Spillover Effects of Status Demotion on Customer Reactions to Loyalty Reward Promotions: The Role of Need for Status and Exclusivity

Abstract

Prior research demonstrates that status demotion in the loyalty reward program heightens negative emotions, particularly when demotion is due to changes in company policies. In this research, we argue that such negative emotions are likely to spillover to evaluations of post-demotion promotions. We further argue that such spillover effects should be attenuated among individuals high in need for status. Study 1 examines the joint effect of the cause of demotion and customers’ need for status on loyalty. In study 2, we investigate the impact of exclusivity cues in post-demotion promotions and show that exclusive promotions diminish the negative impact of policy-based demotions on post-promotion loyalty among individuals high (vs. low) in need for status. Travel and tourism companies might want to consider using geographical location as a proxy for need for status or priming status-seeking via exclusive promotions (“elevate your travel experience”) to alleviate demoted customers’ negative emotions.

Keywords

demotion status loyalty exclusivity loyalty reward program

Introduction

Loyalty reward programs are omnipresent in the travel and tourism industry across rental car companies (Avis Preferred), cruise companies (Carnival cruise line’s VIFP Club), and online travel agencies (Orbitz Rewards). Prior research indicates that US companies spend more than $1.2 billion annually in implementing loyalty reward programs, and program participation has reached a record high of 2.6 billion members (Steinhoff and Palmatier 2016). It is well known that conquering new customers is more expensive than retaining existing ones, and therefore, travel and tourism companies execute loyalty reward programs to improve customer retention (Xie and Chen 2013) and to maximize customer lifetime value (Wang et al. 2016).

In hierarchical loyalty programs, loyalty tiers are determined by the customer’s spending level, and companies award exclusive benefits to those who have achieved a high tier (Dreze and Nunes 2009). Costa Cruises, for instance, offers access to the Club restaurant and home luggage pickup and delivery for their top-tier members (Leppert 2016). Rental car companies allow their preferred members to skip the lines or to have no blackout dates (e.g., Avis Preferred and Enterprise Plus). Prior research has mainly focused on the positive consequences of status promotion and concomitant benefits (e.g., Baloglu, Zhong, and Tanford 2017; Morais, Dorsch, and Backman 2004; McCall and Voorhees 2010; Tanford 2013; Tanford, Raab, and Kim 2011; Terblanche 2015; Xie et al. 2015; Wong and Lam 2016; Yi and Jeon 2003). For instance, Tanford (2013) demonstrates that both attitudinal (e.g., emotional attachment) and behavioral loyalty (e.g., word of mouth) are highest among hotel guests in the premier tier-level.

However, customers can be demoted when their spending does not meet the required level or when the company changes its loyalty program policies. For instance, United Airlines and Starbucks revamped their loyalty program in a way that customers accrue mileage/stars based on the amount spent, as opposed to miles flown/frequency of visits (Bender 2015; Synder 2016). These changes resulted in an outcry among many loyal customers who turned to social media to express their dissatisfaction. Customers may also feel demoted when preferential treatment associated with their tier level is reduced or removed. For example, United Airlines announced to cut its meal options for elite and first-class flyers on certain domestic flights. They also reduced the number of complimentary alcohol and nonalcohol beverage options (Genter 2018).

In fact, previous research suggests that the dampening effect of status demotion is greater than the positive effect of status promotion on loyalty (Wagner, Hennig-Thurau, and Rudolph 2009). The travel and tourism literature has examined preferences for loyalty reward types (Hwang and Mattila 2018), the impact of program benefits on loyalty (Baloglu, Zhong, and Tanford 2017; Dolnicar et al. 2011; Tanford 2013), relationship quality (Lo and Im 2014), and membership utilization/renewal rates (Aluri, Price, and McIntyre 2019). However, to date, there is limited research on how customers respond to loyalty reward promotions once demoted. Companies often send out promotions to their loyalty program members, and consequently, demoted customers are likely to encounter such communications. For instance, the InterContinental Hotel Group launched its “Accelerate 2017” campaign enabling customers to earn extra reward points for hotel stays during certain time periods (Ollila 2017).

In this article, we investigate how negative emotions from status demotion may spillover to evaluations of post-demotion promotions, which in turn influence post-promotion loyalty. Previous research clearly shows that customer emotions are more negative after policy-based (vs. spending-based) demotions (Hwang and Kwon 2016; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009). We propose that such negative emotions are likely to be salient when customers are exposed to post-demotion promotions, and therefore, customer loyalty is likely to decrease. In study 1, we propose a boundary condition for the spillover effect—customers’ need for status. Post-demotion promotions tend to offer an opportunity to regain lost status, and as such, they should buffer the negative impact of policy-based demotions on loyalty among customers high in need for status. Conversely, individuals low in need for status are not as interested in such promotions. Consequently, the negative spillover effect of policy-based (vs. spending-based) demotions is likely to occur, thus lowering loyalty.

In Study 2, we examine a boundary condition for the interaction between cause of demotion and need for status, namely, exclusivity cues in post-demotion promotions. Exclusivity refers to the degree to which promotions are available to a narrow (vs. broad) range of customers, and companies use wording such as “special,” “exclusive,” and “limited offer” to signal exclusivity. There is ample evidence to suggest that products are perceived as more desirable when they are exclusive (vs. inclusive) in nature, particularly among consumers high in need for uniqueness (e.g., Barone and Roy 2010; Steinhart et al. 2014). As such, we argue that exclusive post-demotion promotions are effective in buffering the negative impact of policy-based demotions on loyalty among individuals high in need for status. Conversely, individuals low in need for status tend to be sensitive to equality concerns, and therefore, they are more likely to prefer inclusive promotions. In sum, this research advances our understanding of customer responses to post-demotion promotions, and as such, it provides important implications to practitioners implementing loyalty reward programs in the travel and tourism industry.

Review of Literature for Study 1

Status Demotion

Status can be defined as “a relative standing in a group based on honor and prestige” (Thye 2000, 411). Status demotion refers to “a relocation of a person in a lower social position with lessened authority and lowered power to control certain resources” (Gephart 1978, 559). In the context of hierarchical loyalty programs, status demotion occurs when the customer’s loyalty tier is lowered, thus reducing chances of preferential treatment. Research on status demotion has grown since Wagner, Hennig-Thurau, and Rudolph’s (2009) seminal work. Recent research has examined various factors such as program involvement (e.g., Hwang and Kwon 2016; Mathies and Gudergan 2012; Shin and Park 2014), magnitude of demotion (e.g., Mutter and Kundisch 2014), cause of demotion (e.g., Hwang and Kwon 2016; Lepthien et al. 2017; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009), payment source (e.g., Ramaseshan, Stein, and Rabbanee 2016), monetary compensation (e.g., Lepthien et al. 2017; Wagner, Hennig-Thurau, and Rudolph 2009), and pre-demotion tier level (e.g., Ramaseshan and Ouschan 2017; Shin and Park 2014; Wang et al. 2016).

