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This study aims to propose a data-driven approach, based on open-source tools, that makes it possible to understand customer satisfaction of the accommodation offer of a whole country.

The method starts by extracting information from all hotels of Portugal available at TripAdvisor through Web scraping. Then, a support vector machine is adopted for modeling the TripAdvisor score, which is considered a proxy of customer satisfaction. Finally, knowledge extraction from the model is achieved using sensitivity analysis to unveil the influence of features on the score.

The model of the TripAdvisor score achieved a mean absolute percentage error of around 5 per cent, proving the value of modeling the extracted data. The number of rooms of the unit and the minimum price are the two most relevant features, showing that customers appreciate smaller and more expensive units, whereas the location of the hotel does not hold significant relevance.

National tourist offices can use the proposed approach to understand what drives tourists’ satisfaction, helping to shape a country’s strategy. For example, licensing new hotels may take into account the unit size and other characteristics that make it more attractive to tourists. Furthermore, the procedure can be replicated at any time and in any country, making it a valuable tool for data-driven decision support on a national scale.

Considering the importance of the content created by the host for Airbnb consumers while making purchasing decisions, this study aims to analyze how the Airbnb hosts promote their properties by revealing the predominant attributes considered by hosts when advertising them.

The unstructured textual content of online Airbnb accommodations advertisements (property descriptions) is analyzed through a longitudinal text mining approach. This study defines a pipeline based on a topic modeling approach that allows not only to identity the most prevalent text attributes but also its distribution through time.

This research identifies and characterizes the attributes most advertised over time, on about 30,000 accommodations posted monthly over two years, between 2018 and 2020. Five main topics were identified in the data reflecting only pull motivations. Noteworthy is the slight changes in properties’ descriptions topics along the two years, suggesting that “service” is increasingly being perceived by hosts as an important attribute of Airbnb guest experience.

Through a text analysis, this study provides an insight into peer-to-peer accommodation on the key attributes that hosts consider in the description of their properties to leverage the attractiveness of Airbnb. In the light of existing research, which has predominantly focused on the trustworthiness and attractiveness of the Airbnb advertisement, this research differentiates by analyzing the main attributes in text over time. Given the Airbnb’s changes since its inception, a longitudinal view is relevant to clarify how hosts advertise their properties and how it evolves in the light of these changes.

This paper aims to develop a model to predict online review ratings from multiple sources, which can be used to detect fraudulent reviews and create proprietary rating indexes, or which can be used as a measure of selection in recommender systems.

This study applies machine learning and natural language processing approaches to combine features derived from the qualitative component of a review with the corresponding quantitative component and, therefore, generate a richer review rating.

Experiments were performed over a collection of hotel online reviews – written in English, Spanish and Portuguese – which shows a significant improvement over the previously reported results, and it not only demonstrates the scientific value of the approach but also strengthens the value of review prediction applications in the business environment.

This study shows the importance of building predictive models for revenue management and the application of the index generated by the model. It also demonstrates that, although difficult and challenging, it is possible to achieve valuable results in the application of text analysis across multiple languages.

Real estate agents are professionals who need up-to-date and accurate information about their clients in order to maintain profitable and long-lasting relationships with each of them. A satisfied customer can be very valuable and profitable in the long term. This research focuses on solving the problem of the lack of a mobile Customer Relationship Management (CRM) adapted to the needs of professionals. The importance of solving this problem is related to the importance of optimizing work and resources in a highly abundant information industry.

It was developed of a CRM for mobile devices capable of managing information about the customers and business partners of each user, which provides a set of features well defined by the professionals. These features were collected through 15 face-to-face interviews and validated with six video conference interviews with industry specialists. For the development and evaluation of this artefact was followed the DSR methodology, corresponding each interview to an iteration of this model.

From this research resulted a selection of functionalities considered essential to the real estate agent's work. These features were successfully implemented in a mobile application that real estate agents appreciate for its simplicity and that they feel adds real value to their daily lives. Using this service, the productivity and performance of real estate agents might be improved.

It was verified that the mobile CRM solution developed is a desired solution by real estate agents in terms of customer portfolio management, enhancing the evolution of their relationships and monitoring professional's performance.

The growing presence of projectification is affecting more than its cradle, the industry, characterizing it as a broader phenomenon than initially envisioned. This study aims to provide a literature review on the concept.

The sampling process includes articles from two databases, Web of Science and Scopus, and a backward snowballing sampling through the references, entailing the analysis of 103 documents. The publications were analyzed applying bibliometric, content and semantic analyses both manually and with the assistance of VOSViewer, Bibliometrix, NVivo11 and Tropes v.8.

The results identified 55 definitions of projectification. The study synthesizes them in five levels of analysis to capture their main distinctive aspects, as follows: (1) Private Organizations; (2) Public Sector; (3) Academy; (4) Individuals (work and private life); and (5) Society. The paper concludes by depicting factors as general effects, negative effects, tensions, funding and knowledge, embedded within each level of analysis.

This work sheds light on the evolution of projectification concept, presents a multilevel analysis of its consequences and brings forward the related topics, which still require further investigation.

This study aims to identify the impact of restaurant pandemic mitigation measures on perceived service quality.

