Introduction to the Special Issue: Economic Analysis in Tourism and Hospitality—New Methods and Perspectives

Forecasting

In the area of forecasting, the article by Zhu, Lim and Zhang illustrates the effectiveness of the copula method to analyze and forecast hospitality and tourism stock return volatility. The article by Wu, Cao, Wen, and Song is one of the first to introduce probabilistic scenario forecasting to guide tourism decision making in contexts where two or more dimensions simultaneously define forecasts. A hybrid model, the time-varying parameter panel vector autoregressive (TVP-PVAR) model was adopted for scenario forecasting. The article by Wu, Ji, He, and Tso introduces a novel hybrid approach, SARIMA + LSTM, which combines the traditional time series model, seasonal autoregressive integrated moving average (SARIMA) model with an artificial recurrent neural network method, the long short-term memory (LSTM), to forecast daily tourist arrivals. The authors prove the effectiveness of this method in producing accurate forecasts.

Performance Modeling

In the area of performance modeling, the article by Arbelo, Arbelo-Pérez, and Pérez-Gómez focuses on the issue of heterogeneity in measuring hotel performance. The authors use a Bayesian stochastic frontier model with random coefficients to estimate a profit function for Spanish hotels. The article by Zekan is the first to incorporate the stakeholders’ value judgments in city destination benchmarking. The article uses data envelopment analysis (DEA). The article by Liu and Tsai uses a flexible translog production function with neutral technological progress, estimated in a stochastic frontier framework, to measure technical efficiency change, technological change, scale change, and total factor productivity change for Chinese hotels. The article by Tzeremes and Tzeremes illustrates how the order-α quantile-type estimators can be used to construct a robust version of the Malmquist productivity index, using a sample of hotels form the Balearic Islands. Finally, the article by Peypoch, Song, and Zhang uses a Malmquist productivity index to analyze the performance of Chinese hotels. They demonstrate that the productivity growth of Chinese hotels is mainly driven by technological progress.

Demand Modeling, Economic Impact, And Competitiveness

In the area of demand modeling, Liu, Liu, and Wang introduce a time-varying parameter factor vector autoregression model that is developed based on the Baidu Index to understand the mechanism of tourism demand. The study by Liu, Fan, and Qiu uses a Bayesian two-stage method to estimate the impact of cultural distance on tourism demand while handling collinearity. Their results show that while cultural distance and tourism demand are negatively related, tourism demand is less sensitive to the change in cultural distance. Dogru, Suess, and Turk investigate the competitiveness of international tourism destinations using a regional economic policy tool—a shift-share analysis. The authors show that the competitiveness of tourism destinations depends on the aggregated measure of tourism development. Finally, the article by Zhang and Yang investigates the relationship between inbound tourism and the housing market using a dynamic stochastic general equilibrium (DSGE) model. Their simulation results show that higher inbound tourism demand raises both house prices and rental prices.

Game Theory

The study by Kim, Slutsky, and Thapa applies a game-theoretical model to assess the profit maximizing behavior of hotels when sharing or not sharing private information with competitors. The findings help hotel managers in revenue management decisions, such as room pricing strategy. The article by Keskin and Ucal investigate the strategic dynamics in a market with two different tourism supply chains. They extend the model to an infinite-horizon repeated game.

Other Related Methodologies

The article by Gu, Sheng, Yuen, and Lei illustrates the impact of taxation on the casino industry using mathematical programming. The results suggest that a high tax should be imposed if enough of the tax burden can be shifted to tourists, but a low tax must be offered otherwise. The article by Oliver and Sard uses conditional and unconditional quantile regression to measure and decompose the gender wage gap. They show that segregation of women into worse-paid jobs is one of the main sources of the gender wage gap. The article by Gunter and Onder uses spatial analysis on geotagged photos from Instagram to study the differences among popular sites in Vienna for residents and visitors, and to assess whether geotagged data can help in understanding tourism demand. Finally, the article by Park, Song, and Lee revisits endogeneity and causality issues in panel data and presents several suggestions to alleviate these problems.

In summary, the articles included in the two volumes of this special issue contribute to the advancement of tourism economics research. Some innovative methodological approaches are introduced to the field of tourism economics for the first time. In particular, hybrid models such as the SARIMA + LSTM and TVP-PVAR models combining the strengths of individual methods appear to be an emerging trend. Meanwhile, some important economic theories such as game theory and analytical tools such as the DSGE and DEA methods are applied to the analysis of economic issues of tourism and hospitality from new perspectives. We hope this special issue will inspire further research endeavors in the field of tourism economics.