Information systems research has been long concerned with improving task-related performance. For that purpose the concept of fit is often used to explain how a system’s design can improve performance and overall value. Examples are the theories of cognitive fit (Vessey/Galletta, 1991) or task/technology fit (Zigurs/Buckland, 1998). These theories argue that fitting a computer system to a user and the task a user tries to perform using the computer system enhances the desired outcome and has a positive effect on overall performance (Vessey/Galletta, 1991; Goodhue/Thompson, 1995; Zigurs/Buckland, 1998). Until now, research has mainly focused on performance evaluation criteria that are based on measures of task efficiency, accuracy, or productivity (Zhang/Li, 2004). As argued by Avital/Te’eni (2009) this view was sufficient in the early days of personal computing when computers were seen mainly as productivity tools. Nowadays, productivity gain is no longer the single most important evaluation criterion. Today user’s expectations of computer systems have dramatically changed. In many instances, computer systems are expected to be intelligent, communicative, and stimulating in order to enhance our creativity, reveal opportunities, and support innovation (Abraham/Boone, 1994; Shneiderman, 2002). Particularly in the area of tool-supported innovation management these stimulating aspects are important rather than pure task-oriented performance.
KeywordsGenerative Capacity Design Directive Content Layer Divergent Thinking Computer Support Cooperative Work
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