Journal articles on the topic 'Tourism Forecasting Methodology'
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1
Krasić, Davor, and Petra Gatti. "Forecasting Methodology of Maritime Passenger Demand in a Tourist Destination." PROMET - Traffic&Transportation 21, no. 3 (March 2, 2012): 183–90. http://dx.doi.org/10.7307/ptt.v21i3.224.
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Maritime passenger demand forecasting is a task that is almost always present in the development studies of passenger ports, both due to operational and investment requirements. If a port belongs to a tourist destination, then there is a reasonable intention to use the forecasting model in order to establish the dependence between the passenger and tourist demand. Since the reliability of forecasting depends to a great extent on the quality and availability of data, the forecasting model is often a compromise between the theoretical assumptions and practical possibilities. This paper presents the approach to maritime passenger demand forecasting using a case study of the tourist destination – Poreč, which has been the strongest destination in Croatia regarding tourist traffic for many years. The presented forecasting models can serve as one of the guidelines for further study of the relations between traffic and tourism. KEY WORDS: forecasting maritime passenger demand, forecasting tourist demand, traffic and tourism
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Li, Xin, and Rob Law. "Forecasting Tourism Demand with Decomposed Search Cycles." Journal of Travel Research 59, no. 1 (January 28, 2019): 52–68. http://dx.doi.org/10.1177/0047287518824158.
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This study aims to examine whether decomposed search engine data can be used to improve the forecasting accuracy of tourism demand. The methodology was applied to predict monthly tourist arrivals from nine countries to Hong Kong. Search engine data from Google Trends were first decomposed into different components using an ensemble empirical mode decomposition method and then the cyclical components were examined through statistical analysis. Forecasting models with rolling window estimation were implemented to predict the tourist arrivals to Hong Kong. Results indicate the proposed methodology can outperform the benchmark model in the out-of-sample forecasting evaluation of Choi and Varian (2012). The findings also demonstrate that our proposed methodology is superior in forecasting turning points. This study proposes a unique decomposition-based perspective on tourism forecasting using online search engine data.
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Kyfyak, Vasyl, and Olexander Kyfyak. "A Methodology for Calculating Individual Indicators of Tourism Activity." Turyzm 28, no. 1 (June 1, 2018): 41–45. http://dx.doi.org/10.2478/tour-2018-0005.
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Abstract The purpose of the article is to find modern approaches for calculating the quantity of given characteristic features and accompanying tourist services and goods purchased by tourists, to determine the number of tourists visiting a city and forecasting the volume of travel services for the future. Solutions to the tasks set out in the article have been carried out with the help of both general academic and specialist research methods: analysis and synthesis, systematization and generalization, expert evaluation and extrapolation. Using the example of the city of Chernivtsi (Ukraine) the number of tourists visiting the city has been determined, the volume of services rendered and the average annual growth rate of tourism service implementation over the last five years has been calculated contributing to forecasting the volume of service delivery for the future.
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Kyfyak, Vasyl, and Olexander Kyfyak. "A methodology for calculating individual indicators of tourism activity." Turyzm/Tourism 28, no. 1 (June 30, 2018): 41–45. http://dx.doi.org/10.18778/0867-5856.28.1.13.
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The purpose of the article is to find modern approaches for calculating the quantity of given characteristic features and accompanying tourist services and goods purchased by tourists, to determine the number of tourists visiting a city and forecasting the volume of travel services for the future. Solutions to the tasks set out in the article have been carried out with the help of both general academic and specialist research methods: analysis and synthesis, systematization and generalization, expert evaluation and extrapolation. Using the example of the city of Chernivtsi (Ukraine) the number of tourists visiting the city has been determined, the volume of services rendered and the average annual growth rate of tourism service implementation over the last five years has been calculated contributing to forecasting the volume of service delivery for the future.
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Shulhina, Liudmyla. "Methodology for Forecasting Revenues from the Sale of Innovative Products in the Domestic Tourism Market." Marketing of Scientific and Research Organizations 41, no. 3 (September 1, 2021): 95–114. http://dx.doi.org/10.2478/minib-2021-0016.
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Abstract This article presents a methodology for forecasting the expected sales of innovative tourism products in the domestic market. The principles of the product life cycle concept and consumer behavior theory are taken as starting points for calculating the sales volumes of an innovative product as well as the rate of its penetration into the market. A method of measuring the level of consumer commitment to a travel agency and its offerings is posited, and the relationship between the structure of the target market and market activity in purchasing tourist products is demonstrated. Deep market segmentation is applied to take into account the behavioral peculiarities of individual subsegments (Loyalists Market, Sympathizers Market, Qualified Market, Finders Market, Serviced Market, Possible Market, Potential Consumers Market, Perspective Market). Formulas are proposed for calculating the volume of each of the identified markets. An improved and adapted model for the tourist market (by E. Rogers and F. Bass) is used to calculate the diffusion rates of domestic tourist products. This methodology of forecasting the expected sales of innovative tourism products in the domestic market is empirically confirmed based on data on the domestic tourism market in the region of Vinnytsiya, Ukraine.
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Li, Gang, and Xiaoying Jiao. "Tourism forecasting research: a perspective article." Tourism Review 75, no. 1 (January 15, 2020): 263–66. http://dx.doi.org/10.1108/tr-09-2019-0382.
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Purpose The purpose of this paper is to provide a short review of tourism forecasting literature and general summary of the trends and developments in tourism forecasting and point out directions for future research in the next 75 years. Design/methodology/approach This is a general literature overview. Findings Key trends are identified for next 75 years. Originality/value First overview in tourism forecasting that provides foresight on long-term future trends (over next 75 years).
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Pirthee, Medha. "Grey-based model for forecasting Mauritius international tourism from different regions." Grey Systems: Theory and Application 7, no. 2 (August 7, 2017): 259–71. http://dx.doi.org/10.1108/gs-04-2017-0008.
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Purpose The purpose of this paper is to understand the trend and forecast the number of tourists from different regions of the world to Mauritius. Design/methodology/approach The paper adopts two grey system models, the even model GM(1,1) and the non-homogeneous discrete grey model (NDGM), to forecast the total number of international tourism to Mauritius and its structure from different regions tourist arrivals to Mauritius for the next three years. Grey system theory models were used to account for uncertainties and the dynamism of the tourism sector environment. The two models were applied as a comparison to obtain more reliable forecasting figures. Findings The results demonstrate that both of the grey system models can be successfully applied with high accuracy for Mauritian tourism prediction, and also the number of tourist arrivals to Mauritius shows a continued augmentation for the upcoming years. Practical implications Forecasting is meaningful since the Government of Mauritius, private companies or any concerned authority can adopt the forecasting methods exposed in this paper for the development of the tourism sector through managerial and economic decision making. Originality/value Mauritius is a charming travel destination. Through this paper, it can be seen that future tourism travel to Mauritius has been successfully predicted based on previous data. Moreover, it seems that the grey system theory models have not been utilised yet as forecasting tools for the tourism sector of Mauritius as opposed to other countries such as China and Taiwan.
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Moro, Sérgio, and Paulo Rita. "Forecasting tomorrow’s tourist." Worldwide Hospitality and Tourism Themes 8, no. 6 (December 5, 2016): 643–53. http://dx.doi.org/10.1108/whatt-09-2016-0046.
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Purpose This study aims to present a very recent literature review on tourism demand forecasting based on 50 relevant articles published between 2013 and June 2016. Design/methodology/approach For searching the literature, the 50 most relevant articles according to Google Scholar ranking were selected and collected. Then, each of the articles were scrutinized according to three main dimensions: the method or technique used for analyzing data; the location of the study; and the covered timeframe. Findings The most widely used modeling technique continues to be time series, confirming a trend identified prior to 2011. Nevertheless, artificial intelligence techniques, and most notably neural networks, are clearly becoming more used in recent years for tourism forecasting. This is a relevant subject for journals related to other social sciences, such as Economics, and also tourism data constitute an excellent source for developing novel modeling techniques. Originality/value The present literature review offers recent insights on tourism forecasting scientific literature, providing evidences on current trends and revealing interesting research gaps.
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Hu, Mingming, Mengqing Xiao, and Hengyun Li. "Which search queries are more powerful in tourism demand forecasting: searches via mobile device or PC?" International Journal of Contemporary Hospitality Management 33, no. 6 (May 31, 2021): 2022–43. http://dx.doi.org/10.1108/ijchm-06-2020-0559.
