scholarly journals Quantile Dependence in Tourism Demand Time Series: Evidence in the Southern Italy Market

2020 ◽  
Vol 12 (8) ◽  
pp. 3243
Author(s):  
Giovanni De Luca ◽  
Monica Rosciano
Keyword(s):  
Demand Forecasting ◽  
Tourism Industry ◽  
Tourism Demand ◽  
Campania Region ◽  
Travel And Tourism ◽  
Tourist Destinations ◽  
High Quantiles ◽  
International Tourist ◽  
Long Time ◽  
Hotel Accommodation

Travel and tourism is an important economic activity in most countries around the world. In 2018, international tourist arrivals grew 5% to reach the 1.4 billion mark and at the same time export earnings generated by tourism have grown to USD 1.7 trillion. The rapid growth of the tourism industry has globally attracted the interest of researchers for a long time. The literature has tried to model tourism demand to analyze the effects of different factors and predict the future behavior of the demand. Forecasting of tourism demand is crucial not only for academia but for tourism industries too, especially in line with the principles of sustainable tourism. The hospitality branch is an important part of the tourism industry and accurate passenger flow forecasting is a key link in the governance of the resources of a destination or in revenue management systems. In this context, the paper studies the interdependence of tourism demand in one of the main Italian tourist destinations, the Campania region, using a quantile-on-quantile approach between overall and specific tourism demand. Data are represented by monthly arrivals and nights spent by residents and non-residents in hotels and complementary accommodations from January 2008 to December 2018. The results of the analysis show that the hotel-accommodation component of the tourism demand appears to be more vulnerable than extra-hotel accommodation component to the fluctuations of the overall tourism demand and this feature is more evident for the arrivals than for nights spent. Moreover, the dependence on high quantiles suggests strategy of diversification or market segmentation to avoid overtourism phenomena and/or carrying capacity problems. Conversely, dependence on low quantiles suggests the use of push strategies to stimulate tourism demand. Finally, the results suggest that it could be very useful if the stakeholders of the tourism sector in Campania focused their attention on the collaboration theory.

Artificial Intelligence Applications in Tourism

2011 ◽  
pp. 241-247 ◽  
Author(s):  
Carey Goh ◽  
Henry M.K. Mok ◽  
Rob Law
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Demand Forecasting ◽  
Tourism Industry ◽  
Tourism Demand ◽  
Investment Planning ◽  
Data Mining Techniques ◽  
Travel And Tourism ◽  
The Future ◽  
Multiplier Effects

The tourism industry has become one of the fastest growing industries in the world, with international tourism flows in year 2006 more than doubled since 1980. In terms of direct economic benefits, United Nations World Tourism Organization (UNWTO, 2007) estimated that the industry has generated US $735 billion through tourism in the year of 2006. Through multiplier effects, World Travel and Tourism Council (WTTC, 2007) estimated that tourism will generate economic activities worth of approximately US $5,390 billion in year 2007 (10.4% of world GDP). Owing to the important economic contribution by the tourism industry, researchers, policy makers, planners, and industrial practitioners have been trying to analyze and forecast tourism demand. The perishable nature of tourism products and services, the information-intensive nature of the tourism industry, and the long lead-time investment planning of equipment and infrastructures all render accurate forecasting of tourism demand necessary (Law, Mok, & Goh, 2007). Past studies have predominantly applied the well-developed econometric techniques to measure and predict the future market performance in terms of the number of tourist arrivals in a specific destination. In this chapter, we aim to present an overview of studies that have adopted artificial intelligence (AI) data-mining techniques in studying tourism demand forecasting. Our objective is to review and trace the evolution of such techniques employed in tourism demand studies since 1999, and based on our observations from the review, a discussion on the future direction of tourism research techniques and methods is then provided. Although the adoption of data mining techniques in tourism demand forecasting is still at its infancy stage, from the review, we identify certain research gaps, draw certain key observations, and discuss possible future research directions.

