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Innovation Analytics and Digital Innovation Experimentation: The Rise of Research-driven Online Review Platforms.

Authors :
Mariani, Marcello M.
Nambisan, Satish
Source :
Technological Forecasting & Social Change; Nov2021, Vol. 172, pN.PAG-N.PAG, 1p
Publication Year :
2021

Abstract

• Develops a typology of online review platforms (ORPs). • Describes Research-driven online review platform (RORP). • RORPs combine digital experimentation with AI-based big data analytics capabilities. • RORPs generate novel innovation insights through digital innovation experimentation. • RORPs operate and deliver value through innovation analytics. Big data analytics constitute one of the driving forces of the fourth industrial revolution and represent one of the founding pillars of Industry 4.0. They are increasingly leveraged to create business insights from online reviews of products and services by a wide range of organizations and firms. In this work, we develop a typology of online review platforms (ORPs) and describe a novel platform, research-driven online review platform (RORP), that combines the science and rigor of very large-scale, low-cost, fast-paced, and complex digital experimentation using real-world customers on digital platforms with the power of modern AI-based big data analytics capabilities (BDAC) to generate novel innovation insights for the digital age. Using multiple real-world case studies, we illustrate how RORPs operate and deliver value through innovation analytics, and serve as a powerful tool for digital innovation experimentation, enabling firms to innovate more effectively and transform their business models to adapt to rapidly changing market conditions. We shed light on the BDAC requirements, as well as the benefits and challenges of using RORPs and innovation analytics, particularly in the post-COVID-19 world, and offer strategic and operational implications for entrepreneurs and innovation managers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00401625
Volume :
172
Database :
Supplemental Index
Journal :
Technological Forecasting & Social Change
Publication Type :
Academic Journal
Accession number :
152649728
Full Text :
https://doi.org/10.1016/j.techfore.2021.121009