Skip to main content
SpringerLink
Log in

Mindfully resisting the bandwagon: reconceptualising IT innovation assimilation in highly turbulent environments

  • Research Article
  • Published:
Journal of Information Technology

Abstract

Environmental turbulence (ET), as exemplified by the recent financial crisis between 2007 and 2009, leads to a high degree of uncertainty, and fosters mimicry and resulting bandwagon phenomena in information technology (IT) innovation assimilation processes. In these highly turbulent environments, ‘mindless’ IT innovation assimilation by participating organizations plays a major role in the manifestation and facilitation of mimetic influences. Even in less turbulent economic cycles, highly turbulent industries such as the financial services industry have to deal with demanding IT innovation assimilation processes, and are exposed to varying levels of ET and mimicry. Drawing upon the theory of dynamic capabilities, organizational mindfulness (OM) is one viable means to mitigate the potentially negative consequences of mimetic behaviour. Here, mindful organizations are more successful in overcoming situations of high dynamism, and sometimes are even able to exploit them. So far, little empirical research has been conducted to quantify the influence of OM in scenarios of high dynamism and mimicry. On the basis of 302 complete responses from senior IT managers in the financial services industry from the Anglo-Saxon countries (the United States, Canada and the United Kingdom), this research contributes to a deeper understanding of the interaction of OM with institutional pressures against the background of ET.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2

Similar content being viewed by others

References

  • Abrahamson, E. and Rosenkopf, L. (1990). When Do Bandwagon Diffusions Roll? How Far Do They Go? And When Do They Roll Backwards? A Computer Simulation, Academy of Management Best Paper Proceedings 50 (1): 155–159.

    Article  Google Scholar 

  • Adler, P.S., Glodoftas, B. and Levine, D.L. (1999). Flexibility Versus Efficiency? A Case Study of Model Changeovers in the Toyota Production System, Organization Science 10 (1): 43–68.

    Article  Google Scholar 

  • Aldrich, H.E. and Fiol, C.M. (1994). Fools Rush In? The Institutional Context of Industry Creation, Academy of Management Review 19 (1): 645–670.

    Google Scholar 

  • Ang, S. and Cummings, L.L. (1997). Strategic Response to Institutional Influences on Information Systems Outsourcing, Organization Science 8 (3): 235–256.

    Article  Google Scholar 

  • Armstrong, J. and Overton, T. (1977). Estimating Non-Response Bias in Mail Surveys, Journal of Marketing Research 14 (8): 396–402.

    Article  Google Scholar 

  • Bagozzi, R.P. and Phillips, L.W. (1991). Assessing Construct Validity in Organizational Research, Administrative Science Quarterly 36 (3): 421–458.

    Article  Google Scholar 

  • Barua, A., Konana, P., Whinston, A.B. and Fang, Y. (2004). An Empirical Investigation of Net-Enabled Business Value, MIS Quarterly 28 (4): 585–620.

    Google Scholar 

  • Battilana, J., Leca, B. and Boxenbaum, E. (2009). How Actors Change Institutions: Towards a theory of institutional entrepreneurship, Academy of Management Annals 3 (1): 65–107.

    Article  Google Scholar 

  • Box, G.E.P., Hunter, J.S. and Hunter, W.G. (2005). Statistics for Experimenters: Design, innovation, and discovery, 2nd edn., New York: Wiley-Interscience.

    Google Scholar 

  • Buganza, T., Dell’Era, C. and Verganti, R. (2009). Exploring the Relationships Between Product Development and Environmental Turbulence: The case of mobile TLC services, Journal of Product Innovation Management 26 (3): 308–321.

    Article  Google Scholar 

  • Butler, B.S. and Gray, P.H. (2006). Reliability, Mindfulness, and Information Systems, MIS Quarterly 30 (2): 211–224.

    Google Scholar 

  • Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J. and Brandic, I. (2009). Cloud Computing and Emerging IT Platforms: Vision, hype, and reality for delivering computing as the 5th utility, Future Generation Computer Systems 25 (6): 599–616.

    Article  Google Scholar 

  • Campbell, D.T. and Fiske, D.W. (1959). Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix, Psychological Bulletin 56 (1): 81–105.

    Article  Google Scholar 

  • Cassel, C., Hackl, P. and Westlund, A. (1999). Robustness of Partial Least-Squares Method for Estimating Latent Variable Quality Structures, Journal of Applied Statistics 26 (4): 435–446.

