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This article aims to analyze how gender and decision-making styles of Chief Executive Officers (CEOs) of Small and Medium Enterprises (SMEs) impact the financial performance of the firms they manage.

Data were obtained for 2017 for 185 SMEs in Chile, an emerging economy, including firm information, CEO's sociodemographic characteristics and CEOs' decision-making styles. Generalized Least Squares (GLS) models were estimated to explain the influence of gender and decision-making styles on firm performance, controlling for a series of covariates. To test whether gender moderates the effect of decision-making styles on firm performance, interaction terms were included. Furthermore, models were subject to several robustness procedures, with no significant differences in results.

The authors find evidence of significant relationships for both gender and the avoidant style. Likewise, the authors find evidence of interaction effects between gender and decision-making styles, particularly between gender and the dependent style.

Findings contribute to prior research by analyzing the relationship between CEO gender and SME performance in the context of a Latin American emerging economy; by providing evidence of the impact of decision-making styles on the financial performance of SMEs; and by examining how a specific decision-making style, namely the dependent style, operates differently according to CEO gender, shedding some light on its ambiguous character as described by prior research. For policymakers and authorities, findings indicate the importance of incorporating women to SMEs and supporting their way towards higher management.

Esta investigación analiza cómo el género y los estilos de toma de decisiones de los gerentes generales (CEOs) de las pequeñas y medianas empresas (PYMEs) impactan en el desempeño financiero de las empresas que administran.

Se obtuvieron datos del año 2017 para 185 PYMEs ubicadas en Chile, una economía emergente, incluyendo información de la empresa, así como características sociodemográficas y estilos de toma de decisiones de los gerentes generales. Se estimaron modelos de Mínimos Cuadrados Generalizados (GLS) para explicar la influencia del género y los estilos de toma de decisiones en el rendimiento de la empresa, controlando por una serie de covariables. Para determinar si el género modera el efecto de los estilos de toma de decisiones en el rendimiento de la empresa, se incluyeron términos de interacción. Además, los modelos fueron sometidos a varios procedimientos de robustez, sin encontrar diferencias significativas en los resultados.

Los autores encuentran evidencia de relaciones significativas tanto para el género como para el estilo evitativo. Asimismo, los autores encuentran evidencia de efectos interacción entre el género y estilos de toma de decisiones, particularmente entre el género y el estilo dependiente.

Los hallazgos contribuyen a investigaciones anteriores al analizar la relación entre el género del CEO y el rendimiento de las PYMEs en el contexto de una economía latinoamericana emergente; al proporcionar evidencia del impacto de los estilos de toma de decisiones en el rendimiento financiero de las PYMEs; y al examinar cómo un estilo de toma de decisiones específico, a saber, el estilo dependiente, opera de manera diferente según el género del CEO, esclareciendo su carácter ambiguo tal como ha sido descrito en investigaciones anteriores. Para las autoridades y los responsables de políticas, los hallazgos indican la importancia de incorporar mujeres a las PYMEs y apoyarlas en su ascenso hacia la alta administración.

In this paper the authors study how sociodemographic characteristics and personality traits of the Chief Executive Officer (CEO) impact financial performance in small and medium enterprises (SMEs) in an emerging economy such as Chile.

The authors applied a questionnaire to 185 Chilean SME CEOs during 2017 concerning sociodemographic characteristics (gender, age, experience and marital status), personality traits (extraversion, responsibility, openness to experience, agreeableness, and neuroticism) and firm characteristics.

The authors find that some sociodemographic characteristics (gender and age) significantly impact SME performance. The authors find no significant connection between personality traits and firm performance.

This paper contributes to the business literature by investigating how sociodemographic variables and personality traits of the CEO are related to SME financial performance; by providing new evidence on the relationship between CEO characteristics and firm performance, mostly centered on developed economies, in the context of an emerging economy; and allowing for a better understanding of how CEO decisions impact firm performance.

Este artículo estudia cómo las características sociodemográficas y los rasgos de personalidad del gerente general (CEO) afectan el desempeño financiero de Pequeñas y Medianas Empresas (PYMEs) en una economía emergente como Chile.

Se aplicó un cuestionario a 185 gerentes generales de PYMEs chilenas en 2017 acerca de sus características sociodemográficas (género, edad, experiencia, estado civil), rasgos de personalidad (extraversión, responsabilidad, apertura a la experiencia, amabilidad y neuroticismo) y características de la empresa.

Se encontró que ciertas características sociodemográficas (género, edad) afectan significativamente el desempeño de las PYMEs. No se encontraron asociaciones significativas entre rasgos de personalidad y desempeño de la empresa.

