Manufacturing SMEs and Artificial Intelligence: Between Promises and Paradoxes

Author:

Ravarini AurelioORCID,Zaghloul FatemaORCID,Strada Emanuele

Publisher

Springer Nature Switzerland

Reference39 articles.

1. Zeba, G., Dabić, M., Čičak, M., Daim, T., & Yalcin, H. (2021). Technology mining: Artificial intelligence in manufacturing. Technological Forecasting and Social Change, 171.

2. Coombs, C., Hislop, D., Taneva, S. K., & Barnard, S. (2020). The strategic impacts of Intelligent Automation for knowledge and service work: An interdisciplinary review. The Journal of Strategic Information Systems, 29(4), 1–30.

3. Sharma, M., Luthra, S., Joshi, S., & Kumar, A. (2022). Implementing challenges of artificial intelligence: Evidence from public manufacturing sector of an emerging economy. Government Information Quarterly, 39(4), 101624.

4. Mittal, N., Saif, I., & Silverglate, P. (2020, 07). Deloitte survey: State of AI in the enterprise, third edition: Thriving in the era of pervasive AI. Retrieved from https://www2.deloitte.com/us/en/pages/about-deloitte/articles/press-releases/deloitte-survey-state-of-ai-in-the-enterprise-third-edition.html

5. Awalegaonkar, K., Berkey, R., Douglass, G., & Reilly, A. (2019). AI: Fatta Per Scalare. Retrieved from https://www.accenture.com/it-it/insights/artificial-intelligence/ai-investments

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