Journal articles: 'Visitor arrivals'

1

Petra, Hlaváčková, Slováčková Hana, Březina David, and Michal Jakub. "Comparison of results of visitor arrival monitoring using regression analysis." Journal of Forest Science 64, No. 7 (August 1, 2018): 303–12. http://dx.doi.org/10.17221/20/2018-jfs.

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Monitoring of visitor arrivals is one of the tools which help to ensure good-quality and suitable management of the respective area. This paper is aimed at the monitoring of visitor arrivals when the visitors are counted automatically using a field counting device, namely a pyroelectric sensor. In 2015, visitor arrival monitoring using a pyro sensor was conducted on the selected forest roads in the Křtiny Training Forest Enterprise of Masaryk Forest. Since this method should be employed in another project, it was necessary to find out whether the pyroelectric sensor is a reliable tool and whether it can be used for further research. The aim of this paper is to perform a regression analysis of the data collected at the selected site in order to determine whether the pyroelectric sensor provides relevant information. Two data sets acquired during the first week of the monitoring of visitor arrivals at the single site will be compared. The one set includes data obtained by automatic monitoring using the pyro sensor, the other set contains data gained by means of manual counting by students of the Faculty of Forestry and Wood Technology. Two directions of visitor flows were monitored – in and out. The data were statistically processed using the ADSTAT software. Results of the regression analysis show that the results of the visitor arrival monitoring carried out using a pyro sensor differ just slightly from those gained by manual counting.

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Gani, Azmat, and Michael D. Clemes. "The main determinants effecting international visitor arrivals in New Zealand." Tourism Economics 23, no. 5 (June 30, 2016): 921–40. http://dx.doi.org/10.1177/1354816616656417.

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This study examines the main determinants of international visitor arrivals in New Zealand in light of New Zealand’s major earthquakes in 2010 and 2011 as well as the global financial crisis of 2007. Our results provide strong evidence that visitor origin country per capita incomes, relative prices, real exchange rates, the distance between New Zealand and its main visitor origin countries and New Zealand’s record of good governance are statistically significant determinants of visitor arrivals to New Zealand. Our findings also reveal a negative but statistically insignificant effect of the earthquakes of 2010 and 2011on visitor arrivals to New Zealand. Our findings do not provide any significant regressive effect of the global financial crisis on visitor arrivals to New Zealand.

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Podhorodecka, Katarzyna. "Impact of Tourist and One-Day Visitor Arrivals on Economic Growth. Case Study of the Cayman Islands." Miscellanea Geographica 18, no. 3 (September 30, 2014): 16–25. http://dx.doi.org/10.2478/mgrsd-2014-0013.

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Abstract The Cayman Islands are one of the SISODs, located in the Caribbean Sea, with a high number of foreign visitor arrivals and a GDP based to a large extent on tourism. They are also considered to be SITE islands and may even be characteristic of the subtype, PROFIT-SITE islands. The aim of the article is to provide an answer to the question of whether the increase in the number of tourist and one-day visitor arrivals1 had a positive impact on the creation of GDP in the Cayman Islands during the period 1983-2011. The hypothesis was that such a correlation should exist and it should be a strong positive correlation, but only between the increase in number of tourist arrivals and increase in GDP. The second question was: which year is the most economically affected by the increase in tourist and visitor arrivals (the same or the following year)? The hypothesis was that the biggest impact is recorded in the year in which the increase in tourist and visitor arrivals occurs (not in the following year). The third question was: has the global economic crisis affected the tourism sector in the Cayman Islands? The hypothesis was that the Cayman Islands were not as badly affected by the global economic crisis as other SISOD countries. The methods used by the author were literature analysis, data analysis and the Spearman correlation ratio.

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Kumar, Nikeel, Ronald Ravinesh Kumar, Radika Kumar, and Peter Josef Stauvermann. "Is the tourism–growth relationship asymmetric in the Cook Islands? Evidence from NARDL cointegration and causality tests." Tourism Economics 26, no. 4 (July 2, 2019): 658–81. http://dx.doi.org/10.1177/1354816619859712.

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We examine whether tourism sector development measured by visitor arrivals per capita has asymmetric growth effects in the Cook Islands using quarterly data from 2010Q1 to 2016Q3. Asymmetric cointegration, long-run elasticities, and dynamic multipliers are estimated using the nonlinear autoregressive distributed lag model developed by Shin et al. Asymmetric causality testing is done using the asymmetric vector autoregression approach with insights from Hatemi-J. We identify structural breaks using the Lee and Strazicich multiple endogenous structural break unit root test. The results indicate that a 1% increase in visitor arrivals would increase gross domestic product (GDP) per capita by 0.92%, whereas a 1% decrease in visitor arrivals would decrease GDP per capita by 0.34%. The identified breaks, 2013Q2 and 2015Q3, are positive and significant in the short run only. The causality result confirms a bidirectional association, thus mutually reinforcing the asymmetric relationship between visitor arrivals and economic growth.

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Wulandary, Septie. "Vector Autoregressive Integrated (VARI) Method for Forecasting the Number of Internasional Visitor in Batam and Jakarta." Jurnal Matematika, Statistika dan Komputasi 17, no. 1 (August 24, 2020): 94–108. http://dx.doi.org/10.20956/jmsk.v17i1.10536.

