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This study aims to explore tourism live streamers’ motivations of sharing their travel experiences based on the grounded theory.

The use of purposive and snowball sampling methods was used to conduct 22 in-depth semi-structured interviews. The manuscript was analyzed based on the grounded theory.

This study identifies five tourism live streamers’ motivations of sharing their travel experience, including information sharing, entertainment, self-presentation, monetary incentives and socialization. Information sharing and entertainment are identified as the most important motivations of travel livestreaming (TLS) among the motivations. Monetary incentive is identified as a new motivation for tourism live streamers compared to other social media users.

This study provides valuable suggestions for livestreaming platforms and tourism product providers to attract more tourism live streamers and better serve them.

To the best of the authors’ knowledge, this is one of the first studies to offer empirical findings and discussions on tourism live streamers’ motivations of sharing their travel experiences.

本研究旨在基于扎根理论探讨旅游直播主分享旅游体验的动机。

使用目的性和滚雪球抽样方法进行了22个深入的半结构化访谈。 本研究采用扎根理论对数据进行分析。

本研究发现了五种旅游直播主分享旅游体验的动机, 包括信息共享、娱乐、自我展示、金钱激励和社交。信息共享和娱乐被认为是旅游直播最重要的动机。与其他社交媒体的用户相比, 货币激励被认为是旅游直播的新动机。

本研究为直播平台和旅游产品提供商提供有用的建议, 以吸引更多的旅游直播者并更好地为他们服务。

这是对旅游直播主分享旅游体验的动机提供实证研究结果和讨论的首批研究之一。

este estudio tiene como objetivo explorar las motivaciones de los transmisores en vivo del turismo para compartir sus experiencias de viaje según la teoría fundamentada.

Des méthodes d'échantillonnage raisonné et boule de neige ont été utilisées pour mener 22 entrevues semi-structurées approfondies. Le manuscrit a été analysé sur la base de la théorie ancrée.

este estudio identifica las motivaciones de cinco transmisores en vivo del turismo para compartir su experiencia de viaje, incluido el intercambio de información, el entretenimiento, la autopresentación, los incentivos monetarios y la socialización. El intercambio de información y el entretenimiento se identifican como las motivaciones más importantes de la transmisión en vivo de viajes (TLS) entre las motivaciones. El incentivo monetario se identifica como una nueva motivación para el transmisor en vivo del turismo en comparación con los usuarios de otras redes sociales.

este estudio proporciona sugerencias útiles para que las plataformas de transmisión en vivo y los proveedores de productos turísticos atraigan a más transmisores turísticos en vivo y les brinden un mejor servicio.

este es uno de los primeros estudios que ofrece hallazgos empíricos y debates sobre las motivaciones de los transmisores en vivo del turismo para compartir sus experiencias de viaje.

The purpose of this study is to critically reflect on visually impaired customers’ technology assistance needs and the perceptions of existing technologies’ performance in the contexts of hospitality and tourism.

Following a qualitative approach, this study used in-depth semistructured interviews with 19 participants with visual impairments.

Positive and negative sides of technology-assisted experiences in the hotel, restaurant, and travel domains were summarized, and room for improvement was discussed to enhance the quality of life and travel experience of visually impaired customers.

Findings from this study offer actionable implications and future directions to technicians and managers to make hospitality and travel experiences more inclusive.

This timely reflection addresses a critical situation by offering original ideas and calling for more discussion of under-represented groups with visual impairments.

This paper aims to overcome the limitations of low efficiency, low power density and strong electromagnetic interference (EMI) of the existing pulsed melt inert gas (MIG) welding power supply. So a novel and simplified implementation of digital high-power pulsed MIG welding power supply with LLC resonant converter is proposed in this work.

A simple parallel full-bridge LLC resonant converter structure is used to design the digital power supply with high welding current, low arc voltage, high open-circuit voltage and a wide range of arc loads, by effectively exploiting the variable load and high-power applications of LLC resonant converter.

The efficiency of each converter can reach up to 92.3%, under the rated operating condition. Notably, with proposed scheme, a short-circuit current mutation of 300 A can stabilize at 60 A within 8 ms. Furthermore, the pulsed MIG welding test shows that a stable welding process with 280 A peak current can be realized and a well-formed weld bead can be obtained, thereby verifying the feasibility of LLC resonant converter for pulsed MIG welding power supply.

The high efficiency, high power density and weak EMI of LLC resonant converter are conducive to the further optimization of pulsed MIG welding power supply. Consequently, a high performance welding power supply is implemented by taking adequate advantages of LLC resonant converter, which can provide equipment support for exploring better pulsed MIG welding processes.

This research aims to see whether replication occurs with the focus on the Japanese HR system, following the latest studies on expatriate management in Japan. Whereas the total number of self-initiated expatriates has hugely increased in Japan, the high turnover rate is a big issue. Can this also be evidenced with new data? How does the Japanese HR system, with its notorious reputation for unique people management methods, relate to the expats' reasons for staying in the long or short term?

Replication of research is adopted here with an interview-based qualitative method using the same research design as previous literature. The previous research focused on Chinese and Vietnamese self-initiated expatriates, who occupy the majority of expatriate positions in Japan. This study has a new target group of Thai expatriates, who have a relatively higher educational background than some other expatriates and are expected by the Japanese firms to stay over the long term.

