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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 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.

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.

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.

The establishment of partnerships between companies, government and universities aims to enhance innovation and the technological development of institutions. The biotechnology sector has grown in recent years mainly driven by its cooperative business model. Compared to other countries, this sector is slowly advancing in Brazil, with delays in science, technology and innovation, especially in the private sector. This paper aims to examine, through social network analysis, the collaborative networks between institutions that filed patents in biotechnology – medicinal preparations from plants – whose inventions had Brazil as the priority country.

The study of technological cooperation using patent documents is a reliable approach as they serve as good indicators of the interactions between organizations that focus on innovation and development of new product. Social network analysis of cooperation networks helps to understand the connections between patent assignees, and how they establish relationships.

Results show that public universities are the institutions that most deposit patents, as well as those that co-operate the most, especially Universidade of Campinas. The study also reveals the critical role of Research Support Agencies in stimulating research and technological development, which result in new technologies.

The study applied the social network analysis to provide an overview of the interactions among Brazilian institutions with the purpose of helping in decision-making and inciting public policies to leverage the biotechnology sector.

One of the main contemporary challenges in organisations is finding ways of measuring their intellectual capital (IC), and its effects on competitiveness and financial sustainability. The purpose of this paper is to analyse the influence of IC on the long-term financial performance of Brazilian companies.

Considering that previous studies have not been able to explain the role of IC in financial sustainability (measured by long-term corporate performance), this paper attempts to fill this gap by means of a quantitative, descriptive and applied study. Based on the theories of knowledge management, accounting and finance, the authors have undertaken a study of the companies listed on the BM&FBovespa, based on secondary data, using a multi-industrial cut, over the period 2005 to 2014, using descriptive and multivariate statistics.

The analysis supports three major conclusions: IC influences positively the profitability and corporate return of these companies; the more intangible-intensive public companies listed on the BM&FBovespa demonstrate higher financial sustainability than the others, in terms of profitability and corporate return, either individually, globally or by industry; and that IC helps increase financial performance, systematically, over time.

Contributions of the following types were sought: theoretical (increasing an understanding of the effects of IC on business performance from a long-term perspective – an understanding that is still only incipient in the management literature); and empirical (increasing an understanding of the role of IC in the differentiation of companies, in organisational profitability and on the return on applications of resources).

The original proposal for the measurement of financial performance presented in this paper proved to be valid and consistent, complementing what is known about the subject under examination, contributing to the improvement of management theory and practice and providing a competitive benchmarking process. This can make it possible for company analysts or managers to evaluate their company in relation to its industry or its market as a whole by means of such indicators, individually or combined with other quantitative or qualitative metrics.

The results of this research reduce a gap in the management and accounting literature, as they shed light on the performance measurement process. In addition to the range and depth of the statistical tests carried out, attention should be drawn to the originality of the proposal presented in this paper. This facilitates the measurement of the effects of IC on financial performance through the selection and application of specific indicators for the assessment of the contribution of IC to organisational results.