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1
Witt, Stephen F., and Christine A. Martin. "Econometric Models for Forecasting International Tourism Demand." Journal of Travel Research 25, no. 3 (January 1987): 23–30. http://dx.doi.org/10.1177/004728758702500306.
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Тураев and B. Turaev. "Econometric Models for Tourism Management System Improvement." Economics 2, no. 6 (December 17, 2014): 40–46. http://dx.doi.org/10.12737/6733.
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Role and value of tourism as a factor for impact on economy are considered in this paper. Prerequisites and conditions promoting its development have been revealed. The need in development and implementation of data (including forecast data) in the frame of national economy complex evolution has been justified. The main dynamic and structural tendencies of tourism regional market development, using Uzbekistan as an example, with elements of comparative analysis related to similar indicators of tourism development at the level of world, national and regional economy are investigated in this paper as well. Proceeding from this analysis, recommendations on the tourist services market development have been given.
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Song, Haiyan, Stephen F. Witt, and Thomas C. Jensen. "Tourism forecasting: accuracy of alternative econometric models." International Journal of Forecasting 19, no. 1 (January 2003): 123–41. http://dx.doi.org/10.1016/s0169-2070(01)00134-0.
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Lim, Christine. "An Econometric Classification and Review of International Tourism Demand Models." Tourism Economics 3, no. 1 (March 1997): 69–81. http://dx.doi.org/10.1177/135481669700300105.
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The purpose of the paper is to provide an econometric classification and evaluation of 100 published empirical studies on modelling international tourism demand, according to the recognition and type of omitted explanatory variables, number and type of proxy variables used, method of estimation, and use of various diagnostic tests of the auxiliary assumptions of the various models. An analysis of the adequacy of model specifications and the statistical deficiencies of existing empirical tourism demand models will permit a greater appreciation of the factors which determine changes in international tourism demand and will aid in forecasting future tourism demand.
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Jiao, Eden Xiaoying, and Jason Li Chen. "Tourism forecasting: A review of methodological developments over the last decade." Tourism Economics 25, no. 3 (November 26, 2018): 469–92. http://dx.doi.org/10.1177/1354816618812588.
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This study reviewed 72 studies in tourism demand forecasting during the period from 2008 to 2017. Forecasting models are reviewed in three categories: econometric, time series and artificial intelligence (AI) models. Econometric and time series models that have already been widely used before 2007 remained their popularity and were more often used as benchmark models for forecasting performance evaluation and comparison with respect to new models. AI models are rapidly developed in the past decade and hybrid AI models are becoming a new trend. And some new trends with regard to the three categories of models have been identified, including mixed frequency, spatial regression and combination and hybrid models. Different combination components and combination techniques have been discussed. Results in different studies proved superiority of combination forecasts over average single forecasts performance.
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Abdou, Musonera, Edouard Musabanganji, and Herman Musahara. "Tourism Demand Modelling and Forecasting: A Review of Literature." African Journal of Hospitality, Tourism and Leisure 10(4), no. 10(4) (August 31, 2021): 1370–93. http://dx.doi.org/10.46222/ajhtl.19770720.168.
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This research examines 145 key papers from 1979 to 2020 in order to gain a better sense of how tourism demand forecasting techniques have changed over time. The three types of forecasting models are econometric, time series, and artificial intelligence (AI) models. Econometric and time series models that were already popular in 2005 maintained their popularity, and were increasingly used as benchmark models for forecasting performance assessment and comparison with new models. In the last decade, AI models have advanced at an incredible rate, with hybrid AI models emerging as a new trend. In addition, some new developments in the three categories of models, such as mixed frequency, spatial regression, and combination and hybrid models have been introduced. The main conclusions drawn from historical comparisons forecasting methods are that forecasting models have become more diverse, that these models have been merged, and that forecasting accuracy has improved. Given the complexities of predicting tourism demand, there is no single approach that works well in all circumstances, and forecasting techniques are still evolving.
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Baltas, George. "Econometric Models for Discrete Choice Analysis of Travel and Tourism Demand." Journal of Travel & Tourism Marketing 21, no. 4 (August 15, 2007): 25–40. http://dx.doi.org/10.1300/j073v21n04_04.
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Gričar, Sergej. "IMPLEMENTATION OF VECTOR AUTO-REGRESSION MODELS IN TOURISM: STATE OF THE ART ANALYSIS AND FURTHER DEVELOPMENT." Tourism and hospitality management 28, no. 3 (December 2022): 707–9. http://dx.doi.org/10.20867/thm.28.3.16.
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Purpose The dissertation focuses on time series analysis and is based on several research strategies and methods. The methodology used in the research process was published in four papers as part of international scientific journals indexed in the Web of Science database. Since tourism is one of the most lagged industries in science there is need for new and innovative approaches in key tourist sector determinants modelling and forecasting. This doctoral thesis introduces an extension of time series methodology that focuses on investigating and testing the normal distribution of residuals, as a key adequacy prerequisite of econometric models. This issue has not systematically been considered in quantitative approaches in tourism. The motivation for research of the doctoral thesis are multidimensional: to filter previous research on time series in tourism and to theoretically and empirically improve and redesign time series methodology and methods for tourism. Both issues were successfully presented in one of the published papers. Finally, tourism forecasts should be based on reliable models as evident, from the most recent shocks, ex-ante tourism forecasting has to be considered crucial in evaluating model efficiency. The dissertation aimed to research and develop appropriate econometric models able to capture the specifics of multiple interactions in the tourism market. The research seeks to develop econometric models for the Republics of Slovenia and Croatia, two countries whose economic development is predicated on tourism. Four goals and four specific objectives have been specified during the research process: 1) To introduce an improved time series approach in cointegrated panels. The first specific objective (SO1) is to test at least ten econometric modelling structures that reduce cycle breaks. 2) To examine previous theoretical thinking regarding the cointegration of time series, cross-sectional data, and panels. The second specific objective (SO2) is to outline at least 250 previous empirical studies for the tourism industry. 3) To examine cointegration in tourism data for Slovenia and Croatia. The third objective (SO3) is to model at least three econometric time series equations and mathematical theorems/ lemmas for the tourism industry. 4) To improve and better understand unit root tests in tourism. The specific objective (SO4) is to approach the design of at least three stable and innovative models. Methodology The research relies upon econometric modelling in time series and panels as well as misspecification tests implementation. The study is primarily oriented to the hypotheses testing on a reliable modelling procedure. The research methodology is based on time series and the vector autoregression model (VAR) implementation. Moreover, the cointegrated VAR and the error correction model (ECM) are used. The Granger causality is used to identify trends to determine the direction of the hypothesised research problems. Overall, the study uses regression analysis and summary descriptive statistics. The sensitive analysis relies on panel regression. Summarizing, the added value of the doctoral thesis can be reflected in investigating the normal distribution of time series residuals to obtain accurate results for interpretation and prediction. Findings The most significant research results include time series and panel testing and modelling based on research hypotheses. The main hypothesis (an innovative approach to cointegration, based on empirical evidence for Slovenia and Croatia, which provides unbiased, accurate and validated results for tourism development) was confirmed. The first published paper investigates the possibility and accuracy of using time series data in forecasting tourism demands. The theoretical added value provides ex-ante research results regarding the consequences of the most recent pandemic. The empirical part of the paper discusses the direction of daily Slovenian and Croatian COVID-19 infections and tourist arrivals. Hypothesis 1 the tourism industry in Slovenia has developed rapidly and is expected to continue growing in a positive and sustainable direction without seasonal fluctuation, and 2, the tourism industry in Croatia has a long tradition and opportunity to grow at unprecedented rates hitherto. Volatility in the Croatian tourism industry is significant and has a high standard deviation; were confirmed. Additionally, the modelling strategy was introduced in one of the published papers. The results emphasized a significant influence on tourism demand and, depending on the modelling methodology, the existence of an impact on tourist arrivals of chosen determinants. Moreover, two published papers discussed the direction of economic impacts on tourist arrivals and vice versa. The decisive significance of productivity to real gross wages with a rise in tourist arrivals was confirmed. Furthermore, prices in tourism based on short-run effects and two cointegrated relations were modelled and forecasted. It can be concluded that tourism demand, approximated by tourist arrivals, is volatile on different determinants which were previously not researched or tested by reliable econometrics. Therefore, the set goals and specific study objectives were achieved.
