Minimum Conditional Description Length Estimation for Markov Random Fields

In this paper we discuss a method, which we call Minimum Conditional Description Length (MCDL), for estimating the parameters of a subset of sites within a Markov random field. We assume that the edges are known for the entire graph $G=(V,E)$. Then, for a subset $U\subset V$, we estimate the parameters for nodes and edges in $U$ as well as for edges incident to a node in $U$, by finding the exponential parameter for that subset that yields the best compression conditioned on the values on the boundary $\partial U$. Our estimate is derived from a temporally stationary sequence of observations on the set $U$. We discuss how this method can also be applied to estimate a spatially invariant parameter from a single configuration, and in so doing, derive the Maximum Pseudo-Likelihood (MPL) estimate.Comment: Information Theory and Applications (ITA) workshop, February 201

Eco-innovation practices’ adoption in the automotive industry

Eco-innovation is a construct that is gaining increasing interest from academics and researchers since it is commonly considered in the literature as one of the strategies that allow manufacturing companies not only to significantly reduce the negative impacts on the environment but also the generation of pollutants. However, little is known about the adoption of eco-innovation practices in manufacturing companies, particularly in the automotive industry. Therefore, this research has as main objective to fill this gap in the literature and explore the interdependence between eco-innovation of products, processes and management. The study is conducted through a research framework consisting of 3 measurement scales, 14 items and 3 hypotheses and an extensive review of the literature. A self-administered questionnaire was distributed to a sample of 460 companies in the automotive and auto parts industry in Mexico. Data were analyzed through Confirmatory Factor Analysis, Descriptive Statistics and Structural Equation Modelling. The results obtained show that product eco-innovation, process eco-innovation and management eco-innovation are good indicators for the adoption of eco-innovation practices for companies in the automotive and auto parts industry. The paper addresses a research gap in the academic literature in the eco-innovation field by providing evidence on the interdependence between eco-innovation of products, processes and management and the implementation of their practices in the automotive industry.N/