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Sourcing data for data-driven applications: foundational questions

In: Research Handbook on Artificial Intelligence and Decision Making in Organizations

Author

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  • Sirkka L. Jarvenpaa

Abstract

Decisions on data have irrevocable influence on AI applications. These decisions include making data sourcing decision, data sourcing arrangements, and interactions and experiences to determine data’s fit. Organizations often source data internally, but they also increasingly source data from a wide variety of external sources. This chapter revisits the foundational IS sourcing decisions in the context of data sourcing. Whereas research on IS sourcing decisions has revealed the mechanisms of control and trust and their significance, data sourcing decisions require an understanding of organizational learning experience. Data sourcing demands that organizational learning is a consideration at the outset-it is not just an outcome, or a parallel process to augment machine intelligence. Through three concrete examples, the chapter illustrates data sourcing challenges from the perspective of organizational learning. The chapter concludes with calls for future research on data sourcing from the organizational learning perspective.

Suggested Citation

  • Sirkka L. Jarvenpaa, 2024. "Sourcing data for data-driven applications: foundational questions," Chapters, in: Ioanna Constantiou & Mayur P. Joshi & Marta Stelmaszak (ed.), Research Handbook on Artificial Intelligence and Decision Making in Organizations, chapter 1, pages 17-37, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:21708_1
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    File URL: https://www.elgaronline.com/doi/10.4337/9781803926216.00009
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