How do Benefit and Cost Shape Perceived Value of Hotel Stays?
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1 University of Massachusetts Amherst Amherst Tourism Travel and Research Association: Advancing Tourism Research Globally 2016 ttra International Conference How do Benefit and Cost Shape Perceived Value of Hotel Stays? Xingbao Hu Temple University, Yang Yang Temple University, Follow this and additional works at: Hu, Xingbao and Yang, Yang, "How do Benefit and Cost Shape Perceived Value of Hotel Stays?" (2016). Tourism Travel and Research Association: Advancing Tourism Research Globally This Event is brought to you for free and open access by Amherst. It has been accepted for inclusion in Tourism Travel and Research Association: Advancing Tourism Research Globally by an authorized administrator of Amherst. For more information, please contact
2 How do Benefit and Cost Shape Perceived Value of Hotel Stays? Abstract: Hotel online reviews are important for hoteliers because they provide the aggregated digital footprints of tourists experience and behavior. This paper explores the effects of hotel attributes, reviewer attributes, experience attributes, and their interactions on hotel customers perceived value, with a special focus on the relationship between benefit and cost in shaping customers perceived value of hotel stays. A sample consists of 39,222 reviews from 166 hotels in Los Angeles was extracted from TripAdvisor. Mix effect ordered logit model was employed. Results shows that hotel price and hotel reputation (star level and overall rating) negatively affects perceived value. Customers experience quality positively affects perceived value and moderates the effect of price on perceived value. Customers review expertise positively affects perceived value, but negatively moderates the effect of experience quality on perceived value. Findings support social exchange theory and expectation disconfirmation theory. Some marketing practices are recommended based on the findings. Keywords: hotel, online review, benefit, cost, perceived value Introduction Along with the advancement of new technologies and the wide-spread adaptation of these technologies in the hospitality industry, travelers increasingly rely on online reviews before the travel and heavily involve in posting reviews after their trips (Kim, Mattila and Baloglu, 2011). Previous studies have recognized that perceived value has a significant impact on travelers satisfaction, loyalty, revisit-intentions, and word of mouth (Al-Sabbahy, Ekinci and Riley, 2004; Grewal, Monroe and Krishnan, 1998; Lai, 2015; Oh, 1999; Petrick, 2002). However, few studies examine travelers perception of experience in hotels from the perspective of perceived value by analyzing hotels online reviews. There is still much unknown regarding the perceive value of hotel stays, for example, the relationship between price and satisfaction in shaping the perceived value. The present study aims to abridge this gap by understanding the impacts of hotel attributes, reviewer attributes, experience attributes, and their interactions on hotel customers perceived values based on a mixed effect ordered logit model. Special attention is paid to the relationship between benefit and cost in shaping the perceived value. Literature review and Hypotheses According to Y. H. Kim, Duncan, and Chung (2014), perceived value is the customer s overall appraisal of the net worth of the service or products based on their assessment of benefits they received as against what is offered (costs or sacrificed time, and efforts). Nasution and Mavondo (2008) propose a distinctive definition and regarded perceived value as a trade-off between total benefits and total sacrifices (costs) customers perceived. Trade-off can be viewed as the gap between perceived benefits and sacrifices or costs. Existing studies suggest that perceived value is influenced by three types of variables: 1) hotel attributes, such as hotel price (Botanic,1996; Derbaix and Pham,1991; Oh, 1999; Petrick, 2002; Ye, Li, Wang and Law, 2014), star level (Ye et al., 2014), and hotel overall rating(xie, Zhang and Zhang, 2014); 2) reviewer attributes, e.g. reviewers review expertise (Caltabiano,1983; Weaver, Weber and McCleary, 2007) and past review experience (Kim, Mattila and Baloglu, 2011; Mackiewicz, 2009; Zou, Yu and Hao, 2011); and 3) experience attributes, including reviewers rating of experience (Nasution and Mavondo, 1