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Saleh, Mohammad H., Adnan Turki Garaibeh, Ali Shehadeh, and Jamil J. Jaber. "The Role of Tourism Activity in Economic Growth by Using Some Econometric Models Evidence from Jordan." Modern Applied Science 13, no. 6 (May 23, 2019): 1. http://dx.doi.org/10.5539/mas.v13n6p1.
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Tourism is used as a vital strategy to reach greater economic productivity. The aim of this paper is to investigate the dynamic relationship between touruism growth and economic growth, using annual time series data from Jordan over the period (1990-2016). The study used a variety of methods based on the cobb-Douglus production function, the Koyck geometrical lag model, cointegration analysis, error correction model and causality analysis. We reveal if tourism leads to economic growth or growth leads to tourism development or bidirectional relation exists between two variables. According to the results, there are moderately increasing return to scale in tourism sector. In addition to there is a positive long-term equilibrium relation related to growth with both fixed assets and tourism balance. The results of the Granger causality test have demonstrated the unidirectional hypothesis, where tourism development leads to economic growth. This paper presented a set of suggestions that would improve Jordan's competitiveness in tourism.
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Liu, Han, Ying Liu, Yonglian Wang, and Changchun Pan. "Hot topics and emerging trends in tourism forecasting research: A scientometric review." Tourism Economics 25, no. 3 (November 4, 2018): 448–68. http://dx.doi.org/10.1177/1354816618810564.
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Tourism forecasting has been a focal point of tourism research over the past few decades as a result of the corresponding rapid development and expansion of the tourism industry. A bibliometric analysis, based on 543 articles retrieved from the Web of Science Core Collection database, was carried out to provide insights into hot topics as well as emerging trends in tourism forecasting research. The results show that the research outputs related to tourism forecasting have grown rapidly since 2006. The observed hot topics in tourism forecasting were to predict tourism demand via various models, including time series models, econometric models, and artificial intelligence-based methods, and to compare the forecasting accuracy of models. An emerging trend of tourism forecasting is to use methods based on data from a web-based search engine. Our study provides insights and valuable information for researchers to identify new perspectives on hot topics and research frontiers.
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Wong, Kevin KF. "An Investigation of the Time Series Behaviour of International Tourist Arrivals." Tourism Economics 3, no. 2 (June 1997): 185–99. http://dx.doi.org/10.1177/135481669700300205.
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Most tourism econometric models are based on conventional least squares estimation, which assumes stationarity in their data generating mechanism. However, they fail to recognize the implications of the integrated properties of the historical time series of tourism data. Such time series properties may have important consequences with regard to the theoretical implication and interpretation of these tourism models. In this paper, historical data on international tourist arrivals from six major regions and seventeen individual countries are analysed to determine whether the series is better characterized by a stationary or non-stationary type process. Based on unit root tests, the results in most cases indicate that international tourist arrivals exhibit a non-stationary stochastic process that has the tendency to fluctuate away from a given initial state as time passes. These findings imply that studies which conveniently draw standard inferences from ordinary least squares estimated tourism models based on the levels of international tourist arrivals can be very misleading since non-stationarity in the data will produce inconsistent parameter estimators and unreliable test statistics. Furthermore, model misspecification that arises from unrelated integrated series can seriously bias conventional significance tests towards the acceptance of an apparently significant relationship. In this preliminary investigation, we conclude that econometric tourism models that focus on the levels of international tourist arrivals may not be reliable since the series is non-stationary and is integrated of order one, I(1).
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Ivanov, Stanislav, and Craig Webster. "Measuring the Impact of Tourism on Economic Growth." Tourism Economics 13, no. 3 (September 2007): 379–88. http://dx.doi.org/10.5367/000000007781497773.
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This paper presents a methodology for measuring the contribution of tourism to an economy's growth, which is tested with data for Cyprus, Greece and Spain. The authors use the growth of real GDP per capita as a measure of economic growth and disaggregate it into economic growth generated by tourism and economic growth generated by other industries. The methodology is compared with other existing methodologies; namely, Tourism Satellite Account, Computable General Equilibrium models and econometric modelling of economic growth.
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Lee, Jin-Hee, Jong-hoon Park, and Kwang-Eik Cho. "Analysis of the Determinants of International Inbound Tourism Demand: Application of Econometric Models." Journal of Tourism and Leisure Research 30, no. 12 (December 31, 2018): 143–59. http://dx.doi.org/10.31336/jtlr.2018.12.30.12.143.
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Blažević, Branko. "The strategy of destination development." Tourism and hospitality management 4, no. 2 (December 1998): 263–71. http://dx.doi.org/10.20867/thm.4.2.1.
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The author studies the approach to the conception, strategy and aim of the long-termed tourism destination development and concludes that this expectations are based on historical data. These are so called "adaptive expectations" which are not applicative in the development approach, but they are covered with mathematics - econometric models present in numerous studies about the development of the city and the County towards the national level (as tourism destination).
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Yang, Yixing, Md Qamruzzaman, Mohd Ziaur Rehman, and Salma Karim. "Do Tourism and Institutional Quality Asymmetrically Effects on FDI Sustainability in BIMSTEC Countries: An Application of ARDL, CS-ARDL, NARDL, and Asymmetric Causality Test." Sustainability 13, no. 17 (September 6, 2021): 9989. http://dx.doi.org/10.3390/su13179989.
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The motivation of the study is to investigate the nature of the relationship between institutional quality, tourism, and FDI in BIMSTEC nations for the period 1996Q1–2018Q4. Exploring their nature of association, the study performed several panel econometric models, namely Panel ARDL, Nonlinear ARDL, and Toda-Yamamoto causality test, with symmetric and asymmetric effects of institutional quality and tourism. The results of the Wald test confirmed the long-run asymmetric relationship between institutional quality, tourism, and FDI, both in the long-run and short-run. Furthermore, directional casualty established a feedback hypothesis explaining the relationship between institutional quality, tourism, and FDI.
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Bi, Chao, and Jingjing Zeng. "Nonlinear and Spatial Effects of Tourism on Carbon Emissions in China: A Spatial Econometric Approach." International Journal of Environmental Research and Public Health 16, no. 18 (September 11, 2019): 3353. http://dx.doi.org/10.3390/ijerph16183353.
