Producers' Perceptions and Consumers' Behaviour Toward Certified Beans from Integrated Production (IP) in the Brazilian Central Region

Integrated production (IP) is part of the Brazilian government program to promote sustainable agricultural production. IP ensure minimum food quality standards for domestic market, and export. Furthermore, IP is considered a good option to reduce negative environmental impacts of intensive crops in tropical Savannas, including common beans, as a Brazilian staple food. Although its advantages, and the government’s effort to promote IP, few growers are adopting IP. Maybe, the perception about IP usefulness and/or its ease of use is not too clear. Moreover, the production sector is driven by market signs, and there is few information on the consumer's preferences toward IP certified products in Brazil. In this study, we sought to identify some critical factors that can influence the IP adoption in beans' production. Moreover, we sought to verify the consumers’ perceptions and intention of purchasing IP certified beans (hypothetical product). This report comprises four chapters: (1) an introduction illustrating the context in which the research was based; (2) the results on the study of IP adoption based on the Technology Acceptance Model (TAM); (3) the choice experiment results applied to identify consumers preferences and willingness-to-pay (WTP) for IP label; (4) the results on the Theory of Planned Behaviour (TPB) applied to identify consumers’ perception toward IP certified beans. This research contributes with rich information for the beans’ supply chain, providing several insights to growers, retail and other agents, including policy makers. Beans’ production sector seems to be positively intentioned to adopt IP, but further studies should be conducted to test other adoption indicators using TAM model. Surveyed consumers are willing to pay a premium price for IP labelled beans. They showed a positive attitude toward purchasing IP labelled beans. It is an important information to motivate production sector to offer certified beans to the market.

Analysis of the Slow Food movement impact on the farmers and rural areas’ sustainable development

The evaluation of the farmers’ communities’ approach to the Slow Food vision, their perception of the Slow Food role in supporting their activity and their appreciation and expectations from participating in the event of Mother Earth were studied. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was adopted in an agro-food sector context. A survey was conducted, 120 questionnaires from farmers attending the Mother Earth in Turin in 2010 were collected. The descriptive statistical analysis showed that both Slow Food membership and participation to Mother Earth Meeting were much appreciated for the support provided to their business and the contribution to a more sustainable and fair development. A positive social, environmental and psychological impact on farmers also resulted. Results showed also an interesting perspective on the possible universality of the Slow Food and Mother Earth values. Farmers declared that Slow Food is supporting them by preserving the biodiversity and orienting them to the use of local resources and reducing the chemical inputs. Many farmers mentioned the language/culture and administration/bureaucratic issues as an obstacle to be a member in the movement and to participate to the event. Participation to Mother Earth gives an opportunity to exchange information with other farmers’ communities and to participate to seminars and debates, helpful for their business development. The absolute majority of positive answers associated to the farmers’ willingness to relate to Slow Food and participate to the next Mother Earth editions negatively influenced the UTAUT model results. A factor analysis showed that the variables associated to the UTAUT model constructs Performance Expectancy and Effort Expectancy were consistent, able to explain the construct variability, and their measurement reliable. Their inclusion in a simplest Technology Acceptance Model could be considered in future researches.

Technology Development and Consumer Acceptance of Innovation in Fruit Production

Precision Agriculture (PA) and the more specific branch of Precision Horticulture are two very promising sectors. They focus on the use of technologies in agriculture to optimize the use of inputs, so to reach a better efficiency, and minimize waste of resources. This important objective motivated many researchers and companies to search new technology solutions. Sometimes the effort proved to be a good seed, but sometimes an unfeasible idea. So that PA, from its birth more or less 25 years ago, is still a “new” management, interesting for the future, but an actual low adoption rate is still reported by experts and researchers. This work aims to give a contribution in finding the causes of this low adoption rate and proposing a methodological solution to this problem. The first step was to examine prior research about Precision Agriculture adoption, by ex ante and ex post approach. It was supposed as important to find connections between these two phases of a purchase experience. In fact, the ex ante studies dealt with potential consumer’s perceptions before a usage experience occurred, therefore before purchasing a technology, while the ex post studies described the drivers which made a farmer become an end-user of PA technology. Then, an example of consumer research is presented. This was an ex ante research focused on pre-prototype technology for fruit production. This kind of research could give precious information about consumer acceptance before reaching an advanced development phase of the technology, and so to have the possibility to change something with the least financial impact. The final step was to develop the pre-prototype technology that was the subject of the consumer acceptance research and test its technical characteristics.

