Azizi, Neda and Akhavan, Peyman and Davison, Claire and Haass, Omid and Saremi, Shahrzad and Zaidi, Syed Fawad M (2025) AI-Driven Process Innovation: Transforming Service Start-Ups in the Digital Age. Electronics, 14 (16). p. 3240. DOI https://doi.org/10.3390/electronics14163240
Azizi, Neda and Akhavan, Peyman and Davison, Claire and Haass, Omid and Saremi, Shahrzad and Zaidi, Syed Fawad M (2025) AI-Driven Process Innovation: Transforming Service Start-Ups in the Digital Age. Electronics, 14 (16). p. 3240. DOI https://doi.org/10.3390/electronics14163240
Azizi, Neda and Akhavan, Peyman and Davison, Claire and Haass, Omid and Saremi, Shahrzad and Zaidi, Syed Fawad M (2025) AI-Driven Process Innovation: Transforming Service Start-Ups in the Digital Age. Electronics, 14 (16). p. 3240. DOI https://doi.org/10.3390/electronics14163240
Abstract
<jats:p>In today’s fast-moving digital economy, service start-ups are reshaping industries; however, they face intense uncertainty, limited resources, and fierce competition. This study introduces an Artificial Intelligence (AI)-powered process modeling framework designed to give these ventures a competitive edge by combining big data analytics, machine learning, and Business Process Model and Notation (BPMN). While past models often overlook the dynamic, human-centered nature of service businesses, this research fills that gap by integrating AI-Driven Ideation, AI-Augmented Content, and AI-Enabled Personalization to fuel innovation, agility, and customer-centricity. Expert insights, gathered through a two-stage fuzzy Delphi method and validated using DEMATEL, reveal how AI can transform start-up processes by offering real-time feedback, predictive risk management, and smart customization. This model does more than optimize operations; it empowers start-ups to thrive in volatile, data-rich environments, improving strategic decision-making and even health and safety governance. By blending cutting-edge AI tools with process innovation, this research contributes a fresh, scalable framework for digital-age entrepreneurship. It opens exciting new pathways for start-up founders, investors, and policymakers looking to harness AI’s full potential in transforming how new ventures operate, compete, and grow.</jats:p>
Item Type: | Article |
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Uncontrolled Keywords: | artificial intelligence; start-ups; big data analytics; business process modeling; BPMN; predictive analytics; service innovation; entrepreneurial decision-making |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School Faculty of Social Sciences > Essex Business School > Strategy, Operations and Entrepreneurship |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 19 Aug 2025 10:49 |
Last Modified: | 23 Aug 2025 00:41 |
URI: | http://repository.essex.ac.uk/id/eprint/41391 |
Available files
Filename: electronics-14-03240.pdf
Licence: Creative Commons: Attribution 4.0