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The purpose of this study is to explore the paranormal tourist experience on ghost tours, taking into account the participants’ perceptions and their prior knowledge of the paranormal, in order to determine the principal components of the future of paranormal tourist experience.

The study is divided into two phases. The first phase is based on participant observation during a ghost tour. The second phase is based on a previously published framework for paranormal tourism. It introduces a qualitative adaptation of the orchestra model to look in-depth at how experiences with paranormal tours might shape the future of tourism as a major subtype.

Paranormal tourism has external (situational-enchantment, historical, mystical, ghostly and unsolved mysteries) and internal (affective, cognitive, sensory, behavior and relationship) components that are inter-linked. Future paranormal tourist experiences (FPTEs) must be focused on enhancing these aspects in order to offer an immersive experience.

Consequently, this paper proposes the FPTE model.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

Christmas is the most consumed event of the year, always full of traditions, namely family ones, which are very significant. In this way, it is intended to find out the importance of traditions at Christmas time and analyze their implications for family businesses.

The study is quantitative in nature, based on a questionnaire survey carried out with 551 Portuguese individuals, over 18 years of age, where different issues related to Christmas traditions and family are addressed.

The results demonstrate that the Christmas traditions scale is made up of four factors: family traditions on Christmas Eve, aspects related to the Christmas spirit, changes in Christmas traditions with the COVID-19 pandemic and traditions of participating in events with family at Christmas. Cod and octopus dishes are the most popular dishes on Christmas Eve. In relation to sweets/desserts, king cake, rabanadas, vermicelli, children's bread and sponge cake are the most common on Christmas Eve.

The study helps to understand Portuguese Christmas traditions, providing knowledge that allows defining strategies for family businesses, improving the experience and relationship with consumers at a special time of year. It is hoped that the trends in Christmas traditions in this study will contribute to unveiling the Christmas spirit, also serve as a marketing image and create curiosity and motivation on the part of other cultures to visit Portugal during this festive season, in order to experience Christmas traditions.

This study explores the phenomenon of compassionate leadership, a promising concept in management literature. Despite significant contributions towards the understanding of its antecedents and consequences, the specific role of compassion concerning the leader behavior under extreme pressure remains unexplored.

Drawing empirically on the case of three banks under three different logics, the authors trace how heads of banking branches, namely, middle managers, deal with the paradoxical phenomenon of integrating their human nature with the coetaneous need to achieve aggressive objectives. The authors analyzed interviews using the interpretive research method (Hatch and Yanow, 2003).

The authors identified that the logic of savings banks and credit cooperatives, together with specific human elements, created a healthier environment to develop compassionate behaviors compared to commercial banks. The authors found coherence when linking the institutional message of putting the spotlight on a personalized treatment of customers, and the middle manager compassionate actions towards customers and subordinates.

Suggestions for future theorizing and research are advanced, along with constructive practical implications to rehumanize the dark side of banking for both employees and customers.

The findings provided in this paper are original because they provide further evidence of linking business logics with compassionate leadership of middle managers and its impact on employees and customers.

Much has been speculated about the role that Generation Z will play in achieving more sustainable development. The tourism sector gains a special role in this discussion. On the one hand, tourism, due to its growing importance, has had a significant impact on environmental sustainability. On the other hand, Generation Z will be the largest group of travellers ever in the future. In this context, the objective of the present study is to explore the interest of young Portuguese generation Z in sustainable development goals (SDGs), tourism sustainability (TS) and their pro-environmental habits and how these categories influence the choice of sustainable tourism destination.

An online questionnaire was used to collect data from a sample of 305 young Portuguese. The quantitative analysis was performed with the application of the partial least square (PLS) model.

Overall, the authors found that despite our respondents showing an interest in the SDGs the same interest is not true for tourism. Although most respondents are concerned about choosing a sustainable destination, they do not care about keeping destinations sustainable, nor do they have pro-environmental habits.

This study presents the first evidence of the attitudes, beliefs and pro-environmental habits of Portuguese Gen Zers and their potential contribution to TS.

The present study investigates the impact of opinion leadership and spirituality from three types of social media influencers (SMIs) on individuals’ intentions to conduct recycling. This research is driven by the opinion leadership theory demonstrated by influencer marketing.

This research applies a between-subject experiment to measure the impact of the proposed model. Each participant was exposed to a different influencer: an attractive influencer (Treatment 1, n = 101), an expert influencer (Treatment 2, n = 94), a religious influencer (Treatment 3, n = 99) and a control condition (Treatment 4, n = 102). An ANOVA post-hoc analysis was conducted to further assess the impact dynamics of each influencer based on different demographics such as age, income and level of education. More than 95% of the samples consist of Muslims.

Findings revealed the different dynamics of the effect of opinion leadership and spirituality on the intention to recycle from utilising different types of influencers. Samples derived from a high socio-economic background and exposed to the religious influencer (Treatment 3) have a relatively higher mean score. In general, younger participants with lower incomes and levels of education have less tendency to conduct recycling.

This research attempts to fill the gap in the impact of influencer marketing on green behaviour adoption with the inclusion of spirituality, which has been largely ignored in this context. It offers insights from the perspective of a developing economy that has one of the largest percentages of social media users in the world and from a country that regards a relationship with God as important.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.