تاثیرات ویژگی های مصرف کنندگان بر ادراک منصفانه از قیمت گذاری مدیریت درآمد در صنعت هتلداری

Fairness perceptions play an important role in customers’ behavior, and this study explores which consumer characteristics influence fairness perceptions of revenue management (RM) pricing in the hotel context. To examine such differentiating characteristics, the study conducts a logit analysis by comparing two groups: one group of customers who consider hotels’ RM practices to be fair and the other group considers the practices to be unfair. The findings provide an opportunity for hotel managers to identify customers’ particular characteristics that affect customer's perceptions of the fairness of hotels’ RM pricing practices.

Revenue management (RM, hereafter), also known as yield management, refers to selling perishable service products to the most profitable mix of customers to maximize revenue (Cross, 1997). The airline industry was the initial implementer of RM, and subsequently has had wide acceptance among capacity-constrained service industries to maximize revenue by effectively managing demand and capacity (Weatherford and Bodily, 1992). RM has become an indispensable strategic instrument in the hospitality industry; for example, the hotel industry routinely uses RM to maximize profits by obtaining revenues from rooms that would otherwise be unsold (Choi and Mattila, 2004). RM aims to maximize revenues by charging premium prices when demand is high and lowering prices to stimulate demand when demand is low. RM involves several operational processes, such as segmenting customers, setting prices and rate fences, and controlling capacity to maximize the revenue generated from fixed capacity (Kimes, 1989). Among others, pricing policy is a key element of RM in the hospitality industry. However, consumers may possibly perceive such RM practices as unfair because RM results in a variety of rates for what appears to be identical facilities (Choi and Mattila, 2005). Perceptions of price fairness play an important role in customer satisfaction and subsequent behavior (Oliver and Swan, 1989 and Bei and Chiao, 2001). Extreme reactions occur when consumers feel they have been unfairly treated, especially when the company provides no valid alternative (Seiders and Berry, 1998). For example, people may sanction a business by avoiding repeat custom, by spreading negative word-of-mouth recommendations, or even by using violence (Bougie et al., 2003). Research by Kahneman et al. (1986) showed that consumers are even willing to disadvantage themselves to punish a seller who, they perceived, acted unfairly. Shoemaker (2003) argued that RM can have an adverse effect on customers’ perceptions of the service company, resulting in destroyed customer loyalty. If consumers perceive RM as an unfair policy, consumers’ negative perceptions lead to decreased customer satisfaction and consequently to a worsening of the company's economic success (Lindenmeier and Tscheulin, 2008). Considering the importance of perceived fairness, an essential understanding is the major factors influencing customers’ fairness perceptions of RM pricing among hospitality companies that implement and use RM techniques. However, research, especially in service industry contexts (Bolton and Alba, 2006) of this topic has been sparse until recently (Homburg et al., 2005 and Xia et al., 2004). Previous research has considered price fairness evaluations in reference to past prices and price increases (Bolton and Alba, 2006 and Homburg et al., 2005), and mainly in a context of physical goods (Martín-Ruiz and ondán-Cataluña, 2008). The purpose of the current study, therefore, is to explore consumers’ fairness perceptions toward RM practices in the hotel industry. In particular, the study examines how consumers’ characteristics relate to fairness perceptions of RM pricing. The study performs a logistic regression to identify different consumers’ characteristics between two groups, that is, those with perceptions of fairness and those with perceptions of unfairness. This study provides two main contributions to the revenue management literature. First, the study examines effects of various demographic characteristics (i.e., age, income, gender, and education) along with two important factors (i.e., frequency of use and price consciousness) on consumers’ perceptions of fairness of RM practices. Different from previous studies, such as Beldona and Namasivayam (2006), this study includes all six factors in the model and simultaneously examines them together. By doing so, this study identifies partial effects of each factor while controlling for other factors. Second, this study performs a logistic regression analysis to accomplish the proposed goals. As Xia et al. (2004) argued, price unfairness is a different concept from price fairness, and price fairness may not be an issue until consumers perceive prices to be unfair. Therefore, logistic regression analysis has been selected as an appropriate method, as opposed to choosing regression analysis with the dependent variable as a continuous variable. For the analysis, this study also uses three different data subsets based on the degree of fair/unfairness perception. By performing the logistic regression analysis for the three groups, some characteristics cause extreme unfairness perceptions and others do not. These findings would not have been apparent if the analysis were only a regression analysis with a continuous dependent variable. Next, the study reviews the relevant literature and describes the methodology. Hypotheses and results follow, and conclusions complete the study.

