An Application of Hedonic Pricing Analysis to the Case of Hotel Rooms in Taipei

Chen, Ching-Fu; Rothschild, R.

doi:10.5367/000000010792278310

Cited by 197 publications

(193 citation statements)

References 11 publications

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“…Generalization at the regional scale might allow an assessment to reflect the real usage well, whilst at the scale of the city, where the population density varies [47], the assessment can be strongly biased and the RES will be unevenly distributed in space. Property values increase along the urban-rural gradient (the closer to the city centre, the more expensive) [48][49][50][51][52][53], and a similar pattern should be revealed as property nears RES provisioning of cities' green infrastructure. While the benefits derived from potential ES resources of green infrastructure-such as CO 2 and noise reduction-or a positive influence on microclimate affect all the citizens in the neighbourhood, benefits associated with recreation or choice of an aesthetic neighbourhood to live in are subject to the general laws of demand and supply.…”

Section: Actual and Potential Benefits From Green Infrastructurementioning

confidence: 99%

High Biodiversity of Green Infrastructure Does Not Contribute to Recreational Ecosystem Services

2017

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Urban lakes, especially those of natural origin, provide ecosystem services, recreation being one of the most important and highly valued by city dwellers. Fulfilling the needs of city residents to relax and have contact with nature has become a priority in urbanized areas and has been proven to positively affect people's health and well-being. The recreational potential of water bodies was identified to be the most important aspect of ecosystem services to the residents of the neighboring areas. An assessment of recreational ecosystem services (RES) provisioning to society based on the real time spent by the citizens and housing values in the urban-rural gradient revealed that the economic benefits of lakes differ in urbanized, suburban and rural landscapes. The growth of cities has led to an increased population density in the surroundings of ecologically valuable areas, resulting in higher pressure from visitors seeking recreational areas. Along with urbanization, the impoverishment of ecosystem functions takes place, limiting their capability to provide ecosystem services. In this work, the provisioning of recreational ecosystem services of 28 floodplain lakes located along the urban-rural gradient of the Warsaw agglomeration was assessed. The relationship between the ecological value of the water bodies, measured using naturalness indices, and the recreational ecosystem services they can provide was assessed. The results showed that the floodplain lakes located along the urban-rural gradient are of great importance to the citizens due to their recreational potential. The provisioning of recreational ecosystem services is poorly connected with the ecological characteristics of the floodplain lakes. Only hemeroby was significantly correlated with provisioning, and there was no relationship with factors such as naturalness of vegetation or water quality, demonstrating that public preference was not generally influenced by high ecological quality. These data should be available to potential buyers and be integrated in spatial planning management plans in order to shape future housing policy.

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Section: Actual and Potential Benefits From Green Infrastructurementioning

confidence: 99%

High Biodiversity of Green Infrastructure Does Not Contribute to Recreational Ecosystem Services

2017

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“…Serval important factors affecting the hotel room price have been identified such as location [6,7], hotel category [32,33], customer ratings [34,35], hotel amenities and services [36,37], market accessibility [38], and proximity of competitors [33]. Previous empirical studies often employed a global regression model, considering only the relationship between hotel room price and explanatory variables on a global level.…”

Section: Determinants Effects Detailsmentioning

confidence: 99%

Key Factors Affecting the Price of Airbnb Listings: A Geographically Weighted Approach

et al. 2017

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Airbnb has been increasingly gaining popularity since 2008 due to its low prices and direct interactions with the local community. This paper employed a general linear model (GLM) and a geographically weighted regression (GWR) model to identify the key factors affecting Airbnb listing prices using data sets of 794 samples of Airbnb listings of business units in Metro Nashville, Tennessee. The results showed that the GWR model performs better than the GLM in terms of accuracy and affected variable selections. Statistically significant differences varied across regions in Metro Nashville. The coefficients illustrate a decreasing trend while there is an increase in the distance from the listed units to the convention center, which indicates that Airbnb listing prices are more sensitive to the distance from the convention center in the central area than in other areas. These findings can also provide implications for stakeholders such as Airbnb hosts to gain a better understanding of the market situation and formulate a suitable pricing strategy.

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“…Yet in another study that included 73 hotels in Taipei (Chen and Rothschild, 2010), it was found that such factors as breakfast, business centers or swimming pools do not influence the room price, while the hotel location, TV, Internet access, and availability of the fitness center, have significant influence on room rates. Lee and Jang (2010) showed that hotel prices are affected by the proximity of a hotel to an airport or to central business districts.…”

Section: Related Workmentioning

confidence: 99%

“…Understanding the factors that affect hotel prices using the hedonic pricing theory, received much attention in the research (e.g., Monty and Skidmore 2003;Thrane 2007;Li et al 2008;Hung et al 2010;Chen and Rothschild 2010;Lee and Jang 2010). The results show that there is no universal solution to the factors that affect prices.…”

Section: Introductionmentioning

confidence: 99%

Developing a Price Management Decision Support System for Hotel Brokers Using Free and Open Source Tools

Kisilevich

Keim

Byshko

et al. 2011

Proceedings of the 13th International Conference on Enterprise Information Systems

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Abstract:In the Internet age, e-commerce provides customers global reach to a wide variety of products and plays a dominant role in business activity and competition. Competition is especially aggressive in the online travel domain where wholesalers, e.g. brokerage companies, contract through their contract managers with thousands of hotel brands and trade hotel products (usually hotel nights) for travel businesses or end customers.In order to conclude a profitable contract, a contract manager should be able to compare all the particulars of the prospective partner hotel with those of the competing hotels in the target city. Given that the number of contract managers is comparatively small compared to the large number of hotels, the possible knowledge base is limited. Thus, the hotel brokerage companies are only able to bargain with a relatively limited number of hotels, and the contract profitability relies heavily on the contract managers' expertise and communication skills. In this paper we present a price management decision support system (DSS) for hotel brokers that allows analysis of hotel prices using spatial and non-spatial characteristics, estimation of the objective relative hotel prices, and determination of the profitability of the existing or future contracts. We built our system using free and open source tools including geographic information system and data mining frameworks that allow companies with limited money resources or manpower to implement such a prototype. We show the effectiveness of our tool by covering all the major components of the DSS such as data selection and integration, model management and user interface. We demonstrate our tool on the area of Barcelona, Spain using a real data of 168 hotels provided by one of the travel service providers.

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An Application of Hedonic Pricing Analysis to the Case of Hotel Rooms in Taipei

Cited by 197 publications

References 11 publications

High Biodiversity of Green Infrastructure Does Not Contribute to Recreational Ecosystem Services

High Biodiversity of Green Infrastructure Does Not Contribute to Recreational Ecosystem Services

Key Factors Affecting the Price of Airbnb Listings: A Geographically Weighted Approach

Developing a Price Management Decision Support System for Hotel Brokers Using Free and Open Source Tools

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