    Article  Google Scholar 

  • Chambers, J.M., Cleveland, W.S., Kleiner, B. and Tukey, P.A. (1983). Graphical Methods for Data Analysis, Belmont, CA: Wadsworth.

    Google Scholar 

  • Chin, W.W. (1998). The Partial Least Squares Approach to Structural Equation Modeling, in G.A. Marcoulides (ed.) Modern Methods for Business Research, Hillsdale, NY: Lawrence Erlbaum Associates, pp. 295–336.

    Google Scholar 

  • Chin, W.W. (2000). Frequently asked questions: Partial least squares and PLS-graphs, [WWW document] http://disc-nt.cba.uh.edu/chin/plsfaq/plsfaq.htm (accessed 2 September 2011).

  • Chin, W.W., Marcolin, B.L. and Newsted, P.R. (2003). A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study, Information Systems Research 14 (2): 189–217.

    Article  Google Scholar 

  • D’Agostino, R.B., Belanger, A. and D’Agostino Jr, R.B. (1990). A Suggestion for Using Powerful and Informative Tests of Normality, American Statistician 44 (1): 316–332.

    Google Scholar 

  • Davamanirajan, P., Kauffman, R.J., Kriebel, C.H. and Mukhopadhyay, T. (2006). Systems Design, Process Performance, and Economic Outcomes in International Banking, Journal of Management Information Systems 23 (2): 65–90.

    Article  Google Scholar 

  • Davenport, T. (1993). Process Innovation: Reengineering work through IT, Boston, MA: Harvard Business School.

    Google Scholar 

  • DiMaggio, P.W. and Powell, W.W. (1983). The Iron Cage Revisited: Institutional isomorphism and collective rationality in organizational fields, American Sociological Review 48 (2): 147–160.

    Article  Google Scholar 

  • Dixit, A.K. and Pindyck, R.S. (1994). Investment under Uncertainty, Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Dong, S., Xu, S.X. and Zhu, K.X. (2009). Information Technology in Supply Chains: The value of IT-enabled resources under competition, Information Systems Research 20 (1): 18–32.

    Article  Google Scholar 

  • Efron, B. (1981). Nonparametric standard errors and confidence intervals, Canadian Journal of Statistics 9 (2): 139–172.

    Article  Google Scholar 

  • FDIC (2012). Failed Bank List, [WWW document] http://www.fdic.gov/bank/individual/failed/banklist.html (accessed: 18 April 2012).

  • Festinger, L. (1967). A Theory of Cognitive Dissonance, Evanston, IL: Row Peterson.

    Google Scholar 

  • Fichman, R.G. (2001). The Role of Aggregation in the Measurement of IT-related Organizational Innovation, MIS Quarterly 25 (4): 427–455.

    Article  Google Scholar 

  • Fichman, R.G. (2004). Going Beyond the Dominant Paradigm for Information Technology Innovation Research: Emerging concepts and methods, Journal of the Association for Information Systems 5 (8): 314–355.

    Google Scholar 

  • Fiol, C.M. and O’Connor, E.J. (2003). Waking Up! Mindfulness in the Face of Bandwagons, Academy of Management Review 28 (1): 54–70.

    Google Scholar 

  • Fornell, C. (1992). A National Customer Satisfaction Barometer: The Swedish experience, Journal of Marketing 56 (1): 6–21.

    Article  Google Scholar 

  • Fornell, C. and Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and statistics, Journal of Marketing Research 18 (1): 382–388.

    Article  Google Scholar 

  • Foster, I. (2002). What is the Grid? A Three Point Checklist, GRID Today 1 (6): 22–25.

    Google Scholar 

  • Foster, I. and Kesselman, C. (1999). The Grid: Blueprint for a new computing infrastructure, San Francisco, CA: Morgan Kaufmann.

    Google Scholar 

  • Foster, I., Zhao, Y., Raicu, I. and Lu, S. (2008). Cloud Computing and Grid Computing 360-Degree Compared, in Proceedings of the IEEE Grid Computing Environments Workshop (Austin, TX, USA, 2008); San Diego, CA: IEEE Computer Society Press.

  • Gartner (2010). Forecast: Public Cloud Services, Worldwide and Regions, Industry Sectors, 2009–2014, [WWW document] http://www.gartner.com/DisplayDocument?ref=clientFriendlyUrl&id=1378513 (accessed 29 March 2011).

