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Information Systems Frontiers
Erschienen in: Information Systems Frontiers 6/2019

07.03.2018

Individual Decision-Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability and Perceived Task-Technology Fit Perspective

verfasst von: Michael A. Erskine, Dawn G. Gregg, Jahangir Karimi, Judy E. Scott

Erschienen in: Information Systems Frontiers | Ausgabe 6/2019

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Abstract

Increasingly, spatial decision support systems (SDSS) help consumers, businesses and governmental entities make decisions involving geospatial data. Understanding if, and how, user- and task-characteristics impact decision-performance will allow developers of SDSS to maximize decision-making performance. Furthermore, scholars can benefit from a more comprehensive understanding of what specific characteristics influence decision-making when using an SDSS. This paper provides a synthesis of relevant research and presents a two-factor experiment (n = 200) designed to measure the impact of user- and task-characteristics on decision-performance. Using Cognitive Fit Theory (CFT) as the theoretical framework, we investigate the effect of geospatial reasoning ability (GRA), input complexity, task complexity, and user perceptions of task-technology fit (PTTF), on geospatial decision-making performance. Specifically, we measure GRA as a user-characteristic, while input- and problem-complexity are measured as task-characteristics. A partial least squares (PLS) analysis reveals the statistical significance of user- and task-characteristics on geospatial decision-making performance. Theoretical and managerial implications are discussed in detail.
Vorheriger Artikel Assimilation of Big Data Innovation: Investigating the Roles of IT, Social Media, and Relational Capital
Nächster Artikel Do we Fully Understand Information Systems Failure? An Exploratory Study of the Cognitive Schema of IS Professionals

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Metadaten
Titel
Individual Decision-Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability and Perceived Task-Technology Fit Perspective
verfasst von
Michael A. Erskine
Dawn G. Gregg
Jahangir Karimi
Judy E. Scott
Publikationsdatum
07.03.2018
Verlag
Springer US
Erschienen in
Information Systems Frontiers / Ausgabe 6/2019
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-018-9840-0

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