A Quantitative Assessment of the Risk for Highly Pathogenic Avian Influenza Introduction into Spain via Legal Trade of Live Poultry

Highly pathogenic avian influenza (HPAI) is considered one of the most important diseases of poultry. During the last 9 years, HPAI epidemics have been reported in Asia, the Americas, Africa, and in 18 countries of the European Union (EU). For that reason, it is possible that the risk for HPAI virus (HPAIV) introduction into Spain may have recently increased. Because of the EU free‐trade policy and because legal trade of live poultry was considered an important route for HPAI spread in certain regions of the world, there are fears that Spain may become HPAIV‐infected as a consequence of the legal introduction of live poultry. However, no quantitative assessment of the risk for HPAIV introduction into Spain or into any other EU member state via the trade of poultry has been published in the peer‐reviewed literature. This article presents the results of the first quantitative assessment of the risk for HPAIV introduction into a free country via legal trade of live poultry, along with estimates of the geographical variation of the risk and of the relative contribution of exporting countries and susceptible poultry species to the risk. The annual mean risk for HPAI introduction into Spain was estimated to be as low as 1.36 × 10⁻³, suggesting that under prevailing conditions, introduction of HPAIV into Spain through the trade of live poultry is unlikely to occur. Moreover, these results support the hypothesis that legal trade of live poultry does not impose a significant risk for the spread of HPAI into EU member states.     

Ein Optimierungsmodell für die wöchentliche Tourenplanung unter Einbeziehung der EU-Sozialvorschriften

The Regulation (EC) No 561/2006 and the Directive 2002/15/EC concern the driving and working hours as well as breaks and rest periods of drivers in road transportation. Although the regulations have an enormous effect on vehicle routing and scheduling, only parts of them have been integrated in few solution approaches and some vehicle routing models so far. This paper starts with the presentation of the restrictions of the relevant European Community regulations. Then, a mixed integer linear programming model for the vehicle routing problem with time windows including all rules of the regulations for a planning horizon of an entire week is presented. The model is solved with CPLEX and the impact of the regulations on the resulting vehicle schedules is analyzed by means of computational experiments.     

MOMENT ESTIMATION IN THE CLASS OF BISEXUAL BRANCHING PROCESSES WITH POPULATION–SIZE DEPENDENT MATING

This paper concerns the estimation of the offspring mean vector, the covariance matrix and the growth rate in the class of bisexual branching processes with population‐size dependent mating. For the proposed estimators, some unconditional moments and some conditioned to non‐extinction are determined and asymptotic properties are established. Confidence intervals are obtained and, as illustration, a simulation example is given.     

Characterization of discrete populations through conditional expectations of order statistics

In this paper we give some properties of the expected values of any order statistic when one of its adjacent order statistics is known (order mean function) from a sequence of sizen of independent and identically distributed random variables with discrete distribution. Furthermore, we obtain the explicit expressions of the distribution from these order mean functions, and finally, we show the necessary and sufficient conditions for any real function to be an order mean function. We also add some examples of characterization of discrete distributions from the order mean functions. Partially supported by Consejería de Cultura y Educación (C.A.R.M.), under Grant PIB 95/90.     

Predicting Public Corruption with Neural Networks: An Analysis of Spanish Provinces

We contend that corruption must be detected as soon as possible so that corrective and preventive measures may be taken. Thus, we develop an early warning system based on a neural network approach, specifically self-organizing maps, to predict public corruption based on economic and political factors. Unlike previous research, which is based on the perception of corruption, we use data on actual cases of corruption. We apply the model to Spanish provinces in which actual cases of corruption were reported by the media or went to court between 2000 and 2012. We find that the taxation of real estate, economic growth, the increase in real estate prices, the growing number of deposit institutions and non-financial firms, and the same political party remaining in power for long periods seem to induce public corruption. Our model provides different profiles of corruption risk depending on the economic conditions of a region conditional on the timing of the prediction. Our model also provides different time frameworks to predict corruption up to 3 years before cases are detected.     

