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

References

• Abdallah, Ali, Yogesh K. Dwivedi, and Nripendra P. Rana. 2017. “International Journal of Information Management Factors Influencing Adoption of Mobile Banking by Jordanian Bank Customers: Extending UTAUT2 with Trust.” International Journal of Information Management 37 (3): 99–110. doi:10.1016/j.ijinfomgt.2017.01.002.
   Google Scholar
• Aboelmaged, Mohamed Gamal. 2014. “Predicting E-Readiness at Firm-Level: An Analysis of Technological, Organizational and Environmental (TOE) Effects on e-Maintenance Readiness in Manufacturing Firms.” International Journal of Information Management 34 (5): 639–651. doi:10.1016/j.ijinfomgt.2014.05.002.
   Web of Science ®Google Scholar
• ACMA. 2019. “Indian Auto Component Industry Performance Review-FY 18.” ACMC. https://www.acma.in/uploads/doc/ACMA-Presentation_press-conference_2019.pdf.
   Google Scholar
• Akter, Shahriar, Samuel Fosso Wamba, and Saifullah Dewan. 2017. “Why PLS-SEM Is Suitable for Complex Modelling? An Empirical Illustration in Big Data Analytics Quality.” Production Planning and Control 28 (11–12): 1011–1021. doi:10.1080/09537287.2016.1267411.
   Google Scholar
• Alaiad, Ahmad, and Lina Zhou. 2014. “The Determinants of Home Healthcare Robots Adoption: An Empirical Investigation.” International Journal of Medical Informatics 83 (11): 825–840. doi:10.1016/j.ijmedinf.2014.07.003.
   PubMed Web of Science ®Google Scholar
• Al-Qirim, Nabeel. 2006. “The Role of the Government and E-Commerce Adoption in Small Businesses in New Zealand.” International Journal of Internet and Enterprise Management 4 (4): 293. doi:10.1504/IJIEM.2006.011042.
   Google Scholar
• Al-Qirim, Nabeel. 2007. “The Adoption of ECommerce Communications and Applications Technologies in Small Businesses in New Zealand.” Electronic Commerce Research and Applications 6 (4): 462–473. doi:10.1016/j.elerap.2007.02.012.
   Web of Science ®Google Scholar
• Alshamaila, Yazn, Savvas Papagiannidis, and Feng Li. 2013. “Cloud Computing Adoption by SMEs in the North East of England: A Multi-Perspective Framework.” Journal of Enterprise Information Management 26 (3): 250–275. doi:10.1108/17410391311325225.
   Google Scholar
• Armbruster, Heidi, Steffen Kinkel, Gunter Lay, and Maloca Spomenka. 2005. “Techno-Organisational Innovation in the European Manufacturing Industry.” European Manufacturing Survey. https://ref.sabanciuniv.edu/sites/ref.sabanciuniv.edu/files/emis_bulletin_1.pdf.
   Google Scholar
• Armstrong, J. Scott, and Terry Overton. 1977. “Estimating Nonresponse Bias in Mail Surveys Estimating Nonresponse Bias in Mail Surveys.” Journal of Marketing Research 14 (3): 396–402. doi:10.1177/002224377701400320.
   Web of Science ®Google Scholar
• Awa, Hart O., and Ojiabo Ukoha Ojiabo. 2016. “A Model of Adoption Determinants of ERP within T-O-E Framework.” Information Technology & People 29 (4): 901–930. doi:10.1108/ITP-03-2015-0068.
   Web of Science ®Google Scholar
• Awa, Hart O., Ojiabo Ukoha Ojiabo, and Longlife E. Orokor. 2017. “Integrated Technology-Organization-Environment (T-O-E) Taxonomies for Technology Adoption.” Journal of Enterprise Information Management 30 (6): 893–921. doi:10.1108/JEIM-03-2016-0079.
   Web of Science ®Google Scholar
• Awa, Hart O., Ojiabo Ukoha, Bartholomew C. Emecheta, and Shaofeng Liu. 2016. “Using T-O-E Theoretical Framework to Study the Adoption of ERP Solution.” Cogent Business & Management 3 (1): 1196571–1196523. Cogent: doi:10.1080/23311975.2016.1196571.
   Web of Science ®Google Scholar
• Awa, Hart O., Ojiabo Ukoha, and Sunny R. Igwe. 2017. “Revisiting Technology-Organization-Environment (T-O-E) Theory for Enriched Applicability.” The Bottom Line 30 (01): 2–22. doi:10.1108/BL12-2016-0044.
   Google Scholar
• Baker, J. 2011. “The Technology-Organization-Environment Framework.” In Information Systems Theory: Explaining and Predicting Our Digital Society, edited by Y. Dwivedi, M. Wade, & S. Schneberger. New York: Springer.
   Google Scholar
• Barney, Jay. 1991. “Firm Resources and Sustained Competitive Advantage.” Journal of Management 17 (1): 99–120. doi:10.1177/014920639101700108.
   Web of Science ®Google Scholar
• Barney, Jay. 2001. “Resource-Based Theories of Competitive Advantage: A Ten-Year Retrospective on the Resource-Based View.” Journal of Management 27 (6): 643–650. doi:10.1177/014920630102700602.
   Web of Science ®Google Scholar
• Belanche, Daniel, Luis V. Casaló, and Carlos Flavián. 2019. “Artificial Intelligence in FinTech: Understanding Robo-Advisors Adoption among Customers.” Industrial Management & Data Systems 119 (7): 1411–1430. doi:10.1108/IMDS-08-2018-0368.
