From broken habits to new intentions: how COVID-19 expands our knowledge on post-adoptive use behaviour of digital communication and collaboration

References

• Ågerfalk, P. J. (2014). Insufficient theoretical contribution: A conclusive rationale for rejection? European Journal of Information Systems, 23(6), 593–599. https://doi.org/10.1057/ejis.2014.35
   Web of Science ®Google Scholar
• Ågerfalk, P. J., & Karlsson, F. (2020). Artefactual and empirical contributions in information systems research. European Journal of Information Systems, 29(2), 109–113. https://doi.org/10.1080/0960085X.2020.1743051
   Web of Science ®Google Scholar
• Anderson, C. (2010). Presenting and evaluating qualitative research. American Journal of Pharmaceutical Education, 74(8), 2–4. https://doi.org/10.5688/aj7408141
   PubMed Web of Science ®Google Scholar
• Bagayogo, F. F., Lapointe, L., & Bassellier, G. (2014). Enhanced use of IT: A new perspective on post-adoption. Journal of the Association for Information Systems, 15(7), 361–387. https://doi.org/10.17705/1jais.00367
   Web of Science ®Google Scholar
• Behrendt, S., Klier, J., Klier, M., & Richter, A. (2015). The impact of formal hierarchies on enterprise social networking behavior. Proceedings of the 36th International Conference on Information Systems (ICIS).
   Google Scholar
• Benlian, A. (2015). IT feature use over time and its impact on individual task performance. Journal of the Association for Information Systems, 16(3), 144–173. https://doi.org/10.17705/1jais.00391
   Web of Science ®Google Scholar
• Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010). Predicting collaboration technology use: integrating technology adoption and collaboration research. Journal of Management Information Systems, 27(2), 9–54. https://doi.org/10.2753/MIS0742-1222270201
   Web of Science ®Google Scholar
• Burton-Jones, A., & Straub, D. W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246. https://doi.org/10.1287/isre.1060.0096
   Web of Science ®Google Scholar
• Burton-Jones, A., & Gallivan, M. J. (2007). Toward a deeper understanding of system usage in organizations: A multilevel perspective. MIS Quarterly, 31(4), 657. https://doi.org/10.2307/25148815
   Web of Science ®Google Scholar
• Califf, C., Sarker, S., & Sarker, S. (2020). The bright and dark sides of technostress: A mixed-methods study involving healthcare IT. MIS Quarterly, 44(2), 809–856. https://doi.org/10.25300/MISQ/2020/14818
   Web of Science ®Google Scholar
• Daft, R. L., & Lengel, R. H. (1983). Information richness: A new approach to managerial behavior and organization design. Texas A and M University College Station College of Business Administration.
   Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Dennis, A. R., Fuller, R. M., & Valacich, J. S. (2008). Media, tasks, and communication processes. A theory of media synchronicity. MIS Quarterly, 32(3), 575–600. https://doi.org/10.2307/25148857
   Web of Science ®Google Scholar
• DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121–147. https://doi.org/10.1287/orsc.5.2.121
   Web of Science ®Google Scholar
• Ferratt, T., Prasad, J., & Dunne, E. J. (2018). Fast and slow processes underlying theories of information technology use. Journal of the Association for Information Systems, 19(1), 1–22. https://doi.org/10.17705/1jais.00482
   Web of Science ®Google Scholar
• Frank, L. , Gimpel, H. , Schmidt, M. , &Schoch, M. (2017). Emergent User Roles of a Digital Workplace: A Network Analysis Based on Trace Data Proceedings of the 38th International Conference on Information Systems (ICIS),1–18.
