Did the Military Interventions in the Mexican Drug War Increase Violence?

We analyze publicly available data to estimate the causal effects of military interventions on the homicide rates in certain problematic regions in Mexico. We use the Rubin causal model to compare the post-intervention homicide rate in each intervened region to the hypothetical homicide rate for that same year had the military intervention not taken place. Because the effect of a military intervention is not confined to the municipality subject to the intervention, a nonstandard definition of units is necessary to estimate the causal effect of the intervention under the standard no-interference assumption of stable-unit treatment value assumption (SUTVA). Donor pools are created for each missing potential outcome under no intervention, thereby allowing for the estimation of unit-level causal effects. A multiple imputation approach accounts for uncertainty about the missing potential outcomes.     

Exploiting the balanced scorecard in the Operations Department: the Ducati Motor Holding case

The literature has widely discussed how to measure manufacturing performance. However, even though several indicators have been proposed, manufacturing reporting systems still suffer from a number of problems, which according to recent contributions, can be solved through the adoption of integrated performance measurement systems (PMSs). This article aims at understanding whether such integrated PMSs–namely the balanced scorecard–can actually solve the problems, which usually affect the reporting system of the Operations Department. The article presents a case-study developed in Ducati Motor Holding and then outlines the main conclusions and managerial implications. The empirical analysis demonstrates that the key benefits brought about by the balanced scorecard concern a higher responsiveness of the decision-making process and more intense cooperation among all units related to operations management (namely, manufacturing, logistics, quality management, procurement, maintenance).     

Confidence regions for the stationary point of a quadratic response surface based on the asymptotic distribution of its MLE

Response surface methodology aims at finding the combination of factor levels which optimizes a response variable. A second order polynomial model is typically employed to make inference on the stationary point of the true response function. A suitable reparametrization of the polynomial model, where the coordinates of the stationary point appear as the parameter of interest, is used to derive unconstrained confidence regions for the stationary point. These regions are based on the asymptotic normal approximation to the sampling distribution of the maximum likelihood estimator of the stationary point. A simulation study is performed to evaluate the coverage probabilities of the proposed confidence regions. Some comparisons with the standard confidence regions due to Box and Hunter are also showed.     

A Systematic Literature Review on Recent Lean Research: State‐of‐the‐art and Future Directions

Lean management (LM) has attracted the interest of scientists and practitioners since 1990, when Womack et al. (Womack, J.P., Jones, D.T. and Roos, D. (1990). The Machine that Changed the World. New York, NY: Rawson Associates) popularized the Japanese manufacturing approach aimed at eliminating waste to improve operational performance and customer satisfaction. Over the years, the lean concept has evolved becoming a managerial paradigm applicable to different sectors and processes with impressive results. This heterogeneity of implementations and settings makes the recent LM literature diverse and fragmented, and an extensive analysis of the latest contributions on this field is lacking. To address this gap, the authors propose a systematic literature review (SLR) of 240 articles published in 25 peer‐reviewed academic journals from January 2003 to December 2015. The purpose is to analyse the recent trends in this area and to provide a framework that organizes lean researched issues into mature, intermediate and nascent, based on their position in the research life cycle. Starting from the gaps that the SLR highlights, the authors suggest conducting lean research in the following directions: (a) grounding lean studies on existing managerial theories; (b) addressing service settings such as banking/finance, public sector and education; (c) exploring the role of national culture through cross‐country comparisons; (d) defining and conceptualizing ‘lean‐x’ processes; (e) understanding the relationships between lean and safety/environmental issues, and (f) unveiling the effects on social outcomes. Finally, the proposed framework helps scholars find issues not sufficiently explored that require theory‐building research (to move from nascent to intermediate) or theory‐testing research (to move from intermediate to mature).     

A reference prior for the analysis of a response surface

Standard response surface methodology employs a second order polynomial model to locate the stationary point ξ$\mathit{\xi }$ of the true response function. To make Bayesian analysis more direct and simpler, we refer to an alternative and equivalent parametrization, which contains ξ$\mathit{\xi }$ as parameter of interest. The marginal reference prior of ξ$\mathit{\xi }$ is derived in its general form and particular cases are also given in detail, showing the Bayesian role of rotatability.     

Marketing Archetypes: Applying Jungian Psychology to Marketing Research

In the current situation of growing information overload, individuals are gradually becoming less sensitive to traditional marketing communications. For this reason, traditional marketing research models are no longer capable of giving useful insights to management. This calls for new approaches that can grasp the inner meaning of consumer behaviors and evaluate their relevance. To this end, a new multidisciplinary approach is needed to interpret complex behavioral patterns so as to gain deeper and more effective insights into customers and to understand their behavioral patterns. In this paper, following a short introduction to the basic concepts of Jung's analytical psychology and their relevance for marketing, we propose the use of the Jungian archetypes to implement a market research model, considering the case of an Italian research company's development of the Archetipus® model.