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.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system

Modern control systems are becoming more and more complex and control algorithms more and more sophisticated. Consequently, Fault Detection and Diagnosis (FDD) and Fault Tolerant Control (FTC) have gained central importance over the past decades, due to the increasing requirements of availability, cost efficiency, reliability and operating safety. This thesis deals with the FDD and FTC problems in a spacecraft Attitude Determination and Control System (ADCS). Firstly, the detailed nonlinear models of the spacecraft attitude dynamics and kinematics are described, along with the dynamic models of the actuators and main external disturbance sources. The considered ADCS is composed of an array of four redundant reaction wheels. A set of sensors provides satellite angular velocity, attitude and flywheel spin rate information. Then, general overviews of the Fault Detection and Isolation (FDI), Fault Estimation (FE) and Fault Tolerant Control (FTC) problems are presented, and the design and implementation of a novel diagnosis system is described. The system consists of a FDI module composed of properly organized model-based residual filters, exploiting the available input and output information for the detection and localization of an occurred fault. A proper fault mapping procedure and the nonlinear geometric approach are exploited to design residual filters explicitly decoupled from the external aerodynamic disturbance and sensitive to specific sets of faults. The subsequent use of suitable adaptive FE algorithms, based on the exploitation of radial basis function neural networks, allows to obtain accurate fault estimations. Finally, this estimation is actively exploited in a FTC scheme to achieve a suitable fault accommodation and guarantee the desired control performances. A standard sliding mode controller is implemented for attitude stabilization and control. Several simulation results are given to highlight the performances of the overall designed system in case of different types of faults affecting the ADCS actuators and sensors.