The Impact Of Inward Licensing On New Venture’s Performance. Is inward licensing a winning strategy?

The original idea of the thesis draws on interrelated assumptions: 1) among the tools used, in the markets for technology, for the acquisition of external knowledge, the licensing agreements are acknowledged as one of the most important contractual mechanisms; 2) the liabilities of newness and the liabilities of smallness force new venture to strongly rely on external knowledge sources. Albeit the relevance of this topic, little attention has been paid so far to its investigation, especially in the licensing context; 3) nowadays there is an increasing trend in licensing practices, but the literature on markets for technology focuses almost exclusively on the incentives and rationales that foster firms’ decisions to trade their technologies, under-investigating the role of the acquiring firm, the licensee, overlooking the demand side of the market. Therefore, the thesis investigates the inward licensing phenomenon within the context of new ventures. The main questions that new venture licensee has to address if it decides to undertake an inward licensing strategy, can be summarized as follows: 1) Is convenient for a new venture to choose, as initial technology strategy, the implementation of an inward licensing ? 2) Does this decision affect its survival probabilities? 3) Does the age, at which a new venture becomes a licensee, affect its innovative capabilities? Is it better to undertake a licensing-in strategy soon after founding or to postpone this strategy until the new venture has accumulated significant resources? The findings suggest that new ventures licensees survive less than their non-licensee counterparts; the survival rates are directly connected to the time taken by firms to reach the market;being engaged in licensing-in deals some years after its inception allows a new venture licensee to increase its subsequent capacity to produce innovations.

Corporate Venture Capital: How established firms use external resources to create new competencies

This Doctoral Dissertation is triggered by an emergent trend: firms are increasingly referring to investments in corporate venture capital (CVC) as means to create new competencies and foster the search for competitive advantage through the use of external resources. CVC is generally defined as the practice by non-financial firms of placing equity investments in entrepreneurial companies. Thus, CVC can be interpreted (i) as a key component of corporate entrepreneurship - acts of organizational creation, renewal, or innovation that occur within or outside an existing organization– and (ii) as a particular form of venture capital (VC) investment where the investor is not a traditional and financial institution, but an established corporation. My Dissertation, thus, simultaneously refers to two streams of research: corporate strategy and venture capital. In particular, I directed my attention to three topics of particular relevance for better understanding the role of CVC. In the first study, I moved from the consideration that competitive environments with rapid technological changes increasingly force established corporations to access knowledge from external sources. Firms, thus, extensively engage in external business development activities through different forms of collaboration with partners. While the underlying process common to these mechanisms is one of knowledge access, they are substantially different. The aim of the first study is to figure out how corporations choose among CVC, alliance, joint venture and acquisition. I addressed this issue adopting a multi-theoretical framework where the resource-based view and real options theory are integrated. While the first study mainly looked into the use of external resources for corporate growth, in the second work, I combined an internal and an external perspective to figure out the relationship between CVC investments (exploiting external resources) and a more traditional strategy to create competitive advantage, that is, corporate diversification (based on internal resources). Adopting an explorative lens, I investigated how these different modes to renew corporate current capabilities interact to each other. More precisely, is CVC complementary or substitute to corporate diversification? Finally, the third study focused on the more general field of VC to investigate (i) how VC firms evaluate the patent portfolios of their potential investee companies and (ii) whether the ability to evaluate technology and intellectual property varies depending on the type of investors, in particular for what concern the distinction between specialized versus generalist VCs and independent versus corporate VCs. This topic is motivated by two observations. First, it is not clear yet which determinants of patent value are primarily considered by VCs in their investment decisions. Second, VCs are not all alike in terms of technological experiences and these differences need to be taken into account.

