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This chapter presents a critical examination of the interaction between concepts such as equity and accessibility in a framework of sustainable and inclusive urban development. The analysis compiles a series of reflections that build on previous research that focusses on the role of transport as enabler of opportunities for material and social capital, healthcare and leisure, which contribute to human development and well-being. The research discusses accessibility metrics for mandatory and non-mandatory travel in the context of current global agendas for social and development policies. It also introduces methodological reflections in relation to the analysis of accessibility indices from an equity perspective highlighting the role of equity metrics such as the Palma ratio and Lorenz curves. The authors link accessibility and urban development seeking to inform current approaches for policy development and assessment in a context of high manifested inequity. The research is set in the context of the Bogotá Metropolitan Region, a paradigmatic case of transport development and policy in the Global South. The findings seek to contribute to present transport policy and practice, providing relevant insights to support actions that redistribute accessibility to opportunities and questioning some of the paradigms of mainstream transport planning in cities like Bogotá, suggesting a more relevant role of transport policy as a potential engine of equity and social development.

The purpose of this paper is to identify demographic differences based on how users interact with web applications. The research is needed to develop future systems able to adapt the representation of online information to the user’s specific needs and preferences improving its usability. The following question guides this quest: is there a direct relationship between age and/or gender and interaction?

GOMS (goals, operators, methods, and selection rules) analysis was used to reduce complex interaction tasks into basic operators like pointing, dragging, typing, etc. An experiment was designed to analyse the user performance in the use of these operators through five complex tasks: point-and-click, drag-and-drop, text selection, text edition and menu selection. The sample comprises 592 individuals which took part in the experiment. The performance was analysed using multivariate regression analysis. User laterality and the the user experience were used as control variables.

The factors studied are significant enough to support user classification. The analysis evidenced that men performed significantly better than women when executing interaction pointing and dragging GOMS’s operators, but no significant differences arose with regard to the performance in the typing operators. Older users performed worse in all the interaction tasks. No significant performance differences were detected between left and right-handed users.

The study pretends to lay the ground for developing artificial intelligence-based classification systems (e.g. neural networks, decision trees, etc.) able to detect significant differences in user performance, classifying users according to their age, gender and laterality.

This user profiling would drive the organisation, selection and representation of the online information according to the specific preferences and needs of each user. This would allow the design of new personalisation algorithms able to perform dynamic adaptation of user interfaces in order to improve the usability of online information systems.

This work extends previous research on user performance under a new approach and improved accuracy. First, it relies on the combined and simultaneous analysis of ageing and gender and the use of user laterality and experience as control variables. Second, the use of the GOMS analysis allowed the design of tests that closely resemble the user interaction in online information systems. Third, the size of the sample used in this analysis is much bigger than those used in previous works, allowing a more thorough data analysis which includes the estimation of an advanced model which is quantile regression.

The purpose of this paper is to look into production competence theory by proposing and validating a multidimensional construct, and offering additional empirical evidence regarding the contribution of production competence to business performance.

Production competence is defined as a second‐order factor/construct in terms of five underlying dimensions: cost, flexibility, quality, delivery and environmental protection competence. Different scales are used to measure the construct, validated by a multi‐step process. Data from 274 manufacturing firms and structural equation modelling as the main technique are used for the analysis.

The paper suggests that manufacturing capabilities and their alignment with the competitive priorities pursued must be considered to explain the contribution of manufacturing to business performance. The provided evidence suggests that the manufacturing function significantly contributes to business performance, and enables us to conclude that production competence is a determinant of business performance.

Firms should focus on the development of manufacturing capabilities that are key for the market (and consistent with the business strategy). To achieve this, the production function should be integrated into the strategic planning process of the overall business strategy.

Most research works to date deal with production competence as a one‐dimensional construct and reduce its measurement to a single index, fussing variables of different types. This paper provides a valid multidimensional operationalisation of production competence, considering environmental protection as a fifth manufacturing objective. It also offers additional empirical evidence regarding the positive link between production competence and business performance.

Social media provide an impressive amount of data about users and their interactions, thereby offering computer and social scientists, economists, and statisticians – among others – new opportunities for research. Arguably, one of the most interesting lines of work is that of predicting future events and developments from social media data. However, current work is fragmented and lacks of widely accepted evaluation approaches. Moreover, since the first techniques emerged rather recently, little is known about their overall potential, limitations and general applicability to different domains. Therefore, better understanding the predictive power and limitations of social media is of utmost importance.

Different types of forecasting models and their adaptation to the special circumstances of social media are analyzed and the most representative research conducted up to date is surveyed. Presentations of current research on techniques, methods, and empirical studies aimed at the prediction of future or current events from social media data are provided.

A taxonomy of prediction models is introduced, along with their relative advantages and the particular scenarios where they have been applied to. The main areas of prediction that have attracted research so far are described, and the main contributions made by the papers in this special issue are summarized. Finally, it is argued that statistical models seem to be the most fruitful approach to apply to make predictions from social media data.

This special issue raises important questions to be addressed in the field of social media-based prediction and forecasting, fills some gaps in current research, and outlines future lines of work.

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.

Since the 1990s, several policy instruments have been produced in Belo Horizonte, Brazil, to improve accessibility to urban mobility systems, especially for people with disabilities. However, the city still faces important shortcomings in understanding the demands of the population with disabilities and in implementing an appropriate urban structure. The present work identifies mobility practices and demands for accessibility of this population based on a descriptive analysis of the city’s origin/destination survey (2012) and results of a focus group with representatives of the population with disabilities and public authorities. The analysis demonstrates that the demands of persons with reduced mobility are characterised first by a high level of immobility, comparing to people without disabilities, which has important consequences on access to urban goods, especially jobs and health and educational services. Second, mobility has a relevant role in producing forms of discrimination and exclusion. Third, in addition to the problems faced by the general population, people with reduced mobility also face greater challenges in using transport systems. Ultimately, this analysis points out that the main needs for people with disabilities are related to the problems of articulation between public places and transportation systems, both in terms of infrastructure and in terms of attitude and behaviour of service providers and other citizens.

Increasing physical activity can reduce obesity risk among adolescents. This study analyses how behaviours, ethnicity and various sociocultural characteristics may influence the likelihood of engaging in active commute and other healthy activities. The authors analyse data from the 2010 National Youth Physical Activity and Nutrition Survey. The sample included US Hispanic high school students from 9th to 12th grade. Quasi-Poisson regression was used to understand the association between 24 possible variables and the number of days physically active at least 60 minutes per day. This study will present findings by race and ethnicity: non-Hispanic whites and blacks, as well as Hispanics. The research findings uncover that walking is the most predominant physical activity among Hispanics, especially from school to home, which indicates engagement in active transportation. This study shows the need for tailoring physical activity and health programmes by race and ethnicity. Interventions that encourage active commute can be effective for adolescents to achieve physical activity guidelines – at least 60 minutes per day.