Focal Firms as Technological Gatakeepers within Industrial Districts Knowledge Creation and Dissemination in the Italian Packaging Machinery Industry

Despite the diffusion of communication tools and boundary spanning technologies, knowledge flows in innovation processes retain a distinct localized nature in many industries and geographical clusters emerge as critical areas to foster technological diffusion. In this paper we focus on the role of focal firms in industrial clusters as “gatekeepers” introducing external technological novelties in the cluster and enacting new useful knowledge production locally, thus enhancing international competitive capabilities of all firms in the cluster. We analyze a longitudinal dataset of 720 patents 1 Corresponding Author www.druid.dk granted by USPTO between 1990 and 2003 to firms in the automatic packaging machinery industrial district of Emilia-Romagna in Northern Italy, and a matched-sample to control for the uneven geographical distribution of R&D and patenting activities. Our results show that firms within the cluster use local knowledge to a greater extent and more rapidly than knowledge from the outside than it would be expected given the geographic distribution of innovative activity in the industry. Moreover, focal firms use external knowledge to a greater extent than other firms operating in the cluster, and other (non focal) firms within the cluster use knowledge from focal firms to a greater extent than would be expected given the geographic distribution of innovative activity in the industry. Implications for research on the geographical distribution of innovation activities are discussed.Innovation processes, Knowledge flows, Geographical clusters

The effects of privatization on R&D investments and patent productivity

Over the last two decades privatization programs in different countries radically reduced the role of the State as a key player in the economic arena. We use agency theory to discuss the theoretical relationship between changes in the firm's principal-agent structure following privatization, and incentives to invest in R&D and to patent. We compare the pre and post privatization R&D effort and patenting behavior of 35 companies that were fully or partially privatized in 9 European countries through public share offering between 1980 and 1997. Results show that, after controlling for inter-industry differences, privatization processes negatively affect different measures of R&D commitment. Moreover, the shift from public to private ownership leads to a significant increase in the quantity of patents granted and in their quality, measured by citations' intensity

Privatization and R&D Performance: An Empirical Analysis Based on Tobin's q

In this paper, we analyze the impact of privatization on the firms' R&D performance. We expect that, in the early period after privatization, path dependencies still negatively affect the efficiency of R&D operations. We test our hypothesis using a Tobin's q measure and estimating a hedonic model, already adopted by several scholars to assess the impact of innovation related assets on the firm's market value (Griliches, 1981). We estimate the regression model on an original panel data of 40 firms, including 20 firms privatized through public share offering in different countries of Western Europe over the period 1982-1997 that were matched at the country and industry level with 20 publicly held firms. Our results show that stock markets evaluate R&D investments of newly privatized companies less than R&D investments of industry-matched companies.In this paper, we analyze the impact of privatization on the firms' R&D performance. We expect that, in the early period after privatization, path dependencies still negatively affect the efficiency of R&D operations. We test our hypothesis using a Tobin's q measure and estimating a hedonic model, already adopted by several scholars to assess the impact of innovation related assets on the firm's market value (Griliches, 1981). We estimate the regression model on an original panel data of 40 firms, including 20 firms privatized through public share offering in different countries of Western Europe over the period 1982-1997 that were matched at the country and industry level with 20 publicly held firms. Our results show that stock markets evaluate R&D investments of newly privatized companies less than R&D investments of industry-matched companies.Refereed Working Papers / of international relevanc

From 5G to 6G: Has the Time for Modern Random Access Come?

This short paper proposes the use of modern random access for IoT applications in 6G. A short overview of recent advances in uncoordinated medium access is provided, highlighting the gains that can be achieved by leveraging smart protocol design intertwined with advanced signal processing techniques at the receiver. The authors' vision on the benefits such schemes can yield for beyond-5G systems is presented, with the aim to trigger further discussion.Comment: 2 pages, 1 figure, presented at 6G Summit, Levi, Finland, 201

Grant-Free Access: Machine Learning for Detection of Short Packets

In this paper, we explore the use of machine learning methods as an efficient alternative to correlation in performing packet detection. Targeting satellite-based massive machine type communications and internet of things scenarios, our focus is on a common channel shared among a large number of terminals via a fully asynchronous ALOHA protocol to attempt delivery of short data packets. In this setup, we test the performance of two algorithms, neural networks and random forest, which are shown to provide substantial improvements over {traditional} techniques. Excellent performance is demonstrated in terms of detection and false alarm probability also in the presence of collisions among user transmissions. The ability of machine learning to extract further information from incoming signals is also studied, discussing the possibility to classify detected preambles based on the level of interference they undergo