Nelder, J. A. (1999). Generalized linear models. London: Chapman & Hall.

[45]

Morris, M., & Venkatesh, V. (2010). Job Characteristics and Job Satisfaction: Understanding the role of enterprise resource planning system implementation. MIS Quarterly, 34(1), 143.

Digital Library

[46]

Otondo, R. F., Barnett, T., Kellermanns, F. W., Pearson, A. W., & Pearson, R. A. (2009). Assessing information technology use over time with growth modeling and hierarchical linear modeling: A tutorial. Communications of the Association for Information Systems, 25, 607--640.

[47]

Podsakoff, P. M., MacKenzie, S. B., Jeong-Yeon Lee, & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.

[48]

Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly, 36(1), 21--42.

Digital Library

[49]

Polites, G. L., & Karahanna, E. (2013). The embeddedness of information systems habits in organizational and individual level routines: Development and disruption. MIS Quarterly, 37(1), 221--246.

Digital Library

[50]

Rabe-Hesketh, S., & Skrondal, A. (2012). Multilevel and longitudinal modeling using stata. College Station, Texas: StataCorp LP.

Digital Library

[51]

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Thousand Oaks, Calif.: Sage Publ.

[52]

Schmitz, K. W., Teng, J. T. C., & Webb, K. J. (2016). Capturing the complexity of malleable it use: Adaptive structuration theory for individuals. MIS Quarterly, 40(3), 663-B19.

Digital Library

[53]

Schwarz, A., Rizzuto, T., Carraher-Wolverton, C., Roldán, J. L., & Barrera-Barrera, R. (2017). Examining the impact and detection of the "urban legend" of common method bias. SIGMIS Database, 48(1), 93--119.

Digital Library

[54]

Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York, Oxford: Oxford University Press.

[55]

Sun, H. (2012). Understanding user revisions when using information system features: Adaptive system use and triggers. MIS Quarterly, 36(2), 453--478.

Digital Library

[56]

Sykes, A. T. (2015). Support structures and their impacts on employee outcomes: A longitudinal field study of an enterprise system implementation. MIS Quarterly, 39(2), 473.

Digital Library

[57]

Sykes, T. A., & Venkatesh, V. (2017). Explaining post-implementation employee system use and job performance: Impacts of the content and source of social network ties. MIS Quarterly, 41(3), 917--936.

Digital Library

[58]

Taylor, S. E. (2011). Social Support : A Review, The Oxford Handbook of Health Psychology.

[59]

Thatcher, J. B., McKnight, D. H., Baker, E. W., Arsal, R. E., & Roberts, N. H. (2011). The Role of trust in postadoption IT exploration: An empirical examination of knowledge management systems. IEEE Transactions on Engineering Management, 58(1), 56--70.

[60]

Turel, O. (2014). Quitting the use of a habituated hedonic information system: A theoretical model and empirical examination of Facebook users. European Journal of Information Systems, 24(4), 431--446.

[61]

Turel, O., & Qahri-Saremi, H. (2017). Problematic use of social networking sites: Antecedents and consequence from a dual-system theory perspective. Journal of Management Information Systems, 33(4), 1087--1116.

[62]

Vance, A., Jenkins, J. L., Anderson, B. B., Bjornn, D. K., & Kirwan, B. C. (2018). Tuning out security warnings: A longitudinal examination of habituation through fMRI, eye tracking, and field experiments. MIS Quarterly, 42(2), 355--380.

Digital Library

[63]

Vedadi, A., & Warkentin, M. (2018). Secure behavior over time. SIGMIS Database, 49(1), 39--48.

Digital Library

[64]

Venkatesh, V., Bala, H., & Sykes, T. A. (2010). Impacts of information and communication technology implementations on employees' jobs in service organizations in india: A multi-method longitudinal field study. Production and Operations Management, 19(5), 591--613.

[65]

Venkatesh, V., L. Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157--178.

Digital Library

[66]

Venkatesh, V., Morris, M. G., Gordon B. Davis, & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425--478.

[67]

Weinert, C. (2018). Coping with discrepant information technology events: A literature review. Proceedings of the 26st European Conference of Information Systems - ECIS 2018.

[68]

Weinert, C., Maier, C., Laumer, S., & Weitzel, T. (2019). How do users respond to technostress? An empirical analysis of proactive and reactive coping. Proceedings of the 52nd Hawaii International Conference on System Sciences.

[69]

Wooldridge, J. M. (2002). Introductory econometrics: A modern approach. Mason, Ohio: Thomson/South-Western.

[70]

Yan, L., & Tan, Y. (2014). Feeling Blue?: Go Online: An Empirical Study of Social Support Among Patients. Information Systems Research, 25(4), 690--709.

Digital Library

Cited By

Deranek KHewitt B(2022)Knowledge Management Model Development and Validation Using an ERP SimulationJournal of Computer Information Systems10.1080/08874417.2022.212893663:5(1139-1152)Online publication date: 17-Oct-2022
https://doi.org/10.1080/08874417.2022.2128936
Weinert CMaier CLaumer SWeitzel T(2022)Repeated IT Interruption: Habituation and Sensitization of User ResponsesJournal of Management Information Systems10.1080/07421222.2021.202341139:1(187-217)Online publication date: 11-Apr-2022
https://doi.org/10.1080/07421222.2021.2023411

Index Terms

IS Reappraisal and Technology Adaptation Behaviors: A Longitudinal Study During an IS Implementation
1. Information systems
  1. Information systems applications
    1. Enterprise information systems

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Published In

cover image ACM SIGMIS Database: the DATABASE for Advances in Information Systems

ACM SIGMIS Database: the DATABASE for Advances in Information Systems Volume 51, Issue 4

November 2020

131 pages

ISSN:0095-0033

EISSN:1532-0936

DOI:10.1145/3433148

Editors:
Deborah J. Armstrong
Florida State University, Tallahassee, FL
,
Tom Stafford
Louisiana Tech University, Ruston, LA
,
Mohamed Tazkarji
Louisiana Tech University, Ruston, LA
,
Heidi Seward
Baylor University, Waco, TX

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Copyright © 2020 Copyright is held by the owner/author(s).

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Published: 02 November 2020

Published in SIGMIS Volume 51, Issue 4

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Cited By

Deranek KHewitt B(2022)Knowledge Management Model Development and Validation Using an ERP SimulationJournal of Computer Information Systems10.1080/08874417.2022.212893663:5(1139-1152)Online publication date: 17-Oct-2022
https://doi.org/10.1080/08874417.2022.2128936
Weinert CMaier CLaumer SWeitzel T(2022)Repeated IT Interruption: Habituation and Sensitization of User ResponsesJournal of Management Information Systems10.1080/07421222.2021.202341139:1(187-217)Online publication date: 11-Apr-2022
https://doi.org/10.1080/07421222.2021.2023411

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