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The improvements in connectivity, artificial intelligence, and automation and their increasing penetration into all aspects of society and economy require informed decisions based on rigorous research on the determinants and outcomes of the digital economy. This context has promoted policy incentives dedicated to the digital transformation of business models and societal settings with a potential to disrupt existing markets and form a backbone of future development. The interest in digital economy and the research domains strongly connected to it has generated a wide array of terms that created confusion over its theoretical foundations. Several bibliometric analyses in recent years have attempted to map scientific findings and provide guidelines for future research in this area. However, such analyses draw their conclusions from algorithms that focus on attributes common to all studies without looking at their content. Our study combines bibliometric and in-depth content analyses to shed light on the definition, theoretical underpinnings, and state of the art of research on the digital economy. Our findings show that research in this domain is still in its infancy and the stated focus of studies on digital economy is often not reflected in their content. The study design allows us to make an original contribution by more precisely identifying gaps in the existing knowledge, outlining a detailed research agenda, and providing guidelines for future studies as well as informed policy decisions based on rigorous research on the determinants and outcomes of the digital economy.

The improvements in connectivity, artificial intelligence, and automation and their increasing penetration into all aspects of society and economy require informed decisions based on rigorous research on the determinants and outcomes of the digital economy. This context has promoted policy incentives dedicated to the digital transformation of business models and societal settings with a potential to disrupt existing markets and form a backbone of future development. The interest in digital economy and the research domains strongly connected to it has generated a wide array of terms that created confusion over its theoretical foundations. Several bibliometric analyses in recent years have attempted to map scientific findings and provide guidelines for future research in this area. However, such analyses draw their conclusions from algorithms that focus on attributes common to all studies without looking at their content. Our study combines bibliometric and in-depth content analyses to shed light on the definition, theoretical underpinnings, and state of the art of research on the digital economy. Our findings show that research in this domain is still in its infancy and the stated focus of studies on digital economy is often not reflected in their content. The study design allows us to make an original contribution by more precisely identifying gaps in the existing knowledge, outlining a detailed research agenda, and providing guidelines for future studies as well as informed policy decisions based on rigorous research on the determinants and outcomes of the digital economy. [ABSTRACT FROM AUTHOR]

Digital platforms have the ability to connect people, organizations and resources with the aim of facilitating the core interactions between businesses and consumers as well as assuring a greater efficiency for the business management. New business concepts, such as innovative start-ups, are therefore created based on innovation, scalability and the relationships within the community around them. The purpose of this work is to deeply understand the evolution of business models brought by innovative and dynamic companies operating through online platforms. In order to achieve the objectives set, an exploratory multiple-case study was designed based on in-depth structured interviews. The aim was to conduct a mixed analysis, in order to rely both on qualitative and quantitative data. The structured interview protocol was therefore designed to collect and then analyse data concerning the company profile and managers’ perspectives on the phenomenon of interest. The interview protocol was submitted in advance and then face-to-face interviews were carried out with the following professional figures: Chief Executive Officer (CEO), General Manager, Chief Technology Officer (CTO), Marketing Manager and Developers. Collected data were analysed and processed through the Canvas Business Model in order to clearly outline similarities and differences among the sample. Results can be considered under two viewpoints. On the one hand, this work provides a detailed overview of the companies interviewed, according to the dimensions of: reference market dynamics, type and number of customers, scalability. On the other one, they allow to identify some success patterns regarding key activities, key resources, channel mix strategy, costs management, value proposition, customer segmentation, key partners and the way to obtain revenues. Results from the multiple-case study with 15 Italian start-ups provide interesting insights by comparing the innovative business models developed and highlighting key differences and similarities. Overall, the start-ups analyzed, operating in several sectors, showed great growth prospects and the possibility to create value for their customers through innovative products and services offered through digital platforms.