3 2008) and the performance of hotel attributes (Ekinci,2004; Lockyer, 2002; Oguchi, Okamoto, Shimizu and Matsushima, 2004). Hence, six hypotheses were proposed as follows: Hypothesis 1: Transaction price is negatively associated with hotel guests perceived value. Hypothesis 2: Customers ratings of their experience in hotels influence perceived value. Hypothesis 3: Customers ratings of their experience moderates the effect of price on perceived value. Hypothesis 4: Customers expertise moderates the effect of ratings on perceived value. Hypothesis 5: Customers review experience moderates the effect of rating on perceived value. Hypothesis 6: The performance of hotel attributes, including cleanliness, location, room, quality of service, and sleep quality, affect perceived value. Methodology Data collection Online reviews of hotels in Los Angeles, the second biggest metropolitan areas in the United States, were crawled on TripAdvisor website between November 15, 2016 and December 15, 2015 through a web spider: Bazhuayu. The data collected involves attributes of hotels (name, address, star, overall rating, location, price, and rank), hotel performance (ratings of room quality, service, sleep, cleanliness, location, and value), and characteristics of reviewers (age, gender, number of cities visited, membership level, total membership points). Totally 96,633 online reviews of 231 hotels in Los Angeles were collected. Then hotels with review amount less than 60 were excluded, resulting a sample consisting of 39,222 reviews for 166 hotels in Los Angeles. Empirical model To evaluate the research hypotheses proposed previously, we use a mixed effect ordered logit model. In this model, the dependent variable is a five-point ordinal measure of perceived value score posted on the TripAdvisor. The model is able to accommodate the multi-level structure of data with the reviewer-level information nested within the property level. The mixed-effect ordered logit model is commonly presented as a latent variable model. Defining y as a latent variable ranging from to +, the structural model is y X * ij ij i ij where j indexes the reviewer and i indexes the hotel property. The measurement model for divide y into M ordinal categories: yij m if * m 1 y ij for m 1 to M m where the cut-points τ 1 through τm 1 are estimated. We assume τ0 = and τj = +. In our model, based on the five point scale of value measure, M = 5. The error term ij distributed as logistic with mean 0 and variance π 2 /3 and are independent of i, which is the hotel-property-specific effect. In the proposed econometric model, dependent variable is five-point value score evaluated by the reviewer based on his/her stay in the hotel property. There are four categories of independent 2
4 variables: hotel attributes, reviewer attributes, experience attributes, and interactions. Hotel attributes include hotel price, hotel reputation (measured by hotel star level and overall rating), and volume of hotel online reviews. Reviewer attributes include reviewer total points and volume of reviews. Experience attributes include experience rating, cleanliness rating, location rating, room rating, service rating, and sleep rating. Three interactions are included, including interaction between reviewer total points and experience rating, interaction between volume of reviewers reviews and experience rating, and interaction between price and experience rating. Among these, hotel reputation (including star levels and overall ratings) and the volume of the hotel s total reviews are control variables. Before testing the model, the multicollinearity of independent variables were examined, and the VIFs for all independent variables are smaller than 5, indicating there is no multicollinearity problem in the model. Results The model test results support hypotheses 1, 2, 3, 4, and 6, but not hypotheses 5. In terms of hotel attributes, the result indicates that 1) hotel prices, i.e. economic cost, have significant negative effect on hotel guests perceived value; 2) hotel reputation (measured by hotel star and hotel overall rating) have significant negative influence on perceived value; and 3) volume of hotel reviews does not significantly affect perceived value. Hotel price and hotel reputation set up customers expectation for the hotel experience and both have negative effects on perceived value. The negative impact of hotel reputation on perceived value is different from the findings in some previous studies (Cui, Yang and Hou, 2009) but is consistent with some others (Li and Hitt, 2010; Ye, Li, Wang