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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 review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.

This study examines whether international tourism demand in the Visegrád countries is influenced by countries' risk rating on environmental, social and governance (ESG) factors, as non-economic factors relating to ESG risks have been ignored by previous researches on determinants of international tourism demand.

The study investigates panel data for the Visegrád countries comprising the Czech Republic, Hungary, Poland and Slovakia over the period 1995–2019. Recently developed techniques of augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators are employed so as to take care of cross-sectional dependence, nonstationary residuals and possible heterogeneous slope coefficients.

The regression estimates suggest that besides economic factors, the perception of international tourists regarding ESG risk is another important determinant of international tourism demand in the Visegrád countries. The study also established that income levels in the tourists' originating countries are the most critical determinant of international tourism demand to the Visegrád countries.

The research outcomes of the study include the need for the Visegrád countries to direct policies towards further mitigating their ESG risks in order to improve future international tourism demand in the area. They also need to ensure exchange rate stability to prevent volatility and sudden spikes in the relative price of tourism in their countries.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.

This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism has been identified as a new tourism sub-sector with high potential, and is thus expected to boost economic growth and sustainability.

This study reviews the literature on the determinants of educational tourism demand. Even though the existing literature is intensively discussed, mostly focusing on the educational tourism demand from an individual consumer's perspective, this study makes an innovation in line with the aggregate demand view. The study uses data that consist of the enrolment of international students from 47 home countries who studied in Malaysia from 2008 to 2017. The study utilised the dynamic panel method of analysis.

This study affirms that income per capita, educational tourism price, price of competitor countries and quality of universities based on accredited programmes and world university ranking are the determinants of educational tourism demand in both the short and the long term. Also, a dynamic effect exists in educational tourism demand.

The results imply that government should take the quality of services for existing students, price decisions and QU into account to promote the country as a tertiary education hub and achieve sustainable development.

Research on the determinants of the demand for educational tourism is rare in terms of macro data, and this study includes the roles of QU, competitor countries and dynamic effects.

This paper aims to propose a hybrid-forecasting model for long-term tourism demand forecasting. As such, it attempts to model the tourism demand in the Philippines, which is a relatively underrepresented area in the literature, despite its tourism sector’s growing economic progress.

A hybrid support vector regression (SVR) – seasonal autoregressive integrated moving averages (SARIMA) model is proposed to model the seasonal, linear and nonlinear components of the tourism demand in a destination country. The paper further proposes the use of multiple criteria decision-making (MCDM) approaches in selecting the best forecasting model among a set of considered models. As such, a preference ranking organization method for enrichment of evaluations (PROMETHEE) II is used to rank the considered forecasting models.

The proposed hybrid SVR-SARIMA model is the best performing model among a set of considered models in this paper using performance criteria that evaluate the errors of magnitude, directionality and trend change, of a forecasting model. Moreover, the use of the MCDM approach is found to be a relevant and prospective approach in selecting the best forecasting model among a set of models.

The novelty of this paper lies in several aspects. First, this paper pioneers the demonstration of the SVR-SARIMA model’s capability in forecasting long-term tourism demand. Second, this paper is the first to have proposed and demonstrated the use of an MCDM approach for performing model selection in forecasting. Finally, this paper is one of the very few papers to provide lenses on the current status of Philippine tourism demand.

The purpose of this paper is to examine the impact of various cultural amenities on tourism demand in 168 European cities.

Using data from the European Commission’s Culture and Creative Cities Monitor 2017, a series of regressions are estimated to examine the impact of various cultural amenities on tourism demand while also controlling for other factors that may impact on tourism demand. Diagnostic tests are also conducted to check the robustness of the results.

The results reveal that cultural amenities in the form of sights, landmarks, museums, concerts and shows have a positive impact on tourism demand. By pinpointing the cultural amenities that are important for increasing tourism demand, the findings aid stakeholders in the tourism industry as they develop post-pandemic recovery plans.

This paper identifies two key aspects of the cultural tourism literature that require deeper investigation and aims to address these aspects. Firstly, while many studies focus on a specific or narrow range of cultural amenities, this study includes a series of measures to capture a range of cultural amenities. Secondly, while many studies are narrow in geographical scope, this paper includes data on 168 European cities across 30 countries.

