Promotion Time Cure Rate Model with Bivariate Random Effects

In this article, we consider the inclusion of random effects in both the survival function for at-risk subjects and the cure probability assuming a bivariate normal distribution for those effects in each cluster. For parameter estimation, we implemented the restricted maximum likelihood (REML) approach. We consider Weibull and Piecewise Exponential distributions to model the survival function for non-cured individuals. Simulation studies are performed, and based on a real database we evaluate the performance of our proposed model. Effect of different follow-up times and the effect of considering independent random effects instead of bivariate random effects are also studied.     

Intervention Research as Management Research in Practice: Learning from a Case in the Fashion Design Industry

Research in the field of management and organizational sciences has yielded a deeper understanding of many emerging business issues. However, the relevance of the contributions has been increasingly criticized, in both the academic and public spheres. We propose the intervention research approach – originally developed by the research group at Ecole des Mines de Paris – as a design science approach able to address both the relevance gap issue and the growing complexity of management practice. It is argued that increasing our understanding of management requires research that is more insightful, influential and immediately applicable. This in turn requires closer collaboration between management and researchers during the inquiry process, which is not always easy to achieve. An illustrative case study of an intervention research project focusing on creativity, conducted in Italy in collaboration with a fashion company, demonstrates how intervention research can be rigorous and relevant to practitioners, and how it can advance theoretical knowledge in management science.     

Biopharmaceutical and chemical firms’ R&D disclosure,and cost of equity: The impact of the regulatory regime

Based on the proprietary costs theory, this paper aims to survey whether the regulatory regime (mandatory versus voluntary) of research and development (R&D) narrative disclosures impacts, by the means of a reduced information asymmetry, on the cost of equity capital. In order to construct a disclosure index to investigate the extent and the comprehensiveness of R&D information, the methodology adopted was the content analysis of 77 biopharmaceutical and chemical listed companies’ management reports from eight Western European countries across the period 2005–2009. Hence, we obtained an (unbalanced) panel data of 309 observations. The cost of capital has subsequently been regressed on the disclosure index. Results confirm a larger amount of R&D disclosures whereas information is more regulated, but they do not confirm an inverse relation with the cost of capital.     

Optimal Expediting Policies for a Serial Inventory System with Stochastic Lead Time

In recent supply chains, often operating multiple delivery modes such as standard freight shipping and air is an effective way of addressing both delivery lead time uncertainties and service rates. We propose a model on how to optimally operate multiple delivery modes. We consider a serial supply chain and an expediting option from intermediate installations to the downstream of the chain. The goods move stochastically among the installations and the system faces a stochastic demand. We identify systems that yield simple optimal policies, in which both regular ordering and expediting follow a variant of the base stock policy. Expediting allows the system to be leaner due to the reduced regular order amount. In addition, we provide managerial insights linking expediting, base stock levels, and expediting costs based on analytical and numerical results.     

Some measures of kurtosis and their inference on large datasets

AStA Advances in Statistical Analysis - This paper deals with the estimation of kurtosis on large datasets. It aims at overcoming two frequent limitations in applications: first, Pearson's...     

Can a minimum wage increase have an adverse impact on inequality? Evidence from two Latin American economies

This paper uses a semiparametric model to analyze the impact of an increase in the real minimum wage on inequality in Colombia between 1995 and 1999 and in Paraguay between 1993 and 2000–2001. Simulations suggest that if the employment effects of the minimum wage increase are ignored, the underlying policies would contribute to reduce earnings inequality in Colombia and would be inequality neutral in Paraguay. By considering the drop in wages of those who lost their jobs, simulations suggest that in both countries the policy in question would increase earnings inequality under some assumptions about the employment elasticity of the minimum wage and the new level of earnings unemployed workers rely upon. While these findings do not mean that minimum wage increases in LDCs (Less Developed Countries) necessarily have adverse distributional affects, they suggest that minimum wage policy should be implemented with care depending on how sensitive employment is to wage increases. An erratum to this article can be found at     

Bayesian inference for contingency tables with given marginals

Summary In this paper we introduce a class of prior distributions for contingency tables with given marginals. We are interested in the structrre of concordance/discordance of such tables. There is actually a minor limitation in that the marginals are required to assume only rational values. We do argue, though, that this is not a serious drawback for all applicatory purposes. The posterior and predictive distributions given anM-sample are computed. Examples of Bayesian estimates of some classical indices of concordance are also given. Moreover, we show how to use simulation in order to overcome some difficulties which arise in the computation of the posterior distribution.