   Web of Science ®Google Scholar
• Bharadwaj, Anandhi. 2000. “A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation.” MIS Quarterly 24 (1): 169–196. doi:10.2307/3250983.
   Web of Science ®Google Scholar
• Bibby, Lee, and Benjamin Dehe. 2018. “Defining and Assessing Industry 4.0 Maturity Levels–Case of the Defence Sector.” Production Planning & Control 29 (12): 1030–1043. doi:10.1080/09537287.2018.1503355.
   Web of Science ®Google Scholar
• Borghi, Matteo, and, Marcello M. Mariani. 2020. “Service Robots in Online Reviews: Online Robotic Discourse.” Annals of Tourism Research : 103036 doi:10.1016/j.annals.2020.103036.
   Web of Science ®Google Scholar
• Dhritiman, Biswas. 2018. “The Policy Hack: What’s Stopping i (Ndustrial)Robots.” The Economic Times. https://economictimes.indiatimes.com/small-biz/startups/newsbuzz/the-policy-hack-whats-stopping-industrialrobots/articleshow/65729206.cms.
   Google Scholar
• Brady, M., L. A. Gerhardt, and H. F. Davidson, editors. 2012. Robotics and Artificial Intelligence. Vol. 11. Italy: NATO ASI Series, Springer Science & Business Media.
   Google Scholar
• Bröhl, Christina, Nelles Jochen, Brandl Christopher, and Mertens Alexander 2016. “TAM Reloaded: A Technology Acceptance Model for Human-Robot Cooperation in Production Systems.” In International Conference on Human-Computer Interaction, 97–103. Berlin: Springer Berlin Heidelberg. doi:10.1007/978-3-319-40548-3.
   Google Scholar
• Cao, D., H. Tao, Y. Wang, A. Tarhini, and S. Xia. 2019. “Acceptance of Automation Manufacturing Technology in China: An Examination of Perceived Norm and Organizational Efficacy.” Production Planning and Control 31 (8): 1–13. doi:10.1080/09537287.2019.1669091.
   Web of Science ®Google Scholar
• Chan, Felix T. S., and Alain Y. L. Chong. 2012. “A SEM-Neural Network Approach for Understanding Determinants of Interorganizational System Standard Adoption and Performances.” Decision Support Systems 54 (1): 621–630. doi:10.1016/j.dss.2012.08.009.
   Web of Science ®Google Scholar
• Chau, Patrick and Kar Yan Tam. 1997. “Factors Affecting the Adoption of Open Systems: An Exploratory.” MIS Quarterly 21 (1): 1–24. doi:10.2307/249740.
   Web of Science ®Google Scholar
• Cheng, Hong, Ruixue Jia, Dandan Li, and Hongbin Li. 2019. “The Rise of Robots in China.” Journal of Economic Perspectives 33 (2): 71–88. doi:10.1257/jep.33.2.71.
   Web of Science ®Google Scholar
• Chin, Wynne W., Robert A. Peterson, and Steven P. Brown. 2008. “Structural Equation Modeling in Marketing: Some Practical Reminders.” Journal of Marketing Theory and Practice 16 (4): 287–298. doi:10.2753/MTP1069-6679160402.
   Google Scholar
• Chiu, Chui-Yu, Chen Shi, and Chen Chun-Liang. 2017. “An Integrated Perspective of TOE Framework and Innovation Diffusion in Broadband Mobile Applications Adoption by Enterprises.” International Journal of Management, Economics and Social Sciences (IJMESS) 6 (1): 14–39. doi:http://hdl.handle.net/10419/157921.
   Google Scholar
• Choi, Moon, Sanghyun Kim, and Hyunsun Park. 2018. “Empirical Study on the Factors Influencing Process Innovation When Adopting Intelligent Robots at Small- and Medium-Sized Enterprises-The Role of Organizational Supports.” Information 9 (12): 315. doi:10.3390/info9120315.
   Google Scholar
• Chong, Alain, Yee Loong, and Felix T. S. Chan. 2012. “Structural Equation Modeling for Multi-Stage Analysis on Radio Frequency Identification (RFID) Diffusion in the Health Care Industry.” Expert Systems with Applications 39 (10): 8645–8654. doi:10.1016/j.eswa.2012.01.201.
   Web of Science ®Google Scholar
• Chouhan, Swarnima, Priyanka Mehra, and Ankita Daso. 2017. “India’s readiness for Industry 4.0 – A focus on automotive sector.” http://www.grantthornton.in/insights/articles/indias-readiness-for-industry-4.0–a-focus-on-automotive-sector/.
   Google Scholar
• Dauth, Wolfgang, Findesien Sebastian, Sudekum Jens, and Wober Nicole. 2017. “German Robots: The Impact of Industrial Robots on Workers.” IAB. http://doku.iab.de/discussionpapers/2017/dp3017.pdf.
   Google Scholar
• Davila Delgado, Juan Manuel, Lukumon Oyedele, Anuoluwapo Ajayi, Lukman Akanbi, Olugbenga Akinade, Muhammad Bilal, and Hakeem Owolabi. 2019. “Robotics and Automated Systems in Construction: Understanding Industry-Specific Challenges for Adoption.” Journal of Building Engineering 26: 100868. doi:10.1016/j.jobe.2019.100868.
