Technology acquisition through licensing. Implications for firm strategy

Nowadays licensing practices have increased in importance and relevance driving the widespread diffusion of markets for technologies. Firms are shifting from a tactical to a strategic attitude towards licensing, addressing both business and corporate level objectives. The Open Innovation Paradigm has been embraced. Firms rely more and more on collaboration and external sourcing of knowledge. This new model of innovation requires firms to leverage on external technologies to unlock the potential of firms’ internal innovative efforts. In this context, firms’ competitive advantage depends both on their ability to recognize available opportunities inside and outside their boundaries and on their readiness to exploit them in order to fuel their innovation process dynamically. Licensing is one of the ways available to firm to ripe the advantages associated to an open attitude in technology strategy. From the licensee’s point view this implies challenging the so-called not-invented-here syndrome, affecting the more traditional firms that emphasize the myth of internal research and development supremacy. This also entails understanding the so-called cognitive constraints affecting the perfect functioning of markets for technologies that are associated to the costs for the assimilation, integration and exploitation of external knowledge by recipient firms. My thesis aimed at shedding light on new interesting issues associated to in-licensing activities that have been neglected by the literature on licensing and markets for technologies. The reason for this gap is associated to the “perspective bias” affecting the works within this stream of research. With very few notable exceptions, they have been generally concerned with the investigation of the so-called licensing dilemma of the licensor – whether to license out or to internally exploit the in-house developed technologies, while neglecting the licensee’s perspective. In my opinion, this has left rooms for improving the understanding of the determinants and conditions affecting licensing-in practices. From the licensee’s viewpoint, the licensing strategy deals with the search, integration, assimilation, exploitation of external technologies. As such it lies at the very hearth of firm’s technology strategy. Improving our understanding of this strategy is thus required to assess the full implications of in-licensing decisions as they shape firms’ innovation patterns and technological capabilities evolution. It also allow for understanding the so-called cognitive constraints associated to the not-invented-here syndrome. In recognition of that, the aim of my work is to contribute to the theoretical and empirical literature explaining the determinants of the licensee’s behavior, by providing a comprehensive theoretical framework as well as ad-hoc conceptual tools to understand and overcome frictions and to ease the achievement of satisfactory technology transfer agreements in the marketplace. Aiming at this, I investigate licensing-in in three different fashions developed in three research papers. In the first work, I investigate the links between licensing and the patterns of firms’ technological search diversification according to the framework of references of the Search literature, Resource-based Theory and the theory of general purpose technologies. In the second paper - that continues where the first one left off – I analyze the new concept of learning-bylicensing, in terms of development of new knowledge inside the licensee firms (e.g. new patents) some years after the acquisition of the license, according to the Dynamic Capabilities perspective. Finally, in the third study, Ideal with the determinants of the remuneration structure of patent licenses (form and amount), and in particular on the role of the upfront fee from the licensee’s perspective. Aiming at this, I combine the insights of two theoretical approaches: agency and real options theory.

Gli assetti proprietari e di controllo nell'agroalimentare italiano

The recent default of important Italian agri-business companies provides a challenging issue to be investigated through an appropriate scientific approach. The events involving CIRIO, FERRUZZI or PARMALAT rise an important research question: what are the determinants of performance for Italian companies in the Italian agri – food sector? My aim is not to investigate all the factors that are relevant in explaining performance. Performance depends on a wide set of political, social, economic variables that are strongly interconnected and that are often very difficult to express by formal or mathematical tools. Rather, in my thesis I mainly focus on those aspects that are strictly related to the governance and ownership structure of agri – food companies representing a strand of research that has been quite neglected by previous scholars. The conceptual framework from which I move to justify the existence of a relationship between the ownership structure of a company, governance and performance is the model set up by Airoldi and Zattoni (2005). In particular the authors investigate the existence of complex relationships arising within the company and between the company and the environment that can bring different strategies and performances. They do not try to find the “best” ownership structure, rather they outline what variables are connected and how they could vary endogenously within the whole economic system. In spite of the fact that the Airoldi and Zattoni’s model highlights the existence of a relationship between ownership and structure that is crucial for the set up of the thesis the authors fail to apply quantitative analyses in order to verify the magnitude, sign and the causal direction of the impact. In order to fill this gap we start from the literature trying to investigate the determinants of performance. Even in this strand of research studies analysing the relationship between different forms of ownership and performance are still lacking. In this thesis, after a brief description of the Italian agri – food sector and after an introduction including a short explanation of the definitions of performance and ownership structure, I implement a model in which the performance level (interpreted here as Return on Investments and Return on Sales) is related to variables that have been previously identified by the literature as important such as the financial variables (cash and leverage indices), the firm location (North Italy, Centre Italy, South Italy), the power concentration (lower than 25%, between 25% and 50% and between 50% and 100% of ownership control) and the specific agri – food sector (agriculture, food and beverage). Moreover we add a categorical variable representing different forms of ownership structure (public limited company, limited liability company, cooperative) that is the core of our study. All those variables are fully analysed by a preliminary descriptive analysis. As in many previous contributions we apply a panel least squares analysis for 199 Italian firms in the period 1998 – 2007 with data taken from the Bureau Van Dijck Dataset. We apply two different models in which the dependant variables are respectively the Return on Investments (ROI) and the Return on Sales (ROS) indicators. Not surprisingly we find that companies located in the North Italy representing the richest area in Italy perform better than the ones located in the Centre and South of Italy. In contrast with the Modigliani - Miller theorem financial variables could be significant and the specific sector within the agri – food market could play a relevant role. As the power concentration, we find that a strong property control (higher than 50%) or a fragmented concentration (lower than 25%) perform better. This result apparently could suggest that “hybrid” forms of concentrations could create bad functioning in the decision process. As our key variables representing the ownership structure we find that public limited companies and limited liability companies perform better than cooperatives. This is easily explainable by the fact that law establishes that cooperatives are less profit – oriented. Beyond cooperatives public limited companies perform better than limited liability companies and show a more stable path over time. Results are quite consistent when we consider both ROI and ROS as dependant variables. These results should not lead us to claim that public limited company is the “best” among all possible governance structures. First, every governance solution should be considered according to specific situations. Second more robustness analyses are needed to confirm our results. At this stage we deem these findings, the model set up and our approach represent original contributions that could stimulate fruitful future studies aimed at investigating the intriguing issue concerning the effect of ownership structure on the performance levels.

