IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i4p414-d502516.html
   My bibliography  Save this article

Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach

Author

Listed:
  • Shih-Chia Chang

    (College of Management, National Taipei University of Business, Taipei 10051, Taiwan)

  • Hsu-Hwa Chang

    (Department of Business Administration, National Taipei University of Business, Taipei 10051, Taiwan)

  • Ming-Tsang Lu

    (College of Management, National Taipei University of Business, Taipei 10051, Taiwan)

Abstract

Evaluating Industry 4.0 technology application in small and medium-sized enterprises (SMEs) is an issue that requires a multi-criteria strategy comprising quantitative and qualitative elements. The purpose of this study is to integrate performance estimation of Industry 4.0 technology application using the technology–organization–environment (TOE) framework. Relating TOE to Industry 4.0 technology application evaluation is more multifaceted than other methods and it requires comprehensive analysis. In this study, we applied a multiple-criteria decision-making (MCDM) approach to develop a model which integrates MCDM to perform an assessment that prioritizes the influence weights of Industry 4.0 technology application to SMEs’ factors. Firstly, we carried out a review of the literature and the TOE framework was selected to generate nine elements, along with three aspects used to measure Industry 4.0 technology application in SMEs. Secondly, the approach of the decision-making trial and evaluation laboratory (DEMATEL) was set up using an influence network relations digraph (INRD). The DEMATEL-based analytic network process (DANP) was used to indicate the influence weights linking the above aspects and elements. Lastly, the modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique applied influence weights to assess the aspects/elements in the gaps identified and to investigate how to reduce the gaps so as to estimate the application of Industry 4.0 technology by SMEs. The results show that the technology aspect is the most influential factor.

