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This study focuses on investigating the surface settlement characteristics induced by the construction of a super-large-diameter shield tunnel in composite strata. By utilizing a combination of field monitoring and numerical simulation analysis, the surface settlement patterns encountered during the construction process in horizontally distributed typical soil–rock composite strata were summarized based on the 16.03 m super-large-diameter shield tunnel project in the southerly extension of He’ping Avenue in Wuhan. In addition, the collected data were used to enhance the Peck empirical formula. The results of the study show the following: (1) Significant non-uniform settlement occurs along the tunneling direction when the shield machine passes through soil–rock composite strata. The range of non-uniform settlement is approximately 3.1 times the tunnel diameter (D) in soil sections and 1.9 times the tunnel diameter (D) in rock sections. (2) The impact of composite strata on the maximum settlement is greater than its effect on the settlement trough width, with a larger impact within the soil sections compared to the rock sections. (3) The Peck correction formula, which takes into account the distance between the monitoring cross-section and the composite interface, provides more accurate predictions than the original Peck empirical formula.

Purpose This study aims examine the impact of authentic leadership on the career satisfaction of hospitality employees through the lens of thriving. The two components of thriving, that is, learning and vitality, are tested as mediators, and psychological contract fulfillment is tested as a boundary factor. Design/methodology/approach Data are collected using an online survey through the Qualtrics panel service in the USA. Structural equation modeling and an invariance test are conducted to investigate the framework. Findings The findings show that authentic leadership can determine career satisfaction through the influence of learning and vitality. Moreover, psychological contract fulfillment exerts a conditional effect on this mediation. Practical implications The findings of this study extend the understanding on authentic leadership and its impact under specific conditions. This study offers several meaningful recommendations to hospitality managers on how to influence employees’ career success to maintain sustainable performance. Detailed approaches include establishing practices for regular and authentic leadership development, increasing attention on employee thriving states and addressing employee psychological contracts. Originality/value This study enriches research on authentic leadership and career management in the hospitality industry. Moreover, this study provides meaningful insights by examining the relationships between authentic leadership, thriving, career satisfaction and psychological contracts.

Purpose Most existing studies on the impact of tourism on economic growth adopt an econometric approach that is insufficient to confirm that tourism actually leads to economic growth. Moreover, it cannot explain the causalities of different variables. Taking Mauritius as an example, this study aims to use the dynamic stochastic general equilibrium approach to investigate the contribution of tourism to economic growth when there is a productivity shock in the tourism sector. Design/methodology/approach A two-sector, small, open economy is modelled under the dynamic stochastic general equilibrium framework. The model is estimated using the Bayesian method based on real tourism and macroeconomic data from Mauritius for the period from 1999 to 2014. The impulse response functions are used to simulate the contribution of tourism to economic growth when there is a productivity shock in the tourism sector. Findings The simulation results show that the Mauritian gross domestic product (GDP) would increase by 0.09 per cent if the productivity of tourism is improved by 1 per cent, indicating that tourism could lead to economic growth. Considering the average annual growth rate of the Mauritian GDP, the contribution of tourism to its economic growth is significant. Furthermore, the effects of tourism on economic growth are moderated by price elasticities in international tourism demand. Originality/value This is the first study that estimates the dynamic stochastic general equilibrium model using the Bayesian method in tourism economic field. By correcting the prior information with real tourism and macroeconomic data, the estimation and simulation results are more robust compared with the calibration method, which has been used frequently in tourism studies.

Purpose The purpose of the study is to investigate the impact of implementing anti-dumping duties on imported Australian wine to China in the short- and long-run, respectively. Design/methodology/approach First, the Difference-in-Differences (DID) method is used in this study to evaluate the short-run causal effect of implementing anti-dumping duties on imported Australian wine to China. Second, a Bayesian ensemble method is used to predict 2023–2025 wine exports from Australia to China. The disparity between the forecasts and counterfactual prediction which assumes no anti-dumping duties represents the accumulated impact of the anti-dumping duties in the long run. Findings The anti-dumping duties resulted in a significant decline in red and rose, white and sparkling wine exports to China by 92.59%, 99.06% and 90.06%, respectively, in 2021. In the long run, wine exports to China are projected to continue this downward trend, with an average annual growth rate of −21.92%, −38.90% and −9.54% for the three types of wine, respectively. In contrast, the counterfactual prediction indicates an increase of 3.20%, 20.37% and 4.55% for the respective categories. Consequently, the policy intervention is expected to result in a decrease of 96.11%, 93.15% and 84.11% in red and rose, white and sparkling wine exports to China from 2021 to 2025. Originality/value The originality of this study lies in the creation of an economic paradigm for assessing policy impacts within the realm of wine economics. Methodologically, it also represents the pioneering application of the DID and Bayesian ensemble forecasting methods within the field of wine economics.