and Law, 2014). In terms of reviewer attributes, the result reveals that customers expertise (measured by total points) has a positive effect on perceived value, but it negatively moderates the effect of experience quality on perceived value. No sufficient evidence show that past experience (measured by the volume of reviewer s total reviews) negatively affects perceived value, and past experience does not significantly moderate the effect of experience rating on perceived value, either. These results imply that reviewers who have higher total points, i.e. who provide more, detailed, and serious reviews are more friendly customers. However, the volume of reviews a reviewer posted could not tell if the reviewer is picky or not. These are new findings which have not been mentioned in previous studies. In terms of experience attributes, the result shows that customer experience quality (measured by experience rating) positively affects perceived value, and it positively moderates the impact of price on perceived value; and hotel experience attributes (including the ratings of cleanliness, location, room, service, and sleep quality) positively influences perceived value. Experience attributes represent customers perceived sub-benefits. Their positive impacts and hotel prices negative impacts on customer perceived value imply that social exchange theory could also work in explaining hotel customers perceived value. Conclusion Using hotel reviews data of 166 Los Angeles hotels from 2012 to 2015, this study applied a mixedeffect ordered logit model to understand how perceived value is shaped by hotel attributes, reviewer attributes, experience attributes, and interactions among them. Compared to existing related studies, the method in this study is more rigid and allows hotels to estimate the probability 3
5 of different perceived values a certain customer would have. The results are consistent with Asgarpour, Hamid, Sulaiman and Asgari (2015) s finding that the gap between expectations formed by reading target hotels attributes information (e.g. star level, rank, and rating) and actual experiences will affect customers perceived value. Some new relationships are found in this research, such as the negative impacts of reviewers membership points on perceived value. Results provide several important implications for hoteliers who endeavor to improve their values to customers. First, hotel operators may provide some discounts to these reviewers who have higher total points. It is because as suggested by social exchange theory, the less economic costs reviewers spend, the more positive reviews they would post, and these reviewers typically post more, detailed, and positive reviews. Second, hotel operators should keep in mind that hiring people posting fake positive reviews does not necessarily lead to a long-term success. As implied by expectation disconfirmation theory (Oliver, 1977), although high price, high star levels, and high overall rating may improve hotels image to a certain degree, they also set up customers high expectation on the experience, which usually negatively affects customers perceived value. Third, improving customers experience quality should always be the priority on the agenda of the hotel operators because experience attributes are the most important positive determinants of hotel customer perceived value. Some limitations may temper the generalizability of our results. First, we do not consider other cost-related variable as such travel costs. Second, reviewers may pay different rates for the same hotel, and we are unable to get the data on the exact transaction price. Therefore, we recommend future studies to incorporate more precise and comprehensive cost measures to understand the value model using big data. References Al-Sabbahy, H. Z., Ekinci, Y., and M. Riley (2004). An investigation of perceived value dimensions: Implications for hospitality research. Journal of Travel Research, 42(3): Asgarpour, R., A. B. A. Hamid, Z. B.Sulaiman, and A. A. Asgari (2015). Efficiency or Inefficiency of Customer Satisfaction as One of the Main Antecedents of Customer Loyalty in Tourism and Hospitality Industry. Advanced Science Letters, 21(6): Bojanic, D. C. (1996). Consumer Perceptions of Price, Value and Satisfaction in the Hotel Industry. Journal of Hospitality and Leisure Marketing, 4(1): Cui, L., H. Yang, and H. Hou (2009). A Study of Perceived Quality and Price: Customer Valuebased Pricing Strategy. Paper presented at the ICVE & VM 2009: Proceedings of the 2nd International Conference on Value Engineering and ValueManagement. Beijing, China. Derbaix, C., and M. T. Pham (1991). Affective Reactions to Consumption Situations: A Pilot Investigation. Journal of Economic Psychology, 12(2): Ekinci, Y. (2004). An Investigation of the Determinants of Customer Satisfaction. Tourism Analysis, 8(2-4):