   Web of Science ®Google Scholar
• Delic, Mia, and Daniel R. Eyers. 2020. “The Effect of Additive Manufacturing Adoption on Supply Chain Flexibility and Performance: An Empirical Analysis from the Automotive Industry.” International Journal of Production Economics 228: 107689. Elsevier B.V. doi:10.1016/j.ijpe.2020.
   Web of Science ®Google Scholar
• Depietro, R., E. Wiarda, and M. Fleischer. 1990. “The Context for Change: Organization, Technology and Environment.” The Processes of Technological Innovation 199 (0): 151–175.
   Google Scholar
• Dhakkapa, Bhargav. 2017. “How to Handle the Robot Invasion of Human Labour?” The Hindu. https://www.thehindu.com/thread/economy/should-we-consider-taxing-robots/article19949121.ece.
   Google Scholar
• Dhawan, Rajat, Gupta Shivanshu, Huddar Neeraj, Iyer Bajalji, Mangaleshwaran Ramesh, and Padhi Asutosh. 2018. “The Auto Component Industry in India: Preparing for the Future.” https://www.mckinsey.com/featured-insights/asia-pacific/the-auto-component-industry-in-india-preparing-for-the-future#:∼:text=apromisingfuture&text=The Indian automotive OEM industry,76mn vehicles%2C across segments.
   Google Scholar
• Duan, Y., J. S. Edwards, and Y. K. Dwivedi. 2019. “Artificial Intelligence for Decision Making in the Era of Big Data–Evolution, Challenges and Research Agenda.” International Journal of Information Management 48: 63–71. doi:10.1016/j.ijinfomgt.2019.01.021.
   Web of Science ®Google Scholar
• Dubey, Rameshwar, Zongwei Luo, Angappa Gunasekaran, Shahriar Akter, Benjamin T. Hazen, and Matthew A. Douglas. 2018. “Big Data and Predictive Analytics in Humanitarian Supply Chains.” The International Journal of Logistics Management 29 (2): 485–512. doi:10.1108/IJLM-02-2017-0039.
   Web of Science ®Google Scholar
• Dwivedi, Yogesh K., Laurie Hughes, Elvira Ismagilova, Gert Aarts, Crispin Coombs, Tom Crick, Yanqing Duan, et al. 2019. “Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging Challenges, Opportunities, and Agenda for Research, Practice and Policy.” International Journal of Information Management: 101994. doi:10.1016/j.ijinfomgt.2019.08.002.
   Web of Science ®Google Scholar
• Economic Times. 2019. “Tech’s Still a Strange Word for Manufacturers Here.” Economictimes.com. https://economictimes.indiatimes.com/tech/hardware/techs-still-a-strange-word-for-manufacturers-here/articleshow/71472489.cms.
   Google Scholar
• Fornell, C., and D. F. Larcker. 1981. “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research 18 (1): 39–50. doi:10.2307/3151312.
   Web of Science ®Google Scholar
• Fosso Wamba, Samuel, Angappa Gunasekaran, Mithu Bhattacharya, and Rameshwar Dubey. 2016. “Determinants of RFID Adoption Intention by SMEs: An Empirical Investigation.” Production Planning & Control 27 (12): 979–990. doi:10.1080/09537287.2016.1167981.
   Web of Science ®Google Scholar
• Gefen, David, Detmar Straub, and Marie-Claude Boudreau. 2000. “Communications of the Association for Information Systems Structural Equation Modeling and Regression: Guidelines for Research Practice.” Communications of the Association for Information Systems 4 (1): 1–77. doi:10.17705/100407.
   Google Scholar
• Ghobakhloo, Morteza, Arias-Aranda Daniel, and Benitez-Amado Jose. 2011. “Adoption of E-Commerce Applications in SMEs.” Industrial Management and Data Systems 111 (8): 1238–1269. doi:10.1108/02635571111170785.
   Web of Science ®Google Scholar
• Graetz, George, and Guy Michaels. 2018. “Robots at Work.” The Review of Economics and Statistics 100 (5): 753–768. doi:10.1162/REST.
   Web of Science ®Google Scholar
• Grant, R. M. 1991. “The Resource-Based Theory of Competitive Advantage: Implications for Strategy Formulation.” California Management Review 33 (3): 114–135. 35. doi:10.2307/41166664.
   Web of Science ®Google Scholar
• Grover, Varun. 1993. “An Empirically Derived Model for the Adoption of Customer‐Based Interorganizational Systems.” Decision Sciences 24 (3): 603–640. doi:10.1111/j.1540-5915.1993.tb01295.x.
   Web of Science ®Google Scholar
• Grover, P., A. K. Kar, and Y. K. Dwivedi. 2020. “Understanding Artificial Intelligence Adoption in Operations Management: Insights from the Review of Academic Literature and Social Media Discussions.” Annals of Operations Research : 1–37. doi:10.1007/s10479-020-03683-9.
   Web of Science ®Google Scholar
• Guadagnoli, Edward, and Wayne F. Velicer. 1988. “Relation of Sample Size to the Stability of Component Patterns.” Psychological Bulletin 103 (2): 265–275. doi:10.1037/0033-2909.103.2.265.
   PubMed Web of Science ®Google Scholar
• Gudergan, Siegfried P., Christian M. Ringle, Sven Wende, and Alexander Will. 2008. “Confirmatory Tetrad Analysis in PLS Path Modeling.” Journal of Business Research 61 (12): 1238–1249. doi:10.1016/j.jbusres.2008.01.012.
   Web of Science ®Google Scholar
• Guide, V. Daniel R., and Mikko Ketokivi. 2015. “Notes from the Editors: Redefining Some Methodological Criteria for the.” Journal of Operations Management 37 (1): v–viii. doi:10.1016/S0272-6963(15)00056-X.