Prior research has focused on two causes of status demotion: decreased spending and policy changes (Hwang and Kwon 2016; Lepthien et al. 2017; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009). We rely on the attribution theory (e.g., Folkes 1988; Heider 1958; Weiner 2000) suggesting that an individual tends to infer a cause(s) for an event to himself or herself (internal attribution) or to external factors (external attribution). Accordingly, we propose that when the customer’s status is demoted as a result of his or her decreased spending (policy changes), the customer is likely to attribute the cause of demotion to himself or herself (the company). Causal attributions are particularly relevant for negative events in the travel and tourism context (Choi and Cai 2016), including service failures in the airline context (Nikbin et al. 2014; Weber and Sparks 2010), unethical tourist behaviors (Breitsohl and Garrod 2016), and perceived unfairness regarding airline auxiliary fees (Chung and Petrick 2013). This stream of travel and tourism literature demonstrates that consumers’ external attributions for negative events tend to decrease satisfaction in the airline (Choi and Cai 2016), destination (Breitsohl and Garrod 2016), and theme park context (Tsang, Prideaux, and Lee 2016). Similarly, external attributions for demotion heighten negative emotions (e.g., Wagner, Hennig-Thurau, and Rudolph 2009) and reduce loyalty (e.g., Hwang and Kwon 2016; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009). Previous research further shows that negative word of mouth (WOM) and switching intention are more likely when status demotion is due to company policies (vs. decreased spending) (Hwang and Kwon 2016; van Berlo, Bloemer, and Blazevic 2014). In sum, there is ample evidence to suggest that status demotion due to policy changes is perceived more negatively than demotion due to decreased spending.

In this research, we argue that negative reactions to policy-based (vs. spending-based) demotions are likely to spillover to customer evaluations of post-demotion promotions. Loyalty reward promotions in the hierarchical loyalty program tend to emphasize opportunities to rapidly achieve higher tiers. United Airlines, for example, doubled mileage earned through First or Business Class tickets in 2016 with a slogan “Reach Premier status even faster next year.” Research on spillover effects (Lemon and Wangenheim 2009; Schumann, Wünderlich, and Evanschitzky 2014) shows that negative evaluations about the company may decrease evaluations about other partnered companies in coalition loyalty programs (e.g., Plenti Rewards Program has Macy’s, Exxon Mobil, and AT&T). Likewise, we suggest that negative emotions toward policy-based (vs. spending-based) demotions are likely to spillover to evaluations of post-demotion promotions, which in turn, decrease loyalty.

The Moderating Role of Need for Status

In this research, we further argue that spillover effects of demotion on post-demotion promotions may depend on the customer’s need for status. Previous work in the travel and tourism literature posits that need for status influences consumer experiences and choices (Correia, Kozak, and Reis 2016). Need for status refers to an individual’s motivational state to improve his or her relative standing in a society, thereby acquiring aspiration and respect from others (Dubois, Rucker, and Galinsky 2012; Eastman, Goldsmith, and Flynn 1999). That is, customers high in need for status are motivated to regain their pre-demotion tier level. Prior research demonstrates that individuals high in need for status tend to engage in conspicuous consumption because they believe that higher status is related to greater benefits and privileges (Han, Nunes, and Drèze 2010). In this research, post-demotion promotions that help customers high in need for status to regain their status might lessen the negative impact of policy-based demotions on loyalty. In other words, individuals high in need for status should exhibit uniformly high levels of post-promotion loyalty across the two demotion types (policy changes and decreased spending).

Conversely, we suggest that individuals low in need for status are likely to exhibit lower levels of post-promotion loyalty when demoted because of policy changes (vs. decreased spending). Individuals low in need for status are not highly motivated to restore their lost loyalty tier, thus making post-demotion promotions less relevant. Previous research demonstrates that personal relevance is a critical antecedent for persuasion (Andrews, Durvasula, and Akhter 1990). We thus suggest that the negative spillover effect from policy-based (vs. spending-based) demotions is likely to occur among individuals low in need for status. In other words, customers low in need for status are likely to exhibit lower levels of post-promotion loyalty when demoted because of policy changes (vs. decreased spending).

Formally, we put forth the following predictions:

Hypothesis 1: The negative spillover effect of policy-based (vs. spending-based) demotions is moderated by customers’ need for status. Specifically,

Hypothesis 1a: Customers low in need for status will exhibit lower levels of post-promotion loyalty when demotion is due to policy changes (vs. decreased spending).

Hypothesis 1b: Such differences in loyalty are likely to disappear among customers high in need for status.

The Mediating Role of Negative Emotions

Prior research in the travel and tourism literature demonstrates the importance of customer emotions as antecedents of customer satisfaction and loyalty (Faullant, Matzler, and Mooradian 2011; Prayag, Hosany, and Odeh 2013; Prayag et al. 2017; Yüksel and Yüksel 2007). For instance, relying on Hosany and Gilbert’s (2010) Destination Emotion Scale (DES), Prayag et al. (2017) show that positive surprise during a leisure trip is positively related to overall satisfaction, while Prayag, Hosany, and Odeh (2013) show that joy, love, and positive surprise all are related to satisfaction. Congruent with such previous findings, it is likely that negative emotions reduce satisfaction and loyalty. Specifically, prior research in organizational behavior posits that status demotion results in negative emotions (Smith 2002). Wagner, Hennig-Thurau, and Rudolph’s (2009) work on status demotion examined anger (e.g., angry and annoyed). In addition to anger, the present research examines feelings of betrayal (e.g., Grégoire, Tripp, and Legoux 2009). Feelings of betrayal are important, especially when customers have a strong relationship with a company (Grégoire, Tripp, and Legoux 2009). High-tier customers typically have earned their status via loyalty. Thus, capturing betrayal is relevant in the status demotion context. Previous research in the hierarchical loyalty program context shows that negative affect is related to switching intention (e.g., Hwang and Kwon 2016) and loyalty intention (e.g., Wagner, Hennig-Thurau, and Rudolph 2009). Because of spillover effects (e.g., Lemon and Wangenheim 2009; Schumann, Wünderlich, and Evanschitzky 2014), policy-based (vs. spending-based) demotions are likely to result in greater levels of negative reactions to post-demotion promotions among individuals low in need for status. Such negative feelings, in turn, are likely to have an adverse effect on post-promotion loyalty (Hwang and Kwon 2016; Wagner, Hennig-Thurau, and Rudolph 2009). In other words, negative emotions are the underlying mechanism explaining the impact of the cause of demotion on post-promotion loyalty among customers low in need for status. Conversely, we posit that such a mediation is unlikely among customers high in need for status as post-demotion promotions are expected to satisfy their motivation to regain lost status. Formally, we put forth the following prediction:

Hypothesis 2: Negative emotions (anger and betrayal) will mediate the impact of the cause of demotion on post-promotion loyalty among individuals low in need for status. Such a mediation is unlikely among individuals high in need for status.

The conceptual model is in Table 1 and we test hypotheses 1 and 2 in study 1.

Table 1.

Overview of Studies.

Study 1	Study 2
Conceptual model	Conceptual model

Design 2 (cause of demotion: decreased spending level vs. policy changes) by 2 (need for status: low vs. high) quasi-experimental design	Design 2 (cause of demotion) by 2 (need for status) by 2 (exclusivity cues in post-demotion promotions: inclusive vs. exclusive) quasi-experimental design
Results Hypotheses 1-2 are supported	Results Hypothesis 3 is supported

Study 1. The Impact of the Cause of Demotion and Need for Status on Post-promotion Loyalty

Methods

Study 1 employed a 2 (cause of demotion: decreased spending level vs. policy changes) by 2 (need for status: low vs. high) quasi-experimental design where the cause of status demotion was manipulated and need for status was measured. Our target population is US consumers who have recently stayed at a hotel, and thus we pre-screened participants for their hotel stay frequency during the past six months. This inclusion criterion is congruent with previous research on status demotion (Mathies and Gudergan 2012). Fifty-eight participants were recruited through Amazon Mechanical Turk (MTurk) in July 2017. MTurk is a crowd-sourced online participant pool, and prior studies show that data from MTurk ensure demographic diversity (Buhrmester, Kwang, and Gosling 2011). Prior research in status demotion in the loyalty reward program context used student samples (Shin and Park 2014; van Berlo, Bloemer, and Blazevic 2014) or participants in a certain age group (the 20s; Hwang and Kwon 2016). Thus, we believe that our sample is more representative than a student sample or a sample focusing on a particular age group. We paid $.50 to each participant.

