Influence of Organizational Form and Customer Type on Online Customer Satisfaction Ratings

Lawrence, Benjamin; Perrigot, Rozenn

doi:10.1111/jsbm.12184

Cited by 24 publications

(17 citation statements)

References 86 publications

(172 reference statements)

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“…Value remains the most prominent variable in order to increase the occupancy percentage. Previous research has supported the importance of cleanliness of franchise properties over that of chain-managed properties (Lawrence & Perrigot, 2015); the findings of this study are consistent with those of past studies.…”

Section: Franchisedsupporting

confidence: 92%

“…Bilim and Basoda (2014) found that while consumers pay attention to many different issues, services and related areas are considered to be the prevalent. Lawrence and Perrigot (2015) found that customers were more satisfied with the level of service received at companyowned hotels over that of franchise hotels. The various service components that make customer satisfied may also make them dissatisfied if they are not provided or are found to be delivered inadequately (Berezina et al, 2016).…”

Section: Cleanlinessmentioning

confidence: 97%

“…Previous research identifies that franchise properties outperformed company-owned hotels on cleanliness (Lawrence & Perrigot, 2015); however, there was a gap in the literature to address the cleanliness of independent hotels. The findings of this study support that cleanliness is indeed a concern of guests, and the ratings of such have an impact on the ADR and RevPar.…”

Section: Independentsmentioning

confidence: 99%

“…It is also important for a hotel to easily be locatable (Darini & Khozaei, 2016;Khoo-Lattimore & Ekiz, 2014). Lawrence and Perrigot (2015) found that customers were more satisfied with the location of company-owned units than with the location of units owned by franchisees. In order to generate customer satisfaction, both location and accessibility are important, as they help customers find the hotel easily, provide a pleasant view of the surroundings, and save the customer time when visiting nearby places of interest (Sim, Mak, & Jones, 2006).…”

Section: Locationmentioning

confidence: 99%

“…Customers frequently mention that they appreciate when the rooms, lobby, café, and restaurant are clean (Darini & Khozaei, 2016). Franchise units were found to outperform company-owned hotels with regards to satisfaction for cleanliness measures taken (Lawrence & Perrigot, 2015). Abramova, Shavanova, Fuhrer, Krasnova, and Buxmann (2015) found that cleanliness was a controllable variable by the host and led to higher negative reviews when not addressed properly.…”

Section: Cleanlinessmentioning

confidence: 99%

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An examination of online ratings on hotel performance indicators: An analysis of the Boston hotel market

Markham-Bagnera

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CHAPTER 4: RESULTS AND DISCUSSION ………………………………………….. RevPar) be explained by the independent variables (i.e. cleanliness, location, room, service, staff, value and overall)? Research Contribution While there have been a variety of studies on the use of TripAdvisor and the concept behind it, this would be a first-of-its-kind study, wherein data from TripAdvisor would be compared to the data from Smith Travel Research (STR) in a year-over-year change in popularity rankings and revenue generation. Specifically, this study will be examined in one hotel market, one of the top 25 major markets as identified by STR; hence, this study could be replicated for the other markets, in order to examine the same growth potential in popularity and revenue. Based on future market studies, the identification and establishment of additional theories can then be applied. Definition of Terms Consumer-Generated Media (CGM): non-commercial, detailed, experiential, and up-to-date information, with others outside of the immediate social circle (K. H. Yoo & Gretzel, 2011). Consumer Opinion Portal (COP): a portal through which an online review is published and available for other potential travelers to read and use to make informed decisions (Banyai, 2012; Burton & Khammash, 2010). Electronic Word-of-Mouth (eWOM): any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet (Hennig-Thurau et al., 2004). This category also incorporates a large volume, as 31% of the hotels are rated into this category. The final category, "Budget-oriented," is a hotel that offers "basic comfort and hospitality" (American Automobile Association, n.d.). This is the second smallest category, with only 3% of the hotels ranked here. For the purposes of this study, hotels in the Boston market between the two-to five-diamond levels will be analyzed. The Boston market hosts an extensive variety of luxury-related service properties. According to a recent article, the Boston market is considered to have a high concentration of four and five diamond properties (Stenning, 2016). The sheer volume of properties designates Boston as one of the top five members of the lodging industry. Accordingly, it has been suggested by Bagnera (2016) that "Diamonds really speak to the amount and the quality of services and amenities that are available to the guests" (Stenning, 2016). Management Johnston (1994) examined the literature for an explanation of operations management, as it focuses on the task of managing the process or system for the production of goods and services from labor, plan and machinery, materials, and information. It is a body of knowledge, experience, and techniques covering topics like process design, layout, production planning, inventory control, quality management and control, capacity planning, and workforce management (Johnston, 1994). Kay and Moncarz (2004) examine the various knowledge, skills, and abilities (KSAs) of hotel ma...

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Section: Franchisedsupporting

confidence: 92%

Section: Cleanlinessmentioning

confidence: 97%

Section: Independentsmentioning

confidence: 99%

Section: Locationmentioning

confidence: 99%

Section: Cleanlinessmentioning

confidence: 99%

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An examination of online ratings on hotel performance indicators: An analysis of the Boston hotel market

Markham-Bagnera

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AI‐Driven Sentiment Analysis for Retail Management: A Graph‐Based DSS Comparing Franchise and Company‐Owned Stores

Baray,

Cliquet

2024

Manage Decis Econ

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This paper introduces an AI‐driven Decision Support System (DSS) for sentiment analysis of customer reviews in Starbucks UK. The methodology involves three main steps: collecting customer reviews from trusted sources, applying AI‐driven preprocessing techniques to extract key attributes, and using Graph Machine Learning techniques to unveil customer satisfaction. A new Graph‐Based Sentiment Analysis Algorithm is proposed to extract object–sentiment pairs from each comment and model relationships through a graph‐based approach. Results indicate a superior performance in terms of accuracy and efficiency compared to cell‐based methods. The analysis identifies drivers of customer satisfaction, including value for money, quality experience, and ambiance.

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Does Yelp Matter? Analyzing (And Guide to Using) Ratings for a Quick Serve Restaurant Chain

Gadidov

Priestley

2017

Studies in Big Data

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Influence of Organizational Form and Customer Type on Online Customer Satisfaction Ratings

Cited by 24 publications

References 86 publications

An examination of online ratings on hotel performance indicators: An analysis of the Boston hotel market

An examination of online ratings on hotel performance indicators: An analysis of the Boston hotel market

AI‐Driven Sentiment Analysis for Retail Management: A Graph‐Based DSS Comparing Franchise and Company‐Owned Stores

Does Yelp Matter? Analyzing (And Guide to Using) Ratings for a Quick Serve Restaurant Chain

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