Site selection for companies is a complex and unstructured problem that must be analyzed carefully and properly, since a localization error could drive to bankrupt. This problem has been discussed widely and effectively using multi-attribute methods in a manufacturing context, but it has been little studied in agribusiness. The goal of this work is a methodological approach oriented to evaluate optimal locations of new agri-food warehouses. Furthermore, a literature review is developed, analyzing the location problem and the attributes and techniques most widely used applied to agribusiness, and a case-study is presented in order to exemplify the methodological proposal. The multi-attribute technique called Analytic Hierarchy Process has been selected as the basis for the research, and it is applied to the real case study analyzed: the selection of a site for a new banana distribution warehouse. Six generic criteria have been analyzed: accessibility to the area, distance, cost, security of the region, local acceptance of the company, and its needs. The process includes the assignment of attributes to each one of the generic criteria, as well as the assessment of their importance levels. Three different areas of Guadalajara, Jalisco, and Mexico DF have been evaluated for the case-study, and the methodological proposal has been utilized to determine the best option

Managers implement several Green Supply Chain Management (GSCM) practices to improve sustainability and economic performance, such as environmental management systems (EMS), eco-design (ED), source reduction (SR) and attending to external environmental management (EEM) requirements; however, the relationship among them requires a deep study. This paper reports the case of the Mexican maquiladora industry, analyzing the main relationships among GSCM practices with environmental impact (EI) and environmental cost savings (ECS). The analysis reports three structural equation models (SEM) developed as simple, second-order, and mediating models. Those relationships are tested using 160 responses to a survey applied to the Mexican maquiladora industry and with partial least squares algorithms (PLS), where conditional probabilities for different scenarios in latent variables are also reported. Findings indicate that EMS has a direct effect on EI (β = 0.442) and ECS (β = 0.227), indicating that EMS reduces EI and cost associated with the production process; however, ED has no direct effect on EI (β = 0.019) and ECS ((β = 0.006), and it can be due to the maquiladora nature as foreign companies focused on manufacturing and not to product design.