Objective methods for graphical structural learning

Graphical models are used for expressing conditional independence relationships among variables by the means of graphs, whose structure is typically unknown and must be inferred by the data at hand. We propose a theoretically sound Objective Bayes procedure for graphical model selection. Our method is based on the Expected-Posterior Prior and on the Power-Expected-Posterior Prior. We use as input of the proposed methodology a default improper prior and suggest computationally efficient approximations of Bayes factors and posterior odds. In a variety of simulated scenarios with varying number of nodes and sample sizes, we show that our method is highly competitive with, or better than, current benchmarks. We also discuss an application to protein-signaling data, which wieldy confirms existing results in the scientific literature.     

Issues in the analysis of co-authorship networks

Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines.     

Market Power and Patent Strategies: Evidence from Renaissance Venice

This paper exploits the introduction of the first regularized patent system, which appeared in the Venetian Republic in 1474, to examine the factors shaping inventors’ propensity to use a new form of intellectual property. We combine detailed information on craft guilds and patents in Renaissance Venice and show a negative association between patenting activity and guild statutory norms that strongly restricted entry and price competition. Our analysis shows that the heterogeneity in patenting activity documented by the industrial organization literature is not a special feature of modern technologies, but is rather a persistent phenomenon affected by market power.     

Sustainable tourism planning and climate change adaptation in the Alps: a case study of winter tourism in mountain communities in the Dolomites

A vast body of literature suggests that the European Alpine Region is extremely sensitive to climate change. Winter tourism is closely related to climate variations, especially in mountain regions where resorts are heavily dependent on snow. This paper explores how to effectively integrate a climate change adaptation perspective with local discourses about sustainability and tourism, an increasing priority for policy-makers in the region and elsewhere. It reports on the development and application of a participatory decision support process for the analysis of adaptation strategies for local development of an Alpine tourism destination, Auronzo di Cadore (Dolomites, Italy). This experience significantly contributed to the idea that an efficient combination of modelling capabilities, decision support tools, and participatory processes can substantially improve decision-making for sustainability. The authors show that, in this case study, such a combination of methods and tools allowed for managing the involvement of local actors, stimulating local debates on climate change adaptation and possible consequences on winter tourism, encouraging creativity and smoothing potential conflicts, and easing the integration of the qualitative knowledge and the preferences of the involved actors with quantitative information. This contributed to an integrated sustainability assessment of alternative strategies for sustainable tourism planning.     

Local banking and local economic growth in Italy: some panel evidence

This article provides new evidence on the contribution of local banking to local economic growth (i.e. at county level – the Italian ‘province’) in Italy. A comprehensive data set is used, which includes control variables for social capital and human capital as well as indicators of the quality of local infrastructures and the production structure of the local economy. A linear within-estimator technique with fixed effects is applied to a modified version of the so-called Barro regression in order to address the well-known econometric issues of reverse causality and estimation bias resulting from unobserved district-specific influences.     

Which Way is “Up” in Upgrading? Trajectories of Change in the Value Chain for South African Wine

Global Value Chain (GVC) analysis uses the concept of upgrading to highlight paths for developing country firms to “move up the value chain,” usually through the lenses of four categories—product, process, functional, and inter-sectoral upgrading. The implicit normative expectation is that these firms move toward producing higher value-added products and/or take on more sophisticated functions along a value chain. In this article, upgrading is approached more broadly as “reaching a better deal,” including a balance between rewards and risk. The case study of South African wine shows that better product quality, improved processes, and some functional upgrading have co-existed with processes of “downgrading,” higher risks, and limited rewards, especially in traditional export markets. A reflection on further conceptual development and directions for empirical research is also provided.     

Organizing the purchasing department for innovation

Innovation is by far one of the most important competitive priorities in the current business context. Companies increasingly rely on their supply base to support their innovation potential. As a consequence, the purchasing department might dramatically affect the firm??s innovation capability. This paper aims to investigate??using a multiple case study approach??how the organizational design of the purchasing department could determine a firm??s capability to foster and manage innovation. Seven highly innovative companies were visited and the structures of their purchasing departments were analyzed. Three different configurations for the purchasing department were identified and described.     

Cropland use,yields, and droughts: spatial data modeling for Burkina Faso and Niger

For countries with recurrent droughts, the design of drought impact mitigation measures could benefit from analyses of determinants of yields and prices of local crops at regional and district level. This study applies dynamic spatial panel data regression models to yields and prices of four major food crops across regions of Burkina Faso and Niger, over sample periods between 1984 and 2006. Results lend support to mainly simultaneous spatial spillovers, particularly for millet and cowpea prices and sorghum yields in Niger, and maize yields in Burkina Faso. After accounting for these effects, most crop yields are found to be weakly price‐responsive, as envisaged by a supply‐side geographical diffusion hypothesis. Seasonal rainfall elasticity estimates suggest that dominant food crops have slight advantage margins in terms of relative resilience to rainfall shortages. However, this result is to be weighed against low millet yields in Niger, and marked drops in sorghum yields during officially declared droughts in Burkina Faso.