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Forecasting methods that are often used are time series analysis, the Autoregressive (AR) method. The AR method only carries out univariate analysis, meaning that it carries out a separate model between the number of international visitor coming to Indonesia through Batam and Jakarta. Though there is a possibility, the number of international visitor arriving through Jakarta affects the number of international visitor arriving through Batam. Therefore, in this study the Vector Autoregressive Integrated (VARI) method is used. The VARI model is used on the number of international visitor arrivals per month at Batam and Jakarta for the period Januari 2014 – December 2019. VARI model formation through several stages, namely stationarity test, autoregressive order determination, VARI model formation, and diagnostic checking of the model. With the VARI model, VARI(5,1), the two significant simultaneously equation results are obtained. The Mean Absolute Percentage Error (MAPE) in this model are as follows 1,98% and 2,48% in predicting the number of international visitor arrivals in Batam and Jakarta. In this study also forecasting the number of international visitor arrivals in Batam and Jakarta in January – December 2020

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Chu, Hsiao-Ping, Ming-Liang Yeh, and Tsang-Yao Chang. "Are Visitor Arrivals to China Stationary? An Empirical Note." Asia Pacific Journal of Tourism Research 19, no. 2 (October 30, 2012): 248–56. http://dx.doi.org/10.1080/10941665.2012.739188.

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Kourtzidis, Stavros A., Panayiotis Tzeremes, Nickolaos G. Tzeremes, and Tomáš Heryán. "Integration of tourism markets in Australia." Tourism Economics 24, no. 7 (May 11, 2018): 901–7. http://dx.doi.org/10.1177/1354816618776184.

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By applying the methodological framework of transition modeling and econometric convergence tests introduced by Phillips and Sul, we reveal the existence of convergence clubs and transition convergence paths of international visitor arrivals for Australia. Specifically, by using monthly data of international arrivals over the period of January 1991 to September 2017, we provide evidence that tourism markets can integrate. The analysis suggests the identification of five distinct convergence clubs. This in turn signifies an integration phenomenon of Australia’s tourism market, which is revealed through the different convergence patterns of international visitor arrivals. Finally, it is evident that the revealed integration behavior of Australia’s international tourism market will enable policy makers to target better tourism needs through customized policies.

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Sæþórsdóttir, Anna Dóra, C. Michael Hall, and Þorkell Stefánsson. "Senses by Seasons: Tourists’ Perceptions Depending on Seasonality in Popular Nature Destinations in Iceland." Sustainability 11, no. 11 (May 30, 2019): 3059. http://dx.doi.org/10.3390/su11113059.

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Seasonality in visitor arrivals is one of the greatest challenges faced by tourist destinations. Seasonality is a major issue for sustainable tourism as it affects the optimal use of investment and infrastructure, puts pressure on resources and can create negative experience of crowding at destinations. Peripheral areas commonly experience more pronounced fluctuations in visitor arrivals. Iceland is one of those destinations. Although the number of tourists visiting the country has multiplied in recent years, seasonality is still a major challenge, especially in the more rural peripheral areas of the country. Iceland’s high season for tourism occurs during its brief summer (June to August), but in recent years more people visit the country on shorter winter trips, creating new management challenges. This research is based on an on-site questionnaire survey conducted in seven popular nature destinations in Iceland which compares the experience of summer and winter visitors. The results show that winter visitors are more satisfied with the natural environment while their satisfaction with facilities and service is in many cases lower. The areas are generally perceived as being more beautiful and quieter in winter than in summer. However, most destinations are considered less accessible and less safe in the winter. Tourists are much less likely to experience physical crowding during winter, although winter visitors are more sensitive to crowds, most likely because of expectations of fewer tourists. Finally, this research shows that tourists are less likely to encounter negative effects of tourism on the environment in the winter, (e.g., erosion or damage to rocks and vegetation), than in summer. The results highlight the importance of understanding visitor perceptions in a seasonal and temporal context.

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Prevedouros, Panos D. "Origin-Specific Visitor Demand Forecasting at Honolulu International Airport." Transportation Research Record: Journal of the Transportation Research Board 1600, no. 1 (January 1997): 18–27. http://dx.doi.org/10.3141/1600-03.

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The development of a PC-based and easy-to-use-and-update econometric model system for forecasting arrivals at the Honolulu International Airport is presented. A model system instead of a single model was designed so that differential growth rates from various origins as well as arrivals affected by curfews at the origin or the destination, or both, can be estimated. The airport system of the state facilitates the only mode of transportation into and out of Hawaii. Planning based on reliable demand forecasts is therefore essential. Separate models of arrivals from Australia and New Zealand, Canada, Germany, Korea, and the United Kingdom were specified and estimated using the Cochrane-Orcutt regression method. Several diagnostic tests were employed to arrive at the final models, as problems of correlation (over time) and collinearity (among variables) were present. Independent variables include the gross domestic product, population, monetary exchange rate, and unemployment rate of the origin countries. Historical values for the independent variables were taken from the publications of international organizations. Variables for wars that tend to affect flying security and natural disasters in Hawaii that affect the supply of tourist accommodations were included in the model specifications.

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Purwa, Taly, and Eviyana Atmanegara. "The International Tourism Performance Amidst Several Intervention Events: More than 20 Years of Multi Input Intervention Analysis in Bali, Jakarta, and Kepulauan Riau Provinces." Economics and Finance in Indonesia 66, no. 2 (December 31, 2020): 172. http://dx.doi.org/10.47291/efi.v66i2.870.

