Soutinho, Gustavo

Loading...
Profile Picture

Email Address

Birth Date

Job Title

Last Name

Soutinho

First Name

Gustavo

Name

Gustavo

Biography

Gustavo Domingos da Costa Coelho Soutinho Docente do Departamento de Ciência e Tecnologia da Universidade Portucalense.

Research Projects

Organizational Units

Organizational Unit
REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura. Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture. Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations: - the understanding of local, national and international environment; - the development of activities oriented to professional practice, namely in the business world.

Search Results

Now showing 1 - 7 of 7
  • PublicationRestricted Access
    Impact of climate investment policies on citizens’ perception of pollution damage in the European Union
    2024-12-01 - Ribeiro, Vitor Miguel; Soutinho, Gustavo; Soares, Isabel
    This study examines the impact of climate investment policies on citizens’ perception of pollution damage in the European Union, while controlling for various environmental indicators. The primary panel data estimation outcome indicates that, despite substantial public expenditure on climate action, consumers’ perception of pollution improvement remains unchanged or even worsens. This suggests support for the policy ineffectiveness hypothesis. In view of this result, advocating for strengthened policies aimed at bolstering climate action in the European Union may be considered a non-credible threat from a microeconomics standpoint.
  • PublicationRestricted Access
    A fresh look on verti-zontally differentiated peer-to-peer electricity trading platforms with and without service customization
    2024-12-01 - Ribeiro, Vitor Miguel; Soutinho, Gustavo; Soares, Isabel
    We analyze a two-sided market where two platforms compete in electricity intraday trading. These intermediaries are differentiated both vertically and horizontally and engage in price competition to attract agents from both sides of the market, buyers and sellers. Alongside accounting for quality disparities at the intermediary level, we consider the possibility that platforms may choose to customize electricity intraday trading services. Main results demonstrate that equilibrium outcomes depend on the interaction between the strength of indirect network externalities and the degree of quality differentiation between platforms when service customization is absent. Notably, regardless of whether horizontal or vertical dominance prevails, the intensity of indirect network externalities consistently fosters pro-competitive effects in the private equilibrium. Conversely, when platforms opt for service customization, indirect network externalities do not influence equilibrium access prices and profits if the quality discrepancy between platforms is sufficiently high. This suggests that pro-competitive effects vanish under this specific circumstance. Consequently, this research emphasizes the critical role of service customization in peer-to-peer electricity intraday trading systems. If overlooked by regulators, the surplus enjoyed by incumbent operators at the distribution level, typically attributed to natural monopolies, may be transferred to high-quality platforms that customize services.
  • PublicationRestricted Access
    Survapp: A shiny application for survival data analysis
    2025-01-11 - Silva, Emanuel Vieira Monteiro da; Meira-Machado, Luís Filipe; Soutinho, Gustavo
    There is a substantial demand for user-friendly graphical interfaces that empower professionals with limited programming knowledge to perform statistical analysis. Although R software is widely used for statistical analysis, it lacks an adequately intuitive graphical interface for individuals without statistical and programming skills. This paper aims to address this gap by introducing an application called Survapp, enabling users, regardless of their computational knowledge, to conduct survival analysis. The development leveraged R software, RStudio, and the Shiny package to create an interactive web app. Survapp incorporates diverse methodologies for analyzing survival data, including Kaplan-Meier, log-rank tests, Cox regression models, parametric accelerated failure time models, decision trees, random forests, and competitive risk analysis (a specific case of multi-state models). Survapp enables users to analyze survival data, offering example databases for various methodologies within the application. However, the primary objective is to allow users to import their own data and conduct their respective analyses in a user-friendly environment. A distinguishing aspect of Survapp is its interface, bridging the gap between complex statistical methods and users with limited statistical and programming expertise.
  • PublicationOpen Access
    MSM.app: An interactive Web tool for Survival Analysis and Advanced Multi-State Modeling
    2024-12-02 - Soutinho, Gustavo; Meira-Machado, Luís
    The development of applications aimed at providing interpretable results in a concise and user-friendly manner within the framework of multi-state models represents a promising research avenue, particularly when leveraging open-source tools adaptable to biomedical contexts. This paper introduces MSM.app, an interactive web application constructed using the Shiny package for the R language. MSM.app is structured into two main components, each addressing distinct facets of survival analysis and its extension to intricate multi-state models. The first component allows users to perform classical survival analysis techniques using standard functions from R packages such as survival. The second component supports users in achieving key objectives in multi-state analysis, including the inference of regression models and the estimation of transition probabilities, by integrating with the survidm and mstate R packages. The web application employs dynamic web forms, tables, and graphics, harnessing the capabilities of the Shiny package. This architecture ensures that users, regardless of their level of expertise in informatics, can seamlessly engage in dynamic analyses encompassing critical aspects of multi-state models.
  • PublicationOpen Access
    Estimation of the transition probabilities conditional on covariates with repeated measures: A joint modeling approach
    2024-06-07 - Soutinho, Gustavo; Meira-Machado, Luís
    In recent years, there has been a significant urge of interest in longitudinal and survival data modeling. This approach holds particular significance in cancer research, where it enables the evaluation of how longitudinal markers influence the event of interest. This paper aims to introduce practical estimation techniques for transition probabilities, conditional on observed covariates with repeated measurements. This innovation allows us to incorporate the trajectory of longitudinal outcomes into regression models by accommodating time-varying covariates for each individual. The results presented in this study confirm the superior efficiency of the proposed methods, which merge existing approaches for joint modeling of longitudinal and survival data with the landmark approach for estimating transition probabilities. These methods outperform approaches that do not fully account the information provided by longitudinal covariate measurements.
  • PublicationOpen Access
    Presmoothed estimators of the state occupation probabilities in multi-state survival data
    2024-06-07 - Meira-Machado, Luís; Soutinho, Gustavo
    The progress of a disease can be analyzed using multistate models. These models focus on two key parameters of interest: the transition hazard and the state occupation probabilities. The state occupation probabilities have been consistently estimated by the Aalen-Johansen estimator. This estimator is particularly well-suited for handling censoring and benefits from the Markov assumption in the underlying stochastic process. In some cases, these estimators may lead to estimators with higher variability. To mitigate this issue we propose alternative estimators that incorporate a preliminary estimation approach. We introduce also practical estimation techniques for the state occupation probabilities, considering covariate measures. We explore the finite sample behavior of the estimators through simulations. An application to breast cancer is included.
  • PublicationRestricted Access
    Nonparametric estimation of the conditional bivariate distribution function of censored gap times
    2024-12-04 - Soutinho, Gustavo; Meira-Machado, Luís
    A major goal in recurrent events analysis is to estimate the bivariate distribution function. This estimation is crucial across various fields and applications, as it helps clarify the patterns of recurring events and their underlying patterns. ‘Gap time’ refers to the duration between consecutive occurrences of an event, while the bivariate distribution function represents the joint probability distribution of two such gap times. Despite significant advancements in this area, most existing methods assume independent censoring and neglect the impact of covariates. Therefore, the primary aim of this paper is to develop and introduce nonparametric estimation methods for the bivariate distribution function that incorporate covariate measures. This study seeks to provide more precise and applicable tools for analyzing recurrent event data, thereby enhancing the understanding and interpretation of such events in practical scenarios.