Why am I satisfied? See my reviews – Price and location matter in the restaurant industry

Kim, Jaewook; Lee, Minwoo; Kwon, Wooseok; Park, Hyekyung; Back, Ki‐Joon

doi:10.1016/j.ijhm.2021.103111

Cited by 24 publications

(21 citation statements)

References 55 publications

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“…Pricing decisions play an important role in marketing strategy because they determine where the price should be put in relation to other variables such as the smartphone life cycle, sales targets, and market share. In fact, pricing is a good indicator of product quality, and high-value brands are referred to as "wonderful brands" (Kim, Lee, Kwon, Pak, & Back (2022). Furthermore, because the nature of a smartphone is standard and can be easily proved, a higher price may hinder consumer loyalty because it may not be an indication of superior quality and may only draw attention to the fact that there is more money that needs to be spent.…”

Section: Pricementioning

confidence: 99%

The Relationship Between Marketing Mix and Customer Loyalty among Malaysian Smartphone Users

Rahim¹,

Bakar²,

Muhamed³

et al. 2022

IJARBSS

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This paper seeks to discuss the role of marketing mix 4Ps model (product, price, place and promotion) on the relationship with customer loyalty among Malaysia smartphone users. Smartphone have become almost inseparable in today's digital world. This growth is being stimulated by a variety of factors including social distancing, affordable price, trending lifestyle, more usage of smartphone capabilities, aggressive marketing campaign and robust business strategies by smartphone brands. This paper recommended that all of the marketing mix variables namely; product, price, place, and promotion, have positive significant with customer loyalty specifically among smartphones users in Malaysia. Thus, companies will be required to embrace the variables that, in turn, will enable them to develop effective and efficient plans that incorporate the criteria described in order to increase customer loyalty.

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Section: Pricementioning

confidence: 99%

The Relationship Between Marketing Mix and Customer Loyalty among Malaysian Smartphone Users

Rahim¹,

Bakar²,

Muhamed³

et al. 2022

IJARBSS

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“…The 50 states in the USA were categorized into six regions from STR's nine regional categorizations, combining New England and the Middle Atlantic into New England, combining East North Central and West North Central into North Central, et al, 2014) during the business intelligence process. SentiWordNet 3.0 is mostly used for sentiment classification and evaluation (Kim et al, 2022;Lee et al, 2017) and measures a degree of sentiment ranging from À1 (extremely negative) to 1 (extremely positive) based on the positive, negative and objective words in each review.…”

Section: Methodsmentioning

confidence: 99%

“…(Cho et al , 2014) during the business intelligence process. SentiWordNet 3.0 is mostly used for sentiment classification and evaluation (Kim et al , 2022; Lee et al , 2017) and measures a degree of sentiment ranging from −1 (extremely negative) to 1 (extremely positive) based on the positive, negative and objective words in each review.…”

Section: Methodsmentioning

confidence: 99%

“…Online review studies (Jeong and Jeon, 2008; O’Connor, 2010) have demonstrated that many customers rely on reviews for their purchase decision-making and vacation planning. Recently, Kim et al (2022) suggested that online reviews with photos, comments and other service evaluation factors increase potential customers’ understanding of the products and services they would consume. Furthermore, online reviews are among the most critical information resources and social influences for customers to evaluate alternative products/services, hospitality firms’ business performance and innovative services (Kwon et al , 2021; Lee et al , 2021).…”

Section: Research Backgroundmentioning

confidence: 99%

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Assessing brand performance consistency from consumer-generated media: the US hotel industry

