SARIMA damp trend grey forecasting model for airline industry

The aim of this paper is to propose a new model that improves the Damp Trend Grey Model (DTGM) with a dynamic seasonal damping factor to forecast routes passengers demand (pax) in the air transportation industry. The model is called the SARIMA Damp Trend Grey Forecasting Model (SDTGM). In the DTGM, the damp trend factor is a static smoothing factor because it does not change over time, and therefore, it cannot capture the dynamic behavior of time series data. For this reason, the modification consists in using the trend and seasonality effects of time series data to calculate a dynamic damp trend factor as time grows. The DTGM damping factor is based on the forecasted data obtained by the GM(1,1) model; otherwise, the SDTGM calculates a seasonal damping factor based on historical data using a large amount of data points for short lead-times. The SDTGM has less uncertainty than the DTGM. The simulation results show that the SDTGM captures the seasonality effect and does not allow the forecast to exponentially grow. The SDTGM forecasts more reasonable routes pax for short lead-times when having a large amount of data points than the DTGM. The United States domestic air transport market data are used to compare the performance of the DTGM against the proposed SDTGM.     

Tourism demand response by residents of Latin American countries

A general‐to‐specific methodology was used to build international tourism demand models by residents from Argentina, Brazil, Colombia and Venezuela to Aruba. We seek to evaluate demand parameters, especially elasticity values, which were disaggregated on a country‐to‐country basis. We also aim to learn more about the structure and important variables and investigate the process of adjustment. The study has provided new and compelling evidence that, in the short run, residents in developing countries respond rationally and substantially to economic stimulus. The short‐run income elasticity ranges from the low of 1.52 for Venezuela to the high of 2.34 for Argentina. These results indicate that Aruba will benefit differently from income increases in these four Latin American countries. The coefficients of the price variable had the expected negative signs, inelastic in the short‐run for all countries but significant at the 5% level for Venezuela only. Any deliberate effort to expand tourist arrivals will require a much larger decline in prices than would be the case in the presence of short‐run elastic response. The adjustment elasticity, being less than one, suggests that a period of more than one year is required for Latin American residents to fully adjust their tourism decisions in response to demand shocks. This study would seem to provide some useful information about international tourism demand from developing to developing countries that could form a very good and solid basis for analyses and policy action. Copyright © 2008 John Wiley & Sons, Ltd.     

Tourism,Real Effective Exchange Rate and Economic Growth: Empirical Evidence for Croatia

The aim of this paper is to examine the long‐run and short‐run relationship between tourism, real effective exchange rate and economic growth in Croatia. The econometric framework used for analysis is the Johansen Maximum Likelihood cointegration technique. For testing the stability of long‐run equilibrium relationship vector error correction model technique has been applied on a quarterly data set covering the period 1996–2013. The main findings of the paper confirm the stability of the long‐run equilibrium relationship between tourist arrivals (ARRIVAL), openness of the economy (OPEN) and real effective exchange rate as independent variable and gross domestic product (GDP) as dependent variable in Croatia. Furthermore, the results indicate short‐run causality between OPEN and GDP, as well as between real effective exchange rate and GDP. Copyright © 2014 John Wiley & Sons, Ltd.     

Temporal Granger Causality and the Dynamics Relationship Between Real Tourism Receipts,Real Income and Real Exchange Rates in Malaysia

This study applies the bounds testing approach, error‐correction modelling and persistence profile to analyse the dynamic relationship between real tourism receipts, real income and real exchange rates in Malaysia. The present study covers the annual sample period from 1974 to 2009. The results reveal that a long‐run relationship exists between the variables. In the short run, this study finds no Granger causality between real tourism receipts and real income, whereas there is bidirectional causality in the long‐run. Moreover, we also find unidirectional causality running from real exchange rates to real tourism receipts and real income in both short‐ and long‐run. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling inbound international tourism demand to Portugal

In this paper the Johansen cointegration analysis of time series is used to model the Portuguese inbound international tourism demand from five countries of origin—France, Germany, The Netherlands, Spain and UK. This approach examines the long‐run relationships between the demand for holiday visits and the variables that affect holiday travel such as income, destination prices and travel costs (airfares and road costs). Demand functions, for each country of origin, are estimated using annual data on tourism flows from 1975 to 1997. Copyright © 2002 John Wiley & Sons, Ltd.     

Time series forecasting of quarterly railroad grain carloadings

The participants in the grain logistics system need forecasts of railroad grain carloads. Although forecasting studies have been conducted for virtually every mode, no forecasting studies of quarterly railroad grain transportation have been published. The objectives of the paper are (1) specify a US quarterly railroad grain transportation forecasting model, and (2) empirically estimate the model. The selection of explanatory variables requires that they have a theoretical relationship to railroad grain transportation supply and/or demand, and that the data for the explanatory variables are published in quarterly frequency. However, there are relatively few potential explanatory variables that are published quarterly and those that are available appear to have weak correlation with quarterly railroad grain carloadings. The economic process generating quarterly railroad grain carloadings is quite complex and very difficult to model with regression techniques. Given this problem and the focus on short run forecasting, a time series model was employed to forecast quarterly railroad grain carloadings. An AR(4) model was estimated using the Maximum Likelihood estimation procedure for the 1987:4–1997:4 period. The actual railroad grain carloadings for this period were compared to the forecast carloadings generated by the time series model. For 92% of the 37 quarters the percentage difference between the actual and forecast values was 10% or less. Of the 9 annual observations, the per cent difference between the actual and forecast value was less than 2.6% for 8 of the 9 years. ©     

