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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.

This study aims to investigate the current state of research using deep learning methods for text classification in the tourism and hospitality field and to propose specific guidelines for future research.

This study undertakes a qualitative and critical review of studies that use deep learning methods for text classification in research fields of tourism and hospitality and computer science. The data was collected from the Web of Science database and included studies published until February 2022.

Findings show that current research has mainly focused on text feature classification, text rating classification and text sentiment classification. Most of the deep learning methods used are relatively old, proposed in the 20th century, including feed-forward neural networks and artificial neural networks, among others. Deep learning algorithms proposed in recent years in the field of computer science with better classification performance have not been introduced to tourism and hospitality for large-scale dissemination and use. In addition, most of the data the studies used were from publicly available rating data sets; only two studies manually annotated data collected from online tourism websites.

The applications of deep learning algorithms and data in the tourism and hospitality field are discussed, laying the foundation for future text mining research. The findings also hold implications for managers regarding the use of deep learning in tourism and hospitality. Researchers and practitioners can use methodological frameworks and recommendations proposed in this study to perform more effective classifications such as for quality assessment or service feature extraction purposes.

The paper provides an integrative review of research in text classification using deep learning methods in the tourism and hospitality field, points out newer deep learning methods that are suitable for classification and identifies how to develop different annotated data sets applicable to the field. Furthermore, foundations and directions for future text classification research are set.

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the literature.

To address the research aims, this study conducted a systematic literature review and content analysis of all relevant articles. Following the review, the methodological sections of the selected papers were examined to identify the characteristics and limitations of all data sources used in the papers.

This study revealed several limitations of the use of three major data sources, namely, web scraping with self-made bots, inside Airbnb and AirDNA, for sharing economy research. The review shows that the majority of the selected papers did not acknowledge any limitations, nor did they discuss the quality of the data sources.

The findings of this paper can serve as guidelines for selecting appropriate data sources for research into the sharing economy and cautions researchers to address the limitations of the data sources used.

To the best of the authors’ knowledge, this is the first study that explores the advantages and limitations of data sources used in short-term rental market research.

This paper aims to provide insight into the evolving relationship between humans and machines, understanding its multifaceted impact on our lifestyle and landscape in the past as well as in the present, with implications for the near future. It uses bibliometric analysis combined with a systematic literature review to identify themes, trace historical developments and offer a direction for future human–machine interactions (HMIs).

To provide thorough coverage of publications from the previous four decades, the first section presents a text-based cluster bibliometric analysis based on 305 articles from 2,293 initial papers in the Scopus and Web of Science databases produced between 1984 and 2022. The authors used VOS viewer software to identify the most prominent themes through cluster identification. This paper presents a systematic literature review of 63 qualified papers using the PRISMA framework.

Next, the systematic literature review and bibliometric analysis revealed four major historical themes and future directions. The results highlight four major research themes for the future: from Taylorism to advanced technologies; machine learning and innovation; Industry 4.0, Society 5.0 and cyber–physical system; and psychology and emotions.

There is growing anxiety among humankind that in the future, machines will overtake humans to replace them in various roles. The current study investigates the evolution of HMIs from their historical roots to Society 5.0, which is understood to be a human-centred society. It balances economic advancement with the resolution of social problems through a system that radically integrates cyberspace and physical space. This paper contributes to research and current limited knowledge by identifying relevant themes and offering scope for future research directions. A close look at the analysis posits that humans and machines complement each other in various roles. Machines reduce the mechanical work of human beings, bringing the elements of humanism and compassion to mechanical tasks. However, in the future, smart innovations may yield machines with unmatched dexterity and capability unthinkable today.

This paper attempts to explore the ambiguous and dynamic relationships between humans and machines. The present study combines systematic review and bibliometric analysis to identify prominent trends and themes. This provides a more robust and systematic encapsulation of this evolution and interaction, from Taylorism to Society 5.0. The principles of Taylorism are extended and redefined in the context of HMIs, especially advanced technologies.

The study aims to promote the use of qualitative methods in service research by investigating how these methods are reported in service journals, how the level of reporting has evolved and whether methodological reporting influences the downloads or citations received by qualitative articles.

Methodological reporting practices were identified through content analysis of 318 qualitative articles published in three major service research journals and comparison with prior methodological literature. Regression analysis was used to test how the level of methodological reporting influences article downloads and citations.