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Purpose While relevant research has considered aggregated data from mobile devices and personal computers (PCs), tourists’ search patterns on mobile devices and PCs differ significantly. This study aims to explore whether decomposing aggregated search queries based on the terminals from which these queries are generated can enhance tourism demand forecasting. Design/methodology/approach Mount Siguniang, a national geopark in China, is taken as a case study in this paper; another case, Kulangsu in China, is used as the robustness check. The authors decomposed the total Baidu search volume into searches from mobile devices and PCs. Weekly rolling forecasts were used to test the roles of decomposed and aggregated search queries in tourism demand forecasting. Findings Search queries generated from PCs can greatly improve forecasting performance compared to those from mobile devices and to aggregate search volumes from both terminals. Models incorporating search queries generated via multiple terminals did not necessarily outperform those incorporating search queries generated via a single type of terminal. Practical implications Major players in the tourism industry, including hotels, tourist attractions and airlines, can benefit from identifying effective search terminals to forecast tourism demand. Industry managers can also leverage search indices generated through effective terminals for more accurate demand forecasting, which can in turn inform strategic decision-making and operations management. Originality/value This study represents one of the earliest attempts to apply decomposed search query data generated via different terminals in tourism demand forecasting. It also enriches the literature on tourism demand forecasting using search engine data.
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Panchenko, Svitlana. "Management of the sphere of tourism in a specific market of Ukraine." Problems of innovation and investment-driven department, no. 18 (February 12, 2019): 85–92. http://dx.doi.org/10.33813/2224-1213.18.2019.9.
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he subject of research – religious tourism as a promising direction for the development of tourism. The purpose of the article isimproving the management of religious tourism in the modern tourist market. Methodology of work –applying the methods of analysis, synthesis, comparison, synthesis, forecasting, as well as in the use of historical and cultural approaches. The results of the work – presents proposals for solving the problems of religious tourism, taking into account the specifics of this area. Highlight the problematic issues related to the field of tourism and suggested ways to solve them. Conclusions – as a result of the study, it was established that the religious and tourist potential of our country is not used at the proper level, and the creation of conditions for high-quality religious tourism of our compatriots and foreign citizens requires more active government policies and attracting investments in the tourism.
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Panchenko, Svitlana, Katerina Fokina-Mezentseva, Ievgeniia Dragomirova, Larysa Plakhotnikova, and Inna Levytska. "Use of intelligent technologies in tourism." LAPLAGE EM REVISTA 7, no. 3D (October 7, 2021): 28–34. http://dx.doi.org/10.24115/s2446-6220202173d1687p.28-34.
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The purpose of the article is to explore the essence and features of using intelligent technologies in tourism and to develop proposals for their implementation. The subject of research – intelligent technologies in tourism, the technology of forming the "profile" of the tourist. The research methodology consists in the application of methods of analysis, synthesis, comparison, generalization, forecasting, as well as in the use of systematic and activity approaches. The article presents the technology of forming the "profile" of the tourist. The scientific novelty is that this article proves the effectiveness of the use of intelligent technologies to create a model of the tourist, his "profile" using neural networks. Effective use of information from various sources in the field of tourism is an important and difficult task. Managers are often forced to make decisions based on partial, incomplete and inaccurate information. The article considers knowledge management in a rapidly changing environment for the task of promoting a tourism product.
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Wu, Doris Chenguang, Haiyan Song, and Shujie Shen. "New developments in tourism and hotel demand modeling and forecasting." International Journal of Contemporary Hospitality Management 29, no. 1 (January 9, 2017): 507–29. http://dx.doi.org/10.1108/ijchm-05-2015-0249.
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Purpose The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field. Design/methodology/approach Articles on tourism and hotel demand modeling and forecasting published mostly in both science citation index and social sciences citation index journals were identified and analyzed. Findings This review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, whereas disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area. Research limitations/implications The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implications This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/value The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.
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Ramos, Vicente, Woraphon Yamaka, Bartomeu Alorda, and Songsak Sriboonchitta. "High-frequency forecasting from mobile devices’ bigdata: an application to tourism destinations’ crowdedness." International Journal of Contemporary Hospitality Management 33, no. 6 (March 19, 2021): 1977–2000. http://dx.doi.org/10.1108/ijchm-10-2020-1170.
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Purpose This paper aims to illustrate the potential of high-frequency data for tourism and hospitality analysis, through two research objectives: First, this study describes and test a novel high-frequency forecasting methodology applied on big data characterized by fine-grained time and spatial resolution; Second, this paper elaborates on those estimates’ usefulness for visitors and tourism public and private stakeholders, whose decisions are increasingly focusing on short-time horizons. Design/methodology/approach This study uses the technical communications between mobile devices and WiFi networks to build a high frequency and precise geolocation of big data. The empirical section compares the forecasting accuracy of several artificial intelligence and time series models. Findings The results robustly indicate the long short-term memory networks model superiority, both for in-sample and out-of-sample forecasting. Hence, the proposed methodology provides estimates which are remarkably better than making short-time decision considering the current number of residents and visitors (Naïve I model). Practical implications A discussion section exemplifies how high-frequency forecasts can be incorporated into tourism information and management tools to improve visitors’ experience and tourism stakeholders’ decision-making. Particularly, the paper details its applicability to managing overtourism and Covid-19 mitigating measures. Originality/value High-frequency forecast is new in tourism studies and the discussion sheds light on the relevance of this time horizon for dealing with some current tourism challenges. For many tourism-related issues, what to do next is not anymore what to do tomorrow or the next week. Plain Language Summary This research initiates high-frequency forecasting in tourism and hospitality studies. Additionally, we detail several examples of how anticipating urban crowdedness requires high-frequency data and can improve visitors’ experience and public and private decision-making.
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Tian, Fengjun, Yang Yang, Zhenxing Mao, and Wenyue Tang. "Forecasting daily attraction demand using big data from search engines and social media." International Journal of Contemporary Hospitality Management 33, no. 6 (May 18, 2021): 1950–76. http://dx.doi.org/10.1108/ijchm-06-2020-0631.
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Purpose This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media. Design/methodology/approach Using daily tourist arrival data to Mount Longhu, China in 2018 and 2019, the authors estimated ARMA, ARMAX, Markov-switching auto-regression (MSAR), lasso model, elastic net model and post-lasso and post-elastic net models to conduct one- to seven-days-ahead forecasting. Search engine data and social media data from WeChat, Douyin and Weibo were incorporated to improve forecasting accuracy. Findings Results show that search engine data can substantially reduce forecasting error, whereas social media data has very limited value. Compared to the ARMAX/MSAR model without big data predictors, the corresponding post-lasso model reduced forecasting error by 39.29% based on mean square percentage error, 33.95% based on root mean square percentage error, 46.96% based on root mean squared error and 45.67% based on mean absolute scaled error. Practical implications Results highlight the importance of incorporating big data predictors into daily demand forecasting for tourism attractions. Originality/value This study represents a pioneering attempt to apply the regularized regression (e.g. lasso model and elastic net) in tourism forecasting and to explore various daily big data indicators across platforms as predictors.
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Zakharova, Tеtiana. "THE IMPORTANCE OF INFORMATION TECHNOLOGY FOR FORECASTING THE ACTIVITIES OF THE ENTERPRISE IN THE TOURISM BUSINESS." Three Seas Economic Journal 3, no. 3 (October 31, 2022): 28–33. http://dx.doi.org/10.30525/2661-5150/2022-3-5.
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The aim of the article is to study the importance of information technologies for forecasting business activity in the tourism business. The analysis of the processes taking place in the industry shows a discrepancy between the level of application of information technologies in the activities of domestic business entities in the sphere of tourism development and their implementation in tourist developed countries of the world. Specific features of the creation and implementation of tourism services (a large number of participants and a significant geographical reference, a balanced system of relations between the subjects of the tourism market, territorial differentiation of the tourist product, remoteness of the place of sale of tourist services from the place of their consumption) necessitate an increase in the level of provision of the management system of modern information technology. Methodology. The following methods were used to study this topic: descriptive, idealization, statistical, field research. Much of the data in this study was obtained through observations of both tourism businesses and consumers of tourism services. Results. The need to forecast the results of the enterprise is due to a significant degree of uncertainty and a large number of risks, because the economic environment, both external and internal, is characterized by high dynamics and changes. Forecast indicators are an important component of the management process of the enterprise and its divisions in the context of identifying opportunities and threats, the level of solvency of the enterprise. Practical implications. Activity in the field of information technology is based on a number of features, which are based on the innovation policy of the enterprise in the tourism business: the dynamism of information technology; novelty of products or services provided or produced. This leads to the growth of the information services market, implementation and use of the most modern products in the field of information technology. All this provides a strategic advantage of the company in the market. Value/originality. It is proved that the modern work of the enterprise is impossible without the analysis of future forecasts and development programs that will contribute to the achievement of the expected and desired state of affairs. The development and implementation of forecasting methodology has become an objective requirement for enterprises in any field of activity.