Global cities, Tokyo, urban tourism

2017 ◽  
Vol 3 (2) ◽  
pp. 143-157 ◽  
Author(s):  
Joan Henderson
Keyword(s):  
Tourism Industry ◽  
Global City ◽  
Global Cities ◽  
Content Type ◽  
Tourist Destinations ◽  
International Tourist ◽  
Tourist Flows ◽  
Tourism Resources ◽  
The Relationship

Purpose The purpose of this paper is to explore the relationship between global cities and international tourism with particular reference to the recent experiences of Tokyo which has recently seen a marked increase in arrivals. It addresses questions of the standing of Tokyo as a global city and tourist destination, how the two functions are connected and why changes are occurring. Design/methodology/approach The methodology employed is that of an empirical case study based on the analysis of published materials drawn from a diversity of sources. Findings The defining characteristics of global cities are generally conducive to their function as international tourist destinations. They possess a wealth of tourism resources and amenities which facilitate inbound tourist flows. Tokyo is a prominent example of a global city, but has tended to attract fewer visitors than others in that category. The recent significant growth in arrivals is attributed to changes in the tourism industry and wider environment, yet some challenges remain before it can catch up with its counterparts. Originality/value Fresh insights are afforded into the implications of global city status for tourism and the development of Tokyo as a destination which tends to have been neglected in the literature.

The Development of Travel and Tourism Industry in Iran

2020 ◽  
Vol 9 ◽  
pp. 2173-2179
Author(s):  
Aleksandr B. Orishev ◽  
Azer A. Mamedov ◽  
Igor Yu. Zalysin ◽  
Dmitry V. Kotusov ◽  
Sergey L. Grigoriev
Keyword(s):  
Far East ◽  
Tourism Industry ◽  
Rural Tourism ◽  
Main Research ◽  
Free Trade Zones ◽  
Travel And Tourism ◽  
The Far East ◽  
International Tourist ◽  
Tourist Flows ◽  
Research Findings

The article presents the results of scientific research devoted to the study of tourism in the countries of the Far East, obtained at one of its stages. The purpose of the article is to characterize the state of rural tourism in Iran. The article shows how the attitude to tourism has changed in this country, uncovering the main reasons for the growth of domestic and international tourist flows in recent years. There are several areas of rural tourism in Iran, which include visits to historical villages and free trade zones, camping in nomad tents, recreation in parks and natural resorts, and trips to the desert. The main research findings of the authors demonstrate the problems facing rural tourism in Iran and identify the risks that arise in this sector of the economy.

Which search queries are more powerful in tourism demand forecasting: searches via mobile device or PC?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mingming Hu ◽  
Mengqing Xiao ◽  
Hengyun Li
Keyword(s):  
Mobile Devices ◽  
Demand Forecasting ◽  
Tourism Industry ◽  
Strategic Decision ◽  
Single Type ◽  
Tourism Demand ◽  
Content Type ◽  
Search Queries ◽  
Search Volume ◽  
Aggregated Search

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.

scholarly journals Impact of “Nepal Tourism Year 2011” on Tourist Arrival in Pokhara

2014 ◽  
Vol 6 ◽  
pp. 22-50
Author(s):  
Biswo Kallyan Parajuli ◽  
Yog Raj Paudel
Keyword(s):  
Information Access ◽  
Tourism Industry ◽  
Tourist Destinations ◽  
International Tourist ◽  
The Impact

Tourism is a growing industry in Nepal. Pokhara is one of the major tourist destinations in Nepal. To foster the tourism industry in Nepal then government of Nepal decided on 2008 to launch a national tourism campaign “Nepal Tourism Year 2011” targeting to bring one million international tourists into Nepal in the year 2011. This paper focuses on analyzing the impact of Nepal Tourism Year 2011’s advertisement campaign on tourist arrival in Pokhara city. Also it attempts to highlight the impact of network and information access on tourism arrival. A sincere attempt has also been made to investigate the impact of NTY in bringing international tourist in Nepal particularly in Pokhara. DOI: http://dx.doi.org/10.3126/hjsa.v6i0.10687   Himalayan Journal of Sociology and Anthropology Vol.6 2014: 22-50

Economic Implication of Absence of National Carrier in the Nigeria Aviation Industry

2018 ◽  
Vol 1 (2) ◽  
pp. 1-8
Author(s):  
Gbadamosi Kolawole T ◽  
Adekunle Emmanuel A.
Keyword(s):  
Federal Government ◽  
Airline Industry ◽  
Payback Period ◽  
Tourism Industry ◽  
Aviation Industry ◽  
Economic Implication ◽  
Travel And Tourism ◽  
The Past ◽  
International Tourist ◽  
Foreign Competitors