The Decent Work Questionnaire: Development and validation in two samples of knowledge workers

This research develops a Decent Work Questionnaire (DWQ) to measure workers’ perceptions of decent work. Current measurements of decent work are almost completely lacking at the individual worker level of analysis, and this study contributes to filling the gap. The authors designed their DWQ based on the substantive elements used by the ILO in its Decent Work Agenda, with the final 31‐item version of the DWQ yielding seven factors related to decent work. Showing good reliability coefficient values and good convergent and discriminant validity, this DWQ could open up new avenues for empirical studies on the concept of decent work.     

Violent behaviour,victimization, self-esteem and physical activity of Spanish adolescents according to place of residence: a structural equation model / Conducta violenta,victimización,autoestima y actividad física de adolescentes españoles en función del lugar de residencia: un modelo de ecuaciones estructurales

This study aims to establish and verify an explanatory model for aggressive behaviour, self-esteem, victimization and physical activity in adolescents, and to use this explanatory model to analyse the association of place of residence with these variables. This research analysed 2,273 adolescents from the province of Granada (Spain) using the questionnaires Violent Behaviour at Schools, School Victimization Scale and Global Self-Esteem Scale. An analysis was carried out using structural equations. Results showed that relational and overt aggressiveness are related to self-esteem, victimization and physical activity. Furthermore, relational aggressiveness showed a stronger association with victimization and low self-esteem in adolescents who live in residential care. In addition, overt aggressiveness showed a stronger association with self-esteem in adolescents who live in family homes. Thus, exclusion and social rejection among peers have a greater impact on the victimization of young people who live outside of the family context.     

The role of intercultural,scientific and technological openness on innovation in European regions

This paper analyses the importance of openness for innovation in European regions. Openness is understood from a double angle: intercultural and scientific & technological. Our hypothesis is that each type of openness brings different kinds of knowledge into the regions and results on a different innovation output. S&T openness brings analytical forms of knowledge whilst intercultural openness brings tacit ones. Our results confirm this relationship as S&T openness shows a significant impact on patent activity, but not when a broader innovation indicator is used. Intercultural openness is highly significant when measuring innovation by a broader index and much less when measured by patents.     

A multiple buyer – supplier relationship in the context of SMEs’ digital supply chain management*

Abstract

By underlining the relevance of the use of ICTs, knowledge sharing and electronic markets for SMEs, it emerges the need for stimulating a debate on digitisation process of supply chain management (SCM). Electronic infrastructure in the service sector are reducing each kind of cost and improving multiply buyer–supplier relationships, facilitating negotiations and transactions. However, since the coordination costs are still high, the use of ICTs is limited. This phenomenon thus attracts the interests of scholars and practitioners. Although it still needs to further investigate. Especially, the optimal use of ICTs within SMEs’ SCM have not been studied yet. Therefore, by leveraging on four proxies: ICTs specialised human resources, knowledge sharing activities, buyer–supplier relationships, adoption of electronic markets this optimal was analysed via structural equation modelling based on a sample of 1254 SMEs operating in the service sector in Italy.     

Focused estimation for noisy and small data sets: a Bayesian minimum expected loss estimator approach

Central to many inferential situations is the estimation of rational functions of parameters. The mainstream in statistics and econometrics estimates these quantities based on the plug‐in approach without consideration of the main objective of the inferential situation. We propose the Bayesian Minimum Expected Loss (MELO) approach focusing explicitly on the function of interest, and calculating its frequentist variability. Asymptotic properties of the MELO estimator are similar to the plug‐in approach. Nevertheless, simulation exercises show that our proposal is better in situations characterised by small sample sizes and/or noisy data sets. In addition, we observe in the applications that our approach gives lower standard errors than frequently used alternatives when data sets are not very informative.