Patterns of Data-Driven Decision-Making: How Decision-Makers Leverage Crowdsourced Data
Type
conference paper
Date Issued
2019-12-15
Author(s)
Abstract
Crowdsourcing represents a powerful approach for organizations to collect data from large networks of people. While research already made great strides to develop the technological foundations for processing crowdsourced data, little is known about decision-making patterns that emerge when decision-makers have access to such large amounts of data on people's behavior, opinions, or ideas. In this study, we analyze the characteristics of decision-making in crowdsourcing based on interviews with decision-makers across 10 multinational corporations. For research, we identify four common patterns of decision-making that range from structured and goal-oriented to highly dynamic and data-driven. In this way, we systematize how decision-makers typically source, process, and use crowdsourced data to inform decisions. We also provide an integrated perspective on how different types of decision problems and modes of acquiring information induce such patterns. For practice, we discuss how information systems should be designed to provide adequate support for these patterns.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Event Title
International Conference on Information Systems (ICIS)
Event Location
Munich, Germany
Event Date
15.12.2018-18.12.2018
Division(s)
Eprints ID
258450
File(s)![Thumbnail Image]()
open.access
Name
RhynBlohm_DDDM_2019.pdf
Size
286.7 KB
Format
Adobe PDF
Checksum (MD5)
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