How to cover risk in the hotel sector

González, José Ignacio López; Morini, Sandra; Calatayud, Francisco Pérez

doi:10.1016/s0160-7383(99)00015-8

Cited by 4 publications

(1 citation statement)

References 4 publications

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“…Hospitality operators and academics have made widespread use of hotel room occupancy rates as an indicator of business performance (Ignacio González et al, 1999; Law, 1998, 2004; Moutinho and Peel, 1994; Schwartz and Cohen, 2004). With a view to ensuring coverage of the various hotel categories in the present article, the authors have used the tariffs that are reported in the Hong Kong Tourism Board (HKTB)’s well-structured and maintained historical data set of hotel occupancy rates.…”

Section: Predicting and Forecasting Demandmentioning

confidence: 99%

Predicting hotel occupancies with public data

2016

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This study demonstrates the value of using readily available Organisation for Economic Co-Operation and Development (OECD) indicators to estimate hotel occupancy trends in a particular territory (Hong Kong) drawing upon almost four decades of data (1972–2010). The indicators predict the economic climate at global, regional and national levels by providing comprehensive statistically based economic information. They should be of particular benefit for resource-constrained small and/or independent hotel operations for whom accurate occupancy predictions facilitate a more targeted approach to strategic investments. Using the OECD indicators offers hoteliers an alternative to acquiring expensive data and/or consultant inputs. The article shows the merit of OECD composite indicators generally and of the consumer confidence index in particular as publicly available and reliable data which can provide hoteliers with early signals about shifting demand. It contributes to tourism economics by demonstrating the merit of indices as a supplement to both established demand forecasts and as an input to hotel revenue management systems.

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Section: Predicting and Forecasting Demandmentioning

confidence: 99%

Predicting hotel occupancies with public data

2016

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Type of diversification and firm resources: new empirical evidence from the Spanish tourism industry

Andreu

Claver

Quer

2008

Journal of Tourism Research

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This paper analyses the diversifi cation strategies followed by tourism fi rms from the perspective of the resource-based view. More specifi cally, it seeks to verify whether the composition of the fi rms' resources has a bearing on the decision to undertake one type of diversifi cation or another (related or unrelated). From a mail survey to 80 Spanish tourism fi rms, we identifi ed 94 entries into new business areas. We applied an ordered logit regression and have statistically confi rmed that intangible resources lead to a more related type of diversifi cation.

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Estimating Future Room Occupancy Fluctuations to Optimize Hotel Revenues

Tang¹,

King²,

Kulendran³

2015

Journal of Travel & Tourism Marketing

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The present study proposes a mechanism that estimates future hotel demand and assesses the likelihood of forthcoming occupancy peaks and troughs. In anticipating rate fluctuations, the approach depends less on short term seasonal related factors than many prevailing hotel forecasts. Scholars and practitioners are in broad agreement that accurate assumptions about room occupancies produce better informed strategic planning for staffing, purchasing and budgeting related decisions. The literature has confirmed the difficulty of providing accurate mid to long run hotel industry estimates without a comprehensive revenue management system that considers factors beyond seasonal movements. Hotel managers need advance and accurate notifications about the up and down turns of the occupancies if they would like to maximise revenues. The proposed approach facilitates efficient resource management by reducing the medium to long term financial risks that are associated with volatile occupancy rates. Drawing upon Hong Kong data, the study found that the average contraction period for hotel occupancies from one peak point to the next trough exceeds the duration of the expansion period (defined as the period from one trough point to the next peak). This may be partly attributable to Hong Kong's dynamic image and appeal which has been fostered by destination tourism marketing efforts. The study contributes to industry practice by providing estimations that are applicable to different levels of hotel classification.

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How to cover risk in the hotel sector

Cited by 4 publications

References 4 publications

Predicting hotel occupancies with public data

Predicting hotel occupancies with public data

Type of diversification and firm resources: new empirical evidence from the Spanish tourism industry

Estimating Future Room Occupancy Fluctuations to Optimize Hotel Revenues

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