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Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

The purpose of this paper is to determine whether different scales and ways to collect reviews and ratings found on online travel agencies (OTAs) can affect hotels, and whether hotels obtain the same or different evaluations.

Hotel ratings from five OTAs in four European markets were collected and compared in pairs. An initial comparison was made with the hotel scores of each OTA to show what a typical user would see. Then, a rescaled score (0-10) was used to compare all the OTA scales appropriately and to distinguish between what customers observe and what the reality is.

The results reveal that Booking.com that uses a scale (2.5-10) and Agoda with a scale (2-10) seem to give higher rating scores than Atrapalo (1-10), Travel Republic (0-10) and hotel reservation service (1-10). However, when the scores are rescaled (0-10), the worst ratings are found on Booking.com followed by Agoda.

OTAs should include, next to the scores, the scale used to rate hotels so as to provide users with better and clearer information. Moreover, rating questionnaires should match the verbal denominations with their numerical values to avoid biased ratings.

OTAs and hotel managers are losing information provided by customers because customers are not aware of the scale when rating hotels. Moreover, hotel ratings are used by potential customers to obtain a clearer image of an establishment. However, if some hotels are being overrated by some scales, customers might have higher expectations, which may not be met.

The unique rating scales of Booking.com and Agoda provide additional insights into their hotel evaluations, which seem to be apparently higher when in fact they are not.

在线旅行评论评分量表及其对酒店得分和竞争力的影响

摘要

这项研究旨在研究在线旅行社（OTA）上评论和评级的不同量表和方式是否会影响酒店获得的评估。

本研究收集并比较了来自四个欧洲市场中五个OTA的酒店等级数据。研究首先对每个OTA的酒店得分进行了比较, 以显示一般用户会看到的内容。然后研究使用重新缩放的得分（0-10）来恰当地比较所有OTA的酒店等级, 并区分顾客观察到的内容和现实。

结果显示, Booking.com使用的量表（2.5-10）和Agoda的量表（2-10）, 似乎高于Atrapalo（1-10）, Travel Republic（0-10）和 hotel reservation service （1-10）的评分。但是, 当分数重新调整为（0-10）时, 最差的评分是在Booking.com上, 其次是Agoda。

OTA应在评分旁边注明用于对酒店进行评分的量表, 以便为用户提供更好, 更清晰的信息。此外, 评级问卷应使评价描述与其数值相匹配, 以避免评级出现偏差。

OTA和酒店经理正在丢失客户所提供的信息, 因为客户在对酒店进行评级时并不了解其使用的量表。此外, 潜在客户使用酒店评级来获得更清晰的企业形象。但是, 如果某些酒店被某些网站的评级量表高估, 那么客户可能会有偏高的期望, 而这些期望可能无法被满足。

Booking.com和Agoda的独特评分等级标准为酒店提供了更多见解, 而实际上酒店的情况可能并非如此。

Las escalas de calificación de las opiniones de los viajes online y sus efectos en la valoración y competitividad de los hoteles.

El objetivo de esta investigación es determinar si las diferentes escalas y formas de recopilar opiniones y valoraciones de las Agencias de Viajes Online (OTAs), pueden afectar a si los hoteles tienen las mismas o distintas calificaciones.

Las calificaciones de hoteles de cinco OTAs en cuatro mercados europeos, se recopilaron y compararon por pares. Se realizó una comparación inicial con las puntuaciones de los hoteles de cada OTA, para mostrar lo que vería un usuario típico. Luego, se utilizó una puntuación de reescalado (0-10), para comparar todas las escalas de las OTAs de manera apropiada y así poder diferenciar entre lo que los clientes observan y lo que es en realidad.

Los resultados revelan que Booking.com, que utiliza una escala (2.5-10) y Agoda con una escala (2-10), parecen puntuar con calificaciones más altas que Atrapalo (1-10), Travel Republic (0-10) y hotel reservation service (1-10). Sin embargo, cuando se vuelven a escalar las puntuaciones (0-10), las peores calificaciones se encuentran en Booking.com, seguida de Agoda.

Las OTAs deben incluir, junto a las puntuaciones, la escala utilizada para calificar los hoteles a fin de proporcionar a los usuarios una información mayor y más clara. Además, los cuestionarios de calificación deben hacer coincidir las denominaciones verbales con sus valores numéricos para evitar calificaciones sesgadas.

Por un lado las OTAs y los gerentes de hoteles, están perdiendo información proporcionada por los clientes, porque los clientes no son conscientes del tipo de escala utilizada cuando califican los hoteles. Por otro lado, los clientes potenciales utilizan las calificaciones de los hoteles para obtener una imagen más clara de un establecimiento. Por lo que en muchos casos, los clientes pueden tener expectativas más altas, que pueden no cumplirse, si los hoteles están siendo sobrevalorados por algunas escalas.

Las escalas de calificación únicas de Booking.com y Agoda, brindan información adicional sobre las evaluaciones de sus hoteles que parecen ser aparentemente más altas cuando en realidad no lo son.

An official destination website (ODW) is a key component for tourist’s decision-making processes. ODW acts as a direct channel where users may share experiences and opinions about previous or future travels. At the same time, it drives user participation in destination branding activities. In this context, it is crucial to identify how the destination website, using Web 2.0 technologies, could motivate user’s participation with the brand. The purpose of this paper is to propose and evaluate a model that posits the destination website quality as a determinant factor to predict users’ attitudes toward the website and their willingness to participate in co-creation experiences.

