Acceptance of text-mining systems: The signaling role of information quality

Nathalie Demoulin and Kristof Coussement ()
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Kristof Coussement: IESEG - School of Management (LEM), LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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Abstract: The popularity of the big data domain has boosted corporate interest in collecting and storing tremendous amounts of consumers' textual information. However, decision makers are often overwhelmed by the abundance of information, and the usage of text mining (TM) tools is still at its infancy. This study validates an extended technology acceptance model integrating information quality (IQ) and top management support. Results confirm that IQ influences behavioral intentions and TM tools usage, through perceptions of external control, perceived ease of use, and perceived usefulness; top management support also has a key role in determining the usage of TM tools.

Keywords: Technology acceptance model (TAM); Text mining; Big data; Information quality; Top management support (search for similar items in EconPapers)
Date: 2018-10-29
Note: View the original document on HAL open archive server: https://hal.science/hal-02111772
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Citations: View citations in EconPapers (3)

Published in Information and Management, 2018, ⟨10.1016/j.im.2018.10.006⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02111772

DOI: 10.1016/j.im.2018.10.006

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