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Reducing carbon emissions is crucial to the sustainable development of tourism. However, there are no consistent conclusions about the nexus between tourism and carbon emissions. Considering the possible nonlinear and spatial effects of tourism on carbon emissions, this paper employed spatial econometric models combined with quadratic terms of explanatory variables to explore the nexus between them using Chinese provincial panel data from 2003 to 2016. The main results are as follows: (1) There is a significant inverse U-shaped relationship between tourism development and carbon emissions. In the provinces whose tourism receipts are relatively low, the effects of tourism on carbon emissions are positive but decrease gradually as the tourism receipts increase and then shifts to negative and continues decreasing gradually when the tourism receipts beyond the critical value. (2) For the geographical proximity and industrial relevance, one province’s tourism development not only affects its carbon emissions but also affects its neighbors’ carbon emissions through spatial lag effect (indirect effect) which is also inverse U-shaped. (3) Carbon reduction policies, sustainable education, and transportation infrastructure all have significant moderating effects on the relationship between tourism and carbon emissions, but the moderating effect of the management efficiency of tourism is not statistically significant. Furthermore, improvements to the sustainable education and transportation infrastructure not only strengthen the direct negative effect of tourism on carbon emissions but also strengthen the indirect negative effect of tourism on carbon emissions. This study not only advances the existing literature but is also of considerable interest to policymakers.
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Lee, SoYeun, MinChul Youn, and HakJun Song. "The Determinants of Bi-national Tourism Demand from Russia to Korea - Using Econometric Models -." Journal of Tourism and Leisure Research 30, no. 5 (May 31, 2018): 5–20. http://dx.doi.org/10.31336/jtlr.2018.05.30.5.5.
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Provenzano, Davide. "The migration–tourism nexus in the EU28." Tourism Economics 26, no. 8 (March 10, 2020): 1374–93. http://dx.doi.org/10.1177/1354816620909994.
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This study explores the nexus between tourism and migration on an intra-European scale over the period 2000–2015. Complex-network analysis and gravity models were the investigation methods preferred. For each year under study, we built two country-to-country networks to map and reveal the connections between states as shaped by migration stocks and tourism flows, respectively. Then, the main determinants of the correlation patterns between the two networks were investigated by several econometric analysis. Results point to a quite similar topological structure for the tourism and migration networks as well as to a significant and reciprocal direct influence between tourism and migration movements inside the European Union. No relevant indirect causal relationship is present in the tourism–migration nexus instead.
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Svetlana V. Doroshenko Ksenia A. Posysoeva, Svetlana V. Doroshenko Ksenia A. Posysoeva, and Svetlana V. Doroshenko Ksenia A. Posysoeva Svetlana V. Doroshenko Ksenia A. Posysoeva. "Econometric Estimation of Strategic Development Factors of Russian Border Regions." Economy of Region 17, no. 2 (June 2021): 431–44. http://dx.doi.org/10.17059/ekon.reg.2021-2-6.
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Cross-border development is significantly influenced by global events, such as 1990s transformations, when different inland areas across the world became borderlands. Further, due to 2014 geopolitical changes, the Russian Federation had to establish a new institutional framework regulating the border regional development. The research aims to assess the impact of strategic factors on socio-economic development of these regions. For that purpose, we analysed 47 of 50 Russian border entities divided into two groups of old and new (established after the collapse of the USSR in 1991) border regions. We hypothesise that the factors considered as strategic in these territories manifest differently in old and new border regions. Empirical data, obtained from the Federal State Statistics Service and Unified Interdepartmental Statistical Information System, cover the period from 2000 to 2018. The simulation was conducted using the statistical package Stata 14. We analysed five groups of factors (transport infra- structure, small business, foreign trade, tourism, ecology) as well as corresponding indicators. Gross regional product per capita in comparable prices of 2018 was considered as a dependent variable. Then, we assessed three models explaining the impact of the examined factors on old and new border regions individually and in combination. For each model, pooled regression, as well as random and fixed effects models were constructed. Conducted simulations revealed that the fixed effects models best describe the analysed data. The research results confirmed the hypothesis, showing that transport infrastructure and tourism are more important for new border regions, while the factors of ecology, small business and foreign trade have a greater impact on the development of old borderlands.
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Hsu, Maxwell K., Junzhou Zhang, and Yamin Ahmad. "Government digital information discovery and exploration: the case of unraveling tourism-led-growth paradox in China." Information Discovery and Delivery 45, no. 4 (November 20, 2017): 212–19. http://dx.doi.org/10.1108/idd-10-2016-0036.
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Purpose This study aims to examine the relationship between tourism development and economic growth while considering exports simultaneously. Governments in many countries have been developing and deploying strategies to attract tourism receipts as a means for economic growth. However, assessing the potential impact of tourism on economic growth among large economies is still in its infancy. Design/methodology/approach Using a vector error correction model framework, this study examines the relationship among exports, gross domestic product (GDP) and tourism receipts (including international tourism receipts and domestic tourism receipts in two separate models) with macro data that covers two recent decades (1994-2013) in China. Findings The empirical findings confirm the existence of a long-term equilibrium relationship in each of these two tri-variate models. The empirical findings reveal that (1) both tourism-led-growth and export-led-growth hypotheses are supported, (2) the growth rate of tourism receipts exhibit a higher relevance with GDP growth than export growth and (3) the growth rate of international tourism shows a higher relevance with GDP growth than domestic tourism growth. Originality/value Using macroeconomic data collected by the Chinese government, the current study employs an advanced econometric methodology to explore the potential benefits of tourism on economic growth in China.
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Ribeiro, Luiz Carlos De Santana, Thiago Henrique Carneiro Rios Lopes, Rosa Lívia Gonçalves Montenegro, and José Roberto De Lima Andrade. "Employment dynamics in the Brazilian tourism sector (2006–2015)." Tourism Economics 24, no. 4 (November 6, 2017): 418–33. http://dx.doi.org/10.1177/1354816617736409.
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Tourism is recognized as an activity with great potential for Brazil, not only because of its diverse tourist attractions but also because of the generation of economic dynamics and its capacity to absorb labour. This article investigates the influence of specialization, urbanization and diversification externalities on the tourism employment growth rate in Brazilian municipalities between 2006 and 2015. To this end, we apply Local Indicators of Spatial Association and spatial econometric models. Both techniques enable the visualization of a spatial and temporal overview of the convergence process in tourism employment in Brazil. The main results suggest that the externalities of specialization, urbanization and diversification positively affect the employment growth rate in the tourism sector. Nevertheless, the employment growth rate for tourism in neighbouring municipalities reduces local employment in the same sector, which we interpret as arising from a competitive effect.
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Novitri, Qorina, Junaidi Junaidi, and Muhammad Safri. "Determinan Penerimaan Daerah dari Sektor Pariwisata di Kabupaten/Kota Provinsi Jambi." Jurnal Perspektif Pembiayaan dan Pembangunan Daerah 1, no. 3 (January 1, 2014): 149. http://dx.doi.org/10.22437/ppd.v1i3.1548.