  • Goswami, S., Teo, H.H. and Chan, H.C. (2008). Real Options from RFID Adoption: The role of institutions and managerial mindfulness, in Proceedings of the 29th Annual International Conference on Information Systems (ICIS) (Paris, France, 2008); Atlanta, GA: Association for Information Systems.

  • Hackenbroch, W. and Henneberger, M. (2007). Grid Computing Infrastructures and their Value for Risk Management, in Proceedings of the 40th Annual Hawaii International Conference on System Sciences (HICSS) (Waikoloa, Hawaii, 2007); San Diego, CA: IEEE Computer Society Press.

  • Hair, J., Anderson, R., Tatham, R. and Black, W. (1998). Multivariate Data Analysis with Readings, 4th edn, Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Henseler, J. (2012). PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis, in W.A. Gaul, A. Geyer-Schulz, L. Schmidt-Thieme and J. Kunze (eds.) Challenges at the Interface of Data Analysis, Computer Science, and Optimization, Berlin, Heidelberg: Springer, pp. 495–501.

    Chapter  Google Scholar 

  • Henseler, J., Ringle, C.M. and Sinkovics, R.R. (2009). The Use of Partial Least Squares Path Modeling in International Marketing, in R.R. Sinkovics and P.B. Ghauri (eds.) Advances in International Marketing, Vol. 20, Bingley: Emerald JAI Press, pp. 277–319.

    Chapter  Google Scholar 

  • Hsieh, J.J.P.-A., Rai, A. and Keil, M. (2008). Understanding Digital Inequality: Comparing continued use behavioral models of the socio-economically advantaged and disadvantaged, MIS Quarterly 32 (1): 97–126.

    Google Scholar 

  • Hulland, J. (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A review of four recent studies, Strategic Management Journal 20 (2): 195–204.

    Article  Google Scholar 

  • Iansiti, M. (1998). Technology Integration: Making critical choices in a dynamic world, Boston, MA: Harvard Business Press.

    Google Scholar 

  • IDC (2010). Through 2014 Public IT Cloud Services Will Grow at More Than Five Times the Rate of Traditional IT Products, New IDC Research Finds [WWW document] http://www.idc.com/about/viewpressrelease.jsp?containerId=prUS22393210&sectionId=null&elementId=null&pageType=SYNOPSIS (accessed 18 April 2012).

  • Jap, S.D. (2001). Perspectives on Joint Competitive Advantages in Buyer–Supplier Relationships, International Journal of Research in Marketing 18 (1–2): 19–35.

    Article  Google Scholar 

  • Jaworski, B.J. and Kohli, A.K. (1993). Market Orientation: Antecedents and consequences, Journal of Marketing 57 (7): 53–70.

    Article  Google Scholar 

  • Johns, G. (2006). The Essential Impact of Context on Organizational Behavior, Academy of Management Review 31 (2): 386–408.

    Article  Google Scholar 

  • Jordan, S., Messner, M. and Becker, A. (2009). Reflection and Mindfulness in Organizations: Rationales and possibilities for integration, Management Learning 40 (4): 465–473.

    Article  Google Scholar 

  • Jorion, P. (2006). Value at Risk, 3rd edn, Burr Ridge, IL: Richard D. Irwin.

    Google Scholar 

  • Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for behavioral economics, American Economic Review 93 (5): 1449–1475.

    Article  Google Scholar 

  • Karimi, J., Somers, T.M. and Bhattacherjee, A. (2007a). The Impact of ERP Implementation on Business Process Outcomes: A factor-based study, Journal of Management Information Systems 24 (1): 101–134.

    Article  Google Scholar 

  • Karimi, J., Somers, T.M. and Bhattacherjee, A. (2007b). The Role of Information Systems Resources in ERP Capability Building and Business Process Outcomes, Journal of Management Information Systems 24 (2): 221–260.

    Article  Google Scholar 

  • Keil, M., Tuunainen, V. and Wassenaar, A. (2000). A Cross-Cultural Study on Escalation of Commitment Behaviors in Software Projects, MIS Quarterly 24 (2): 299–325.

    Article  Google Scholar 

  • Knight, A.P. (2004). Measuring Collective Mindfulness and Exploring its Nomological Network, Unpublished Master thesis, University of Maryland, College Park.

