REVENUE MANAGEMENT PRACTICES IN RESTAURANT INDUSTRY VS AIRLINE/HOTEL INDUSTRIES: A CONSUMER PERCEPTION STUDY ABSTRACT

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1 REVENUE MANAGEMENT PRACTICES IN RESTAURANT INDUSTRY VS AIRLINE/HOTEL INDUSTRIES: A CONSUMER PERCEPTION STUDY Reza Etemad-Sajadi Ecole Hôtelière Lausanne (EHL) Lausanne, Switzerland reza.etemad@ehl.ch and Arnaud Durand Ecole Hôtelière Lausanne (EHL) Lausanne, Switzerland arnaud.durand@ehl.ch ABSTRACT Revenue management can be defined as the application of information systems and pricing strategies to allocate the right capacity to the right customer at the right place at the right time (Kimes and Wirtz, 2003; Weatherford and Bodily, 1992). These practices are well known for airlines and hotels and seem to be well accepted by the clients in these two industries. The customers seem to understand the process and to see the benefit for them. The idea of this research is to see how customers can perceive the fairness of these practices in the restaurant industry, compared to the two industries mentioned above. Key Words: revenue management, restaurant/hotel/airline industries, fairness, customer perception, pricing strategy INTRODUCTION Theory shows that restaurant managers will increase their income by using revenue management technics. But these practices are underused (Kimes, 2004). One of the major reasons comes from the fact that it can be perceived negatively and unfairly. Customers seem to find these practices not acceptable in this sector. An unfair perception will influence the customers behaviour with the risk of diminishing attendances of the establishment (Kahneman et al., 1986a). Revenue management strategies will only be successful if customers perceive them to be fair (Kimes and Wirtz, 2003; Bei and Chiao, 2001). Thus knowing what customers are ready to accept becomes a crucial question. The aim of this paper is: - To define revenue management practices in restaurant industry. - To evaluate the customers perception of these practices. - To compare the customers perception of practices in airline, hotel and restaurant industries. Based on the manner revenue management practices will be perceived by the different profile of clients, we want to know more about their behaviour in the future. Revenue management PROBLEM BACKGROUND Revenue management or yield management as it was firstly called in airline industry is the application of analytic tools that predicts consumer behaviour and optimizes product availability and price in order to maximize revenue growth (Cross, 1997). The challenge is to understand customers' perception of product value and accurately aligning product prices, placement and availability with each customer segment (Cross, 1997). For Kimes (2004), a good revenue management strategy consists of the use of two levers i) duration control and ii) demand based pricing. As mentioned above, the airline was the first industry to develop these practices in the early 70s by implementing deeply discounted fare products to fill seats that would otherwise stay empty (Cross et al., 2009). To control the risk of revenue dilution (high fare passengers shift to the newly discounted fare) they put in place restrictions (Cross et al., 2009). These practices can achieve a consequent increase in revenue for hospitality industry (Sanket and Bowman, 2004). Airline, hotel and rental car are the three major traditional industries where revenue management has been applied (Chiang & al., 2007). Because of its success in these industries, researchers and practitioners have