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The purpose of this study was to analyze whether the number of hotel room occupancy rate, the GDP of the tourism sector, the number of restaurants and eating houses, the average length of stay, and number of tourists influence the reception area of the tourism sector in the District / City of Jambi Province. The analysis used in this study is the analysis of growth, econometric analysis using panel data models, and analysis of barriers and opportunities. The results showed that simultaneous number of hotel room occupancy rate, the GDP of the tourism sector, the number of restaurants and eating houses, the average length of stay, and number of travelers significant effect on local revenues from the tourism sector in the District / City of Jambi Province. Keywords: Regional Revenues from the tourism sector, Total Room Occupancy Rate, GDP Tourism Sector, Total Restaurant and Eating, Average Length of Stay
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Ding, Rijia, and Meng Huang. "The Spatial Difference of “Internet plus Tourism” in Promoting Economic Growth." Sustainability 13, no. 21 (October 25, 2021): 11788. http://dx.doi.org/10.3390/su132111788.
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The “Internet plus Tourism” mode, which is the coordination of the internet and tourism, has become a new driving force for regional economic growth. In order to investigate the mechanism and superiority of “Internet plus Tourism” in terms of economic growth compared with the independent effects of the internet and tourism on economic growth, this paper uses the DEA model to calculate the tourism efficiency of 30 provinces in China from 2011 to 2019 and three spatial econometric models to comparatively analyze the independent effects of the internet and tourism with the synergized effect of “Internet plus Tourism” on economic growth. The results show that (1) the overall pattern of the internet is that coastal areas are ranked higher; (2) tourism efficiency presents a polarized hierarchical structure; (3) The effect of “Internet plus Tourism” on economic growth is significantly positive and is significantly greater than the independent effects of the internet and tourism on economic growth; (4) the internet, tourism, and “Internet plus Tourism” have different effects on economic growth in different regions. Therefore, the paper suggests that China should accelerate the integration of “Internet plus Tourism” and realize sustainable economic development.
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Liu, Jun, Mengting Yue, Fan Yu, and Yun Tong. "The contribution of tourism mobility to tourism economic growth in China." PLOS ONE 17, no. 10 (October 27, 2022): e0275605. http://dx.doi.org/10.1371/journal.pone.0275605.
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Mobility is the key factor in promoting tourism economic growth (TEG), and the transportation infrastructure has essential functions for maintaining an orderly flow of tourists. Based on the theory of fluid mechanics, we put forward the indicator of tourism mobility (TM). This study is the first to measure the level of TM in China and analyze the spatiotemporal evolution characteristics of TM. Applying the Exploratory Spatial Data Analysis method, we analyze the global and local spatial correlation characteristics of TM. Moreover, we further estimate the contribution of TM to TEG by econometric models and the LMDI method. The results show that (1) the TM in China has maintained rapid growth for a long time. However, there are differences in the rate of growth in different regions. The TM in each region only showed a significant positive spatial correlation in 2016–2018. The space-time pattern is constantly changing over time. The local spatial autocorrelation results of TM are stable, and various agglomeration states are stably distributed in some provinces. (2) The regression results of the traditional panel data model and spatial panel data model both show that TM has a significant positive effect on TEG. Moreover, TM has a negative spatial spillover effect on neighboring regions. (3) The result from the decomposition of LMDI shows that the overall contribution of TM to TEG is 15.76%. This shows that improving TM is a crucial way to promote the economic growth of tourism.
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Pereira, José, Mário Basto, and Amélia Silva. "Comparing logit model with discriminant analysis for predicting bankruptcy in Portuguese hospitality sector." European Journal of Tourism Research 16 (July 1, 2017): 276–80. http://dx.doi.org/10.54055/ejtr.v16i.289.
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Portugal’s tourism sector is on permanent expansion and contributes significantly to the Portuguese economy. However, it has been facing the problem of business failure. The main goal of this paper is to develop an econometric and a multivariate model for forecasting business failure in the hospitality industry using logit and discriminant analysis. The present paper does not explore the causes of business failure but rather aims to propose a model that may help anticipate failure, so that decision makers can minimize the negative effects of this phenomenon. The results confirm that the models for forecasting business failure contribute positively to setting macroeconomic policies and tourism development support programs and are relevant for investors, stockholders, and decision makers.
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Shah, Imtiyaz Ahmad, and Imtiyaz ul Haq. "The Impact of Tourism Development and Economic Growth on Poverty Reduction in Kazakhstan." Acta Universitatis Sapientiae, Economics and Business 10, no. 1 (September 1, 2022): 77–90. http://dx.doi.org/10.2478/auseb-2022-0005.
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Abstract The paper examines the long-run relationship between poverty reduction, economic growth, and tourism development in Kazakhstan during the period of 2001–2017. We expand the basic model by including other poverty determinants such as inequality, unemployment, and spending on health. We use the Autoregressive Distributed Lag (ARDL) approach to test the co-integration of variables, as the ARDL bound test of co-integration is less restrictive and provides more reliable coefficients than other time series econometric models. The ARDL bound test results show that there exists a long-run relationship between the said variables. The coefficients of all variables have the expected signs in the long run.
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Sharma, Himanshu, and Anu G. Aggarwal. "What factors determine reviewer credibility?" Kybernetes 49, no. 10 (November 18, 2019): 2547–67. http://dx.doi.org/10.1108/k-08-2019-0537.
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Purpose The experiential nature of travel and tourism services has popularized the importance of electronic word-of-mouth (EWOM) among potential customers. EWOM has a significant influence on hotel booking intention of customers as they tend to trust EWOM more than the messages spread by marketers. Amid abundant reviews available online, it becomes difficult for travelers to identify the most significant ones. This questions the credibility of reviewers as various online businesses allow reviewers to post their feedback using nickname or email address rather than using real name, photo or other personal information. Therefore, this study aims to determine the factors leading to reviewer credibility. Design/methodology/approach The paper proposes an econometric model to determine the variables that affect the reviewer’s credibility in the hospitality and tourism sector. The proposed model uses quantifiable variables of reviewers and reviews to estimate reviewer credibility, defined in terms of proportion of number of helpful votes received by a reviewer to the number of total reviews written by him. This covers both aspects of source credibility i.e. trustworthiness and expertness. The authors have used the data set of TripAdvisor.com to validate the models. Findings Regression analysis significantly validated the econometric models proposed here. To check the predictive efficiency of the models, predictive modeling using five commonly used classifiers such as random forest (RF), linear discriminant analysis, k-nearest neighbor, decision tree and support vector machine is performed. RF gave the best accuracy for the overall model. Practical implications The findings of this research paper suggest various implications for hoteliers and managers to help retain credible reviewers in the online travel community. This will help them to achieve long term relationships with the clients and increase their trust in the brand. Originality/value To the best of authors’ knowledge, this study performs an econometric modeling approach to find determinants of reviewer credibility, not conducted in previous studies. Moreover, the study contracts from earlier works by considering it to be an endogenous variable, rather than an exogenous one.
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Moraru, Andreea-Daniela, Cristina Duhnea, Alina Barbulescu, Mariana Juganaru, and Ion-Danut Juganaru. "Residents’ Attitude toward Tourism—Do the Benefits Outweigh the Downsides? The Case of Constanta, Romania." Sustainability 13, no. 2 (January 17, 2021): 882. http://dx.doi.org/10.3390/su13020882.
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While the positive economic impact of tourism cannot be denied, it has also a number of negative side effects. The article focuses on the residents’ perception regarding the tourist activity and on identifying the factors influencing their acceptance for the tourist activity, in Constanta (Romania). A questionnaire based quantitative research was employed, creating several indexes, subsequently included in econometric models in order to reveal the factors which determine residents’ acceptance and support for tourism. The results reveal that residents are highly in favour of tourism activity and support tourism expansion and further development. Most respondents considered that tourism contributed to the improvement of the city image and identified a fairly positive economic impact, while tourism was accountable for the increase in several negative phenomena. The impact of tourist activity on the sustainable development of the city was perceived as medium positive, while most respondents considered that the number of tourists should increase. The residents’ acceptability toward tourism was revealed to depend on several variables and computed indexes: city development index, impact on residents’ quality of life index, sustainable development index, and perceived intensity of contact with tourists.
