Abstract
Email marketing plays a key role in business communications and is one of the most widely used applications by consumers. The literature review points to several determinants that, when applied, increase the open rate of newsletters. This research evaluates the impact of six determinants of persuasion on the opening rate of a newsletter in the hotel industry. The determinants are the day of sending, the time of sending, subject line personalization, scarcity appeal, curiosity appeal, and authority figure. The chosen methodology focused on real experiments, using a high-end luxury hotel, and the respective customer database. The newsletter was sent to the subscriber list, where one part received the control and the other part received a variant with the test version. Ten A/B tests were conducted for each determinant. The results obtained were not in line with what is indicated in the literature review. Although the literature review yielded results that showed that the application of determinants increased the open rate of newsletters, this study obtained findings to the opposite and did not confirm what was prescribed by the reviewed literature. The results of the A/B tests were conclusive and revealed that the determinants did not increase the open rate of newsletters.

Abstract
The aim of this study is to examine the impacts of board size, gender diversity and independence on ESG performance whilst also examining the impact of country-level social trust on such performance. We perform a panel data analysis and the least squares method for a sample of 75 European banks and a time span of 4 years from 2016 to 2019. We find that ESG performance is positively associated with board gender diversity and independence, and negatively associated with board size. Surprisingly, we find a negative relationship between country-level social trust and ESG performance. This is an important finding that we interpret as being related to the loss of confidence in the banking sector in the wake of the 2008 financial crisis. To regain such trust, the banking sector is likely to have suffered higher social pressure to engage in ESG activities in countries where social trust is lower. © 2023 by the authors.

Abstract
There is a recognized need to study sustainability in fashion. Several studies have documented the determinants that influence fashion purchase intention. However, the determinants that influence the purchase of sustainable fashion still need to be understood, particularly those factors associated with influencers and electronic word-of-mouth. This study aimed to examine the constructs influencer credibility, influencer expertise, influencer similarity, influencer'sparasocial relationship, E-WOM homophily, E-WOM expertise, trust in the influencer, trust in social media, performance expectation, consumer knowledge, environmental beliefs, brand awareness and willingness to pay more, and their effect on purchase intention. The research methodology consisted of consumer interviews that were conducted using an online platform, and structural equation modeling was used to test the research hypotheses. The results obtained indicate that consumer knowledge and willingness to pay more are the only constructs that positively affect the purchase intention of sustainable fashion. © 2023, IGI Global. All rights reserved.

Abstract
This study examined the determinants of purchase intention of green cosmetics, and eight semi-structured interviews were performed to identify them. The determinants identified were environmental awareness, lifestyle, willingness to pay, ethical issues and social and economic justice, cosmetic quality, concern with health, certification labels, trust in the brand, and advertising. Environmental awareness, lifestyle, willingness to pay, quality issues, ethics, and social and economic justice, as well as quality expectations, health concerns, and product knowledge, are the most significant determinants in the intention to purchase green cosmetics. Determinants such as certification labels, brand trust, and advertising are less significant. The research is relevant for the cosmetics industry and its brands to adapt their strategy and product offering to meet consumers’ needs and increase the consumption of green cosmetics and can also serve as a basis for the development of new quantitative studies on the purchase intention of green cosmetics. © 2023 by IGI Global.

Abstract
The use of social media in health is emerging as a means of bringing the various actors together with several benefits. In the specific case of cancer disease, these tools can help patients to improve their psychological well-being and their outcomes. As cancer is the cause of a quarter of deaths in Portugal, it is a pressing issue to understand which tools and information both patients and health professionals find most useful to build effective health social media. It was observed that there is a latent need for an oncology social environment, allowing greater well-being for patients and strengthening their relationship with health professionals and institutions, constituting an asset to the services provided. This chapter fills a gap in the bibliography by bringing together the views of both patients and health professionals from several areas, in close collaboration with the Francisco Gentil Portuguese Oncology Institute of Porto, E.P.E. © 2024, IGI Global. All rights reserved.

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.