Este trabajo contribuye a la literatura de negocios al investigar cómo las variables sociodemográficas y los rasgos de personalidad del gerente general se relacionan con el desempeño financiero de las PYMEs; al entregar nueva evidencia sobre la relación entre características del gerente general y el desempeño de la empresa, mayoritariamente centrada en economías desarrolladas, en el contexto de una economía emergente; y al permitir una mejor comprensión de cómo las decisiones del gerente general afectan el desempeño de las empresas.

The purpose of this paper is to investigate how chief executive officer (CEO) gender relates to financial performance in small and medium enterprises (SMEs) in a Latin American emerging economy like Chile.

The authors apply a questionnaire on a sample of 188 SMEs in Chile in 2017. The authors apply multiple ordinary least squares regression models to test the effects of CEO gender on SME performance using the industry location indicators to account for unobserved heterogeneity in the sample. As a robustness test the authors use hierarchical regression analysis.

The authors find a positive relationship between the presence of female CEOs and firm performance. Then, when probing whether the sociodemographic characteristics of the CEO are related to firm performance or moderate the gender-performance relationship, the authors do not find statistically significant evidence that these types of characteristics affect the performance of SMEs.

To the best of the authors’ knowledge, the present study is the first to investigate the relationship between CEO gender and financial performance of SMEs in an emerging Latin American economy. The study contributes to the general literature by reporting comparable evidence with studies in developed economies.

The effects of the COVID-19 pandemic on cities have transformed the lives of urban societies across the globe. One of such effects has been the redefinition of access and urban mobility patterns, exposing divides and inequalities along the lines of class, gender and social positions. In Latin America, long-term lockdowns and widespread containment-oriented restrictions have deepened already acute conditions of poverty and deprivation. Low-income and socially vulnerable households and individuals in countries such as Colombia find themselves unable, or in a disadvantaged position, to work from home, access goods and services securely and avoid transport modes that increase exposure to contagion. This chapter examines inequalities in urban mobility and access to essential opportunities in urban settings in Colombia, through data collected from 3,900 respondents to a web survey organised during the national lockdown in the country in April 2020. The chapter presents a Latent Class Analysis model exploring how intersecting differences in class, gender, ethnicity, age and other relevant socioeconomic characteristics, influence the degree of adaptability and capacity to adapt to the challenging conditions posed by COVID-19 for physical travel and carrying out everyday activities. Building on three distinct classes of mobility and access-related conditions, the chapter reflects on structural inequalities associated with Colombian cities’ urban form, functional and productive structures and its wide social gaps. The chapter builds on empirical findings to reflect on urban policy and discuss avenues for addressing social and spatial inequalities worsened by the pandemic.

According to the Colombian Labour Ministry, in 2015, 750,000 persons officially worked as household employees. Ninety-eight per cent of these employees are women who tend to live in Bogotá’s (southern) urban fringe and travel to the city’s wealthier north on a daily basis. Yet public transportation in the Colombian capital is subject to stratification. Besides overcrowding and delays, petty crime and sexual harassment, fringe areas remain underserved. Based on ethnographic data, in this chapter, the authors discuss findings from a 3-year research project on female household employees’ subjective experience of space. Specifically, the authors explore their capacity (motility) to be mobile. This perspective breaks with the limits of bounded categories such as ‘urban’, ‘neighbourhood’ or ‘class’, to highlight their situational and spatial mutability. Moreover, an investigation of motility includes people’s potential to move as well as their subjective experiences of mobility. The research shows how gender intersects with local labour regimes and infrastructure to negatively affect women’s mobility. Urban stratification is not only a question of locale of residence and access to services, but importantly (re)produced in the household employees’ subjective experience of their daily commute, which they describe as suffering. In their limited spare time, female household employees abstain from travelling, effectively curbing their active appropriation of urban space. The research thus illuminates how spatial, social and economic dimensions mutually interact to impact on the women’s lives and possibilities.

The spatial development of urban areas affects the characteristics of landscape as well as people’s aesthetic perception of it. Specifically, sprawl results in an urban morphology which is diametrically opposed to the compact city model and which assumes several kinds of patterns: for example “striped”, “ribbon” or “leapfrogged” urban development. Assessing urban morphology in spatial terms is crucial to urban policy, while landscape metrics are the key to a comprehensive understanding of different urban development patterns. The purpose of this paper to design and test an urban morphology indicator (UMI) for the Lombardy Regional Landscape Plan.