   Google Scholar
• Gursoy, Dogan, Oscar Hengxuan Chi, Lu Lu, and Robin Nunkoo. 2019. “Consumers Acceptance of Artificially Intelligent (AI) Device Use in Service Delivery.” International Journal of Information Management 49: 157–169. doi:10.1016/j.ijinfomgt.2019.03.008.
   Web of Science ®Google Scholar
• Hair, J. F., Jr., G. T. M. Hult, C. M. Ringle, and M. Sarstedt. 2017. A Primer on Partial Least Squares Structural Equation Modeling. Long Range Planning. 2nd ed. Landon, UK: Sage Publication.
   Google Scholar
• Hair, Joe F., Christian Ringle, and Marko Sarstedt. 2011. “PLS-SEM: Indeed a Silver Bullet.” Journal of Marketing Theory and Practice 19 (2): 139–151. doi:10.2753/MTP1069-6679190202.
   Google Scholar
• Hair Jr, Joe F., Marko Sarstedt, Lucas Hopkins, and Volker G. Kuppelwieser. 2014. “Partial Least Squares Structural Equation Modeling (PLS-SEM): an Emerging Tool in Business Research.” European Business Review 26 (2): 106–121. doi:10.1108/EBR-10-2013-0128.
   Google Scholar
• Hassan, Mayadah, Maged Ali, Emel Aktas, and Kholoud Alkayid. 2015. “Factors Affecting Selection Decision of Auto-Identification Technology in Warehouse Management: An International Delphi Study.” Production Planning & Control 26 (12): 1025–1049. doi:10.1080/09537287.2015.1011726.
   Web of Science ®Google Scholar
• Hassan, Haslinda, Alexei Tretiakov, and Dick Whiddett. 2017. “Factors Affecting the Breadth and Depth of E-Procurement Use in Small and Medium Enterprises.” Journal of Organizational Computing and Electronic Commerce 27 (4): 304–324. Taylor & Francis: doi:10.1080/10919392.2017.1363584.
   Web of Science ®Google Scholar
• Henderson, Dave, Steven D. Sheetz, and Brad S. Trinkle. 2012. “International Journal of Accounting Information Systems the Determinants of Inter-Organizational and Internal in-House Adoption of XBRL: A Structural Equation Model.” International Journal of Accounting Information Systems 13 (2): 109–140. Elsevier Inc.: doi:10.1016/j.accinf.2012.02.001.
   Web of Science ®Google Scholar
• Henseler, Jörg, and Wynne W. Chin. 2010. “A Comparison of Approaches for the Analysis of Interaction Effects between Latent Variables Using Partial Least Squares Path Modeling.” Structural Equation Modeling: A Multidisciplinary Journal 17 (1): 82–109. doi:10.1080/10705510903439003.
   Web of Science ®Google Scholar
• Hossain, Mohammad Alamgir, Craig Standing, and Caroline Chan. 2017. “The Development and Validation of a Two-Staged Adoption Model of RFID Technology in Livestock Businesses.” Information Technology & People 30 (4): 785–808. doi:10.1108/ITP-06-2016-0133.
   Web of Science ®Google Scholar
• Hsu, Ching Wen., Ching Chiang Yeh 2017. “Understanding the Factors Affecting the Adoption of the Internet of Things.” Technology Analysis & Strategic Management 29, (9): 1089–1102. doi:10.1080/09537325.2016.1269160.
   Web of Science ®Google Scholar
• Huang, Zhenyu, Brian D. Janz, and Mark N. Frolick. 2008. “A Comprehensive Examination of Internet-EDI Adoption.” Information Systems Management 25 (3): 273–286. doi:10.1080/10580530802151228.
   Web of Science ®Google Scholar
• Huang, Ming-Hui, and Roland T. Rust. 2018. “Artificial Intelligence in Service.” Journal of Service Research 21 (2): 155–172. doi:10.1177/1094670517752459.
   Web of Science ®Google Scholar
• Hwang, Bang-Ning, Chi-Yo Huang, and Chih-Hsiung Wu. 2016. “A TOE Approach to Establish a Green Supply Chain Adoption Decision Model in the Semiconductor Industry.” Sustainability8 (2): 168. doi:10.3390/su8020168.
   Web of Science ®Google Scholar
• Iacovou, Charalambos L., Izak Benbasat, and Albert S. Dexter. 1995. “Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology.” MIS Quarterly 19 (4): 465–485. doi:10.2307/249629.
   Web of Science ®Google Scholar
• IBEF. 2019. “Auto components.” https://www.ibef.org/industry/autocomponents-india.aspx.
   Google Scholar
• IFR. 2018. “Executive summary world robotics 2018 industrial robots.” https://ifr.org/downloads/press2018/Executive_Summary_WR_2018_Industrial_Robots.pdf.
   Google Scholar
• Ivanov, S., Gretzel, U., Berezina, K., Sigala, M. and Webster, C. (2019). “Progress on robotics in hospitality and tourism: a review of the literature.” Journal of Hospitality and Tourism Technology 10 (4): 489–521.
   Google Scholar
• Ivanov, Stanislav, Webster Craig, and Berezina Katerina. 2018. “Adoption of Robots and Service Automation by Tourism and Hospitality Companies.” Revista Turismo & Desenvolvimento 1 (27/28): 1501–1517.
