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This study addresses the gap in understanding text analytics within the service domain, focusing on new service development to provide insights into key research themes and trends in text analytics approaches to service development. It explores the benefits and challenges of implementing these approaches and identifies potential research opportunities for future service development. Importantly, this study offers insights to assist service providers to make data-driven decisions for developing new services and optimising existing ones.

This research introduces the hybrid thematic analysis with a systematic literature review (SLR-TA). It delves into the various aspects of text analytics in service development by analysing 124 research papers published from 2012 to 2023. This approach not only identifies key practical applications but also evaluates the benefits and difficulties of applying text analytics in this domain, thereby ensuring the reliability and validity of the findings.

The study highlights an increasing focus on text analytics within the service industry over the examined period. Using the SLR-TA approach, it identifies eight themes in previous studies and finds that “Service Quality” had the most research interest, comprising 42% of studies, while there was less emphasis on designing new services. The study categorises research into four types: Case, Concept, Tools and Implementation, with case studies comprising 68% of the total.

This study is groundbreaking in conducting a thorough and systematic analysis of a broad collection of articles. It provides a comprehensive view of text analytics approaches in the service sector, particularly in developing new services and service innovation. This study lays out distinct guidelines for future research and offers valuable insights to foster research recommendations.

This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

The main goal of any organization is to achieve the best quality of work through employees, and managers play a very important role in this field. Managers and leaders of organizations often face with paradoxes that make decision-making difficult. The purpose of this paper is to develop a competency model for human resource managers considering the importance of the role of paradoxes for organizations.

The research methodology is of a mixed type and with an approach based on paradox theory and using theme analysis and fuzzy Delphi, it seeks to provide a model of paradoxical managers’ competence. The statistical sample included 11 experts working in the information and communication technology industry, who were selected using the snowball and judgmental sampling method.

The results of this research show that the competency model of human resource managers has three managerial, organizational and individual levels and has 15 themes including strategic partner, organizational knowledge, awareness of the industry environment, awareness of the external environment, paradoxical thinking, managerial knowledge, relationship management, resource management , leadership, human resources analyzer, information technology (IT) knowledge, personality traits, development, multitasking and cognitive competence. The most important theme identified is paradoxical thinking and familiarity with IT knowledge, and it is suggested that human resource managers working in this field should preferably study technical and engineering fields at the undergraduate level and shift to human resource management fields at the graduate level.

The distinguishing feature of this paper is the presentation of a competency model based on paradox theory. Paradoxes are part of organizational life. Therefore, there should be a paradoxical view in all organizational analysis.

Tourists with different cultural backgrounds think and behave differently. Accurately capturing and correctly understanding cultural differences will help tourist destinations in product/service planning, marketing communication and attracting and retaining tourists. This research employs Hofstede's cultural dimensions theory to analyse the variations in destination image perceptions of Chinese-speaking and English-speaking tourists to Xiamen, a prominent tourist attraction in China.

The evaluation utilizes a two-stage approach, incorporating LDA and BERT-BILSTM models. By leveraging text mining, sentiment analysis and t-tests, this research investigates the variations in tourists' perceptions of Xiamen across different cultures.

The results reveal that cultural disparities significantly impact tourists' perceived image of Xiamen, particularly regarding their preferences for renowned tourist destinations and the factors influencing their travel experience.

This research pioneers applying natural language processing methods and machine learning techniques to affirm the substantial differences in the perceptions of tourist destinations among Chinese-speaking and English-speaking tourists based on Hofstede's cultural theory. The findings furnish theoretical insights for destination marketing organizations to target diverse cultural tourists through precise marketing strategies and illuminate the practical application of Hofstede's cultural theory in tourism and hospitality.

Built upon customer engagement marketing theory and uses and gratification theory, this study examines the link between individual social media marketing (SMM) performance indicators and restaurant sales performance at the firm level. Moreover, the study investigates the moderating effect of advertising expenditure on this proposed relationship.

Random effect regression models were developed in Stata to examine the associations between SMM performance indicators, advertising expenditure, and restaurant firm revenue. Twelve years of SMM data from brands' Facebook pages were collected with a web scraper built in Python. Natural language processing was used to analyze the sentiment of user-generated content (UGC).

