Search results

The present study assesses the impact resistance of the shear thickening fluids-filled (STFs-filled) foam through drop-hammer impact tests.

The maximum residual impact load and specific impact energy absorption rate of STF-filled foam are studied with varying thickness (4–14 mm), densities (0.35–0.6 g/cm3) and hardness (40–50 Rockwell Hardness C Scale (HRC)) under different ambient temperatures (−20−20 °C) and impact energies (25–75 J).

The following conclusions are obtained from this study: (1) the higher the impact energy, the greater the maximum residual impact force and energy absorption efficiency of the material; (2) the impact resistance of STF-filled foam can be improved with the decrease of ambient temperature, achieving the highest energy absorption rate at −10?. (3) STF-filled foam substrate has the highest impact resistance, the lowest maximum residual impact force and the highest energy absorption coefficient when the density is 0.35  g/cm3, the hardness is 45HC and the thickness is 10 mm.

This is the first paper to analyze the impact of both environmental factors and material properties on the impact resistance of STF-filled foam. The results show that the decrease in temperature and the increase in hardness can enhance the impact resistance of STF-filled foam.

Financial flexibility, investment efficiency and effective corporate governance mechanisms have been issues of concern to stakeholders. Yet, little empirical evidence on the combined moderating effects investment efficiency and corporate governance mechanisms on the nexus between financial flexibility and firm performance. This study aims to address this gap and extend the extant literature by examining the moderating effects of corporate governance and investment efficiency on the nexus between financial flexibility and financial performance.

The empirical study is based on progression analysis using a sample of 13,865 US listed companies selected from BoardEx (WRDS) for the period (2010–2022) with 89,198 firm-year observations.

Findings of this study indicate that financial flexibility improves firm value as well as accounting performance. Furthermore, the results reveal that both investment efficiency and corporate governance moderate the effect of financial flexibility on firm performance. The authors complement and extend the literature on the optimal investment strategies domain by showing that the combined impact of corporate governance mechanisms and investment efficiency strengthens the nexus between financial flexibility and firm performance.

Key limitations of this study due to the characteristics of the sample selection: country-specific context and proxies used by this study.

Findings of this study have managerial and theoretical implications for firms’ boardrooms, institutional and individual investors, regulators, academics and other stakeholders regarding behavioural aspects of investment decision-making.

The authors’ novel contribution to the extant literature is articulated by the conceptual framework underlying this study and by the new evidence regarding exploring the combined effect of corporate governance mechanisms on nexus between financial flexibility and companies’ performance.

Financial flexibility and investment efficiency are of vital importance in strategic choices at boardrooms, particularly in post-crisis recovery strategies. This study examines the moderating effects of investment efficiency and investment scale on the relationship between financial flexibility and firm performance.

The authors use sample of 10,755 US-listed firms over the period 2010–2021 to examine the relationships between investment scale, investment efficiency, financial flexibility and firm performance. Particular attention is paid to overinvestment and underinvestment.

Findings of this study reveal that financial flexibility mitigates investment inefficiency through reducing overinvestment. Financial flexibility contributes to boost a firm’s accounting and market performance. Additionally, investment efficiency and investment scale have moderating effects on the relationship between financial flexibility and firm performance. However, the influence of investment efficiency is greater than the influence of investment scale. Finally, the authors find that the direct and indirect effects of financial flexibility are stronger on market performance than accounting performance, implying that market is more sensitive to corporate financial policies.

Findings of this study have implications for scholars, decision-makers policymakers, investors and other stakeholders.

This study has its own limitations due to the sample selection issues, country context and the research model adopted by this study.

The novel contribution to the extant literature is incorporating the influence of investment scale and investment efficiency into the relationship between financial flexibility and firm performance.

When encountering novel technology, customers often use the term “cool” to express their thoughts; therefore, coolness has become crucial for launching service robots. However, research on the impact mechanism of “coolness” is lacking. This study explored the relationship between delight and behavioral intention regarding the coolness of service robots in the food and beverage industry while discussing the mediating roles of utilitarian and hedonic values.

Questionnaires were distributed online with links to the survey posted on restaurant discussion boards on Facebook and online community platforms such as Dcard. In total, 540 responses were deemed valid. The hypotheses were tested using the partial least squares structural equation modeling method.

