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The purpose of this research is to determine the convenience of using a contract model as an integration mechanism for decision-making in a decentralized supply chain of small agricultural producers in a developing country, taking as hypothesis coordinated chain achieves better management. The analysis is based on information obtained by direct inquiry to 99 small producers in the region, about planning, production, marketing and distribution in the chain, supplemented with secondary information sources.

As a methodology an analysis of maturity in the chain based on the Capability Maturity Model Integration is done, whose evaluation is later analyzed as a fuzzy logic model, with the support of the fuzzy logic of the MATLAB toolbox, to study the convenience of the use of the contract against the other mechanisms, and to establish an approximation to the level of readiness of the chain toward integration.

Results obtained show that the small farmer supply chain studied, from a maturity perspective, has a strong disposition for the use of contracts as an integration mechanism.

The supply chain for small producers presents a high dispersion, little consolidated offer capacity and lack of coordination. Limitations in terms of information and criteria unification are a challenge for future research. Results have socioeconomic implications for small producers and can serve as a guide to formulate policies by the governments in Latin American countries.

As practical implications, it can be stated that the use of supply contracts is a real mechanism that can be implemented in this type of chain, to break the mistrust between the echelons and improve the supply chain performance. This research will allow to establish support programs from local governments for the sustainability and improving income of small producers. In addition, contracts will allow to formalize the linkage of small producers to a sustainable commercial network.

Small agricultural producers in developing countries live in unfavorable conditions, with socioeconomic limitations. This work offers an alternative for their productive activity development that will allow them access to marketing chains in a safe way and improve their living conditions.

Previous studies related to the maturity toward the chain integration and fuzzy logic as a hybrid methodology, were not found in the literature, and less even applied to a chain of small agricultural products.

Urban logistics pooling is seen as a serious alternative to imposed urban consolidation centers. However, such strategies are quite new in urban distribution and merit to be evaluated using adapted methods that take into account the group decision nature of resource pooling. This chapter aims to propose, via an experimental collaborative decision support method, to define a grid of indicators and a reference situation database to measure the sustainable performance of urban logistics pooling systems.

The proposed methodology combines a systematic literature analysis of Key Performance Indicators and a group decision support method to choose a suitable set to define a dashboard. First, we identify the main sustainability indicators from an overview of the literature, and class them into the categories of the 4As Sustainable Transport vision (i.e., Awareness, Act and shift, Avoidance, and Anticipation). Then, a group of 20 experts is solicited for an iterative experimental group decision-making method to converge to the concordance of a set of indicators.

The method allowed us to define a hierarchic dashboard agreed by all experts with seven main indicators and nine secondary indicators. Moreover, the experts signaled the need of defining a unified basis of comparison to estimate initial situations. To do this, we proposed a database of urban routes from the French Surveys on Urban Goods Transport.

The proposed dashboard is an example, and to provide a more unified one, the experience has to be iterated using different groups of decision-makers.

This method has the advantage of proposing a dashboard agreed by all involved stakeholders. Therefore, this chapter shows the patterns to reproduce it since the method is able to be replicated in any context of group decision in urban logistics.

The originality of the chapter arises on the use of an experimental group decision method using a group with a majority of practitioners, and to validate it by consensus.

The purpose of this paper is to propose a sustainable dashboard for evaluating the sustainable performance of urban delivery systems from the perspective of operational logistics managers, one of the categories of stakeholders given less consideration by public authorities in their quest for consensus.

First, a synthesis of the main works on the subject is proposed to provide a common grid of economic, environmental and social/societal indicators for sustainable supply chain management (SSCM), after which the method for defining the dashboard is presented. This method is derived from a collaborative decision-support approach and applied to a panel of operational logistics managers. Using a co-constructive method, a group of experts is consulted first separately, then by small groups and then a group restitution and consensus search process is made to find an agreed-upon set of indicators.

The results show a difference between the indicators chosen in the individual phase and those defined in small groups. They also show a gap between classical expert-obtained indicators (mainly made by one or a small group of non-operational experts) and the proposed dashboard, made by and for operational managers.

The originality of the paper is that it addresses two issues (urban logistics evaluation and consensus search) by using methods of natural and active pedagogy and shows by an experimental method the interests and opportunities of collaboration in defining sets of indicators for urban logistics evaluation.

With the increasing urbanization rates in emerging countries such as the ones in Latin America and the Caribbean, urban logistics solutions and initiatives are widely needed. Urban planners often consider only passenger transportation and leave freight transportation unattended, thus increasing externalities and degrading the transportation of goods. This chapter presents three urban logistics solutions, which intend to tackle problems related to urbanization and last mile delivery operations challenges by evaluating location models for loading and unloading bays, urban transfer centers location models, and freight trip generation models. The presented solutions were proposed by several researchers of the Institute of Innovation in Productivity and Logistics CATENA-USFQ over the last four years and remain theoretical at the moment. However, we present estimated results of potential implementations in three districts of Quito: Historic Center, Entertainment District, and Corporate District. This chapter not only presents the mentioned urban logistics solutions in Quito but also gives an overview of the followed methodology, which can be replicated in countries and cities of similar characteristics of the region.

With an increasing urbanization trend over the last decades, urban agglomerations are facing different challenges that affect its inhabitants: pollution, traffic congestion, thriving population growth rates, and economic uncertainty. In the context of Latin America, where less than 20% of its inhabitants live in rural areas and with a projection to decrease to close to 10% by the year 2030, providing solutions to reduce the impact of this increase of population, on at least one of the issues, seems logical.

This study focuses on the urban logistics component to propose a classification method for homogeneous areas, using Factor Analysis (FA) and analysis of variance (ANOVA) as the main supporting tools. The proposed methodology builds up on the square kilometer (KM2) methodology developed by MIT Center for Transportation and Logistics, applying it in a neuralgic section of the downtown area of a mid-sized city in Latin America: Córdoba, Argentina. The selection was made considering the logistic restrictions, commercial density, and the relevance of the area for the city. Our proposed methodology uses relevant variables for urban logistics to perform the statistical analysis. The main goal is to develop a data-driven methodology to identify clusters to guide Córdoba's urban logistics policy and decision-making processes.

The results suggest a clear relationship between the different commercial activities and the location inside the area, splitting the area under study clearly into two main sections with similar overall characteristics and two subsections inside each one of them, which should be considered as a basis for further urban logistic analysis and implementation of specific best practices that fit the particular needs.