"European Union: a civil or a political power in the Euro-Mediterranean Partnership?" In EURO-MED INTEGRATION AND THE 'RING OF FRIENDS': THE MEDITERRANEAN'S EUROPEAN CHALLENGE, VOL. IV"

This article claims that within the framework of the Euro-Mediterranean Partnership, the Union mainly assumes the role of civilian power. Sometimes it also has to assume the political power role and becomes influential by using the attraction of full membership. However, in cases like the conflict in the Middle East, where the Union still wants to be influential but the 'membership' instrument cannot work, the Union displays a poor record. In such situations, institutionalisation of the security dimension of the Euro-Mediterranean Partnership may help

Entrepreneurial Attitudes and Behaviours in Small-Scale Dairy Farms in Turkey

Dairy farms are quite important to transform Turkish livestock sector into being more productive and competitive in the process of EU integration. The purpose of this study is to determine the socio economic features of dairy farms in Turkey and to determine producers’ individual and management goals in the future. In addition, farmers’ level of participation related to the attitudes, behaviors and subjective norm components are determined and an entrepreneurship index is constructed to determine the factors that influence social economic characteristics of entrepreneurship. The material of the study consists of 167 surveys obtained from Cattle Breeders Association of Turkey in 17 cities through the postal mail in 2007. A five “Likert Scale” was used to determine behaviors and attitudes of farmers as well as descriptive statistics. In each category, factor weights were calculated based on factor analyses. Then, the social economic factors that determine entrepreneurship index were estimated using “Logistic Regression”. The results indicate that the primary goals of farmers are high income, enjoying the job, better life conditions, earning respect, utilizing the resources, better image, and producing high quality products. When entrepreneurial behaviors and attitudes are examined it was found that most of the farmers aim at earning high profit as a main goal and value dairy milk farming. The logistic regression shows that the factors that determine entrepreneur index are age, experience and area of feed crops.Small-Scale Dairy Farms, Entrepreneur Index, Theory of Planned Behavior, Turkey, Consumer/Household Economics, Livestock Production/Industries, Production Economics, Q12, Q16,

The role of membership change on knowledge transfer in groups

Groups can capitalize on knowledge to the extent that it is shared among its members. However, groups are in constant flux as its membership structure changes with new members joining and others exiting continuously. In this paper, we examine the effects of membership change on the knowledge flows and stocks within the group. Specifically, we focus on membership changes that involve the replacement of an oldtimer by a newcomer that joins the group. We argue that membership change affects the extent of knowledge transfer, the type of knowledge transferred and the knowledge stock held by the group. Specifically we focus on two dimensions of knowledge: component (technical) and architectural. Firms may benefit from recognizing these relationships and differences on the pool of knowledge held to improve knowledge flows in groups and enhance their performance, namely their innovative ability.membership change, newcomer, knowledge transfer, knowledge, turnover

A Grouping Genetic Algorithm for Joint Stratification and Sample Allocation Designs

Predicting the cheapest sample size for the optimal stratification in multivariate survey design is a problem in cases where the population frame is large. A solution exists that iteratively searches for the minimum sample size necessary to meet accuracy constraints in partitions of atomic strata created by the Cartesian product of auxiliary variables into larger strata. The optimal stratification can be found by testing all possible partitions. However the number of possible partitions grows exponentially with the number of initial strata. There are alternative ways of modelling this problem, one of the most natural is using Genetic Algorithms (GA). These evolutionary algorithms use recombination, mutation and selection to search for optimal solutions. They often converge on optimal or near-optimal solution more quickly than exact methods. We propose a new GA approach to this problem using grouping genetic operators instead of traditional operators. The results show a significant improvement in solution quality for similar computational effort, corresponding to large monetary savings.Comment: 22 page

Bayesian Shrinkage Estimation and Model Selection

We introduce a new shrinkage variable selection operator which we term Adaptive Ridge Selector (ARiS). This approach is inspired by the Relevance Vector Machine (RVM) of Tipping (2001), which uses a Bayesian hierarchical linear model to do sparse estimation. RVM was originally introduced to obtain sparse solutions in the case of kernel regression where one has many highly correlated bases (features). Extending the RVM algorithm, we include a proper prior distribution for the precisions of the regression coefficients along with a hyper-parameter to be chosen. Based upon this model, we derive the full set of conditional posterior distributions for parameters as would typically be done when applying Gibbs sampling. However, instead of simulating samples from the posterior distribution in order to estimate posterior means of quantities, we apply the Lindley-Smith mechanism (Lindley and Smith, 1972). This approach sequentially maximizes the conditional distributions, in order to find the joint maximum of the posterior distribution given the value of the hyper-parameter. An empirical Bayes method is proposed for choosing this hyperparameter leading to ARiS-eB. Having moved from a Bayes argument, we also look at the problem from a penalized least squares estimation angle. From the conventional viewpoint, the proposed method eliminates the need for combinatorial search techniques over a discreet model space, converting the model selection problem into the maximization of the marginal likelihood over a one dimensional continuous space. Close similarities exist between this estimator obtained and the lasso-type shrinkage estimators. The lasso(Tibshirani, 1996) and its variants, as will be thoroughly discussed, use 1-norm for regularization leading to sparse solutions. The estimator proposed here is contrasted with various other shrinkage estimators along with simulation studies and real data examples. Inference is also possible using a very straight forward Gibbs sampling procedure after the active variables are determined in the model. The model is also extended to handle departures from normality in the likelihood