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AI-empowered scale development: Testing the potential of ChatGPT

Stefan Hoffmann, Wassili Lasarov, Yogesh Dwivedi Orcid Logo

Technological Forecasting and Social Change, Volume: 205, Start page: 123488

Swansea University Author: Yogesh Dwivedi Orcid Logo

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DOI (Published version): 10.1016/j.techfore.2024.123488

Abstract

AI-tools such as ChatGPT can assist researchers to improve the performance of the research process. This paper examines whether researchers could apply ChatGPT to develop and empirically validate new research scales. The study describes a process how to prompt ChatGPT to assist the scale development...

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Published in: Technological Forecasting and Social Change
ISSN: 0040-1625
Published: Elsevier BV 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa66530
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first_indexed 2024-05-29T17:56:24Z
last_indexed 2024-05-29T17:56:24Z
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spelling v2 66530 2024-05-29 AI-empowered scale development: Testing the potential of ChatGPT d154596e71b99ad1285563c8fdd373d7 0000-0002-5547-9990 Yogesh Dwivedi Yogesh Dwivedi true false 2024-05-29 CBAE AI-tools such as ChatGPT can assist researchers to improve the performance of the research process. This paper examines whether researchers could apply ChatGPT to develop and empirically validate new research scales. The study describes a process how to prompt ChatGPT to assist the scale development of a new construct, using the example of the construct of perceived value of ChatGPT-supported consumer behavior. The paper reports four main empirical studies (US: N = 148; Australia: N = 317; UK: N = 108; Germany: N = 51) that have been employed to validate the newly developed scale. The first study purifies the scale. The following studies confirm the adjusted factorial validity of the reduced scale. Although the empirical data imply a simplification of the initial multi-dimensional scale, the final three-dimensional operationalization is highly reliable and valid. The paper outlines the shortcomings and several critical notes to stimulate more research and discussion in this area. Journal Article Technological Forecasting and Social Change 205 123488 Elsevier BV 0040-1625 Artificial intelligence; ChatGPT; ChatGPT-supported consumer behavior; Scale development; Validation 1 8 2024 2024-08-01 10.1016/j.techfore.2024.123488 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University Another institution paid the OA fee This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. 2024-06-10T11:49:04.2631944 2024-05-29T18:54:27.1095938 Faculty of Humanities and Social Sciences School of Management - Business Management Stefan Hoffmann 1 Wassili Lasarov 2 Yogesh Dwivedi 0000-0002-5547-9990 3 66530__30582__e81f30d61a2649128369ca9134d2e480.pdf 66530.VoR.pdf 2024-06-10T11:27:34.4500309 Output 1403426 application/pdf Version of Record true © 2024 The Author(s). This is an open access article under the CC BY license. true eng http://creativecommons.org/licenses/by/4.0/
title AI-empowered scale development: Testing the potential of ChatGPT
spellingShingle AI-empowered scale development: Testing the potential of ChatGPT
Yogesh Dwivedi
title_short AI-empowered scale development: Testing the potential of ChatGPT
title_full AI-empowered scale development: Testing the potential of ChatGPT
title_fullStr AI-empowered scale development: Testing the potential of ChatGPT
title_full_unstemmed AI-empowered scale development: Testing the potential of ChatGPT
title_sort AI-empowered scale development: Testing the potential of ChatGPT
author_id_str_mv d154596e71b99ad1285563c8fdd373d7
author_id_fullname_str_mv d154596e71b99ad1285563c8fdd373d7_***_Yogesh Dwivedi
author Yogesh Dwivedi
author2 Stefan Hoffmann
Wassili Lasarov
Yogesh Dwivedi
format Journal article
container_title Technological Forecasting and Social Change
container_volume 205
container_start_page 123488
publishDate 2024
institution Swansea University
issn 0040-1625
doi_str_mv 10.1016/j.techfore.2024.123488
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
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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
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description AI-tools such as ChatGPT can assist researchers to improve the performance of the research process. This paper examines whether researchers could apply ChatGPT to develop and empirically validate new research scales. The study describes a process how to prompt ChatGPT to assist the scale development of a new construct, using the example of the construct of perceived value of ChatGPT-supported consumer behavior. The paper reports four main empirical studies (US: N = 148; Australia: N = 317; UK: N = 108; Germany: N = 51) that have been employed to validate the newly developed scale. The first study purifies the scale. The following studies confirm the adjusted factorial validity of the reduced scale. Although the empirical data imply a simplification of the initial multi-dimensional scale, the final three-dimensional operationalization is highly reliable and valid. The paper outlines the shortcomings and several critical notes to stimulate more research and discussion in this area.
published_date 2024-08-01T11:49:03Z
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score 11.012678

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