Discussion on relational networks and knowledge flows from a corporate to a regional perspective

On the channels through which is encouraged the spread of knowledge coming to firms and regions from outside many research and studies have been written. The debate has considered many questions and this thesis focuses on two different paths that have in common some forms of inter-firm relationships, that are mergers and acquisitions (M&A), Joint Ventures (JV)and Strategic alliances (SA). The first study investigate the effects of international mergers and acquisitions (M&As) on the long run performance of the acquirer firm. The paper uses a dataset that cross information from two different databases on a large sample of Italian companies in order to obtain performance data of Italian firms involved in an international M&A as acquirer. The main data for our analysis are from Thomson SDC Platinum, and comprise acquisitions of international firms by Italian companies during the years 2000-2012, merged firm-level performance data from BvD Amadeus. Considering the fact that companies that expand by M&As are usually bigger than others, with the possible occurrence of selection bias caused by the absence of a valid counterfactual, we used the Propensity score matching methodology (PSM) to estimates whether there is an effect in performance of enter into an agreement. It is assumed the result is positive, even if with differences. Such a study should give deep insights into the workings of deals between companies in the Italian case, taking into account previous analysis and improve the literature with a view that include data on both cross-border and intra-national M&As. The second study investigate the factors that determine patenting performance, including relational activities. We will provide an original framework within a knowledge production function model. We focus on the role of relational networks, proxied with mergers and acquisitions, joint ventures and strategic alliances, in influencing the behaviour of local innovation systems, considering Italian provinces data (NUTS3) from 2000 to 2012. We use a variable that counts the number of joint memberships of provinces within the considered concluded agreements.