The paper describes an UMI that can be used to identify the heterogeneity of built-up patterns according to urban porosity, fragmentation and patch shape. This UMI is a result of Esri ArcGIS 10.3 “grouping analysis” which works by applying a spatial statistical metric for clustering geometries in a given geographical area.

Morphological analysis was used in regional urban development policies with a view to minimising impact on surrounding ecosystems and preserving the natural environment and landscape. It defines 28 different urban morphology patterns in the region, which are divided into systems, polarities and urbanised units.

The proposed methodology differs from those traditionally used in qualitative/descriptive landscape planning and supports the identification of morphological features with quantitative statistical and spatial data, allowing a fine-scale assessment of complex metrics.

The purpose of this paper is to present a variational mesh h-adaption approach for strongly coupled thermomechanical problems.

The mesh is adapted by local subdivision controlled by an energy criterion. Thermal and thermomechanical problems are of interest here. In particular, steady and transient purely thermal problems, transient strongly coupled thermoelasticity and thermoplasticity problems are investigated.

Different test cases are performed to test the robustness of the algorithm for the problems listed above. It is found that a better cost-effectiveness can be obtained with that approach compared to a uniform refining procedure. Because the algorithm is based on a set of tolerance parameters, parametric analyses and a study of their respective influence on the mesh adaption are carried out. This detailed analysis is performed on unidimensional problems, and a final example is provided in two dimensions.

This work presents an original approach for independent h-adaption of a mechanical and a thermal mesh in strongly coupled problems, based on an incremental variational formulation. The approach does not rely on (or attempt to provide) error estimation in the classical sense. It could merely be considered to provide an error indicator. Instead, it provides a practical methodology to adapt the mesh on the basis of the variational structure of the underlying mathematical problem.

This paper tries to explore the possibilities of developing sustainable, community-based tourism (CBT) in Boa Vista in Cape Verde, Africa. Island territories are generally considered preferential tourist destinations. However, the negative effects of tourism in these destinations should not be overlooked, among them environmental concerns and impacts on the culture of the island’s inhabitants. The development of CBT takes on special relevance, as it based on planning schemes in conjunction with the local community who share the positive effects derived from tourism.

The methodology used consisted in designing two surveys: one focusing on the supply side and another on the demand side of tourism to define and analyse the current status of this sector in Boa Vista. The survey on tourism supply was distributed among a panel of experts formed by tourism service providers located in Boa Vista. The statistical results of the responses and the discussion carried out by the panel of experts permitted the development of a SWOT matrix. The survey on demand was administered to foreign tourists in different parts of the island. A total of 202 valid surveys were obtained.

The main results of the fieldwork are twofold. On the supply side of tourism, the community is making an enormous effort to actively participate in the development of sustainable tourism, efforts which are often constrained by the geographical barriers of Boa Vista (sandy soil, poor accessibility to other islands) and the institutional and political situation of the island. As regards the demand side of tourism, the vast majority of tourists stay at the island’s all-inclusive resorts, whereas few tourists require the services provided by the community, mainly because they are unaware that such services exist.

Certain island destinations are more appropriate for tourists wishing to flee mass tourism enclaves due to their natural environment, relative isolation and the traditional culture of their inhabitants. For this reason, it is important to develop a CBT model for these destinations in which initiatives are planned in conjunction with members of the local community who participate in decision-making processes and benefit equally from the positive effects of tourism. Although several case studies have been reported in the research on CBT initiatives, few studies have been carried out on CBT in island territories. This is the main contribution in this paper.

The purpose of this paper is to propose an integrated fuzzy approach to determine important universal usability problems (UUPs) by providing experts who behave like real users and to establish a work plan to correct the most important ones.

In this study, a fuzzy multi-criteria decision-making approach with three stages is proposed for the evaluation of universal usability. At the first stage, UUPs are identified by performing modified heuristic evaluation, and severity rating of each problem is determined by experts. At the second stage, critical problems are specified by applying the fuzzy Delphi considering these severity ratings. At the third stage, Fuzzy Decision Making Trial and Evaluation Laboratory approach is applied to prioritize critical problems as sub and main criteria. An illustrative example related to emergency service is performed to apply the proposed approach.

Results showed that the elevator button design, the elevator emergency button design and the position of the floor signboard are the first three problems that should be primarily improved as sub-criteria. In terms of main criteria, equitable use, simple and intuitive use, and perceptible information are the first three main criteria that should be improve in emergency service.

This study is original in terms of methodology and providing a new perspective for building design evaluation. The results can help the designers to see the UUPs in buildings, to focus the most important UUPs and to establish improvement ranking. These advantages provide time and cost-effective design improvement actions.

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.