Critical analysis of the impact of artificial intelligence integration with cutting-edge technologies for production systems
Open accessAbstract
Scientific research on emerging technologies underscored the advantages of their implementation within production systems, with a particular focus on artificial intelligence (AI). In particular, the integration of AI with other cutting-edge technologies is a relevant topic which can potentially lead to huge impacts in terms of business performance. Yet, literature on the subject, although rich, is still fragmented, limited to specific cases and applications, but lacking in a comprehensive classification framework. Therefore, using a systematic literature review, this study provides an overview of how the combination of AI and other cutting-edge technologies could potentially improve market and organisational performance in business functions and processes. By classifying the literature of case studies and real-world applications into specific taxonomies, the research considers an indicator, the co-occurrence ratio, highlighting the most significant and emerging combinations between AI and other cutting-edge technologies, also specifying the contexts in which they are used. The study shows that AI is strongly interconnected with other cutting-edge technologies, suggesting a research agenda in which the integration of AI with other emerging technologies is promising within specific production systems contexts, providing benefits and opportunities for companies.
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Under challenging environmental circumstances, hybrid MCDM-blockchain models support operational resilience, strategic alignment, and risk reduction.
“Under challenging environmental circumstances, these models support operational resilience, strategic alignment and risk reduction71–74.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [73]
Recent research supports the importance of combining cutting-edge decision-making frameworks with new technology to improve sustainability performance, consistent with the study's findings.
“Recent research supports the importance of combining cutting-edge decision-making frameworks with new technology to improve sustainability performance, which is consistent with the study’s findings.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [73]
Hybrid strategies combining MCDM under uncertainty with blockchain technology have proven beneficial in resolving implementation issues in sustainable supply chains and renewable energy.
“Particularly, hybrid strategies that combine MCDM under uncertainty with blockchain technology have proven to be very beneficial in resolving implementation issues in sustainable supply chains and renewable energy.”
From A decision-support framework for evaluating AI-enabled ESG strategies in the context of sustainable manufacturing systems (2025) · cites this paper as [73]
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References 178 · Cited by 79
Research works printed but not linked: 1
- Zhao, L., Sun, S., Kong, Q., & Wang, X. (2009). Food traceability system based on iris recognition middleware. ICIC Express Letters, 3, 1251-1256.
- Authors
- Varriale, V., Cammarano, A., Michelino, F., & Caputo, M.
- Affiliations
- University of Salerno (IT)
- Corresponding author
- Varriale, Vincenzo
- Venue
- Journal of Intelligent Manufacturing
- Published
- 2023-11-13
- Volume
- 36
- Issue
- 1
- Pages
- 61-93
- ISSN
- 0956-5515 (ISSN-L)
- 1572-8145
- OpenAlex
- W4388651791
- Cited by
- 79
- References
- 178
- Citations by year
- 2026: 24 · 2025: 40 · 2024: 15
- FWCI
- 14.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Intelligent Manufacturing (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Università degli Studi di Salerno
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence, emerging technologies, production systems, technology integration, firm performance, organizational performance, market performance, technology taxonomy, manufacturing industry
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