Strategy as a matter of beliefs: the recorded music industry reinventing itself by rethinking itself

Managerial and organizational cognition studies the ways cognitions of managers in groups, organizations and industries shape their strategies and actions. Cognitions refer to simplified representations of managers’ internal and external environments, necessary to cope with the rich, ambiguous information requirements that characterize strategy making. Despite the important achievements in the field, many unresolved puzzles remain as to this process, particular as to the cognitive factors that condition actors in framing a response to a discontinuity, how actors can change their models in the face of a discontinuity, and the reciprocal relation between cognition and action. I leverage on the recent case of the recorded music industry in the face of the digital technology to study these issues, through a strategy-oriented study of the way early response to the discontinuity was constructed and of the subsequent evolution of this response. Through a longitudinal historical and cognitive analysis of actions and cognitions at both the industry and firm-level during the period in which the response took place (1999-2010), I gain important insights on the way historical beliefs in the industry shaped early response to the digital disruption, on the role of outsiders in promoting change through renewed vision about important issues, and on the reciprocal relationship between cognitive and strategic change.

The impact of R&D in firm value across Europe

In this thesis the impact of R&D expenditures on firm market value and stock returns is examined. This is performed in a sample of European listed firms for the period 2000-2009. I apply different linear and GMM econometric estimations for testing the impact of R&D on market prices and construct country portfolios based on firms’ R&D expenditure to market capitalization ratio for studying the effect of R&D on stock returns. The results confirm that more innovative firms have a better market valuation,investors consider R&D as an asset that produces long-term benefits for corporations. The impact of R&D on firm value differs across countries. It is significantly modulated by the financial and legal environment where firms operate. Other firm and industry characteristics seem to play a determinant role when investors value R&D. First, only larger firms with lower financial leverage that operate in highly innovative sectors decide to disclose their R&D investment. Second, the markets assign a premium to small firms, which operate in hi-tech sectors compared to larger enterprises for low-tech industries. On the other hand, I provide empirical evidence indicating that generally highly R&D-intensive firms may enhance mispricing problems related to firm valuation. As R&D contributes to the estimation of future stock returns, portfolios that comprise high R&D-intensive stocks may earn significant excess returns compared to the less innovative after controlling for size and book-to-market risk. Further, the most innovative firms are generally more risky in terms of stock volatility but not systematically more risky than low-tech firms. Firms that operate in Continental Europe suffer more mispricing compared to Anglo-Saxon peers but the former are less volatile, other things being equal. The sectors where firms operate are determinant even for the impact of R&D on stock returns; this effect is much stronger in hi-tech industries.

La ricerca del valore nell'impresa cooperativa di lavorazione e trasformazione: cooperative e imprese capitalistiche a confronto

La ricerca si propone un duplice obbiettivo: 1. provare, attraverso l’applicazione di un metodo teorico tradizionale di analisi economico-finanziaria, il livello ottimale di equilibrio finanziario fra accesso al credito esterno e capitale proprio; 2. mostrare l’utilità di alcuni strumenti finanziari partecipativi per la ricapitalizzazione dell’impresa cooperativa. Oggetto di studio è l’impresa cooperativa che si occupa di una o più fasi del processo di lavorazione, trasformazione e prima commercializzazione del prodotto agricolo conferito dai soci, confrontata con le imprese di capitali che svolgono la medesima attività. La società cooperativa e quella capitalistica saranno, pertanto analizzate in termini di liquidità generata, redditività prodotta e grado di indebitamento, attraverso il calcolo e l’analisi di una serie di indici, tratti dai rispettivi bilanci d’esercizio. È opportuno sottolineare che nella seguente trattazione sarà riservato uno spazio al tema della ricerca del valore nell’impresa cooperativa inteso come espressione della ricchezza creata dai processi aziendali in un determinato periodo di tempo tentando di definire, se esiste, una struttura finanziaria ottimale , ossia uno specifico rapporto tra indebitamento finanziario e mezzi propri, che massimizzi il valore dell’impresa. L’attenzione verso la struttura finanziaria, pertanto, non sarà solo rivolta al costo esplicito del debito o dell’equity, ma si estenderà anche alle implicazioni delle scelte di finanziamento sulle modalità di governo dell’impresa. Infatti molti studi di economia aziendale, e in particolar modo di gestione d’impresa e finanza aziendale, hanno trattato il tema dell’attività di governo dell’impresa, quale elemento in grado di contribuire alla creazione di valore non solo attraverso la selezione dei progetti d’investimento ma anche attraverso la composizione della struttura finanziaria.

