Abstract With the popularization of concept metaverse, non‐immersive virtual reality (VR) has become a focus tourism destination marketing. Drawing upon telepresence theory, this study identifies antecedents and consequences to help interpret tourist behavior in context VR experience. Results revealed that mental imagery vividness positively predict satisfaction; Telepresence predicts satisfaction intention during experiences. Our work enriches theory by identifying VR, provides meaningful...

Timely predicting tourist demand is extremely important for the tourism industry. However, due to limited availability of data, most relevant research studies have focused on data a quarterly or monthly basis. In this article, we propose novel hybrid approach, SARIMA + LSTM, that is, seasonal autoregressive integrated moving average (SARIMA) combined with long short-term memory (LSTM) forecast daily arrivals Macau SAR, China. The LSTM model artificial intelligence nonlinear method which has...

Virtual Reality (VR) has been widely adopted by destination marketing organizations (DMOs) to promote a destination. However, the existing literature lacks solid theoretical foundation interpret phenomenon of VR experience. To address this research gap, study aims advance our understanding how two distinct presences (telepresence and sense presence) are formed they influence user responses after A framework was proposed including vividness, presence, telepresence, satisfaction, intention...

Guided by the Stimulus–Organism–Response (S–O–R) and aesthetics frameworks, this research investigated impacts of non-immersive virtual reality (VR) on visitors' perceived utilitarian hedonic values, attitudes toward VR, visit intention. Three hundred thirty-five respondents who had completed a guided tour provided Hong Kong Railway Museum using personal devices such as computers smartphones without having aid more advanced technologies were surveyed. The results revealed that design...

Large Language Models have attracted the attention of tourism researchers, and many discussions been published in leading journals. However, little research has conducted on how to use research. In this paper, we propose a new tourist arrival forecasting model based Model. The Model is used extract produce satisfaction scores from review comments by tourists. generated are incorporated into take full advantage extracted information comments. We applied predict Macao. Experiment results show...

This study investigates how the customer environmental attitude-behavior gap affects a hotel's total carbon emissions and profits. Results indicate that this does not affect profits in peak season but so off-season. It leads to hotel underpricing, thus resulting occupancy increase, emission increase profit decrease. The negative impacts intensify if more customers promising support for reduction have gap. However, holding attitudes change still gap, of on vary with market situations.

In this paper, we applied the temporal fusion transformer model to crude oil price movement modeling and forecasting. The has been adopted in forecasting using attention mechanism, capture different level of autocorrelations among observations prices. Empirical evaluation based multi-horizon ahead conducted. Experiment results show that introduction process improved accuracy significantly at longer time horizon.

The forecasting of tourist arrival depends on the accurate modeling prevalent data patterns found in arrival, especially for daily where changes are more complex and highly nonlinear. In this paper, a new multiscale mode learning-based model is proposed to exploit different features movement. Two popular Mode Decomposition models (MD) Convolutional Neural Network (CNN) introduced at scales extracted using these two MD which dynamically decompose into distinctive intrinsic function (IMF)...

Multi-source data is widely used in the field of energy future prices forecasting, improvement forecast ability and screening are becoming focus current research. In this paper, two tree-based models (namely, Random Forest XGBoost model) employed to predict China's crude oil prices. The empirical analysis confirms that model have superior prediction performances than benchmark performs best. An important finding there a time gap between investor information search processing because...

The purpose of this study was to examine if there were differences in perception by guests on safety and security Airbnb licensed properties. results indicate are the implication is that properties should consider improving their measures from perspectives both service quality marketing.

With the growing appetite of appreciating local gastronomy and need destination branding for culinary tourism, food events have become increasingly popular in many cities. Authenticity has long been recognized as one important factor to evaluate food-related experience; however, likability is rarely examined. The study gives a first attempt include likability, hedonic perspective, together with authenticity, evaluating event experience at festival. A valid sample 447 attendees was recruited...

This study, grounded in Bandura's social cognitive theory, investigates the effects of coaching on knowledge creation and mediating effect self-efficacy. Utilizing data from a 3-wave longitudinal field study involving 290 employees within top 100 chain enterprise China, analysis was conducted using Partial Least Squares Structural Equation Modeling. The findings reveal that face-to-face facilitation positively influences all four dimensions creation, while guidance has diminishing most...

A 100μW, 13bit ADC used for sensor array applications is presented in this paper. The employs an extended counting architecture which the residual error from a first-order incremental ΣΔ modulator encoded by cyclic to achieve high accuracy at relatively speed. Hardware reuse technique utilized low power consumption and small silicon area. prototype implemented 0.18μm CMOS technology with 1.8V supply voltage core area only 0.06mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...

ABSTRACTThe feed index is a weighted sum of the number reactions (i.e. reading, comments, retweets, likes and dislikes, so on.) that content engine actively recommends distributes to users. It provides valuable information from big data on Internet high marketing value Destination Marketing Organization as can be customized. A large-scale empirical study impact tourist arrival forecasting accuracy has been conducted, with new approach proposed incorporate into model higher accuracy. Firstly,...

This paper aims to investigate the role of a consumer satisfaction index (CSI) for financial investments in Hong Kong market. Using yearly data (HKCSI) compile CSI at company level, effect on market value is identified. A hypothesized investment portfolio based only level created, and its return compares with widely used measuring stock performance Kong. formal statistical test outperformance portfolios that load conducted. Capital Asset Pricing Model (CAPM), beta risk entire time period...

In this paper, we used the Baidu feed index to quantify valuable information from search engine, and proposed a China's crude oil futures price forecasting model with index. The empirical analysis confirms that index, which characterizes investor attention of participants in market, provides for internet concerns sentiment, has significant impact on forecasting. We found time lag between query results changes, mostly lies within shorter range. engine data would produce forecasts superior performance.

This study aims to conduct a systematic review on human rights as related mega-events (MEs) locate possible key areas and gaps for further research in the field. A literature has been undertaken utilizing databases of Scopus, Web Sciences, Google Scholar. final sample 127 articles was used this exercise. Findings resulted past studies classified into six groups 18 topics recommending future research. The findings contribute theory by identifying underlining orientating such discovering some...