Suggested Citation

  • Shih-Chia Chang & Hsu-Hwa Chang & Ming-Tsang Lu, 2021. "Evaluating Industry 4.0 Technology Application in SMEs: Using a Hybrid MCDM Approach," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:414-:d:502516
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/4/414/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/4/414/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fernanda Strozzi & Claudia Colicchia & Alessandro Creazza & Carlo Noè, 2017. "Literature review on the ‘Smart Factory’ concept using bibliometric tools," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6572-6591, November.
    2. Schniederjans, Dara G. & Curado, Carla & Khalajhedayati, Mehrnaz, 2020. "Supply chain digitisation trends: An integration of knowledge management," International Journal of Production Economics, Elsevier, vol. 220(C).
    3. Osterrieder, Philipp & Budde, Lukas & Friedli, Thomas, 2020. "The smart factory as a key construct of industry 4.0: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 221(C).
    4. de Sousa Jabbour, Ana Beatriz Lopes & Jabbour, Charbel Jose Chiappetta & Foropon, Cyril & Godinho Filho, Moacir, 2018. "When titans meet – Can industry 4.0 revolutionise the environmentally-sustainable manufacturing wave? The role of critical success factors," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 18-25.
    5. Raj, Alok & Dwivedi, Gourav & Sharma, Ankit & Lopes de Sousa Jabbour, Ana Beatriz & Rajak, Sonu, 2020. "Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective," International Journal of Production Economics, Elsevier, vol. 224(C).
    6. Ming-Tsang Lu & Gwo-Hshiung Tzeng & Hilary Cheng & Chih-Cheng Hsu, 2015. "Exploring mobile banking services for user behavior in intention adoption: using new hybrid MADM model," Service Business, Springer;Pan-Pacific Business Association, vol. 9(3), pages 541-565, September.
    7. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    8. Li, Ling, 2018. "China's manufacturing locus in 2025: With a comparison of “Made-in-China 2025” and “Industry 4.0”," Technological Forecasting and Social Change, Elsevier, vol. 135(C), pages 66-74.
    9. Mellor, Stephen & Hao, Liang & Zhang, David, 2014. "Additive manufacturing: A framework for implementation," International Journal of Production Economics, Elsevier, vol. 149(C), pages 194-201.
    10. Mehrdokht Pournader & Yangyan Shi & Stefan Seuring & S.C. Lenny Koh, 2020. "Blockchain applications in supply chains, transport and logistics: a systematic review of the literature," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2063-2081, April.
    11. Dalenogare, Lucas Santos & Benitez, Guilherme Brittes & Ayala, Néstor Fabián & Frank, Alejandro Germán, 2018. "The expected contribution of Industry 4.0 technologies for industrial performance," International Journal of Production Economics, Elsevier, vol. 204(C), pages 383-394.
    12. Reynolds, Elisabeth B. & Uygun, Yilmaz, 2018. "Strengthening advanced manufacturing innovation ecosystems: The case of Massachusetts," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 178-191.
    13. Fukuda, Kayano, 2020. "Science, technology and innovation ecosystem transformation toward society 5.0," International Journal of Production Economics, Elsevier, vol. 220(C).
    14. Yeh, Ching-Chiang & Chen, Yi-Fan, 2018. "Critical success factors for adoption of 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 209-216.
    15. Urbinati, Andrea & Bogers, Marcel & Chiesa, Vittorio & Frattini, Federico, 2019. "Creating and capturing value from Big Data: A multiple-case study analysis of provider companies," Technovation, Elsevier, vol. 84, pages 21-36.
    16. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2007. "Extended VIKOR method in comparison with outranking methods," European Journal of Operational Research, Elsevier, vol. 178(2), pages 514-529, April.
    17. Yong Yin & Kathryn E. Stecke & Dongni Li, 2018. "The evolution of production systems from Industry 2.0 through Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 848-861, January.
    18. Lu, Yang & Papagiannidis, Savvas & Alamanos, Eleftherios, 2018. "Internet of Things: A systematic review of the business literature from the user and organisational perspectives," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 285-297.
    19. Lu, Ming-Tsang & Hsu, Chao-Che & Liou, James J.H. & Lo, Huai-Wei, 2018. "A hybrid MCDM and sustainability-balanced scorecard model to establish sustainable performance evaluation for international airports," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 9-19.
    20. Tortorella, Guilherme Luz & Cawley Vergara, Alejandro Mac & Garza-Reyes, Jose Arturo & Sawhney, Rapinder, 2020. "Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers," International Journal of Production Economics, Elsevier, vol. 219(C), pages 284-294.
    21. James J. H. Liou & Ming-Tsang Lu & Shu-Kung Hu & Chia-Hua Cheng & Yen-Ching Chuang, 2017. "A Hybrid MCDM Model for Improving the Electronic Health Record to Better Serve Client Needs," Sustainability, MDPI, vol. 9(10), pages 1-13, October.
    22. Kummitha, Rama Krishna Reddy & Crutzen, Nathalie, 2019. "Smart cities and the citizen-driven internet of things: A qualitative inquiry into an emerging smart city," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 44-53.
    23. Scott J. Wallsten, 2000. "The Effects of Government-Industry R&D Programs on Private R&D: The Case of the Small Business Innovation Research Program," RAND Journal of Economics, The RAND Corporation, vol. 31(1), pages 82-100, Spring.
    24. Julien Gardan, 2016. "Additive manufacturing technologies: state of the art and trends," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3118-3132, May.