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Gričar, Sergej. "IMPLEMENTATION OF VECTOR AUTO-REGRESSION MODELS IN TOURISM: STATE OF THE ART ANALYSIS AND FURTHER DEVELOPMENT." Tourism and hospitality management 28, no. 3 (December 2022): 707–9. http://dx.doi.org/10.20867/thm.28.3.16.
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Purpose The dissertation focuses on time series analysis and is based on several research strategies and methods. The methodology used in the research process was published in four papers as part of international scientific journals indexed in the Web of Science database. Since tourism is one of the most lagged industries in science there is need for new and innovative approaches in key tourist sector determinants modelling and forecasting. This doctoral thesis introduces an extension of time series methodology that focuses on investigating and testing the normal distribution of residuals, as a key adequacy prerequisite of econometric models. This issue has not systematically been considered in quantitative approaches in tourism. The motivation for research of the doctoral thesis are multidimensional: to filter previous research on time series in tourism and to theoretically and empirically improve and redesign time series methodology and methods for tourism. Both issues were successfully presented in one of the published papers. Finally, tourism forecasts should be based on reliable models as evident, from the most recent shocks, ex-ante tourism forecasting has to be considered crucial in evaluating model efficiency. The dissertation aimed to research and develop appropriate econometric models able to capture the specifics of multiple interactions in the tourism market. The research seeks to develop econometric models for the Republics of Slovenia and Croatia, two countries whose economic development is predicated on tourism. Four goals and four specific objectives have been specified during the research process: 1) To introduce an improved time series approach in cointegrated panels. The first specific objective (SO1) is to test at least ten econometric modelling structures that reduce cycle breaks. 2) To examine previous theoretical thinking regarding the cointegration of time series, cross-sectional data, and panels. The second specific objective (SO2) is to outline at least 250 previous empirical studies for the tourism industry. 3) To examine cointegration in tourism data for Slovenia and Croatia. The third objective (SO3) is to model at least three econometric time series equations and mathematical theorems/ lemmas for the tourism industry. 4) To improve and better understand unit root tests in tourism. The specific objective (SO4) is to approach the design of at least three stable and innovative models. Methodology The research relies upon econometric modelling in time series and panels as well as misspecification tests implementation. The study is primarily oriented to the hypotheses testing on a reliable modelling procedure. The research methodology is based on time series and the vector autoregression model (VAR) implementation. Moreover, the cointegrated VAR and the error correction model (ECM) are used. The Granger causality is used to identify trends to determine the direction of the hypothesised research problems. Overall, the study uses regression analysis and summary descriptive statistics. The sensitive analysis relies on panel regression. Summarizing, the added value of the doctoral thesis can be reflected in investigating the normal distribution of time series residuals to obtain accurate results for interpretation and prediction. Findings The most significant research results include time series and panel testing and modelling based on research hypotheses. The main hypothesis (an innovative approach to cointegration, based on empirical evidence for Slovenia and Croatia, which provides unbiased, accurate and validated results for tourism development) was confirmed. The first published paper investigates the possibility and accuracy of using time series data in forecasting tourism demands. The theoretical added value provides ex-ante research results regarding the consequences of the most recent pandemic. The empirical part of the paper discusses the direction of daily Slovenian and Croatian COVID-19 infections and tourist arrivals. Hypothesis 1 the tourism industry in Slovenia has developed rapidly and is expected to continue growing in a positive and sustainable direction without seasonal fluctuation, and 2, the tourism industry in Croatia has a long tradition and opportunity to grow at unprecedented rates hitherto. Volatility in the Croatian tourism industry is significant and has a high standard deviation; were confirmed. Additionally, the modelling strategy was introduced in one of the published papers. The results emphasized a significant influence on tourism demand and, depending on the modelling methodology, the existence of an impact on tourist arrivals of chosen determinants. Moreover, two published papers discussed the direction of economic impacts on tourist arrivals and vice versa. The decisive significance of productivity to real gross wages with a rise in tourist arrivals was confirmed. Furthermore, prices in tourism based on short-run effects and two cointegrated relations were modelled and forecasted. It can be concluded that tourism demand, approximated by tourist arrivals, is volatile on different determinants which were previously not researched or tested by reliable econometrics. Therefore, the set goals and specific study objectives were achieved.
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Sakhuja, Sumit, Vipul Jain, Sameer Kumar, Charu Chandra, and Sarit K. Ghildayal. "Genetic algorithm based fuzzy time series tourism demand forecast model." Industrial Management & Data Systems 116, no. 3 (April 11, 2016): 483–507. http://dx.doi.org/10.1108/imds-05-2015-0165.
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Purpose – Many studies have proposed variant fuzzy time series models for uncertain and vague data. The purpose of this paper is to adapt a fuzzy time series combined with genetic algorithm (GA) to forecast tourist arrivals in Taiwan. Design/methodology/approach – Different cases are studied to understand the effect of variation of fuzzy time series order, number of intervals and population size on the fitness function which decreases with increase in fuzzy time series order and number of fuzzy intervals, but do not have marginal effect due to change in population size. Findings – Results based on an example of forecasting Taiwan’s tourism demand was used to verify the efficacy of proposed model and confirmed its superiority to existing models providing solutions for different orders of fuzzy time series, number of intervals and population size with a smaller forecasting error as measured by root mean square error. Originality/value – This study provides a viable forecasting methodology, adapting a fuzzy time series combined with an evolutionary GA. The proposed hybridized framework of fuzzy time series and GA, where GA is used to calibrate fuzzy interval length, is flexible and replicable to many industrial situations.
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Kalna-Dubinyuk, Tetyana. "Application of information and consulting technologiesin the tourism business." Problems of Innovation and Investment Development, no. 20 (November 2019): 81–89. http://dx.doi.org/10.33813/2224-1213.20.2019.8.
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The subject of the research is information and consulting technologies withinteractive consulting in rural tourism. The purpose of this article is to reveal therole of the interactive consulting systems in rural tourism business developmentas wellcreation of tourist information and consulting centers. Methodology of carrying out the work-system-structural and comparative analyzes (to form an algorithm of interactive consulting system for rural tourism); monograph (whenstudying problems of functioning of rural tourism); modeling and forecasting (inthe process of building an interactive consulting system for rural tourism). Resultsof the work-creation of tourist is suggested information and consulting centerswith interactive rural tourism consulting systems based on the optimal combinationof computer hardware, computer networks, software, operating systems and databases that have the mission of accumulating, storing and transmitting large amountsof data in electronic form and provide a variety of tourist information (from advertising to routes and placement), consultations (from the selection of vacations,the creation of rural houses, categorization to using of alternative energy sources,etc.), organization of training on exercise of active tourism and tourist guidingothers. Conclusions-Establishment of a network of tourist information and counseling centers, providing the necessary recommendations for prompt customersatisfaction, will ensure sustainable rural development and the well-being of theunited territorial communities.
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Lytvyn, Nataliia, and Svitlana Panchenko. "Using intelligent technologies for tourism." Problems of Innovation and Investment Development, no. 24 (April 27, 2021): 96–105. http://dx.doi.org/10.33813/2224-1213.24.2021.9.
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The purpose of the article is to explore the essence and features of using intelligent technologies in tourism and to develop proposals for their implementation. The subject of research – intelligent technologies in tourism, the technology of forming the “profile” of the tourist. The research methodology consists in the application of methods of analysis, synthesis, comparison, generalization, forecasting, as well as in the use of systematic, activity approaches. The article presents the technology of forming the “profile” of the tourist. It is established that it is necessary to create a world of tourist models, the “profile” of the tourist, as it is a matter of formalizing such poorly structured concepts as “impressions”, “intentions”, etc., it is necessary to use artificial intelligence technologies, in particular neural networks. The scientific novelty is that this article proves the effectiveness of the use of intelligent technologies to create a model of the tourist, his “profile” using neural networks. Conclusions. Effective using of information from various sources in the field of tourism is an important and difficult task. Managers are often forced to make decisions based on partial, incomplete and inaccurate information. The article considers knowledge management in a rapidly changing environment for the task of promoting a tourism product. Neural network technology allows for the effective formation of the “tourist profile” and use all the information in available databases. Key words: tourism, intelligent technologies for tourism, neural networks, tourist profile, tourist product.
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Hotra, Victoria V. "ІNFORMATION SUPPORT FOR TOURISM AND HOTEL BUSINESS DEVELOPMENT." Bulletin of the Kyiv National University of Technologies and Design. Series: Economic sciences 155, no. 1 (September 2, 2021): 15–21. http://dx.doi.org/10.30857/2413-0117.2021.1.2.