  • Kruskal, W.H. and Wallis, W.A. (1952). Use of Ranks in One-Criterion Variance Analysis, Journal of the American Statistical Association 47 (260): 583–621.

    Article  Google Scholar 

  • Langer, E.J. (1989). Minding Matters: The consequences of mindlessness–mindfulness, San Diego, CA: Academic Press.

    Google Scholar 

  • Langer, E.J. and Moldoveanu, M. (2000). The Construct of Mindfulness, Journal of Social Issues 56 (1): 1–9.

    Article  Google Scholar 

  • Lawrence, P.R. and Lorsch, J.W. (1967). Organization and Environment, Irwin, IL: Homewood.

    Google Scholar 

  • Levene, H. (1960). Robust Tests for Equality of Variances, in I. Olkin (ed.) Contributions to Probability and Statistics, Palo Alto, CA: Stanford University Press, pp. 278–292.

    Google Scholar 

  • Liang, H., Nilesh, S., 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 

  • Loch, K.D., Straub, D.W. and Kamel, S. (2003). Diffusing the Internet in the Arab World: The role of social norms and technological culturation, IEEE Transactions on Engineering Management 50 (1): 45–63.

    Article  Google Scholar 

  • MacKenzie, S.B., Podsakoff, P.M. and Jarvis, C.B. (2005). The Problem of Measurement Model Misspecification in Behavioral and Organizational Research and Some Recommended Solutions, Journal of Applied Psychology 90 (4): 710–730.

    Article  Google Scholar 

  • McGill, A.R., Johnson, M.D. and Bantel, K.A. (1993). Cognitive Complexity and Conformity: The effects on performance in a turbulent environment, Academy of Management Proceedings 75 (3): 379–383.

    Article  Google Scholar 

  • Meyer, J. and Rowan, B. (1977). Institutional Organizations: Formal structure as myth and ceremony, American Journal of Sociology 83 (2): 340–363.

    Article  Google Scholar 

  • Miller, L. and Smith, K. (1983). Handling Non-Response Issues, Journal of Extension 21 (9–10): 45–50.

    Google Scholar 

  • Mintzberg, H. (1973). The Nature of Managerial Work, New York: Harper & Row.

    Google Scholar 

  • Moore, G.C. and Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation, Information Systems Research 2 (3): 192–222.

    Article  Google Scholar 

  • Nunnally, J.C. (1978). Psychometric Theory, New York: McGraw-Hill.

    Google Scholar 

  • Overby, E., Bharadwaj, A.S. and Sambamurthy, V. (2006). Enterprise Agility and the Enabling Role of Information Technology, European Journal of Information Systems 15 (2): 120–131.

    Article  Google Scholar 

  • Pavlou, P.A. and El Sawy, O.A. (2006). From IT Leveraging Competence to Competitive Advantage in Turbulent Environments: The case of new product development, Information Systems Research 17 (3): 198–227.

    Article  Google Scholar 

  • Petter, S., Straub, D. and Rai, A. (2007). Specifying Formative Constructs in Information Systems Research, MIS Quarterly 31 (4): 623–656.

    Google Scholar 

  • Podsakoff, P.M., MacKenzie, S.B., Jeong-Yeon, L. and 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): 879–903.

    Article  Google Scholar 

  • Podsakoff, P.M. and Organ, D.W. (1986). Self-reports in Organizational Research: Problems and prospects, Journal of Management 12 (4): 531–544.

    Article  Google Scholar 

  • Powell, W.W. and Colyvas, J.A. (2008). Microfoundations of Institutional Theory, in R. Greenwood, C. Oliver, K. Sahlin and R. Suddaby (eds.) Handbook of Organizational Institutionalism, London: Sage, pp. 276–298.

    Chapter  Google Scholar 

  • Qureshi, I. and Compeau, D. (2009). Assessing Between-Group Differences in Information Systems Research: A comparison of covariance – and component-based SEM, MIS Quarterly 33 (1): 197–214.

    Google Scholar 

  • Ragu-Nathan, B.S., Apigian, C.H., Ragu-Nathan, T.S. and Tu, Q. (2004). A Path Analytic Study of the Effect of Top Management Support for Information Systems Performance, Omega 32 (6): 459–471.

    Article  Google Scholar 

  • Rai, A., Brown, P. and Tang, X. (2009). Organizational Assimilation of Electronic Procurement Innovations, Journal of Management Information Systems 26 (1): 257–296.