The aim of the study is to access the economic implication of absence of National carrier in the Nigeria aviation industry. The airline industry is the key drive of the travel and tourism industry and also a major contributor to many countries’ overall economy through international tourist arrivals and departures. The study estimate the amount of revenue Nigeria is losing to capital flights for not having a viable national carrier over the past ten years that is from 2007 to 2016.The estimated amount of revenue loss was examined on airlines offering direct flights on Nigeria to London route, in which we have two foreign airlines (British airways and Virgin Atlantic airline)and a Nigeria’s private national carrier which is Med-view airline. The class of tickets and services in each class of ticket being offered by the airlines was examined. The study reveals an estimate of total of over $6 Billion revenue were being lost to hands of foreign competitors over the past ten years with British airways generating closely to $4 billion, while Virgin Atlantic generated over $2.3 billion and Med-view generated over $133 million in the past ten years. The study also reveals that the higher the passenger carried the higher the revenue and vice versa. However, establishing a national carrier by the federal government is imminent which will express Nigeria culture and to better serve passengers especially Nigerians. Finally, banks and other governmental financial institutions should make available enough funds with longer payback period and little interest for both existing airlines to upgrade their services and new entrants to be able to purchase necessary equipment’s to make them competitive in the market.

scholarly journals Malaysia Tourism Demand Forecasting Using Box-Jenkins Approach

2018 ◽  
Vol 7 (4.30) ◽  
pp. 454 ◽  
Author(s):  
Diyana Izyan Amir Hamzah ◽  
Maria Elena Nor ◽  
Sabariah Saharan ◽  
Noor Fariza Mohd Hamdan ◽  
Nurul Asmaa Izzati Nohamad
Keyword(s):  
Demand Forecasting ◽  
Information Criterion ◽  
Research Paper ◽  
Tourism Industry ◽  
Percentage Error ◽  
Tourism Demand ◽  
Absolute Deviation ◽  
Correct Judgment ◽  
Accurate Forecast ◽  
Future Strategy

Tourism industry in Malaysia is crucial and has contributes a huge part in Malaysia’s economic growth. The capability of forecasting field in tourism industry can assist people who work in tourism-related-business to make a correct judgment and plan future strategy by providing the accurate forecast values of the future tourism demand. Therefore, this research paper was focusing on tourism demand forecasting by applying Box-Jenkins approach on tourists arrival data in Malaysia from 1998 until 2017. This research paper also was aiming to produce the accurate forecast values. In order to achieve that, the error of forecast for each model from Box-Jenkins approach was measured and compared by using Akaike Information Criterion (AIC), Mean Absolute Deviation (MAD), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). Model that produced the lowest error was chosen to forecast Malaysia tourism demand data. Several candidate models have been proposed during analysis but the final model selected was SARIMA (1,1,1)(1,1,4)12. It is hoped that this research will be useful in forecasting field and tourism industry.

eVisa’s impacts on travel and tourism: the case of Turkey

2018 ◽  
Vol 9 (1) ◽  
pp. 14-32 ◽  
Author(s):  
Kadir Çakar ◽  
Nadzeya Kalbaska ◽  
Ali Inanir ◽  
Tuba Şahin Ören
Keyword(s):  
Design Methodology ◽  
Psychological Perspective ◽  
Tourism Demand ◽  
Content Type ◽  
Travel And Tourism ◽  
Tourist Destinations ◽  
Travel Motivation ◽  
Positive Effects ◽  
Research Findings ◽  
Depth Interviews