Replication of the findings of the latest studies occurs in this research. The turnover rate is as high as other national expatiates, with similar reasons, related to the Japanese HR system. However, there are also different issues. The main reasons they give for not staying in the long-term are unhealthy work habits, followed by slower promotion and ambiguous work content/role. The Japanese HR system is a dehumanising mechanism leading to a stressful work environment, which is the most critical concern for them and the main reason they choose not to remain in the long term.

Past studies indicate an expectation gap between Japanese firms and expatriates, which is also found in this study. Additionally, an assumption gap between them about security under the HR system is also confirmed. Security means working healthily for expatriates while it means long-term employment for Japanese firms.

This paper aims to explore the matching effect of hospitality brand image (cool vs non-cool) and service agents (Artificial intelligence [AI] vs human staff) on brand attitude, with a focus on assessing the role of feeling right as a mediator and service failure as a moderator.

This paper tested the hypotheses through three experiments and a Supplementary Material experiment, which collectively involved 835 participants.

The results indicated that the adoption of AI by cool brands can foster the right feeling and enhance consumers’ positive brand attitudes. In contrast, employing human staff did not lead to improved brand attitudes toward non-cool brands. Furthermore, the study found that service failure moderated the matching effect between service agents and cool brand images on brand attitude. The matching effect was observed under successful service conditions, but it disappeared when service failure occurred.

The findings offer practical guidance for hospitality companies in choosing service agents based on brand image. Cool brands can swiftly transition to AI, reinforcing their modern, cutting-edge image. Traditional brands may delay AI adoption or integrate it strategically with human staff.

To the best of the authors’ knowledge, this paper represents one of the first studies to address the issue of selecting the optimal service agent based on hospitality brand image. More importantly, it introduces the concept of a cool hospitality brand image as a boundary condition in the framework of AI research, providing novel insights into consumers’ ambivalent responses to AI observed in previous studies.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

This study aims to empirically test the influence of pull factors on the intention to engage in Muslim-friendly travel. This study proposes a distinct path between Islamic attributes and emotional value and scepticism, along with destination image and its functional value. This study also proposes the role of halal awareness in moderating the relationship between Islamic attributes and scepticism.

This study used a quantitative approach using an online survey. The authors purposively selected younger individuals who had travelled inside the country at least three times during the past five years. With a total of 416 valid responses, this study used variance-based partial least squares to test the hypotheses.

The results show that intention to engage in Muslim-friendly travel is positively influenced by emotional and functional values, but negatively by scepticism. Emotional value and scepticism are influenced by Islamic attributes, whereas functional value is influenced by destination image. More specifically, halal awareness is proven to moderate the relationship between Islamic attributes and scepticism, in which individuals with a higher level of halal awareness tend to be less sceptical about halal offerings.

This study supports a previous study in which emotional and functional values are considered differently by consumers. Furthermore, the dual role of Islamic attributes, as pull factors, is confirmed, providing a deeper understanding of its influence on emotional value and scepticism. To the best of the authors’ knowledge, this study is also the first to investigate the role of halal awareness in increasing the level of scepticism among Muslim consumers.

This study aims to investigate the factors that affect an audience's purchase decisions on a new type of social media, namely live video streaming platforms.

This study is based on data from an online survey providing 488 valid responses. These responses are used to test the research model by employing partial least squares (PLS) modeling.

Three antecedents (consumer competitive arousal, gift design aesthetics and broadcaster's image) influence the audience's purchase decisions (impulse buying and continuous buying intention). Chinese impression management (mianzi) acts as a moderator. Self-mianzi, mutual mianzi and other mianzi (i.e. three subtypes of mianzi) moderate the effects of consumer competitive arousal, gift design aesthetics and broadcaster's image on impulse buying.

The findings encourage practitioners developing marketing strategies for live video streaming platforms in the Chinese cultural context to consider peer influence, gift appearance, broadcaster's image and mianzi.

Drawing on the community gift-giving model and face-negotiation theory, this study provides an integrated research model to investigate a new type of social media (live video streaming). It offers insight into virtual gifting behaviors by confirming the effects of three antecedents on the audience's purchase decisions, with mianzi acting as a moderator.

The primary aim of this study is to detail the use of soft computing techniques in business and management research. Its objectives are as follows: to conduct a comprehensive scientometric analysis of publications in the field of soft computing, to explore the evolution of keywords, to identify key research themes and latent topics and to map the intellectual structure of soft computing in the business literature.

This research offers a comprehensive overview of the field by synthesising 43 years (1980–2022) of soft computing research from the Scopus database. It employs descriptive analysis, topic modelling (TM) and scientometric analysis.

This study's co-citation analysis identifies three primary categories of research in the field: the components, the techniques and the benefits of soft computing. Additionally, this study identifies 16 key study themes in the soft computing literature using TM, including decision-making under uncertainty, multi-criteria decision-making (MCDM), the application of deep learning in object detection and fault diagnosis, circular economy and sustainable development and a few others.

This analysis offers a valuable understanding of soft computing for researchers and industry experts and highlights potential areas for future research.

This study uses scientific mapping and performance indicators to analyse a large corpus of 4,512 articles in the field of soft computing. It makes significant contributions to the intellectual and conceptual framework of soft computing research by providing a comprehensive overview of the literature on soft computing literature covering a period of four decades and identifying significant trends and topics to direct future research.