Participants were randomly assigned to one of the two conditions and asked to imagine that they were a loyal customer of Hotel ABCD and that there were four tiers in the hotel’s loyalty program (Platinum, Gold, Silver, and Blue). The cause of status demotion was manipulated by stating that the downgrading was a result of a new company policy or a result of the focal customer’s reduced spending level during the past year. Following status demotion, they were asked to imagine that the hotel emailed them a new loyalty reward promotion (“Stay two nights or more and double your loyalty tier credit”). The stimuli are shown in Appendix A. Next, loyalty intention, negative emotions, manipulation checks, scenario realism, need for status, and demographics were measured.

Measures

Loyalty was measured by asking the extent to which they agree with the four statements (e.g., “I would recommend the hotel to someone who seeks my advice (1=strongly disagree, 7=strongly agree) (Zeithaml, Berry, and Parasuraman 1996) (α=.97). Negative emotions were measured with three items (e.g., “How angry/ annoyed/ betrayed would you feel in the scenario?”) (bipolar; 1=not at all, 7=very much) (Grégoire, Tripp, and Legoux 2009; Wagner, Hennig-Thurau, and Rudolph 2009) (α=.95). To check the manipulation for the cause of demotion, we had two items (e.g., “Thinking about the reason why your loyalty tier was lowered, is the cause something . . .”) (bipolar, 1=that reflects an aspect of yourself, 7=that reflects an aspect of the company) (Russell 1982) (r=.92, p <.01). Scenario realism was measured with two items (e.g., “The scenario was realistic”) (1=not at all, 7=very much) (Wu, Mattila, and Hanks 2015) (r=.59, p <.01). Need for status was measured with four items (e.g., “I have a desire to increase my position in the social hierarchy”) (1=strongly disagree, 7=strongly agree) (Dubois, Rucker, and Galinsky 2012) (α=.93). All survey measures are shown in Appendix B.

Results

Demographics

Participants’ age ranged from 20 to 46. (M=32.03, SD=6.81). They were 55.2% male, and 55.2% had a college degree. About forty-one percent of the participants had an annual household income between $40,000 and $79,999. Forty-three percent of the participants are currently or have been a member of a hotel loyalty program.

Manipulation checks

Overall, participants perceived the scenarios as realistic (M=5.50, SD=1.36). To check the manipulation for the cause of demotion, we ran an independent samples t test. The results showed that when status demotion was due to policy changes (vs. a decreased number of nights of hotel stay), participants attributed the cause of demotion to the hotel (M_{decreased spending} =4.08, M_{policy changes} = 5.52), t(56)=3.13, p <.01. Thus, our manipulation was effective.

Post-promotion loyalty

We regressed post-promotion loyalty on the cause of demotion, mean-centered need for status, and their interaction. The results showed that the overall model was significant, F(3, 54)=4.61, p<.01, as well as the interaction, t(54)=−2.89, p<.01 (see Table 2). The results of a spotlight analysis (e.g., Spiller et al. 2013) showed that when need for status was low (i.e., one standard deviation lower than the mean), the cause of demotion was significantly related to loyalty (Coefficient=−1.94, SE=0.56, t=−3.48, p<.01). That is, participants whose status was demoted because of company policy (vs. their decreased spending) exhibited lower levels of loyalty, supporting hypothesis 1a. Conversely, when need for status was high (i.e., one standard higher than the mean), the cause of demotion was not significantly related to loyalty (Coefficient=0.36, SE=0.56, t=.65, p>.1), supporting hypothesis 1b (see Figure 1b). Therefore, hypothesis 1 is fully supported.

Table 2.

Regression Results from Study 1.

Model	Unstandardized Coefficient		Standardized Coefficient	t	p
Model	b	SE	b_standardized	t	p
Constant	4.28	0.27		15.76	<.001
Cause of demotion	−0.79	0.39	−0.25	−2.02	.05
Need for status	−0.16	0.16	−0.15	−0.97	.34
Interaction	0.72	0.25	0.46	2.89	<.01

Loyalty as a dependent variable. Adjusted R²=.20.

Figure 1.

Spotlight analysis results from study 1.

Moderated mediation

To test hypothesis 2, we conducted a moderated mediation analysis (Hayes 2013; bias-corrected bootstrap sample=5,000, Model 8). Moderated mediation was significant (coefficient: 0.34, SE=0.21, 95% CI = 0.00 to 0.83). Moreover, negative emotions mediated the impact of the cause of demotion on loyalty when participants’ need for status was one standard deviation lower than the mean (coefficient= −1.15, SE=0.48, 95% CI = −2.29 to −0.41). However, negative emotions did not mediate such a relationship when need for status was one standard deviation higher than the mean (coefficient= −0.05, SE=0.39, 95% CI = −0.85 to 0.70). Taken together, these results provide support for hypothesis 2. The results are summarized in Table 3.

Table 3.

Moderated Mediation Results from Study 1.

Antecedent		Consequent
		M (Negative Emotions)				Y (Loyalty)
		Coeff.	SE	p		Coeff.	SE	p
X (Cause)	a_1i	3.99	1.35	<.01	c’	−1.67	0.90	.07
M (Negative emotions)		–	–	–	b _i	−0.49	0.08	<.01
V (Need for status)	a_2i	0.38	0.21	.07	c₂’	0.03	0.13	.83
X × V	a_3i	−0.70	0.32	.03	c₃’	0.37	0.20	.07
Constant	i₁	1.51	0.88	.09	i ₂	5.63	0.56	<.01
		R² = .17F(3, 54) = 3.72, p<.05				R² = .52F(4, 53) = 14.10, p<.01

Discussion

The findings from study 1 provide support for the moderating role of need for status in influencing spillover effects of the cause of demotion on post-demotion promotions and post-promotion loyalty. Congruent with previous research (Breitsohl and Garrod 2016; Choi and Cai 2016; Hwang and Kwon 2016; Lepthien et al. 2017; Tsang, Prideaux, and Lee 2016; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009), participants low in need for status showed lower levels of loyalty when the demotion was due to policy changes (vs. decreased spending). Negative emotions toward the promotion are the underlying mechanism explaining the adverse effect of policy-based demotions on post-promotion loyalty among low need in status individuals. Conversely, post-demotion promotions enable customers high in need for status to regain their lost status (e.g., Correia, Kozak, and Reis 2016; Dubois, Rucker, and Galinsky 2012; Eastman, Goldsmith, and Flynn 1999), thus lessening the negative impact of policy-based demotions. Accordingly, participants high in need for status showed no difference in loyalty across the two demotion conditions.¹ In study 2, we investigate how exclusivity cues in a post-demotion promotion interact with the cause of demotion and need for status.