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As one of the priority sectors in economic development of Indonesia, tourism is expected to be the main key in accelerating economic and social growth, hence reducing poverty. The tourism performance, especially international tourism market, is highly prone to intervention events that can reduce the number of inbound tourists and produce a negative impact on economic development of the destination country. Therefore, anticipating and mitigating various intervention events is necessary to maintain the performance of the tourism sector in Indonesia. This study investigates the magnitude and patterns of impact of several intervention events on the number of international visitor arrivals via the three main ports of entry of Indonesia, i.e. Soekarno-Hatta Airport, Ngurah Rai Airport, and Batam Port. The multi input intervention models were constructed by covering intervention events, i.e. terrorism, disease pandemic, global financial crisis, natural disaster, and government policy, occurring in a relatively long time span, more than two decades, from January 1999 to August 2020. The results show that an intervention event does not always have a significant impact on the number of international visitor arrivals at the three main ports of entry. Generally, all intervention events can lead to a decrease in the number of international visitor arrivals but with different magnitude and pattern, with the biggest and longest impact is caused by COVID-19 pandemic. The direct or non-delayed pattern of impact only appears for terrorism and natural disaster that affect the number of international visitor arrivals via Ngurah Rai Airport.

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Balli, Hatice Ozer, Wai Hong Kan Tsui, and Faruk Balli. "Modelling the volatility of international visitor arrivals to New Zealand." Journal of Air Transport Management 75 (March 2019): 204–14. http://dx.doi.org/10.1016/j.jairtraman.2018.10.002.

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12

Chong, Terence Tai‐Leung, and Alex Wing‐Ho Yiu. "Nexus between visitor arrivals and residential property rents in Hong Kong." Pacific Economic Review 24, no. 3 (September 29, 2017): 464–78. http://dx.doi.org/10.1111/1468-0106.12241.

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13

Rossello-Nadal, Jaume. "Forecasting Turning Points in International Visitor Arrivals in the Balearic Islands." Tourism Economics 7, no. 4 (December 2001): 365–80. http://dx.doi.org/10.5367/000000001101297928.

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14

Mapjabil, Jabil, Rosmiza Mohd Zainol, Noorziah Mohd Salleh, Datu Razali Datu Eranza, and Sanisah Sarida Awang Hamat. "TAHAP KEPUASAN PENGUNJUNG TERHADAP KEMUDAHAN DAN PERKHIDMATAN GERAI MAKANAN LAUT DI KOTA KINABALU, SABAH." Asian People Journal (APJ) 3, no. 2 (October 31, 2020): 122–33. http://dx.doi.org/10.37231/apj.2020.3.2.221.

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Seafood stall facilities are one of the tourist attractions when it comes to seeking food in Kota Kinabalu. In the Malaysian context, studies related to tourism and the food sector are scarce and limited. The purpose of this study was to identify the characteristics of respondents' visits to seafood stalls, review the level of visitor satisfaction of basic amenities at seafood stalls, and to examine the satisfaction level of the seafood services visited in Kota Kinabalu. The number of respondents is 91 people consisting of local residents, including daily visitors and domestic tourists. The respondents involved in this study were daily visitors, domestic tourists, visiting family or friends living in Kota Kinabalu. Regardless of their primary purposes of the visit, the majority of them were satisfied with seafood stall facilities and services except for the hygiene and safety aspects of the area. Such facilities include facilities for the disabled. It must be noted that the availability of parking space is the main problem faced by respondents when visiting seafood stalls. In terms of policy implications, all stakeholders, especially the government, need to be aware of the current market demand and plan strategies to increase tourist arrivals to the state. Therefore, the findings of this study are important to policymakers, especially the Ministry of Tourism in Sabah. Keywords: Level of Visitor Satisfaction, Facilities and Services, Seafood

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15

Kenchington, Richard A. "Tourism in the Galápagos Islands: The Dilemma of Conservation." Environmental Conservation 16, no. 3 (1989): 227–32. http://dx.doi.org/10.1017/s0376892900009309.

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The Galapágos Archipelago is an area of very special significance to ecologists. Its unique flora and fauna, rugged scenery, and historical connections with Charles Darwin, make it a place of environmental pilgrimage. Between 1970 and 1985, visiting tourist numbers, comprised largely of foreign naturalists, grew from negligible levels to about 15,000 per annum. In 1987, visitor arrivals to the Galápagos grew to 32,500 following the opening of a second airport in 1986.Management of tourism has involved a policy which requires most visitors to be accommodated on boats, places strict controls on the sites which can be visited, and requires tourists to be accompanied by highly-trained Naturalist Guides. The policy precludes development of any substantial island-based tourist infrastructure. Recently this approach has become increasingly inadequate in the face of rapid small-scale, little coordinated, tourist development.

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Shahbaz, Muhammad, Ronald Ravinesh Kumar, Stanislav Ivanov, and Nanthakumar Loganathan. "The nexus between tourism demand and output per capita with the relative importance of trade openness and financial development." Tourism Economics 23, no. 1 (September 21, 2016): 168–86. http://dx.doi.org/10.5367/te.2015.0505.