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Bigović, Miloš. "Demand forecasting within Montenegrin tourism using Box-Jenkins methodology for seasonal ARIMA models." Tourism and hospitality management 18, no. 1 (June 2012): 1–18. http://dx.doi.org/10.20867/thm.18.1.1.
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The purpose of this paper is to construct adequate seasonal ARIMA models, using Box-Jenkins methodology, and to implement them in order to forecast short run flows of tourist arrivals and tourist overnight stays in Montenegro. Time scope covers ten years, from 2001/01 to 2010/12, while twelve months of 2011 are out-of-sample forecasts. Close inspection of related time series was applied which revealed no extreme and unusual specificities in the data. Therefore, only economic impacts have been affected the time series. This was important because econometric intervention analysis was excluded from models designing and building. As a result, our approach was based on time series modelling without need to take care of any structural breaks. Modified Box-Pierce and Jarque-Bera test statistics confirmed good quality of the models. Further, the results show excellent forecasting performances of specified models. According to forecasting output, Montenegro can expect upgrowth in terms of tourist arrivals as well as in terms of tourist overnight stays. The model has shown around 7,25% rise in arrivals, which is about 91 thousands tourists more in 2011 compared with the previous year. On the other hand, the calculated rise of overnight stays is around 8,42%, or about 670 thousands more than the year before.
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Ferrai, Guido, José Mondéjar Jiménez, and Yanyun Zhao. "The statistical information for tourism economics. The National Accounts perspective." National Accounting Review 4, no. 2 (2022): 204–17. http://dx.doi.org/10.3934/nar.2022012.
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<abstract> <p>Statistical information strengthening in tourism sector is recommended by the United Nations World Tourism Organization (UNWTO). Economic-statistical information is basic for carrying out effective quantitative economic analysis of tourism. Tourism Satellite Account (TSA) is not a suitable source of information for econometric analysis. National Accounts (NA), in the form of Input-Output (I-O) Tables, Computable General Equilibrium (CGE) models or Social Accounting Matrices (SAMs) represent a good source of economic-statistical information and of economic impact analysis. This paper shows how it is appropriate to focus on the definition of tourists and tourism enterprises, overcoming the uncertainties and distortions in the analyses and results that the current leaning on a generic definition of tourism entails. Furthermore, it is argued that the best impact analysis can be conducted through the use of a SAM, which in addition to being structurally consistent with the choice of defining and implementing tourists and tourist enterprises, confirming its usefulness, allows to analyse fully and, from a theoretical point of view, more correctly than I-O Tables and CGE models, the impact of inbound tourism expenditure on production structure represented by branches, on factors and therefore on GVA/GDP produced by the branches themselves and on households expenditure. Furthermore, the suggested approach offers actual possibilities for assessing the economic sustainability of tourism development. Regional and national impact analyses carried out with the use of SAMs confirm the positions claimed in the paper.</p> </abstract>
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Park, Deukhee, Sanghoon Kang, and Gyehee Lee. "Demand forecasting of Japanese tourists to Korea for sustainable tourism growth : An application of time-series econometric models." International Journal of Tourism and Hospitality Research 34, no. 3 (March 31, 2020): 47–60. http://dx.doi.org/10.21298/ijthr.2020.3.34.3.47.
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KOSOVA, Robert, and Valentina SINAJ. "Mathematical Modeling of Tourism Development. An Application to Albanian Tourism." Journal of Environmental Management and Tourism 12, no. 6 (September 30, 2021): 1707. http://dx.doi.org/10.14505//jemt.v12.6(54).26.
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The article contains a comprehensive study of tourist arrivals in Albania in the years 1994 to 2020. During this period, the trend of tourism development has been studied, using the widely approved concept of Tourist Area Cycle Theory (TALC). During these years, the number of tourists has been growing rapidly, and, the touristic sites of Albania have been transformed to serve touristic purposes, especially the coastline. Recently the geographic touristic map has been enlarged to the mountain and rural areas, touristic villages, and cultural, archaeological, historical tourism. The dynamics of tourism development have been studied by many researchers, academics, and institutions to provide a complete and clear picture of the history and predict the future of the tourism industry. Econometric, mathematical or mixed models are applied to fit the tourism development and they have been helpful and have served the purpose. The model we have used to analyze the arrivals in Albania is the Logistical and the Gompertz model, largely used to estimate growth under limited resources. The tourist arrivals, i.e., the number of tourists entering the destination country have been considered as the most important variable to describe the tourism development. Several useful software is mostly used to fit the historical data and predict future arrivals such as Stata, Lab fit, Curve Expert, Spss, etc. In our case the Stata software to run the data provided for this article. The data for this article are provided from INSTAT (National Institute of Statistics), (http://www.instat.gov.al/) and other National Institutions such as the Ministry of Tourism and Environment of Albania, (https://turizmi.gov.al/), and several International Institutional such as the World Bank, (https://data.worldbank.org/indicator/ST.INT.ARVL?locations=AL), World Tourism Organization, (https://www.unwto.org/statistic/basic-tourism-statistics). The data, together with the growing numbers of tourists show the significant impact of tourism on the economic development of the country, income, contribution to the Gross Domestic Product (GDP), employment, etc.
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Deng, Taotao, and Yukun Hu. "Modelling China’s outbound tourist flow to the ‘Silk Road’: A spatial econometric approach." Tourism Economics 25, no. 8 (November 4, 2018): 1167–81. http://dx.doi.org/10.1177/1354816618809763.
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With the ancient Silk Road as the historical background, the ‘Belt and Road’ initiative aims to foster common development of regional economies. Regional tourism development is an essential part of the initiative. Taking 55 countries participating in the initiative as a research sample, the article investigates the determinants and spillover effect of Chinese outbound tourist flows by spatial panel models. Furthermore, we identify different spillover paths from the perspectives of geographic and cultural proximities. The results confirm that there exist significant positive spillover effects in tourist flows among countries with geographic proximity. Meanwhile, there exist significant positive spillover effects in tourist flows among countries with cultural proximity. In addition, geographic and cultural distances between China and tourist destinations have negative impacts on Chinese outbound tourist flow.
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Mazaraki, Anatoliy, Margaryta Boiko, Alla Okhrimenko, Svitlana Melnychenko, and Tetiana Zubko. "The impact of the national tourism system on the economic growth in Ukraine." Problems and Perspectives in Management 17, no. 4 (November 15, 2019): 93–103. http://dx.doi.org/10.21511/ppm.17(4).2019.08.
