Cited by 204Technology Adoption and User BehaviourImpact of AI and Big Data on Business and SocietyDigital Transformation in Industry

The DOI matches its Crossref record; 122 of the 126 references it cites were found in a registry or an index, and 2 are not checked yet; none of the 14 sources its claims cite is checked for support yet.

Adoption of AI-empowered industrial robots in auto component manufacturing companies

Open access

Abstract

The usage of AI-empowered Industrial Robots (InRos) is booming in the Auto Component Manufacturing Companies (ACMCs) across the globe. Based on a model leveraging the Technology, Organisation, and Environment (TOE) framework, this work examines the adoption of InRos in ACMCs in the context of an emerging economy. This research scrutinises the adoption intention and potential use of InRos in ACMCs through a survey of 460 senior managers and owners of ACMCs in India. The findings indicate that perceived compatibility, external pressure, perceived benefits and support from vendors are critical predictors of InRos adoption intention. Interestingly, the study also reveals that IT infrastructure and government support do not influence InRos adoption intention. Furthermore, the analysis suggests that perceived cost issues negatively moderate the relationship between the adoption intention and potential use of InRos in ACMCs. This study offers a theoretical contribution as it deploys the traditional TOE framework and discovers counter-intuitively that IT resources are not a major driver of technology adoption: as such, it suggests that a more comprehensive framework than the traditional RBV should be adopted. The work provides managerial recommendations for managers, shedding light on the antecedents of adoption intention and potential use of InRos at ACMCs in a country where the adoption of InRos is in a nascent stage.

Checked 2026-10-10 · 2 references not checked yet

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This paper uses a TOE-based model to examine adoption intention and potential use of AI-empowered industrial robots (InRos) among Indian auto component manufacturing companies (ACMCs). It finds perceived compatibility, perceived benefits, external pressure, and vendor support predict adoption intention, while IT infrastructure and government support do not, and perceived cost issues negatively moderate the intention-to-use relationship.

Key findings

  • In a survey of 460 valid ACMC respondents, perceived compatibility (β=0.195, p<0.05), perceived benefits (β=0.380, p<0.01), external pressure (β=0.244, p<0.01), and support from vendors (β=0.108, p<0.05) significantly predicted InRos adoption intention.
  • IT infrastructure (β=0.284, n.s.) and government support (β=0.273, n.s.) did not significantly influence adoption intention.
  • Adoption intention predicted potential use of InRos (β=0.348, p<0.01), but perceived cost issues negatively moderated that relationship (ADN × COI → PTU, β=-0.105, p<0.01).
  • The model explained 68.9% of variance in adoption intention (R²=.689) and 62.2% of variance in potential use (R²=.622).

Methods

  • Quantitative survey design using the Technology, Organisation, and Environment (TOE) framework, extended with resource-based view considerations, to test eight hypotheses about InRos adoption intention and potential use.
  • Data came from ACMCs in Indian automobile hubs (Maharashtra, Tamil Nadu, Gujarat, Madhya Pradesh, and the National Capital Region); 460 questionnaires were suitable for analysis out of 720, with a 63.8% response rate, and data collection took 14 months.
  • Measures were adapted from prior TOE/innovation-adoption literature, pretested with 30 managers and piloted with 110 respondents; analysis used PLS-SEM with SmartPLS 2.0, plus tests for non-response bias (p=0.36), common method bias (single factor 28.62%), and endogeneity.

Limitations

  • Stated: the empirical setting is India, so implications mainly relate to that emerging economy, and InRos adoption drivers may vary across geographic regions or countries; the model could be enriched with constructs such as anthropomorphism, trust, organisational fit, security, perceived values, and control variables such as firm size and industry type; future work should examine other sectors, service contexts, assimilation/implementation/actual usage, and dynamic capabilities.
  • Evident from the text: the study relies on cross-sectional, self-report survey data from managers/owners in Indian ACMCs already using some advanced technology, which limits causal inference and may restrict generalisability beyond this sample and context.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1080/09537287.2021.1882689

Cites

122 of 126 references verified0 citation errors · 2 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

17 Own result · 13 Not checked yet · 11 Own method · 6 Own interpretation · 2 No basis given

Verify all 14 references — free account

Show all 29 claims

  • Probably not a substantial claim. 13
  • It may state two separate claims as one. 9
20 of 20
  • The paper relies on this without support.

    Different environmental settings and cultural contexts might affect differently the drivers and outcomes of InRos adoption.

    “However, different environmental settings and cultural contexts might affect differently the drivers and outcomes of InRos adoption.”
  • The paper relies on this without support.

    AI-empowered Industrial Robots' adoption is necessary for companies to be competitive in the marketplace.

    “AI-empowered Industrial Robots' adoption is necessary for companies to be competitive in the marketplace.”
  • The paper relies on this without support.

    There are barely a few multinational ACMCs who could afford the use of AI empowered InRos for manufacturing.

    “There are barely a few multinational ACMCs who could afford the use of AI empowered InRos for manufacturing.”
  • The paper relies on this without support.

