The Evolution of Knowledge and the Dynamics of an Industry Network

The paper moves a step forward in the direction of establishing a connection between the structure and evolution of knowledge bases and the structure and evolution of organizational forms in innovative activities in a science-intensive industry. The paper has an explicit focus on the dynamics of the network of collaborative agreements in R&D in the pharma/biotech industry after the “molecular biology revolution”. Using a comprehensive dataset, built by the authors integrating several sources in the industry, the dynamics of the network over time is extensively analyzed. With regards to network structure, it is found that, while the size of the network increases over time due to net flows of entry, its topological properties remain relatively unchanged. The evolution of the network has occurred without relevant deformations in the core-periphery profile. With regards to age-dependent propensity to collaborate, the paper finds that the extent of inter-generational collaboration is much more significant than intra-generational collaboration. In addition, the propensity of firms of a given generation to enter into collaboration with firms of a different generation increases with the distance between the two, while the total number of intra-generational collaborations decreases over time and, moreover, tends to decrease for most recent generations. In the paper a unitary and coherent explanation of the evidence is developed, coming to reveal the existence of a striking isomorphism between structural properties of the dynamics of knowledge and of the evolution of network structure. This revised version was published online in July 2006 with corrections to the Cover Date.     

A general inversion theorem for cointegration

A generalization of the Granger and the Johansen Representation Theorems valid for any (possibly fractional) order of integration is presented. This Representation Theorem is based on inversion results that characterize the order of the pole and the coefficients of the Laurent series representation of the inverse of a matrix function around a singular point. Explicit expressions of the matrix coefficients of the (polynomial) cointegrating relations, of the Common Trends and of the Triangular representations are provided, either starting from the Moving Average or the Auto Regressive form. This contribution unifies different approaches in the literature and extends them to an arbitrary order of integration. The role of deterministic terms is discussed in detail.     

Non-parametric regression on compositional covariates using Bayesian P-splines

Methods to perform regression on compositional covariates have recently been proposed using isometric log-ratios (ilr) representation of compositional parts. This approach consists of first applying standard regression on ilr coordinates and second, transforming the estimated ilr coefficients into their contrast log-ratio counterparts. This gives easy-to-interpret parameters indicating the relative effect of each compositional part. In this work we present an extension of this framework, where compositional covariate effects are allowed to be smooth in the ilr domain. This is achieved by fitting a smooth function over the multidimensional ilr space, using Bayesian P-splines. Smoothness is achieved by assuming random walk priors on spline coefficients in a hierarchical Bayesian framework. The proposed methodology is applied to spatial data from an ecological survey on a gypsum outcrop located in the Emilia Romagna Region, Italy.     

Behavioural Addictions in Adolescents and Young Adults: Results from a Prevalence Study

Our study aims to assess the prevalence of behavioural addictions in an adolescent population, evaluating the effects of gender and age, and to assess the correlations among different behavioural addictions. 2853 high school students were assessed in order to evaluate the prevalence of behavioural addictions such as Pathological Gambling (PG), Compulsive Buying (CB), Exercise Addiction (EA), Internet Addiction (IA), and Work Addiction (WA), in a population of Italian adolescents. The South Oaks Gambling Screen-Revised Adolescent (SOGS-RA), the Compulsive Buying Scale (CBS), the Exercise Addiction Inventory (EAI), the Internet Addiction Test (IAT), and the Work Addiction Risk Test (WART), were compiled anonymously by the students. Overall prevalence was 7.0% for PG, 11.3% for CB, 1.2% for IA, 7.6% for WA, 8.5% for EA. PG and EA were more common among boys, while gender had no effect on the other conditions. CB was more common among younger (<18 years old) students. The scores of all of these scales were significantly correlated. The strong correlation among different addictive behaviours is in line with the hypothesis of a common psychopathological dimension underlying these phenomena. Further studies are needed to assess personality traits and other clinical disorders associated with these problems behaviours.     

Assessing multiple prior models of behaviour under ambiguity

The recent spate of theoretical models of behaviour under ambiguity can be partitioned into two sets: those involving multiple priors and those not involving multiple priors. This paper provides an experimental investigation into the first set. Using an appropriate experimental interface we examine the fitted and predictive power of the various theories. We first estimate subject-by-subject, and then estimate and predict using a mixture model over the contending theories. The individual estimates suggest that 24% of our 149 subjects have behaviour consistent with Expected Utility, 56% with the Smooth Model, 11% with Rank Dependent Expected Utility and 9% with the Alpha Model; these figures are close to the mixing proportions obtained from the mixture estimates where the respective posterior probabilities of each of them being of the various types are 25%, 50%, 20% and 5%; and using the predictions 22%, 53%, 22% and 3%. The Smooth model appears the best.     

Little naked pangs of the self: the real performance of the self and the function of trust in Goffman's action theory

The aim of this article is to discuss some of the leading features of Erving Goffman's action theory as an alternative to the ‘orthodox’ paradigms of sociology, viewed as a structuralist and functionalist science that defines social constructs by their shared rules and values, and as a drifting of action, in the sense of intention, toward an individualistic version. The author examines Goffman's shift of the focus of attention from the boundaries of a social sense of action to the social dialectic of ‘defining a situation’ (W. Thomas) as conducted by the social actors in a renewal of Simmel's ‘empowering covenants’ (wechselwirkung) in the multiple casual social connections that make up the ‘social buzz’ in a society. The author moreover discusses Goffman's action as a kind of playacting regulating cognitive and expressive face-to-face ‘traffic’ between the social actors. This relational dynamic creates an interactive play based on encounters – in which one's opening to another is fraught with risks of deception – regulated by trust as a central resource for social interactions. Trust, in its interpersonal and systemic variants, constitutes a universal social datum and an elementary precondition for social exchanges and the cooperation between individuals. Trust, thus, functions as comparer between reciprocal expectations and a regulator of freedom tending to the stability of the social system.     

Human Reliability Analysis by Fuzzy "CREAM"

This article proposes a systematic procedure for computing probabilities of operator action failure in the cognitive reliability and error analysis method (CREAM). The starting point for the quantification is a previously introduced fuzzy version of the CREAM paradigm that is here further extended to account for: (1) the ambiguity in the qualification of the conditions under which the action is performed (common performance conditions, CPCs) and (2) the fact that the effects of such conditions on human performance reliability may not all be equal.     

BEHAVIORAL PATTERNS IN SOCIAL NETWORKS

In this article, we focus on the analysis of individual decision‐making for the formation of social networks, using experimentally generated data. We analyze the determinants of the individual demand for links under the assumption of agents' static expectations and identify patterns of behavior that correspond to three specific objectives: players propose links so as to maximize expected profits (myopic best response strategy); players attempt to establish the largest number of direct links (reciprocator strategy); and players maximize expected profits per direct link (opportunistic strategy). These strategies explain approximately 74% of the observed choices. We demonstrate that they are deliberately adopted and, by means of a finite mixture model, well identified and separated in our sample. (JEL C33, C35, C90, D85)