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The paper aims at analyzing the impact of tourism on the economic growth in Ukraine considering its global significance and dynamic development. Tourism should be considered not as a separate phenomenon, but as a complex socio-economic-ecological system, i.e. the national tourism system (NTS). The study attempts to reveal the nature and determinants of the national tourism system impact on economic growth, and also empirically substantiates this in the Ukrainian context. Since the economic decisions require a huge amount of information and different models, a multivariate least square model has been proposed to determine the causal links between NTS and economic growth. The paper also presents the economic parameters such as Ukrainian GDP as a dependent variable, volume of domestic tourism consumption, income from international passenger carriage, international tourism expenditures in the country, the volume of services provided in temporary accommodation and catering establishments, and country’s income from NTS as independent variables. The paper is based on the 2000–2017 statistical data. It concludes that the increase of total NTS contribution to GDP is influenced by all considered factors except the international tourism expenditures in the country. A proposed econometric factor analysis model can be used as a tool to analyze and forecast the socio-economic NTS processes. The hypothesis of the NTS`s impact on economic growth is substantiated.
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Morley, Clive. "Demand Modelling Methodologies: Integration and other Issues." Tourism Economics 6, no. 1 (March 2000): 5–19. http://dx.doi.org/10.5367/000000000101297442.
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The exponential growth in tourist numbers motivates serious analysis of this phenomenon. The econometric methods commonly used do not take this central feature of demand seriously in the form and estimating of tourism demand models. Cointegration analysis has been used in recognition of the problem as a technical estimation issue. But this is unsatisfactory, due to both technical methodological concerns with the use of cointegration analysis and because it overcomes the growth issue rather than incorporating it into the model. A model form which does incorporate growth is proposed. Other, newer methods – neural networks and structural equations modelling – are sometimes applied, but these too are not unproblematic.
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Guirao, Begoña, and Juan L. Campa. "Should Implications for Tourism Influence the Planning Stage of a New HSR Network? The Experience of Spain." Open Transportation Journal 10, no. 1 (April 30, 2016): 22–34. http://dx.doi.org/10.2174/1874447801610010022.
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Transportation and tourism are two closely linked economic activities and the scientific common view is that promoting transportation infrastructure may contribute to the development of tourism industry. But in the case of the building of new High-Speed Rail (HSR) lines, their extremely high construction costs require empirical evidence (at least at the planning stage) that certain economic activities, like tourism, are reinforced.The aim of this paper is to assess empirically the effects of HSR on tourism in Spain, using a ranking model of city pairs, in order to establish a better way of allocating financial resources for public investments. There is practically no literature on empirical methodologies to assess the effects of new HSR on tourism and the current literature on tourism demand is dominated by econometric models using a single-equation time-series based approach, where the reduction of the travel cost generated by transport infrastructure can be considered. In this paper, the new proposed methodology is tested by application to 1,176 city pairs in Spain, a country with over 20 years of operating experience and the longest HSR network in Europe, where tourism represents more than 10% of the GDP. Results clearly show that the implementation of a tourism variable in the model offers a more effective approach for determining the implications of tourism on HSR demand and should be taken into account by policymakers in the HSR planning process. Finally, studies at local level demonstrate that future research is needed to complement this planning stage methodology.
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Thrane, Christer. "Modelling tourists’ length of stay." Tourism Economics 22, no. 6 (September 21, 2016): 1352–66. http://dx.doi.org/10.5367/te.2015.0489.
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Modelling of tourists’ length of stay (LOS) is an expanding topic of study. A common thread in this literature is the use of sophisticated statistical/econometric methods. The present study builds on and extends an article critical of the statistical craftsmanship in prior LOS modelling studies. On the basis of an updated assessment of current practice and two small-scale case studies, two main conclusions are drawn. First, the available evidence suggests that the ordinary least squares (OLS) regression model produces qualitatively similar findings to much more complicated methods, such as duration and count data models. The principle of parsimony and the so-called KISS rule thus dictate that OLS regression analysis should be the preferred estimation technique in LOS modelling studies. Second, the quality of LOS modelling studies will most likely be improved by intensifying the use of the long-established tools of the trade explicated in influential econometric textbooks rather than by testing new estimation methods.
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Kurata, Shohei, and Yasuo Ohe. "Competitive Structure of Accommodations in a Traditional Japanese Hot Springs Tourism Area." Sustainability 12, no. 7 (April 10, 2020): 3062. http://dx.doi.org/10.3390/su12073062.
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This paper investigates the competitive structure of prices in a traditional hot springs resort area in Japan from a spatial econometric perspective. This perspective has not been addressed in hot springs—or “onsen” in Japanese—tourism areas, which have been gradually losing momentum due to the ageing of operators and diversification of leisure activities. The study area is one of the three oldest hot springs in Japan, the Dogo Onsen area in Matsuyama, where hotels and ryokans are clustered. First, we present a conceptual framework that characterizes two strategies, namely, differentiation and partnership strategies. Then, spatial error models are employed to test the hypothesis that spatial closeness intensifies price competition, while social closeness mitigates price competition. The estimation results reveal that our hypothesis was verified, in that the social network which has been nurtured for generations in the study hot spring area mitigates price competition, in comparison with the non-hot spring area in Matsuyama. Thus, good partnerships among local operators based on social networks should be more closely scrutinized for the revitalization of traditional hot springs areas.
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Huang, Ya-Ling. "Forecasting the demand for health tourism in Asian countries using a GM(1,1)-alpha model." Tourism and hospitality management 18, no. 2 (2012): 171–81. http://dx.doi.org/10.20867/thm.18.2.1.
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The purpose – Accurately forecasting the demand for international health tourism is important to newly-emerging markets in the world. The aim of this study was presents a more suitable and accurate model for forecasting the demand for health tourism that should be more theoretically useful. Design – Applying GM(1,1) with adaptive levels of α (hereafter GM(1,1)-α model) to provide a concise prediction model that will improve the ability to forecast the demand for health tourism in Asian countries. Methodology – In order to verify the feasibility of the proposed approach, using available secondary and primary data covering the period from 2002 through 2009 obtained from the RNCOS “Opportunities in Asian Health tourism” report. Based on a unique and characteristics database for the health tourism industry, this study applies the adaptive α in a Grey forecasting model (GM(1,1)-α) to predict the demand for health tourism in Asian countries. Approach – Implementation of demand forecasting in health tourism is examined on the short-term and limited dataset, due to importance of a minimum the predicated error on underlying basis for the econometric model for health tourism markets. Findings – Key findings present that the optimal value of α in GM(1,1) can minimize the predicted error. Finally, in the case of the demand for health tourism in Asian countries, using GM(1,1)-α to predict error is clearly better than the use of the original GM(1,1) and time series models. The originality of this research – The originality comes from the analysis of the demand forecasting in health tourism of Asian countries, which provides an easy and accurate method to predict the demand for health medical tourism and ideas for further improvements in the sector of health tourism.
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Ponce, Pablo, Nathalie Aguirre-Padilla, Cristiana Oliveira, José Álvarez-García, and María de la Cruz del Río-Rama. "The Spatial Externalities of Tourism Activities in Poverty Reduction." Sustainability 12, no. 15 (July 30, 2020): 6138. http://dx.doi.org/10.3390/su12156138.
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Poverty is one of the main indicators of economic development worldwide, in such a way that one of the Sustainable Development Goals is to eradicate poverty in all its forms worldwide. The objective of this research was to examine the effect of the gross value added (GVA) of tourism on poverty in the 198 contiguous Ecuadorian cantons. The methodology used was the application of a set of spatial econometric models to capture the regional effect of tourism on poverty. Data were obtained from the Central Bank of Ecuador and the National Survey of Employment, Unemployment and Under-Employment of the National Institute of Statistics and Census (INEC). The results show that tourism activities and regional poverty are negatively related; thus, a 1% increase in tourism-related economic activity decreases the regional poverty of the canton itself by 4.31%, and that of neighboring cantons by between 0.7% and 2.4%. The inclusion of the control variables shows that schooling and the mestizo population contribute to reducing the canton’s poverty, since the regions with a high GVA of tourism have high levels of schooling and a mestizo population. Thus, regional poverty increases when the level of schooling increases in neighboring cantons. On the other hand, in cantons with a high Mestizo population, compared to the African-American population, the poverty of the canton and its neighboring regions decreases. Public policy measures which aim at reducing poverty must take into account spatial spills from tourist activity in the cantons.