Using a combined qualitative and quantitative method, this paper provides an exploratory research that examines the role of destination website quality on attitudes toward the website and the willingness to participate in online co-creation experiences.

Findings confirm that there is a direct and significant relationship between website quality, attitudes toward the website and willingness to participate in online co-creation experiences. Moreover, attitudes toward the website partially mediate relationships between destination website quality and willingness to participate in online co-creation experiences.

The literature of value co-creation is trying to identify which factors drive consumer’s participation with brands across different consumption contexts. This study provides evidence that confirms, from a tourism destination website point of view, that website quality is one of these key factors that motives user’s co-creation with a destination.

The paper presents a mathematical problem involving quasistatic contact between a thermo-electro-viscoelastic body and a lubricated foundation, where the contact is described using a version of Coulomb’s law of friction that includes normal damped response conditions and heat exchange with a conductive foundation. The constitutive law for the material is thermo-electro-viscoelastic. The problem is formulated as a system that includes a parabolic equation of the first kind for the temperature, an evolutionary elliptic quasivariational inequality for the displacement and a variational elliptic equality for the electric stress. The author establishes the existence of a unique weak solution to the problem by utilizing classical results for evolutionary quasivariational elliptic inequalities, parabolic differential equations and fixed point arguments.

The author establishes a variational formulation for the model and proves the existence of a unique weak solution to the problem using classical results for evolutionary quasivariational elliptic inequalities, parabolic difierential equations and fixed point arguments.

The author proves the existence of a unique weak solution to the problem using classical results for evolutionary quasivariational elliptic inequalities, parabolic difierential equations and fixed point arguments.

The author studies a mathematical problem between a thermo-electro-viscoelastic body and a lubricated foundation using a version of Coulomb’s law of friction including the normal damped response conditions and the heat exchange with a conductive foundation, which is original and requires a good understanding of modeling and mathematical tools.

In this work, we estimated the different entropies like Shannon entropy, Rényi divergences, Csiszár divergence by using Jensen’s type functionals. The Zipf’s–Mandelbrot law and hybrid Zipf’s–Mandelbrot law are used to estimate the Shannon entropy. The Abel–Gontscharoff Green functions and Fink’s Identity are used to construct new inequalities and generalized them for m-convex function.

The flexibility of batch process enables its wide application in fine-chemical, pharmaceutical and semi-conductor industries, whilst its complexity necessitates control performance monitoring to ensure high operation efficiency. This paper proposes a data-driven approach to carry out controller performance monitoring within batch based on linear quadratic Gaussian (LQG) method.

A linear time-varying LQG method is proposed to obtain the joint covariance benchmark for the stochastic part of batch process input/output. From historical golden operation batch, linear time-varying (LTV) system and noise models are identified based on generalized observer Markov parameters realization.

Open/closed loop input and output data are applied to identify the process model as well as the disturbance model, both in Markov parameter form. Then the optimal covariance of joint input and output can be obtained by the LQG method. The Hotelling's Tˆ2 control chart can be established to monitor the controller.

(1) An observer Markov parameter approach to identify the time-varying process and noise models from both open and closed loop data, (2) a linear time-varying LQG optimal control law to obtain the optimal benchmark covariance of joint input and output and (3) a joint input and output multivariate control chart based on Hotelling's T² statistic for controller performance monitoring.

This paper aimed a fractional-order sliding mode-based lateral lane-change control method that was proposed to improve the path-tracking accuracy of vehicle lateral motion.

In this paper the vehicle presighting and kinematic models were established, and a new sliding mode control isokinetic convergence law was devised based on the fractional order calculus to make the front wheel turning angle approach the desired value quickly. On this basis, a fractional gradient descent algorithm was proposed to adjust the radial basis function (RBF) neuron parameter update rules to improve the compensation speed of the neural network.

The simulation results revealed that, compared to the traditional sliding mode control strategy, the designed controller eliminated the jitter of the sliding mode control, sped up the response of the controller, reduced the overshoot of the system parameters and facilitated accurate and fast tracking of the desired path when the vehicle changed lanes at low speeds.

This paper combines the idea of fractional order calculus with gradient descent algorithm, proposed a fractional-order gradient descent method applied to RBF neural network and fast adjustment the position and width of neurons.

This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor (BR) onboard the vehicle, which overcomes the vulnerability of having conventional temperature sensor.

In this study, the energy model based sensorless estimation method is developed. By analyzing the structure and the convection dissipation process of the BR onboard the vehicle, the energy-based operational temperature model of the BR and its cooling domain is established. By adopting Newton's law of cooling and the law of conservation of energy, the energy and temperature dynamic of the BR can be stated. To minimize the use of all kinds of sensors (including both thermal and electrical), a novel regenerative braking power calculation method is proposed, which involves only the voltage of DC traction network and the duty cycle of the chopping circuit; both of them are available for the traction control unit (TCU) of the vehicle. By utilizing a real-time iterative calculation and updating the parameter of the energy model, the operational temperature of the BR can be obtained and monitored in a sensorless manner.

In this study, a sensorless estimation/monitoring method of the operational temperature of BR is proposed. The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR, instead of adding dedicated thermal sensors. The results also validate the effectiveness of the proposal is acceptable for the engineering practical.

The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks. The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.