   Google Scholar
• Füller, J., Hutter, K., Hautz, J., & Matzler, K. (2014). User roles and contributions in innovation-contest communities. Journal of Management Information Systems, 31(1), 273–308. https://doi.org/10.2753/MIS0742-1222310111
   Web of Science ®Google Scholar
• Gephart, R. P. (2004). Sensemaking and new media at work. American Behavioral Scientist, 48(4), 479–495. https://doi.org/10.1177/0002764204270283
   Web of Science ®Google Scholar
• Glaser, B. G., & Strauss, A. L. (2009). The discovery of grounded theory. Strategies for qualitative research. New Brunswick:Aldine.
   Google Scholar
• Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213. https://doi.org/10.2307/249689
   Web of Science ®Google Scholar
• Goodhue, D. L. (1995). Understanding user evaluations of information systems. Management Science, 41(12), 1827–1844. https://doi.org/10.1287/mnsc.41.12.1827
   Web of Science ®Google Scholar
• Griffith, T. L., & Northcraft, G. B. (1994). Distinguishing between the forest and the trees: Media, features, and methodology in electronic communication research. Organization Science, 5(2), 272–285. https://doi.org/10.1287/orsc.5.2.272
   Web of Science ®Google Scholar
• Griffith, T. L. (1999). Technology features as triggers for sensemaking. Academy of Management Review, 24(3), 472–488. https://doi.org/10.5465/amr.1999.2202132
   Web of Science ®Google Scholar
• Herzog, C., Richter, A., & Steinhueser, M. (2015). Towards a framework for the evaluation design of enterprise social software. Proceedings of the 36th International Conference on Information Systems (ICIS).
   Google Scholar
• Hu, P. J., Chau, P. Y., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112. https://doi.org/10.1080/07421222.1999.11518247
   Web of Science ®Google Scholar
• Jasperson, J., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoption behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525–557. https://doi.org/10.2307/25148694
   Web of Science ®Google Scholar
• Kelly, J. (2020). The massive work-from-home-COVID-19 test was a great success and will be the new norm, Forbes, https://www.forbes.com. Retrieved August 2, 2020, from https://www.forbes.com/sites/jackkelly/2020/05/11/the-massive-work-from-home-covid-19-test-was-a-great-success-and-will-be-the-new-norm/
   Google Scholar
• Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management Science, 51(5), 741–755. https://doi.org/10.1287/mnsc.1040.0326
   Web of Science ®Google Scholar
• Leech, B. L. (2002). Asking questions: Techniques for semistructured interviews. Political Science and Politics, 35(4), 665–668. https://doi.org/10.1017/S1049096502001129
   Web of Science ®Google Scholar
• Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705. https://doi.org/10.2307/25148817
   Web of Science ®Google Scholar
• Lou, H., Luo, W., & Strong, D. (2000). Perceived critical mass effect on groupware acceptance. European Journal of Information Systems, 9(2), 91–103. https://doi.org/10.1057/palgrave.ejis.3000358
   Web of Science ®Google Scholar
• Louis, M. R., & Sutton, R. I. (1991). Switching cognitive gears: From habits of mind to active thinking. Human Relations, 44(1), 55–76. https://doi.org/10.1177/001872679104400104
   Web of Science ®Google Scholar
• Lucas, H. C., & Spitler, V. K. (1999). Technology use and performance: A field study of broker workstations. Decision Sciences, 30(2), 291–311. https://doi.org/10.1111/j.1540-5915.1999.tb01611.x
   Web of Science ®Google Scholar
• Maitlis, S., & Christianson, M. (2014). Sensemaking in organizations: Taking stock and moving forward. The Academy of Management Annals, 8(1), 57–125. https://doi.org/10.1080/19416520.2014.873177
   Web of Science ®Google Scholar