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The article substantiates the need to enhance the information support for tourism and hotel business which is currently associated with a range of information and methodological issues, such as the assessment of tourist flows; tourism and hotel market satisfaction, congruence between customer needs and supply in the tourist services market; assessing load infrastructure as well as anthropogenic effects on the environment; study on the state of industry development and measuring of its contribution into the total gross domestic product. The paper presents a research methodology to explore tourism and hotel business settings, in particular the regional tourist services market, based on the market environment evaluation, identification of factors affecting tourism actors’ performance efficiency and estimation of their impact on final economic outcomes. The above methodology involves a comprehensive approach to the application of theoretical and applied principles of sectoral and territorial analysis and aims at building the regional tourism policy key drivers. It is argued that in the context of new risks and challenges, modern Ukraine should pursue a robust constructive recreational and tourism policy. Depending on the level at which the policy is defined and implemented, this study makes out government policy, regional policy, and the policy of individual tourism and hotel businesses. As an effective solution, the findings suggest modeling a government recreational policy based on strategic planning which translates into a comprehensive document that includes analytical information and business forecasting, as well as an action plan including a set of activities and projects to be implemented by market participants in the tourism and hotel sector.
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Nguyen, Le Quyen, Paula Odete Fernandes, and João Paulo Teixeira. "Analyzing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks." Forecasting 4, no. 1 (December 28, 2021): 36–50. http://dx.doi.org/10.3390/forecast4010003.
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Vietnam has experienced a tourism expansion over the last decade, proving itself as one of the top tourist destinations in Southeast Asia. The country received more than 18 million international tourists in 2019, compared to only 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and incomes for Vietnam’s tourism sector, making it the key driver to the socio-economic development of the country. Following the COVID-19 pandemic, only 3.8 million international tourists visited Vietnam in 2020, plummeting by 78.7% year-on-year. The latest outbreak in early summer 2021 made the sector continue to hit bottom. Although Vietnam’s tourism has suffered extreme losses, once the contagion is under control worldwide, the number of international tourists to Vietnam is expected to rise again to reach pre-pandemic levels in the next few years. First, the paper aims to provide a summary of Vietnam’s tourism characteristics with a special focus on international tourists. Next, the predictive capability of artificial neural network (ANN) methodology is examined with the datasets of international tourists to Vietnam from 2008 to 2020. Some ANN architectures are experimented with to predict the monthly number of international tourists to the country, including some lockdown periods due to the COVID-19 pandemic. The results show that, with the correct selection of ANN architectures and data from the previous 12 months, the best ANN models can be forecast for next month with a MAPE between 7.9% and 9.2%. As the method proves its forecasting accuracy, it would serve as a valuable tool for Vietnam’s policymakers and firm managers to make better investment and strategic decisions.
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Cherevko, Oleksandr, Natalia B�elousova, and Julia Golovchuk. "ESTIMATION OF THE FUNCTIONALITY OF USING THE TECHNIQUE FOR FORECASTING THE REGIONAL ECONOMIC DEVELOPMENT OF INCLUSIVE TOURISM." Actual Problems of Economics 1, no. 236 (February 28, 2021): 4–11. http://dx.doi.org/10.32752/1993-6788-2021-1-236-4-11.
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The issues of the prospects for the development of inclusive tourism in Ukraine, taking into account the economic opportunities of the regions of Ukraine, are considered. The international experience of introducing inclusive tourism as a product of the tourism industry is analyzed, estimated indicators of the economic priorities for the development of this direction are given. The problems and prospects for the implementation of this direction in the Ukrainian society are determined in the form of a methodology for forecasting the economic development of regions of Ukraine. Developers of forecasts of socio-economic development of regional programs are one of the state mechanisms of state regulation, through which regularity is achieved in the development of productive forces, the interests of industries and territories are coordinated. Significant influence on the formation of a system of guidelines for forecasting the socio-economic development of regions and the formation of regional economic policy, have provisions for assessing the status and prospects of socio-economic development of regions. In recent years (2014-2021), inclusive tourism has been actively developing in all developed countries of the world. In Ukraine, inclusive tourism is only gaining momentum as a tourist and social service, there is a transition from medical to social model, when all the expressions "all different but equal" is gaining new meaning in modern Ukrainian society. Taking into account the world experience, we can assume that inclusive tourism can be a powerful tool for rehabilitation, opportunities for tourist travel, communication with people who have the status of psychological barriers.
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Huang, Ya-Ling. "Forecasting the demand for health tourism in Asian countries using a GM(1,1)-alpha model." Tourism and hospitality management 18, no. 2 (2012): 171–81. http://dx.doi.org/10.20867/thm.18.2.1.
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The purpose – Accurately forecasting the demand for international health tourism is important to newly-emerging markets in the world. The aim of this study was presents a more suitable and accurate model for forecasting the demand for health tourism that should be more theoretically useful. Design – Applying GM(1,1) with adaptive levels of α (hereafter GM(1,1)-α model) to provide a concise prediction model that will improve the ability to forecast the demand for health tourism in Asian countries. Methodology – In order to verify the feasibility of the proposed approach, using available secondary and primary data covering the period from 2002 through 2009 obtained from the RNCOS “Opportunities in Asian Health tourism” report. Based on a unique and characteristics database for the health tourism industry, this study applies the adaptive α in a Grey forecasting model (GM(1,1)-α) to predict the demand for health tourism in Asian countries. Approach – Implementation of demand forecasting in health tourism is examined on the short-term and limited dataset, due to importance of a minimum the predicated error on underlying basis for the econometric model for health tourism markets. Findings – Key findings present that the optimal value of α in GM(1,1) can minimize the predicted error. Finally, in the case of the demand for health tourism in Asian countries, using GM(1,1)-α to predict error is clearly better than the use of the original GM(1,1) and time series models. The originality of this research – The originality comes from the analysis of the demand forecasting in health tourism of Asian countries, which provides an easy and accurate method to predict the demand for health medical tourism and ideas for further improvements in the sector of health tourism.
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Ghalehkhondabi, Iman, Ehsan Ardjmand, William A. Young, and Gary R. Weckman. "A review of demand forecasting models and methodological developments within tourism and passenger transportation industry." Journal of Tourism Futures 5, no. 1 (May 2, 2019): 75–93. http://dx.doi.org/10.1108/jtf-10-2018-0061.
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Purpose The purpose of this paper is to review the current literature in the field of tourism demand forecasting. Design/methodology/approach Published papers in the high quality journals are studied and categorized based their used forecasting method. Findings 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. Originality/value This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.
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Kummong, Ratree, and Siriporn Supratid. "Thailand tourism forecasting based on a hybrid of discrete wavelet decomposition and NARX neural network." Industrial Management & Data Systems 116, no. 6 (July 11, 2016): 1242–58. http://dx.doi.org/10.1108/imds-11-2015-0463.
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Purpose – Accurate forecast of tourist arrivals is crucial for Thailand since the tourism industry is a major economic factor of the country. However, a nonstationarity, normally consisted in nonlinear tourism time series can seriously ruin the forecasting computation. The purpose of this paper is to propose a hybrid forecasting method, namely discrete wavelet decomposition (DWD)-NARX, which combines DWD and the nonlinear autoregressive neural network with exogenous input (NARX) to cope with such nonstationarity, as a consequence, improve the effectiveness of the demand-side management activities. Design/methodology/approach – According to DWD-NARX, wavelet decomposition is executed for efficiently extracting the hidden significant, temporal features contained in the nonstationary time series. Then, each extracted feature set at a particular resolution level along with a relative price as an exogenous input factor are fed into NARX for further forecasting. Finally, the forecasting results are reconstructed. Forecasting performance measures rely on mean absolute percentage error, mean absolute error as well as mean square error. Model overfitting avoidance is also considered. Findings – The results indicate the superiority of the DWD-NARX over other efficient related neural forecasters in the cases of high forecasting performance rate as well as competently coping with model overfitting. Research limitations/implications – The scope of this study is confined to Thailand tourist arrivals forecast based on short-term projection. To resolve such limitations, future research should aim to apply the generalization capability of DWD-NARX on other domains of managerial time series forecast under long-term projection environment. However, the exogenous input factor is to be empirically revised on domain-by-domain basis. Originality/value – Few works have been implemented either to handle the nonstationarity, consisted in nonlinear, unpredictable time series, or to achieve great success on finding an appropriate and effective exogenous forecasting input. This study applies DWD to attain efficient feature extraction; then, utilizes the competent forecaster, NARX. This would comprehensively and specifically deal with the nonstationarity difficulties at once. In addition, this study finds the effectiveness of simply using a relative price, generated based on six top-ranked original tourist countries as an exogenous forecasting input.
