Introduction. The paper deals with the topic of increasing integration of individuals and companies in innovation processes by means of Web-based software platforms. We consider why people participate and contribute in platforms and the characteristics of the platforms and the possible managerial actions (i.e., the drivers for motivations) to enhance these motivations? Method. An empirical qualitative analysis of twenty important platforms, leading to a cause-effect map of drivers and motivations. Both primary data (from a Delphi study and interviews) and secondary data (documents, Website explanations, etc.) were used. Analysis. Qualitative analysis was used to examine the interactions between specific drivers for enhancing specific motivations. Results. Nine groups of drivers, classified into three groups, were found. Strategies for driving the motivations that could encourage users to play an active role in the platforms are proposed. Conclusions. The findings could be useful for community managers and platform designers because they suggest choices for platform design that could attract potentially innovative participants and sustain a high level of collaboration for innovation-related contributions. © the authors, 2012.
What drives collective innovation? exploring the system of drivers for motivations in open innovation, web-based platforms / Battistella, C.; Nonino, Fabio. - In: INFORMATION RESEARCH. - ISSN 1368-1613. - ELETTRONICO. - 17:1(2012), p. paper 513.
What drives collective innovation? exploring the system of drivers for motivations in open innovation, web-based platforms
NONINO, FABIO
2012
Abstract
Introduction. The paper deals with the topic of increasing integration of individuals and companies in innovation processes by means of Web-based software platforms. We consider why people participate and contribute in platforms and the characteristics of the platforms and the possible managerial actions (i.e., the drivers for motivations) to enhance these motivations? Method. An empirical qualitative analysis of twenty important platforms, leading to a cause-effect map of drivers and motivations. Both primary data (from a Delphi study and interviews) and secondary data (documents, Website explanations, etc.) were used. Analysis. Qualitative analysis was used to examine the interactions between specific drivers for enhancing specific motivations. Results. Nine groups of drivers, classified into three groups, were found. Strategies for driving the motivations that could encourage users to play an active role in the platforms are proposed. Conclusions. The findings could be useful for community managers and platform designers because they suggest choices for platform design that could attract potentially innovative participants and sustain a high level of collaboration for innovation-related contributions. © the authors, 2012.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.