Data Mining For Hotel Occupancy Rate: An Independent Component Analysis Approach

Wu, Edmond H. C.; Law, Rob; Jiang, Brianda

doi:10.1080/10548408.2010.481585

Cited by 21 publications

(17 citation statements)

References 28 publications

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“…The demand for hotel accommodation is measured by a variety of variables, from different perspectives. Some variables relate to the scale of demand, such as guest arrivals (Guizzardi and Stacchini, 2015), the number of nights stayed (Falk, 2014;Lim et al, 2009), the number of rooms sold (such as Corgel et al, 2013;Song et al, 2011b), and occupancy rates (Koupriouchina et al, 2014;Wu et al, 2010).…”

Section: Measurement Of Hotel Demandmentioning

confidence: 99%

New developments in tourism and hotel demand modeling and forecasting

Song

Shen

2017

IJCHM

240

217

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Design/Methodology/approachArticles on tourism and hotel demand modeling and forecasting published in both Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) journals were identified and analyzed. FindingsThis review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, while disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior, and consumer confidence indicators, among others. More sophisticated techniques such as Research limitations/implicationsThe main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting. Practical implicationsThis review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices. Originality/valueThe value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

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Section: Measurement Of Hotel Demandmentioning

confidence: 99%

New developments in tourism and hotel demand modeling and forecasting

Song

Shen

2017

IJCHM

240

217

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“…Smeral, 1988Smeral, , 2010Witt & Martin, 1987); and there are studies examining macroeconomic factors, for example GDP on hotel occupancy rate. Wheaton and Rossoff (1998) used GDP to study the lodging industry demand of the United States of America, and a recent study by Wu et al (2010) also revealed that there is a correlation relationship between GDP and hotel occupancy rate in Hong Kong. Moreover, previous studies also revealed that economy performance is closed linked with hotel industry development and prosperity (e.g.…”

Section: Gross Domestic Product Consumer Price Index and Inflationmentioning

confidence: 97%

“…Together with another four factors from the same study (Lam & Lei, 2010), namely seasonality, star rating, GDP and inflation rate; yet they were revealed as important factors associated with tourist arrivals, tourism demands and hotel industry demand (e.g. Chen, 2010;Smeral, 1988;Wu, Law, & Jiang, 2010) in the existing literature, therefore they were included in this study for further investigation. These were seasonality, star rating, gross domestic product (GDP) and the inflation rate.…”

Section: Background Of the Studymentioning

confidence: 98%

“…In addition, Barney (2002) advocated as well accounting and financial related aspects in measuring organization's competitive advantages. Financial data including average daily rate (ADR), revenue per available room (RevPAR), average room rate (ARR) (Enz et al, 2014;Hung, Shang, & Wang, 2010;Lee & Jang, 2011), and occupancy rate (Jeffrey & Barden, 2000, 2001O'Neill, 2011;Wu et al, 2010), they are the most commonly used ones as revealed from previous hospitality literatures concerning hotel business performance. Thus, financial related factors are chosen to be examined in this study.…”

Section: Hotel's Business Performance and Factorsmentioning

confidence: 99%

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Determinants of hotel occupancy rate in a Chinese gaming destination

Lei¹,

Lam

2015

Journal of Hospitality and Tourism Management

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“…Table 1 summarizes five studies focusing on hotel occupancy rate. Two of them analyzed Hong Kong, one of the largest and most populated cities in the world and encompassing a specific context, as Wu et al (2010) pointed by identifying the influence of disease outbreaks on occupancy rate. The remaining three are country scope analyses (e.g., UK, Switzerland, and USA).…”

Section: Literature Reviewmentioning

confidence: 99%

Identification of common city characteristics influencing room occupancy

Moro

Rita

2019

IJTC

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Purpose National tourism offices worldwide implement marketing strategies to influence tourists’ choices. However, there is more than meets the eye when it comes to choosing a city as a tourism destination. The purpose of this paper is to answer which are the characteristics that play a key role in room occupancy. Design/methodology/approach Diverse characteristics such as the city offer, demographics, natural amenities (e.g. number of beaches) and also politics (e.g. type of government) are combined into a decision tree model to unveil the relevance of each in determining room occupancy. The empirical experiments used data known in 2015 from 43 cities from Europe and the rest of the World to model room occupancy rate in 2016. Findings While the seasonality effect plays the most significant role, other less studied features such as the type of political party prior to current government were found to have an impact in room occupancy. Originality/value This study unveiled that center–right and right governments are generally more sensitive to promote its city as a tourism destination.

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Data Mining For Hotel Occupancy Rate: An Independent Component Analysis Approach

Cited by 21 publications

References 28 publications

New developments in tourism and hotel demand modeling and forecasting

New developments in tourism and hotel demand modeling and forecasting

Determinants of hotel occupancy rate in a Chinese gaming destination

Identification of common city characteristics influencing room occupancy

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