The paper investigates how big data analysis and analytics can reshape business model design to encourage the co-development of innovation through the application of a data-driven orientation. The main objectives of the study are: (1) to detect the enabling dimensions of business models for the co-development of innovation; (2) to investigate how the enabling dimensions can be oriented strategically toward the emergence of data-driven innovation. The empirical research is based on a case study performed through qualitative content analysis to explore an Italian agrifood company, Amadori. The results obtained allow the introduction of a three-layered framework that can encourage future studies to: (1) investigate business models enablers for value co-creation and the way in which their combination can produce innovation; (2) detect the different data-oriented and management strategies that redefine business models to develop innovation systematically.
Redesigning Business Models for Data-Driven Innovation: A Three-Layered Framework
Loia F.
2021
Abstract
The paper investigates how big data analysis and analytics can reshape business model design to encourage the co-development of innovation through the application of a data-driven orientation. The main objectives of the study are: (1) to detect the enabling dimensions of business models for the co-development of innovation; (2) to investigate how the enabling dimensions can be oriented strategically toward the emergence of data-driven innovation. The empirical research is based on a case study performed through qualitative content analysis to explore an Italian agrifood company, Amadori. The results obtained allow the introduction of a three-layered framework that can encourage future studies to: (1) investigate business models enablers for value co-creation and the way in which their combination can produce innovation; (2) detect the different data-oriented and management strategies that redefine business models to develop innovation systematically.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.