Review of Literature for Study 2

The Role of Exclusivity Cues in Post-demotion Promotions

We argue that exclusivity cues in post-demotion promotions are likely to moderate the interactive effect of the cause of demotion and need for status on post-promotion loyalty. Exclusivity refers to the extent to which the promotion is available only to several (vs. many) customers (Barone and Roy 2010). Companies often use exclusive promotions (e.g., “special offers limited to the top 5% of our customers”) to reward loyal customers based on their transaction histories (Barone and Roy 2010). On the other hand, less exclusive offers are available to a broader range of customers (e.g., “100 bonus reward points on your first booking with us”). Previous research in behavioral pricing demonstrates that consumers are motivated to pursue a relative advantage over others when seeking exclusive deals (Barone and Roy 2010). That is, promotions that are available only to a few customers are likely to elicit the feeling of being chosen, thus leading to perceptions of a higher standing compared to others who did not receive such exclusive promotions.

We propose that exclusive post-demotion promotions are particularly effective in reducing the negative spillover effects of policy-based demotions on loyalty among customers high in need for status. The commodity theory posits that positive feelings of “being selected” are heightened by opportunities for gaining a scarce commodity (Brock 1968). Because customers high in need for status are inclined to increase their relative standing in a society, feelings of being chosen and honored may be highly salient to them. Similarly, prior research demonstrates that exclusivity of a product primes status-seeking (Gierl and Huettl 2010). Therefore, we argue that customers high in need for status are likely to evaluate exclusive post-demotion promotions positively irrespective of the type of demotion (i.e., policy-based vs. spending-based). Consequently, post-promotion loyalty should remain uniformly high among customers high in need for status.

Conversely, when post-demotion promotions are inclusive, not only the focal customer but also other program members will receive a chance to regain their lost tier. That is, the focal customer’s relative standing among other loyalty program members remains the same. The lack of exclusivity is unlikely to alleviate the feeling of deprivation of status (e.g., Sharma and Alter 2012). Thus, individuals high in need for status are likely to perceive inclusive promotions as less relevant. Similarly, prior research has documented that status-based loyalty may be undermined when benefits associated with high loyalty tiers are available to nonmembers or low-spending members (Henderson, Beck, and Palmatier 2011). Therefore, we argue that inclusive post-demotion promotions tend to dissipate status seeking and personal relevance among individuals high in need for status. Hence, the negative spillover effects from policy-based demotions are likely to influence loyalty among individuals high in need for status. That is, they may exhibit lower levels of loyalty when the demotion is due to policy changes (vs. their decreased spending), and the promotion is inclusive in nature.

We propose an opposite pattern of results among individuals low in need for status. In other words, they should exhibit more favorable reactions to inclusive (vs. exclusive) post-demotion promotions. Exclusive promotions tend to prime status seeking (Gierl and Huettl 2010), and consequently, such promotions are not relevant to individuals low in need for status. This low personal relevance of exclusive post-demotion promotions might magnify the importance of the cause of demotion. That is, greater levels of negative reactions to policy-based (vs. spending-based) demotions may spill over to post-promotion loyalty (e.g., Lemon and Wangenheim 2009; Schumann, Wünderlich, and Evanschitzky 2014). Conversely, we argue that inclusive post-demotion promotions are effective among individuals low in need for status. Previous research shows that individuals sensitive to equality (i.e., low in need for status) tend to exhibit favorable attitudes toward inclusive deals (Barone and Roy 2010). Inclusive promotions tend to reduce feelings of guilt due to potential advantageous inequality (e.g., Scheer, Kumar, and Steenkamp 2003). Thus, we expect similar levels of loyalty across the two demotion types among individuals low need in status when the promotion is inclusive in nature. Taken together, we put forth the following hypotheses:

Hypothesis 3: Promotion type will moderate the joint impact of the cause of demotion and need for status on post-promotion loyalty. Specifically,

Hypothesis 3a: When post-demotion promotions are inclusive, individuals high in need for status will exhibit lower levels of loyalty in the policy-based (vs. spending-based) demotion condition. No such differences are expected among individuals low in need for status.

Hypothesis 3b: When post-demotion promotions are exclusive, individuals low in need for status will exhibit lower levels of loyalty in the policy-based (vs. spending-based) demotion condition. No such differences are expected among individuals high in need for status.

The conceptual model is in Table 1, and we test hypothesis 3 in study 2.

Study 2. The Impact of the Cause of Demotion, Need for Status, and Exclusivity of Post-demotion Promotions on Post-promotion Loyalty

Methods

This study employed a 2 (cause of demotion: decreased spending level vs. policy changes) by 2 (need for status: low vs. high) by 2 (exclusivity cues in post-demotion promotions: inclusive vs. exclusive) quasi-experimental design. The cause of status demotion and exclusivity cues were manipulated, and need for status was measured. We pre-screened participants for their hotel stay frequency during the past six months. Two hundred thirty-six participants were recruited through Amazon Mechanical Turk (MTurk) in July 2017. We paid $.50 to each participant.

Participants were randomly assigned to one of the four conditions and asked to imagine that they were a loyal customer of Hotel ABCD and that there were four tiers in the hotel’s loyalty program (Platinum, Gold, Silver, and Blue). The cause of status demotion was manipulated as in Study 1. Exclusivity cues in the loyalty promotion were manipulated by stating that “this exclusive offer is sent to only 0.5% of our loyalty program members” (an exclusive promotion) or “all loyalty program members are invited to participate” (an inclusive promotion). The stimuli are shown in Appendix A. After participants’ exposure to the scenario, behavioral loyalty, manipulation checks, scenario realism, need for status, and demographics were measured.

Measures

Loyalty was measured with the same four items as in Study 1 (α=.97) (Zeithaml, Berry, and Parasuraman 1996). Manipulation check for the cause of demotion was also adapted from study 1 (r=.82, p <.01) (Russell 1982). Manipulation check for exclusivity cues involved four items (e.g., “The rewards promotion was inclusive—exclusive”) with a 7-point, bipolar scale (α=.92) (Barone and Roy 2010). Scenario realism was measured with the same two items as in study 1 (r=.68 p <.01) (Wu, Mattila, and Hanks 2015). Need for status was measured with the same four items as in study 1 (α=.95) (Dubois, Rucker, and Galinsky 2012) (see Appendix B).

Results

Demographics

Participants’ age ranged from 19 to 73 (M=36.17, SD=11.50). They were 50.4% male, and 55.5% had a college degree. About 49 percent of the participants had an annual household income between $40,000 and $79,999. Forty-three percent of the participants are currently or have been a member of a hotel reward program.

Manipulation checks

Overall, participants perceived the scenarios as realistic (M=5.68, SD=1.23). To check for the manipulation of the cause of demotion, a two-way analysis of variance (ANOVA) was conducted. The results showed that only the main effect for the cause of demotion was significant, F(1, 232)=32.29, p <.01. Specifically, when status was demoted because of policy changes (vs. decreased spending level), participants attributed the cause of status demotion to the hotel (M_{decreased spending} =4.78, M_{policy changes} = 6.01). The main effect of the manipulation for exclusivity cues, F(1, 232)=2.51, p >.1, and the interaction term, F(1, 232)=1.39, p >.1, were insignificant. Thus, our manipulation for the cause of demotion was effective.

To check for the manipulation of exclusivity cues, a two-way ANOVA was conducted. The findings showed that only the main effect of exclusivity cues was significant, F(1, 232)=38.30, p <.01. When the promotion was available only for 0.5 percent of the loyalty program members (vs. for all members), participants perceived it as more exclusive (M_inclusive =4.08, M_exclusive = 5.36). The main effect of the cause of demotion, F(1, 232)=.18, p >.1, and the interaction term, F(1, 232)=.77, p >.1, were not significant. Thus, our manipulation of exclusivity cues was successful.

