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- A SLR on Customer Dropout PredictionPublication . Sobreiro, Pedro; Martinho, DomingosDropout prediction is a problem that is being addressed with machine learning algorithms; thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as which features should be selected and how to measure accuracy while considering whether the features are appropriate according to the business context in which they are employed. To solve these questions, the goal of this paper is to develop a systematic literature review to evaluate the development of existing studies and to predict the dropout rate in contractual settings using machine learning to identify current trends and research opportunities. The results of this study identify trends in the use of machine learning algorithms in different business areas and in the adoption of machine learning algorithms, including which metrics are being adopted and what features are being applied. Finally, some research opportunities and gaps that could be explored in future research are presented.
- Hybrid Random Forest Survival Model to Predict Customer Membership DropoutPublication . Sobreiro, Pedro; Martinho, DomingosDropout prediction is a problem that must be addressed in various organizations, as retaining customers is generally more profitable than attracting them. Existing approaches address the problem considering a dependent variable representing dropout or non-dropout, without considering the dynamic perspetive that the dropout risk changes over time. To solve this problem, we explore the use of random survival forests combined with clusters, in order to evaluate whether the prediction performance improves. The model performance was determined using the concordance probability, Brier Score and the error in the prediction considering 5200 customers of a Health Club. Our results show that the prediction performance in the survival models increased substantially in the models using clusters rather than that without clusters, with a statistically significant difference between the models. The model using a hybrid approach improved the accuracy of the survival model, providing support to develop countermeasures considering the period in which dropout is likely to occur.
- Teaching Sentiment in Emergency Online Learning—A Conceptual ModelPublication . Ricardo Vardasca, PhD, ASIS, FRPS; Martinho, Domingos; Sobreiro, PedroDue to the COVID-19 pandemic, higher education institutions with a face-to-face model have found themselves in the contingency of migrating to online learning. This study explores the perspective of all the lecturers at a Portuguese private higher education institution who were invited to participate, regardless of their research area, in this questionnaire. It aims to propose and test a conceptual model that combines attitudes, preferred activities, and technological experience with the sentiment about the impact of this experience on students’ learning process, on their teaching activity, and on the strategy of higher education institutions. An online questionnaire was conducted to 65 lecturers engaging in emergency online lecturing. The obtained results showed that lecturers reveal a positive attitude towards online lecturing, tend to prefer activities in which they feel most comfortable in face-to-face lecturing, and consider having technological experience useful for online activities. Lecturers have a positive sentiment about the impact of online learning on students’ learning, their faculty career, and the strategy of higher education institutions. The proposed conceptual model test shows that the model has well-fitting conditions. The results confirm the hypotheses formulated: namely, the predictive effect of attitude, preferred activities, and technological experience on sentiment. Faculty engagement in emergency online lecturing shows that the members are available to participate in the changing process, and the proposed conceptual model can be used to assess this readiness.
- Performance Evaluation of Information Systems in Portuguese MunicipalitiesPublication . Pratas, Antonio; Sobreiro, Pedro; Martinho, DomingosThe success of organizations increasingly depends on the performance of their information systems, and public bodies are no exception. If the service provided to all of us, as citizens, depends on this performance, then it is essential that we can evaluate it. This research evaluates the performance of information sys tems in the Portuguese municipalities, applying the DeLone and McLean model, which is based on the perceptions of the systems’ users. The research is based on a self-administered questionnaire to a representative sample of Portuguese munici palities employees. The six dimensions of the model were: system quality, infor mation quality, service quality, utilization, user satisfaction and impacts. A seventh dimension - demographics - and its relationship with the original model were also analyzed. The results show that DeLone and McLean model is suitable for the Por tuguese municipalities context, and it was concluded that the system quality and information quality dimensions have a major effect on user satisfaction and inten tion to use/use, respectively. It was also found that the user satisfaction dimension has a strong effect, and the intention to use/use dimension has a moderate effect on Impacts. These results provide relevant information for decision-making related to the evolution of information systems in Portuguese municipalities, showing the importance of investing in the systems quality and the quality of the information produced.