2 begun trying to adopt it in a wide range of industries such as restaurants, casinos, etc. (Chiang et al., 2007). The common points with those different industries are fixe capacity, perishable inventory, demand inventory, time variable demand, appropriate cost structure and segmentable customers (Kimes, 2004). In fact a lot of service providers can take advantage of revenue management. As pricing policy is a key element of revenue management, the degree of fairness perceived by the customers plays an important role in their satisfaction (Bei and Chiao, 2001). Other consequence of an unfair perception can be the negative word of mouth about the company (Bougie et al., 2003). Fairness of these practices as perceived by customers Fairness perception is the judgment of whether or not customers accept an outcome and/or a transaction process (Bolton et al., 2003). Previous researches about the fairness perceived have examined the effects of the rate fences when they are associated with i) the surcharge or the discount in price, ii) the information given (or not) to the customer about the pricing policy and iii) the knowledge (or not) about a reference price. The Table 1 developed by Heo and Lee (2011) summarized the most important research done on fairness perceptions of revenue management in the hospitality industry. By the use of scenarios researchers examined the impact on the fairness perception of the customers. Kimes (1994) studied the perceived fairness of several pricing policy in airline and hotel industries. The pricing policy was based on the i) day of booking, ii) discount asked (customers who did not insist on a lower rate received no discount, customers who insisted for a lower rate received 10-20% discount), iii) familiarity with discount (no discount if customer does not ask) and iv) cancellation penalties. She found that revenue management practices are less acceptable in hotel industry compared to airline industry. Kimes repeated this study in 2002 and found that there was no difference in fairness perception between the two industries. Customers accepted more and more these practices in hotel industry. Kimes and Wirtz (2002) studied revenue management applied to golf industry. The pricing policy was based on the i) time of day, ii) time of booking, iii) two for one coupon, iv) reservation fee, v) no show fee, vi) varying price levels and vii) tee time interval. Golfers perceive arrival duration control practices in the form of reservation fees or no-show fees as fair. Moreover clients perceive demand-based pricing in the form of coupons (two for the price of one), time of day and reduced tee time intervals as fair. Time of booking pricing was perceived as neutral to slightly unfair. Kimes and Wirtz (2003b) tried to apply revenue management to restaurant industry. The pricing policy was based on i) lunch/dinner period, ii) weekday/weekend period, iii) time of the day, iv) table location, v) two for one coupons. They found that revenue management pricing in the form of coupons, time of day pricing and lunch/dinner pricing are considered to be fairer compared to the other practices. Choi and Mattila (2005) found that consumers who receive no information about pricing policy as i) day of the week, ii) weekday/weekend, iii) length of stay and iv) day of booking, judged that the process was unfair. It seems therefore important and fair to communicate the pricing policy to clients. They expected to be informed. Wirtz and Kimes (2007) found that framing and fencing conditions (i.e. whether a respondent was advantaged or disadvantaged by revenue management practices) have strong effects on fairness perceptions when customers are less familiar with revenue management pricing. This involves taking time to explain to customers the advantages for them. The impact of demographic characteristics of customers on the fairness perceived Comparing the profile of clients, Beldona and Namasivayam (2006) examined the impact of gender on the fairness perceived and the repurchase intentions. They found that female customers perceived these practices significantly less fair across all pricing scenarios in both discount and surplus frames. Sweeney and McFarlin (1997) found that women reacted more strongly to evidence of procedural fairness than men. Rosa Diaz (2004) found that women were more aware of prices compared to men. Another variable, that is often used, is the age of respondents. Heo and Lee (2011) found that younger hotel guests judged more acceptable the price variability and revenue management practices. As far as the influence of the respondent s income is concerned, Rosa Diaz (2004) found that customers with a low income were more knowledgeable about prices. Finally Choi and Mattila (2006) found that US consumers perceived the variability of prices and the application of these practices more fair and acceptable, compared to Korean consumers. The cultural dimension seems to have an impact on the fairness perceived. It can also be explained by the fact that in US, clients are more often confronted with these practices in other industries.

