An Input-Process-Output Approach to Interorganizational Teams: The Influence of Work Group Diversity, Trust and Shared Leadership on Communication Network and Team Outputs.

The market’s challenges bring firms to collaborate with other organizations in order to create Joint Ventures, Alliances and Consortia that are defined as “Interorganizational Networks” (IONs) (Provan, Fish and Sydow; 2007). Some of these IONs are managed through a shared partecipant governance (Provan and Kenis, 2008): a team composed by entrepreneurs and/or directors of each firm of an ION. The research is focused on these kind of management teams and it is based on an input-process-output model: some input variables (work group’s diversity, intra-team's friendship network density) have a direct influence on the process (team identification, shared leadership, interorganizational trust, team trust and intra-team's communication network density), which influence some team outputs, individual innovation behaviors and team effectiveness (team performance, work group satisfaction and ION affective commitment). Data was collected on a sample of 101 entrepreneurs grouped in 28 ION’s government teams and the research hypotheses are tested trough the path analysis and the multilevel models. As expected trust in team and shared leadership are positively and directly related to team effectiveness while team identification and interorganizational trust are indirectly related to the team outputs. The friendship network density among the team’s members has got positive effects on the trust in team and on the communication network density, and also, through the communication network density it improves the level of the teammates ION affective commitment. The shared leadership and its effects on the team effectiveness are fostered from higher level of team identification and weakened from higher level of work group diversity, specifically gender diversity. Finally, the communication network density and shared leadership at the individual level are related to the frequency of individual innovative behaviors. The dissertation’s results give a wider and more precise indication about the management of interfirm network through “shared” form of governance.

Graph algorithms for bioinformatics

Biological data are inherently interconnected: protein sequences are connected to their annotations, the annotations are structured into ontologies, and so on. While protein-protein interactions are already represented by graphs, in this work I am presenting how a graph structure can be used to enrich the annotation of protein sequences thanks to algorithms that analyze the graph topology. We also describe a novel solution to restrict the data generation needed for building such a graph, thanks to constraints on the data and dynamic programming. The proposed algorithm ideally improves the generation time by a factor of 5. The graph representation is then exploited to build a comprehensive database, thanks to the rising technology of graph databases. While graph databases are widely used for other kind of data, from Twitter tweets to recommendation systems, their application to bioinformatics is new. A graph database is proposed, with a structure that can be easily expanded and queried.

Law, Informal Institutions and Trust: an Experimental Perspective

This dissertation has studied how legal and non-legal mechanisms affect the levels of trust and trustworthiness in an economy, and whether and when subtle psychological factors are crucial for establishing trust and even for recovering trust from a breach of contract. The first Chapter has addressed the question of whether formal legal enforcement crowds out or crowds in the amount of trust in a society. We find that formal legal mechanisms, especially formal contracts backed by a powerful authority, normally undermine trust except when they are perceived as legitimate, or when there are no strong social norms of fairness (i.e. the population in a society is considerably heterogeneous), or when the environment in which repeated commercial relationships take place becomes highly uncertain. The second Chapter has examined whether the endogenous adoption of a collective punishment institution can help a society coordinate on an efficient outcome, characterized by high levels of trust and trustworthiness. The experimental results show that the endogenous introduction of collective punishment by means of a majority-voting rule does not significantly improve coordination on the efficient equilibrium. Not all subjects seem to be able to anticipate the change in behavior induced by the introduction of the mechanism, and a majority of them vote against it. The third Chapter has explored whether high-trustors adapt their behavior in response to others’ trustworthiness or untrustworthiness more quickly, which in turn supports them to maintain higher default expectations of others’ trustworthiness relative to low-trustors. Our experimental results reveal that high-trustors are better than low-trustors at predicting others’ trustworthiness because they are less susceptible to the anticipated aversive emotions aroused by the potential betrayal and thereby have a higher willingness to acquire the valuable information about their partner’s actions.