Manufacturing feature-based cost management system: a case study in Brazil

Feature costing is a topic of recent discussion related to cost management systems (CMSs) aimed at understanding how product features influence production process costs. It raises as a key issue in mass customisation environments where a single product model can present hundreds of menu options. In this study, we explore the concept of feature costing beyond the use of activity-based costing (ABC). We propose a CMS based on features and common elements as costing objects instead of products. In our model, we use the unit of production effort method to organise the direct manufacturing costs, ABC method to address the indirect cost and the standard methods to compute raw materials costs. We illustrate the method in the production of bus seats in a Brazilian manufacturing company. This study gives different perspectives to the international academic community on the use of a different CMS used by many Brazilian companies.     

Bayesian Inference in Dynamic Disequilibrium Models: An Application to the Polish Credit Market

We propose a Bayesian approach for inference in a dynamic disequilibrium model. To circumvent the difficulties raised by the Maddala and Nelson (1974 Maddala , G. , Nelson , F. ( 1974 ). Maximum likelihood methods for models of markets in disequilibrium . Econometrica 42 ( 6 ): 1013 – 1030 .[Crossref], [Web of Science ®] , [Google Scholar]) specification in the dynamic case, we analyze a dynamic extended version of the disequilibrium model of Ginsburgh et al. (1980 Ginsburgh , V. , Tishler , A. , Zang , I. ( 1980 ). Alternative estimation methods for two regime models . European Economic Review 13 : 207 – 228 .[Crossref], [Web of Science ®] , [Google Scholar]). We develop a Gibbs sampler based on the simulation of the missing observations. The feasibility of the approach is illustrated by an empirical analysis of the Polish credit market, for which we conduct a specification search using the posterior deviance criterion of Spiegelhalter et al. (2002 Spiegelhalter , D. J. , Best , N. G. , Carlin , B. P. , Van Der Linde , A. ( 2002 ). Bayesian measures of complexity and fit . Journal of the Royal Statistical Society, Ser. B 64 : 583 – 639 .[Crossref] , [Google Scholar]).     

Asymptotic normality of frequency polygons for random fields

The purpose of this paper is to investigate asymptotic normality of the frequency polygon estimator of a stationary mixing random field indexed by multidimensional lattice points space Z^N$Z^N$. Appropriate choices of the bandwidths are found.     

Comparing Immigration Policies: An Overview from the IMPALA Database

This paper introduces a method and preliminary findings from a database that systematically measures the character and stringency of immigration policies. Based on the selection of that data for nine countries between 1999 and 2008, we challenge the idea that any one country is systematically the most or least restrictive toward admissions. The data also reveal trends toward more complex and, often, more restrictive regulation since the 1990s, as well as differential treatment of groups, such as lower requirements for highly skilled than low‐skilled labor migrants. These patterns illustrate the IMPALA data and methods but are also of intrinsic importance to understanding immigration regulation.     

Gambling Problems Among Community Cocaine Users

Cocaine use is highly prevalent and a major public health problem. While some studies have reported frequent comorbidity problems among cocaine users, few studies have included evaluation of gambling problems. This study aimed to estimate the prevalence of gambling problems and compare those who were at-risk gamblers with non-problem gamblers in terms of mental health problems, substance use problems, and some risk factors (i.e. family antecedents, erroneous perceptions and coping strategies) among individuals who smoke or inject cocaine. A total of 424 smoked or injected cocaine users recruited through community-based programs in Montreal (Quebec) completed the questionnaire, including the Canadian Pathological Gambling Index, the Composite International Diagnostic Interview, the CAGE, and the Severity Dependence Scale. Of the sample, 18.4 % were considered at-risk gamblers, of whom 7.8 % had problems gambling and 10.6 % were moderate-risk gamblers. The at-risk group was more likely to have experienced a recent phobic disorder and alcohol problems than the non-problem group. A multivariate analysis showed that, compared to those who were non-problem gamblers, the at-risk ones were more likely to have lost a large sum of money when they first started gambling, believed that their luck would turn, and gambled in reaction to painful life events. These results indicate the need to include routines for screening to identify gambling problem among cocaine users.     

The contribution of opinion surveys in forecasting aggregate demand in the four main EC countries

This paper presents for the four main EC countries forecasting models of aggregate demand components based on various tendency surveys. Its objective is to work out practical models both in terms of data requirement and computation as the models are to be used regularly for very short-term forecasting. In spite of a great simplicity of the specifications, the regression results prove quite acceptable. Forecasting exercises compare reasonably well with the results of more elaborate procedures.     

Profiling Donors of Blood,Money, and Time

Understanding donor profiles is crucial for donor relationship management. Whereas previous research has focused on profiling blood, money, or time donor segments separately, we define seven donor profiles based on their former donation behavior for blood, money, and time donation and compare them to non‐donors. Relying on representative data from the German Socio Economic Panel, we use an extensive set of characteristics that include sociodemographic, psychographic, health‐related, and geographical measures and simultaneously investigate profiles of donors for single and multiple donation forms and non‐donors by means of a multinomial logistic model. Our results reveal valuable insights for donor acquisition and retention strategies of nonprofit organizations along the identified profiling characteristics of donor segments. By this, our findings help nonprofit organization managers to better target single and multiple donors across three donation forms.