    The majority of research on advanced industrial manufacturing technologies such as InRos is focused on developed countries in the West rather than emerging economies such as India.

    “the majority of the research related to advanced industrial manufacturing technologies such as InRos is focused on developed countries in the West rather than emerging economies such as India.”
  • The paper relies on this without support.

    Different environmental settings and cultural contexts may generate different results.

    “However, different environmental settings and cultural contexts may generate different results.”
  • The paper relies on this without support.

    Most ACMCs are not aware of government schemes and government taxation has created a slowdown in the automation industry.

    “GSP is not a signficant contributor as most of the ACMCs are not aware of the government schemes and even government taxation has created slowdown in the automation industry.”
  • The paper relies on this without support.

    The increased rate of Goods and Services Tax imposed by the Government of India and the automobile market slowdown is a major challenge for ACMCs.

    “Currently, the increased rate of Goods and Services Tax (GST) imposed by Government of India (GoI) and the automobile market slowdown is a major challenge for ACMCs.”
  • The paper relies on this without support.

    InRos is a new technology in India, and there is not much skilled manpower available in ACMCs.

    “InRos is a new technology in India; hence, there is not much skilled manpower available in the ACMCs.”
  • The paper relies on this without support.

    External pressure is faced by ACMCs due to the globalization of the Indian automobile sector.

    “External pressure is faced by the ACMCs due to the globalization of the Indian automobile sector.”
  • The paper relies on this without support.

    In India, many global customers exist and they expect the usage of advanced technology in manufacturing for accurate and fast production.

    “In India, many global customers exist and they expect the usage of advanced technology in manufacturing for accurate and fast production.”
  • The paper relies on this without support.

    ACMCs face pressure not just from competitors but also from customers' demand for quick delivery of auto components and products.

    “ACMCs face pressure not just from the competitors but also from customers' demand for quick delivery of the auto components and products.”
  • The paper relies on this without support.

    InRos vendors are strongly marketing InRos to ACMCs.

    “In this technology-driven manufacturing environment, InRos vendors are strongly marketing InRos to ACMCs.”
  • The paper relies on this without support.

    Managers feel that training and continuous support from InRos vendors are required for better adoption of InRos.

    “Managers feel that training and continuous support from InRos vendors are required for better adoption of InRos.”
  • The paper relies on this without support.

    InRos boost productivity by automation of various activities in the manufacturing process.

    “InRos boost the productivity by automation of various activities in the manufacturing process.”
  • The paper relies on this without support.

    InRos improves return on investment.

    “It also improves the return on investment.”
  • The paper relies on this without support.

    InRos is an innovative and complex technology, and ACMCs require assistance from vendors.

    “InRos is an innovative and complex technology and ACMCs require assistance from vendors.”
16 of 16

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Citations

Cites

Show all 116 references

Research works printed but not linked: 12

  1. 10.1108/bl12-2016-0044 · DOI
  2. Baker J., 2011, Information Systems Theory: Explaining and Predicting Our Digital Society
  3. 10.1016/j.ijpe.2020 · DOI
  4. Depietro R., 1990, The Processes of Technological Innovation, 199, 151
  5. 10.17705/100407 · DOI
  6. 10.1162/rest · DOI
  7. Ivanov Stanislav, 2018, Revista Turismo & Desenvolvimento, 1, 1501
  8. Keen P. G. W., 1991, Shaping the Future
  9. 10.1016/j.techfore.2019.119752 · DOI
  10. Nunnally J. C., 1978, Psychometric Theory
  11. Penrose E. T., 1958, The Theory of the Growth of the Firm
  12. 10.1108/jbim-06-2016-0122 · DOI

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Metadata

Authors
Pillai, R., Sivathanu, B., Mariani, M., Rana, N. P., Yang, B., & Dwivedi, Y. K.
Affiliations
  • Department of Management, Pune Institute of Business Management, Pune, India
  • Sri Balaji University, Pune (IN)
  • University of Reading (GB)
  • University of Bradford (GB)
  • Chongqing Technology and Business University (CN)
  • Swansea University (GB)
Corresponding author
Rana, Nripendra P.
Venue
Production Planning & Control
Published
2021-02-18
Volume
33
Issue
16
Pages
1517-1533
ISSN
  • 0953-7287 (ISSN-L)
  • 1366-5871
OpenAlex
W3093090100
Cited by
195
References
116
Citations by year
2026: 29 · 2025: 52 · 2024: 46 · 2023: 33 · 2022: 18 · 2021: 15
FWCI
23.92
Type
journal article
Language
en
Open access
Locations
  • Production Planning & Control (publishedVersion)
  • CentAUR (University of Reading) (submittedVersion)
  • Bradford Scholars (University of Bradford) (submittedVersion)
  • Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion, other-oa)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
Keywords
technology adoption, adoption intention, technology-organization-environment framework, perceived compatibility, external pressure, perceived benefits, vendor support, perceived cost, IT infrastructure, government support, emerging economy, India

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