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Volkova, Irina, and Ilya Skryak. "INVESTIGATION OF THE SPECIFICS OF THE ENTRY TOURISM IN UKRAINE." GEOGRAPHY AND TOURISM, no. 44 (2018): 34–43. http://dx.doi.org/10.17721/2308-135x.2019.44.34-43.
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The purpose of the work is to study the specifics of entry tourism in Ukraine. The research methodology is based on the information material presented at government institutions (State Statistics Service of Ukraine, Kyiv Oblast State Administration, etc.). In the process of research, statistical, analytical, comparative methods (tabular, graphical) were used. As a result of the conducted studies, the current state and dynamics of international arrivals in Ukraine was considered. Diversification of foreign citizens for the purpose of entry to Ukraine is shown. The indicators of the largest importing countries of tourist flows to Ukraine are analyzed. Considered the dynamics of incomes from international arrivals. The scientific novelty is the study of the current state of inbound tourism in Ukraine. The practical significance lies in the forecasting and planning of tourism activities, the use of research materials in the educational process in the training of tourism professionals.
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Bigović, Miloš. "Demand forecasting within Montenegrin tourism using Box-Jenkins methodology for seasonal ARIMA models." Tourism and hospitality management 18, no. 1 (June 2012): 1–18. http://dx.doi.org/10.20867/thm.18.1.1.
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The purpose of this paper is to construct adequate seasonal ARIMA models, using Box-Jenkins methodology, and to implement them in order to forecast short run flows of tourist arrivals and tourist overnight stays in Montenegro. Time scope covers ten years, from 2001/01 to 2010/12, while twelve months of 2011 are out-of-sample forecasts. Close inspection of related time series was applied which revealed no extreme and unusual specificities in the data. Therefore, only economic impacts have been affected the time series. This was important because econometric intervention analysis was excluded from models designing and building. As a result, our approach was based on time series modelling without need to take care of any structural breaks. Modified Box-Pierce and Jarque-Bera test statistics confirmed good quality of the models. Further, the results show excellent forecasting performances of specified models. According to forecasting output, Montenegro can expect upgrowth in terms of tourist arrivals as well as in terms of tourist overnight stays. The model has shown around 7,25% rise in arrivals, which is about 91 thousands tourists more in 2011 compared with the previous year. On the other hand, the calculated rise of overnight stays is around 8,42%, or about 670 thousands more than the year before.
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Opanaschuk, Yuriy, Tеtiana Kolisnychenko, and Antonina Verhun. "WORLD ACHIEVEMENTS AND INNOVATIVE TECHNOLOGIES IN MODERN TOURISM AND HOTEL RESTAURANT BUSINESS." Problems of Innovation and Investment Development, no. 27 (December 21, 2021): 57–66. http://dx.doi.org/10.33813/2224-1213.27.2021.6.
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The purpose of the article – find out and summarize the practical experience of using innovative technologies in the hotel and restaurant and tourism business. The research methodology consists in the application of methods of analysis, synthesis, comparison, generalization, forecasting, as well as in the use of systemic and activity-based approaches. The scientific novelty lies in the fact that this article presents modern product innovations, technological innovations in the development of transport infrastructure, accommodation facilities for the premium segment and tourism innovations in different regions of the world. Conclusions. As a result of the study, it was found that innovations in the tourist infrastructure contribute to a change in the structure of demand and the volume of tourist flow, to attract funds to the country, create opportunities to increase the attractiveness of a tourist destination. Keywords: innovations, innovative activity, product innovations, technological innovations, transport infrastructure, hotel infrastructure.
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Chatkaewnapanon, Yuthasak, and Joan Marie Kelly. "Community arts as an inclusive methodology for sustainable tourism development." Journal of Place Management and Development 12, no. 3 (August 5, 2019): 365–90. http://dx.doi.org/10.1108/jpmd-09-2017-0094.
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Purpose Community arts practice gives voice to a younger generation, who must be studied as part of the development process from commencement, to accomplish building sustainable destination development in the direction of future prosperity for the rural community. Design/methodology/approach This paper challenges a relatively weak critical practice of the community-based tourism (CBT) by introducing community arts methodologies as a research approach in the context of tourism, the opportunity is created to give voice to a younger generation that must also be included in the development aims of the CBT to achieve sustainable community tourism development. Findings The CBT aims to support access to quality participation in the development process. However, investment in education and building tourism entrepreneurs is not inclusive of the future generations beyond the original generation. Consideration of the desires and imaginations of the future generations must be part of the CBT project for tourism development sustainability. Building awareness of the fragility and value of tourist attractions and resources, in a younger generation that never experienced the original attractions of the traditional village, is critical to achieving the objectives of the CBT. Research limitations/implications The paper is not yet attempting to examine the empirical data of this research. Rather, it challenges current CBT research processes as having a narrow reach into a community. Practical implications Tourism developers and local communities should include an understanding of what directions and what opportunities the next and future generations will have to continue sustainable development. Including children’s imaginations into a community’s tourism development plans will benefit awareness of the present context and assist locals in forecasting the next stage of village development. The present tourism planners would then have a holistic vision for a design strategy sustaining rural livelihoods that acknowledge the limits of nature-based resources and cultural resources. Social implications Community arts research offers the possibility of inclusive participation of community members. Arts methodology attempts to articulate ideas in visual form, for the aim of discussion, reflection and realization of the desires and concerns of the community in terms of lifestyle, environment and cultural heritage, in preparation for the future generation taking control of tourism development. The process aims to impact future decisions effecting the course of tourism development in rural Thailand. Originality/value The paper discusses the potential contribution of community arts practice as a complementary tool by taking into account different aspects of sustainable tourism into CBT concept. The paper evaluates what has been missing in advancing our understanding of sustainable rural tourism development in Thailand. It fills the gaps with a methodological approach that gives voice to the local community. The purpose of this paper is to rethinking the ideology and approach of CBT to be inclusive of all demographics of society for the goal of achieving sustainable tourism and sustainable community development in Thailand context.
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Кривошеева, Татьяна, Tatiana Krivosheeva, Татьяна Харитонова, and Tatyana Kharitonova. "Identifying the Moscow Region Tourism Industry Demand for Personnel Training." Universities for Tourism and Service Association Bulletin 8, no. 2 (May 27, 2014): 55–61. http://dx.doi.org/10.12737/3876.
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This article deals with the issues of identification of the demand for training the personnel for the Moscow
region tourism industry. The range of issues raised in the article covers (1) the causes of the trained personnel
shortage in the region; (2) the employers’ general approaches to candidates’ applications processing; (3)
the current and expected enrollment in Tourism- and Hospitality-related training programmes; and (4) the
creation of forecast scenarios of Moscow region tourism industry development, which vividly demonstrate a growing demand for personnel. The article focuses on the evaluation methodology of the demand for the
tourism industry personnel and its approbation in a number of Moscow-region-based municipal entities.
The evaluation methodology is based on the trend analysis of the tourism industry development indices,
strategic and standard-and-goal programming, the multiplier theory, extrapolative and scenario forecasting.
The strategic guidelines for Moscow region tourism industry development correspond to the performance
targets of the development of domestic and inbound tourism in the Moscow region in effect until 2018: a
twofold increase in the number of tourists using collective accommodation facilities, a 30% increase in the
tourist companies’ customership, up to a 4-% increase in the number of foreign tourists using collective
accommodation facilities, etc. The application of the methodology developed by the authors of the article
allows of the conclusion that, for the innovative development scenario, the number of jobs in the Moscow
region tourism industry should have reached 6,000 by 2018. The methodology can be applied to assess the
current and expected demand for personnel as observed in a variety of business domains in different regions
of the Russian Federation.
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Litovka and Demenina. "The process of marketing research in the tourism sector." Problems of Innovation and Investment Development, no. 23 (April 10, 2020): 128–36. http://dx.doi.org/10.33813/2224-1213.23.2020.13.
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The subject of the research is a set of theoretical and practical aspects of the use of basic marketing research in planning the work of a tourist organization. The purpose of the article is to clarify and improve the basic theoretical approaches in the use of marketing research, to offer them systematically at each stage of developing the marketing strategy of a tourism enterprise. The research methodology consists in the application of methods of analysis, synthesis, comparison, generalization, forecasting, as well as in the use of systemic, activity, historical approaches. The results of the work – presented proposals for solving problems in the field of tourism, in particular in conducting marketing research at travel agencies. The problematic issues in the field of tourism from the point of view of the analysis of the market of specific services arecovered. Conclusions. Tourism organizations need market monitoring, constant andconsistent marketing research due to high competitiveness and time challenges.
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Valiyeva, Gunel. "METHODOLOGY OF CONDUCTING RECREATIONAL ZONING AND OPPORTUNITIES FOR ITS APPLICATION IN AZERBAIJAN." GEOGRAPHY AND TOURISM, no. 58 (2020): 19–24. http://dx.doi.org/10.17721/2308-135x.2020.59.19-24.
