Transforming Value Delivery: A Product Operating Model for Digital Innovation and Competitive Advantage

Riti Raul Ionut (), Dresan Pop Cristina Terezia (), Năstăsoiu Ioana-Alexandra () and Bacali Laura ()
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Riti Raul Ionut: Technical University of Cluj-Napoca, Cluj, Romania
Dresan Pop Cristina Terezia: Technical University of Cluj-Napoca, Cluj, Romania
Năstăsoiu Ioana-Alexandra: Technical University of Cluj-Napoca, Cluj, Romania
Bacali Laura: Technical University of Cluj-Napoca, Cluj, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 4161-4172

Abstract: Advances and innovations in servicing technologies have changed operational and organizational systems from long-structured bureaucratic systems to more flexible and customer-oriented product systems. Although prior research has investigated technologies supporting activities and using the Agile frames, the knowledge deficits in driving the restoration of organizational value creation systems have not been adequately filled. This paper fills these gaps by presenting a comprehensive product operating model that shows innovation, scalability, and customer value proposition. Using WHO, WHAT, and HOW, the study divides work and design approaches regarding customer-oriented product and service delivery. Arguing from theory and grounding the findings in case organizational examples in Amazon and Spotify, the study shows how technology enablers such as artificial intelligence, business analytics, and real-time monitoring facilitate decision-making and operations agility. The results present practical implications for scholars and industry professionals based on a curriculum that integrates theory and practice for digital innovation. This study provides the basis for sustaining competitive advantage in the dynamic environment by offering organizations a sound, flexible, and proliferative model.

Keywords: business-oriented product operating models; digitization; organizational innovation and improvement; practical methodologies; customer orientation; technologies; business analytics (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:4161-4172:n:1038

DOI: 10.2478/picbe-2025-0319

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