Moderated regression

To test hypothesis 3, we regressed loyalty on the cause of status demotion (0=decreased spending, 1=policy changes), exclusivity cues (0=inclusive offer, 1=exclusive offer), mean-centered need for status (M=3.98, SD= 1.64, min=1, max=7), their two-way interactions, and the three-way interaction (PROCESS Model 3; Hayes 2013). The results show that the overall model was significant, F(7, 228)=3.33, p <.01, as well as the three-way interaction, t(228) = 2.29, p <.05 (see Table 4). Moreover, the two-way interaction between the cause of demotion and need for status was significant in the inclusive offer condition (B = −0.20, SE=0.09, t= −2.37, p <.05), but it did not reach significance in the exclusive offer condition (B=0.10, SE=0.10, t=.98, p >.1).

Table 4.

Moderated Multiple Regression Results from Study 2.

Model	Unstandardized Coefficient		t	p
Model	b	SE	t	p
Constant	4.12	0.20	20.82	<.001
Cause of demotion (C)	−0.44	0.28	−1.56	.12
Need for status (N)	0.43	0.12	3.49	<.001
Exclusivity cues (E)	−0.62	0.31	−2.03	.04
C × N	0.01	0.43	.02	.98
C × E	−0.41	0.17	−2.37	.02
N × E	−0.51	0.19	−2.65	.01
C × N × E	0.60	0.26	2.29	.02

Note: Adjusted R²=.10.

To decompose the simple interaction in the inclusive promotion condition (see Figure 2B), we conducted spotlight analyses. Specifically, when the post-demotion promotion was inclusive, the cause of demotion was significantly related to loyalty (B=−1.11, SE=0.41, t=−2.73, p<.01) among participants high in need for status. That is, loyalty was lower when the demotion was due to policy changes (M=3.71) rather than due to decreased spending (M=4.82) (p<.05). We further predicted that their reactions to inclusive post-demotion promotions should be unaffected by the cause of demotion, resulting in similar levels of loyalty among participants low in need for status. Congruent with our prediction, post-promotion loyalty did not differ across spending-based (M=3.42) and policy-based demotion conditions (M=3.65) (p>.1). Thus, hypothesis 3a is fully supported.

Figure 2.

(A) Simple interaction results in the exclusive promotion condition from study 2. (B) Simple interaction results in the inclusive promotion condition from study 2.

Conversely, when the post-demotion promotion was exclusive, the cause of demotion was not significantly related to loyalty (B=−0.11, SE=0.45, t=−0.23, p>.1) among participants high in need for status (see Figure 2a). That is, loyalty ratings did not differ across policy-based (M=3.26) and spending-based (M=3.37) demotions among participants high in need for status (p>.1). When it comes to individuals low in need for status, we predicted that their reactions to exclusive post-demotion promotions should be more negative when the demotion is due to policy changes (vs. decreased spending), thus lowering post-promotion loyalty. There is a marginally significant difference in loyalty ratings between policy-based demotion (M=2.88) and spending-based demotion (M=3.63) (p=.10). Thus, hypothesis 3b is partially supported.

Discussion

Study 2 provides evidence for a three-way interaction between the cause of demotion, need for status, and exclusivity of post-demotion promotions on post-promotion loyalty. We argue that the relevance of post-demotion promotions may vary based on need for status such that high (low) need for status individuals may consider exclusive (inclusive) promotions as highly desirable. Exclusive promotions tend to prime status-seeking (Gierl and Huettl 2010), and therefore, such promotions are highly relevant for individuals high in need for status. Conversely, individuals sensitive to equality concerns, including low need for status consumers, tend to favor inclusive deals (Barone and Roy 2010). Accordingly, we show that individuals high (low) in need for status exhibited similar levels of loyalty when the promotion was exclusive (inclusive) in nature. Conversely, we demonstrate that when post-demotion promotions are irrelevant, negative spillover effects are likely to occur. Specifically, individuals high in need for status showed lower levels of loyalty when the demotion was due to policy changes (vs. decreased spending), and the promotion was inclusive in nature.

General Discussion

The main purposes of this research are twofold: (1) to examine how the cause of demotion and need for status jointly influence post-promotion loyalty (study 1) and (2) to investigate the impact of exclusive (vs. inclusive) post-demotion promotions on the interactive effect of the cause of demotion and need for status on post-promotion loyalty (study 2). Relying on the attribution theory (e.g., Folkes 1988; Heider 1958; Weiner 2000), prior research has established robust support for the claim that demotions caused by policy changes (vs. decreased spending) are perceived in a highly negative light (Hwang and Kwon 2016; Lepthien et al. 2017; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009). This research extends this stream of marketing literature by demonstrating that need for status and the nature of post-demotion promotions (exclusive vs. inclusive) jointly influence the impact of negative spillover effects of policy-based demotions on loyalty.

More importantly, this research contributes to the travel and tourism literature by extending the notion of the attribution theory to status demotion and by investigating emotional consequences of causal attributions. Previous research shows that tourists exhibiting higher levels of pre-visit loyalty are less likely to engage in external attributions for a negative event at the tourist destination (Choi and Cai 2016). In this research, we demonstrate that loyalty can be a consequence of causal attributions for demotion such that policy-based (vs. spending-based) demotions are likely to decrease post-demotion loyalty, particularly among consumers low in need for status. This research further adds to the travel and tourism literature by examining the moderating effect of need for status in the relationship between the cause of demotion and customers’ emotional responses. Previous research demonstrates the moderating effect of customers’ social identification with the airline company in the relationship between the cause of service failure and company evaluations (Weber and Sparks 2010). Specifically, Weber and Sparks (2010) argue that a strong (vs. weak) identification with the company buffers the negative impact of external attributions for a service failure on company evaluations. In this research, high (vs. low) need for status buffers the carryover effects of external attributions for status demotion on post-demotion loyalty.

Unlike some previous studies examining the joint effect of two or three attributional dimensions—causality, stability, and controllability—on fairness, satisfaction, or loyalty (Chung and Petrick 2013; Nikbin et al. 2014; Tsang, Prideaux, and Lee 2016), we focused on the causal dimension. Prior work on status demotion has adopted the causal dimension in explaining differences between policy-based and spending-based demotions (Hwang and Kwon 2016; Lepthien et al. 2017; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009), and as such, the application of such a dimension in this research is well justified.

In study 1, we demonstrate a basic boundary condition for the spillover effects of policy-based demotions on post-promotion loyalty. Our findings show that customers high in need for status exhibited uniformly high levels of post-promotion loyalty regardless of the cause of demotion. Need for status is a universal motive and previous research posits that status perceptions are critical drivers of loyalty across various industry sectors (Henderson, Beck, and Palmatier 2011). Drawing from the status consumption literature (Gierl and Huettl 2010; Han, Nunes, and Drèze 2010; Yang and Mattila 2017), we argue that post-demotion promotions are desirable among individuals high in need for status as such promotions meet their motivation to regain lost status. Conversely, consumers low in need for status tend to perceive post-demotion promotions less desirable as regaining status is less important for such consumers. As such, it is not surprising that the negative spillover effects from policy-based demotions were observed in low in need for status participants’ loyalty ratings.