3 Table 1 Summary of research on fairness perceptions of RM in the hospitality industry (Heo and Lee, 2011) Author(s) Title Industry Pricing Policy Kimes (1994) Perceived fairness of yield management Airline and hotel Day of booking, discount asked, familiarity with discount, cancellation penalties Kimes and Wirtz (2002) Perceived fairness of revenue management in the US golf industry Golf industry Time of day, two for one coupon, time of booking, reservation fee, no show fee, varying price levels, tee time interval pricing Kimes (2002) Perceived fairness of yield management Airline and hotel Day of booking, discount asked, familiarity with discount, cancellation penalties Kimes and Wirtz (2002) Perceived fairness of demand-based pricing for restaurants Restaurant Lunch/dinner, weekday/weekend, time of the day, table location, two for one coupons Kimes and Wirtz, (2003a, b) Has revenue management become acceptable? Restaurant Lunch/dinner, weekday/weekend, time of day, table location, two for one coupons Choi and Mattila (2004) revenue management and its impact on customers perceptions of fairness Day of the week, weekday/weekend, length of stay, day of booking Choi and Mattila (2005) Impact of Information on Customer Fairness Perceptions of Revenue Management Day of the week, length of stay, day of booking Choi and Mattila (2006) The role of disclosure in variable hotel pricing: a crosscultural comparison of customers fairness perceptions Day of the week, length of stay, day of booking Beldona and Namasivayam (2006) Gender and demandbased pricing: differences in perceived (un)fairness and re-patronage intentions Seasonality, day of booking, weekday/weekend Wirtz and Kimes (2007) The moderating role of familiarity of fairness perceptions of revenue management pricing Restaurant Lunch/dinner, duration The impact of cultural orientation on Beldona and Kwansa (2008) perceived fairness over demand-based pricing Source: Heo and Lee (2011), readapted. Seasonality, booking date, weekday/weekend

4 FRAMEWORK In this article, we decided to select the following restaurant revenue management practices: price variability based on the period a) lunch/dinner, b) weekday/weekend, c) time of the day (e.g. between 2 pm and 4 pm, cheaper price), d) location of the table (e.g. table view, space, etc.), e) speed of service (e.g. fast vs normal service), f) date of booking (e.g. reduction if the client books more than 4 days in advance or full price without reservation), g) number of people at the table (e.g. cheaper if more than 6 people) and finally h) time spent at the table. As far as the demographic characteristics are concerned, we kept the age, gender and income into account. The Figure 1 shows our framework. Figure 1 Research framework METHOD An on-line survey was conducted for a convenience sample. Thus, the sampling method is nonprobabilistic. We received 126 answers. However, 12 questionnaires were incomplete. Thus, the final sample consists of 114 respondents. The questionnaire was composed of three parts. First we started with questions related to customers perception of revenue management practices applied to restaurant (mid-scale restaurants). The respondents were asked to give their perception on a scale from 1 (totally unfair) to 4 (totally fair). With this scale, we wanted to make them choose between fair and unfair. However they also had the possibility to mention no opinion, in a column added on the right side of the scale. The second part of the questionnaire concerned respondents perception of revenue management practices applied to airline, hotel and restaurant industries. This part was useful to compare the fairness perceived by respondents for each of these industries. Finally the third part of the questionnaire concerned personal data on the respondent s profile. We normalized the indicators in order to measure the correlations. We used SPSS for the quantitative analysis.

5 RESULTS The Figure 2 shows the degree of fairness perceived by customers for revenue management practices linked to restaurant industry. In general these practices are almost all rejected in our research. The only practice that seems to be acceptable by customers is the price variation between lunch and dinner (mean = 2.53). The second fairest practice is the price variation based on the date of booking (mean = 2.29). However this value is lower than 2.50 and thus seems to be also judged somehow unacceptable. The most unfairly felt practice is the price variation based on time spent at the table (mean = 1.41). Customers seem to reject totally this practice. The practices, based on table location (mean = 1.78) and speed of service (mean = 1.82), are also perceived as unfair. Figure 2 Customers perception of restaurant revenue management practices (1 = totally unfair, 4 = totally fair) The Table 2 shows ANOVA results comparing men and women respondents. Instead of the price variability based on time spent at the table, men seem to accept more restaurant revenue management practices. However the two practices with a significant difference are price variation based on the date of booking and the number of people at the table (respectively F = and F = 4.634). It confirms the findings in other articles and the sources aforementioned in our problem background chapter.