The results indicate that coolness positively impacted both utilitarian and hedonic values and that both perceived values positively impacted delight. Moreover, coolness does not directly impact delight but must be mediated by perceived value to be effective.

Increasing customer perceptions of the coolness of service robots is recommended. Moreover, regarding customer revisits, utilitarian value services can delight customers more effectively than hedonic value services.

The stimulus-organism-response model was used to identify the relationships among coolness, perceived value, delight and behavioral intention. Moreover, the authors investigated the impact of coolness on utilitarian and hedonic values. These findings are significant for the development of smart restaurants and provide a critical reference for exploring service robots.

The paper aims to reveal the intellectual structure of studies on artificial intelligence (AI) in the fields of tourism and hospitality. Evaluations regarding the intellectual structure have been made based on co-author, co-word and citation.

The study is exploratory in nature. The study, using bibliometric analysis, provides a Web of Sciences (WOS) overview. The data has been obtained from the WOS database by coding as “artificial intelligence” and “tourism” and “hospitality.” VOSviewer program has been used to obtain and analyze the data.

The findings of the research show that studies on the use of AI in tourism and hospitality have become very popular, especially in the last 4 years. The authors of the study are working in the tourism and hospitality fields and have a high h-index. Generally, in current AI studies in tourism, topics such as robot, automation, ChatGPT, technology adoption and mechanical learning are studied. It has also been determined that topics related to the future of destinations and literature reviews are also discussed.

Although this paper examines all studies identified as a result of filtering, the analysis is limited to 195 studies. However, due to the widespread use of AI in tourism-related studies recently, bibliometric analysis has been made with extensive filtering. As studies on the subject become more widespread in the coming years, it would be useful to repeat similar studies by filtering with more specific quotas.

There are a few similar studies on the subject in the field. However, these studies need to be repeated at certain periods. This paper contributes to monitoring the literature of AI studies, which are new to use in tourism and hospitality, and to the formation of a theoretical framework on the subject.

At the forefront of current research is the investigation of how big data analytics capability (BDAC) and artificial intelligence capability (AIC) can enhance performance in concert. Therefore, current study intended to conduct more deep research into emerging phenomena and attempts to cover the gap by exploring how entrepreneurial orientations (EO) emphasize the use of two emerging capabilities under the moderating role of environmental dynamism which in turn augment co-innovation and hotel performance.

Data were collected from four-star and five-star hotels located in Kula Lumpur and Langkawi in Malaysia. A total of 260 responses were obtained from IT staff and senior managers with the assistance of a Manpower agency for data analysis. The hypotheses were examined by analyzing the data using PLS-SEM technique through Smart PLS 3 software.

The result revealed that EO has a positive and significant effect on co-innovation (CIN). Additionally, the BDAC and AIC have been tested and proven to be potential mediators between EO and CIN. Also, environmental dynamism as moderator has positive and significant effect on BDAC and co-innovation performance, however, not significant impact on AIC and co-innovation performance. Lastly, findings displayed positive and significant moderated mediation impact of environmental dynamics on BDAC and CIN with hotel performance, but not significant influence on AIC and co-innovation with hotel performance. For theoretical corroboration of the research findings, the current study integrated EO, resource-based view theory and contingent dynamic capabilities (CDC), because neither single stance can explicate an extant research framework.

This study anticipated the several implications for the entrepreneurs of hospitality industry. Managers are recommended to invest in the entrepreneurial traits of the employees/organizations and make strategic readjustment of their capabilities for sustained business performance.

The study goes beyond the normal inquiry by investigating moderated mediation impact of environmental dynamism between two emerging capabilities, co-innovation and hotel performance relationships. Another novelty of this study is to culminate the exploitation and adoption of emerging IT-based capabilities in cross domains of management, entrepreneurship, information systems management within the hotel industry.

The purpose of this study is to explore whether five factors drawn from the unified theory of acceptance and use of technology (UTAUT) and UTAUT2 significantly influence customers' intention to use hotel in-room voice assistants (VAs). It further examined culture as a moderator of the relationships between the five factors and customers' intention to use.

The authors collected data from US and Singapore to examine cultural differences in customer acceptance of in-room VAs. All hypotheses were tested via structural equation modeling and multi-group analysis.