International tourism and economic development in South Africa: a Granger causality test

One of the major objectives of macroeconomic policies in many developing countries is sustained economic growth, and South Africa has been striving to achieve and maintain this in various ways. One of these is through international tourism. Although international tourism contributes to the growth of many economies, it is in turn, impacted by growth in many developed countries. Real gross domestic product (GDP), international tourism earnings, real effective exchange rate and exports were analysed within a multivariate vector auto regressive model using annual data covering 1980–2005. The main focus of this study therefore was to demonstrate the direction of causality between international tourism earnings and long‐run economic growth of South Africa, among other variables, using Granger causality analysis. The result obtained showed a unidirectional causality running from international tourism earnings to real GDP, both in the short run and in the long run. The error correction mechanism carried out also supported this causality. Copyright © 2009 John Wiley & Sons, Ltd.     

Air transportation demand forecast through Bagging Holt Winters methods

This paper expands the fields of application of combined Bootstrap aggregating (Bagging) and Holt Winters methods to the air transportation industry, a novelty in literature, in order to obtain more accurate demand forecasts. The methodology involves decomposing the time series into three adding components: trend, seasonal and remainder. New series are generated by resampling the Remainder component and adding back the trend and seasonal ones. The Holt Winters method is used to modelling each time series and the final forecast is obtained by aggregating the forecasts set. The approach is tested using data series from 14 countries and the results are compared with five methodology benchmarks (SARIMA, Holt Winters, ETS, Bagged.BLD.MBB.ETS and Seasonal Naive) using Symmetric Mean Absolute Percentage Error (sMAPE). The empirical results obtained with Bagging Holt Winters methods consistently outperform the benchmarks by providing forecasts that are more accurate.     

Short-term forecasting of air passenger by using hybrid seasonal decomposition and least squares support vector regression approaches

In this study, two hybrid approaches based on seasonal decomposition and least squares support vector regression (LSSVR) model are proposed for short-term forecasting of air passenger. In the formulation of the proposed hybrid approaches, the air passenger time series is first decomposed into three components: trend-cycle component, seasonal factor and irregular component. Then the LSSVR model is used to predict the components independently and these prediction results of the components are combined as an aggregated output. Empirical analysis shows that the proposed hybrid approaches are better than other time series models, indicating that they are promising tools to predict complex time series with high volatility and irregularity.     

Corruption and Tourism: An Empirical Investigation in a Non‐linear Framework

This article investigates the effect of corruption on tourism demand for a panel of countries during 1999–2009 by using panel least square and fixed effects regressions. Prior research has considered only the linear effects of corruption on tourism. We examine the relationship between corruption and tourism in a non‐linear framework after controlling for economic and heritage factors. The findings suggest that corruption has a significant effect on tourism demand and that this effect is non‐linear. Copyright © 2014 John Wiley & Sons, Ltd.     

International tourism specialisation of small countries

International tourism has expanded enormously over recent decades, fuelled by changing consumer tastes, advances in transport and new holiday destinations. The present study aims at analysing the linkages between economic growth and tourism‐based economies. An econometric model for a selected number of small countries has been implemented to investigate the nature, magnitude and overall significance of the demand for tourism. Countries were selected to capture regional diversity, differences in market orientation and a range of experiences, from emerging to long‐standing industries. The results show that tourism can be a significant engine of economic growth, when the elasticity of substitution between manufacturing goods and tourism services is < 1. Finally two stylised facts emerged, namely: (i) countries specialised in tourism register good economic performances; (ii) these same countries have small dimensions as defined by international trade theory. Copyright © 2006 John Wiley & Sons, Ltd.     

A Comparative Analysis of Three Types of Tourism Demand Forecasting Models: Individual,Linear Combination and Non‐linear Combination

This paper investigates the combination of individual forecasting models and their roles in improving forecasting accuracy and proposes two non‐linear combination forecasting models using Radial Basis Function and Support Vector Regression neural networks. These two non‐linear combination models plus the standard Multi‐layer Perceptron neural network‐based non‐linear combination model are examined and compared with the linear combination models. The UK inbound tourism quarterly arrival data is used and the empirical results demonstrate that the proposed non‐linear combination models are robust and outperform the linear combination models that currently dominate in the tourism forecasting literature. Copyright © 2013 John Wiley & Sons, Ltd.     