    Article  Google Scholar 

  • Ringle, C.M., Wende, S. and Will, A. (2005). SmartPLS 2.0 (beta), [WWW document] http://www.smartpls.de (accessed 28 April 2011).

  • RMA (2010). Data Quality: Is the glass half empty or half full?, [WWW document] http://ebiz.rmahq.org/eBusPPRO/Default.aspx?TabId=55&ProductId=30500 (accessed 28 April 2010).

  • Rogers, E.M. (1995). Diffusion of Innovations, New York: The Free Press.

    Google Scholar 

  • Rosenkopf, L. and Abrahamson, E. (1999). Modeling Reputational and Informational Influences in Threshold Models of Bandwagon Innovation Diffusion, Computational and Mathematical Organization Theory 5 (1): 361–384.

    Article  Google Scholar 

  • Sambamurthy, V., Bharadwaj, A. and Grover, V. (2003). Shaping Agility through Digital Options: Reconceptualizing the role of information technology in contemporary firms, MIS Quarterly 27 (2): 237–263.

    Google Scholar 

  • Sarstedt, M., Henseler, J. and Ringle, C.M. (2011). Multi-Group Analysis in Partial Least Squares (PLS) Path Modeling: Alternative methods and empirical results, Advances in International Marketing 22 (1): 195–218.

    Article  Google Scholar 

  • SEC (2008). Bank of America Corporation Form 10–K, [WWW document] http://www.sec.gov/archives/edgar/data/70858/000119312509041126/D10K.htm (accessed 28 April 2010).

  • Sharma, S., Durand, R. and Gur-Arie, O. (1981). Identification and Analysis of Moderator Variables, Journal of Marketing Research 18 (3): 291–299.

    Article  Google Scholar 

  • Sivo, S.A., Saunders, C., Chang, Q. and Jiang, J.J. (2006). How Low Should You Go? Low Response Rates and the Validity of Inference in IS Questionnaire Research, Journal of the Association for Information Systems 7 (6): 351–414.

    Google Scholar 

  • Sternberg, R.J. (2000). Images of Mindfulness, Journal of Social Issues 56 (1): 11–26.

    Article  Google Scholar 

  • Straub, D. (1989). Validating Instruments in MIS Research, MIS Quarterly 13 (2): 147–169.

    Article  Google Scholar 

  • Straub, D., Boudreau, M.-C. and Gefen, D. (2004). Validation Guidelines for IS Positivist Research, Communications of the Association for Information Systems 13 (24): 380–427.

    Google Scholar 

  • Strong, P. (2005). Enterprise Grid Computing, ACM Queue 3 (6): 50–59.

    Article  Google Scholar 

  • Sugumaran, V., Tanniru, M. and Storey, V.C. (2008). A Knowledge-Based Framework for Extracting Components in Agile Systems Development, Information Technology and Management 9 (1): 37–53.

    Article  Google Scholar 

  • Swanson, E.B. (1994). Information Systems Innovation among Organizations, Management Science 40 (9): 1069–1092.

    Article  Google Scholar 

  • Swanson, E.B. and Ramiller, N.C. (2004). Innovating Mindfully with Information Technology, MIS Quarterly 28 (4): 553–583.

    Google Scholar 

  • Tanriverdi, H. (2005). Information Technology Relatedness, Knowledge Management Capability, and Performance of Multibusiness Firms, MIS Quarterly 29 (2): 311–334.

    Google Scholar 

  • Teece, D.J. (2007). Explicating Dynamic Capabilities: The nature and microfoundations of (sustainable) enterprise performance, Strategic Management Journal 28 (13): 1319–1350.

    Article  Google Scholar 

  • Teece, D.J., Pisano, G. and Shuen, A. (1997). Dynamic Capabilities and Strategic Management, Strategic Management Journal 18 (7): 509–533.

    Article  Google Scholar 

  • Tenbrunsel, A.E., Galvin, T.L., Neale, M.A. and Bazerman, M.H. (1996). Cognitions in Organizations, in S.R. Clegg, C. Hardy and W.R. Nord (eds.) Handbook of Organization Studies, Thousand Oaks, CA: Sage, pp. 313–337.