The objective of this study is to examine what consumers’ characteristics influence their fairness perceptions of RM practices in the hotel context. The study compared two groups: one group that perceives hotels’ RM practices as fair and the other group that perceives the practices as unfair to reveal hotel guests’ differentiating characteristics in terms of their fairness perceptions of RM practices. The study conducts a logistic analysis to accomplish the study goal. In testing the proposed hypotheses, the study compares the fair and unfair group that includes the most respondents (main model); the (un)fair group consists of the respondents who answered, ‘somewhat (un)fair’, ‘(un)fair’, and ‘very (un)fair.’ The study further compares the two additional sub-groups; Model A consists of the respondents who answered, ‘(un)fair’, and ‘very (un)fair’ while Model B consists of the respondents who answered, ‘very (un)fair.’ The main model comparison reveals that more frequent users of hotels, younger hotel guests, and more educated people tend to perceive hotels’ RM practices to be fair, compared to their counterparts. In addition to these main findings that are based on hypothesis testing, this study compared the two additional sub-groups and found some interesting results: first, hotel guests’ household income seems to play a marginally significant role in differentiating the fair group from the unfair group throughout all three model comparisons in that people with higher household incomes perceive RM practices to be fair at a marginal significance level. Second, some unique findings exist for the two additional model comparisons: hotel guests’ price consciousness and genders become significant factors while the education levels become an insignificant factor for differentiating the very fair and very unfair group in Model B. Based on the findings about hotel guests’ household income levels, hoteliers, according to a particular brand or hotel property, may want to develop their RM strategies differently. Full-service or luxury hotel brands or properties may be able to more comfortably and rigorously explore the use of RM practices because their customers tend to show a higher level of fairness perceptions toward such practices. Thus hotels may increase revenues through RM practices, especially the variable pricing strategy based on demand level, without damaging their customers’ fairness perceptions. On the other hand, economy or budget brands or properties may want to be very cautious about implementing RM practices due to the finding that their customers tend to perceive such practices as unfair. Consequently, RM practices may hurt the budget-oriented hotels’ performance in a long run. However, further examination may illuminate this issue because this study's implications are based on the assumption that hotel guests with higher income levels stay at hotels in a higher price-range. Moreover, this implication is made without considering other various rate fences which may cause different outcomes in customers’ perceptions. With regard to gender effect on fairness perceptions, our findings for the entire sample do not support the argument of previous research that females are more sensitive to fairness (Adams, 1965 and Beldona and Namasivayam, 2006). However, an additional analysis that compares only the very fair and very unfair group revealed the gender effect to be significant, suggesting that more females than males perceive the RM practices as very unfair. According to our findings, the gender effect does not exist throughout the all different levels of fairness perceptions, but only for an extreme case, and this is interesting because some of the previous studies’ general findings about the gender effect might be driven from such extreme cases. However, according to Sweeney and McFarlin (1997), fairness perceptions among women and men are different in terms of both procedural and distributive fairness, and thus further detailed investigation on the two types of fairness are strongly encouraged and will enrich the RM literature. From a practical perspective, hoteliers may incorporate the gender effect in their market segment development or sales practices. For example, they may use the gender difference information when developing their target markets. Some overlooked market segments may be identified when focusing on male guests rather than females, even when basing decisions on existing market segments. One important finding among members of the extreme groups (very fair vs. very unfair) is about the price consciousness that differentiates the two groups. The analysis revealed a negative relationship between the price consciousness and fairness perceptions, suggesting that price conscious hotel guests tend to perceive hotels’ RM practices as more unfair, supporting previous studies (for example, Han et al., 2001 and Sinha and Batra, 1999). The findings may provide an important insight to hoteliers, especially, in the current economic downturns where many hotels competitively offer discounted rates to survive. Because of such prevalent discounting practice, average room rates are expected to decline more than 9% from 2008 to June 2009 (Smith, 2009). Although many hoteliers have believed that discounting room rate is necessary to sustain revenue and to steal market share, the demand for hotels has been found to be inelastic to such discounting practice (Carroll, 1986, Enz, 2003 and Enz et al., 2009). Moreover, deeply discounted rates may reduce customer's reference price and increase price conscious customers’ unfairness perceptions of RM pricing without boosting occupancy to offset the rate decline. Therefore, hotels need to make pricing decisions carefully by clearly limiting the bottom line of their discounted rate even during economic downturns. This argument can be also aligned with previous findings that it takes considerable amount of time for hotels to recover from such discounted rates (Wolff, 2004) and also there are negative long-term effects from the discounting practice (Enz et al., 2009). In addition, findings of this study may be used as a basis to suggest that hoteliers need to develop various types of rate fences to allow guests to distinguish each transaction (or product). Use of rate fences (either physical or non-physical) makes differences for service offerings from a customer's perspective, rendering RM pricing strategies effective. For example, hotels frequently charge different prices for weekdays and weekends without additional rate fences, because hoteliers believe those are different service products. The important issue is whether or not customers really perceive those to be different service offerings. Xia et al. (2004) extended social-comparison theory to pricing and suggested that customers compare transactions and prices paid. When the degree of perceived similarity between transactions is high, customers have little differential information to justify price differences, and thus customers are likely to believe that they are entitled to equivalent prices and are likely to view price differences as unfair (Xia et al., 2004). Consequently, when the degree of perceived similarity between transactions is low, more hotel guests may perceive RM pricing to be fair. For this reason, hotels need to improve customers’ awareness that all transactions are not alike, so customers, in particular those who are price conscious, can distinguish the transactions. During peak periods, when charging premium prices, hotels may add amenities (e.g., free wireless internet or free breakfast) to justify a higher price than the lower one during slow periods. In addition, considering that females, more than males, tend to perceive RM practices to be very unfair, hotels may seek to develop more female-oriented rate fences to mediate such strong negative perceptions held by females. For example, hotels may include amenities that females prefer (e.g., complimentary spa, massage pass or travel makeup kit) when practicing variable pricing policies. The study is not free from limitations. First, since data from this study were collected from students (undergraduates and graduates) and staff members of one university, results may not be generalized to an overall population. Collecting more general observations from various sources is desirable, especially to improve generalizability. Also this study assumed that survey participants make their own reservations, but business travelers often have a personal assistant who reserves accommodations, and thus the use of frequency as a measure may not correctly represent familiarity with RM pricing and price knowledge. In addition, it is possible that two constructs, the price consciousness and the frequency of use, are partially overlapped. Therefore, this study performed an additional analysis without the price consciousness to see if any changes would occur. The results from the modified model, however, confirmed the same effects of the frequency of use and other demographic variables on customers’ fairness perceptions as found from the original model. Last, several other elaborations are possible. Perhaps future research could incorporate the influences of reference prices and brand loyalty for each consumer into the fairness perceptions measurement. Future research may also explore the relationship of consumers’ characteristics within the constructs of procedural, distributive and interactional fairness, and consider different degrees of monetary advantage or disadvantage.