    25. Doh, Soogwan & Kim, Byungkyu, 2014. "Government support for SME innovations in the regional industries: The case of government financial support program in South Korea," Research Policy, Elsevier, vol. 43(9), pages 1557-1569.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Daniel Fernández & Álvaro Rodríguez-Prieto & Ana M. Camacho, 2022. "Optimal Parameters Selection in Advanced Multi-Metallic Co-Extrusion Based on Independent MCDM Analytical Approaches and Numerical Simulation," Mathematics, MDPI, vol. 10(23), pages 1-26, November.
    2. Alok Raj & Anand Jeyaraj, 2023. "Antecedents and consequents of industry 4.0 adoption using technology, organization and environment (TOE) framework: A meta-analysis," Annals of Operations Research, Springer, vol. 322(1), pages 101-124, March.
    3. Shih-Hsien Tseng & Hsiu-Chuan Chen & Tien Son Nguyen, 2022. "Key Success Factors of Sustainable Organization for Traditional Manufacturing Industries: A Case Study in Taiwan," Mathematics, MDPI, vol. 10(22), pages 1-17, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Culot, Giovanna & Orzes, Guido & Sartor, Marco & Nassimbeni, Guido, 2020. "The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    2. Gillani, Fatima & Chatha, Kamran Ali & Sadiq Jajja, Muhammad Shakeel & Farooq, Sami, 2020. "Implementation of digital manufacturing technologies: Antecedents and consequences," International Journal of Production Economics, Elsevier, vol. 229(C).
    3. Cifone, Fabiana Dafne & Hoberg, Kai & Holweg, Matthias & Staudacher, Alberto Portioli, 2021. "‘Lean 4.0’: How can digital technologies support lean practices?," International Journal of Production Economics, Elsevier, vol. 241(C).
    4. Mariani, Marcello & Borghi, Matteo, 2019. "Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
    5. Colombari, Ruggero & Geuna, Aldo & Helper, Susan & Martins, Raphael & Paolucci, Emilio & Ricci, Riccardo & Seamans, Robert, 2023. "The interplay between data-driven decision-making and digitalization: A firm-level survey of the Italian and U.S. automotive industries," International Journal of Production Economics, Elsevier, vol. 255(C).
    6. Juin-Hao Ho & Gwo-Guang Lee & Ming-Tsang Lu, 2020. "Exploring the Implementation of a Legal AI Bot for Sustainable Development in Legal Advisory Institutions," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
    7. Stornelli, Aldo & Ozcan, Sercan & Simms, Christopher, 2021. "Advanced manufacturing technology adoption and innovation: A systematic literature review on barriers, enablers, and innovation types," Research Policy, Elsevier, vol. 50(6).
    8. Tamvada, Jagannadha Pawan & Narula, Sanjiv & Audretsch, David & Puppala, Harish & Kumar, Anil, 2022. "Adopting new technology is a distant dream? The risks of implementing Industry 4.0 in emerging economy SMEs," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    9. Laubengaier, Désirée A. & Cagliano, Raffaella & Canterino, Filomena, 2022. "It Takes Two to Tango: Analyzing the Relationship between Technological and Administrative Process Innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    10. Virmani, Naveen & Sharma, Shikha & Kumar, Anil & Luthra, Sunil, 2023. "Adoption of industry 4.0 evidence in emerging economy: Behavioral reasoning theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    11. Mitsuhiro Fukuzawa & Ryosuke Sugie & Youngwon Park & Jin Shi, 2022. "An Exploratory Case Study on the Metrics and Performance of IoT Investment in Japanese Manufacturing Firms," Sustainability, MDPI, vol. 14(5), pages 1-21, February.
    12. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    13. Bai, Chunguang & Dallasega, Patrick & Orzes, Guido & Sarkis, Joseph, 2020. "Industry 4.0 technologies assessment: A sustainability perspective," International Journal of Production Economics, Elsevier, vol. 229(C).
    14. Tsai, Pei-Hsuan, 2020. "Strategic evaluation criteria to assess competitiveness of the service industry in Taiwan," Journal of Policy Modeling, Elsevier, vol. 42(6), pages 1287-1309.
    15. Rafael, Lizarralde Dorronsoro & Jaione, Ganzarain Epelde & Cristina, López & Ibon, Serrano Lasa, 2020. "An Industry 4.0 maturity model for machine tool companies," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    16. Shu-Kung Hu & James J. H. Liou & Ming-Tsang Lu & Yen-Ching Chuang & Gwo-Hshiung Tzeng, 2018. "Improving NFC Technology Promotion for Creating the Sustainable Education Environment by Using a Hybrid Modified MADM Model," Sustainability, MDPI, vol. 10(5), pages 1-24, April.
    17. Bo-Wei Zhu & Jia-Rui Zhang & Gwo-Hshiung Tzeng & Shan-Lin Huang & Lei Xiong, 2017. "Public Open Space Development for Elderly People by Using the DANP-V Model to Establish Continuous Improvement Strategies towards a Sustainable and Healthy Aging Society," Sustainability, MDPI, vol. 9(3), pages 1-29, March.
    18. Cugno, Monica & Castagnoli, Rebecca & Büchi, Giacomo, 2021. "Openness to Industry 4.0 and performance: The impact of barriers and incentives," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    19. Roland Zs. Szabo & Iva Vuksanović Herceg & Robert Hanák & Lilla Hortovanyi & Anita Romanová & Marian Mocan & Dragan Djuričin, 2020. "Industry 4.0 Implementation in B2B Companies: Cross-Country Empirical Evidence on Digital Transformation in the CEE Region," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    20. Alok Raj & Anand Jeyaraj, 2023. "Antecedents and consequents of industry 4.0 adoption using technology, organization and environment (TOE) framework: A meta-analysis," Annals of Operations Research, Springer, vol. 322(1), pages 101-124, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:414-:d:502516. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.