The Law and Economics of Hedge Fund Regulation: A Comparison between the U.S. and the EU

This doctoral dissertation seeks to assess and address the potential contribution of the hedge fund industry to financial instability. In so doing, the dissertation investigates three main questions. What are the contributions of hedge funds to financial instability? What is the optimal regulatory strategy to address the potential contribution of hedge funds to financial instability? And do new regulations in the U.S. and the EU address the contribution of hedge funds to financial instability? With respect to financial stability concerns, it is argued that despite their benefits, hedge funds can contribute to financial instability. Hedge funds’ size and leverage, their interconnectedness with Large Complex Financial Institutions (LCFIs), and the likelihood of herding behavior in the industry can potentially undermine financial stability. Nonetheless, the data on hedge funds’ size and leverage suggest that these features are far from being systemically important. In contrast, the empirical evidence on the interconnectedness of hedge funds with LCFIs and their herding behavior is mixed. Based on these findings, the thesis focuses on one particular aspect of hedge fund regulation: direct vs. indirect regulation. In this respect, a major contribution of the thesis to the literature consists in the explicit discussion of the relationships between hedge funds and other market participants. Specifically, the thesis locates the domain of the indirect regulation in the inter-linkages between hedge funds and prime brokers. Accordingly, the thesis argues that the indirect regulation is likely to address the contribution of hedge funds to systemic risk without compromising their benefits to financial markets. The thesis further conducts a comparative study of the regulatory responses to the potential contribution of hedge funds to financial instability through studying the EU Directive on Alternative Investment Fund Managers (AIFMD) and the hedge fund-related provisions of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010.

Matrix Designs and Methods for Secure and Efficient Compressed Sensing

The idea of balancing the resources spent in the acquisition and encoding of natural signals strictly to their intrinsic information content has interested nearly a decade of research under the name of compressed sensing. In this doctoral dissertation we develop some extensions and improvements upon this technique's foundations, by modifying the random sensing matrices on which the signals of interest are projected to achieve different objectives. Firstly, we propose two methods for the adaptation of sensing matrix ensembles to the second-order moments of natural signals. These techniques leverage the maximisation of different proxies for the quantity of information acquired by compressed sensing, and are efficiently applied in the encoding of electrocardiographic tracks with minimum-complexity digital hardware. Secondly, we focus on the possibility of using compressed sensing as a method to provide a partial, yet cryptanalysis-resistant form of encryption; in this context, we show how a random matrix generation strategy with a controlled amount of perturbations can be used to distinguish between multiple user classes with different quality of access to the encrypted information content. Finally, we explore the application of compressed sensing in the design of a multispectral imager, by implementing an optical scheme that entails a coded aperture array and Fabry-Pérot spectral filters. The signal recoveries obtained by processing real-world measurements show promising results, that leave room for an improvement of the sensing matrix calibration problem in the devised imager.

Engineering Complex Computational Ecosystems

Self-organising pervasive ecosystems of devices are set to become a major vehicle for delivering infrastructure and end-user services. The inherent complexity of such systems poses new challenges to those who want to dominate it by applying the principles of engineering. The recent growth in number and distribution of devices with decent computational and communicational abilities, that suddenly accelerated with the massive diffusion of smartphones and tablets, is delivering a world with a much higher density of devices in space. Also, communication technologies seem to be focussing on short-range device-to-device (P2P) interactions, with technologies such as Bluetooth and Near-Field Communication gaining greater adoption. Locality and situatedness become key to providing the best possible experience to users, and the classic model of a centralised, enormously powerful server gathering and processing data becomes less and less efficient with device density. Accomplishing complex global tasks without a centralised controller responsible of aggregating data, however, is a challenging task. In particular, there is a local-to-global issue that makes the application of engineering principles challenging at least: designing device-local programs that, through interaction, guarantee a certain global service level. In this thesis, we first analyse the state of the art in coordination systems, then motivate the work by describing the main issues of pre-existing tools and practices and identifying the improvements that would benefit the design of such complex software ecosystems. The contribution can be divided in three main branches. First, we introduce a novel simulation toolchain for pervasive ecosystems, designed for allowing good expressiveness still retaining high performance. Second, we leverage existing coordination models and patterns in order to create new spatial structures. Third, we introduce a novel language, based on the existing ``Field Calculus'' and integrated with the aforementioned toolchain, designed to be usable for practical aggregate programming.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.