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Understanding the Determinants of Big Data Analytics Adoption

Understanding the Determinants of Big Data Analytics Adoption

Surabhi Verma, Sushil Chaurasia
ISBN13: 9781668436622|ISBN10: 1668436620|EISBN13: 9781668436639
DOI: 10.4018/978-1-6684-3662-2.ch075
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MLA

Verma, Surabhi, and Sushil Chaurasia. "Understanding the Determinants of Big Data Analytics Adoption." Research Anthology on Big Data Analytics, Architectures, and Applications, edited by Information Resources Management Association, IGI Global, 2022, pp. 1549-1577. https://doi.org/10.4018/978-1-6684-3662-2.ch075

APA

Verma, S. & Chaurasia, S. (2022). Understanding the Determinants of Big Data Analytics Adoption. In I. Management Association (Ed.), Research Anthology on Big Data Analytics, Architectures, and Applications (pp. 1549-1577). IGI Global. https://doi.org/10.4018/978-1-6684-3662-2.ch075

Chicago

Verma, Surabhi, and Sushil Chaurasia. "Understanding the Determinants of Big Data Analytics Adoption." In Research Anthology on Big Data Analytics, Architectures, and Applications, edited by Information Resources Management Association, 1549-1577. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-6684-3662-2.ch075

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Abstract

This article aims to empirically investigate the factors that affects the adoption of big data analytics by firms (adopters and non-adopters). The current study is based on three feature that influence BDA adoption: technological context (relative advantage, complexity, compatibility), organizational context (top management support, technology readiness, organizational data environment), and environmental context (competitive pressure, and trading partner pressure). A structured questionnaire-based survey method was used to collect data from 231 firm managers. Relevant hypotheses were derived and tested by partial least squares. The results indicated that technology, organization and environment contexts impact firms' adoption of big data analytics. The findings also revealed that relative advantage, complexity, compatibility, top management support, technology readiness, organizational data environment and competitive pressure have a significant influence on the adopters of big data analytics, whereas relative advantage, complexity and competitive pressure have a significant influence on the non-adopters of big data analytics.

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