6 Grewal, D., K. B. Monroe, and R. Krishnan (1998). The Effects of Price-Comparison Advertising on Buyers' Perceptions of Acquisition Value, Transaction Value, and Behavioral Intentions. Journal of Marketing, 62(2): Guillet, B. D., and R. Law (2010). Analyzing Hotel Star Ratings on Third-party Distribution Websites. International Journal of Contemporary Hospitality Management, 22(6): Kim, E. E. K., A. S. Mattila, and S. Baloglu (2011). Effects of Gender and Expertise on Consumers Motivation to Read Online Hotel Reviews. Cornell Hospitality Quarterly, 52(4): Kim, Y. H., J. Duncan, and B. W. Chung (2014). Involvement, Satisfaction, Perceived Value, and Revisit Intention: A Case Study of a Food Festival. Journal of Culinary Science and Technology, 13(2): Lai, I. K. W. (2015). Traveler Acceptance of an App-Based Mobile Tour Guide. Journal of Hospitality and Tourism Research, 39(3): Li, X., and L. M. Hitt (2010). Price effects in online product reviews: an analytical model and empirical analysis. MIS quarterly, 34(4): Lockyer, T. (2002). Business guests Accommodation Selection: The View from Both Sides. International Journal of Contemporary Hospitality Management, 14(6): Mackiewicz, J. (2009). Assertions of Expertise in Online Product Reviews. Journal of Business and Technical Communication, 24(1): Moe, W., and M. Trusov, (2011). The Value of Social Dynamics in Online Product Ratings Forums. Journal of Marketing Research, 48(3): Mohsin, A., and T. Lockyer (2010). Customer Perceptions of Service Quality in Luxury Hotels in New Delhi, India: An Exploratory Study. International Journal of Contemporary Hospitality Management, 22(2): Moliner, M. A., J. Sánchez, R. M. Rodríguez, and L. Callarisa (2007). Relationship Quality With a Travel Agency: The Influence of the Postpurchase Perceived Value of a Tourism package. Tourism and Hospitality Research, 7(3-4): Nasution, H. N., and F. T. Mavondo (2008). Customer Value in the hotel Industry: What Managers Believe They Deliver and What Customer Experience. International Journal of Hospitality Management, 27(2): Oguchi, T., N. Okamoto, M. Shimizu, and K. Matsushima (2004). Factors Predictive of Consumers Satisfaction with Hotels through Analysis of Internet Evaluations on a Travel Website. In: Proceedings of the Asia Pacific Tourism Association 10 th Annual Conference (pp ). Nagasaki, Japan. Oh, H. (1999). Service quality, Customer Satisfaction, and Customer Value: A Holistic Perspective. International Journal of Hospitality Management, 18(1): Oh, H., M. Jeong, S. Baloglu, M. Erdem, P. Brewer, and K. Mayer (2010). Evaluating Stability of the Performance-satisfaction Relationship across Selected Lodging Market Segments. International Journal of Contemporary Hospitality Management, 22(7):
7 Oliver, R. L. (1977). Effect of Expectation and Disconfirmation on Postexposure Product Evaluations: An alternative interpretation. Journal of Applied Psychology, 62(4): 480. Pearce, P. L., and M. Caltabiano (1983). Inferring Travel Motivation from Travelers Experiences. Journal of Travel Research, 22 (2): Petrick, J. F. (2002). Development of a Multi-dimensional Scale for Measuring the Perceived Value of a Service. Journal of Leisure Research, 34(2): Schlosser, A. (2005). Posting versus Lurking: Communicating in a Multiple Audience Context. Journal of Consumer Research, 32(2): Weaver, P. A., K. Weber, and K. W. McCleary (2007). Destination Evaluation: The Role of Previous Travel Experience and Trip Characteristics. Journal of Travel Research, 45(3): Xie, K. L., Z. Zhang, and Z. Zhang (2014). The Business Value of Online Consumer Reviews and Management Response to Hotel Performance. International Journal of Hospitality Management, 43: Ye, Q., Li, H., Z. Wang, and R. Law (2014). The Influence of Hotel Price on Perceived Service Quality and Value in E-tourism: An Empirical Investigation Based on Online Traveler Reviews. Journal of Hospitality and Tourism Research, 38(1): Zou, P., B.Yu, and Y. Hao (2011). Does the Valence of Online Consumer Reviews Matter for Consumer Decision Making? The Moderating Role of Consumer Expertise. Journal of computers, 6(3):
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