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This article revisits the tourism-growth nexus in Malaysia using time series quarterly data over the period 1975–2013. The authors examine the impact of tourism using two separate indicators – tourism receipts per capita and visitor arrivals per capita. Using the augmented Solow production function and the autoregressive distributed lag bounds procedure, they also incorporate trade openness and financial development and account for structural breaks in series. The results show the evidence of cointegration between the variables. Assessing the long-run results using both indicators of tourism demand, it is noted that the elasticity coefficient of tourism is 0.13 and 0.10 when considering visitor arrivals and tourism receipts (in per capita terms), respectively. Notably, the impact of tourism demand is marginally higher with visitor arrivals. The elasticity of trade openness is 0.19, that of financial development is 0.09 and that of capital share is 0.15. In the short run, the coefficient of tourism is marginally negative, and for financial development and trade openness, it is 0.01 and 0.18, respectively. The Granger causality tests show bidirectional causation between tourism and output per capita, financial development and tourism and trade openness and tourism demand, duly indicating the feedback or mutually reinforcing impact between the variables and providing evidence that tourism is central to enhancing the key sectors and the overall income level.

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Fauzi, Nur Fatihah, Nurul Shahiera Ahmadi, Nor Hayati Shafii, and Huda Zuhrah Ab Halim. "A Comparison Study on Fuzzy Time Series and Holt-Winter Model in Forecasting Tourist Arrival in Langkawi, Kedah." Journal of Computing Research and Innovation 5, no. 1 (October 2, 2020): 34–43. http://dx.doi.org/10.24191/jcrinn.v5i1.138.

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The tourism industry in Malaysia has been growing significantly over the years. Tourism has been one of the major donors to Malaysia’s economy. Based on the report from the Department of Statistics, a total of domestic visitors in Malaysia were recorded at about 221.3 million in 2018 with an increase of 7.7% alongside a higher record in visitor arrivals and tourism expenditure. This study aims to make a comparison between two methods, which are Fuzzy Time Series and Holt-Winter in forecasting the number of tourist arrival in Langkawi based on the monthly tourist arrival data from January 2015 to December 2019. Both models were generated using Microsoft Excel in obtaining the forecast value. The Mean Square Error (MSE) has been calculated in this study to get the best model by looking at the lowest value. The result found that Holt-Winter has the lowest value that is 713524285 compared to the Fuzzy Time Series with a value of 2625517469. Thus, the Holt-Winter model is the best method and has been used to forecast the tourist arrival for the next 2 years. The forecast value for the years 2020 and 2021 are displayed by month.

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Charles, Jacky S., and Thomas M. Fullerton. "Research Note: An Error Correction Analysis of Visitor Arrivals in the Bahamas." Tourism Economics 18, no. 1 (February 2012): 253–59. http://dx.doi.org/10.5367/te.2012.0101.

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Narayan, Paresh Kumar. "Examining the behaviour of visitor arrivals to Australia from 28 different countries." Transportation Research Part A: Policy and Practice 42, no. 5 (June 2008): 751–61. http://dx.doi.org/10.1016/j.tra.2008.01.032.

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Hui, Tak-Kee, and Edith Yuen. "Study of trends in US visitor arrivals in Singapore: a nonparametric approach." Tourism Management 19, no. 3 (June 1998): 289–91. http://dx.doi.org/10.1016/s0261-5177(98)00019-3.

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Ete, Agustinus Angelaus, Suhartono Suhartono, and Raden Mohammad Atok. "SSA and ARIMA for Forecasting Number of Foreign Visitor Arrivals to Indonesia." Inferensi 3, no. 1 (March 30, 2020): 55. http://dx.doi.org/10.12962/j27213862.v3i1.6882.

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Chow, Clement Kong Wing, and Wai Hong Kan Tsui. "Cross‐border tourism: Case study of inbound Russian visitor arrivals to China." International Journal of Tourism Research 21, no. 5 (July 2, 2019): 693–711. http://dx.doi.org/10.1002/jtr.2297.

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Kourentzes, Nikolaos, Andrea Saayman, Philippe Jean-Pierre, Davide Provenzano, Mondher Sahli, Neelu Seetaram, and Serena Volo. "Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team." Annals of Tourism Research 88 (May 2021): 103197. http://dx.doi.org/10.1016/j.annals.2021.103197.

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Liu, Anyu, Laura Vici, Vicente Ramos, Sauveur Giannoni, and Adam Blake. "Visitor arrivals forecasts amid COVID-19: A perspective from the Europe team." Annals of Tourism Research 88 (May 2021): 103182. http://dx.doi.org/10.1016/j.annals.2021.103182.

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Kim, Min-Seong, Jinwon Kim, and Brijesh Thapa. "Influence of Environmental Knowledge on Affect, Nature Affiliation and Pro-Environmental Behaviors among Tourists." Sustainability 10, no. 9 (August 31, 2018): 3109. http://dx.doi.org/10.3390/su10093109.

