Innovating in Circles

A Qualitative Analysis on Cycles of IT Feature Recombinations for Performative and Creative Outcomes




IT post-adoption, IT innovation, IT features, recombination, learning cycles


Innovations do not emerge in isolation but are at least to some extent recombinations of previously existing building blocks. In this paper, we will build on the recombination processes feature set broadening and deepening to show how individuals innovate with IT. In our understanding, the out-comes of innovative use can be performative (improving existing task performance) or creative (leading to new deliverables). We build on a longitudinal case of stresstracking initially designed to improve meditation, but ultimately increasing work productivity by using the meditation tool in an innovative way. Using a theoretically grounded analysis framework, we were able to derive eight propositions on the attainment of performative and creative outcome of innovative IT use. We postulate that innovation only occurs through repeating cycles of recombination processes. Particularly, we propose that it is instrumental to run through a phase that does not benefit any task-related outcomes to trigger true creative outcomes.


Download data is not yet available.


L. Argote, E. Miron-Spektor, “Organizational Learning: From Experience to Knowledge.” Org Sci, vol.22, no.5, pp. 1123–1137, 2011,

C. M. Flath, S. Friesike, M. Wirth, F. Thiesse, “Copy, transform, combine: Exploring the remix as a form of innovation.” JIT, vol.32, no.4, pp. 306–325, 2017,

L. Fleming, S. Mingo, D. Chen, “Collaborative Brokerage, Generative Creativity, and Creative Success.” Admin Sci Quart, vol.52, no.3, pp. 443–475, 2007,

M. Gruber, D. Harhoff, K. Hoisl, “Knowledge Recombination Across Technological Boundaries: Scientists vs. Engineers.” Mgmt Sci, vol.59, no.4, pp. 837–851, 2013,

A. Majchrzak, L. P. Cooper, O. E. Neece, “Knowledge Reuse for Innovation.” Mgmt Sci, vol.50, no.2, pp. 174–188, 2004,

S. Nambisan, R. Agarwal, M. Tanniru, “Organizational mechanisms for enhancing us-er innovation in information technology.” MISQ, vol.23, no.3, pp. 365–395, 1999,

J. Carlo, K. Lyytinen, G. Rose, “A Knowledge-Based Model of Radical Innovation in Small Software Firms.” MISQ, vol.36, no.3, pp. 865–895, 2012.

A. Benlian “IT feature use over time and its impact on individual task performance.” JAIS, vol.16, no.3, pp. 144–173, 2015, 10.17705/1jais.00391

M. K. Ahuja, and J. B. Thatcher, “Moving beyond intentions and toward the theory of trying: Effects of work environment and gender on post-adoption information technol-ogy use.” MISQ, vol.29, no.3, pp. 427–459, 2005.

J. Jasperson, P. E. Carter, R. Zmud, “A Comprehensive Conceptualization of Post-Adoptive Behaviors Associated with Information Technology Enabled Work Systems.” MISQ, vol.29, no.3, pp. 525–557, 2005,

R. Agarwal, “Individual acceptance of information technologies.” In Framing the do-mains of IT management research: Glimpsing the future through the past (Zmud, R. W. Ed.), pp. 85–104, Cincinnati, Ohio: Pinnaflex, 2000.

S. Nambisan, “Information Technology and Product/Service Innovation: A Brief As-sessment and Some Suggestions for Future Research.” JAIS, vol.14, no.4, 2013,

Y. Rahrovani, A. Pinsonneault, “User’s Perceived IS Slack Resources and their Ef-fects on Innovating with IT.” ICIS 2014, Auckland, New Zealand, 2014,

A. Ortiz de Guinea, J. Webster, “An investigation of information systems use patterns: Technological events as triggers, the effect of time, and consequences for perfor-mance.” MISQ, vol.37, no.4, pp. 1165–1188, 2013,

F. F. Bagayogo, L. Lapointe, G. Bassellier, “Enhanced use of IT: A new perspective on post-adoption.” JAIS, vol.15, no.7, pp. 361–387, 2014, 10.17705/1jais.00367

J. P. A. Hsieh, A. Rai, S. X. Xu, “Extracting business value from IT: A sensemaking perspective of post-adoptive use.” Mgmt Sci, vol.57, no.11, pp. 2018–2039, 2011,

J. P. A. Hsieh, R. Zmud, “Understanding Post-Adoptive Usage Behaviors: A Two-Dimensional View.” Comp Info Sys Fac Publ, 2006,

H. Sun “Understanding user revisions when using information system features: Adap-tive system use and triggers.” MISQ, vol.36, no.2, pp. 453–478, 2012,