   Google Scholar
• Jasimuddin, Sajjad M., Nishikant Mishra, and Nasser A. Saif Almuraqab. 2017. “Modelling the Factors That Influence the Acceptance of Digital Technologies in E-Government Services in the UAE: A PLS-SEM Approach.” Production Planning & Control 28 (16): 1307–1317. doi:10.1080/09537287.2017.1375144.
   Web of Science ®Google Scholar
• Jia, Qiong, Yue Guo, and Stuart J. Barnes. 2017. “Enterprise 2.0 Post-Adoption: Extending the Information System Continuance Model Based on the Technology-Organization-Environment Framework.” Computers in Human Behavior 67: 95–105. doi:10.1016/j.chb.2016.10.022.
   Web of Science ®Google Scholar
• Kamble, Sachin, Angappa Gunasekaran, and Himanshu Arha. 2019. “Understanding the Blockchain Technology Adoption in Supply Chains-Indian Context.” International Journal of Production Research 57 (7): 2009–2033. doi:10.1080/00207543.2018.1518610.
   Web of Science ®Google Scholar
• Kaplan, Andreas, and Michael Haenlein. 2019. “Siri, Siri, in My Hand: Who’s the Fairest in the Land? On the Interpretations, Illustrations, and Implications of Artificial Intelligence.” Business Horizons 62 (1): 15–25. doi:10.1016/j.bushor.2018.08.004.
   Web of Science ®Google Scholar
• Keen, P. G. W. 1991. Shaping the Future. Boston, MA: Harvard Business School Press.
   Google Scholar
• Kildal, Johan, Izaskun Fernández, Stief Paul, Dantan Jean-Yves, Etienne Alain, and Siadat Ali. 2018. “Potential Users’ Key Concerns and Expectations for the Adoption of Cobots.” Procedia CIRP 72: 21–26. doi:10.1016/j.procir.2018.03.104.
   Google Scholar
• Kopacek, P. 1999. “Intelligent Manufacturing: Present State and Future Trends.” Journal of Intelligent and Robotic Systems 26 (3/4): 217–229. doi:10.1023/A:1008168605803.
   Web of Science ®Google Scholar
• Kumar, Karippur, Shalini Chandra, and Sushma Manava. 2016. “Factors Influencing Adoption of Agumentted Reality Technology for E-Commerce.” Factors Influencing Adoption of Augmented Reality Technology for E-Commerce 342. http://aisel.aisnet.org/pacis2016/342.
   Google Scholar
• Lai, Yuan, Sun Huifen, and Ren Jifan. 2018. “Understanding the Determinants of Big Data Analytics (BDA) Adoption in Logistics and Supply Chain Management: An Empirical Investigation.” International Journal of Logistics Management 29 (2): 676–703.
   Web of Science ®Google Scholar
• Li, Bo-hu, Bao-cun Hou, Wen-tao Yu, Xiao-bing Lu, and Chun-wei Yang. 2017. “Applications of Artificial Intelligence in Intelligent Manufacturing: A Review.” Frontiers of Information Technology & Electronic Engineering 18 (1): 86–96. doi:10.1631/FITEE.1601885.
   Web of Science ®Google Scholar
• Lin, Hsiu Fen. 2014. “Understanding the Determinants of Electronic Supply Chain Management System Adoption: Using the Technology-Organization-Environment Framework.” Technological Forecasting and Social Change 86: 80–92. Elsevier Inc.: doi:10.1016/j.techfore.2013.09.001.
   Web of Science ®Google Scholar
• Lin, Chieh‐Yu, and Yi‐Hui Ho. 2009. “RFID Technology Adoption and Supply Chain Performance: An Empirical Study in China’s Logistics Industry.” Supply Chain Management: An International Journal 14 (5): 369–378. doi:10.1108/13598540910980288.
   Web of Science ®Google Scholar
• Lin, Danping, C. K. M. Lee, Henry Lau, and Yang Yang. 2018. “Strategic Response to Industry 4.0: An Empirical Investigation on the Chinese Automotive Industry.” Industrial Management & Data Systems 118 (3): 589–605. doi:10.1108/IMDS-09-2017-0403.
   Web of Science ®Google Scholar
• Maduku, Daniel K., Mercy Mpinganjira, and Helen Duh. 2016. “Understanding Mobile Marketing Adoption Intention by South African SMEs: A Multi-Perspective Framework.” International Journal of Information Management 36 (5): 711–723. Elsevier Ltd: doi:10.1016/j.ijinfomgt.2016.04.018.
   Web of Science ®Google Scholar
• Mani, Sunil. 2018. “Robot Apocalypse: Does It Matter for India’s Manufacturing Industry?” Centre for Development Studies Working Paper No. 474. SSRN Electronic Journal. Tokyo. doi:10.2139/ssrn.3182255.
   Google Scholar
• Marcello Mariani, Matteo Borghi (2019), “Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries”, Technological Forecasting and Social Change 149: 119752. doi:10.1016/j.techfore.2019.119752.
   Google Scholar
• Mariani, Marcello, and, Matteo Borghi. 2019. “Industry 4.0: A Bibliometric Review of Its Managerial Intellectual Structure and Potential Evolution in the Service Industries.” Technological Forecasting and Social Change 149: 119752 doi:10.1016/j.techfore.2019.119752.
   Web of Science ®Google Scholar
• Mariani, Marcello M., Matteo Borghi, and Sergey Kazakov. 2019. “The Role of Language in the Online Evaluation of Hospitality Service Encounters: An Empirical Study.” International Journal of Hospitality Management 78: 50–58. (October 2018). Elsevier: doi:10.1016/j.ijhm.2018.11.012.
