An Analysis of Word-of-Mouse Ratings and Guest Comments of Online Hotel Distribution Sites

Stringam, Betsy Bender; Gerdes, John

doi:10.1080/19368623.2010.508009

Cited by 182 publications

(143 citation statements)

References 39 publications

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“…For example, Stringam and Gerdes (2010), utilizing a content analysis, determined the percentage of specific words hotel guests used to describe hotels whose overall rating range from 1 to 5, with 5 being the highest grade. The words such as ''staff,'' ''price,'' ''airport,'' and ''downtown'' were mentioned more frequently by the guests who provided high than low ratings.…”

Section: Author (Year)mentioning

confidence: 99%

Does hotel attribute importance differ by hotel? Focusing on hotel star-classifications and customers’ overall ratings

Rhee

Yang

2015

Computers in Human Behavior

121

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Section: Author (Year)mentioning

confidence: 99%

Does hotel attribute importance differ by hotel? Focusing on hotel star-classifications and customers’ overall ratings

Rhee

Yang

2015

Computers in Human Behavior

121

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“…It is therefore not surprising that most academic research on TripAdvisor is found in the tourism literature and focuses on hotel reviews. Previous studies tend to focus on practical issues such as how users decide how to trust reviews, the response of hotels to reviews, or the content of negative reviews and complaints (O 'Connor, 2008;Cunningham et al, 2010;Sparks and Browning, 2010;Stringam and Gerdes, 2010;Ayeh et al, 2013). In contrast, our substantive interest, discussed elsewhere, is in how TripAdvisor works to convey cultural meanings.…”

Section: Case Selectionmentioning

confidence: 48%

The Web as History

Brügger¹

2017

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A CIP catalogue record for this book is available from The British Library.This book is published under a Creative Common 4.0 International license (CC BY 4.0). This license allows you to share, copy, distribute and transmit the work; to adapt the work and to make commercial use of the work providing attribution is made to the authors (but not in any way that suggests that they endorse you or your use of the work). Attribution should include the following information: Niels Brügger and Ralph Schroeder (eds. Table 5.2 Linear regression model explaining amount of country news mentions on BBC online 113 Table 5.3 Linear regression model explaining amount of country outlinks on BBC online 115 Table 6.1)Evaluation of the navigation and user interface of state websites 128 Table 7.1 Topics in three selected GeoCities neighbourhoods 149 Table 8.1 Direction and manifestation of ties in online networks 163 Table 8.2 Composition of sites (abortion stance) 167 Table 8.3 Composition of sites (site type) 167 Table 8.4 Top-20 sites ranked by Google, 2005 and 2015 169 Table 8.5 Network statistics 172 Table 8.6 Top-20 sites by indegree (full network) 176 Table 8.7 Top-20 sites by indegree (participant subnetwork) 178 Table 8.8 Top-20 sites by outdegree (full network) 179 Grant Blank is the Survey Research Fellow at the Oxford Internet Institute, University of Oxford. He is a sociologist specializing in the political and social impact of computers and the internet, the digital divide, statistical and qualitative methods, and cultural sociology. He is currently working on a project asking how cultural hierarchies are constructed in online reviews of cultural attractions. His other project links sample survey data with census data to generate small area estimates of Internet use in Great Britain. He holds a PhD from the University of Chicago. L iS t o f Co N t Ri B u to R S xivJonathan Bright is a Research Fellow at the Oxford Internet Institute, University of Oxford. He is a political scientist specialising in political communication and computational social science (especially 'big data' approaches to the social sciences). His research concerns how people get information about politics, and how this process is changing in the internet era.

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“…The findings of these comparisons influence customer purchasing decisions, as well as whether they will recommend the service providers to other individuals (Gerdes, Stringam & Brookshire, 2008;Stringam & Gerdes, 2010). The absence of a set of uniform standards in an industry makes it difficult to compare establishments (Hong et al, 2012).…”

Section: The Concept Of Benchmarkingmentioning

confidence: 99%

Barriers to the practice of benchmarking in South African restaurants

Kleynhans

Roberson

2017

Problems and Perspectives in Management

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The main purpose of this study is to find the barriers of benchmarking use in independent full-service restaurants in South Africa. The global restaurant industry entities operate in a highly competitive environment, and restaurateurs should have a visible advantage over competitors. A competitive advantage can be achieved only if the quality standards in terms of food and beverage products, service quality, relevant technology and price are comparable to the industry leaders. This study has deployed a descriptive, quantitative research design on the basis of a relatively large sample of restaurateurs. The data was collected through the SurveyMonkey website using a standardised questionnaire The questionnaire was mailed to 2699 restaurateurs, and 109 respondents returned fully completed answer sheets. Descriptive and inferential statistics were used to analyze the data. The main findings were as follows: 43% of respondents had never done benchmarking; only 5.5% respondents considered themselves as highly knowledgeable about benchmarking; respondents thought that the most significant barriers to benchmarking were difficulties with obtaining exemplar (benchmarking partner) best-practice information and adapting the anomalous (own) practices to derive a benefit from best practices. The results of this study should be used to shape the knowledge about benchmarking practices in order to develop suitable solutions for the problems in South African restaurants.

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An Analysis of Word-of-Mouse Ratings and Guest Comments of Online Hotel Distribution Sites

Cited by 182 publications

References 39 publications

Does hotel attribute importance differ by hotel? Focusing on hotel star-classifications and customers’ overall ratings

Does hotel attribute importance differ by hotel? Focusing on hotel star-classifications and customers’ overall ratings

The Web as History

Barriers to the practice of benchmarking in South African restaurants

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