    Google Scholar 

  • Teo, H.H., Wei, K.K. and Benbasat, I. (2003). Predicting Intention to Adopt Interorganizational Linkages: An institutional perspective, MIS Quarterly 27 (1): 19–49.

    Google Scholar 

  • Thomas, J.B., Clark, S.M. and Gioia, D.A. (1993). Strategic Sensemaking and Organizational Performance: Linkages among scanning, interpretation, action, and outcomes, Academy of Management Journal 36 (1): 239–270.

    Article  Google Scholar 

  • Tornatzky, L.G. and Fleischer, M. (1990). The Processes of Technological Innovation, Massachusetts/Toronto: Lexington Books.

    Google Scholar 

  • Valorinta, M. (2009). Information Technology and Mindfulness in Organizations, Industrial and Corporate Change 18 (5): 963–997.

    Article  Google Scholar 

  • Venkatesh, V. and Morris, M.G. (2000). Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior, MIS Quarterly 24 (1): 115–139.

    Article  Google Scholar 

  • Weick, K.E. and Sutcliffe, K.M. (2001). Managing the Unexpected: Assuring high performance in an age of complexity, San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Weick, K.E. and Sutcliffe, K.M. (2007). Managing the Unexpected: Resilient performance in an age of uncertainty, San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Weick, K.E., Sutcliffe, K.M. and Obstfeld, D. (1999). Organizing for High Reliability: Processes of collective mindfulness, Research in Organizational Behavior 21 (1): 81–123.

    Google Scholar 

  • Weinhardt, C., Anandasivam, A., Blau, B., Borissov, N., Meinl, T., Michalik, W. and Stößer, J. (2009). Cloud Computing: A classification, business models, and research directions, Business and Information Systems Engineering 1 (5): 391–399.

    Article  Google Scholar 

  • Wold, H. (1982). Soft Modeling: The basic design and some extensions, in K.G. Jöreskog and H. Wold (eds.) Systems under Indirect Observation: Causality, structure, prediction, Amsterdam: North-Holland, pp. 1–54.

    Google Scholar 

  • Yi, M.Y. and Davis, F.D. (2003). Developing and Validating an Observational Learning Model of Computer Software Training and Skill Acquisition, Information Systems Research 14 (2): 146–169.

    Article  Google Scholar 

  • Zhu, K., Dong, S., Xu, S.X. and Kraemer, K.L. (2006a). Innovation Diffusion in Global Contexts: Determinants of post-adoption digital transformation of European companies, European Journal of Information Systems 15 (6): 601–616.

    Article  Google Scholar 

  • Zhu, K. and Kraemer, K.L. (2005). Post-Adoption Variations in Usage and Value of E-Business by Organizations: Cross-country evidence from the retail industry, Information Systems Research 16 (1): 61–84.

    Article  Google Scholar 

  • Zhu, K., Kraemer, K.L. and Xu, S. (2006b). The Process of Innovation Assimilation by Firms in Different Countries: A technology diffusion perspective on e-business, Management Science 52 (10): 1557–1576.

    Article  Google Scholar 

  • Zhu, K., Kraemer, K.L., Xu, S. and Dedrick, J. (2004). Information Technology Payoff in E-Business Environments: An international perspective on value creation of e-business in the financial services industry, Journal of Management Information Systems 21 (1): 17–54.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Information Systems, Goethe University Frankfurt, Frankfurt am Main, Germany

    Martin Wolf, Roman Beck & Immanuel Pahlke

Authors
  1. Martin Wolf
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roman Beck
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Immanuel Pahlke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Martin Wolf.

Appendix

Appendix

Tables A1, A2, A3, A4, A5, A6 and A7

Table A1 Measurement items
Full size table
Table A2 Guttman scale for Grid assimilation (ASSM)
Full size table
Table A3 Measurement scales for business processes performance second-order construct
Full size table
Table A4 Measurement scales for organizational mindfulness score
Full size table
Table A5 Tests for equality of variance and normality among bootstrapping estimations
Full size table
Table A6 Tests for non-response bias based on archival and self-reported data
Full size table
Table A7 Tests for non-response bias, based on archival and self-reported data
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wolf, M., Beck, R. & Pahlke, I. Mindfully resisting the bandwagon: reconceptualising IT innovation assimilation in highly turbulent environments. J Inf Technol 27, 213–235 (2012). https://doi.org/10.1057/jit.2012.13

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/jit.2012.13

Keywords

Search

Navigation