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Complex thinking is an important tool for effective decision-making, as it helps people to better understand uncertain situations by considering the multiple variables and relationships involved in a situation, thus being able to identify patterns and connections that would not otherwise be evident. This article presents the results of a bibliometric study to identify academic publications that consider the correlation between decision-making in the business area and complex thinking competency and its sub-competencies. The intention was to have a theoretical horizon that provides a complete overview of the current academic situation regarding the correlation of both professional skills to identify areas of opportunity for new studies. Methodologically, we conducted a literature review using Scopus and Web of Science databases under the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) protocol from which a sample of 339 articles related to both topics was obtained. R, Rstudio, and Bibliometrix were used for the quantitative analysis of the data. The results showed an academic tendency to associate decision-making in business with critical thinking, paying little attention to the other sub-competencies of complex thinking. Furthermore, we found a concentration of research in specific universities and countries, repeating a tendency to study only a few sub-competencies. Overall, this work sheds light on the broad opportunity to link the complex thinking macro-competency with decision-making in business, to provide more extraordinary skills and tools to future professionals.

In recent years, rapid population growth and the accelerated urbanization of cities as a result of different economic, political and social forces have been accentuating the unequal distribution of the different socio-economic strata over its territory. Thus, the geographical concentration of individuals according to their socio-economic status is related to their access to resources and the rules they are subject to in order to access these resources. In this sense, the homogeneous geographical concentration of population strata with low socio-economic status is associated with physically and socially devalued spaces that accentuate and reproduce in an intergenerational manner the conditions of poverty that affect the development of cities. Accordingly, public policies and urban interventions have sought to mitigate the phenomenon of the differentiated distribution of social groups on the territory, known as socio-spatial segregation. Nevertheless, whether by omission or lack of capacity, the bulk of anti-segregation policies in the Latin American region have tended to reinforce patterns of inequality that have existed since colonial times. For this reason, the objective of this doctoral thesis is to analyze the trends and effects on the socio-spatial dynamics caused by urban policies in the city of Guadalajara, Mexico in order to establish proposals for mitigation and improvement. The study analyses the socio-economic structure of the city and its relationship with land markets, with the unequal supply of public goods, as well as with public works spending by the local government administration. The study has carried out various statistical analyses, such as principal component analysis, cluster analysis and regression analysis considering the compositional nature of the data. In this sense, the consideration of the compositional nature of the data in the statistical analysis performed has been a contribution of this thesis to the existing literature on urban stud, En los últimos años, el crecimiento demográfico acelerado y la rápida urbanización de las ciudades producto de distintas fuerzas económicas, políticas y sociales, ha venido acentuando la distribución diferenciada de los distintos estratos socioeconómicos sobre su territorio. Así, la concentración geográfica de los individuos acorde a su estatus socioeconómico se relaciona con el acceso a recursos y con las reglas a las que están sometidos para acceder a estos. En este sentido, la concentración geográfica homogénea de los estratos poblacionales con estatus socioeconómico bajo se asocia con espacios física y socialmente devaluados que acentúan y reproducen de forma intergeneracional las condiciones de pobreza que afecta al desarrollo de las ciudades. Consecuentemente, las políticas públicas e intervenciones urbanas han buscado mitigar el fenómeno de la distribución diferenciada de los grupos sociales sobre el territorio, conocido como segregación socioespacial. Sin embargo, ya sea por omisión o por falta de capacidad, gran parte de las políticas anti segregación en el caso de la región latinoamericana han tendido a reforzar los patrones de desigualdad existentes desde la época colonial. Por tal motivo, el objetivo de esta tesis doctoral consiste en analizar las tendencias y efectos en las dinámicas socioespaciales causadas por las políticas urbanas de la ciudad de Guadalajara, México con la finalidad de establecer propuestas de mitigación y mejora. El estudio realiza un análisis de la estructura socioeconómica de la ciudad y su relación con los mercados de suelo, con la oferta diferenciada de bienes públicos, así como con el gasto de obra pública realizado por la administración gubernamental local. El estudio ha realizado diversos análisis estadísticos, como el análisis de componentes principales, el análisis de conglomerados y el análisis de regresión considerando el carácter composicional de los datos. En este sentido, considerar la naturaleza composicional de los d, Postprint (published version)