   Web of Science ®Google Scholar
• Masood, Tariq, and Johannes Egger. 2019. “Augmented Reality in Support of Industry 4.0—Implementation Challenges and Success Factors.” Robotics and Computer-Integrated Manufacturing 58: 181–195. doi:10.1016/j.rcim.2019.02.003.
   Web of Science ®Google Scholar
• Mathews, Sam. 2017. “India Ready to Accelerate Industrial Robotics Adoption.” Systemantics.Com. http://www.systemantics.com/2017/04/24/india-ready-to-accelerate-industrial-robotics-adoption/.
   Google Scholar
• Menifestias. 2020. “Robotics in India.” Manifestias.com. https://www.manifestias.com/2020/02/28/robotics-in-india/.
   Google Scholar
• Mittal, Sameer, Muztoba Ahmad Khan, Jayant Kishor Purohit, Karan Menon, David Romero, and Thorsten Wuest. 2020. “A Smart Manufacturing Adoption Framework for SMEs.” International Journal of Production Research 58 (5): 1555–1573. Taylor & Francis: 1–19. doi:10.1080/00207543.2019.1661540.
   Web of Science ®Google Scholar
• Müller-Abdelrazeq, Sarah L., Kathrin Schönefeld, Max Haberstroh, and Frank Hees. 2019. “Interacting with Collaborative Robots — A Study on Attitudes and Acceptance in Industrial Contexts.” In Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction, Human–Computer Interaction Series, 101–117. Cham: Springer International Publishing. doi:10.1007/978-3-030-17107-0.
   Google Scholar
• Nunnally, J. C. 1978. Psychometric Theory. Edited by 2. New York, NY: McGraw-Hill.
   Google Scholar
• OEMupdate. 2018. “Top Robotic Applications in Automotive Industry.” OEMupdate.com. http://www.oemupdate.com/technology/top-robotic-applications-in-automotive-industry/.
   Google Scholar
• Oliveira, Tiago, and Maria F. Martins. 2010. “Understanding E-Business Adoption across Industries in European Countries.” Industrial Management & Data Systems 110 (9): 1337–1354. doi:10.1108/02635571011087428.
   Web of Science ®Google Scholar
• Oliveira, Tiago, Ricardo Martins, Saonee Sarker, Manoj Thomas, and Aleš Popovič. 2019. “Understanding SaaS Adoption: The Moderating Impact of the Environment Context.” International Journal of Information Management 49: 1–12. doi:10.1016/j.ijinfomgt.2019.02.009.
   Web of Science ®Google Scholar
• Oliveira, Tiago, Manoj Thomas, and Mariana Espadanal. 2014. “Assessing the Determinants of Cloud Computing Adoption: An Analysis of the Manufacturing and Services Sectors.” Information & Management 51 (5): 497–510. doi:10.1016/j.im.2014.03.006.
   Web of Science ®Google Scholar
• Osakwe, Christian Nedu, Miloslava Chovancová, and Monica Agu. 2016. “Can Micro-Enterprises Leverage on the Adoption of Corporate Websites to Bolster Their Brand Visibility? Examining Salient Adoption Issues in Nigeria.” Information Development 32 (4): 904–919. doi:10.1177/0266666915573551.
   Web of Science ®Google Scholar
• Pan, Yunhe. 2016. “Heading toward Artificial Intelligence 2.0.” Engineering 2 (4): 409–413. doi:10.1016/J.ENG.2016.04.018.
   Web of Science ®Google Scholar
• Park, Eunil, and Sang Jib Kwon. 2016. “The Adoption of Teaching Assistant Robots: A Technology Acceptance Model Approach.” Program 50 (4): 354–366. doi:10.1108/PROG-02-2016-0017.
   Google Scholar
• Paryanto, Matthias,  Brossog, Martin Bornschlegl, and Jörg Franke. 2015. “Reducing the Energy Consumption of Industrial Robots in Manufacturing Systems.” International Journal of Advanced Manufacturing Technology 78 (5–8): 1315–1328. doi:10.1007/s00170-014-6737-z.
   Web of Science ®Google Scholar
• Penrose, E. T. 1958. The Theory of the Growth of the Firm. New York: Wiley.
   Google Scholar
• Peteraf, Margaret. 1993. “The Cornerstones of Competitive Advantage: A Resource-Based View Margaret.” Strategic Management Journal 14 (3): 179–191. doi:10.4324/9780203847589.
   Web of Science ®Google Scholar
• Pillai, Rajasshrie, and Brijesh Sivathanu. 2020. “Adoption of Artificial Intelligence (AI) for Talent Acquisition in IT/ITeS Organizations.” Benchmarking: An International Journal 27 (9): 2599–2629. doi:10.1108/BIJ-04-2020-0186.
   Web of Science ®Google Scholar
• Pillai, Rajasshrie, Brijesh Sivathanu, and Yogesh K. Dwivedi. 2020. “Shopping Intention at AI-Powered Automated Retail Stores (AIPARS).” Journal of Retailing and Consumer Services 57: 102207. doi:10.1016/j.jretconser.2020.102207.
   Web of Science ®Google Scholar
• Podsakoff, Philip M., Scott B. MacKenzie, Jeong-Yeon Lee, and Nathan P. Podsakoff. 2003. “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.” The Journal of Applied Psychology 88 (5): 879–903. doi:10.1037/0021-9010.88.5.879.