• Massey, A. P., & Montoya-Weiss, M. M. (2006). Unraveling the temporal fabric of knowledge conversion: A model of media selection and use. MIS Quarterly, 30(1), 99. https://doi.org/10.2307/25148719
   Web of Science ®Google Scholar
• McDonald, T., & Siegall, M. (1992). The effects of technological self-efficacy and job focus on job performance, attitudes, and withdrawal behaviors. The Journal of Psychology, 126(5), 465–475. https://doi.org/10.1080/00223980.1992.10543380
   Web of Science ®Google Scholar
• Mesgari, M., & Okoli, C. (2019). Critical review of organisation-technology sensemaking: Towards technology materiality, discovery, and action. European Journal of Information Systems, 28(2), 205–232. https://doi.org/10.1080/0960085X.2018.1524420
   Web of Science ®Google Scholar
• Microsoft. (2021). Microsoft Teams help & learning. Retrieved September 24, 2021, from https://support.microsoft.com/en-us/teams
   Google Scholar
• Möhring, K., Naumann, E., Reifenscheid, M., Weiland, A., Blom, A. G., Wenz, A., Rettig, T., Lehrer, R., Krieger, U., Juhl, S., Friedel, S., Fikel, M., & Cornesse, C. (2020). Die Mannheimer Corona-Studie: Schwerpunktbericht zur Nutzung und Akzeptanz von Homeoffice in Deutschland während des Corona-Lockdowns, University of Mannheim. Retrieved August 2, 2020, from https://www.uni-mannheim.de/media/Einrichtungen/gip/Corona_Studie/MannheimerCoronaStudie_Homeoffice_2020-07-09.pdf
   Google Scholar
• Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
   Web of Science ®Google Scholar
• Myers, M. D., & Newman, M. (2007). The qualitative interview in IS research: Examining the craft. Information and Organization, 17(1), 2–26. https://doi.org/10.1016/j.infoandorg.2006.11.001
   Google Scholar
• Orlikowski, W. J., Yates, J., Okamura, K., & Fujimoto, M. (1995). Shaping electronic communication: The metastructuring of technology in the context of use. Organization Science, 6(4), 423–444. https://doi.org/10.1287/orsc.6.4.423
   Web of Science ®Google Scholar
• Ortiz de Guinea, A., & Webster, J. (2017). Combining variance and process in information systems research: Hybrid approaches. Information and Organization, 27(3), 144–162. https://doi.org/10.1016/j.infoandorg.2017.06.002
   Web of Science ®Google Scholar
• Parker, R. E., & Ingram, A. L. (2011). Considerations in choosing online collaboration systems: Functions, uses, and effects. Journal of the Research Center for Educational Technology, 7(1), 2–15.
   Google Scholar
• Pawlowski, J. M., Bick, M., Peinl, R., Thalmann, S., Maier, R., Hetmank, L., Kruse, P., Martensen, M., & Pirkkalainen, H. (2014). Social knowledge environments. Business & Information Systems Engineering, 6(2), 81–88. https://doi.org/10.1007/s12599-014-0318-4
   Web of Science ®Google Scholar
• 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. https://doi.org/10.25300/MISQ/2013/37.1.10
   Web of Science ®Google Scholar
• Riemer, K., Stieglitz, S., & Meske, C. (2015). From top to bottom. Business & Information Systems Engineering, 57(3), 197–212. https://doi.org/10.1007/s12599-015-0375-3
   Web of Science ®Google Scholar
• Rosing, M. V., White, S., Cummins, F., & Man, H. D. (2015). Business Process Model and Notation—BPMN . In The complete business process handbook (pp. 433–457). Elsevier. https://www.sciencedirect.com/book/9780127999593/the-complete-business-process-handbook
   Google Scholar
• Sabherwal, R., Jeyaraj, A., & Chowa, C. (2006). Information system success: Individual and organizational determinants. Management Science, 52(12), 1849–1864. https://doi.org/10.1287/mnsc.1060.0583
   Web of Science ®Google Scholar
• Saga, V. L., & Zmud, R. W. (1993). The nature and determinants of IT acceptance, routinization, and infusion. Proceedings of the IFIP TC8 Working Conference on Diffusion, Transfer and Implementation of Information Technology, 67–86.