Furthermore, our mediation results are consistent with prior work in the travel and tourism literature demonstrating the relationship between customer emotions and loyalty (e.g., Faullant, Matzler, and Mooradian 2011; Hwang and Kwon 2016; Prayag, Hosany, and Odeh 2013; Prayag et al. 2017; van Berlo, Bloemer, and Blazevic 2014; Wagner, Hennig-Thurau, and Rudolph 2009; Yüksel and Yüksel 2007). Faullant, Matzler, and Mooradian (2011), for example, show that negative emotions (i.e., fear) are negatively related to satisfaction during a mountaineering experience. This research extends their work by examining the influence of other negative emotions, specifically, betrayal and anger on customer loyalty in the context of status demotion. Furthermore, Wagner, Hennig-Thurau, and Rudolph (2009) suggest that status demotion due to external (vs. internal) causes leads to greater levels of negative affect, thus having an adverse impact on loyalty. Congruent with this stream of literature, our findings indicate that negative emotions toward the post-demotion promotion mediate the impact of the cause of demotion on post-promotion loyalty among individuals low in need for status.

Lastly, we contribute to the marketing communications literature by demonstrating the interactive effect of the cause of demotion, need of status, and exclusivity of post-demotion promotions on post-promotion loyalty. Prior research suggests that the effectiveness of exclusive price promotions hinges on customer characteristics such as self-construal and gender (Barone and Roy 2010). Barone and Roy (2010), for example, show that preferences for exclusive (vs. inclusive) price promotions are more pronounced among customers high in independent self-construal as such individuals are motivated by uniqueness. Other studies (e.g., Balachander and Stock 2009; Gierl and Huettl 2010; Steinhart et al. 2014) suggest that brand/product type moderates the effectiveness of scarcity signals on product evaluations. Our findings indicate that exclusive post-demotion promotions are highly salient to individuals high in need for status, thus attenuating the negative spillover effects of policy-based demotions on loyalty. Finally, more inclusive post-demotion promotions are more suitable for individuals low in need for status as such consumers are driven by equality concerns (e.g., Barone and Roy 2010). To our knowledge, this research is among the first to demonstrate the cause of demotion and need for status as boundary conditions for the effectiveness of exclusive promotions.

Findings of this research show that when customers are demoted because of causes controllable by the company such as changes in the rewards program policy, their loyalty towards the company is likely to decrease among individuals low in need for status. However, post-demotion promotions may buffer the negative impact of policy-based demotions, particularly among customers high in need for status. Therefore, travel and tourism companies may want to use customer information to gauge need for status and send loyalty promotions to customers high in need for status. Companies can use the customer’s geographic location as a proxy for need for status (Malshe 2012). For example, Esri, a company specializing in spatial data analytics, classifies US residents into 67 different segments based on socioeconomic and demographic information (ArcGIS 2017). People living in ZIP code 90274 (the Palos Verdes peninsula in Los Angeles County in Southern California) tend to be affluent, yet exhibit low levels of need for status (Yang and Mattila 2017).

Furthermore, companies may prime customers’ need for status via advertising. For example, in Hilton’s e-Miles program, a female model wearing a professional business attire looks at a promotion stating “Get to your next getaway faster with e-Miles.” Professional attire and the messaging are likely to induce status motivation. In a similar vein, Marriott Rewards had a “double miles” offer for its new members with a slogan “Earn up to 35,000 bonus miles. Onward and Upward” (Ollila 2014). Using words such as upward, elevate, and higher in advertising may prompt customer motivations for status. Highlighting exclusive benefits associated with high loyalty tiers may also encourage status-seeking. For example, United MileagePlus using the slogan “elevate your travel experience” emphasizes benefits such as free check-in luggage, complimentary tier upgrades, and priority boarding associated with Silver status (Ollila 2016). By priming status motivations through post-demotion promotions, companies might lessen negative emotions caused by policy-based demotions.

Lastly, marketers may want to use exclusivity cues (e.g., “This offer is exclusive to you,” “This offer is sent to only 0.5% of our loyalty program members”) in post-demotion promotions for customers high in need for status. For example, Crystal Cruises launched a new brand campaign, “All Exclusive,” for luxury travel experiences in 2015. Such exclusive promotions are likely to satisfy motivation for status promotion, and therefore, are desirable among customers high in need for status. In sum, companies may want to tailor their loyalty reward promotions in terms of exclusivity to meet the needs of multiple customer segments.

As with other studies, this research has several limitations, which open avenues for future research. First, the sample size in study 1 is rather small. Second, this research adopts an experimental design with hypothetical scenarios to ensure internal validity at the expense of external validity (Weiner 2000). Hierarchical loyalty programs and the underpinning mechanism for such programs are similar across various industry sectors, including hospitality and tourism (e.g., Henderson, Beck, and Palmatier 2011). Thus, our hospitality context is not necessarily a limiting factor. Yet, future research may use field studies in the context of other travel industry sectors, thus enhancing the generalizability of our findings. Third, it may be interesting to show the enduring effects of our findings in a longitudinal design. For example, Wang et al. (2016) conducted a field experiment in cooperation with a large US hotel chain and contrasted changes in revenue among three groups: reward success, reward failure, and control group. Thus, future field studies may use customer data regarding the number and the cause of demotions/promotions to predict long-term loyalty.

It may be interesting to examine other variables that moderate customer responses to post-demotion promotions and loyalty. For example, high-tiered customers such as Platinum members may react more negatively to status demotion than their lower-tiered counterparts because they are more aversive to status demotion (Wang et al. 2016). Familiarity with the loyalty reward program may also influence customers’ reactions to demotions. Future research may also merit from investigating more granular levels of exclusivity (promotions available to only 0.5% vs. 2% vs. 10% of the loyalty program members). Many companies monitor customer spending patterns and regularly notify customers of a potential status demotion. For example, Starbucks and Marriott International e-mail customers about their current status and renewal dates. By regularly notifying customers of their chances to move up in the loyalty tier, customers might be less likely to attribute the cause of status demotion to the company. Future research should examine the role of notification of potential status demotion on customer emotions and loyalty. Lastly, our participants were US consumers, and previous research shows that cultural factors (i.e., power distance belief) influence an individual’s need for status (e.g., Gao, Winterich, and Zhang 2016). Thus, future cross-cultural research is warranted. In conclusion, we believe that there are plenty of promising areas for further research in status demotion in the loyalty reward program context and this research advances our understanding of customer reactions to post-demotion promotions.

Footnotes

Appendices

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors gratefully acknowledge financial support from the Marriott Foundation.

Notes

ORCID iD

YooHee Hwang

Author Biographies

YooHee Hwang is a PhD candidate at the School of Hospitality Management at the Pennsylvania State University. Her research interests focus on cross-cultural research, customer emotions, and relationship marketing.

Anna S. Mattila, PhD, is the Marriott professor of Lodging Management at the School of Hospitality management at the Pennsylvania State University. She holds a PhD in services marketing from Cornell University. Her research interests focus on service encounters with a particular interest in service recovery, corporate social responsibility, social media and cross-cultural research.

References

Aluri

Price

B. S.

McIntyre

N. H.

2019. “Using Machine Learning to Cocreate Value through Dynamic Customer Engagement in a Brand Loyalty Program.” Journal of Hospitality and Tourism Research 43 (1): 78–100.

Andrews

J. C.

Durvasula

Akhter

S. H.

1990. “A Framework for Conceptualizing and Measuring the Involvement Construct in Advertising Research.” Journal of Advertising 19 (4): 27–40.