Rag2-/-;gammac-/- immunodeficient mice, a new preclinical model to study antitumor approaches

Animal models have been relevant to study the molecular mechanisms of cancer and to develop new antitumor agents. Anyway, the huge divergence in mouse and human evolution made difficult the translation of the gained achievements in preclinical mouse based studies. The generation of clinically relevant murine models requires their humanization both concerning the creation of transgenic models and the generation of humanized mice in which to engraft a functional human immune system, and reproduce the physiological effects and molecular mechanisms of growth and metastasization of human tumors. In particular, the availability of genotypically stable immunodepressed mice able to accept tumor injection and allow human tumor growth and metastasization would be important to develop anti-tumor and anti-metastatic strategies. Recently, Rag2-/-;gammac-/- mice, double knockout for genes involved in lymphocyte differentiation, had been developed (CIEA, Central Institute for Experimental Animals, Kawasaki, Japan). Studies of human sarcoma metastasization in Rag2-/-; gammac-/- mice (lacking B, T and NK functionality) revealed their high metastatic efficiency and allowed the expression of human metastatic phenotypes not detectable in the conventionally used nude murine model. In vitro analysis to investigate the molecular mechanisms involved in the specific pattern of human sarcomas metastasization revealed the importance of liver-produced growth and motility factors, in particular the insulin-like growth factors (IGFs). The involvement of this growth factor was then demonstrated in vivo through inhibition of IGF signalling pathway. Due to the high growth and metastatic propensity of tumor cells, Rag2-/-;gammac-/- mice were used as model to investigate the metastatic behavior of rhabdomyosarcoma cells engineered to improve the differentiation. It has been recently shown that this immunodeficient model can be reconstituted with a human immune system through the injection of human cord blood progenitor cells. The work illustrated in this thesis revealed that the injection of different human progenitor cells (CD34+ or CD133+) showed peculiar engraftment and differentiation abilities. Experiments of cell vaccination were performed to investigate the functionality of the engrafted human immune system and the induction of specific human immune responses. Results from such experiments will allow to collect informations about human immune responses activated during cell vaccination and to define the best reconstitution and experimental conditions to create a humanized model in which to study, in a preclinical setting, immunological antitumor strategies.

Entrepreneurial opportunities, capability development and the performance of new firms

This study aims at providing a theoretical framework encompassing the two approaches towards entrepreneurial opportunity (opportunity discovery and opportunity creation) by outlining a trajectory from firm creation to capability development, to firm performance in the short term (firm survival) and the medium/long term (growth rate). A set of empirically testable hypotheses is proposed and tested by performing qualitative analyses on interviews on a small sample of entrepreneurs and event history analysis on a large sample of firms founded in the United States in 2004.

Identity dynamics and the emergence of new organizational arrangements: A multi-level study

Organizational and institutional scholars have advocated the need to examine how processes originating at an individual level can change organizations or even create new organizational arrangements able to affect institutional dynamics (Chreim et al., 2007; Powell & Colyvas, 2008; Smets et al., 2012). Conversely, research on identity work has mainly investigated the different ways individuals can modify the boundaries of their work in actual occupations, thus paying particular attention to ‘internal’ self-crafting (e.g. Wrzesniewski & Dutton, 2001). Drawing from literatures on possible and alternative self and on positive organizational scholarship (e.g., Obodaru, 2012; Roberts & Dutton, 2009), my argument is that individuals’ identity work can go well beyond the boundaries of internal self-crafting to the creation of new organizational arrangements. In this contribution I analyze, through multiple case studies, healthcare professionals who spontaneously participated in the creation of new organizational arrangements, namely health structures called Community Hospitals. The contribution develops this form of identity work by building a grounded model. My findings disclose the process that leads from the search for the enactment of different self-concepts to positive identities, through the creation of a new organizational arrangement. I contend that this is a particularly complex form of collective identity work because it requires, to be successful, concerted actions of several internal, external and institutional actors, and it also requires balanced tensions that – at the same time - enable individuals’ aspirations and organizational equilibrium. I name this process organizational collective crafting. Moreover I inquire the role of context in supporting the triggering power of those unrealized selves. I contribute to the comprehension of the consequences of self-comparisons, organizational identity variance, and positive identity. The study bears important insights on how identity work originating from individuals can influence organizational outcomes and larger social systems.

