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Article
Publication date: 13 March 2020

Murat Alper Basaran, Seden Dogan and Kemal Kantarci

Web 2.0 applications enable travelers to evaluate several services and assessment attributes. Constructed websites in several languages trigger a new way of data collections…

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Abstract

Purpose

Web 2.0 applications enable travelers to evaluate several services and assessment attributes. Constructed websites in several languages trigger a new way of data collections resulting in data streams leading to the accumulation of vast amounts of data, called big data. The need for analysis is in high demand. This study aims to construct a model to investigate which single attribute or interrelated ones having an impact on the performances of hotels.

Design/methodology/approach

The total number of 1,137 observations collected from the website HolidayCheck.de are used from the hotels in the Bavaria region in 2016. Bavaria is a region where both domestic and foreign travelers mostly prefer to visit. Fuzzy rule-based systems, which is a combination of fuzzy set theory (FST) and fuzzy logic, are used. Although the FST is used to convert linguistically expressed perceptions by travelers into mathematically usable data, fuzzy logic is used to construct a model between service attributes and price-performance (PP) to attain the set of single and interrelated attributes on the assessment of PP.

Findings

No single attribute plays a key role in PP assessment. However, two or more interrelated combinations have different impacts on PP. For example, when “Food—Drink” and “Room” moves together from average to good level, PP reaches the highest level of assessment.

Research limitations/implications

Accessibility to too much data is difficult.

Practical implications

A model can be continuously run so that any changes can be observed during the incoming of data.

Social implications

As the consumer reviews and ratings are the crucial source of information for other travelers, hoteliers must monitor and respond them on time in order to deal with the complaints.

Originality/value

Travelers’ perceptions or evaluations are treated with a FST that measures the impression of human beings. New modeling enables researchers to observe not only any single attribute but also interrelated ones on the PP.

Details

International Journal of Contemporary Hospitality Management, vol. 32 no. 4
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 24 June 2020

Seden Doğan, Murat Alper Basaran and Kemal Kantarci

Fuzzy rule-based system (FRBS), a soft computing method used for big data analysis, is used to determine which single hotel attribute or interrelated hotel attributes used in…

Abstract

Purpose

Fuzzy rule-based system (FRBS), a soft computing method used for big data analysis, is used to determine which single hotel attribute or interrelated hotel attributes used in Travel 2.0 data play a role on price–performance (PP).

Design/methodology/approach

FRBS, based on fuzzy set theory, is used using the data set of four- and five-star hotels in the Alanya destination in Turkey collected from HolidayCheck.de website for the period between 2009 and 2016.

Findings

Single attributes do not have an impact on PP. At least two or more attributes are necessary to have an impact on PP. Compensations among attributes that are observed to be leading to PP not to change from their current level. Instead of assuming a linear relationship between hotel attributes and PP, non-linearity should often be assumed. In addition, some hotel attributes do not have an impact on PP until some other attribute reaches a certain level.

Research limitations/implications

The limitations of this research can be grouped under two topics. While the first is related to data, which is German-speaking tourists staying at four- and five-star hotels between 2009 and 2016, the second is the limitation on generalizability. By implementing other types of data related to hotel attributes, new insights can be generated to shed light on different aspects of the relationship between hotel attributes and PP or other measures such as overall evaluation.

Originality/value

A data-driven model called FRBS is constructed using original verbal statements. Novel insights pertinent to relations between hotel attributes and PP have been extracted.

论使用乏晰规则为本系统(Fuzzy Rule-Based Systems)探究决定价格-效益的因素:使用旅游2.0用户对酒店的在线评价作为数据摘要

研究目的

乏晰规则为本系统(FRBS)作为大数据分析的软计算方法, 接用旅游2.0数据来分析出哪个酒店属性或者相关酒店属性对于价格-效益(PP)有直接作用。

研究设计/方法/途径

本论文采用FRBS以Fuzzy Set理论为基础, 采集2009年至2016年之间的HolidayCheck.de网站上的土耳其阿拉尼亚目的地的四星和五星酒店数据作为样本, 进行分析计算。

研究结果

酒店个别属性并不对PP具有直接影响。至少两个或者以上属性加和对PP有直接影响。酒店属性与PP的关系并不是预想的那样线性关系, 而是非线性的。此外, 一些酒店属性起初并不对PP有影响, 而是直到其他属性达到一定的水平后才起反应。

研究原创性/价值

本论文使用原始文本数据来构建以数据导向的FRBS模型。本论文给出了对于酒店属性和PP的关系相关的新型建议。

Details

Journal of Hospitality and Tourism Technology, vol. 11 no. 2
Type: Research Article
ISSN: 1757-9880

Keywords

Book part
Publication date: 24 November 2010

Abstract

Details

Tourism in the Muslim World
Type: Book
ISBN: 978-1-84950-920-6

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