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Jeju Island is a popular destination in South Korea that is dependent on nature-based tourism. The annual increase in the influx of visitors has created major environmental impacts due to overuse and commercial expansion. With projected growth in arrivals and the development of tourism infrastructure, the island will experience perpetual challenges for sustainable management of natural resources. However, the role of visitors will be central via a commitment to practice pro-environmental behaviors to protect the island from further degradation. This study was grounded in the cognition-affection-attitude-behavior model to examine the predictive validity of tourists’ environmental knowledge, environmental affect, and nature affiliation on pro-environmental behavior. The data comprised responses from 304 domestic visitors who had visited Jeju Island. The empirical findings indicate that environmental affect was significantly impacted by two dimensions of environmental knowledge (i.e., subjective and objective). Additionally, nature affiliation was positively impacted by environmental affect, while pro-environmental behavior was significantly influenced by both environmental affect and nature affiliation. Overall, these findings provide theoretical and practical implications for sustainable tourism at a nature-based destination. The findings can be utilized for implementation of intervention programs and visitor management at Jeju Island.

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Kumar, Nikeel, and Ronald Ravinesh Kumar. "Relationship between ICT and international tourism demand: A study of major tourist destinations." Tourism Economics 26, no. 6 (July 2, 2019): 908–25. http://dx.doi.org/10.1177/1354816619858004.

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In this article, we study the effect of ICT on tourism demand in nine major tourist destinations based on visitor arrivals. Mobile and broadband subscriptions are used to proxy for ICT. Additionally, we account for price, source country’s income, and the destination’s income. Balanced panels for the period 1995–2017 and 2002–2017 are used for mobile and broadband subscriptions, respectively. The pooled mean group approach is used for estimation. The results indicate a 1% increase in mobile subscriptions and broadband would increase international visitor arrivals by 0.04% and 0.11%, respectively. The elasticity coefficients of price and income are −0.71 and 1.58, respectively, based on the mobile subscription model, and −0.88 and 1.83, respectively, based on broadband subscription. The destination’s income has only a short-run positive association with tourism demand. The causality results indicate that ICT cause tourism demand, and support for technology-led growth hypothesis in the major tourist destinations.

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Lee, Chew Ging. "Whether a Shock Has a Temporary or Permanent Effect on Visitor Arrivals in Singapore." Tourism Review International 14, no. 1 (January 1, 2010): 43–46. http://dx.doi.org/10.3727/154427211x12954639814939.

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Mangindaan, Joy Melchisedec Pierre, and Tipaluck Krityakierne. "Analysis of international visitor arrivals in Bali: modeling and forecasting with seasonality and intervention." Journal of Physics: Conference Series 1132 (November 2018): 012069. http://dx.doi.org/10.1088/1742-6596/1132/1/012069.

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Qiu, Richard T. R., Doris Chenguang Wu, Vincent Dropsy, Sylvain Petit, Stephen Pratt, and Yasuo Ohe. "Visitor arrivals forecasts amid COVID-19: A perspective from the Asia and Pacific team." Annals of Tourism Research 88 (May 2021): 103155. http://dx.doi.org/10.1016/j.annals.2021.103155.

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Narayan, Paresh Kumar. "Testing the Unit Root Hypothesis When the Alternative is a Trend Break Stationary Process: An Application to Tourist Arrivals in Fiji." Tourism Economics 11, no. 3 (September 2005): 351–64. http://dx.doi.org/10.5367/000000005774352971.

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The unit root hypothesis owes much to the work of Dickey and Fuller and has gained momentum since the seminal contribution of Perron (1989), who introduced the idea of structural breaks in unit root tests. In a recent study Sen (2003), extending the work of Zivot and Andrews (1992), recommends the F-test statistic for a unit root in the presence of a structural change in the economy. The central aim of this paper is to apply the Sen test to tourist arrivals to Fiji. The idea behind this exercise is to identify the year of the structural break and, more importantly, to examine whether the break has had a permanent or temporary effect on tourist arrivals in Fiji. Among our key results, we find that visitor arrivals in Fiji from Australia, New Zealand and the USA are stationary, implying that shocks have a temporary effect.

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Lai, Sue Ling, Ming Liu, Kuo Cheng Kuo, and Ray Chang. "Energy Consumption Forecasting in Hong Kong Using ARIMA and Artificial Neural Networks Models ." Applied Mechanics and Materials 672-674 (October 2014): 2085–97. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.2085.

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There have been considerable efforts contributed to the development of effective energy demand forecast models due to its critical role for economic development and environmental protection. This study focused on the adoption of artificial neural network (ANN) and autoregressive integrated moving average (ARIMA) models for energy consumption forecasting in Hong Kong over the period of 1975-2010. Four predictors were considered, including population, GDP, exports, and total visitor arrivals. The results show most ANN models demonstrate acceptable forecast accuracy when single predictor is considered. The best single input model is the case with GDP as predictor. Population and exports are the next proper single inputs. The model with total visitor arrivals as sole predictor does not perform satisfactorily. This indicates that tourism development demonstrates a different pattern from that of energy consumption. In addition, the forecast accuracy of ANN does not improve considerably as the number of predictors increase. Findings imply that with the ANN approach, choosing appropriate predictors is more important than increasing the number of predictors. On the other hand, ARIMA generates forecasts as accurate as some good cases by ANN. Results suggest that ARIMA is not only a parsimonious but effective approach for energy consumption forecasting in Hong Kong.

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Chen, Ying-Chih, Hsin-Hong Kang, and Tzer-Chyun Yang. "A Study on the Impact of SARS on the Forecast of Visitor Arrivals to China." Journal of Asia-Pacific Business 8, no. 1 (March 22, 2007): 31–50. http://dx.doi.org/10.1300/j098v08n01_04.