While researchers have studied the impact of social media on tourist behaviour Milano et al. (2011) and Hays et al. (2013), very few studies have explored the impact of social media on sustainable tourism, and thus, it can be said to be in its “infancy” (Han et al., 2017). There exists a “knowledge gap” not just with tourists but also with researchers, as the issue on sustainable tourism consumption is “rarely investigated directly in tourism researches” or consumer behaviour studies, and there is often discrepancy in literature on the issue (Cohen et al., 2014; Bray et al., 2011). While the potential for social media in promoting sustainable tourism is known considering the use of it for socialisation and knowledge sharing, empirical researches to make in depth enquiry on the same is “rare” (Ali and Frew, 2010; Sarkar et al., 2014). Also, the differences between markets for sustainable tourism amongst different markets needs to explored further (Weber, 2019). The purpose of this study is to fill this gap by proposing a conceptual framework and empirically testing how social media can be used to generate and promote sustainable tourism demand among through evidences from Indian tourists. RQ1: what are the key drivers to use social media by sustainable tourists? RQ2: can social media promotions help sustainable demand generation through spreading awareness and connecting fellow sustainable tourists?

A total of 350 Indian tourists were reached through Google forms distributed through various channels, amongst which 265 responded with a response rate of 75.7%. The data were coded and checked for any outliers and missing values. To avoid any biases, incomplete forms were not counted and after data cleaning, 250 respondents were found to be appropriate with all the responses. Analysis of demographic and travel profile was done through SPSS 22 to check variances in the groups, frequencies and chi square values were calculated. Since this is an exploratory study, the aim was more on prediction rather than model confirmation, thus the technique used and found to be appropriate was partial least squares structural equation modelling (PLS-SEM).

Variances of social media were used in the demographic groups and found that there was no significant difference found as per age and education. Even variation of travel habits was found to be not significant with social media use. It can be seen that social media promotion activities indeed create awareness amongst people about sustainability; creating awareness about sustainability indeed leads to connecting green tourists together. On the other hand, social media promotional activities may not necessarily connect potential green tourists together; awareness positively impacts the generation of sustainable demand is also supported. It can be seen that merely connecting potential green tourists does not necessarily create demand. Social media promotion activities are indeed instrumental in creating a sustainable demand amongst tourist.

This study takes into account the informational and environmental knowledge aspect of sustainable behaviour adoption by green tourists (Swarbrooke and Horner, 2007; Miller, 2003; Chan et al., 2014). This study draws implications based on the behaviour of Indian tourists and thus, the generalisation to other countries may not be as accurate as Indians differ culturally from the world at large. Even though the study involves different age groups, the mean age is of younger Indian tourists, which is also often considered as the most active users of social media and thus likely to be impacted more. Also, it is believed that these younger green consumers who are already inclined towards sustainability tend to seek more information on ethical issues (Finney, 2014). The sample size of the study is very small (n = 250) and was only checked for variation amongst gender and profession; other aspects such as income and employment (Swarbrooke and Horner, 2007; Miller, 2003) have been kept out of the study and thus not included as a part of demographics. More demographic characteristics can be taken into account to study if they play a mediating role in generating sustainable demand as a part of the analysis of this conceptual framework proposed.

Internet allows users to obtain information about products and brands to its users through various social media such as blogs, forums, wikis content sharing, etc. (Hennig-Thurau and Walsh, 2003; Reilly and Weirup, 2010). Strategies can thus be formulated to target sustainable tourists with sustainable destinations and amenities, so as to attract those tourists who appreciate and commit to the cause of sustainability (López-Sánchez and Pulido-Fernández, 2016). Using social media as a promotion tool can help in educating customers (Xiang and Gretzel, 2010) on the various sustainable tourism services they intend to offer, as the results supports the use of social media promotion for generating sustainable demand amongst the tourists. Also, the sustainable tourism providers can make use of promotional activities focussing on building online pro environmental tourist-based communities using the user generated contents which can positively lead to adoption of collective social behaviour and sustainable practices (Han et al., 2017). Specifically, the use of short interactive messages can be used for social media promotions, so as to increase “organisation prominence” amongst the green target groups online (Strähle and Gräff, 2017). While it was noted that different markets react differently to the idea of sustainability, and thus, different markets need to be explored deeper (Weber, 2019); this study attempts to provide a perspective of Indian tourists which not just adds to the literature on Indian tourist behaviour but also provides a viewpoint of the Asian tourists. It also enriches the existing literature on the use of AIDA model for services and tourism specifically which as a theoretical base is unexplored.