   Google Scholar
• Sandberg, J., & Tsoukas, H. (2015). Making sense of the sensemaking perspective: Its constituents, limitations, and opportunities for further development. Journal of Organizational Behavior, 36(S1), S6–S32. https://doi.org/10.1002/job.1937
   Web of Science ®Google Scholar
• Schafer, P. (2020). Introducing insights in Teams to power wellbeing and productivity, Microsoft, techcommunity.microsoft.com. Retrieved September 23, 2020, from https://techcommunity.microsoft.com/t5/workplace-analytics-myanalytics/introducing-insights-in-teams-to-power-wellbeing-and/ba-p/1675767
   Google Scholar
• Spataro, J. (2020). Remote work trend report: Meetings, Microsoft, microsoft.com. Retrieved 2 August, 2020, from https://www.microsoft.com/en-us/microsoft-365/blog/2020/04/09/remote-work-trend-report-meetings/
   Google Scholar
• Speier, C., Valacich, J. S., & Vessey, I. (1999). The influence of task interruption on individual decision making: An information overload perspective. Decision Sciences, 30(2), 337–360. https://doi.org/10.1111/j.1540-5915.1999.tb01613.x
   Web of Science ®Google Scholar
• Strauss, A., & Corbin, J. (1990). Basics of qualitative research. Sage publications.
   Google Scholar
• Sun, H. (2012). Understanding user revisions when using information system features: Adaptive system use and triggers. MIS Quarterly, 36(2), 453. https://doi.org/10.2307/41703463
   Web of Science ®Google Scholar
• 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. https://doi.org/10.25300/MISQ/2017/41.3.11
   Web of Science ®Google Scholar
• Taylor, J. R., & van Every, E. J. (1999). The emergent organization. Routledge.
   Google Scholar
• Tibshirani, R., Walther, G., & Hastie, T. (2001). Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(2), 411–423. https://doi.org/10.1111/1467-9868.00293
   Web of Science ®Google Scholar
• Trevino, L. K., Lengel, R. H., & Daft, R. L. (1987). Media symbolism, media richness, and media choice in organizations. Communication Research, 14(5), 553–574. https://doi.org/10.1177/009365087014005006
   Web of Science ®Google Scholar
• van Alstyne, M., & Zhang, J. (2003). EMailNet: A system for automatically mining social networks from organizational email communication. North American Association for Computational Social and Organization Sciences.
   Google Scholar
• van Slyke, C., Ilie, V., Lou, H., & Stafford, T. (2007). Perceived critical mass and the adoption of a communication technology. European Journal of Information Systems, 16(3), 270–283. https://doi.org/10.1057/palgrave.ejis.3000680
   Web of Science ®Google Scholar
• Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27(3), 451–481. https://doi.org/10.1111/j.1540-5915.1996.tb00860.x
   Web of Science ®Google Scholar
• Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
   Web of Science ®Google Scholar
• Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483–502. https://doi.org/10.2307/25148853
   Web of Science ®Google Scholar
• Venkatesh, V., 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. https://doi.org/10.2307/41410412
   Web of Science ®Google Scholar
• Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: guidelines for conducting mixed methods research in information systems. MIS Quarterly, 37(1), 21–54. https://doi.org/10.25300/MISQ/2013/37.1.02
   Web of Science ®Google Scholar
• Venkatesh, V., Brown, S. A., & Sullivan, Y. W. (2016). Guidelines for conducting mixed-methods research: An extension and illustration. Journal of the Association for Information Systems, 17(7), 435–494. https://doi.org/10.17705/1jais.00433
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428
   Web of Science ®Google Scholar
• Weick, K. E. (1979). The social psychology of organizing (2nd edn ed.). Addison-Wesley.
   Google Scholar
• Weick, K. E. (1995). Sensemaking in organizations. Sage publications, Thousand Oaks.
   Google Scholar
• Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409–421. https://doi.org/10.1287/orsc.1050.0133
   Web of Science ®Google Scholar