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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.

The article traces the origins of the competitive intelligence fields and identifies both the practitioner, academic and inter‐disciplinary views on CI practice. An examination of the literature relating to the field is presented, including the identification of the linear relationship which CI has with marketing and strategic planning activities.

Bibliometric assessment of the discipline. Findings reveal the representation of cross disciplinary literature which emphasises the multi‐faceted role which competitive intelligence plays in a modern organization.

The analysis supports the view of competitive intelligence being an activity consisting dominantly of environmental scanning and strategic management literature. New fields of study and activity are rapidly becoming part of the competitive intelligence framework.

The analysis only uses ABI Inform as the primary sources for literature alongside Society of Competitive Intelligence Professionals (SCIP) and Competitive Intelligence Foundation (CIF) publications, particularly the Journal of Competitive Intelligence and Management. A more comprehensive bibliometric analysis might reveal additional insights. Simple counts were used for analytical purposes rather than co‐citation analysis.

Attention is drawn to the need for the integration of additional, complementary fields of study and competitive intelligence practice. It is clear that today's competitive intelligence practitioner cannot afford to rely on what they learned 20 years ago in order to ensure the continued competitive advantage of their firm. A keen understanding of all business functions, especially marketing and planning is advocated.

While there have been bibliographies of competitive intelligence literature there have been few attempts to relate this to the three distinct areas of practice. This article is of use to scholars in assisting them to disentangle the various aspect of competitive intelligence and also to managers who wish to gain an appreciation of the potential which competitive intelligence can bring to marking and business success.

The purpose of this paper is to present a spatial decision support system (SDSS) to be used by the local authorities of a city in the planning and response phase of a disaster. The SDSS focuses on the management of public spaces as a resource to increase a vulnerable population’s accessibility to essential goods and services. Using a web-based platform, the SDSS would support data-driven decisions, especially for cases such as the COVID-19 pandemic which requires special care in quarantine situations (which imply walking access instead of by other means of transport).

This paper proposes a methodology to create a web-SDSS to manage public spaces in the planning and response phase of a disaster to increase the access to essential goods and services. Using a regular polygon grid, a city is partitioned into spatial units that aggregate spatial data from open and proprietary sources. The polygon grid is then used to compute accessibility, vulnerability and population density indicators using spatial analysis. Finally, a facility location problem is formulated and solved to provide decision-makers with an adaptive selection of public spaces given their indicators of choice.

The design and implementation of the methodology resulted in a granular representation of the city of Lima, Peru, in terms of population density, accessibility and vulnerability. Using these indicators, the SDSS was deployed as a web application that allowed decision-makers to explore different solutions to a facility location model within their districts, as well as visualizing the indicators computed for the hexagons that covered the district’s area. By performing tests with different local authorities, improvements were suggested to support a more general set of decisions and the key indicators to use in the SDSS were determined.

This paper, following the literature gap, is the first of its kind that presents an SDSS focused on increasing access to essential goods and services using public spaces and has had a successful response from local authorities with different backgrounds regarding the integration into their decision-making process.

Demand for goods/services has increased in Latin America due to urbanization, leading to a complex delivery system and increased logistical activities. In Quito, the Historic Center and La Mariscal are two zones that face logistical challenges. The objective of this chapter is to analyze the commercial logistic activities related to loading and unloading goods in these zones. To address this urban freight problem, this chapter proposes a solution through the calculation of the optimal number and location of loading and unloading bays in each zone based on actual commercial activity data. First, a delivery survey was completed in each zone regarding frequency and amount of deliveries. Then, based on the data obtained, an optimization model is proposed to determine the optimal number and location of loading and unloading bays. Finally, a simulation model of the delivery process is performed to readjust the bay’s optimal number. A total number of 75 and 98 bays were calculated to serve the total shopping district of a representative square kilometer (km²) of the Historic Center and La Mariscal. This solution aims to minimize the delivery time and the distance for deliveries, improve urban freight transportation, and reduce traffic. This study could be used as a baseline and guide for further research in urban logistics, especially in Latin America, where urban logistics is still under study. This chapter is part of a Research Project of Urban Logistics in Quito, led by Universidad San Francisco de Quito (USFQ), in association with the Megacity Logistics Lab of MIT.

The purpose of this paper is to examine the influence of the emotional intelligence (EI) of the person in charge of making human resource management (HRM) decisions on the adoption of high-performance human resource (HR) practices in small- and medium-sized enterprises (SMEs).

This study takes evidences from 157 HR decision makers in SMEs who autonomously make the decisions in the HR area and were responsible for the HR practices in their firm. The authors used multiple linear regression analysis to test the hypotheses.

Results show that both the EI and the different EI competencies of which it is comprised affect the adoption of various HR practices. Thus, the main theoretical contribution of this work stems from the incorporation of a psychological variable (EI) as an antecedent of HRM. Managers of the SME will find guidance about which emotional competencies are the most important for them to be more successful in their roles and for improving HRM.

First, the sample of firms the authors studied is limited to a specific geographic area in one country – Spain (Canary Islands) – that will necessarily limit generalisation of the results obtained to other populations of SMEs. Researchers should replicate the current model in other geographic areas. Second, and with regard the methodology, researchers could explore other tools to measure EI and emotional competencies. It would be interesting to measure this construct using qualitative analytical techniques, with 360 – or 180 – degree tools. Finally, the current study is cross-sectional in nature, which limits our ability to draw causal inferences from the data. This cross-sectional design prevents us, for example, from analysing EI’s influence on the continued development of high-performance HR practices over time. Future research using longitudinal methodologies to study these variables could provide additional advances in this area. This work makes important contributions to both the literature and the business world. With regard to the theoretical implications, results confirm that EI as a whole, as well as in terms of its specific emotional competencies, affects the decision making related to the adoption of high-performance HR practices, which is known to contribute to the organisational performance.

With regard its practical implications, SMEs’ owners-managers and HR practitioners may find our results and conclusions interesting. Indeed, recommendations in business management have often been accompanied by new approaches in HRM (Kent, 2005), as this study proposes. In particular, managers will find evidence of how a decision-maker’s higher EI propitiates the adoption of high-performance HR practices, thus being able to improve HRM in their SMEs. Moreover, managers will obtain guidance on which emotional competencies are the most important for adopting each HR practice, and so find greater success in their HRM roles. SMEs could organise programmes to develop the HR decision-maker’s emotional competencies, as large firms do for their executives.

Thus, the main theoretical contribution of this work stems from the incorporation of a psychological variable (EI) as an antecedent of HRM. Managers of the SME will find guidance about which emotional competencies are the most important for them to be more successful in their roles and for improving HRM.

Although scarce in the literature of entrepreneurship, the Aztec and Mayas (as well as the Incas), two of the most important civilizations in ancient Latin America, are considered by us as entrepreneurs. This is our departing point for understanding where entrepreneurship was born and built in Latin America. Unfortunately, its indigenous communities still are far behind in terms of labor, quality of life, poverty, and economic opportunities. From the ethnic entrepreneurship theory and after a deep literature review, a model is proposed for our region, a starting point to analyze and understand its processes in our region, thus making an impact on the development of public policies that can ultimately alleviate and improve the condition of this communities, and by going back to its roots, give a clearer picture of the reasons behind the present and future condition of entrepreneurship in Latin America.