Purpose Leader–member exchange (LMX) theory is particularly relevant to the hospitality and tourism industry due to its labor-intensive and service-focused nature. However, the hospitality literature regarding the impact of LMX on its various outcomes have inconsistent results. A holistic review of LMX studies is nonexistent in the current literature. Thus, the purpose of this study is to use a meta approach to quantitatively summarize and examine the relationship between LMX and its outcomes in the hospitality and tourism literature. Design/methodology/approach A total of 89 individual observations from 36 studies conducted between 1997 and 2018 were identified. A Bayesian random effect model was introduced into the hospitality and tourism literature for the first time to implement the meta-analysis. Findings The results suggest significant differences in the impact of LMX on various groups of outcomes. LMX has the strongest impact on firms’ practice-related outcomes, such as organizational justice and employee empowerment. Few moderators are identified on the impact of LMX, such as LMX measure, culture, industry sector and statistical method. Practical implications Findings yielded several recommendations for both hospitality researchers and organizations in developing LMX related studies, as well as managing employees. Originality/value This study is the first Bayesian meta-analysis in the hospitality and tourism literature; it complements LMX theory by linking it to cognitive appraisal theory. Specific characteristics of LMX in the hospitality and tourism industry, such as the measurement of LMX and the effect of industry sector, are also identified.

Purpose Wine producers and marketing professionals increasingly recognize the significance of online wine reviews. Emotions have long been acknowledged as influential in online review behaviors. However, considering the multisensory nature of the wine experience, consumers’ wine expertise also plays a substantial role. Hence, this study aims to examine the online review behaviors exhibited by wine consumers through the dual lens of wine expertise and emotionality. Design/methodology/approach Two studies were conducted to address the research question. Study 1 explored the relationship among expertise, emotionality and review behaviors using a panel data model, with a data set consisting of 4,600,922 reviews from Vivino.com. Study 2 used a multigroup structural equation modeling (SEM) analysis using data obtained from an online survey. Study 2 aimed to investigate the interactive impact of emotionality and expertise on online review intention mediated by customer engagement. Findings The findings from Study 1 demonstrated a positive correlation between emotionality and online wine reviews. In addition, expertise displayed a bell-shaped relationship with both emotionality and online wine reviews. Study 2, in turn, uncovered that novices and experts experienced a direct influence of emotionality on their review intentions. In contrast, for those classified as ordinary, the influence of emotionality on review intention occurred indirectly through the mediation of customer engagement. Originality/value This paper extends the current literature on online wine review by integrating the effect of emotion and expertise on online wine review behaviors, expanding the examination of Dunning–Kruger effect in the wine literature. It also adds value by introducing emotionality and the Evaluative Lexicon into the hospitality literature, extending the measurement of emotion from valence and extremity to a third dimension, emotionality, in hospitality and wine domains.

Purpose Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked. Design/methodology/approach A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt. Findings Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments. Originality/value This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

Purpose The impact of demand fluctuation during crisis events is crucial to the dynamic pricing and revenue management tactics of the hospitality industry. The purpose of this paper is to improve the accuracy of hotel demand forecast during periods of crisis or volatility, taking the 2019 social unrest in Hong Kong as an example. Design/methodology/approach Crisis severity, approximated by social media data, is combined with traditional time-series models, including SARIMA, ETS and STL models. Models with and without the crisis severity intervention are evaluated to determine under which conditions a crisis severity measurement improves hotel demand forecasting accuracy. Findings Crisis severity is found to be an effective tool to improve the forecasting accuracy of hotel demand during crisis. When the market is volatile, the model with the severity measurement is more effective to reduce the forecasting error. When the time of the crisis lasts long enough for the time series model to capture the change, the performance of traditional time series model is much improved. The finding of this research is that the incorporating social media data does not universally improve the forecast accuracy. Hotels should select forecasting models accordingly during crises. Originality/value The originalities of the study are as follows. First, this is the first study to forecast hotel demand during a crisis which has valuable implications for the hospitality industry. Second, this is also the first attempt to introduce a crisis severity measurement, approximated by social media coverage, into the hotel demand forecasting practice thereby extending the application of big data in the hospitality literature.

This paper examines the contribution of tourism to the economy of Thailand and to the global economy. The findings suggest that tourism in Thailand generates significant economic impact on output and value added.

In the globalization era, many products in the tourism industry are imported from other economies; whereas other products may be exported as intermediates to other economies. Researchers have assessed the economic impact of tourism for more than 40 years, but have shed little light on the economic impact on economies in the global value chain. To fill this gap, this analysis used the multiregional input–output table with 35 industries and 63 economies to comprehensively examine the economic contribution of tourism to Thailand as well as to the global economy. Findings suggest that tourism in Thailand generates significant economic impact on output and value added. The industry has stronger intra-spillover and linkage with domestic industries, particularly downstream industries, and weaker connections with industries in other economies in the global supply chain. The multiregional input–output model also reveals that it can measure the export performance of the industry more accurately than the traditional input–output model. Findings generate comprehensive empirical results for destinations and regional organizations to more accurately strategize tourism or regional tourism development plans.