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• W3035532817 abstract "Future economic trends in the U.S. hotel industry are often discussed and debated at hotel investment conferences and elsewhere, typically without discussion of the underlying economic indicators that lodging prognosticators should track to predict lodging demand growth and decline. This research endeavors to rank the predictive ability of various economic variables and determine which may be the strongest predictors of lodging demand trends. In addition, we seek to identify a relatively small group of economic variables, that is, a consideration set that may best serve lodging prognosticators with determining the future direction of lodging demand. In our analyses, we evaluate both economic indicators and quarterly change in those indicators. Furthermore, we analyze autoregressive and moving average features of lodging demand in recent years. We present models that prognosticators may use to project lodging demand trends. Although there are a variety of variables that serve to predict lodging demand trends, gross domestic private investment (GDPI) is noted as a particularly effective predictor of lodging demand trends, and it has been effective over all the recent time periods we studied. This information should be beneficial to lodging practitioners/analysts as well as academics." @default.
• W3035532817 created "2020-06-19" @default.
• W3035532817 creator A5051014383 @default.
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• W3035532817 date "2020-06-08" @default.
• W3035532817 modified "2023-10-16" @default.
• W3035532817 title "Predicting Lodging Demand Trends in the U.S. Hotel Industry" @default.
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• W3035532817 doi "https://doi.org/10.1177/1938965520916443" @default.
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