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The role of the social and technical factors in creating business value from big data analytics: A meta-analysis

Thuy Duong Oesterreich, Eduard Anton, Frank Teuteberg, Yogesh Dwivedi Orcid Logo

Journal of Business Research, Volume: 153, Pages: 128 - 149

Swansea University Author: Yogesh Dwivedi Orcid Logo

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DOI (Published version): 10.1016/j.jbusres.2022.08.028

Abstract

Big data analytics (BDA) has recently gained importance as an emerging technology for handling big data. The use of advanced techniques with differing levels of intelligence, such as descriptive, predictive, prescriptive, and autonomous analytics, is expected to create value for firms. By viewing BD...

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Published in: Journal of Business Research
ISSN: 0148-2963
Published: Elsevier BV 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa60854
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first_indexed 2022-08-18T19:51:48Z
last_indexed 2023-01-13T19:21:17Z
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spelling 2022-09-23T16:39:58.5260233 v2 60854 2022-08-18 The role of the social and technical factors in creating business value from big data analytics: A meta-analysis d154596e71b99ad1285563c8fdd373d7 0000-0002-5547-9990 Yogesh Dwivedi Yogesh Dwivedi true false 2022-08-18 BBU Big data analytics (BDA) has recently gained importance as an emerging technology for handling big data. The use of advanced techniques with differing levels of intelligence, such as descriptive, predictive, prescriptive, and autonomous analytics, is expected to create value for firms. By viewing BDA as a sociotechnical system, we conduct a meta-analysis of 107 individual studies to integrate prior evidence on the role of the technical and social factors of BDA in creating BDA business value. The findings underline the predominant role of the social components in enhancing firm performance, such as the BDA system’s human factors and a nurturing organizational structure, in contrast to the minor role of the technological factors. However, both the technical and social factors are found to be strong determinants of BDA business value. Through the combined lens of sociotechnical theory and the IS business value framework, we contribute to research and practice by enhancing the understanding of the main technical and social determinants of BDA business value at the firm level. Journal Article Journal of Business Research 153 128 149 Elsevier BV 0148-2963 Big data analytics; IT business value; Firm performance; Meta-analysis; Moderator analysis; Sociotechnical theory 1 12 2022 2022-12-01 10.1016/j.jbusres.2022.08.028 COLLEGE NANME Business COLLEGE CODE BBU Swansea University SU Library paid the OA fee (TA Institutional Deal) 2022-09-23T16:39:58.5260233 2022-08-18T20:48:53.9549940 Faculty of Humanities and Social Sciences School of Management - Business Management Thuy Duong Oesterreich 1 Eduard Anton 2 Frank Teuteberg 3 Yogesh Dwivedi 0000-0002-5547-9990 4 60854__25097__32b0fba7f0b949358a8584bf5508d726.pdf 60854_VoR.pdf 2022-09-08T17:07:43.0245286 Output 1573367 application/pdf Version of Record true © 2022 The Authors. This is an open access article under the CC BY-NC-ND license true eng http://creativecommons.org/licenses/by-nc-nd/4.0/
title The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
spellingShingle The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
Yogesh Dwivedi
title_short The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
title_full The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
title_fullStr The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
title_full_unstemmed The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
title_sort The role of the social and technical factors in creating business value from big data analytics: A meta-analysis
author_id_str_mv d154596e71b99ad1285563c8fdd373d7
author_id_fullname_str_mv d154596e71b99ad1285563c8fdd373d7_***_Yogesh Dwivedi
author Yogesh Dwivedi
author2 Thuy Duong Oesterreich
Eduard Anton
Frank Teuteberg
Yogesh Dwivedi
format Journal article
container_title Journal of Business Research
container_volume 153
container_start_page 128
publishDate 2022
institution Swansea University
issn 0148-2963
doi_str_mv 10.1016/j.jbusres.2022.08.028
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
description Big data analytics (BDA) has recently gained importance as an emerging technology for handling big data. The use of advanced techniques with differing levels of intelligence, such as descriptive, predictive, prescriptive, and autonomous analytics, is expected to create value for firms. By viewing BDA as a sociotechnical system, we conduct a meta-analysis of 107 individual studies to integrate prior evidence on the role of the technical and social factors of BDA in creating BDA business value. The findings underline the predominant role of the social components in enhancing firm performance, such as the BDA system’s human factors and a nurturing organizational structure, in contrast to the minor role of the technological factors. However, both the technical and social factors are found to be strong determinants of BDA business value. Through the combined lens of sociotechnical theory and the IS business value framework, we contribute to research and practice by enhancing the understanding of the main technical and social determinants of BDA business value at the firm level.
published_date 2022-12-01T04:19:19Z
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score 11.013082

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