The results showed that performance expectancy, social influence and hedonic motivation significantly affected customers' intentions to use in-room VAs, while effort expectancy and facilitating conditions did not. The results confirmed that culture did not play a substantial role in moderating the relationships between these factors and intentions to use.

This study established that the instrument and structural paths in the research model were equivalent across two samples from different countries. The findings may not generalize to other countries as the data arises from customers in the US and Singapore.

The findings provide important implications for hotel operators and vendors seeking to enhance customer acceptance of in-room voice technology.

This study addresses the gaps of extant research by developing and testing a research model to better understand the influential factors of in-room VA adoption within the hotel domain.

This article analyzes research on digital transformation in the tourism sector, providing insights into leading work, authors, journals, trends and future research opportunities. However, limited in-depth research exists on this topic, and the existing studies lack an understanding of its development, scope and relevant areas.

The study utilized the Scopus database to identify 61 articles on digital transformation in the tourism sector. The research employed VOSviewer software to analyze publication and citation structure, incorporating bibliometric variables like co-authorship, co-citation network, keywords co-occurrence network and bibliographic coupling.

The study yielded valuable insights from top-cited articles, revealing their contributions to digital transformation in tourism research. It also highlighted publication trends and the impact of authors, journals and studies and conducted co-occurrence, co-authorship and bibliographic analyses to identify key trends and issues in the tourism sector. The study calls for further examination of the digital revolution in tourism research and outlines future opportunities for researchers in this area.

To enhance the comprehensiveness of data collection, it is recommended that researchers consider including publications from databases such as WOS (Web of Science), Dimensions and PubMed in addition to the Scopus database. This broader inclusion of sources can provide different network structures and valuable insights from the field of digital transformation in the tourism sector.

The research provides substantial value to the study of digital transformation in tourism by focusing on bibliometric data from the Scopus database for the period from 2017 to 2022. By analyzing this data, it identifies significant trends in digital transformation within tourism research. Additionally, the study uncovers new areas of digitization in the tourism sector, further enhancing its value and relevance.

The purpose of this study is to conduct a thematic content analysis of facial emotion recognition (FER) research within the context of the hospitality and tourism industry. Through this analysis, the study aims to identify key themes, trends and implications of the utilization of FER technology in enhancing customer emotions and experiences within hospitality and tourism settings.

This is qualitative research that utilizes thematic content analysis. The research data were obtained from the Scopus database. A total of 45 articles (titles, abstracts and keywords) were coded into MAXQDA and VOSWiever programs for data analyses and mapping.

Based on the analyses, the predominant term used in titles was emotion, indicating its centrality in the research domain. Moreover, the most prevalent concepts in this field were emotion and experience. Notably, facial emotion recognition emerged as the most frequently utilized term within this context. Within the hospitality and tourism industry, FER was primarily employed within the travel sub-branch. Finally, the research culminated in the visualization of the theoretical framework and conceptual background, offering a comprehensive overview of the field.

There is a growing demand for using FER technology specifically within the hospitality and tourism industry context; therefore, growing scientific research has been conducted on this topic recently. By conducting a thematic content analysis, this study uncovered novel insights into the utilization of this technology to enhance customer emotions and experiences, thereby contributing to a deeper understanding of its potential implications and applications within the hospitality and tourism industry.

This study profiles and segments potential tourists on the basis of their various attitudes toward artificial intelligence (AI) services. Furthermore, this study distinguishes descriptors among the different clusters, such as preference for using diverse AI services, overall image of AI services, willingness to use AI services (WUAI), willingness to pay more for AI services (WPAI) in tourism and hospitality, and characteristics of respondents.

An online survey was conducted in South Korea. Data on 758 potential tourists were used for K-means cluster analysis.

This study identified three distinct tourist segments with differentiated attitudes toward AI services: the group aspiring to use or fantasizing about AI services (Cluster 1), the group being knowledgeable and supportive of AI services (Cluster 2), and the group having low interest about AI services (Cluster 3).

Members of Cluster 2 were the most marketable as this segment exhibited the greatest knowledge of and support for AI services, while Cluster 1 would be an ideal segment to launch and test novel AI services.

This study extends the authors’ knowledge of AI scholarship by unpacking the existing market segments, which could be tapped to sustain AI penetration in the tourism industry. Hence, this study contributes to existing debates on AI scholarship, which is predominated by conceptual reflections and issues of AI services in the tourism and hospitality field.