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Aim: The main aim of the article to analyze the principles and methodology of recreational zoning, the related theories, as well as the factors, which must be successively considered in this process. The methodological basis of the article is the theoretical provisions set forth in the works of Azerbaijani and foreign scholars in defining theoretical and methodological peculiarities of the state programs, international experience in the organization of Recreation Zones. Results: The carried work also demonstrates the feasibility of the conduction of recreational zoning in Azerbaijan, with distinguishing sub-regions within the boundaries of touristic-recreational region of Gusar. The tourism- recreation zone of Gusar specifically predicts the main directions of development of the microdistrict by type of tourism. In accordance to the selection of areas for the Gusar tourism-recreation zone are taken into account the potential for the development of various types of tourism, as well as the suitability for the joint organization of many services. From this point of view, in the formation of recreational tourism zones graphic of dependence is considered the basis for the development of areas. The article shows that the advantages of applying this dependence graphic is suitable for the Gusar recreation and tourism zone. At the same time, the separation of Chilagir-Urva-Khuray, Anig-Laza, Hazra-Sudur micro-recreation regions in the Gusar recreation-tourism zone is due to the existence of similar natural-geographical conditions and conditions for the organization of different types of tourism. The structure of employment is dominated by agriculture and, in part, by tourism. Potato-growing and livestock are the main agricultural sectors. Scientific novelty: The practical significance of the article is the selection of areas suitable for tourism development in the Gusar Tourism and Recreation Zone, and the forecasting of tourism development trends, taking into account the ecological balance.
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Dragan, Dejan, Abolfazl Keshavarzsaleh, Tomaž Kramberger, Borut Jereb, and Maja Rosi. "Forecasting US Tourists’ inflow to Slovenia by modified Holt-Winters Damped model: A case in the Tourism industry logistics and supply chains." Logistics & Sustainable Transport 10, no. 1 (June 1, 2019): 11–30. http://dx.doi.org/10.2478/jlst-2019-0002.
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Abstract Forecasting is important in many branches of logistics, including the logistics related to Tourism supply chains. With an increasing inflow of American tourists, planning and forecasting the US tourists’ inflow to Slovenia have gained far more importance attention amongst scholars and practitioners. This study, therefore, was conducted to forecast the American tourists’ inflow to Slovenia using one of the predictive models based on the exponential smoothing approach, namely Holt-Winters damped additive (HWDA) exponential smoothing method. The model was modified by several improvements, while the obtained results were generalized to other supply chain components. The results show that the forecasting system can predict well the observed inflow, while the methodology used to derive the model might have enriched the plethora of existing practical forecasting approaches in the tourism domain. Benchmarking demonstrates that the proposed model outperforms a competitive ARIMA model and official forecasts. The practical implications are also discussed in this paper.
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Pavlić, Ivana. "Cruise tourism demand forecasting - the case of Dubrovnik." Tourism and hospitality management 19, no. 1 (2013): 125–42. http://dx.doi.org/10.20867/thm.19.1.9.
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The purpose – Cruising is nowadays a mass phenomenon since an increasing number of passengers worldwide have been taking part in this form of tourism. Therefore the purpose of this paper is to forecast cruise tourism demand at the level of micro destination. Design/Methodology/Approach – Dubrovnik has become one of the most important and most frequently visited destinations for cruise tourism in the Mediterranean. The rapidly increasing number of passengers on cruise voyages has put Dubrovnik among the leading cruise destinations in the Mediterranean. Dubrovnik is now facing the problem of concentration of a large number of ships and passengers in a short period of time. Consequently, this paper aims at forecasting the number of passengers from cruise ships within the next five year period in order to highlight eventual consequences and the necessity for implementation of a different management policy in accepting cruise ships and passengers at the destination to satisfy the requirements of both the passengers from cruisers and stationary tourists on one side and on the other side to improve the living standards of the local community. For this purpose the seasonal ARIMA model has been used which incorporates both seasonal autoregressive and moving average factor in the modelling process. Findings – With application of the above mentioned model and having in mind that forecasting was carried out under assumption that there will be no significant changes in the existing conditions it is to be concluded the cruise ship passenger arrivals in Dubrovnik area in 2015 will reach 1.294.316 making an increase of 31% in comparison with the year 2011 at an average growth rate of 7.06%. Originality of the research – Research was carried out to indicate the necessity for implementation of the new model of management for passengers from cruise ships by tourism destination management.
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Jassim, R. Shakir Al, Karan Jetly, Ahmad Abushakra, and Sh Al Mansori. "A Review of the Methods and Techniques Used in Tourism Demand Forecasting." EAI Endorsed Transactions on Creative Technologies 9, no. 4 (January 13, 2023): e1. http://dx.doi.org/10.4108/eetct.v9i31.2986.
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The purpose of this paper is to discuss the methodology and results of researchers who conducted a study concerning the forecasting of tourism demand. In more detail, this study aims to examine and assess various studies about search engines, web traffic data, and social media data, specifically. Using an extensive database of indexed articles, we conducted the review with the goal of providing a solid understanding of the literature. The findings of our study revealed that few researchers integrate different data sources when forecasting tourism demand. Therefore, the authors of this paper decided to conduct a systematic review to provide researchers with a comprehensive overview of the importance of such data. This paper may inspire Omani researchers to undertake similar research based on its findings, which is currently lacking. Thus, this paper will improve understanding of how data sources affect forecasting accuracy and how modern technologies can support economic growth.
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Svitlana, Panchenko. "Religious tourism management: prospects for development in Ukraine." Problems of Innovation and Investment Development, no. 22 (April 10, 2020): 109–16. http://dx.doi.org/10.33813/2224-1213.22.2020.14.
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The subject of the study is the management of religious tourism. the purposeof the study are ways to improve the sphere of religious tourism with the help ofthe main management functions. the research methodology consists in the application of methods of analysis, synthesis, comparison, generalization, forecasting,as well as in the use of systemic, activity, historical and cultural approaches.theresults of the work – proposals are presented for solving the problems of religioustourism, taking into account the specifics of this sphere. The problematic issuesin the field of religious tourism from the point of main management functions arehighlighted. conclusions – the study found that religious tourism has great potential in terms of management and marketing research in the field of tourism.
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Croce, Valeria. "Can tourism confidence index improve tourism demand forecasts?" Journal of Tourism Futures 2, no. 1 (March 14, 2016): 6–21. http://dx.doi.org/10.1108/jtf-12-2014-0026.
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Purpose The link between confidence and economic decisions has been widely covered in the economic literature, yet it is still an unexplored field in tourism. The purpose of this paper is to address this gap, and investigate benefits in forecast accuracy that can be achieved by combining the UNWTO Tourism Confidence Index (TCI) with statistical forecasts. Design/methodology/approach Research is conducted in a real-life setting, using UNWTO unique data sets of tourism indicators. UNWTO TCI is pooled with statistical forecasts using three distinct approaches. Forecasts efficiency is assessed in terms of accuracy gains and capability to predict turning points in alternative scenarios, including one of the hardest crises the tourism sector ever experienced. Findings Results suggest that the TCI provides meaningful indications about the sign of future growth in international tourist arrivals, and point to an improvement of forecast accuracy, when the index is used in combination with statistical forecasts. Still, accuracy gains vary greatly across regions and can hardly be generalised. Findings provide meaningful directions to tourism practitioners on the use opportunity cost to produce short-term forecasts using both approaches. Practical implications Empirical evidence suggests that a confidence index should not be collected as input to improve their forecasts. It remains a valuable instrument to supplement official statistics, over which it has the advantage of being more frequently compiled and more rapidly accessible. It is also of particular importance to predict changes in the business climate and capture turning points in a timely fashion, which makes it an extremely valuable input for operational and strategic decisions. Originality/value The use of sentiment indexes as input to forecasting is an unexplored field in the tourism literature.
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Kachniewska, Magdalena. "The Use of Big Data in Tourism Sales Forecasting." International Journal of Contemporary Management 19, no. 2 (2020): 7–35. http://dx.doi.org/10.4467/24498939ijcm.20.004.12669.