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Ashartono, Rakhmat, Myrza Rahmanita, and Diena Mutiara Lemy. "The Effect of Destination Management and Community Participation to The Visitors Consumption at Tebing Breksi Sleman Yogyakarta." TRJ Tourism Research Journal 2, no. 1 (October 17, 2018): 1. http://dx.doi.org/10.30647/trj.v2i1.19.

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The development of a new tourist destination indeed needs more attention to increase the number of tourist arrivals coming in an area. Breksi Cliff is one of the new destinations in Sleman district which is in the development period, with the development of Breksi cliff is expected to increase the level of welfare of the surrounding community through the development of the destination and community participation itself. This research is a research with descriptive method of analysis with quantitative approach to know accurate information about matters related to Tourism Destination Management and Public Participation to Welfare Society through Visitor Consumption. for the data analysis techniques alone will use Structural Equation Modeling. From the results of the study found that the level of community welfare Taman Tebing Breksi can increase with the management of destinations and community participation itself through the consumption of visitors

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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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Hsieh, Shun-Chieh. "Tourism Demand Forecasting Based on an LSTM Network and Its Variants." Algorithms 14, no. 8 (August 18, 2021): 243. http://dx.doi.org/10.3390/a14080243.

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The need for accurate tourism demand forecasting is widely recognized. The unreliability of traditional methods makes tourism demand forecasting still challenging. Using deep learning approaches, this study aims to adapt Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit networks (GRU), which are straightforward and efficient, to improve Taiwan’s tourism demand forecasting. The networks are able to seize the dependence of visitor arrival time series data. The Adam optimization algorithm with adaptive learning rate is used to optimize the basic setup of the models. The results show that the proposed models outperform previous studies undertaken during the Severe Acute Respiratory Syndrome (SARS) events of 2002–2003. This article also examines the effects of the current COVID-19 outbreak to tourist arrivals to Taiwan. The results show that the use of the LSTM network and its variants can perform satisfactorily for tourism demand forecasting.

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Min, Jennifer C. H. "TOURISM BEHAVIOR TOWARD DISASTERS: A CROSS-CULTURAL COMPARISON." Social Behavior and Personality: an international journal 35, no. 8 (January 1, 2007): 1031–32. http://dx.doi.org/10.2224/sbp.2007.35.8.1031.

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The current study extends the author's previous study in which Hofstede's uncertainty avoidance dimension (1991) was applied to the case of the September 21st earthquake in 1999, the largest natural disaster of the 20th century in Taiwan. The study assessed how the behavior of Japanese and United States tourists has been affected. The results indicate clear differences in rebound status between Japanese and American visitor arrivals that are remarkably consistent with Hofstede's conceptualization – the Japanese tended toward uncertainty avoidance more than the Americans.

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Bhattacharya, Mita, and Paresh Kumar Narayan *. "Testing for the random walk hypothesis in the case of visitor arrivals: evidence from Indian tourism." Applied Economics 37, no. 13 (July 20, 2005): 1485–90. http://dx.doi.org/10.1080/00036840500109332.

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McDonald, Michelle L., and Royston O. Hopkin. "The future of hospitality education in Grenada." International Journal of Contemporary Hospitality Management 15, no. 3 (June 1, 2003): 156–60. http://dx.doi.org/10.1108/09596110310470185.

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The quality of hospitality education is a topical issue. It is being increasingly realised that the education level of tourism employees impacts on the quality of a country’s tourism industry. As the most tourism‐oriented region globally, the Caribbean is slowly awakening to the realisation that, unless its tourism employees are highly educated and skilled, the region will continue to account for an insignificant percentage of world tourism arrivals. In Grenada, hospitality education courses are limited, given the small tourism plant and comparatively low visitor arrivals. Research was undertaken by one of the authors, to explore the opinions of the accommodation sector about current education provisions and the future direction that courses should take. Integration of all stakeholders in the implementation of the broad education policy outlined by the government is crucial to improving hospitality education in Grenada to ensure a competitive tourism industry.

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Tang, Tuck Cheong, and Koi Nyen Wong. "Research Note: The SARS Epidemic and International Visitor Arrivals to Cambodia: Is the Impact Permanent or Transitory?" Tourism Economics 15, no. 4 (December 2009): 883–90. http://dx.doi.org/10.5367/000000009789955206.

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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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Semlitsch, John H. P. "The Friction of Recognition." Athanor 37 (December 3, 2019): 11–20. http://dx.doi.org/10.33009/fsu_athanor116674.

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Life began for me at a point different from where it began for the visitor in front of me. The work started at yet another point for someone arriving later than I did. The footage may have already begun again for some early arrivals to the exhibition. That evening, Life (2017) began again for all of us, probably more than once. Drew Bacon’s most recent animation started for viewers as it was constantly refreshed and reinvigorated through the sporadic recognition of his images. When I first witnessed Bacon’s Life, I thought the footage ran continuously forward, taking new material for its own figuration as it swept through a limitless digital inventory.

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NARAYAN, PARESH KUMAR, and ARTI PRASAD. "EXAMINING THE BEHAVIOUR OF VISITOR ARRIVALS TO AUSTRALIA FROM TWENTY DIFFERENT COUNTRIES: AN APPLICATION OF PANEL UNIT ROOT TESTS." Economic Papers: A journal of applied economics and policy 27, no. 3 (September 2008): 265–71. http://dx.doi.org/10.1111/j.1759-3441.2008.tb01042.x.