A. Burton-Jones, A., D. W. Straub, “Reconceptualizing system usage: An approach and empirical test.” ISR, vol.17, no.3, pp. 228–246, 2006,

X. Li, J. P. A. Hsieh, A. Rai, “Motivational Differences Across Post-Acceptance In-formation System Usage Behaviors: An Investigation in the Business Intelligence Systems Context.” ISR, vol.24, no.3, pp. 659–682, 2013,

D. J. Beal, R. R. Cohen, M. J. Burke, C. L. McLendon, “Cohesion and performance in groups: A meta-analytic clarification of construct relations.” J Appl Psy, vol.88, no.6, pp. 989–1004, 2003,

A. Burton-Jones, A., C. Grange, “From Use to Effective Use: A Representation Theo-ry Perspective.” ISR, vol.24, no.3, pp. 632–658, 2013,

K. S. Lassila, J. C. Brancheau, “Adoption and utilization of commercial software packages: Exploring utilization equilibria, transitions, triggers, and tracks.” JMIS, vol.16, no.2, pp. 63–90, 1999,

S. Sundaram, A. Schwarz, E. Jones, W. Chin, “Technology use on the front line: How information technology enhances individual performance.” J Acad Mark Sci, vol.35, no.1, pp. 101–112, 2007.

L. P. Robert, T. A. Sykes, “Extending the Concept of Control Beliefs: Integrating the Role of Advice Networks.” ISR, vol.28, no.1, pp. 84–96, 2017,

C. K. W. de Dreu, M. A. West, “Minority dissent and team innovation: The importance of participation in decision making.” J Appl Psy, vol.86, no.6, pp. 1191–1201, 2001,

T. L. Griffith, “Technology Features as Triggers for Sensemaking.” Acad Mgmt Rev, vol.24, no.3, pp. p. 472, 1999,

G. DeSanctis, M. S. Poole, “Capturing the complexity in advanced technology use: Adaptive structuration theory.” Org Sci, vol.5, no.2, pp. 121–147, 1994,

A. Ortiz de Guinea, M. L. Markus, “Why break the habit of a lifetime? Rethinking the roles of intention, habit, and emotion in continuing information technology use.” MISQ, vol.33, no.3, pp. 433–444, 2009,

M. Limayem, M., S. G. Hirt, C. M. K. Cheung, “How habit limits the predictive power of intention.” MISQ, vol.31, no.4, pp. 705–737, 2007,

H. Barki, G. Paré, C. Sicotte, “Linking IT implementation and acceptance via the con-struct of psychological ownership of information technology.” JIT, vol.23, no.4, pp. 269–280, 2008,

K. A. Saeed, S. Abdinnour, “Understanding post-adoption IS usage stages: An empir-ical assessment of self-service IS.” ISJ, vol.23, no.3, pp. 219-244, 2013,

I. Benbasat, D. K. Goldstein, M. Mead, “The Case Research Strategy in Studies of In-formation Systems.” MISQ, vol.11, no.3, pp. p. 369, 1987,

L. Dubé, G. Paré, “Rigor in Information Systems Positivist Case Research: Current Practices, Trends, and Recommendations.” MISQ, vol.27, no.4, p. 597, 2003.

R. K. Yin, Case study research. 4th ed. Thousand Oaks, CA: Sage, 2009.

M. B. Miles, A. M. Huberman, j. Saldana, Qualitative Data Analysis. 3rd ed. Thousand Oaks, CA: Sage, 2015.

T. W. Ferratt, J. Prasad, E. Dunne, “Fast and Slow Processes Underlying Theories of Information Technology Use.” JAIS, vol.19, no.1, 2018.

P. G. Audia, J. A. Goncalo, “Past Success and Creativity over Time: A Study of Inventors in the Hard Disk Drive Industry.” Mgmt Sci, 53, no.1, pp. 1–15, 2007,

G. Hirst, D. van Knippenberg, J. Zhou, “A Cross-Level Perspective on Employee Cre-ativity: Goal Orientation, Team Learning Behavior, and Individual Creativity.” AMJ, vol.52, no.2, pp. 280–293, 2009,

R. Katila, R., G. Ahuja, “Something old, something new: a longitudinal study of search behavior and new product introduction.” AMJ, vol.45, no.6, pp. 1183–1194, 2002.,



How to Cite

Ebner, K., Bassellier, G., & Smolnik, S. (2021). Innovating in Circles: A Qualitative Analysis on Cycles of IT Feature Recombinations for Performative and Creative Outcomes. Business Information Systems, 1, 293–305.

Conference Proceedings Volume