Besser entscheiden im Team — aber wie?

Investment committees of banks, pension funds or investment clubs meet regularly. The members decide together about the allocation and the timing of their own assets or their customers assets. This article will point out some pitfalls and chances that are typical in this decision making process. Especial focus is set on financial psychological aspects with regards to information processing and decision making processes. At the end of the article the author will indicate a sustainable way to improve the quality of team decisions.     

Können Organisationen nicht lernen? Facetten organisationaler Lernkulturen

Recently, the concept of ‘learning culture’ has entered the discussion on learning organizations and organizational learning, especially in the German speaking countries. Most of the academics, but also practitioners seem to use the term ‘learning culture’ in a particular sense as nurturing a self-directed, on-the-job learning of all employees. An implicit, often neglected assumption of this conception is that organizations can be divided into those who have a learning culture and those who do not. Although this idea of a dichotomy is also found in the discussion on learning organizations, it can be called into question. Past research has shown that (organizational) learning is a multifaceted phenomenon. Different organizations engage in very diverse kinds of learning due to the fact that they are facing varying environmental conditions. This brings us to doubt the idea of a ?one-best-way“ learning culture. Following the basic question, who learns what, how, when and why, the article presents a set of distinguishing attributes to distinguish between different types of learning cultures. Finally, yet unanswered questions and paths for future research are discussed.     

Eine integrative Theorie des Problemlösens in Gruppen: Problemlöseprozess und Problemlöseerfolg

This paper is the first paper in a three-part article series presenting an integrative theory of problem solving in groups on the basis of theory and research on group processes, problem solving and decision making. Group problem solving is differentiated into three main focuses of action, namely taskwork, group organisation and socio-emotional regulation. The present paper focuses on aspects of group organization. A theory of the structure of group mental models is developed. The mental model of problem solving groups is differentiated into a short-term and a long-term memory system. Under each memory system, several memory units are proposed containing declarative and procedural knowledge on aspects of the problem at hand and aspects of the group. Based on the assumption that success in problem solving results from the group’s success in solving various subproblems, recommendations for structuring the problem solving process are being drafted. It is suggested that during an initial orientation stage all occurring subproblems be rated according to their need for action and stored in the short term memory system. In the following action stage, the various subproblems stored in the short term memory system should be worked off in the order of their respective need for action. Based on characteristics of the subproblems at hand and on situative constraints, propositions concerning the resources needed for belabouring the various subproblems are established. Consequences with regard to the working mode of the group are derived.     

Small area estimation for longitudinal surveys

Over the last few years many studies have been carried out in Italy to identify reliable small area labour force indicators. Considering the rotated sample design of the Italian Labour Force Survey, the aim of this work is to derive a small area estimator which borrows strength from individual temporal correlation, as well as from related areas. Two small area estimators are derived as extensions of an estimation strategies proposed by Fuller (1990) for partial overlap samples. A simulation study is carried out to evaluate the gain in efficiency provided by our solutions. Results obtained for different levels of autocorrelation between repeated measurements on the same outcome and different population settings show that these estimators are always more reliable than the traditional composite one, and in some circumstances they are extremely advantageous.The present paper is financially supported by Murst-Cofin (2001) Lutilizzo di informazioni di tipo amministrativo nella stima per piccole aree e per sottoinsiemi della popolazione (National Coordinator Prof. Carlo Filippucci).     

Convexity-based clustering criteria: theory,algorithms, and applications in statistics

This paper deals with the construction of optimum partitions of for a clustering criterion which is based on a convex function of the class centroids as a generalization of the classical SSQ clustering criterion for n data points. We formulate a dual optimality problem involving two sets of variables and derive a maximum-support-plane (MSP) algorithm for constructing a (sub-)optimum partition as a generalized k-means algorithm. We present various modifications of the basic criterion and describe the corresponding MSP algorithm. It is shown that the method can also be used for solving optimality problems in classical statistics (maximizing Csiszárs -divergence) and for simultaneous classification of the rows and columns of a contingency table.     

Technology spillover and regional convergence process: a statistical analysis of the Italian case

Recent literature broadly highlight the importance of modelling technological innovation effects on economic growth. This paper develops a methodology that allows to measure technology contribution to economic convergence; the choice of a regional framework also allows to underline interregional knowledge transmission as a the major channel of technological progress. Moreover, the specification of a dynamic growth model enables to evaluate both the regional convergence and the effect of innovation on long-run labour productivity without resorting to any technology index measurement. We contribute to the methodological literature also by comparing different dynamic panel data estimation procedures and by detecting both the presence of small sample bias and the existence of a nearly unit root autoregressive process in labour productivity series. The results of an empirical analysis on Italian regions show how most of innovation resources derives from relevant spillover mechanisms. Furthermore, technology spillover intensity seems to be strongly affected by geography and productive structure of regions.Financial support by Fondazione Cassa di Risparmio di Rimini and Uniturim S.p.A. is gratefully acknowledged.     

Estimating the fundamental frequency of a periodic function

In this paper we consider the problem of estimation of the fundamental frequency of a periodic function, which has several applications in Speech Signal Processing. The problem was originally proposed by Hannan (1974) and later on Quinn and Thomson (1991) provided an estimation procedure of the unknown parameters. It is observed that the estimation procedure of Quinn and Thomson (1991) is quite involved numerically. In this paper we propose to use two simple estimators and it is observed that their performance are quite satisfactory. Asymptotic properties of the proposed estimators are obtained. The large sample properties of the estimators are compared theoretically. We present some simulation results to compare their small sample performance. One speech data is analyzed using this particular model.     

The univariate distribution function for a particular bilinear model

The aim of the paper is to find the univariate stationary distribution of a particular bilinear process. In this context, we propose a novel approach to derive the distribution function. It is based on a recursive formula and allows to relax the conditions on the moments of the process. We also show that the derived approximation converges to the true distribution function. The accuracy of the recursive formula is evaluated for finite sample dimensions by a small simulation study.Received: February 2003, Revised: May 2004,     

Optimal use of two auxiliary variables in double sampling

Double sampling scheme is used when cheap auxiliary variables may be measured to improve the estimation of a finite population parameter. Several estimators for population mean, ratio of means and variance are available, when two dependent samples are drawn. However, there are few proposals for the case of independent samples. In this paper both cases of dependent and independent samples are dealt with. A general approach for estimating a finite population parameter is given, showing that all the proposed estimators are particular cases of the same general class. The minimum variance bound for any estimator in this class is provided (at the first order of approximation). Furthermore, an optimal estimator which reaches this minimum is found.