The study identifies 29 reporting practices related to 9 key methodological reporting areas. The overall level of methodological reporting in published qualitative articles has increased over time. While differences in the level of reporting between service journals persist, they are narrowing. The level of methodological reporting did not influence downloads or citations of qualitative articles.

Service scholars using qualitative methods should pay attention to methodological reporting as it can improve the chances of being published. Factors such as theoretical contributions are likely to have a greater influence on article impact than methodological reporting.

No prior study has explored methodological reporting practices across different qualitative methodologies or how reporting influences article impact. For authors, reviewers and editors, the study provides an inventory of reporting practices relevant for evaluating qualitative articles, which should lower barriers for qualitative methods in service research by providing practical guidelines on what to focus on when reporting and assessing qualitative research.

This study examines the effects of employer attractiveness (EA) on employee engagement (EE) and employee performance (EP).

Mixed method. The analytical technique is the Partial Least Squares Structural Equation Modeling through survey questionnaires collected from 937 respondents as employees from 37 enterprises in Vietnam.

EA has a positive impact on EE and EP factors. However, EE has no statistically significant impact on EP.

This study helps managers build solutions toward retaining talent and improving EP through the strategy of building EA. Concurrently, this study guides the important factors to build an effective EA.

This study explores the relationship between three factors: EA, EE and EP. This has added a new research direction of EA to existing employees. In addition, the study results provide a new perspective on the relationship between EE and EP.

Drawing from conservation of resources (COR) and regulatory fit theories, this paper aims to propose and examine moderated mediation model of service innovative behavior among salespeople.

The hypothesized links were gauged based on time-lagged and multiple sources of data collected from salespeople and their supervisors in a large-scale multi-brand retail firm.

The hypothesized relationships were confirmed, and the moderated mediation model proposed in this paper was viable. Results suggest that person–job (P-J) fit boosts salespeople’s service innovative behavior, and intrinsic motivation (INTMOT) mediates this relationship. Promotion focus strengthens the positive influence of P-J fit on salespeople’s INTMOT. More importantly, promotion focus moderates the indirect positive link between P-J fit and service innovative behavior through INTMOT.

This research enhances the current knowledge by assessing promotion focus as a moderator of the impact of P-J fit on service innovative behavior via INTMOT among salespeople. To the best of the authors’ knowledge, there is no established research examining the abovementioned links in the sales literature.

The purpose of this study is to disclose ontology of DSI as a novel concept in servitization community, explore the research context and themes (i.e. technological and industrial sectors) where DSI emerges, unveil methodological complexities of the research on digital servitization and DSI and provide guidelines for future research avenues regarding DSI.

Bearing in mind the relative novelty of DSI as a concept in servitization literature, the authors adopted a systematic literature review approach to identify 111 peer-reviewed articles published in English language and available in business and management disciplines via scholar databases (Scopus). The analysis of literature discloses descriptive and thematic insights regarding digital servitization and DSI.

The study provides valuable insights from the descriptive and thematic analyses where classification of articles per publication year, citations, methodology/type of the paper, geographical location of data collection, as well as industrial sector and technological contexts are discussed. Moreover, the unique value of this study is observed through its specific focus on the characteristics of DSI-related literature.

The study is among the first of its kind to provide extensive descriptive and thematic insights on the available literature dealing with digital servitization and DSI, mapping out prior research across a wide spectrum of publication outlets and illustrating the chronological evolution of research on digital servitization and DSI.

This paper aims to provide an exposition of the constructive research approach (CRA) to show the potential utility of CRA in transcending or mitigating the methodological and practical issues involved in researching organisations.

The paper is a literature review, and resulting thematic discussion of methodological and practical issues involves in action research (AR) in organisations through the lens of the CRA approach.

The paper identifies that CRA has benefits in orientation to a practical outcome grounded in a theoretical domain but with leeway to facilitate creativity, which can also potentially improve the quality of the collaborative relationships. The centrality of the construction within the method provides a “vantage point” to manage the emic (inside) and etic (outside) positionality concerns of action researchers working within organisational settings.

CRA has multiple practical benefits for action researchers and their collaborators in terms of time, risk and collaborative commitment.

The paper develops a useful tactical framework for discussing the practical and methodological issues when considering AR in organisations and highlights how CRA can be used in wider organisational scholarship outside its roots in management accounting.

