Browse > Article
http://dx.doi.org/10.13106/jafeb.2020.vol7.no6.255

Factors Affecting Adoption of Industry 4.0 by Small- and Medium-Sized Enterprises: A Case in Ho Chi Minh City, Vietnam  

NGUYEN, Xuan Truong (Marketing Department, University of Finance - Marketing)
LUU, Quang Khai (Marketing Department, University of Finance - Marketing)
Publication Information
The Journal of Asian Finance, Economics and Business / v.7, no.6, 2020 , pp. 255-264 More about this Journal
Abstract
The fourth industrial revolution has attracted much academic attention in these past few years. However, research on systematic and extensive factors affecting adoption of Industry 4.0 by SMEs in developing countries, especially in Vietnam, has been unavailable. This study aims to explore the impact of factors that influence the actual adoption of Industry 4.0 by SMEs in Ho Chi Minh City. Mixed-method research was utilized in this study including in-depth interviews of 12 participants and quantitative research of 396 respondents who are representative of SMEs by both online and via paper surveys. The SPSS and SmartPLS 3 software were employed to help analyze the collected data. The results indicate that perceived development of the human resource, perceived on-time, perceived saving cost, perceived improve product quality, perceived saving time, perceived ease-of-use, business resources, and conditions of the business environment, perceived usefulness, perceived enhanced customer relationship, and adoption intention, all have a positive significant effect on actual adoption of Industry 4.0. The results seem to suggest that managerial efforts aimed at increasing the factors' perceptions of adoption of Industry 4.0 and personal relevance of the technology will contribute to implementation success, where success is defined as effectual usage of the Industry 4.0.
Keywords
Industry 4.0; Elements of Industry 4.0; Small and Medium Enterprises; Adoption of Industry 4.0; Ho Chi Minh City;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
1 Nguyen, X. T. (2019). Factors impacting on Korean consummer goods purchase decision of Vietnam's generation Z. Journal Distribution Science, 17(10), 61-71.   DOI
2 Oesterreich, T. D. & Teuteberg, F. (2016). Understanding the implications of digitisation and automation in the context of Industry 4.0. Computers in Industry, 83, 121-139.   DOI
3 Potluri, R. M., & Vajjhala, N. R. (2018). A Study on Application of Web 3.0 Technologies in Small and Medium Enterprises of India. Journal of Asian Finance, Economics and Business, 5(2), 73-79. https://doi.org/10.13106/jafeb.2018.vol5.no2.73.   DOI
4 Potter, A., Towill, D. R, & Christopher, M. (2015). Evolution of the migratory supply chain model. Supply Chain Management A International Journal, 20(6), 603-612.   DOI
5 Radziwon, A., Bilberg, A., Bogers, M., & Madsen, E. S. (2014). The smart factory: exploring adaptive and flexible manufacturing solutions. Procedia Engineering, 69, 1184-1190.   DOI
6 Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-339.   DOI
7 Harrigan, P., Ramsey, E., & Ibbotson, P. (2011). Critical factors underpinning the e-CRM activities of SMEs. Journal of Marketing Management, 27(5-6), 503-529.   DOI
8 Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557-582.   DOI
9 Agostini, L., & Nosella, A. (2019). The adoption of Industry 4.0 technologies in SMEs: results of an international study. Management Decision, 58(4), 625-643.   DOI
10 Kopetz, H. (2011). Real-time systems: design principles for distributed embedded applications. Springer Science & Business Media.
11 Lawshe, C. H. (1975). A quantitative approach to content validity 1. Personnel Psychology, 28(4), 563-575.   DOI
12 Erol, S., Jager, A., Hold, P., Ott, K., & Sihn, W. (2016). Tangible Industry 4.0: a scenario-based approach to learning for the future of production. Procedia CiRp, 54(1), 13-18.   DOI
13 Fishbein, M., & Ajzen, I. (1975). Intention and Behavior: An introduction to theory and research.
14 Friederichsen, M. R. M. B. N., & Keller, M. (2014). How virtualization, decentralization and network building change the manufacturing landscape: An Industry 4.0 perspective. International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 8(1), 37-44.
15 Fonseca, L. M. (2018, May). Industry 4.0 and the digital society: concepts, dimensions and envisioned benefits. In Proceedings of the international conference on business excellence (Vol. 12, No. 1, pp. 386-397). Sciendo.
16 Gourlay, C. (1999). Partners apart: managing civil-military cooperation in humanitarian interventions. UNIDIR.
17 Green, G. C., Hevner, A. R., & Collins, R. W. (2005). The impacts of quality and productivity perceptions on the use of software process improvement innovations. Information and Software Technology, 47(8), 543-553.   DOI
18 Ha, V. D. (2020). Impact of Organizational Culture on the Accounting Information System and Operational Performance of Small and Medium Sized Enterprises in Ho Chi Minh City. Journal of Asian Finance, Economics and Business, 7(2), 301-308. https://doi.org/10.13106/jafeb.2020.vol7.no2.301.   DOI
19 Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R.L. (1995). Multivariate data analysis (4th ed.). USA: Prentice-Hall, Inc.