   PubMed Web of Science ®Google Scholar
• Podsakoff, Philip M., and Dennis W. Organ. 1986. “Self-Reports in Organizational Research: Problems and Prospects.” Journal of Management 12 (4): 531–544. doi:10.1177/014920638601200408.
   Web of Science ®Google Scholar
• Puklavec, Borut, Tiago Oliveira, and Aleš Popovič. 2018. “Understanding the Determinants of Business Intelligence System Adoption Stages an Empirical Study of SMEs.” Industrial Management & Data Systems 118 (1): 236–261. doi:10.1108/IMDS-05-2017-0170.
   Web of Science ®Google Scholar
• PWC. 2018. “Adopting a New Generation of Industrial Robots.” PwC, no. June 17.
   Google Scholar
• PWC. 2019. “Indian Automotive Sector: Creating Future-Ready Organizations.” https://www.pwc.in/assets/pdfs/industries/automotive/indian-automotive-sector.pdf.
   Google Scholar
• Queiroz, Maciel M., and Samuel Fosso Wamba. 2019. “Blockchain Adoption Challenges in Supply Chain: An Empirical Investigation of the Main Drivers in India and the USA.” International Journal of Information Management 46: 70–82. doi:10.1016/j.ijinfomgt.2018.11.021.
   Web of Science ®Google Scholar
• Ramanathan, Ramakrishnan, Elly Philpott, Yanqing Duan, and Guangming Cao. 2017. “Adoption of Business Analytics and Impact on Performance: A Qualitative Study in Retail.” Production Planning & Control 28 (11–12): 985–998. doi:10.1080/09537287.2017.1336800.
   Web of Science ®Google Scholar
• Rampasso, Izabela S., Rosley Anholon, Dirceu da Silva, Robert E. C. Ordóñez, and Osvaldo L. G. Quelhas. 2019. “Maturity Analysis of Manufacturing Cells.” Production Planning & Control 30 (15): 1250–1264. doi:10.1080/09537287.2019.1612108.
   Web of Science ®Google Scholar
• Reyes, Pedro M., Suhong Li, and John K. Visich. 2016. “Determinants of RFID Adoption Stage and Perceived Benefits.” European Journal of Operational Research 254 (3): 801–812. doi:10.1016/j.ejor.2016.03.051.
   Web of Science ®Google Scholar
• Ringle, C. M., S. Wende, and A. Will. 2005. “Smart PLS 2.0.” https://www.smartpls.com/.
   Google Scholar
• Roger, E. 1995. Diffusion of Innovations. 4th ed. New York: The Free Press.
   Google Scholar
• Rumelt, R. 1984. “Towards a Strategic Theory of the Firm.” In Competitive Strategic Management, edited by R. Lamb, 556–570. Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Russell, Stuart, and Norvig Peter. 2016. Artificial Intelligence: A Modern Approach. Malaysia: Perason Education limited. doi:10.1108/JBIM-06-2016-0122.
   Google Scholar
• Sackey, Samuel Mensah, and Andre Bester. 2016. “Industrial Engineering Curriculum in Industry 4.0 in a South African Context.” South African Journal of Industrial Engineering 27 (4): 101–114. doi:10.7166/27-4-1579.
   Web of Science ®Google Scholar
• Sangani, Priyanka. 2019. “Automation is Sweeping across India’s Manufacturing Space.” Economic Times. https://www.economictimes.indiatimes.com/articleshow/69262579.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst.
   Google Scholar
• Sangomla, Akshit. 2019. “Robots Are Here, Almost.” Downtoearth.Org.In. https://www.downtoearth.org.in/news/science-technology/robots-are-here-almost-63433.
   Google Scholar
• Schmidt, Rainer, Mohring Michael, Harting Ralf-Christian, Reichstein Christopher, Neumaier Pascal, and Jozinovic Philip. 2015. “Industry 4.0 - Potentials for Creating Smart Product: Empirical Reserach Results.” Business Information Systems:18th International Conference, BIS 2015 Poznań, Poland, Proceedings. Vol. 208. doi:10.1007/978-3-319-19027-3.
   Google Scholar
• Schuetz, Sebastian, and Viswanath Venkatesh. 2020. “Blockchain, Adoption, and Financial Inclusion in India: Research Opportunities.” International Journal of Information Management 52: 101936. doi:10.1016/j.ijinfomgt.2019.04.009.
   Web of Science ®Google Scholar
• Shaltoni, Abdel. 2017. “From Websites to Social Media: Exploring the Adoption of Internet Marketing in Emerging Industrial Markets.” Journal of Business & Industrial Marketing 32 (7): 1009–10019. doi:10.1108/JBIM-06-2016-0122.
   Web of Science ®Google Scholar
• Simoes, Ana C., Antonio L. Soares, and Ana C. Barros. 2019. “Drivers Impacting Cobots Adoption in Manufacturing Context: A Qualitative Study.” In Advances in Manufacturing II, edited by Justyna Trojanowska, Olaf Ciszak, José Mendes Machado, and Ivan Pavlenkodoi, Vol. 1: 203–212. Cham: Springer Nature Switzerland AG. doi:10.1007/978-3-030-18715-6.
   Google Scholar
• Sivathanu, Brijesh. 2019. “Adoption of Industrial IoT (IIoT) in Auto-Component Manufacturing SMEs in India.” Information Resources Management Journal 32 (2): 52–57.