A total of 15,251 reviews were collected from 300 TripAdvisor Lisbon restaurant Web pages between March 2020 and December 2021, when Covid-19 contingency measures were in place. Grounded on the online reviews, a word frequency matrix was created and used as input on partial least squares–structural equation modeling to test the proposed hypotheses.

The results suggest that precaution measures, such as the Vaccination Certificate, negative tests and restaurant layout configuration, positively influenced perceived service quality and consumer satisfaction, moderated by consumers’ beliefs.

This study provides relevant information for restaurant managers, which will help them implement strategies to guarantee service quality, consumer satisfaction and revisit intentions in future pandemic scenarios.

We present a critical literature review debating Brazilian research on social and environmental accounting (SEA). The aim of this study is to understand the role of politics in the construction of hegemonies in SEA research in Brazil. In particular, we examine the role of hegemony in relation to the co-option of SEA literature and sustainability in the Brazilian context by the logic of development for economic growth in emerging economies. The methodological approach adopts a post-structural perspective that reflects Laclau and Mouffe’s discourse theory. The study employs a hermeneutical, rhetorical approach to understand and classify 352 Brazilian research articles on SEA. We employ Brown and Fraser’s (2006) categorizations of SEA literature to help in our analysis: the business case, the stakeholder–accountability approach, and the critical case. We argue that the business case is prominent in Brazilian studies. Second-stage analysis suggests that the major themes under discussion include measurement, consulting, and descriptive approach. We argue that these themes illustrate the degree of influence of the hegemonic politics relevant to emerging economics, as these themes predominantly concern economic growth and a capitalist context. This paper discusses trends and practices in the Brazilian literature on SEA and argues that the focus means that SEA avoids critical debates of the role of capitalist logics in an emerging economy concerning sustainability. We urge the Brazilian academy to understand the implications of its reifying agenda and engage, counter-hegemonically, in a social and political agenda beyond the hegemonic support of a particular set of capitalist interests.

The objective of this research is to develop an solution to water management at the scale of buildings, through the technological resources. Automating analysis using 3D models helps increase efficiency in buildings during the operational phase, consequently promotes sustainability.

This study presents a methodology based on Design Science Research to automate water management at building scale integrating BIM-IoT-FM. Data from smart meters (IoT) and the BIM model were integrated to be applied in facilities management (FM) to improve performance of the building. The methodology was implemented in a prototype for the web, called AquaBIM, which captures, manages and analyzes the information.

The application of AquaBIM allowed the theoretical evaluation and practical validation of water management methodology. By BIM–IoT integration, the consumption parameters and ranges for 17 categories of activities were determined to contribute to fulfill the research gap for the commercial buildings. This criterion and other requirements are requirements met in order to obtain the AQUA-HQE environmental sustainability certification.

Traditionally, water management in buildings is based on scarce data. The practical application of digital technologies improves decision-making. Moreover, the creation of consumption indicators for commercial buildings contributes to the discussion in the field of knowledge.

This article emphasizes the investigation of the efficiency of use in commercial buildings using operational data and the use of sustainable consumption indicators to manage water consumption.

The purpose of this paper is to examine, through a qualitative lens, how community elder abuse and the ageing process are represented in the older adults’ narratives reporting abuse perpetrated by family members.

A qualitative study of a convenience sample of 22 interviews from 24 older adults (two couples) aged 60 years or older who had experienced one or more types of abuse and had sought help about the victimisation experience. A general inductive approach of thematic content analysis was employed.

The four main emergent themes related to the passage of time or the perception of becoming old within the process of abuse were: abuse grown old, abuse after entering later life, vulnerability to abuse and responses to abuse. Ageing was found to be associated with an increase vulnerability to abuse and an important element in shaping how older adults experience, report and cope with victimization. The social and contextual issues of being older also influenced the decision of ending (or not) the abuse and the victims’ repertoire of responses.

Despite the little suitability of chronological age to define and delimit elder abuse, understanding the phenomenon demands the recognition of ageing (both as a process and as a product) in order to more accurately identify aetiology processes and develop interventions.

This article aims to examine the related effects between out-of-class activities, mediated by in-class activities, on the perception of course and teacher performance in a flipped classroom institutionalized setting.

The authors argue that institutionalized out-of-class (content) and in-class (learning) activities positively impact course and teaching quality perception. This study used a sample of 978 responses from MBA students to conduct a path model analysis to test four hypotheses developed from literature from flipped classroom proposing the positive relationship of out-of-class activities in in-class activities and its influence on the course and teaching performance.

The findings reported that out-class and in-class activities and educator performance influenced course performance perception. In-class activities mediated the out-of-class activities’ impact and directly impacted educator’s and course performance. Educator performance is positively correlated with course performance. Overall, executives have a positive perception on institutionalized flipped classroom for MBA courses as an effective provision form. The flipped classroom is able to mobilize their experiences and enrich learners’ educational experience.

Only one unit of the higher education organization was studied, and the authors do not consider indirect effects of the environment on variable’s relationships nor the indirect effects whose would be a suggested for future studies.

The present study provides new insights on flipped classroom. This study evidenced that flipped classroom planned and standardized in an institutional level positively impacts the outcome within the context of executive education.