20 Leong, L. Y., Ooi, K. B., Chong, A. Y. L., & Lin, B. (2011). Influence of individual characteristics, perceived usefulness and ease of use on mobile entertainment adoption. International Journal of Mobile Communications, 9(4), 359-382.   DOI
21 Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International journal of information management, 31(3), 252-260.   DOI
22 Lonn, S., & Teasley, S. D. (2009). Saving time or innovating practice: Investigating perceptions and uses of Learning Management Systems. Computers & Education, 53(3), 686-694.   DOI
23 Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1-10.   DOI
24 Matopoulos, A., & Bourlakis, M. (2011). Identifying innovation strategies: insights from the Greek food manufacturing sector. International Journal of Innovation and Regional Development, 3(2), 159-173.   DOI
25 UNIDO. (2016). Opportunities and Challenges of the New Industrial Revolution for Developing Countries and Economies in Transition. Retrieved 20 May 2019 from www.unido.org/fileadmin/user_media_upgrade/Resources/Publications/Unido_industry-4_NEW.pdf.
26 Velocloud. (2015). Devcon Provides Reliable Access to Cloud Apps and Improves Remote Collaboration. Retrieved 20 May 2020 from: http://www.velocloud.com/ customers/case-studydevcon.
27 Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.   DOI
28 Wang, L., Torngren, M., & Onori, M. (2015). Current status and advancement of cyber-physical systems in manufacturing. Journal of Manufacturing Systems, 37, 517-527.   DOI
29 Wang, S., Wan, J., Li, D., & Zhang, C. (2016). Implementing smart factory of industrie 4.0: an outlook. International Journal of Distributed Sensor Networks, 12(1), 3159805.   DOI
30 Yoo, S. K., & Kim, B. Y. (2018). The Effective Factors of Cloud Computing Adoption Success in Organization. The Journal of Asian Finance, Economics and Business, 6(1), 217-229. http://doi.org/10.13106/jafeb.2019.vol6.no1.217.   DOI
31 Yuchun, X. & Mu, C. (2017). An Internet of Things based framework to enhance just-in-time manufacturing. The Journal of Engineering Manufacture, 232(13), 2353-2363.
32 Zhou, K., Liu, T., & Zhou, L. (2015, August). Industry 4.0: Towards future industrial opportunities and challenges. In 2015 12th International Conference on fuzzy systems and knowledge discovery (FSKD) (pp. 2147-2152). IEEE.
33 Watkins, K. E., & Marsick, V. J. (1997). Dimensions of the learning organization questionnaire. Warwick, RI: Partners for the learning organization.
34 Yin, Y., & Qin, S. F. (2019). A smart performance measurement approach for collaborative design in Industry 4.0. Advances in Mechanical Engineering, 11(1), 1-15.
35 Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.   DOI
36 Russmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., & Harnisch, M. (2015). Industry 4.0: The future of productivity and growth in manufacturing industries. Boston Consulting Group, 9(1), 54-89.
37 Santos, K., Loures, E., Pjechnicki, F., Canciglieri, O. (2017). Opportunities Assessment of Product Development Process in Industry 4.0. Procedia Manufacturing, 11(1), 358-1365.
38 Akanmu, A. & Anumba, C. J. (2015). Cyber-physical systems integration of building information models and physical construction. Engineering, Construction, and Architectural Management 22(5), 516-535.   DOI
39 Amoako-Gyampah, K. (2007). Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation. Computers in human behavior, 23(3), 1232-1248.   DOI
40 Amoako-Gyampah, K., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information&management, 41(6), 731-745.   DOI
41 Sardroud, J. M. (2012). Influence of RFID technology on automated management of construction materials and components. Scientia Iranica, 19(3), 381-392.   DOI
42 Sarstedt, M., Ringle, C. M., & Hair, J. F. (2017). Partial least squares structural equation modeling. Handbook of market research, 26, 1-40.
43 Schwab, K. (2017). The Fourth Industrial Revolution. New York: Crown Publishing Group.
44 Smith, P. (2014). BIM & the 5D Project Cost Manager. Procedia - Social and Behavioral Sciences, 119, 475-484.   DOI
45 Suki, N. M., & Suki, N. M. (2011). Exploring the relationship between perceived usefulness, perceived ease of use, perceived enjoyment, attitude and subscribers' intention towards using 3G mobile services. Journal of Information Technology Management, 22(1), 1-7.
46 Sundblad, W. (2018). How Industry 4.0 Helps Manufacturers Solve Workforce Challenge Retrieved 20 May 2019 From https://www.forbes.com/sites/willemsundbladeurope/2018/08/28/how-industry-4-0-helps-manufacturers-solve-workforcechallenges/
47 Szajna, B. (1996). Empirical evaluation of the revised technology acceptance model. Management Science, 42(1), 85-92.   DOI
48 Szozda, N. (2017). Industry 4.0 and its impact on the functioning of supply chains. LogForum, Scientific Journal of Logistics, 13(4), 401-414.
49 Taylor, S., & Todd, P. A. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly. 19(4), 561-570.   DOI
50 Mavri, M. (2015). Redesigning a Production Chain Based on 3D Printing Technology. Knowledge and Process Management, 22(3), 141-147.   DOI
51 Moeuf, A., Pellerin, R., Lamouri, S., Tamayo-Giraldo, S., & Barbaray, R. (2018). The industrial management of SMEs in the era of Industry 4.0. International Journal of Production Research, 56(3), 1118-1136.   DOI
52 Muchran, M., & Ahmar, A. S. (2019). Application of TAM model to the use of information technology. arXiv preprint arXiv:1901.11358.
53 Nguyen, T. H., Newby, M., & Macaulay, M. J. (2015). Information technology adoption in small business: Confirmation of a proposed framework. Journal of Small Business Management, 53(1), 207-227.   DOI
54 Nguyen, X. T. (2018). The Impact of Hallyu 4.0 and Social Media on Korean Products Purchase Decision of Generation C in Vietnam. Journal of Asian Finance, Economics, and Business, 5(3) 81-93. http://doi.org/10.13106/jafeb.2018.vol5.no3.81.   DOI