Artificial Intelligence (AI) represents a set of techniques that enable new ways of innovation and allows firms to offer new features of products and services, to improve production, marketing and administration processes, and to introduce new business models. This paper analyses the extent to...

Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. A main feature of new general-purpose technology is to enable new ways of production that may increase productivity. So...

This paper is concerned with exploring the implications of replicability issues over the medical innovation process. Each research setting is characterized by a specific level of replicability, variability increasing with the complexity of the testing settings. The study introduces new measures...

Firms can use different sources of external knowledge for developing and implementing innovations. Some knowledge is provided deliberately by the source and constitutes intended knowledge spillovers, e.g., knowledge disclosed in publications or patent files. Other sources represent unintended...

Public financial support for firm-level Research and Innovation (R&I) can generate important socio-economic returns. This is especially true if firms use this support to develop radical innovation, defined as new-to-market goods and services. However, radical innovation is risky, and prone to...

Reverse engineering allows firms to learn about critical components and design features of competitors' technologies. Historically, reverse engineering has often been used to help technological laggards to catch-up and profit from other's inventions. However, through reverse engineering firms...

Artificial Intelligence (AI) is considered to be the next general-purpose technology, with the potential of performing tasks commonly requiring human capabilities. While it is commonly feared that AI replaces labor and disrupts jobs, we instead investigate the potential of AI for overcoming...

This paper analyzes the impact of network externalities on R&D competition between an incumbent and a potential entrant. The analysis shows that the incumbent always invests more than the entrant in the development of higher quality network goods. However, the incumbent exhibits a too low level...

This paper studies the incentives to undertake uncertain R&D initiatives in a dynamic duopoly network industry. It is shown that network externalities positively affect the incentives to invest in R&D. In the model, competition resembles a preemption race and, therefore, market performance...

We develop a model of R&D competition between an incumbent and a potential entrant with network externalities and durable goods. We show that the threat of entry eliminates the commitment problem that an incumbent may face in its R&D decision due to the goods? durability. Moreover, a potential...