A new 3D modelling paradigm for discrete model

Until few years ago, 3D modelling was a topic confined into a professional environment. Nowadays technological innovations, the 3D printer among all, have attracted novice users to this application field. This sudden breakthrough was not supported by adequate software solutions. The 3D editing tools currently available do not assist the non-expert user during the various stages of generation, interaction and manipulation of 3D virtual models. This is mainly due to the current paradigm that is largely supported by two-dimensional input/output devices and strongly affected by obvious geometrical constraints. We have identified three main phases that characterize the creation and management of 3D virtual models. We investigated these directions evaluating and simplifying the classic editing techniques in order to propose more natural and intuitive tools in a pure 3D modelling environment. In particular, we focused on freehand sketch-based modelling to create 3D virtual models, interaction and navigation in a 3D modelling environment and advanced editing tools for free-form deformation and objects composition. To pursuing these goals we wondered how new gesture-based interaction technologies can be successfully employed in a 3D modelling environments, how we could improve the depth perception and the interaction in 3D environments and which operations could be developed to simplify the classical virtual models editing paradigm. Our main aims were to propose a set of solutions with which a common user can realize an idea in a 3D virtual model, drawing in the air just as he would on paper. Moreover, we tried to use gestures and mid-air movements to explore and interact in 3D virtual environment, and we studied simple and effective 3D form transformations. The work was carried out adopting the discrete representation of the models, thanks to its intuitiveness, but especially because it is full of open challenges.

The United Nations 'quasi-prosecutorial' investigative mechanisms: assessing a new institutional model in the international criminal justice landscape

This work aims to provide a theoretical examination of three recently created bodies of the United Nations mandated to investigate the alleged international crimes committed in Syria (IIIM), Iraq (UNITAD) and Myanmar (IIMM). Established as a compromise solution in the paralysis of international criminal jurisdictions, these essentially overlapping entities have been depicted as a ‘new generation’ of UN investigative mechanisms. While non-judicial in nature, they depart indeed from traditional commissions of inquiry in several respects due to their increased criminal or ‘quasi-prosecutorial’ character. After clarifying their legal basis and different mandating authorities, a comparative institutional analysis is thus carried out in order to ascertain whether these ‘mechanisms’ can be said to effectively represent a new institutional model. Through an in-depth assessment of their mandates, the thesis is also intended to outline both the strengths and the criticalities of these organs. Given their aim to facilitate criminal proceedings by sharing information and case files, it is suggested that more attention shall be paid to the position of the person under investigation. To this end, some proposals are made in order to enhance the mechanisms’ frameworks, especially from the angle of procedural safeguards. As a third aspect, the cooperation with judicial authorities is explored, in order to shed light on the actors involved, the relevant legal instruments and the possible obstacles, in particular from a human rights perspective. Ultimately, drawing from the detected issues, the thesis seeks to identify some lessons learned which could be taken into account in case of creation of new ad hoc investigative mechanisms or of a permanent institution of this kind.

Regularization meets GreenAI: a new framework for image reconstruction in life sciences applications

Ill-conditioned inverse problems frequently arise in life sciences, particularly in the context of image deblurring and medical image reconstruction. These problems have been addressed through iterative variational algorithms, which regularize the reconstruction by adding prior knowledge about the problem's solution. Despite the theoretical reliability of these methods, their practical utility is constrained by the time required to converge. Recently, the advent of neural networks allowed the development of reconstruction algorithms that can compute highly accurate solutions with minimal time demands. Regrettably, it is well-known that neural networks are sensitive to unexpected noise, and the quality of their reconstructions quickly deteriorates when the input is slightly perturbed. Modern efforts to address this challenge have led to the creation of massive neural network architectures, but this approach is unsustainable from both ecological and economic standpoints. The recently introduced GreenAI paradigm argues that developing sustainable neural network models is essential for practical applications. In this thesis, we aim to bridge the gap between theory and practice by introducing a novel framework that combines the reliability of model-based iterative algorithms with the speed and accuracy of end-to-end neural networks. Additionally, we demonstrate that our framework yields results comparable to state-of-the-art methods while using relatively small, sustainable models. In the first part of this thesis, we discuss the proposed framework from a theoretical perspective. We provide an extension of classical regularization theory, applicable in scenarios where neural networks are employed to solve inverse problems, and we show there exists a trade-off between accuracy and stability. Furthermore, we demonstrate the effectiveness of our methods in common life science-related scenarios. In the second part of the thesis, we initiate an exploration extending the proposed method into the probabilistic domain. We analyze some properties of deep generative models, revealing their potential applicability in addressing ill-posed inverse problems.