Artificial intelligence and internet of things adoption in operations management: Barriers and benefits

Rocha, Isabela F.; Kissimoto, Kumiko O.

doi:10.1590/1678-6971/eRAMR220119.en

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Resources and Entrepreneurial Development • RAM, Rev. Adm. Mackenzie 23 (4) • 2022 • https://doi.org/10.1590/1678-6971/eRAMR220119.en copy

Artificial intelligence and internet of things adoption in operations management: Barriers and benefits

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Purpose:

Based on the context of digital transformation and the evolution of digital technologies, this research sought to understand how artificial intelligence (AI) and internet of things (IoT) collaborate to improve the efficiency of operations management (OM).

Originality/value:

Digital transformation and the use of new technologies, such as AI and IoT, have impacted the management of the companies’ operation. A preliminary survey carried out in the Web of Science (WoS) database, analyzing data through the VOSviewer bibliometric software, identified an important relationship between AI, IoT, and OM through industry 4.0 (i4.0), which has as one of its main objectives the improvement in OM. The results of this research bring a practical contribution to business managers, such as the identification of the main barriers and expected benefits when adopting AI and IoT in their operations. For researchers, this study differs from studies already published by conducting a systematic review of the literature that investigates the relationship of OM with technological tools, such as AI and IoT.

Design/methodology/approach:

A systematic review of the literature was carried out with the objective of analyzing all articles that brought some contribution to a better understanding of how AI and IoT collaborate to improve the efficiency of operations.

Findings:

The results demonstrated how AI and IoT were being incorporated into OM, identifying the main barriers of its use, as well as indications of research gaps that may lead to further investigations to advance on this topic.

Keywords:
digital technologies; digital transformation; operations management; artificial intelligence; internet of things

Database	Search strings	Articles
WoS	TS = (“Operation management” OR “operations management” OR “production management” OR “Operation* manager” OR “Production manager”) AND TS = (“digital transformation” OR “IoT” OR “AI” OR “Internet of Things” OR “Artificial Intelligence” OR “Industry 4.0” OR “I4.0” OR “Technolog* Trends” OR “Digital Trends” OR “Digital Technolog” OR “Digitali”)	401
Scopus	TITLE-ABS-KEY (“Operation management” OR “operations management” OR “production management” OR “Operation manager” OR “Production manager”) AND TITLE-ABS-KEY (“digital transformation” OR “IoT” OR “AI” OR “Internet of Things” OR “Artificial Intelligence” OR “Industry 4.0” OR “I4.0” OR “Technolog Trends” OR “Digital Trends” OR “Digital Technolog” OR “Digitali”).	1,005

	2007	2011	2017	2018	2019	2020	2021
GO ∩ IA	1	1		2	3	9	3
GO ∩ IoT			1	7	2	12
GO ∩ i4.0			1	6	4	12	2

Barriers to adopt AI and IoT	Authors
Incorrect, incomplete or non-existent data model	Venkatesh (2021)Venkatesh, V. (2021). Adoption and use of AI tools: A research agenda grounded in UTAUT. Annals of Operations Research, 308, 641–652.
Scenario changes	Venkatesh (2021)Venkatesh, V. (2021). Adoption and use of AI tools: A research agenda grounded in UTAUT. Annals of Operations Research, 308, 641–652.
It might cause uncertainity and lead to errors	Lee and Zhag (2016)Lee, C., & Zhang, S. (2016). Development of an industrial internet of things suite for smart factory towards re-industrialization in Hong Kong. 6th International Workshop of Advanced Manufacturing and Automation., Venkatesh (2021)Venkatesh, V. (2021). Adoption and use of AI tools: A research agenda grounded in UTAUT. Annals of Operations Research, 308, 641–652., and Wang et al. (2021)Wang, Y., Skeete, J.-P., & Owusu, G. (2021). Understanding the implications of artificial intelligence on field service operations: A case study of BT. Production Planning & Control, 1–17.
Internal and external resistance	Lohmer and Lasch (2020)Lohmer, J., & Lasch, R. (2020). Blockchain in operations management and manufacturing: Potential and barriers. Computers & Industrial Engineering, 149, 106789.
Technological barriers	Lohmer and Lasch (2020)Lohmer, J., & Lasch, R. (2020). Blockchain in operations management and manufacturing: Potential and barriers. Computers & Industrial Engineering, 149, 106789.
High investments	Lee and Zhang (2016)Lee, C., & Zhang, S. (2016). Development of an industrial internet of things suite for smart factory towards re-industrialization in Hong Kong. 6th International Workshop of Advanced Manufacturing and Automation. and Tortorella et al. (2019)Tortorella, G. L., Giglio, R., & Van Dun, D. H. (2019). Industry 4.0 adoption as a moderator of the impact of lean production practices on operational performance improvement. International Journal of Operations & Production Management, 39(6/7/8), 860–886.

Gaps	Future reserach opportunities	Authors
Process automation and use of AI and other digital technologies	Among all the different processes in the OM context, which of them are done routinely and could be automated?	Lohmer and Lasch (2020)Lohmer, J., & Lasch, R. (2020). Blockchain in operations management and manufacturing: Potential and barriers. Computers & Industrial Engineering, 149, 106789.
Interaction of AI and IoT tools	How can the interaction between AI and IoT and other technologies, such as blockchain in operations, contribute to the creation of new values?	Wamba and Queiroz (2020)Wamba, S. F., & Queiroz, M. M. (2020). Blockchain in the operations and supply chain management: Benefits, challenges and future research opportunities. Elsevier.
Challenges of the implementation of AI, IoT, big data, and cloud computing technologies, from the perspective of managers.	How do people and companies perceive the issue of success and failure in implementing new technologies in operation?	Kumar et al. (2018)Kumar, S., Mookerjee, V., & Shubham, A. (2018). Research in operations management and information systems interface. Production and Operations Management, 27(11), 1893–1905.
Impact of socioeconomic context on the adoption of new technologies	Expand the research on I4.0 (and its tools, such as AI and IoT) and OM in a regional way, to understand whether the socioeconomic context can affect the adoption of new technologies.	Tortorella et al. (2019)Tortorella, G. L., Giglio, R., & Van Dun, D. H. (2019). Industry 4.0 adoption as a moderator of the impact of lean production practices on operational performance improvement. International Journal of Operations & Production Management, 39(6/7/8), 860–886.
Analysis of the impacts of OM’s digitalization processes	Global research to identify similarities, differences, problems, and consequences.	Bienhaus and Haddud (2018)Bienhaus, F., & Haddud, A. (2018). Procurement 4.0: Factors influencing the digitisation of procurement and supply chains. Business Process Management Journal, 24(4), 965–984.

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[1] Correspondence concerning this article should be addressed to Kumiko O. Kissimoto, Rua Oleska Winogradow, 100, Jardim das Flores, Osasco, São Paulo, Brazil, ZIP code 06120-042. Email: kissimoto.kumiko@unifesp.br