Penalized triograms: total variation regularization for bivariate smoothing

Summary.  Hansen, Kooperberg and Sardy introduced a family of continuous, piecewise linear functions defined over adaptively selected triangulations of the plane as a general approach to statistical modelling of bivariate densities and regression and hazard functions. These triograms enjoy a natural affine equivariance that offers distinct advantages over competing tensor product methods that are more commonly used in statistical applications. Triograms employ basis functions consisting of linear 'tent functions' defined with respect to a triangulation of a given planar domain. As in knot selection for univariate splines, Hansen and colleagues adopted the regression spline approach of Stone. Vertices of the triangulation are introduced or removed sequentially in an effort to balance fidelity to the data and parsimony. We explore a smoothing spline variant of the triogram model based on a roughness penalty adapted to the piecewise linear structure of the triogram model. We show that the roughness penalty proposed may be interpreted as a total variation penalty on the gradient of the fitted function. The methods are illustrated with real and artificial examples, including an application to estimated quantile surfaces of land value in the Chicago metropolitan area.     

Correction to: Comparison of joint control schemes for multivariate normal i.i.d. output

AStA Advances in Statistical Analysis - In the original paper, we incorrectly stated that...     

Involvement and emancipation of the worker. Action research in a university hospital

The present action research article is linked to an ergonomics project in a university hospital. The author's proposal is to focus action on the effective worker involvement required for the creation of spaces/mechanisms within organizations where people can enhance cooperation and deliberation on matters relating to work. For this purpose, a committee was introduced to assist in finding problems and solutions directly in work situations, so that workers could experience relative autonomy allowing them to develop procedures and choose tools appropriate to their own real needs. Based on this organizational implementation and on subsequent interviews, the practical results are analyzed and related to employee involvement. One can conclude that workers in all areas of the organization can be active elements for improving working conditions and productivity in companies.     

The workers role in knowledge management and sustainability policies

Based on the concepts of sustainability and knowledge management, this article seeks to identify points of contact between the two themes through an exploratory study of existing literature. The first objective is to find, in international literature, the largest number of papers jointly related to the theme of knowledge management and sustainability. In these documents, the authors looked at the kind of relationship existing between the two themes and what the benefits introduced in organizations are. Based on an ergonomic point of view, the second objective of this article is to analyze the role of the worker (whether at the strategic or operational level) and his importance in this context. The results demonstrate that there is very little literature that addresses the two themes together. The few papers found, however, can be said to show the many advantages of introducing sustainability policies supported by adequate knowledge management. Very little has been studied with regards to the role of workers, which could be interpreted as meaning that little importance is given to the proactive role they may play. On the other hand, there is a high potential for future research in these areas, based on the high level of consideration of workers in knowledge management and sustainability literature, as well as in literature in the areas of ergonomics and sociology.     

Correction to: Vertical and Horizontal Inequality in Ecuador: The Lack of Sustainability

Social Indicators Research - The article Vertical and Horizontal Inequality in Ecuador: The Lack of Sustainability, written Ivan Gachet, Diego F. Grijalva, Paúl A. Ponce and Damián...     

Critical objective function values in linear sum assignment problems

The linear sum assignment problem has been well studied in combinatorial optimization. Because of the integrality property, it is a linear programming problem with a variety of efficient algorithms to solve it. In the given research, we present a reformulation of the linear sum assignment problem and a Lagrangian relaxation algorithm for its reformulation. An important characteristic of the new Lagrangian relaxation method is that the optimal Lagrangian multiplier yields a critical bottleneck value. Lagrangian relaxation has only one Lagrangian multiplier, which can only take on a limited number of values, making the search for the optimal multiplier easy. The interpretation of the optimal Lagrangian parameter is that its value is equal to the price that must be paid for all objects in the problem to be assigned.     

Who knows what? Reconfiguring the governance and the capabilities of the supply chain between physical and digital processes in the fashion industry

Abstract

On the basis of an exploratory multiple-case qualitative longitudinal study in the fashion industry, this article describes how digital technologies enabled choices among different types of supply chain governance. In doing so, this study responds to calls for governance-oriented longitudinal explorations and suggests an alternative path of governance choices in which the digital technologies become the platform that allows a dynamic discourse between outsourcer and outsourcee. Our results show that, when firms decide to leverage their performances through the adoption of information technology, they need to define their knowledge transfer capacities in order to adopt the appropriate type of governance model. With this article, we contribute to the global value chain literature adding to the knowledge transfer dimension.     

Sample size determination and treatment screening in two‐stage phase II clinical trials via ROC curve

In pharmaceutical‐related research, we usually use clinical trials methods to identify valuable treatments and compare their efficacy with that of a standard control therapy. Although clinical trials are essential for ensuring the efficacy and postmarketing safety of a drug, conducting clinical trials is usually costly and time‐consuming. Moreover, to allocate patients to the little therapeutic effect treatments is inappropriate due to the ethical and cost imperative. Hence, there are several 2‐stage designs in the literature where, for reducing cost and shortening duration of trials, they use the conditional power obtained from interim analysis results to appraise whether we should continue the lower efficacious treatments in the next stage. However, there is a lack of discussion about the influential impacts on the conditional power of a trial at the design stage in the literature. In this article, we calculate the optimal conditional power via the receiver operating characteristic curve method to assess the impacts on the quality of a 2‐stage design with multiple treatments and propose an optimal design using the minimum expected sample size for choosing the best or promising treatment(s) among several treatments under an optimal conditional power constraint. In this paper, we provide tables of the 2‐stage design subject to optimal conditional power for various combinations of design parameters and use an example to illustrate our methods.