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Muhammad, Faqeer, Rehmat Karim, Javed Akhter Qureshi, Naveed Razzaq, Madeeha Zahra, and Irfan Ali. "Environmental Degradation, Quality of Institutions and Tourism: New Evidence from Pakistan." International Journal of Economic and Environmental Geology 10, no. 3 (November 14, 2019): 125–28. http://dx.doi.org/10.46660/ijeeg.vol10.iss3.2019.321.
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This study explores the effects of tourism, quality of institutions and FDI on environmental degradation inPakistan for the two time periods i.e. 1996-2017 and 2000-2017. Quality of institutions is included in the time period2000-2017 which is adopted from world governance indicators but due to lack of the data it has not been included insecond time (1999-2017). To find out the relationship among given variables, Ordinary Least Square (OLS) regressionwas carried out, moreover, Breusch-Godfrey Serial Correlation LM test, Heteroscedasticity Test and HistogramNormality test were also applied to diagnose the econometric issues in the given models. The findings of the studyrevealed that tourism is significant and influential factor of environmental degradation in Pakistan. Similarly, foreigndirect investment is also contributing in environmental degradation but its effect is insignificant for both time periods.On the other hand, an inverse relationship is observed between quality of institution and environmental degradation.The outcomes of the study suggest that environmental degradation can be overcome by increasing the quality of theinstitutions. Moreover, the government initiatives to attract foreign tourists by introducing new visa policy, whichincludes; electronic visa, on arrival visa and opening new avenues for tourists (e.g. Kartarpur Corridor and CPECinitiatives etc.) will have tremendous impact on the national economy. However, environmental degradation is theoutcome of tourism, therefore, policy maker’s needs to consider the negative effects of tourism in addition to itspositive effects on the economy.
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Muhammad, Faqeer, Rehmat Karim, Javed Akhter Qureshi, Naveed Razzaq, Madeeha Zahra, and Irfan Ali. "Environmental Degradation, Quality of Institutions and Tourism: New Evidence from Pakistan." International Journal of Economic and Environmental Geology 10, no. 3 (November 14, 2019): 125–28. http://dx.doi.org/10.46660/ojs.v10i3.321.
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This study explores the effects of tourism, quality of institutions and FDI on environmental degradation inPakistan for the two time periods i.e. 1996-2017 and 2000-2017. Quality of institutions is included in the time period2000-2017 which is adopted from world governance indicators but due to lack of the data it has not been included insecond time (1999-2017). To find out the relationship among given variables, Ordinary Least Square (OLS) regressionwas carried out, moreover, Breusch-Godfrey Serial Correlation LM test, Heteroscedasticity Test and HistogramNormality test were also applied to diagnose the econometric issues in the given models. The findings of the studyrevealed that tourism is significant and influential factor of environmental degradation in Pakistan. Similarly, foreigndirect investment is also contributing in environmental degradation but its effect is insignificant for both time periods.On the other hand, an inverse relationship is observed between quality of institution and environmental degradation.The outcomes of the study suggest that environmental degradation can be overcome by increasing the quality of theinstitutions. Moreover, the government initiatives to attract foreign tourists by introducing new visa policy, whichincludes; electronic visa, on arrival visa and opening new avenues for tourists (e.g. Kartarpur Corridor and CPECinitiatives etc.) will have tremendous impact on the national economy. However, environmental degradation is theoutcome of tourism, therefore, policy maker’s needs to consider the negative effects of tourism in addition to itspositive effects on the economy.
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Dłubakowska-Puzio, Ewa K., Michał Karpuk, and Kamil Puzio. "Analysis of Tourism Service Quality in Kołobrzeg Region by Means of Time Series Models." Comparative Economic Research. Central and Eastern Europe 15, no. 4 (March 8, 2013): 31–44. http://dx.doi.org/10.2478/v10103-012-0024-8.
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The aim of the given paper is to present the analysis of tourism services by means of time series models and forecasting of evaluation of tourism services. Tourism services are analysed according to various parameters: hotel stay price, hotel services quality (such as cleanness of rooms, check-in, information provision etc.), catering quality and medical service quality. The research has been undertaken on the basis of responses of foreign guests of 13 hotels in Kołobrzeg region taken from 1400 questionnaires divided according to age and sex of respondents. Various econometric models were used for the analysis of statistic regularities. First, customers evaluated quality of their stay in hotels. These data were examined during the 2006-2009 time period as a stochastic process. It was found that the processes are nonstationary, that is why the ARIMA (1,1,1) model was used in the study. On the basis of the analyses and prognoses one can deduce that models of time series make it possible to estimate a tendency that occurs for an analysed parameter, however misprediction is quite possible to appear (up to 30 %). Similar results were achieved during the analysis of evaluation of hotel stay quality on the basis of sex of respondents. One should point out that an average value of male evaluation rate is higher than an average value of female evaluation rate. Time series for analysed variables were integrated into level I(1). A certain co-integrational connection was found between the evaluation of hotel stay and number of stays in a given hotel, where tourists that have already visited a given hotel for several times presumably give a high evaluation rate of hotel stay quality. The result of the analysis of long-term relation between hotel stay and duration of check-in is presented in high mutual dependence of hotel evaluation rate on evaluation of check-in duration. A hotel stay price influences hotel stay evaluation in a negative way, but catering and medical services are considered as standard and do not have any particular influence on hotel stay evaluation. The undertaken study shows that methods that take into account time series can be successfully used in analysis of parameters of tourist comfort and in evaluation of hotel services.
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Mohammed, Ibrahim, Basak Denizci Guillet, and Rob Law. "Modeling dynamic price dispersion of hotel rooms in a spatially agglomerated tourism city for weekend and midweek stays." Tourism Economics 25, no. 8 (February 3, 2019): 1245–64. http://dx.doi.org/10.1177/1354816619826829.
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In spite of the abundant evidence suggesting the existence of spatial agglomeration in the hotel industry and the potential for spatial econometric methods to contribute to the understanding on the effect of spatial competition on room pricing, limited research has been conducted in this regard. To contribute to this area of research, this study applied spatial models to examine online pricing data of hotels in Hong Kong to determine the effect of spatial agglomeration on dynamic or intertemporal price dispersion. The findings revealed that the magnitude of dynamic price dispersion is not only influenced by demand but also the pricing of neighboring hotels and hotel-specific attributes, such as number of rooms, star rating, chain affiliation, and scale. A major implication of this finding is that real-time tracking and analysis of neighboring hotels’ prices could be an effective strategy to stay competitive in a spatially agglomerated environment.
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Yerdelen Tatoglu, Ferda, and Hasan Gul. "Analysis of tourism demand using a multi-dimensional panel gravity model." Tourism Review 75, no. 2 (November 17, 2019): 433–47. http://dx.doi.org/10.1108/tr-05-2019-0147.