Trees provide a broad amount of ecosystem services in urban areas. Although it is well documented that trees are essential for the well-being and livability of cities, trees are often not evenly distributed. Studies have found that urban residents with a deprived socioeconomic status are associated with a lower coverage and access to urban trees in their communities, yet a fair distribution of trees contributes to the sustainability and resilience of cities. In this context, the environmental justice movement seeks to ensure equal distribution of green infrastructure and its benefits throughout a territory. The objective of this study is threefold: (i) to determine whether urban trees in Guadalajara, Mexico, are distributed equally; (ii) to assess the association between urban trees and socioeconomic status; and (iii) to introduce compositional data analysis to the existing literature. Due to the compositional nature of the data, compositional analysis techniques are applied. We believe this novel approach will help define the proper management of data used in the literature. The outcomes provide insights for urban planners working towards the Sustainable Development Goals to help eradicate the uneven distribution of urban trees in cities., Peer Reviewed, Postprint (published version)

The location and context in which people live influences and conditions their opportunities in life. This becomes relevant in a world subject to rapid urban and demographic growth, in which different economic, social, and political forces generate and accentuate disparities in cities. The foregoing generates an unequal distribution of the different social groups in the territory known as socio-spatial segregation. The study of this phenomenon incorporates a large number of variables belonging to different dimensions. Nonetheless, few studies have addressed socio-spatial segregation with a multivariate analysis approach. In addition, the existing studies may have obtained misleading outcomes by not acknowledging the inherent compositional nature of their variables. The objective of the present study is twofold: (i) To assess whether the phenomenon of socio-spatial segregation in Guadalajara, Mexico exists; and (ii) to introduce and stress the use of compositional techniques for the study of socio-spatial segregation. The study applied principal component analysis and cluster analysis considering the compositional nature of census variables, particularly from economic and educative indicators. In addition, the study used geographical information tools to depict and interpret the results. The results are intended to serve in the fulfillment of the Sustainable Development Goals towards inclusive and sustainable cities., Peer Reviewed, Postprint (published version)

Urban green infrastructure such as parks, gardens and trees, provide several ecosystem services and benefits. Particularly trees provide a broad amount of services in urban areas, such as improving air quality, mitigating carbon pollution and heat-island effect, attenuating storm-water floods, reducing noise and serving as habitat for different species among others. Likewise, urban trees provide different social (i.e., social cohesion), economic (i.e., increase in property value), psychological (i.e., stress reduction) and medical (i.e., increase in longevity of life) benefits (Landry, 2009; Roy et al., 2012; Battisti et al., 2019). Although it is well documented that trees are essential for the well-being and health of urban areas and their inhabitants, trees are not evenly distributed in urban areas. Previous studies have found that urban residents with a deprived socioeconomic status are associated with low coverage of urban trees in their communities (Hernández and Villaseñor, 2017; Park and Kwan, 2017; Wang and Qiu, 2018). Therefore, environmental justice seeks to ensure that green infrastructure and its benefits are distributed equally throughout the territory (Anguelovski, 2013; Gould and Lewis, 2017). The objective of this study is to determine whether the distribution of urban trees in the city of Guadalajara, Mexico is distributed equally or not among its colonies and urban districts. The information is obtained from the first and only tree census conducted in the city on June 2018 and treated with geographic information systems (GIS). The attributes of the tree dataset include their location (urban blocks, streets, parks and gardens), heights and diameters of their canopy (Government of Guadalajara, 2019). For the analysis and due to the compositional nature of the data, compositional analysis techniques are applied (see Aitchison, 1986; Pawlowsky-Glahn, et al., 2015; Filzmoser et al., 2018). With this novel approach, we contribute to the existing literat, Peer Reviewed, Postprint (author's final draft)

Different authors have highlighted the internal existing social differences in cities as a consequence of different economic, social and political forces. The mercantile logic that affects urban spaces incentives the dichotomy winners-losers in the current urban landscape and leads to the differentiation and unequal distribution of certain social groups within the urban space. This clear differentiation in distribution of social groups in the urban space has been called socio-spatial segregation. This concept arises from the urban sociology, the first studies were focused on the differentiation of ethnicity and income level to identify the most vulnerable groups and of mitigate their current situation through different policies. A more significant number of variables belonging to different dimensions (social, economic, political and environmental) have been incorporated into the study of this phenomenon, traditionally addressed by different disciplines such as sociology, geography and anthropology. Nonetheless, few studies have addressed it from a multivariate analysis approach. Moreover, the few existing studies with a multivariate statistical analysis ignored or did not know the compositional nature of their data. The objective of the present study is to apply the compositional data analysis in urban studies to better understand socio-spatial segregation in the different urban contexts. Specifically, the analysis of social-spatial segregation considering the compositional nature of the data in the city of Guadalajara, Mexico, is carried out. Socio-economic and socio-educative variables from census data of approximately 13,520 urban blocks grouped in 395 colonias and seven urban districts are used to carry out this study through the most straightforward compositions of two parts. Additionally, Principal Component Analysis (PCA) and cluster analysis are performed to identify the socio-economic distribution within the territory. The analysis is complemented with the, Peer Reviewed, Postprint (published version)