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Background. The explosion of big data (BD), automation, and machine learning have allowed contemporary businesses to better understand and predict human behavior. In scientific research big data have been widely used to study consumer journey and opinions. One of the tools enabling forecasting of sales volume is the Bass diffusion model, which universal nature has been proven in many applications in forecasting the sale of products belonging to various market segments. This article considers the use of BD as exogenous variables in the Bass model to predict the sales of tourist packages. Research aims. The purpose of the research is to assess the impact of using big data on improving the accuracy of forecasts for the sale of tourist packages. The Generalized Bass Model (GBM) has been thus expanded to include big data, which means that exogenous variables include: (1) marketer-generated content (MGC) and (2) user-generated content (UGC), including volume of web search and blog posts. Methodology. This article analyzes online news, blog posts and web search traffic volume related to tourist packages, and then integrates the information into the Bass model, treating it as part of the exogenous variables representing the marketing efforts of tour operators. It has been assumed that the volume of tour operators’ web news is a proxy for content generated by marketers (MGC), while the volume of blog posts and web search traffic constitute user-generated content (UGC). Key findings. The empirical analysis found that by incorporating big data into the Bass model provides more accurate prediction of tourist packages’ sales volume. In addition, UGC (as an exogenous variable) is better at predicting sales volume than MGC. UGC is a fairly good tool explaining the level of interest and involvement of potential tourists. However, it has been shown that forecasting efficiency is different for blog posts and web search traffic volumes.
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Panchenko, Svitlana, and Svitlana Litovka-Demenina. "THE IMPLICATIONS OF MARKETING RESEARCH FOR TOURISM DURING THE COVID-19 PANDEMIC." Problems of Innovation and Investment Development, no. 26 (September 29, 2021): 82–89. http://dx.doi.org/10.33813/2224-1213.26.2021.8.
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The purpose of the article is, taking into account the importance of marketing research in the field of tourism, to propose an adequate marketing strategy for a tourism enterprise in the context of the Covid-19 pandemic. Methodology – the application of methods of analysis, synthesis, comparison, generalization, forecasting, as well as the use of systemic, activity-based, histori- cal approaches. The scientific novelty is in the proposals for solving problems in the field of tourism, in particular, in conducting marketing research at travel companies in the conditions of Covid-19. Conclusions. As a result of the study, it was found that tourism organizations require market monitoring in the context of Covid-19, constant and consistent marketing research in connection with the reformatting of the market with new challenges of the time. Keywords: marketing research, pandemic, Covid-19, tourism product, tourism
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Lajante, Mathieu, Riadh Ladhari, and Elodie Massa. "Role of affective forecasting in customers’ hotel service experiences." International Journal of Contemporary Hospitality Management 34, no. 3 (December 20, 2021): 1062–83. http://dx.doi.org/10.1108/ijchm-04-2021-0530.
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Purpose Research on the role of affective forecasting in hotel service experiences is in its infancy, and several crucial questions remain unanswered. This study aims to posit that affective forecasting is a significant antecedent of customers’ affective reactions during a hotel stay. The authors investigate how customers’ service quality expectations influence their affective forecasting and how customers’ affective forecasting before an upcoming hotel service experience influences their affective reactions during the hotel service experience. Design/methodology/approach The authors collected data through online questionnaires distributed among 634 US adults who had stayed at a hotel within the past month. Findings The results show that: service quality expectations influence affective forecasting; affective forecasting influences affective reactions; service quality expectations influence perceived service quality, thereby influencing affective reactions and affective reactions and service quality perception influence electronic Word-Of-Mouth intentions. Practical implications The study suggests that hotel managers should identify what hotel performance attributes customers value most and depict how these attributes elicit positive affective reactions in advertising to influence customers’ purchase decisions. Originality/value This is one of the few studies to investigate the antecedents and consequences of affective forecasting in hotel service experiences.
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Andrei, Tudorel, Andreea Mirică, Ionela-Roxana Glăvan, Georgiana Andreea Ferariu, and Ioan Mincu Radulescu-George. "Seasonal adjustment of tourism data for Romania using JDemetra+." Proceedings of the International Conference on Applied Statistics 1, no. 1 (October 1, 2019): 8–16. http://dx.doi.org/10.2478/icas-2019-0002.
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Abstract Tourism statistic data can is an important source for measuring touristic patterns. As this area became more and more dynamic with the globalisation process, business owners, business analysts, policy makers as well as researchers are highly interested in having accurate, reliable and diverse data on tourism in order to perform analysis. Seasonal adjustment presents a real challenge for all researchers that operate with data sources from tourism sector. Usage of time series presents both opportunities and may contribute to improvement of forecasting touristic specifics relaying on demand and supply side of seasonality phenomenon. However, seasonally adjusted data is viewed as major challenge for businesses operating in the touristic sector. The present research focuses on a methodology that includes monthly tourist data arrivals in Romania. The seasonal adjustment process is performed with JDemetra+, both considering and excluding calendar effect. JDemetra+ is the software officially recommended by Eurostat for seasonal adjustment, being tested extensively by many experts in the field, from various organisations. The seasonal adjustment process pointed out promising and qualitative results, as no Easter and trading days effect were present, suggesting effect of calendar omission from the process. Our obtained results showed up significantly better results for the 5 years series span. The similarities for TRAMO-SEATS and X13 obtained results indicate that in order to minimise sensitivity and choose correctly between the two packages, further revisions may be considered. This paper provides an excellent starting point for further research aimed at improving data on tourism. The methodology tested in this research can be further improved and applied on other data regarding tourism.
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Liu, Han, Ying Liu, Gang Li, and Long Wen. "Tourism demand nowcasting using a LASSO-MIDAS model." International Journal of Contemporary Hospitality Management 33, no. 6 (July 22, 2021): 1922–49. http://dx.doi.org/10.1108/ijchm-06-2020-0589.
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Purpose This study aims to examine whether and when real-time updated online search engine data such as the daily Baidu Index can be useful for improving the accuracy of tourism demand nowcasting once monthly official statistical data, including historical visitor arrival data and macroeconomic variables, become available. Design/methodology/approach This study is the first attempt to use the LASSO-MIDAS model proposed by Marsilli (2014) to field of the tourism demand forecasting to deal with the inconsistency in the frequency of data and the curse problem caused by the high dimensionality of search engine data. Findings The empirical results in the context of visitor arrivals in Hong Kong show that the application of a combination of daily Baidu Index data and monthly official statistical data produces more accurate nowcasting results when MIDAS-type models are used. The effectiveness of the LASSO-MIDAS model for tourism demand nowcasting indicates that such penalty-based MIDAS model is a useful option when using high-dimensional mixed-frequency data. Originality/value This study represents the first attempt to progressively compare whether there are any differences between using daily search engine data, monthly official statistical data and a combination of the aforementioned two types of data with different frequencies to nowcast tourism demand. This study also contributes to the tourism forecasting literature by presenting the first attempt to evaluate the applicability and effectiveness of the LASSO-MIDAS model in tourism demand nowcasting.
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Claveria, Oscar, Enric Monte, and Salvador Torra. "A new forecasting approach for the hospitality industry." International Journal of Contemporary Hospitality Management 27, no. 7 (October 12, 2015): 1520–38. http://dx.doi.org/10.1108/ijchm-06-2014-0286.
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Purpose – This study aims to apply a new forecasting approach to improve predictions in the hospitality industry. To do so, the authors developed a multivariate setting that allows the incorporation of the cross-correlations in the evolution of tourist arrivals from visitor markets to a specific destination in neural network models. Design/methodology/approach – This multiple-input-multiple-output approach allows the generation of predictions for all visitor markets simultaneously. Official data of tourist arrivals to Catalonia (Spain) from 2001 to 2012 were used to generate forecasts for one, three and six months ahead with three different networks. Findings – The study revealed that multivariate architectures that take into account the connections between different markets may improve the predictive performance of neural networks. Additionally, the authors developed a new forecasting accuracy measure and found that radial basis function networks outperform the rest of the models. Research limitations/implications – This research contributes to the hospitality literature by developing an innovative framework to improve the forecasting performance of artificial intelligence techniques and by providing a new forecasting accuracy measure. Practical implications – The proposed forecasting approach may prove very useful for planning purposes, helping managers to anticipate the evolution of variables related to the daily activity of the industry. Originality/value – A multivariate neural network framework has been developed to improve forecasting accuracy, providing professionals with an innovative and practical forecasting approach.
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Dinis, Gorete, Zélia Breda, Carlos Costa, and Osvaldo Pacheco. "Google Trends in tourism and hospitality research: a systematic literature review." Journal of Hospitality and Tourism Technology 10, no. 4 (November 27, 2019): 747–63. http://dx.doi.org/10.1108/jhtt-08-2018-0086.
