An exact semidefinite programming approach for the max-mean dispersion problem

This paper proposes an exact algorithm for the Max-Mean dispersion problem (\(Max-Mean DP\)), an NP-Hard combinatorial optimization problem whose aim is to select the subset of a set such that the average distance between elements is maximized. The problem admits a natural non-convex quadratic fractional formulation from which a semidefinite programming (SDP) relaxation can be derived. This relaxation can be tightened by means of a cutting plane algorithm which iteratively adds the most violated triangular inequalities. The proposed approach embeds the SDP relaxation and the cutting plane algorithm into a branch and bound framework to solve \(Max-Mean DP\) instances to optimality. Computational experiments show that the proposed method is able to solve to optimality in reasonable time instances with up to 100 elements, outperforming other alternative approaches.     

Testing for Spatial Autocorrelation: The Regressors that Make the Power Disappear

We show that for any sample size, any size of the test, and any weights matrix outside a small class of exceptions, there exists a positive measure set of regression spaces such that the power of the Cliff–Ord test vanishes as the autocorrelation increases in a spatial error model. This result extends to the tests that define the Gaussian power envelope of all invariant tests for residual spatial autocorrelation. In most cases, the regression spaces such that the problem occurs depend on the size of the test, but there also exist regression spaces such that the power vanishes regardless of the size. A characterization of such particularly hostile regression spaces is provided.     

Potential and ‘Power of a Collectivity to Act’<Superscript>*</Superscript>

This paper connects two notions: Hart and Mas-Colell’s ‘potential’, related to the value of coalitional games, and Coleman’s earlier notion of ‘power of a collectivity to act’, related to the easiness to make decisions by means of a voting rule. ^*This research has been supported by the Spanish Ministerio de Ciencia y Tecnología under project BEC2000-0875, and by the Universidad del País Vasco under project UPV/EHU000031.321-HA-7918/2000. The first author acknowledges financial support from the Spanish Ministerio de Ciencia y Tecnología under the Ramón y Cajal programme.     

The moderating effect of product complexity on new product development and supply chain management integration

The purpose of this study is to investigate whether product complexity moderates the impact of integration programs in both new product development (NPD) and supply chain (SC) management on operational performance. Results are based on statistical analyses of data collected from an international sample of manufacturing firms through the fifth edition of the International Manufacturing Strategy Survey (IMSS 5). The main findings are that NPD and SC integration do have an impact on performance, while product complexity alone has not. When considering the moderating effect, complexity has no impact on NPD integration, while there is a negative moderating impact on SC integration. This study bridges together different streams of research, showing how both NPD and SC integration allow managing product complexity while improving performance.     

Conditional and predictive probability integral transforms

The conditional probability integral transform, used in goodness-of-fit tests, is compared with its Bayesian counterpart, the predictive probability integral transform, and it is shown that under suitable conditions, in the presence of an adequate group structure, they yield the same transformed random variable, usually uniform on the unit interval.     

Estimability and linearity in normal regression

In the normal regresion model, a relation between the notion of estimability of a distribution and the existence of a linear function of the observations with some desired property is studied. Several definitions of estimability are shown to be equivalent.     

Linking global value chains and supply chain management: evidence from the electric motors industry

The global value chain (GVC) framework and its central concept of governance are increasingly advocated as powerful tools for interpreting managerial issues with particular reference to global supply chain (SC) management. However, a gap still exists about how the GVC concepts, which have been developed at the industry level, can be applied at the company level. The aim of this work is therefore to investigate how the concepts of GVC structure and governance are related to the way the SC is managed. Several research propositions drawn from the literature are investigated by means of seven case studies in the electric motors industry. The results show that the GVC can be a useful framework for understanding and deploying SC management at the company level. Moreover, the analysis of the governance modes provides an effective tool to explain the existing degree of technological and operational collaboration in the SC. Finally, we show the importance of considering such contextual factors as company size and the competitive priorities of the company to move seamlessly between the GVC, at the industry level, and SC management, at the company level.     

Challenging the courtesy bias interpretation of favorable clients' perceptions of family planning delivery

Favorable client perceptions of provider's interpersonal behavior in contraceptive delivery, documented in clinic exit questionnaires, appear to contradict results from qualitative evaluations and are attributed to clients' courtesy bias. In this study, trained simulated clients requested services from Ministry of Health providers in three countries. Providers excelled in courteousness/respect in Peru and Rwanda; in India, providers were less courteous and respectful when the simulated clients chose the pill. Privacy and two-way communication were less prevalent in all three countries. The findings challenge the courtesy bias interpretation. Global results from qualitative studies may have expressed the views of the minority of clients who are not treated well by providers.     

Distortions of Asymptotic Confidence Size in Locally Misspecified Moment Inequality Models

This paper studies the behavior, under local misspecification, of several confidence sets (CSs) commonly used in the literature on inference in moment (in)equality models. We propose the amount of asymptotic confidence size distortion as a criterion to choose among competing inference methods. This criterion is then applied to compare across test statistics and critical values employed in the construction of CSs. We find two important results under weak assumptions. First, we show that CSs based on subsampling and generalized moment selection (Andrews and Soares (2010)) suffer from the same degree of asymptotic confidence size distortion, despite the fact that asymptotically the latter can lead to CSs with strictly smaller expected volume under correct model specification. Second, we show that the asymptotic confidence size of CSs based on the quasi‐likelihood ratio test statistic can be an arbitrary small fraction of the asymptotic confidence size of CSs based on the modified method of moments test statistic.     

A comparative assessment of track plates to quantify fine scale variations in the relative abundance of Norway rats in urban slums

Norway rats (Rattus norvegicus) living in urban environments are a critical public health and economic problem, particularly in urban slums where residents are at a higher risk for rat borne diseases, yet convenient methods to quantitatively assess population sizes are lacking. We evaluated track plates as a method to determine rat distribution and relative abundance in a complex urban slum environment by correlating the presence and intensity of rat-specific marks on track plates with findings from rat infestation surveys and trapping of rats to population exhaustion. To integrate the zero-inflated track plate data we developed a two-component mixture model with one binary and one censored continuous component. Track plate mark-intensity was highly correlated with signs of rodent infestation (all coefficients between 0.61 and 0.79 and all p-values?<?0.05). Moreover, the mean level of pre-trapping rat-mark intensity on plates was significantly associated with the number of rats captured subsequently (Odds ratio1.38; 95 % CI 1.19–1.61) and declined significantly following trapping (Odds ratio 0.86; 95 % CI 0.78–0.95). Track plates provided robust proxy measurements of rat abundance and distribution and detected rat presence even when populations appeared ‘trapped out’. Tracking plates are relatively easy and inexpensive methods that can be used to intensively sample settings such as urban slums, where traditional trapping or mark-recapture studies are impossible to implement, and therefore the results can inform and assess the impact of targeted urban rodent control campaigns.