ArcGIS. 2017. “Main Page.” http://www.arcgis.com/features/index.html/ (accessed July 29, 2017).

Balachander

Stock

2009. “Limited Edition Products: When and When Not to Offer Them.” Marketing Science 28 (2): 336–55.

Baloglu

Zhong

Y. Y.

Tanford

2017. “Casino Loyalty: The Influence of Loyalty Program, Switching Costs, and Trust.” Journal of Hospitality and Tourism Research 41 (7): 846–68.

Barone

M. J.

Roy

2010. “Does Exclusivity Always Pay Off? Exclusive Price Promotions and Consumer Response.” Journal of Marketing 74 (2): 121–32.

Bender

. 2015. “United Airlines Is Changing Its MileagePlus Program: Winners and Losers.” Forbes. https://www.forbes.com/ (accessed November 2, 2017).

Breitsohl

Garrod

2016. “Assessing Tourists’ Cognitive, Emotional and Behavioural Reactions to an Unethical Destination Incident.” Tourism Management 54:209–220.

Brock

T. C.

1968. “Implications of Commodity Theory for Value Change.” In Psychological Foundations of Attitudes, edited by Greenwald

A. G.

Brock

T. C.

Ostrom

T. M.

, 243–75. New York: Academic Press.

10.

Buhrmester

Kwang

Gosling

S. D.

2011. “Amazon’s Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?” Perspectives on Psychological Science 6 (1): 3–5.

11.

Choi

Cai

L. A.

2016. “Tourist Causal Attribution: Does Loyalty Matter?” Journal of Travel and Tourism Marketing 33 (9): 1337–47.

12.

Chung

J. Y.

Petrick

J. F.

2013. “Price Fairness of Airline Ancillary Fees: An Attributional Approach.” Journal of Travel Research 52 (2): 168–81.

13.

Correia

Kozak

Reis

2016. “Conspicuous Consumption of the Elite: Social and Self-Congruity in Tourism Choices.” Journal of Travel Research 55 (6): 738–50.

14.

Dolnicar

Grabler

Grün

Kulnig

2011. “Key Drivers of Airline Loyalty.” Tourism Management 32 (5): 1020–26.

15.

Dreze

Nunes

J. C.

2009. “Feeling Superior: The Impact of Loyalty Program Structure on Consumers’ Perceptions of Status.” Journal of Consumer Research 35 (6): 890–905.

16.

Dubois

Rucker

D. D.

Galinsky

A. D.

2012. “Super Size Me: Product Size as a Signal of Status.” Journal of Consumer Research 38 (6): 1047–62.

17.

Eastman

J. K.

Goldsmith

R. E.

Flynn

L. R.

1999. “Status Consumption in Consumer Behavior: Scale Development and Validation.” Journal of Marketing Theory and Practice 7 (3): 41–52.

18.

Faullant

Matzler

Mooradian

T. A.

2011. “Personality, Basic Emotions, and Satisfaction: Primary Emotions in the Mountaineering Experience.” Tourism Management 32 (6): 1423–30.

19.

Folkes

V. S.

1988. “Recent Attribution Research in Consumer Behavior: A Review and New Directions.” Journal of Consumer Research 14 (4): 548–65.

20.

Gao

Winterich

K. P.

Zhang

2016. “All That Glitters Is Not Gold: How Others’ Status Influences the Effect of Power Distance Belief on Status Consumption.” Journal of Consumer Research 43 (2): 265–81.

21.

Genter

J. T.

2018. “United Ditches Meals on Certain First Class Flights, Rebrands ‘Snacks’ as ‘Meals.’” The Points Guy, https://www.thepointsguy.com/ (accessed June 9, 2018).

22.

Gephart

R. P.

1978. “Status Degradation and Organizational Succession: An Ethnomethodological Approach.” Administrative Science Quarterly 23 (4): 553–81.

23.

Gierl

Huettl

2010. “Are Scarce Products Always More Attractive? The Interaction of Different Types of Scarcity Signals with Products’ Suitability for Conspicuous Consumption.” International Journal of Research in Marketing 27 (3): 225–35.

24.

Grégoire

Tripp

T. M.

Legoux

2009. “When Customer Love Turns Into Lasting Hate: The Effects of Relationship Strength and Time on Customer Revenge and Avoidance.” Journal of Marketing 73 (6): 18–32.

25.

Han

Y. J.

Nunes

J. C.

Drèze

2010. “Signaling Status with Luxury Goods: The Role of Brand Prominence.” Journal of Marketing 74 (4): 15–30.

26.

Hayes

A. F.

2013. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. Guilford Press.

27.

Heider

1958. The Psychology of Interpersonal Relations. New York: Wiley.

28.

Henderson

C. M.

Beck

J. T.

Palmatier

R. W.

2011. “Review of the Theoretical Underpinnings of Loyalty Programs.” Journal of Consumer Psychology 21 (3): 256–76.

29.

Hosany

Gilbert

2010. “Measuring Tourists’ Emotional Experiences toward Hedonic Holiday Destinations.” Journal of Travel Research 49 (4): 513–26.

30.

Hwang

Kwon

2016. “Effects of Demotion in Loyalty Programs on Brand-Switching Intentions.” Service Business 10 (3): 489–505.

31.

Hwang

Mattila

A. S.

2018. “Is It My Luck or Loyalty? The Role of Culture on Customer Preferences for Loyalty Reward Types.” Journal of Travel Research 57 (6): 769–778.

32.

Lemon

K. N.

Wangenheim

F. V.

2009. “The Reinforcing Effects of Loyalty Program Partnerships and Core Service Usage: A Longitudinal Analysis.” Journal of Service Research 11(4): 357–70.

33.

Leppert

2016. “A Brief Guide to Mainstream Cruise Line Loyalty Programs.” Fox News. http://www.foxnews.com.

34.

Lepthien

Papies

Clement

Melnyk

2017. “The Ugly Side of Customer Management–Consumer Reactions to Firm-Initiated Contract Terminations.” International Journal of Research in Marketing 34 (4): 829–50.

35.

A. S.

H. H.

2014. “Drivers of Customer–Brand Relationship Quality: A Case of Mainland Chinese Hotel Loyalty Program Members.” Journal of Travel and Tourism Marketing 31 (7): 763–82.

36.

Malshe

2012. “When Should Luxury Brands Use Social Media?” http://ashwinmalshe.wordpress.com/2012/11/03/when-should-luxury-brandsuse-social-media/. (accessed November 3, 2012).

37.

Mathies

Gudergan

S. P.

2012. “Do Status Levels in Loyalty Programmes Change Customers’ Willingness to Pay?.” Journal of Revenue and Pricing Management 11 (3): 274–88.

38.

McCall

Voorhees

2010. “The Drivers of Loyalty Program Success: An Organizing Framework and Research Agenda.” Cornell Hospitality Quarterly 51 (1): 35–52.

39.

Morais

D. B.

Dorsch

M J.

Backman

S. J.

2004. “Can Tourism Providers Buy Their Customers’ Loyalty? Examining the Influence of Customer-Provider Investments on Loyalty.” Journal of Travel Research 42 (3): 235–43.

40.

Mutter

Kundisch

2014. “Don’t Take Away My Status!—Evidence from the Restructuring of a Virtual Reward System.” Computer Networks 75: 477–90.

41.

Nikbin

Marimuthu

Hyun

S. S.

Ismail

2014. “Effects of Stability and Controllability Attribution on Service Recovery Evaluation in the Context of the Airline Industry.” Journal of Travel and Tourism Marketing 31 (7): 817–34.

