La sostenibilità organizzativa dei progetti agricoli di cooperazione internazionale allo sviluppo

The importance of organizational issues to assess the success of international development project has not been fully considered yet. After a brief overview, in 1st chapter, on main actors involved on international cooperation, in the 2nd chapter an analysis of the literature on the project success definition, focused on the success criteria and success factors, was carried out by surveying the contribution of different authors and approaches. Traditionally projects were perceived as successful when they met time, budget and performance goals, assuming a basic similarity among projects (universalistic approach). However, starting from a non-universalistic approach, the importance of organization’s effectiveness, in terms of Relations Sustainability, emerged as a dimension able to define and assess a project success. The identification of the factors influencing the relationship between and inside the organizations becomes consequently a priority. In 3th chapter, starting from a literature survey, the different analytical approaches related to the inter and intra-organization relationships are analysed. They involve two different groups: the first includes studies focused on the type of organizations relationship structure (Supply Chains, Networks, Clusters and Industrial Districts); the second group includes approaches related to the general theories on firms relationship interpretation (Transaction Costs Economics, Resource Based View, Organization Theory). The variables and logical frameworks provided by these different theoretical contributions are compared and classified in order to find out possible connections and/or juxtapositions. Being an exhaustive collection of the literature on the subject is impossible, the main goal is to underline the existence of potentially overlapping and/or integrating approaches examining the contribution provided by different representative authors. The survey showed first of all many variables in common between approaches coming from different disciplines; furthermore the non overlapping variables can be integrated contributing to a broader picture of the variables influencing the organization relations; in particular a theoretical design for the identification of connections between the inter and the intra-organizations relations was made possible. The results obtained in 3th chapter help to defining a general theoretical framework linking the different interpretative variables. Based on extensive research contributions on the factors influencing the relations between organizations, the 4th chapter expands the analysis of the influence of variables like Human Resource Management, Organizational Climate, Psychological Contract and KSA (Knowledge, Skills, Abilities) on the relation sustainability. A detailed analysis of these relations is provided and a research hypothesis are built. According to this new framework in 5th chapter a statistical analysis was performed to qualify and quantify the influence of Organizational Climate on the Relations Sustainability. To this end the Structural Equation Modeling (SEMs) has adopted as method for the definition of the latent variables and the measure of their relations. The results obtained are satisfactory. An effective strategy to motivate the respondents to participate in the survey seems to be at the moment one of the major obstacles to the analysis implementation since the organizational performances are not specifically required by the projects’ evaluation guidelines and they represent an increase in the project related transaction costs. Their explicit introduction in the project presentation guidelines should be explored as an opportunity to increase the chances of success of these projects.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.