The study adds to the rising interest in understanding the behavioural changes in tourists (Hall, 2016) and provides insights on “the versatility of the topic of relationship between sustainable tourism and marketing” (Font and McCabe, 2017). While ethical consumption is essential to preserve resources, the study of this area of consumer behaviour is “under examined”, as majority studies focus on products, very few studies elucidate on encouraging it through social marketing (Newholm and Shaw, 2007). Thus, this study attempts to fill the gap in the literature by proposing a framework for generating sustainable demand amongst tourists so that they are inclined socially and sustainably both through the use of social media. It is often noted that tourists are unwilling to change their travel behaviour as a result of lack of awareness or due to hesitance of sacrificing (Juvan and Dolnicar, 2014; Miller et al., 2010). This study provides empirical evidence that supports the awareness of sustainability as a means of generating sustainable demand amongst tourists. Knowledge regarding tourism demand helps in the further development of tourism products and its marketing initiatives (Weber, 2019). Thus, it allows tourism players to understand that Indian tourists are open to sustainable tourist practices if enough information is provided to them.

Several studies have been made that analyze factors that affect the demand of tourism from several optics. This paper aims to study the factors that determine the demand for tourism in Mexico, through an econometric analysis, by using the Johansen cointegration model (1991) to determine the long-term elasticity between the demand of tourists and the wealth related to its main markets (the USA and Canada) and the relative prices in Mexico and its two main competitors (the Dominican Republic and Costa Rica).

The authors used econometric analysis using Johansen’s cointegration model (1991), using as a dependent variable the demand of tourists from the main countries of origin (the USA and Canada), taking as data the number of tourists by air in the period 1980-2015, according to information from the SIIMT. The independent variables are the relative wealth of the country of origin of the tourists (wealth of the tourist in Mexico concerning the wealth in their country of origin) and the relative prices of the destination country with respect to the country of competition. The source for per capita income and the consumer price index is the World Bank.

The results obtained in this document show that in the long-term the price is a factor of impact in the purchase decision of both markets analyzed. Presenting an elastic demand to the price, which implies that the market is sensitive to the variations of the price of tourist services, opting for the destination that offers better prices, with a higher sensitivity to the price when compared with Costa Rica. Coinciding with previous studies carried out in other tourist destinations, such as in the work of Patsouratis et al. (2005).

The main contribution of this work is to determine the long-term relationship, through a cointegration analysis of Johansen (1991). A methodology that has not been used to perform a competitive analysis between countries. Additionally, the present work uses variables different from those considered in previous works; the dependent variable is the demand of tourists from the main countries of origin (the USA and Canada) and as dependent variables the relative wealth of the country of origin of the tourists (Wealth of the tourist in Mexico with respect to wealth in their country of origin) and the relative prices of the destination country with respect to the country of competition.

The purpose of this paper is to focus on the reforms in the public-holiday-policy system and their influence on the domestic tourism in China. The major reforms in the Chinese holiday system in the last 20 years and the overall changes in the demand for domestic tourism are analyzed in this paper to provide a better understanding of China’s holiday-system reform for policy makers in the future.

This paper summarizes the development and reform of the holiday system in China. Policy review and domestic tourism statistics were applied to study the intrinsic relationship between the holiday system and the domestic tourism. The statistics of domestic tourism are cited, including the growth rates of both urban and rural tourists, the domestic tourism expenditure per capita, etc. Finally, this research explains the trends of these rates in a comprehensive background.

The increasing length of holidays positively affects the domestic tourism demand by increasing the leisure time. Yet, the holiday-tourism activities lead to a series of problems, such as a huge pressure on transportation, overloaded tourist attractions, and threats to safety precautions. Paid leave, price leverage, and more reasonable tourist-attraction arrangements will be effective in easing China’s holiday rush.

Through studying the intrinsic relationship between the holiday system and the domestic tourism, this paper points out the problems of excessive concentration of domestic tourism demand in a particular time, caused by the holiday system. Solutions and suggestions are provided on the basis of the analysis.