Understanding information systems success: a hybrid view

References

• Beaudry, A., & Pinsonneault, A. (2005). Understanding user responses to information technology: A coping model of user adaptation. MIS Quarterly, 29(3), 493–524. https://doi.org/10.2307/25148693
   Web of Science ®Google Scholar
• Bélanger, F., Cefaratti, M., Carte, T., & Markham, S. E. (2014). Multilevel research in information systems: Concepts, strategies, problems, and pitfalls. Journal of the Association for Information Systems, 15(9), 614–650. https://doi.org/10.17705/1jais.00371
   Web of Science ®Google Scholar
• Burton-Jones, A., & Gallivan, M. J. (2007). Toward a deeper understanding of system usage in organisations: A multilevel perspective. MIS Quarterly, 31(4), 657–679. https://doi.org/10.2307/25148815
   Web of Science ®Google Scholar
• Burton-Jones, A., & Grange, C. (2013). From use to effective use: A representation theory perspective. Information Systems Research, 24(3), 632–658. https://doi.org/10.1287/isre.1120.0444
   Web of Science ®Google Scholar
• Burton-Jones, A., McLean, E. R., & Monod, E. (2015). Theoretical perspectives in IS research: From variance and process to conceptual latitude and conceptual fit. European Journal of Information Systems, 24(6), 664–679. https://doi.org/10.1057/ejis.2014.31
   Web of Science ®Google Scholar
• Charmaz, K. (2003). Grounded theory: Objectivist and constructivist methods. In N. K. Denzin & Y. S. Lincoln (Eds.), Strategies for qualitative inquiry (2nd ed ed., pp. 249–291). Sage.
   Google Scholar
• DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. https://doi.org/10.1287/isre.3.1.60
   Web of Science ®Google Scholar
• DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
   Web of Science ®Google Scholar
• Gable, G. G., Sedera, D., & Chan, T. (2008). Re-conceptualizing information system success: The IS-impact measurement model. Journal of the Association for Information Systems, 9(7), 18. https://doi.org/10.17705/1jais.00164
   Web of Science ®Google Scholar
• Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183–213. https://doi.org/10.2307/249751
   Web of Science ®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
• Klein, K. J., & Kozlowski, S. W. (2000). Multilevel theory, research, and methods in organisations: Foundations, extensions, and new directions. Jossey-Bass.
   Google Scholar
• Langley, A. (1999). Strategies for theorizing from process data. Academy of Management Review, 24(4), 691–710. https://doi.org/10.5465/amr.1999.2553248
   Web of Science ®Google Scholar
• Langley, A., & Truax, J. (1994). A process study of new technology adoption in smaller manufacturing firms. Journal of Management Studies, 31(5), 619–652. https://doi.org/10.1111/j.1467-6486.1994.tb00632.x
   Web of Science ®Google Scholar
• Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 29(3), 461–491. https://doi.org/10.2307/25148692
   Web of Science ®Google Scholar
• Markus, M. L., & Robey, D. (1988). Information technology and organisational change: Causal structure in theory and research. Management Science, 34(5), 583–598. https://doi.org/10.1287/mnsc.34.5.583
   Web of Science ®Google Scholar
• Miles, M. B., & Huberman, A. M. (1984). Drawing valid meaning from qualitative data: Toward a shared craft. Educational Researcher, 13(5), 20–30. https://doi.org/10.3102/0013189X013005020
   Google Scholar
• Mohr, L. B. (1982). Explaining organisational behavior. Jossey-Bass.
   Google Scholar
• Morgeson, F. P., & Hofmann, D. A. (1999). The structure and function of collective constructs: Implications for multilevel research and theory development. Academy of Management Review, 24(2), 249–265. https://doi.org/10.5465/amr.1999.1893935
   Web of Science ®Google Scholar
• Nan, N. (2011). Capturing bottom-up information technology use processes: A complex adaptive systems model. MIS Quarterly, 35(2), 505–532. https://doi.org/10.2307/23044054
   Web of Science ®Google Scholar
• Negoita, B., Lapointe, L., & Rivard, S. (2018). Collective information systems use: A typological theory. MIS Quarterly, 42(4), 1281–1301. https://doi.org/10.25300/MISQ/2018/13219
   Web of Science ®Google Scholar
• Newman, M., & Robey, D. (1992). A social process model of user-analyst relationships. MIS Quarterly, 16(2), 249–266. https://doi.org/10.2307/249578
   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
• Paré, G., Bourdeau, S., Marsan, J., Nach, H., & Shuraida, S. (2008). Re-examining the causal structure of information technology impact research. European Journal of Information Systems, 17(4), 403–416. https://doi.org/10.1057/ejis.2008.34
   Web of Science ®Google Scholar
• Patton, M. Q. (1990). Qualitative evaluation and research methods. SAGE Publications, inc.
   Google Scholar
• Pentland, B. T. (1999). Building process theory with narrative: From description to explanation. Academy of Management Review, 24(4), 711–724. https://doi.org/10.5465/amr.1999.2553249
   Web of Science ®Google Scholar
• Peterson, M. F. (1998). Embedded organizational events: The units of process in organization science. Organization Science, 9(1), 16–33. https://doi.org/10.1287/orsc.9.1.16
   Web of Science ®Google Scholar
• Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236–263. https://doi.org/10.1057/ejis.2008.15
   Web of Science ®Google Scholar
• Petter, S., DeLone, W., & McLean, E. R. (2013). Information systems success: The quest for the independent variables. Journal of Management Information Systems, 29(4), 7–62. https://doi.org/10.2753/MIS0742-1222290401
   Web of Science ®Google Scholar
• Pettigrew, A. M. (1992). The character and significance of strategy process research.strategic. Management Journal, 13(S2), 5–16. https://doi.org/10.1002/smj.4250130903
   Google Scholar
• Sabherwal, R., & Robey, D. (1995). Reconciling variance and process strategies for studying information system development. Information Systems Research, 6(4), 303–327. https://doi.org/10.1287/isre.6.4.303
   Web of Science ®Google Scholar
• Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8(3), 240–253. https://doi.org/10.1287/isre.8.3.240
   Web of Science ®Google Scholar
• Shaw, T., & Jarvenpaa, S. (1997). Process models in information systems. In A. S. Lee, J. Liebenau, & J. I. DeGross (Eds.), Information Systems and Qualitative Research. International Federation for Information Processing. (pp. 70-100). https://doi.org/10.1007/978-0-387-35309-8_6
   Google Scholar
• Strauss, A., & Corbin, J. (1998). Basics of qualitative research techniques. Sage publications.
   Google Scholar
• Van de Ven, A. H., & Poole, M. S. (2005). Alternative approaches for studying organizational change. Organization Studies, 26(9), 1377–1404. https://doi.org/10.1177/0170840605056907
   Web of Science ®Google Scholar
• Wang, Y., Meister, D., & Wang, Y. (2011). Reexamining relative advantage and perceived usefulness: An empirical study. (Report). International Journal of Information and Communication Technology Education, 7(1), 46–59. https://doi.org/10.4018/jicte.2011010105
   Google Scholar
• Wilson, M., & Howcroft, D. (2002). Re-conceptualising failure: Social shaping meets IS research. European Journal of Information Systems, 11(4), 236–250. https://doi.org/10.1057/palgrave.ejis.3000437
   Web of Science ®Google Scholar
• Zhang, M., & Gable, G. G. (2017). A systematic framework for multilevel theorizing in information systems research. Information Systems Research, 28(2), 203–224. https://doi.org/10.1287/isre.2017.0690
   Web of Science ®Google Scholar