42.

Ollila

. 2014. “Marriott Rewards New Member Double Miles Offer (Nine Airlines) October 15–January 31, 2015.” http://www.loyaltylobby.com/ (accessed October 13, 2017).

43.

Ollila

. 2016. “United Airlines Marriott Rewards RewardsPlus 50% Premier Qualifying Miles Promotion.” http://www.loyaltylobby.com/ (accessed October 13, 2017).

44.

Ollila

. 2017. “IHG Rewards Club Accelerate Promotion for stays September 1–December 31, 2017 (Post Your Offers!).” http://www.loyaltylobby.com/ (accessed November 2, 2017).

45.

Prayag

Hosany

Muskat

Del Chiappa

2017. “Understanding the Relationships between Tourists’ Emotional Experiences, Perceived Overall Image, Satisfaction, and Intention to Recommend.” Journal of Travel Research 56 (1): 41–54.

46.

Prayag

Hosany

Odeh

2013. “The Role of Tourists’ Emotional Experiences and Satisfaction in Understanding Behavioral Intentions.” Journal of Destination Marketing and Management 2 (2): 118–27.

47.

Ramaseshan

Ouschan

2017. “Investigating Status Demotion in Hierarchical Loyalty Programs.” Journal of Services Marketing 31 (6): 650–61.

48.

Ramaseshan

Stein

Rabbanee

F. K.

2016. “Status Demotion in Hierarchical Loyalty Programs: Effects of Payment Source.” The Service Industries Journal 36 (9–10): 375–95.

49.

Russell

1982. “The Causal Dimension Scale: A Measure of How Individuals Perceive Causes.” Journal of Personality and Social Psychology 42 (6): 1137–45.

50.

Scheer

L. K.

Kumar

Steenkamp

J. B. E.

2003. “Reactions to Perceived Inequity in US and Dutch Interorganizational Relationships.” Academy of Management Journal 46 (3): 303–16.

51.

Schumann

J. H.

Wünderlich

N. V.

Evanschitzky

2014. “Spillover Effects of Service Failures in Coalition Loyalty Programs: The Buffering Effect of Special Treatment Benefits.” Journal of Retailing 90 (1): 111–18.

52.

Sharma

Alter

A. L.

2012. “Financial Deprivation Prompts Consumers to Seek Scarce Goods.” Journal of Consumer Research 39 (3): 545–60.

53.

Shin

J. K.

Park

M. S.

2014. “The Effect of Status, Truth of Messages, Involvement on Loyalty When Customer Experience Demotion in Retail Loyalty Program.” Journal of Digital Convergence 12 (3): 89–94.

54.

Smith

2002. “The Humiliating Organization: The Functions and Dysfunctions of Degradation.” In The Civilized Organization: Norbert Elias and the Future of Organization Studies, edited by Van Iterson

Mastenbroek

Willem

Newton

Tim

Smith

Dennis

. Philadelphia: John Benjamins, 41–57.

55.

Spiller

S. A.

Fitzsimons

G. J.

Lynch

J. G.

Jr McClelland

G. H.

2013. “Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression.” Journal of Marketing Research 50 (2): 277–88.

56.

Steinhart

Kamins

Mazursky

Noy

2014. “Effects of Product Type and Contextual Cues on Eliciting Naive Theories of Popularity and Exclusivity.” Journal of Consumer Psychology 24 (4): 472–83.

57.

Steinhoff

Palmatier

R. W.

2016. “Understanding Loyalty Program Effectiveness: Managing Target and Bystander Effects.” Journal of the Academy of Marketing Science 44 (1): 88–107.

58.

Synder

. 2016. “Customers Are Furious with Starbucks’ New Rewards Program.” Fortune, https://www.fortune.com/ (accessed November 2, 2017).

59.

Tanford

2013. “The Impact of Tier Level on Attitudinal and Behavioral Loyalty of Hotel Reward Program Members.” International Journal of Hospitality Management 34:285–94.

60.

Tanford

Raab

Kim

Y. S.

2011. “The Influence of Reward Program Membership and Commitment on Hotel Loyalty.” Journal of Hospitality and Tourism Research 35 (3): 279–307.

61.

Terblanche

N. S.

2015. “Customers’ Perceived Benefits of a Frequent-Flyer Program.” Journal of Travel and Tourism Marketing 32 (3): 199–210.

62.

Thye

S. R.

2000. “A Status Value Theory of Power in Exchange Relations.” American Sociological Review 65 (3): 407–32.

63.

Tsang

N. K.

Prideaux

Lee

2016. “Attribution of Inappropriate Visitor Behavior in a Theme Park Setting–A Conceptual Model.” Journal of Travel & Tourism Marketing 33 (8): 1088–105.

64.

van Berlo

Bloemer

Blazevic

2014. “Customer Demotion in Hierarchical Loyalty Programmes.” The Service Industries Journal 34 (11): 922–37.

65.

Wagner

Hennig-Thurau

Rudolph

2009. “Does Customer Demotion Jeopardize Loyalty?” Journal of Marketing 73 (3): 69–85.

66.

Wang

Lewis

Cryder

Sprigg

2016. “Enduring Effects of Goal Achievement and Failure within Customer Loyalty Programs: A Large-Scale Field Experiment.” Marketing Science 35 (4): 565–75.

67.

Weber

Sparks

2010. “Service Failure and Recovery in a Strategic Airline Alliance Context: Interplay of Locus of Service Failure and Social Identity.” Journal of Travel and Tourism Marketing 27 (6): 547–64.

68.

Weiner

2000. “Attributional Thoughts about Consumer Behavior.” Journal of Consumer Research 27 (3): 382–7.

69.

Wong

I. A.

Lam

I. K. V

. 2016. “A Multilevel Investigation of the Role of Retail Stores in Cross-Border Shopping.” Journal of Travel and Tourism Marketing 33 (6): 837–53.

70.

Mattila

A. S.

Hanks

2015. “Investigating the Impact of Surprise Rewards on Consumer Responses.” International Journal of Hospitality Management 50:27–35.

71.

Xie

K. L.

Chen

C. C.

2013. “Progress in Loyalty Program Research: Facts, Debates, and Future Research.” Journal of Hospitality Marketing and Management 22 (5): 463–89.

72.

Xie

K. L.

Xiong.

Chen

C. C.

2015. “Understanding Active Loyalty Behavior in Hotel Reward Programs through Customers’ Switching Costs and Perceived Program Value.” Journal of Travel and Tourism Marketing 32 (3): 308–24.

73.

Yang

Mattila

A. S.

2017. “The Impact of Status Seeking on Consumers’ Word of Mouth and Product Preference—A Comparison Between Luxury Hospitality Services and Luxury Goods.” Journal of Hospitality and Tourism Research 41 (1): 3–22.

74.

Jeon

2003. “Effects of Loyalty Programs on Value Perception, Program Loyalty, and Brand Loyalty.” Journal of the Academy of Marketing Science 31 (3): 229–40.

75.

Yüksel

2007. “Shopping Risk Perceptions: Effects on Tourists’ Emotions, Satisfaction and Expressed Loyalty Intentions.” Tourism Management 28 (3): 703–13.

76.

Zeithaml

V. A.

Berry

L. L.

Parasuraman

1996. “The Behavioral Consequences of Service Quality.” Journal of Marketing 60 (2): 31–46.