From generative fit to generative capacity: Exploring an emerging dimension of information systems design and task performance

Michel Avital*, Dov Te'Eni

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Information systems (IS) research has been long concerned with improving task-related performance. The concept of fit is often used to explain how system design can improve performance and overall value. So far, the literature has focused mainly on performance evaluation criteria that are based on measures of task efficiency, accuracy, or productivity. However, nowadays, productivity gain is no longer the single evaluation criterion. In many instances, computer systems are expected to enhance our creativity, reveal opportunities and open new vistas of uncharted frontiers. To address this void, we introduce the concept of generativity in the context of IS design and develop two corresponding design considerations - 'generative capacity' that refers to one's ability to produce something ingenious or at least new in a particular context, and 'generative fit' that refers to the extent to which an IT artefact is conducive to evoking and enhancing that generative capacity. We offer an extended view of the concept of fit and realign the prevailing approaches to human-computer interaction design with current leading-edge applications and users' expectations. Our findings guide systems designers who aim to enhance creative work, unstructured syntheses, serendipitous discoveries, and any other form of computer-aided tasks that involve unexplored outcomes or aim to enhance our ability to go boldly where no one has gone before. In this paper, we explore the underpinnings of 'generative capacity' and argue that it should be included in the evaluation of task-related performance. Then, we briefly explore the role of fit in IS research, position 'generative fit' in that context, explain its role and impact on performance, and provide key design considerations that enhance generative fit. Finally, we demonstrate our thesis with an illustrative vignette of good generative fit, and conclude with ideas for further research.

Original languageEnglish
Pages (from-to)345-367
Number of pages23
JournalInformation Systems Journal
Issue number4
StatePublished - Jul 2009


  • Creativity
  • Generative capacity
  • Generative design
  • Human-computer interaction
  • Requirements engineering
  • Systems design


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