A WEIGHTED RANK MEASURE OF CORRELATION

Spearman's rank correlation coefficient is not entirely suitable for measuring the correlation between two rankings in some applications because it treats all ranks equally. In 2000, Blest proposed an alternative measure of correlation that gives more importance to higher ranks but has some drawbacks. This paper proposes a weighted rank measure of correlation that weights the distance between two ranks using a linear function of those ranks, giving more importance to higher ranks than lower ones. It analyses its distribution and provides a table of critical values to test whether a given value of the coefficient is significantly different from zero. The paper also summarizes a number of applications for which the new measure is more suitable than Spearman's.     

Redesigning the Downtown of an Expansive Sunbelt City: The Phoenix Case

ABSTRACT

Non-motorized traffic safety is a major public health concern, especially in the sprawling sunbelt cities of the United States. Phoenix is ranked quite high on the number of pedestrian and cyclist crashes in North American cities. This article analyses non-motorist safety incidents in downtown Phoenix. Non-motorist safety concerns were addressed by examining crash types in order to suggest adequate safety treatments. We also demonstrated the use of a countermeasure framework for higher crash locations denominated hotspots. Our findings indicate that it is important to implement a combination of countermeasures to reduce the high number of non-motorist crashes in city centers.     

On the number of local minima for the multidimensional assignment problem

The Multidimensional Assignment Problem (MAP) is an NP-hard combinatorial optimization problem occurring in many applications, such as data association, target tracking, and resource planning. As many solution approaches to this problem rely, at least partly, on local neighborhood search algorithms, the number of local minima affects solution difficulty for these algorithms. This paper investigates the expected number of local minima in randomly generated instances of the MAP. Lower and upper bounds are developed for the expected number of local minima, E[M], in an MAP with iid standard normal coefficients. In a special case of the MAP, a closed-form expression for E[M] is obtained when costs are iid continuous random variables. These results imply that the expected number of local minima is exponential in the number of dimensions of the MAP. Our numerical experiments indicate that larger numbers of local minima have a statistically significant negative effect on the quality of solutions produced by several heuristic algorithms that involve local neighborhood search.Partially supported by the NSF grant DMI-0457473.     

Powerful nonparametric statistics to compare k independent ROC curves

The authors deal with the problem of comparing receiver operating characteristic (ROC) curves from independent samples. From a nonparametric approach, they propose and study three different statistics. Their asymptotic distributions are obtained and a resample plan is considered. In order to study the statistical power of the introduced statistics, a simulation study is carried out. The (observed) results suggest that, for the considered models, the new statistics are more powerful than the usually employed ones (the Venkatraman test and the usual area under the ROC curve criterion) in non-uniform dominance situations and quite good otherwise.     

Temporary Employment,Working Conditions and Expected Exits from Firms

This paper analyses two issues related to working conditions and temporary employment. First, why do temporary workers exhibit lower scores in objective indicators of working life? Second, what is the influence of working conditions on mobility? Using information for Spanish workers, the results indicate that differences in working conditions remain after controlling for individual, job and firm characteristics: in particular, temporary workers with short job tenure seem to occupy jobs with poorer working conditions. Moreover, there is evidence that workers with worse working life are more likely to expect to leave their current firms.     

Existence and Uniqueness of Solutions to the Bellman Equation in the Unbounded Case

We study the problem of the existence and uniqueness of solutions to the Bellman equation in the presence of unbounded returns. We introduce a new approach based both on consideration of a metric on the space of all continuous functions over the state space, and on the application of some metric fixed point theorems. With appropriate conditions we prove uniqueness of solutions with respect to the whole space of continuous functions. Furthermore, the paper provides new sufficient conditions for the existence of solutions that can be applied to fairly general models. It is also proven that the fixed point coincides with the value function and that it can be approached by successive iterations of the Bellman operator.     

Urban risks due to climate change in the Andean municipality of Pasto,Colombia: A Bayesian network approach

The current trends of climate change will increase people's exposure to urban risks related to events such as landslides, floods, forest fires, food production, health, and water availability, which are stochastic and very localized in nature. This research uses a Bayesian network (BN) approach to analyze the intensity of such urban risks for the Andean municipality of Pasto, Colombia, under climate change scenarios. The stochastic BN model is linked to correlational models and local scenarios of representative concentration trajectories (RCP) to project the possible risks to which the municipality of Pasto will be exposed in the future. The results show significant risks in crop yields, food security, water availability and disaster risks, but no significant risks on the incidence of acute diarrheal diseases (ADD) and acute respiratory infections (ARI), whereas positive outcomes are likely to occur in livestock production, influenced by population growth. The advantage of the BN approach is the possibility of updating beliefs in the probabilities of occurrence of events, especially in developing, intermediate cities with information-limited contexts.     

Three dimensions of effective mission implementation

Mission statements are generally considered an important tool for strategy implementation. However, several authors have shown that there is a ‘hole’ in the mission theory, which in practice explains the inconsistency in mission statements in many companies because of the lack of motivation related to the mission. This article aims to bridge this gap by analysing the relationship between the mission of a company and its members' motivation. It entails an extension of the mission theory, in which three dimensions of mission development are analysed: formal, dynamic and motivational. On the basis of this framework, three forms of mission consistency are considered to explain the effectiveness of mission implementation: authenticity, coherence and integrity.     

The Moderating Effect of Countries’ Development on the Characterization of the Social Entrepreneur: An Empirical Analysis with GEM Data

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - The objective of this paper is to analyze the moderating effect that the level of development of countries exerts on the...     

Bayesian comparison of diagnostic tests with largely non-informative missing data

This work was motivated by a real problem of comparing binary diagnostic tests based upon a gold standard, where the collected data showed that the large majority of classifications were incomplete and the feedback received from the medical doctors allowed us to consider the missingness as non-informative. Taking into account the degree of data incompleteness, we used a Bayesian approach via MCMC methods for drawing inferences of interest on accuracy measures. Its direct implementation by well-known software demonstrated serious problems of chain convergence. The difficulties were overcome by the proposal of a simple, efficient and easily adaptable data augmentation algorithm, performed through an ad hoc computer program.