Data quality management, data usage experience and acquisition intention of big data analytics

Ohbyung Kwon, Namyeon Lee and Bongsik Shin

International Journal of Information Management, 2014, vol. 34, issue 3, 387-394

Abstract: Big data analytics associated with database searching, mining, and analysis can be seen as an innovative IT capability that can improve firm performance. Even though some leading companies are actively adopting big data analytics to strengthen market competition and to open up new business opportunities, many firms are still in the early stage of the adoption curve due to lack of understanding of and experience with big data. Hence, it is interesting and timely to understand issues relevant to big data adoption. In this study, a research model is proposed to explain the acquisition intention of big data analytics mainly from the theoretical perspectives of data quality management and data usage experience. Our empirical investigation reveals that a firm's intention for big data analytics can be positively affected by its competence in maintaining the quality of corporate data. Moreover, a firm's favorable experience (i.e., benefit perceptions) in utilizing external source data could encourage future acquisition of big data analytics. Surprisingly, a firm's favorable experience (i.e., benefit perceptions) in utilizing internal source data could hamper its adoption intention for big data analytics.

Keywords: Big data analytics; Resource-based view; Data quality management; IT capability; Data usage (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:34:y:2014:i:3:p:387-394

DOI: 10.1016/j.ijinfomgt.2014.02.002

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