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Articles

A techno-social perspective of innovation jams: defining and characterising

Pages 30-46 | Received 04 Mar 2020, Accepted 25 Jan 2021, Published online: 11 Feb 2021
 

ABSTRACT

Understanding technology’s influence on the implementation of new models of innovation is of increasing importance to research scholars. This study aims to understand through a techno-social perspective the underlying characteristics of innovation jams and how they contribute to the implementation of OI. This paper presents innovation jams through a 10-year longitudinal study from 2001 to 2011 and posits innovation jams as an ongoing accomplishment that was constituted and reconstituted through the techno and social systems in their development for innovative activity. The investigation contributes to theory and practice by placing innovation jams into three research streams that connect the role of technology to the implementation of OI. The study differentiates innovation jams from crowdsourcing as an innovation model and offers ten dimension and changing definitions of innovation jams as they evolved. Finally, the study connects the techno-social approach to the practice of OI and suggests both the technical and social systems are reinforcing factors when implementing OI practices supported.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Steve Diasio

Steve Diasio holds a Clinical Associate Professor Entrepreneurship and Innovation in the Muma College of Business at the University of South Florida. As a researcher on innovation, Steve's contributions include extending the open innovation paradigm through his investigation with IBM Innovation Jams. Steve argues that inflows and outflows of knowledge within open innovation are relevant beyond product and service innovation and through the application of emerging technology can support managerial decision-making. Research during his Ph.D. studies at ESADE Business School culminated in framing his Open Model of Decision-Support research agenda.

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