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Determinants of information and digital technology implementation for smart manufacturing

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  • Morteza Ghobakhloo

Abstract

This study aims to identify and analyse factors that determine the implementation of Information and Digital Technologies (IDT) of smart manufacturing. By performing a state-of-the-art and content-driven review of literature, consulting a group of experts from academia and industry, and implementing interpretive structural modelling methodology, the study identified eleven enabling factors and mapped the contextual interrelationships among them. The study further explained the complex precedence relationships that exist among determinants of smart manufacturing IDT adoption. Results showed that perceived benefits and management support are the two driver determinants that act as stepping-stones in the implementation of smart manufacturing IDT. Operations technology maturity and cybersecurity maturity were found to be the dependent determinants of smart manufacturing IDT implementation and highly driven by the linkage and driver determinates. The findings are expected to assist academicians, industrialists, and the policymakers with achieving a detailed understanding of smart manufacturing transformation processes, and conditions that facilitate the manufacturing digitalisation in the Industry 4.0 era.

Suggested Citation

  • Morteza Ghobakhloo, 2020. "Determinants of information and digital technology implementation for smart manufacturing," International Journal of Production Research, Taylor & Francis Journals, vol. 58(8), pages 2384-2405, April.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:8:p:2384-2405
    DOI: 10.1080/00207543.2019.1630775
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    Cited by:

    1. Qiao, Lu & Li, Lin & Fei, Junjun, 2022. "Information infrastructure and air pollution: Empirical analysis based on data from Chinese cities," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 563-573.
    2. Mnahel Babgi & Benyamin Aghhavani-Shajari & Marion Vieux, 2023. "Evolution of Digitalization and Internationalization Literature: A Bibliometric and Content Analysis for Future Research Agenda," Post-Print hal-04398156, HAL.
    3. Lin, Shunzhi & Lin, Jiabao, 2023. "How organizations leverage digital technology to develop customization and enhance customer relationship performance: An empirical investigation," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Evgeniy V. Kislitsyn, 2021. "Russia’s information technology sector: The competitive environment transformation and structural shifts’ assessment," Journal of New Economy, Ural State University of Economics, vol. 22(2), pages 66-87, July.
    5. Oliveira-Dias, Diéssica de & Maqueira-Marin, Juan Manuel & Moyano-Fuentes, José & Carvalho, Helena, 2023. "Implications of using Industry 4.0 base technologies for lean and agile supply chains and performance," International Journal of Production Economics, Elsevier, vol. 262(C).
    6. Asadi, Shahla & Nilashi, Mehrbakhsh & Iranmanesh, Mohammad & Hyun, Sunghyup Sean & Rezvani, Azadeh, 2022. "Effect of internet of things on manufacturing performance: A hybrid multi-criteria decision-making and neuro-fuzzy approach," Technovation, Elsevier, vol. 118(C).
    7. Diéssica Oliveira-Dias & José Moyano-Fuentes & Juan Manuel Maqueira-Marín, 2022. "Understanding the relationships between information technology and lean and agile supply chain strategies: a systematic literature review," Annals of Operations Research, Springer, vol. 312(2), pages 973-1005, May.
    8. Vimal K.E. K & Sivakumar K & Jayakrishna Kandasamy & Vaibhav Venkat & Raghuraman Srinivasan Mani, 2023. "Barriers to the adoption of digital technologies in a functional circular economy network," Operations Management Research, Springer, vol. 16(3), pages 1541-1561, September.
    9. Núñez-Merino, Miguel & Maqueira-Marín, Juan Manuel & Moyano-Fuentes, José & Castaño-Moraga, Carlos Alberto, 2022. "Industry 4.0 and supply chain. A Systematic Science Mapping analysis," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    10. Arranz, Carlos F.A. & Arroyabe, Marta F. & Arranz, Nieves & de Arroyabe, Juan Carlos Fernandez, 2023. "Digitalisation dynamics in SMEs: An approach from systems dynamics and artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    11. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
    12. Jang, Hyunmi & Haddoud, Mohamed Yacine & Roh, Saeyeon & Onjewu, Adah-Kole Emmanuel & Choi, Taeeun, 2023. "Implementing smart factory: A fuzzy-set analysis to uncover successful paths," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    13. 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.
    14. Saleh Fahed Alkhatib & Rahma Asem Momani, 2023. "Supply Chain Resilience and Operational Performance: The Role of Digital Technologies in Jordanian Manufacturing Firms," Administrative Sciences, MDPI, vol. 13(2), pages 1-25, January.
    15. Gautam Dutta & Ravinder Kumar & Rahul Sindhwani & Rajesh Kr. Singh, 2021. "Digitalization priorities of quality control processes for SMEs: a conceptual study in perspective of Industry 4.0 adoption," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1679-1698, August.
    16. Han, Myat Su & Ma, Shuang (Sara) & Wang, Yonggui & Tian, Qinghong, 2023. "Impact of technology-enabled product eco-innovation: Empirical evidence from the Chinese manufacturing industry," Technovation, Elsevier, vol. 128(C).
    17. Tian, Meng & Chen, Yang & Tian, Guanghao & Huang, Wei & Hu, Chuan, 2023. "The role of digital transformation practices in the operations improvement in manufacturing firms: A practice-based view," International Journal of Production Economics, Elsevier, vol. 262(C).

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