Dimensions of indian consumers’ beliefs about AI: an orthogonal linear transformation approach

Authors

DOI:

https://doi.org/10.20397/2177-6652/2023.v23i1.2534

Keywords:

AI applications, Customer-Machine interaction, Indian Consumer Market, Customer Satisfaction

Abstract

Artificial intelligence is revolutionizing business practices across different domains. It is very important and essential for businesses to understand the consumers’ beliefs about this expensive complex AI technology before they invest their resources in AI applications. This research aims to capture the various dimensions of consumers beliefs about AI technology with respect to the Indian consumer market. By conducting a pan India survey of  1028 Indian consumers, their thoughts on the various dimensions of AI were measured on a Likert scale. These fifty statements measuring the various AI dimensions were loadedonto nine factors comprising of fortyfour statements using the Principal Component Factor analysis which was then followed by the Varimax rotation. These nine factors comprising of statements with Eigen values greater than 1 were then renamed to form meaningful AI beliefs namely: Trust in AI, Knowledge about AI, Personalization Preference, Current usage of AI, Awareness of AI, Positive outlook on Current AI Performance, Future Dangers of AI, Negative outlook on Current AI Performance and Desired Applications of AI. The extracted factors which were derived based on ground research could serve as an instrument to measure the various AI beliefs of consumers, mainly for businesses attempting to understand their target consumer market. This reliable instrument with high Cronbach score could help to understand the consumers preferences prior to AI  investments.

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Published

2023-03-01

How to Cite

Isidore, R., & Arun, C. J. (2023). Dimensions of indian consumers’ beliefs about AI: an orthogonal linear transformation approach. Journal of Management & Technology, 23(1), 10–28. https://doi.org/10.20397/2177-6652/2023.v23i1.2534

Issue

Vol. 23 No. 1 (2023)

Section

ARTIGO

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