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Publications

Publications by CEGI

2023

Data Envelopment Analysis: A Review and Synthesis

Authors
Camanho, S; D’Inverno, G;

Publication
Lecture Notes in Economics and Mathematical Systems

Abstract

2023

Internal Benchmarking for Efficiency Evaluations Using Data Envelopment Analysis: A Review of Applications and Directions for Future Research

Authors
Piran, FS; Camanho, S; Silva, MC; Lacerda, DP;

Publication
Lecture Notes in Economics and Mathematical Systems

Abstract

2023

Curbing Dropout: Predictive Analytics at the University of Porto

Authors
Blanquet, L; Grilo, J; Strecht, P; Camanho, A;

Publication
Atas da Conferencia da Associacao Portuguesa de Sistemas de Informacao

Abstract
This study explores data mining techniques for predicting student dropout in higher education. The research compares different methodological approaches, including alternative algorithms and variations in model specifications. Additionally, we examine the impact of employing either a single model for all university programs or separate models per program. The performance of models with students grouped according to their position on the program study plan was also tested. The training datasets were explored with varying time series lengths (2, 4, 6, and 8 years) and the experiments use academic data from the University of Porto, spanning the academic years from 2012 to 2022. The algorithm that yielded the best results was XGBoost. The best predictions were obtained with models trained with two years of data, both with separate models for each program and with a single model. The findings highlight the potential of data mining approaches in predicting student dropout, offering valuable insights for higher education institutions aiming to improve student retention and success. © 2023 Associacao Portuguesa de Sistemas de Informacao. All rights reserved.

2023

How Startups and Entrepreneurs Survived in Times of Pandemic Crisis: Implications and Challenges for Managing Uncertainty

Authors
Silva E.; Beirão G.; Torres A.;

Publication
Journal of Small Business Strategy

Abstract
The recent pandemic crisis has greatly impacted startups, and some changes are expected to be long-lasting. Small businesses usually have fewer resources and are more vulnerable to losing customers and investors, especially during crises. This study investigates how startups’ business processes were affected and how entrepreneurs managed this sudden change brought by the COVID-19 outbreak. Data were analyzed using qualitative research methods through in-depth interviews with the co-founders of eighteen startups. Results show that the three core business processes affected by the COVID-19 crisis were marketing and sales, logistics and operations, and organizational support. The way to succeed is to be flexible, agile, and adaptable, with technological knowledge focusing on digital channels to find novel opportunities and innovate. Additionally, resilience, self-improvement, education, technology readiness and adoption, close relationship with customers and other stakeholders, and incubation experience seem to shield startups against pandemic crisis outbreaks.

2023

Trustworthy artificial intelligence and machine learning: Implications on users' security and privacy perceptions

Authors
Do Espírito Santo Faria, RM; Torres, AI; Beirão, G;

Publication
Confronting Security and Privacy Challenges in Digital Marketing

Abstract
Artificial intelligence (AI) has altered our world in numerous ways. Although its application has benefits, the underlying issues surrounding privacy and security in AI need to be understood, not only by the organizations that use it but also by the users that are susceptible to its vulnerabilities. To better understand the impact of privacy and security in AI, this chapter reviews the current literature on artificial intelligence, trustworthiness, and privacy and security concepts and uses bibliometric techniques to understand and identify current trends in the field. Finally, the authors highlight the challenges facing AI and machine learning and discuss the results obtained from the bibliometric analysis, which provides insight into the several implications for managers and contributions to future research and policy. © 2023, IGI Global. All rights reserved.

2023

Rethinking Technology-Based Services to Promote Citizen Participation in Urban Mobility

Authors
Duarte, SP; de Sousa, JP; de Sousa, JF;

Publication
INTERNATIONAL JOURNAL OF DECISION SUPPORT SYSTEM TECHNOLOGY

Abstract
Cities are complex and dynamic systems in which a network of actors interact, creating value through different activities. Cities can, therefore, be viewed as service ecosystems. Municipalities take advantage of digitalization to implement a service-dominant logic in urban and mobility planning and management, developing strategies with which citizens, local authorities, and other actors can create value together. While citizens are offered a better service experience, local authorities use citizens' input to improve decision-making processes. This research considers that designing an integrated service supported by an integrated information system can respond to current challenges in decision-making and information access for transport and mobility. Through a multidisciplinary methodological approach, this work proposes some guidelines to design an integrated information system to improve citizens' participation in urban planning and mobility services.

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