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Li, Hengyun, Carey Goh, Kam Hung, and Jason Li Chen. "Relative Climate Index and Its Effect on Seasonal Tourism Demand." Journal of Travel Research 57, no. 2 (January 23, 2017): 178–92. http://dx.doi.org/10.1177/0047287516687409.

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This study proposes a relative climate index based on the push and pull theory to assess the effects of relative climate variability on seasonal tourism demand. The relative climate index measures the climatic comfort of a destination relative to that of the tourist origin. Using the proposed approach, the effects of the relative climate comfort on seasonal tourism demand are empirically tested based on a quarterly panel data set of visitor arrivals from Hong Kong to 13 major Chinese cities. The intra-annual seasonality and interannual variability are both tested in the model. The results indicate that the intra-annual relative climate positively influences tourism demand in Mainland regions, where the climate is significantly different from that of Hong Kong.

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Cvetkoska, Violeta, and Petra Barišić. "THE EFFICIENCY OF THE TOURISM INDUSRTY IN THE BALKANS." ЗБОРНИК РАДОВА ЕКОНОМСКОГ ФАКУЛТЕТА У ИСТОЧНОМ САРАЈЕВУ 1, no. 14 (October 5, 2017): 31. http://dx.doi.org/10.7251/zrefis1714031c.

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The countries in the Balkan region report an increase in the number of tourist arrivals and spending but the question that remains is if their overall tourism industry is efficient. Using the methodology data envelopment analysis, this paper analyzes the efficiency of the tourism industry in the Balkans at the macro level. Eleven countries in the Balkan region were included in the research, namely Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Greece, Macedonia, Montenegro, Romania, Serbia, Slovenia, and Turkey. The period of observation was six years (2010-2015). Two inputs and two outputs were selected. Visitor exports and domestic travel and tourism spending were inputs, while travel and tourism total contribution to GDP and employment were outputs. According to the obtained results, there was no country that was efficient in every year in every window, and it was found that the most efficient country in the whole observed period is Albania, while the least efficient country is Montenegro.

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Kovács, Zoltán, György Vida, Ábel Elekes, and Tamás Kovalcsik. "Combining Social Media and Mobile Positioning Data in the Analysis of Tourist Flows: A Case Study from Szeged, Hungary." Sustainability 13, no. 5 (March 8, 2021): 2926. http://dx.doi.org/10.3390/su13052926.

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Despite the growing importance of mobile tracking technology in urban planning and traffic forecasting, its utilization in the understanding of the basic laws governing tourist flows remains limited. Knowledge regarding the motivations and spatial behavior of tourists has great potential in sustainable tourism studies. In this paper, we combine social media (Twitter) and mobile positioning data (MPD) in the analysis of international tourism flows in Szeged, a secondary urban center in Hungary. First, the content of geotagged and non-geotagged Twitter messages referring to Szeged in a six-month period of 2018 was analyzed. In this way specific events attracting foreign tourists were identified. Then, using MPD data of foreign SIM cards, visitor peaks in the investigated period were defined. With the joint application of the social media and mobile positioning analytical tools, we were able to identify those attractions (festivals, sport and cultural events, etc.) that generated significant tourism arrivals in the city. Furthermore, using the mixed-method approach we were also able to analyze the movements of foreign visitors during one large-scale tourism event and evaluate its hinterland. Overall, this study supports the idea that social media data should be combined with other real-time data sources, such as MPD, in order to gain a more precise understanding of the behavior of tourists. The proposed analytical tool can contribute to methodological and conceptual development in the field, and information gained by its application can positively influence not only tourism management and planning but also tourism marketing and placemaking.

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Jumanazarov, Sanjar, Alisher Kamilov, and Kiattipoom Kiatkawsin. "Impact of Samarkand’s Destination Attributes on International Tourists’ Revisit and Word-of-Mouth Intention." Sustainability 12, no. 12 (June 24, 2020): 5154. http://dx.doi.org/10.3390/su12125154.

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Samarkand, Uzbekistan is a relatively unknown but emerging tourism destination. The city was once a major trading hub along the Great Silk Road. The once great city of Samarkand was hidden from the world tourism market, only to emerge after the country gained its independence in 1991. Since then, the artistically beautiful and historically-rich monuments have been attracting tourists from around the world. However, Samarkand has not been gaining much research attention at the same rate as international tourist arrivals. Thus, this study aims to comprehensively assess the city’s destination attributes and their impact on international visitor loyalty behaviors. The literature review process identified 16 destination attribute dimensions. Additionally, cognitive and affective evaluation, satisfaction, revisit intention, and word-of-mouth intention were identified and added to form the study model. A total of 223 international tourist samples were collected in Samarkand to validate the proposed model. The findings revealed 10 attributes to be consistently rated by the samples. Subsequently, the attributes were significantly influencing all subsequent hypothesized relationships. Both theoretical and practical implications are also discussed.

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Marković, Ana Tripković, Miško Rađenović, and Anisa Murić. "Tourists and Local Stakeholders Attitudes Towards Offer and Market Position of Tourist Destination Budva." ECONOMICS 4, no. 2 (December 1, 2016): 113–32. http://dx.doi.org/10.1515/eoik-2017-0008.

