The adoption intention of industrial robots in Indian ACMCs: an empirical study

Poornima Sehrawat and Hemantkumar P. Bulsara

International Journal of Process Management and Benchmarking, 2024, vol. 18, issue 1, 107-125

Abstract: This research assesses the adoption intention of InRb in ACMCs with the employee's perspective using technology, organisation and environment (TOE) framework. This paper examines the adoption intention as well as potential use of InRb in auto component manufacturing organisations by conducting surveys of 403 employees and managers of Indian ACMCs. The finding shows that perceived usefulness, perceived intelligence, commitment to learn, perceived trust, perceived ease of use, and personal innovativeness are the special predictors of InRb adoption intention. This paper shows the negative effect of perceived ease of use on perceived usefulness. Furthermore, the study explains the positive effect of stickiness as a moderating factor on the adoption intention of InRb and its potential use. This work also provides managerial contribution by highlighting the reasons for the adoption intention of InRb and its potential use in Indian ACMC where the advanced technology adoption is at a very emerging stage.

Keywords: Industry 4.0; automated industrial robots; adoption intention; AND; actual adoption; auto component manufacturing organisations; ACMCs. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=140644 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpmbe:v:18:y:2024:i:1:p:107-125

Access Statistics for this article

More articles in International Journal of Process Management and Benchmarking from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().