   Web of Science ®Google Scholar
• Soffar, Heba. 2019. “Industrial Robot (Auto Industry) Uses, Advantages and Disadvantages.” Online Sciences. https://www.online-sciences.com/robotics/industrial-robot-auto-industry-uses-advantages-and-disadvantages/.
   Google Scholar
• Steven, Marks. 2019. “Pros and Cons of Using Industrial Robots in Your Manufacturing Operation.” Wilfli.Com. https://www.wipfli.com/insights/blogs/manufacturing-tomorrow-blog/pros-and-cons-of-industrial-robots-in-manufacturing.
   Google Scholar
• Sun, Shiwei, Casey G. Cegielski, Lin Jia, and Dianne J. Hall. 2018. “Understanding the Factors Affecting the Organizational Adoption of Big Data.” Journal of Computer Information Systems 58 (3): 193–203. Taylor & Francis: doi:10.1080/08874417.2016.1222891.
   Web of Science ®Google Scholar
• Tapiero, Charles S. 1990. “Technology and the Manufacturing Process.” Production Planning & Control 1 (2): 85–91. doi:10.1080/09537289008919301.
   Google Scholar
• Teece, David J., Gary Pisano, and Amy Shuen. 1997. “Dynamic Capabilities and Strategic Management.” Strategic Management Journal 18 (7): 509–533. doi:10.1142/9789812834478_0002.
   Web of Science ®Google Scholar
• Teulieres, Marc, Jonathan Tilley, Lea Bolz, Peter Leuwing-Dehm, and Susanne Wagner. 2019. “Industrial Robotics - Insights into the Sector’s Grwoth Dynamics.” Mckinsey & Company. https://www.mckinsey.com/∼/media/McKinsey/Industries/AdvancedElectronics/OurInsights/Growthdynamicsinindustrialrobotics/Industrial-robotics-Insights-into-the-sectors-future-growth-dynamics.ashx.
   Google Scholar
• Troshani, Indrit, Jerram Cate, and Gerrard Michael. 2010. “Exploring the Organizational Adoption of Human Resources Information Systems (HRIS) in the Australian Public Sector.” ACIS 2010 Proceedings - 21st Australasian Conference on Information Systems.
   Google Scholar
• Tsou, Hung Tai., and Sheila Hsuan Yu Hsu. 2015. “Performance Effects of Technology-Organization-Environment Openness, Service Co-Production, and Digital-Resource Readiness: The Case of the IT Industry.” International Journal of Information Management 35 (1): 1–14. doi:10.1016/j.ijinfomgt.2014.09.001.
   Web of Science ®Google Scholar
• Tung, Vincent, Wing Sun, and Norman Au. 2018. “Exploring Customer Experiences with Robotics in Hospitality.” International Journal of Contemporary Hospitality Management 30 (7): 2680–2697. doi:10.1108/IJCHM-06-2017-0322.
   Google Scholar
• Turja, Tuuli, and Atte Oksanen. 2019. “Robot Acceptance at Work: A Multilevel Analysis Based on 27 EU Countries.” International Journal of Social Robotics 11 (4): 679–689. no. 0123456789. Springer Netherlands. doi:10.1007/s12369-019-00526-x.
   Web of Science ®Google Scholar
• Venkatesh, Viswanath, and Fred D. Davis. 2000. “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies.” Management Science 46 (2): 186–204. doi:10.1287/mnsc.46.2.186.11926.
   Web of Science ®Google Scholar
• Wang, Yu Yin., Yi Shun Wang, and Tung Ching Lin. 2018. “Developing and Validating a Technology Upgrade Model.” International Journal of Information Management 38 (1): 7–26. doi:10.1016/j.ijinfomgt.2017.07.003.
   Web of Science ®Google Scholar
• Wang, Yu Min., Yi Shun Wang, and Yong Fu Yang. 2010. “Understanding the Determinants of RFID Adoption in the Manufacturing Industry.” Technological Forecasting and Social Change 77 (5): 803–815. doi:10.1016/j.techfore.2010.03.006.
   Web of Science ®Google Scholar
• Wang, Yi-Shun, Ching-Hsuan Yeh, and Yi-Wen Liao. 2013. “What Drives Purchase Intention in the Context of Online Content Services? The Moderating Role of Ethical Self-Efficacy for Online Piracy.” International Journal of Information Management 33 (1): 199–208. doi:10.1016/j.ijinfomgt.2012.09.004.
   Web of Science ®Google Scholar
• Wei, Jie, Paul Benjamin Lowry, and Stefan Seedorf. 2015. “The Assimilation of RFID Technology by Chinese Companies: A Technology Diffusion Perspective.” Information & Management 52 (6): 628–642. doi:10.1016/j.im.2015.05.001.
   Web of Science ®Google Scholar
• Wernerfelt, Birger. 1984. “A Resource Based View of the Firm.” Strategic Management Journal 5 (2): 171–180. doi:10.1002/smj.4250050207.
   Web of Science ®Google Scholar
• Yeh, Ching Chiang, and Yi Fan Chen. 2018. “Critical Success Factors for Adoption of 3D Printing.” Technological Forecasting and Social Change 132 (6): 209–216. doi:10.1016/j.techfore.2018.02.003.
   Google Scholar
• Zhu, Kevin, and Kenneth L. Kraemer. 2005. “Post-Adoption Variations in Usage and Value of e-Business by Organizations: Cross-Country Evidence from the Retail Industry.” Information Systems Research 16 (1): 61–84. doi:10.1287/isre.1050.0045.
   Web of Science ®Google Scholar