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Summary There are various definitions of tourist destination. All of them define tourist destination as an area with specific tourist facilities and attractions, (primary and secondary elements) which tourists choose as their journey goal. Budva individually represents the largest tourist destination due to number of arrivals and overnight stays. During its life cycle Budva has gone through different phases as a tourist destination. This thesis implies that it is not enough to use only common quantitative indicator of visitor number to define proper the position of tourist destination and predict further development. This text is based on a comparative analysis of the attitudes of tourists and local stakeholders in the three field researches, conducted in the period between 2015 and 2016. The thesis comes to the conclusion that the actual growth is based on meeting the needs of existing markets and tourists. On the other side, aspect of desired market position disagrees with scores of tourist offer elements- which should be input for improvement and preparation for the next stage in the destination development.

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Kusuma, Dedy Hidaya, and Moh Nur Shodiq. "Sistem Rekomendasi Destinasi Pariwisata Menggunakan Metode Hibrid Case Based Reasoning dan Location Based Service Sebagai Pemandu Wisatawan di Banyuwangi." INTENSIF 1, no. 1 (February 1, 2017): 28. http://dx.doi.org/10.29407/intensif.v1i1.540.

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As one of the fastest growing tourist destinations, the number of tourist arrivals in Banyuwangi Regency shows a significant growth where in the range of 2010 - 2015 there is an increase of domestic tourists by 161% and abroad by 210%. The increase in tourist numbers is not a trouble-free process, especially with regard to visitor preferences that change over time. Tourist information and a variety of tourist interests often make tourists confused in determining the choice of any destination to visit. While Banyuwangi tourism information that is available in printed form or that can be accessed online still requires tourists to sort and choose their own in accordance with the interests and preferences so that tourists need any suggestions or recommendations. In the field of tourism, this recommendation may include objects to be visited, existing tourist events, travel schedules, travel routes, availability of infrastructure and so forth. The recommendation system proposed in this research uses a combination of (hybrid) case-based reasoning and location-based methods. The system is built in the form of android based mobile applications. Input from users to the system of travelers preferences include tourist types, tariff categories, modes of transportation, and tourism activities. These preferences together with user location based on GPS coordinates are further compared to the tourist object attributes stored on the system using the nearest neighbor similarity method. The output of the system in the form of recommendation of tourism object that has the highest similarity to the user preference. The results of this study are expected to assist tourists in choosing tourism objects in Banyuwangi according to their preferences or demand criteria.

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Purwaningsih, Tuti, Anusua Ghosh, and Chumairoh Chumairoh. "Spatial data modeling in disposable income per capita in china using nationwide spatial autoregressive (SAR)." International Journal of Advances in Intelligent Informatics 3, no. 2 (July 31, 2017): 98. http://dx.doi.org/10.26555/ijain.v3i2.93.

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China as a country became the economic center of the world. However, with a population of 1.3 billion, China's per capita income is still at number 80 in the world. In the world, considering the imbalance between town and country with 100 million people still living in poverty. Thus, to address this imbalance, it is necessary to study the condition in depth, because income per capita is often used as a benchmark to measure the prosperity of a country. With greater and equitable income per capita, the country will be judged increasingly affluent. Two factors, mainly industry and tourism, play an important role in the economic progress in China. These are include Per capita Disposable Income Nationwide (yuan), Total Value of Exports of operating units (1,000 USD), Registered Unemployed Person in Urban Area (10000 person), Foreign Exchange Earning from International tourism(in millions USD) and Number of Overseas Visitor Arrivals (million person/time). Thus, it is necessary to investigate the influence of these factors to increase per capita income. Since the economic development of a region usually affect the surrounding area, this study aims to include spatial effects, using Spatial Autoregressive (SAR) Model. The results suggest that the per capita income affected by the Tourism factor is about 58.65% (R-squared).

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Lin, Vera Shanshan. "Judgmental adjustments in tourism forecasting practice: How good are they?" Tourism Economics 25, no. 3 (November 16, 2018): 402–24. http://dx.doi.org/10.1177/1354816618806727.

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This study aims to evaluate the accuracy of different judgmental forecasting tasks, compare the judgmental forecasting behaviour of tourism researchers and practitioners and explore the validity of experts’ judgmental behaviour by using the Hong Kong visitor arrivals forecasts over the period 2011Q2−2015Q4. Delphi-based judgmental forecasting procedure was employed through the Hong Kong Tourism Demand Forecasting System, an online forecasting support system, to collect and combine experts’ adjusted forecasts. This study evaluates forecasting performance and explores the characteristics of judgmental adjustment behaviour through the use of a group of error measures and statistical tests. The findings suggest a positive correlation between forecast accuracy and the level of data variability, and that experts’ adjustments are more beneficial in terms of achieving higher accuracy for series with higher variability. Industry practitioners’ forecasts outperformed academic researchers, particularly in making short-term forecasts. However, no significant difference was found between the two panels in making directionally correct forecasts. Experts’ judgmental intervention was found most useful for those series most in need of adjustment. The size of adjustment was found to have a strong and significantly positive association with the direction of forecast adjustment, but no statistically significant evidence was found regarding the relationship between accuracy improvement and adjustment size.

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Journal articles on the topic 'Visitor arrivals'

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