Jeong

Shin

Lee

et al. 2022

IJCHM

Self Cite

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Purpose Given the importance of performance consistency of chain hotels in customers’ decision-making and service evaluation, this study aims to explore how consistently chain hotel brands offer quality service and carry out their performance from the eyes of customers through online reviews on TripAdvisor of the top five US hotel chains (i.e. Choice, Hilton, InterContinental, Marriott and Wyndham) and their brands. Design/methodology/approach The research objectives were achieved through methodological triangulation: business intelligence, data visualization analytics and statistical analyses. First, the data collection and pre-processing of consumer-generated media (CGM) (i.e. TripAdvisor online reviews) were performed using business intelligence for further analyses. Using data visualization analytics (i.e. box-and-whisker plot by region and brand), the geographic patterns of performance attributes (i.e. online review ratings, including location, sleep, cleanliness, room and service) were depicted. Using a series of analyses of variance and regression analyses, the results were further assessed for the impacts of brand performance inconsistency on consumers’ perceived value, sentiment and satisfaction. Findings The empirical results demonstrate that there are significant performance inconsistencies in performance attributes (location, sleep, cleanliness, room and service) by brands throughout the six regions in the US hotel market. More importantly, the findings confirm that brand performance consistency significantly influences consumers’ perceived service quality (i.e. perceived value, satisfaction and sentiment). Originality This study is one of the first attempts to empirically explore hotel brand performance consistency in the US hotel market from customer reviews on CGM. To measure hotel brand performance in the US hotel market, this study collected and analyzed user-generated big data for the top 5 US hotel chains through business intelligence, visualization analytics and statistical analysis. These integrated and novel research methods would help tourism and hospitality researchers analyze big data in an innovative data analytics approach. The findings of the study contribute to the tourism and hospitality field by confirming hotel brand performance inconsistency and such inconsistent performance affected customers’ service evaluations. Practical Implications This study demonstrates the significant impact of hotel brand performance consistency on consumers’ perceived value, emotion and satisfaction. Considering that online reviews are perceived as a credible source of information, the findings suggest that the hotel industry pays special attention to brand performance consistency to improve consumers’ perceived value, emotion and satisfaction.

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“…Choi et al (2022) examined the effects of six dimensions including food quality, service quality, atmosphere, convenience, price and vegetarian menu options, on the CS of vegetarian customers and found that only price and vegetarian menu options had significant positive effects on vegetarian customers' satisfaction. Kim et al (2022) investigated the impact of customers' service perception in online reviews on CS and revealed the importance of price and location in the restaurant industry. In the same vein as the restaurant type, the moderating role of cultural origin and generation gap was also uncovered by extant literature (Harrington et al, 2012;Jia, 2020;Nakayama and Wan, 2018).…”

Section: Dining Experience Customer Satisfaction and Revisit Intentionmentioning

confidence: 99%

Modeling customer satisfaction and revisit intention from online restaurant reviews: an attribute-level analysis

Zhao

Liu

2023

IMDS

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PurposeThe purpose of this paper is to detect predefined service attributes and their sentiments from online restaurant reviews, and then to measure the effects of customer sentiments toward service attributes on customer satisfaction (CS) and revisit intention (RVI) simultaneously.Design/methodology/approachThis study proposed a supervised framework to model CS and RVI simultaneously from restaurant reviews. Specifically, the authors detected the predefined service dimensions from online reviews based on random forest. Then, the sentiment polarities of the reviews toward each predefined dimension were identified using light-gradient boosting machine (LightGBM). Finally, the effects of attribute-specific sentiments on CS and RVI were evaluated by a bagged neural network-based model. The proposed framework was evaluated by 305,000 restaurant comments collected from DianPing.com, a Yelp-like website in China.FindingsThe authors obtained a hierarchal importance order of the investigated service themes (i.e. location, service, environment, price and food). The authors found that food played the most important role in affecting both CS and RVI. The most salient attribute with respect to each service theme was also identified.Originality/valueUnlike prior work relying on the data collected from surveys, this study is among the first to model the relationship among service attributes, CS and RVI simultaneously from real-world data. The authors established a hierarchal structure of eighteen attributes within five service themes and estimated their effects on both CS and RVI, which will broaden our understanding of customer perception and behavioral intention during service consumption.

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Why am I satisfied? See my reviews – Price and location matter in the restaurant industry

Cited by 24 publications

References 55 publications

The Relationship Between Marketing Mix and Customer Loyalty among Malaysian Smartphone Users

The Relationship Between Marketing Mix and Customer Loyalty among Malaysian Smartphone Users

Assessing brand performance consistency from consumer-generated media: the US hotel industry

Modeling customer satisfaction and revisit intention from online restaurant reviews: an attribute-level analysis

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