6 Table 2 Comparison between man and woman respondents: ANOVA results Mean Min Max ANOVA p-value Price variation Men Women (F) a) Lunch/dinner b) Weekend/weekday c) Time of the day d) Table location e) Speed of service f) Date of booking * g) Number of people at * the table h) Time spent at the table Note: * Significant at the 0.05 level. Comparing between the three industries (airline, hotel and restaurant), the Figure 3 confirms that customers judge the variation of price unfair for restaurant industry. On a scale from 1 (totally unfair) to 4 (totally fair), the mean is equal to For hotel industry the mean is equal to 2.77 and for airline industry the mean is equal to Customers find fairer the application of revenue management to airline industry. The application of revenue management to hotel industry seems to be also positively perceived. It is higher than the average but not so much. Despite the fact that revenue management practices are well known and accepted for airline and hotel industries, they are not acceptable by the clients in restaurant industry. The customers seem to accept the rules of price variability in airline and hotel industries, but they do not see the benefit for them in restaurant industry. Figure 3 Fairness perceived by customers for each industry (1 = totally unfair, 4 = totally fair) The Table 3 shows that the respondent s age influences significantly the answers. The correlation is negative. It means that older respondents find these practices more unfair than younger respondents. This is the case for the three industries. This result confirms the findings in other publications. The correlation is also negative between the respondent s income and its perception of the degree of fairness of these practices. However as the correlation between the age and income is high, we must be careful with this finding. In other words, we are not sure if the influence of the income on the fairness is due to the link with the age or not. The age seems to influence more the fairness perceived, compared to the income.

7 Table 3 Correlation between variables Variables Age 1 2. Income.593** 1 3. Fairness of these practices perceived in airline industry -.351** -.274** 1 4. Fairness of these practices perceived in hotel industry -.265** -.195*.691** 1 5. Fairness of these practices perceived in restaurant industry -.237** -.179*.347**.452** 1 Notes: * Significant at the 0.05 level. ** Significant at the 0.01 level. CONCLUSION Revenue management practices are well known for airline/hotel industries and customers seem to accept the price variation in these two industries. But customers don t see the benefit for them in restaurant industry. Women judge more unfair these practices in the three industries. Moreover younger customers seem to accept more these practices. It confirms the research done by Heo and Lee (2011) where they found that younger clients tend to perceive hotels revenue management practices fairer than older clients. As it took time for these practices to be more acceptable in hotel industry, it will maybe take more time to render these practices acceptable in restaurant industry. It seems that customers are not yet ready for that. It can be interesting to make the same research in five or ten years and see an eventual evolution in the general perception. It was the case between the two researches done by Kimes in 1994 and Kimes (1994) found a significant difference of perception of these practices between airline and hotel industries. However in 2002, Kimes found that revenue management practices in the two industries have the same level of acceptability. As far as the restaurant industry is concerned, Wirtz and Kimes (2007) argued that as the customers become more and more familiar with these practices, the unfairness perception can decline over time. The firms who want to apply revenue management practices must educate their clients. It seems important to insure that customers see the advantages of these practices for themselves. This is the first think to keep in mind before applying these practices. REFERENCES Bei, L.T. & Chiao, Y. (2001). The determinants of customer loyalty: an analysis of intangible factors in three service industries. International Journal of Commerce and Management, 16(3/4): Beldona, S. & Namasivayam, K. (2006). Gender and demand-based pricing: differences in perceived (un)fairness and repatronage intentions. Journal of Hospitality and Leisure Marketing, 14(4): Beldona, S. & Kwansa, F. (2008). The impact of cultural orientation on perceived fairness over demand-based pricing. International Journal of Hospitality Management, 27(4): Bolton, L.E., Warlop, L. & Alba, J.W. (2003). Consumer perception of price (un)fairness. Journal of Consumer Research, 29(4): Bougie, R., Pieters, R. & Zeelenberg, M. (2003). Angry customers don t come back, they get back: the experience and behavioral implications of anger and dissatisfaction in services. Journal of the Academy of Marketing Science, 31(4): Chiang, W.C., Chen, J.C.H. & Xu, X. (2007). An overview of research on revenue management current issues and future research. International Journal of Revenue Management, 1(1): Choi, S. & Mattila, A.S. (2004). revenue management and its impact on customers perceptions of fairness. Journal of Revenue and Pricing Management, 2(4):

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