Rural Tourism Partnerships and Actor Mobility

In this paper, I examine actor mobility within the context of rural tourism partnerships (RTPs). The term ‘actor’ refers to those who have a stake in tourism planning, promotion and development such as policy makers, businesses, non‐profit making sector and community groups. Mobility is embedded in personal and social histories of actors as well as the policy framework that impacts their daily lives and informs their motives for being (dis)associated with RTPs. While exploring how actors' journeys transform rural localities' socio‐economic fabric, I find the writings of Lefebvre and de Certeau particularly useful because of their focus on counter‐hegemonic practices that shape the ‘everyday life’. Given that most rural societies in current times comprise an intricate mix of long‐term residents, seasonal‐home owners and migrants, each with their distinct set of life stories and value preferences with regard to their place of dwelling, my thrust in this paper on actor mobility is likely to identify new areas of future research on RTPs. Copyright © 2013 John Wiley & Sons, Ltd.     

Tourism development and environmental degradation in the United States: evidence from wavelet-based analysis

The recent literatures indicate that the tourism development (TD) has significant influence over the environmental degradation of both high-tourist-arrival and low-tourist-arrival countries. This study investigates the empirical influence of TD on environmental degradation in a high-tourist-arrival economy (i.e. United States), using the wavelet transform framework. This new methodology enables the decomposition of time-series at different time–frequencies. In this study, we have used maximal overlap discrete wavelet transform (MODWT), wavelet covariance, wavelet correlation, continuous wavelet power spectrum, wavelet coherence spectrum and wavelet-based Granger causality analysis to analyse the relationship between TD and CO₂ emission in the United States by using the monthly data from the period of 1996(1) to 2015(3). Results indicate that TD is majorly having the positive influence over CE in short, medium and long run. We find the unidirectional influence of TD on CE in short run, medium and long run in the United States.     

The Incidence of Smartphone Usage among Tourists

We explore smartphone utilization by tourists from 24 countries visiting either Rome, Italy or Athens, Greece. By extending a standard technology acceptance model, we identify common travel uses for smartphones, which include taking photos, social networking, viewing maps, finding transportation and searching for shops and restaurants. Younger cohorts utilize their phones more than older cohorts, but there is no difference in utilization between females and males. The most important factors affecting behaviour are how often the tourist normally utilizes their smartphone when at home, and whether or not the tourist has non‐WiFi data access. We conclude with recommendations for future research. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessing mainland Chinese tourists' satisfaction with Hong Kong using tourist satisfaction index

The purpose of this study is to test a two‐step tourist satisfaction index framework empirically. The first step estimates sectoral‐level satisfaction indexes based on a structural equation model, and the second obtains an overall tourist satisfaction index by conducting second‐order confirmatory factor analysis. This study is a pilot test of the theoretical framework based on three tourism‐related service sectors in Hong Kong. The results indicate that mainland Chinese tourists are most satisfied with the hotel sector in Hong Kong, followed by the retail sector, and least satisfied with local tour operators. The aggregate tourist satisfaction index is 74.04 out of 100. The results of this study have important practical implications for long‐term destination management. Copyright © 2010 John Wiley & Sons, Ltd.     

A theoretical model of mobile augmented reality acceptance in urban heritage tourism

Latest mobile technologies have revolutionized the way people experience their environment. Recent research explored the opportunities of using augmented reality (AR) in order to enhance user experience; however, there is only limited research on users’ acceptance of AR in the tourism context. The technology acceptance model is the predominant theory for researching technology acceptance. Previous researchers used the approach of proposing external dimensions based on the secondary literature; however, they missed the opportunity to integrate context-specific dimensions. This paper therefore aims to propose an AR acceptance model in the context of urban heritage tourism. Five focus groups, with young British female tourists visiting Dublin and experiencing a mobile AR application, were conducted. The data were analysed using thematic analysis and revealed seven dimensions that should be incorporated into AR acceptance research, including information quality, system quality, costs of use, recommendations, personal innovativeness and risk as well as facilitating conditions.     

基于傅里叶级数的铁路客运量预测研究

基于傅里叶级数预测模型,以我国2004—2009年铁路客运量为数据基础,通过将时间序列划分为趋势性与季节性部分,分别采用最小二乘法与傅里叶级数法对两者进行拟合,应用Matlab软件编程,求出预测模型,并进行客运量预测。通过对预测结果的误差分析,结果表明:采用傅里叶级数预测法预测我国铁路客运量的效果较好。     

Guidebook use by Japanese tourists: a qualitative study of Australia inbound travellers

This qualitative investigation into guidebook use reports on in‐depth interviews conducted with 26 Japanese individuals and one couple who had visited Australia during the five previous years. Focusing on the stages before, during and after travel the research framework was based on Vogt and Fesenmaier's model of information needs. It was found that functional needs were the dominant influences during the prior to travel phase, with some non‐functional needs (hedonic, aesthetic and innovation) also being influential. During the travel phase, only functional needs were evident. Some respondents were identified as being deliberate non‐users of guidebooks. The variable ‘tourist type’ was found to be helpful for distinguishing between users and non‐users and for identifying those with functional needs. The use of guidebooks by those whose needs are both functional and non‐functional may be unaffected by this variable. When the attitudes of those who actively dislike guidebooks and those who hesitate to use them are aggregated, a view emerges of guidebooks as a symbol of standardised tourism. Copyright © 2006 John Wiley & Sons, Ltd.