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.

Radar based improvements and diagnosis of the convective capabilities of the cosmo-2 model

In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.

Modeling systems and vis/NIR device to improve peach and nectarine pre and post-harvest fruit maturity management

During the last decade peach and nectarine fruit have lost considerable market share, due to increased consumer dissatisfaction with quality at retail markets. This is mainly due to harvesting of too immature fruit and high ripening heterogeneity. The main problem is that the traditional used maturity indexes are not able to objectively detect fruit maturity stage, neither the variability present in the field, leading to a difficult post-harvest management of the product and to high fruit losses. To assess more precisely the fruit ripening other techniques and devices can be used. Recently, a new non-destructive maturity index, based on the vis-NIR technology, the Index of Absorbance Difference (IAD), that correlates with fruit degreening and ethylene production, was introduced and the IAD was used to study peach and nectarine fruit ripening from the “field to the fork”. In order to choose the best techniques to improve fruit quality, a detailed description of the tree structure, of fruit distribution and ripening evolution on the tree was faced. More in details, an architectural model (PlantToon®) was used to design the tree structure and the IAD was applied to characterize the maturity stage of each fruit. Their combined use provided an objective and precise evaluation of the fruit ripening variability, related to different training systems, crop load, fruit exposure and internal temperature. Based on simple field assessment of fruit maturity (as IAD) and growth, a model for an early prediction of harvest date and yield, was developed and validated. The relationship between the non-destructive maturity IAD, and the fruit shelf-life, was also confirmed. Finally the obtained results were validated by consumer test: the fruit sorted in different maturity classes obtained a different consumer acceptance. The improved knowledge, leaded to an innovative management of peach and nectarine fruit, from “field to market”.

Use of shared memory in the context of embedded multi-core processors: exploration of the technology and its limits

Modern embedded systems embrace many-core shared-memory designs. Due to constrained power and area budgets, most of them feature software-managed scratchpad memories instead of data caches to increase the data locality. It is therefore programmers’ responsibility to explicitly manage the memory transfers, and this make programming these platform cumbersome. Moreover, complex modern applications must be adequately parallelized before they can the parallel potential of the platform into actual performance. To support this, programming languages were proposed, which work at a high level of abstraction, and rely on a runtime whose cost hinders performance, especially in embedded systems, where resources and power budget are constrained. This dissertation explores the applicability of the shared-memory paradigm on modern many-core systems, focusing on the ease-of-programming. It focuses on OpenMP, the de-facto standard for shared memory programming. In a first part, the cost of algorithms for synchronization and data partitioning are analyzed, and they are adapted to modern embedded many-cores. Then, the original design of an OpenMP runtime library is presented, which supports complex forms of parallelism such as multi-level and irregular parallelism. In the second part of the thesis, the focus is on heterogeneous systems, where hardware accelerators are coupled to (many-)cores to implement key functional kernels with orders-of-magnitude of speedup and energy efficiency compared to the “pure software” version. However, three main issues rise, namely i) platform design complexity, ii) architectural scalability and iii) programmability. To tackle them, a template for a generic hardware processing unit (HWPU) is proposed, which share the memory banks with cores, and the template for a scalable architecture is shown, which integrates them through the shared-memory system. Then, a full software stack and toolchain are developed to support platform design and to let programmers exploiting the accelerators of the platform. The OpenMP frontend is extended to interact with it.