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Purpose This study aims to estimate the determinants of international tourist flows between destinations by using the panel gravity model. Design/methodology/approach The multi-dimensional panel gravity model was used to analyse tourism originating from 30 different countries to the 14 most-visited countries in the world between 2008 and 2016. Income (i.e. per capita gross domestic product for both the origin and destination countries), distance between countries, various economic indicators and six dummy variables were added to the gravity model as control variables. Findings The results indicated that tourist arrivals depended mainly on economic factors, i.e. income and trade variables were significant determinants of tourist arrivals. The results also suggested that estimated international tourist flows are a negative function of distance, as is postulated in economic theory. Originality/value In recent years, gravity models have been used frequently to analyse international tourism demand and have demonstrated their ability to evaluate the effects of various determinants of international tourism for many countries. The literature includes studies that used a two-dimensional panel gravity model to analyse the determinants of tourism demand to a single country from many different countries. This study differs in terms of specificity; in that, it relied on a three-dimensional panel gravity model that allowed for modelling of multiple destination countries. As a result, more comprehensive and general results relative to the determinants of tourism demand were obtained. In addition, the application of a non-nested three-dimensional panel data model, which has limited use, contributes a new perspective to the econometric literature.
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Shanthi, A., and R. Thamilselvan. "Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India." Restaurant Business 118, no. 3 (March 11, 2019): 137–52. http://dx.doi.org/10.26643/rb.v118i3.7637.
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The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets
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Ye, Shun, Honggen Xiao, Tianyu Ying, and Lingqiang Zhou. "Determinants of small accommodation business size." International Journal of Contemporary Hospitality Management 31, no. 4 (April 8, 2019): 1626–46. http://dx.doi.org/10.1108/ijchm-04-2018-0290.
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PurposeThis paper aims to model and empirically test the determinants of small accommodation business (SAB) size.Design/methodology/approachThis study distinguishes among three aspects of SAB size (accommodation scale, investment and employment) and between two modes of growth (managerial and entrepreneurial growth). A conceptual framework was developed based on business growth theory, whereby three econometric models were constructed and estimated to predict size variations. Data were collected through a survey on 200 SABs in North Zhejiang Province of China. Effects of the determinants were contrasted between different size indicators.FindingsThe SAB size can be affected by personal factors (employed working experience, education level, industry-specific know-how), interpersonal factor (relative ties to other SABs) and environmental factor (association support). The interpersonal and environmental factors tend to contribute to managerial growth, while the personal factors are usually conducive to entrepreneurial growth.Research limitations/implicationsThis study addresses the questions of “why some SABs grow larger in size than others” and “why different SABs grow in different ways”. But more contexts and business types should be examined so as to ensure generalizability through future studies.Practical implicationsThe research findings can provide guidelines for local tourism administration to encourage or regulate SAB development.Originality/valueThis study is among the first endeavors to examine the multidimensionality and determinants of business size in tourism and hospitality; it contributes to literature by expanding tourism entrepreneurship research into a/the “growth paradigm”.
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Zhou, Chunbo, and Marios Sotiriadis. "Exploring and Evaluating the Impact of ICTs on Culture and Tourism Industries’ Convergence: Evidence from China." Sustainability 13, no. 21 (October 25, 2021): 11769. http://dx.doi.org/10.3390/su132111769.
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Information and communications technologies (ICTs) have been driving the digital revolution of all industries worldwide. Industrial convergence constitutes a new feature and trend of contemporary industrial development and has received extensive attention from the media and public. However, the interrelationship between the two concepts—industrial convergence and ICTs—remains under-researched. This paper aims to explore and evaluate the ICTs’ impact on industrial convergence by focusing on the interrelationship between culture and tourism. The study takes an industrial economics perspective with a specific focus on the multi-dimensional (direct, moderated, and threshold) effects. A research framework was suggested synthesizing three econometric models and encompassing three hypotheses. The research model was then empirically tested and validated through quantitative research using China’s provincial panel data from 2004 to 2018. The study’s findings indicate a positive influence/relationship between ICTs and market-oriented reforms in the culture and tourism industries’ convergence. Moreover, a positive labor-convergence relationship was found, while the negative government–convergence relationship was uncovered in control variables. Regarding the moderating effect, the interaction of ICTs and market-oriented reforms is positively correlated with industrial convergence. In addition, there is a single-threshold effect of consumer demand on the ICTs–convergence relationship. This article extends our knowledge in two ways by addressing the knowledge gap regarding the interrelationship between culture and tourism and by providing new insights into the influence of ICTs on this industrial convergence that has theoretical and practical implications.
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Mostafa, Mohamed M., and Mohaned Al-Hamdi. "Kuwaiti consumers’ willingness to pay for environmental protection in Failaka island: a contingent valuation analysis." Tourism Review 71, no. 3 (August 15, 2016): 219–33. http://dx.doi.org/10.1108/tr-05-2016-0012.
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Purpose Evidence suggests that a growing number of consumers across the world are becoming more environmentally responsible in terms of their personal habits and lifestyles. In this paper, the authors aim to use both parametric and non-parametric econometric models to estimate Kuwaiti consumers’ willingness to pay (WTP) for environmental protection in Failaka island. Design/methodology/approach Contingent valuation methods based on log-logistic and log-normal regression models revealed that consumers in Kuwait are willing to pay a price premium of approximately 40 Kuwaiti dinars for environmental protection in Failaka island based on the double-bound dichotomous choice model. Findings Socio-economic variables have no significant influence on the respondent’s WTP. As expected income has a positive relationship with WTP and bid price has negative relationship with WTP to protect the environment in Failaka island. Originality/value This study highlight the fact that understanding consumers’ environmental-friendly behaviors may play an important role in formulating environmental policy changes to face complex problems as diverse as environmental pollution or environmental degradation.
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Sánchez-Ollero, José Luis, Alejandro García-Pozo, and Macarena Marchante-Lara. "Measuring the effects of quality certification on labour productivity." International Journal of Contemporary Hospitality Management 27, no. 6 (August 10, 2015): 1100–1116. http://dx.doi.org/10.1108/ijchm-02-2014-0057.
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Purpose – The purpose of this study was to evaluate the impact of quality certifications on apparent labour productivity in a sample of hotels in Spain. Design/methodology/approach – In line with Mairesse and Kremp (1993), the theoretical model was based on a Cobb–Douglas production function readapted to the goals of the study. Findings – The descriptive results show that labour productivity increases only when certifications and quality standards specific to the hospitality industry are implemented and the tourist destination is committed to quality. The econometric analysis shows that the hotel category, belonging to a chain, and outsourcing services have a positive impact on labour productivity. In contrast, the location of the establishment in areas other than the coast or the capital city of a province has a negative effect on labour productivity. Of the quality models and certifications studied, only the Spanish Q-Mark certificate significantly improves hotel productivity (an average increase of 23.27 per cent). Practical implications – These results provide support for the Spanish Tourism Quality System implemented by the Spanish Ministry of Tourism, which has not only attempted to increase the quality of tourism hotels by increasing their competitiveness and performance but also by providing them with a quality certificate that can be used as a marketing strategy in international markets. Originality/value – The main contribution of this study is to show how the adoption of quality standards and certifications increases or decreases labour productivity in hotels. Given that most of the previous literature has only taken into account quantities, this study adds to the literature by incorporating the concept of quality into productivity issues.