Purpose The purpose of this study was to investigate eVisa applications. eVisa is a service that falls under eTourism, whose growing use can be attributed to its ability to simplify the process of obtaining a visa. The objectives of this study were twofold: to explore the eVisa experience of tourists who have previously visited Turkey by using the service and to analyse the perceptions of stakeholders who have contributed to eVisa. Design/methodology/approach The present research has utilised two methodologies within the context of qualitative research methods. Data were gathered from tourists by using reviews (n = 1690) and in-depth interviews key actors (n = 4), which represent consumers and contributors’ perspectives on the eVisa system, respectively. While consumers dictate the demand of the service, contributors control its supply. The contributors referenced herein are relevant eVisa stakeholders in Antalya. Findings The research findings revealed eVisa facilitation’s positive effects on a destination’s image and tourists’ intentions to revisit destinations compared to when they use traditional visa-obtaining processes. The research findings then present suitable data for destination managers and policymakers regarding eVisa facilitation, followed by this study’s conclusions and implications. Research limitations/implications eVisa facilitation can foster demand for travel and tourism while maintaining bureaucratic elements of the traditional visa procedure. From a psychological perspective, eVisa facilitation can positively affect travel motivation to certain destinations where eVisas are applicable, as well as positively influence intentions to revisit tourist destinations. Originality/value The originality and uniqueness of the present study lies in its contribution to the increasing recognition of the significance and positive impacts of eVisa facilitation on travel and tourism demand.

scholarly journals Effects of Terrorism and Political Instability on Tourist Behavior: 2016 conflicts in Turkey

2020 ◽  
Vol 4 (2) ◽  
pp. 21-40
Author(s):  
Onur Koyuncu
Keyword(s):  
Multivariate Regression ◽  
Design Research ◽  
Statistical Tests ◽  
Tourism Industry ◽  
Sufficient Evidence ◽  
Tourism Demand ◽  
Tourist Behavior ◽  
Tourist Destinations ◽  
Forecasting Methods ◽  
Coup Attempt

Aim: This article investigates the effects of two attacks and a failed coup attempt during 2016 on the tourist behavior. Foreign tourist data for the 2003-2019 period is analyzed to observe irregularities in Turkey’s national tourism income. Design / Research methods: Linear regression, multivariate regression and regression based static forecasting methods are applied for modeling the relationships. These models are supported with statistical tests. Conclusions / findings: Results on this study are in accordance with the current literature in the sense that conflicts in 2016 caused a shift in tourist behavior which in turn impaired the tourism industry in Turkey. Repercussions did not endure longer than expected and Turkish tourism recovered rapidly, only facing a serious loss due to the shift in tourism demand trend. Originality / value of the article: This study makes an addition to the terror and tourism literature, especially for the Mediterranean region and specifically for Turkey both of which are among the most popular tourist destinations worldwide. The aftermath of attacks and the coup attempt in Turkey during 2016 have not been researched before. The data and the outcomes presented sufficient evidence to infer on this issue.

scholarly journals Modelling and Forecasting Inbound Tourism Demand to Croatia using Artificial Neural Networks: A Comparative Study

2020 ◽  
Vol 11 (21) ◽  
pp. 55-70
Author(s):  
Murat Cuhadar
Keyword(s):  
Demand Forecasting ◽  
Tourism Industry ◽  
Percentage Error ◽  
Accurate Estimation ◽  
Tourism Demand ◽  
Tourist Flows ◽  
Ann Models ◽  
Optimal Forecasting ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Tourism demand is the basis on which all commercial decisions concerning tourism ultimately depend. Accurate estimation of tourism demand is essential for the tourism industry because it can help reduce risk and uncertainty as well as effectively provide basic information for better tourism planning. The purpose of this study is to develop the optimal forecasting model that yields the highest accuracy when compared to the forecast performances of three different methods, namely Artificial Neural Network (ANN), Exponential Smoothing, and Box-Jenkins methods for forecasting monthly inbound tourist flows to Croatia. Prior studies have been applied to forecast tourism demand to Croatia based on time series models and casual methods. However, the monthly and comparative tourism demand forecasting studies using ANNs are still limited, and this paper aims to fill this gap. The number of monthly foreign tourist arrivals to Croatia covers the period between January 2005-December 2019 data were used to build optimal forecasting models. Forecasting performances of the models were measured by Mean Absolute Percentage Error (MAPE) statistics. As a result of the experiments carried out, when compared to the forecasting performances of various models, 12 lagged ANN models, which have [4-3-1] architecture, were seen to perform best among all models applied in this study. Considering both the empirical findings obtained from this study and previous studies on tourism forecasting, it can be seen that ANN models that do not have any negativities (such as over-training, faulty architecture, etc.) produce successful forecasting results when compared with results generated by conventional statistical methods.

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