The results suggest that restaurant annual sales revenue increases as the volume of brand posts, “like”s, “share”s and positive comments on restaurants' Facebook pages increase. However, the total number of comments and the number of negative comments show non-significant associations with revenue. Firm advertising expenditure negatively moderates the relationships between sales revenue and the number of “like”s, “share”s, total comments and positive comments.

Restaurants benefit from making frequent posts on SNSs. Promotions that motivate online users to “like”, share, and comment on brand posts should be implemented. Firms with limited advertising budgets are encouraged to actively create buzz on SNSs due to evidenced stronger effects of UGC on sales performance than large advertisers.

This research bridges the gap by studying the effects of individual SMM performance indicators on restaurant financial outcomes. The findings support the effectiveness of SMM; and, for the first time, demonstrate that SMM could generate a more profound impact for firms with low advertising budgets.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

Explore the role of traditional cafés in Lisbon and botequins in Rio de Janeiro in the history and culture of their respective cities, based on an analysis of the comments published on TripAdvisor.

Using a mixed methodology, 7,430 evaluations were analyzed, of which 5,473 were for Portuguese cafés and 1,957 for Brazilian botequins. A content analysis and statistical treatment were carried out. A line-by-line analysis was also conducted to code the emotions reported in the customer reviews.

The analysis categorized the comments into Gastronomy, Nostalgia, History and Heritage, and Quality of Service. Nostalgia garnered the highest percentage of positive comments for both Portuguese cafés and Brazilian botequins. These results emphasize the importance attached to sentimental connections and historical narratives, particularly those associated with notable individuals who frequented these places. Furthermore, no statistically significant differences were identified according to the type of establishment, which suggests a consistent pattern between cafés and traditional botequins.

Draws attention to the importance of a collaborative partnership between restaurant owners and tourism authorities. This strategic alliance not only serves to raise the cultural profile of cities, but also generates substantial economic benefits. It also ensures the lasting legacy of these historic establishments, celebrating the past, enriching the present and safeguarding the future.

Studying the cafés of Lisbon and the botequins of Brazil is important not only for understanding the history and culture of these countries but also for analyzing issues related to socialization, identity, artistic expression and urban transformations.

Social networking sites have become breeding grounds for the spread of fake news and misinformation. At the height of the Covid-19 pandemic, the spread of fake news intensified, causing complications for health communicators by drowning authentic information from verifiable official sources. Looking at the impact of this growing phenomenon on people’s attitudes and behaviour during the pandemic, research in the area must be populated to help governments, supranational organisations, non-governmental organisations as well as civil society organisations to formulate policies to curb the menace. This study was therefore undertaken to unravel current gaps and future research avenues to empower academia in achieving the desired scholarly impact.

The study adopted the systematic review approach, relying on 56 peer-reviewed articles on social media, fake news and misinformation in the Covid-19 pandemic.

The study found that the use of social media during the height of the pandemic led to unhelpful information creation and sharing behaviours such that people’s self-awareness reduced drastically, thereby impeding the fight against the pandemic. The study also established that Entertainment motives, Ignorance and Altruism motives were the dominant factors that influenced the spread of fake news. There was evidence of the marginalization of research on the subject matter from contexts such as Africa, South America and Oceania.

This study has established existing gaps in issues and evidence, methodology, theory and context and consequently discussed future research avenues for social media use and the spread of fake news. The study has also provided practical implications for both governmental and non-governmental organisations in curbing the phenomenon of fake news and misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2022-0366.

This comparative book review is concerned with two recent studies of essential workers in Germany: Jana Costas’ Dramas of Dignity and Peter Birke’s Grenzen aus Glas [literally ‘borders made from glass’]. While Costas is interested in studying how individual cleaners preserve their sense of dignity despite their widely believed stigmatizing work roles, Birke is interested in the power resources migrant workers can potentially mobilize for improving their working conditions despite the multi-dimensional (inter-sectional) precarity they confront in their life situation. In the context of German industrial and organizational sociology, both studies represent comparatively rare exemplars of detailed qualitative and ethnographic work that illuminate the labour process from taking a workers’ perspective. Using different approaches to fieldwork, both studies reveal the precarious nature of being an essential worker in areas such as meat packing, warehouse work, and cleaning. This general observation gives rise to some concluding speculations about the emancipatory potential of ethnographic research, in labour studies and beyond.