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Purpose This paper aims to conduct a review of the literature published, between 2006 and 2018, that used search engine data on tourism and hospitality research, namely, Google Insights for Search and Google Trends. More specifically, it intends to identify the purpose and context of the data use, ascertaining the main findings and reviewing the methodological approaches. Design/methodology/approach A systematic literature review of Scopus indexed research has been carried out. Given the novelty of search engine data use in tourism and hospitality research and the relatively low number of search results in Scopus, other databases were used to broaden the scope of analysis, namely, EBSCO and Google Scholar. The papers selected were subjected to content and statistical analyses. Findings Google Trends data use in tourism and hospitality research has increased significantly from 2012 to 2017, mainly for tourism forecasting/nowcasting; knowing the interest of users’ searches for tourist attractions or destinations; showing the relationship between the official tourism statistics and the search volume index of Google Trends; and estimating the effect of one event on tourism demand. The categories and search terms used vary with the purpose of the study; however, they mostly focus on the travel category and use the country as the search term. Originality/value Google Trends has been increasingly used in research publications in tourism and hospitality, but the range of its applications and methods used has not yet been reviewed. Therefore, a systematic review of the existing literature increases awareness of its potential uses in tourism and hospitality research and facilitates a better understanding of its strengths and weaknesses as a research tool.
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Butko, T. V., V. M. Prokhorov, L. O. Parkhomenko, and A. O. Prokopov. "Improvement of Technology of Passenger Intermodal Transportation with Involvement of Railway Transport in the Conditions of Tourism Development." Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, no. 1(91) (February 15, 2021): 37–50. http://dx.doi.org/10.15802/stp2021/228106.
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Purpose. The main purpose of the authors is to define and methodically substantiate the ways to increase the efficiency of intermodal passenger transportations with the involvement of high-speed trains as an auxiliary mode of transport in terms of sea and river tourism. Methodology. In the process of research the following was used: the method of factor analysis – to determine the factors influencing the attractiveness of tourist travel using high-speed trains as ancillary transport; method of skipping stops – to increase the efficiency of using high-speed trains as an auxiliary mode of transport when making tourist trips; methods of construction and training of generative-adversarial networks for the formation of model of passenger flows forecasting, on the basis of historical data of multivariate time series; method of genetic algorithms – to optimize the model of mixed-integer programming, which allows obtaining the optimal scheme of high-speed trains on the line. Findings. In order to preserve the attractiveness of tourist travels and increase the route speed of trains, it is proposed to improve the technology of planning their work based on the method of skipping stops. A mathematical model of mixed-integer programming has been formed, which simultaneously provides the attractiveness of tourist travel and profitability for railway operators. To prepare the initial data, a method for forecasting passenger flows based on multivariate time series has been developed. The optimization procedure of the generated model was implemented in the form of software in the Matlab language. Originality. The method of skipping stops, which was first used to improve the technology of intermodal passenger traffic, was further developed in the work. An original method for predicting passenger flows based on multivariate time series using a modern model of generative-competitive neural networks is proposed. Practical value. The obtained results are aimed at improving the methodological approaches to the formation of modern technologies of intermodal passenger transportation and the realization of the potential of high-speed rail transportations as a basis for the comprehensive development of tourism.
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BABURIN, Vyacheslav, and Svetlana BADINA. "FORECASTING OF DAMAGES FROM NATURAL HAZARDS FOR THE “NORTHERN CAUCASUS RESORTS” TOURIST CLUSTER." Sustainable Development of Mountain Territories 12, no. 3 (September 30, 2020): 349–56. http://dx.doi.org/10.21177/1998-4502-2020-12-3-349-356.
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The article proposes a methodological approach to potential damage from natural hazards forecasting in case of large-scale investment projects realization in ski tourism planning, as well as to assessing changes in the vulnerability of the territory in which these projects will be implemented. The method was verified on the data of the “Northern Caucasus Resorts” tourist cluster. The study purpose is the creation and verification of a methodology for socio-economic damage predicting in limit values and vulnerability changing in the regions of the “North Caucasus Resorts” tourist cluster objects localization for the long term. Research methods – statistical (a structural approach based on the identification of common structural patterns of several sets). The lack of statistical information on significant parameters for forecasting determine necessitates of using the various logically non-contradictory revaluations based on the identified structural similarities for the calculation of their values within the planning horizon. The study results and main conclusions – in case of the “North Caucasus Resorts” tourist cluster creation the number of people potentially located in avalanche and mudflow danger areas will significantly increase in all of its facilities localization municipalities, which indicate an increase in the individual risk of death level for this territory. The present population in the ski season in some of the most remote and underdeveloped areas can increase up to 30 times. The increment in the value of the fixed assets for the municipalities under consideration will be from two to 90 times, potential damages in limit values will reach tens of billions rubles.
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Chen, Yen-Cheng, Pei-Ling Tsui, Hsin-I. Chen, Hui-Ling Tseng, and Ching-Sung Lee. "A dining table without food: the floral experience at ethnic fine dining restaurants." British Food Journal 122, no. 6 (September 13, 2019): 1819–32. http://dx.doi.org/10.1108/bfj-08-2018-0541.
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Purpose A high-end ethnic restaurant is a tourism experience that can increase the attractiveness and brand recognition of a tourism destination. The restaurant environment is a key element that affects consumer visits. The purpose of this paper is to adopt Schmitt’s experience module to analyse tourist preferences and experiences with respect to floral styles in ethnic fine dining restaurants. The results of this study are intended to serve as a reference for operators of fine dining establishments in designing flower arrangements. Design/methodology/approach This study adopts a quantitative research method. A sample was developed using tablet computers to simulate flower arrangements in restaurants. The research tools included a floral style preference scale and a tourist floral experience scale. Findings Based on the results, the test subjects preferred European floral design styles in restaurants. Restaurant environments with floral arrangements were best at relaxing the test subjects. A restaurant’s floral style was positively correlated with various aspects of the tourist experience. Gender, age, Chinese flower styles, Japanese flower styles, European flower styles and other variables enabled forecasting the degree of the tourist experience. Originality/value When a consumer exhibits higher preference for a restaurant’s floral style, the level of the tourist experience increases. This study investigates the aesthetic experience of restaurants and restaurant atmosphere as a marketing tool. Sensory stimulation within the restaurant atmosphere can be based on the five senses such that tourists may, through the design of the restaurant environment, have specific emotional reactions that improve their tourist experience and reinforce the restaurant’s brand image.
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Litovka-Demenina, Svetlana, and Panchenko Svitlana. "The impact of COVID-19 on the development of marketing research in tourism during a pandemic and the global crisis." Problems of Innovation and Investment Development, no. 25 (June 30, 2021): 74–83. http://dx.doi.org/10.33813/2224-1213.25.2021.8.
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The purpose of the article – to clarify and improve the basic practical ap- proaches in the use of marketing research, to offer them systematically The research methodology consists in the application of methods of analysis, synthesis, comparison, generalization, forecasting, as well as in the use of sys- temic, activity, historical approaches. The scientific novelty is that this article presents proposals for solving problems in the field of tourism, in particular in conducting marketing research on travel agencies in the COVID-19, the transition to new marketing moves, taking into ac- count the new challenges of the time. Conclusions. The study found that tourism organizations need to monitor the market under COVID-19, constant and consistent marketing research in connection with the reformatting of the market and the tough challenges of the time. Keywords: marketing, marketing research, marketing tools, pandemic, COVID-19, strategy, tourism product.
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Thongchaichirapha, Natawan. "The Use of a Delphi Survey to Create a Forecasting Model Regarding the Impact of Fluctuations of the Baht on Tourism in Thailand." International Journal of System Modeling and Simulation 2, no. 3 (September 30, 2017): 19. http://dx.doi.org/10.24178/ijsms.2017.2.3.19.
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Despite the vast research by inbound and outbound tourists does impact of Thai currency, little is known about the perspective of Thai baht fluctuation, officially that relate to Banks, tourists company and Thailand economics. The overall image that emerges from literature is directly result effects. This study recover the data of semi-structure questionnaire for create a forecasting model through Delphi survey. This survey method will useful to justify the main factors that refer to the objective of this research. To create forecasting model for tourists was based on Thai baht fluctuation demanded on two examine impacts from inbound and outbound tourists. In additional methodology, data collectives is another method that ensure to support research more reliable enough on forecasting model. In seven panelists of participant contributed knowledge and expertise in the subject of government, tourism and financial, For Delphi survey methods were conducted in three round of Delphi survey panel, in each round have different questions depends on previous round result. Which mean, on first round is important to start to vary connected the final round of questions adjust. Even though, the result might have lack of consensus result because the participants had a different ideas to investigate answered questions but look forward on percentage result significantly that for economics change were main factor that impact also contribute to baht fluctuation on tourism in Thailand.
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Qiu, Richard T. R., Anyu Liu, Jason L. Stienmetz, and Yang Yu. "Timing matters: crisis severity and occupancy rate forecasts in social unrest periods." International Journal of Contemporary Hospitality Management 33, no. 6 (June 8, 2021): 2044–64. http://dx.doi.org/10.1108/ijchm-06-2020-0629.
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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.