In the wake of COVID-19, the cruise industry is experiencing an unprecedented talent management challenge. Extant research suggests a broad range of work values that may attract job candidates to the cruise industry. The purpose of this study is to assess whether there are significant differences in the importance ratings of these work values for the millennials, compared to those of the preceding generation X.

With the support of a leading recruitment agency, the authors obtained responses to an online survey of 1,320 job candidates, of whom 830 were millennials. Using a quantitative approach, the authors asked them to assess the importance of eight work value domains. The authors ranked these domains for the millennials and for generation X and compared mean importance ratings using t-tests.

The results of this study reveal that differences between millennials and generation X in the ranking of the eight work value domains do exist. The authors did not find support for any systematic differences in terms of “extrinsic” versus “intrinsic” work values. However, the results show that the importance of “ego-driven” work values (e.g. support, development, compensation, work–life balance and comfort) is significantly higher for millennials. Conversely, for the more “altruistic” factors, there are no significant differences between the two generations.

Based on a very large sample of job candidates from the cruise industry, the results support the predictions of generational theories. The authors show that differences in work value ratings between generation X and the millennials exist. The authors also provide a novel perspective on the dimensions along which these differences materialize.

在一家领先的招聘机构的支持下, 我们对1320名求职者进行了在线调查, 其中830名是千禧一代。利用定量方法定量评估求职者八个工作价值域的重要性。对千禧一代和X一代的这些领域进行了排名, 并使用t检验重要性评分平均值。

新冠肺炎疫情后, 邮轮行业面临着前所未有的人才管理挑战。现有的研究表明, 广泛的工作价值观可能会吸引求职者进入邮轮行业。本研究的目的是评估千禧一代对这些工作价值的重要性评分与上一代X相比是否存在显著差异。

研究结果显示, 千禧一代和X一代在这八个工作价值领域的排名上确实存在差异。在“外在”和“内在”工作价值方面, 没有任何系统差异的证据支持。然而, 研究结果指出, “自我驱动”的工作价值观（如支持、发展、薪酬、工作与生活的平衡和舒适）对千禧一代的重要性明显更高。相反, 对于更“利他”的因素, 两代人之间没有显著差异。

基于邮轮行业的大量求职者样本, 结果支持代际理论的预测。研究表明, X一代和千禧一代在工作价值评价上存在差异。还提供了一个关于这些差异实现维度的新视角。

Con el apoyo de una importante agencia de contratación, se obtuvieron respuestas a una encuesta online de 1.320 candidatos a un puesto de trabajo, de los cuales 830 eran de la generación del milenio (milenials). A partir de un enfoque cuantitativo, se preguntó que evaluaran la importancia de ocho dimensiones sobre valores laborales. Se clasificaron estas dimensiones para los milenials y para la generación X y se compararon las valoraciones medias de su importancia mediante pruebas t.

A raíz del Covid-19, el sector de los cruceros está experimentando un reto de gestión del talento sin precedentes. La investigación existente sugiere una amplia gama de valores laborales que pueden atraer a los candidatos al sector de los cruceros. El objetivo de esta investigación es evaluar si existen diferencias significativas en las puntuaciones sobre la importancia de estos valores laborales para los millenials, en comparación con los de la generación X precedente.

Nuestros resultados revelan que existen diferencias entre los milenials y la generación X en la clasificación de las ocho dimensiones sobre valores laborales. No se encuentra apoyo para ninguna diferencia sistemática en términos de valores laborales “extrínsecos” frente a “intrínsecos”. Sin embargo, nuestros resultados muestran que la importancia de los valores laborales “impulsados por el ego” (por ejemplo, el apoyo, el desarrollo, la retribución, el equilibrio entre la vida laboral y personal y la comodidad) es significativamente mayor para los milenials. Por el contrario, para los factores más “altruistas” no hay diferencias significativas entre las dos generaciones.

Basándonos en una muestra muy amplia de candidatos a un puesto de trabajo en el sector de los cruceros, nuestros resultados respaldan las predicciones de las teorías generacionales. Se demuestra que existen diferencias en las valoraciones del trabajo entre la generación X y los milenials. También, se aporta una perspectiva novedosa sobre las dimensiones a lo largo de las cuales se materializan estas diferencias.