Anchoring decisions: the role of decoy pricing in consumer choices

Abstract

Purpose

Hospitality firms aim to increase their profits by implementing a variety of marketing activities, including using decoy pricing to provide alternative choices for consumers. Decoys are relatively higher-priced offerings that signal lower value than the other offerings in the consideration set. The purpose of this research is to investigate the influence of decoy pricing on consumer choices across various contexts in the foodservice and hotel industries.

Design/methodology/approach

Across the pilot and four main studies, the current research employs a sequential exploratory mixed-method design to investigate the influence of decoy pricing in the foodservice and lodging industries. The qualitative part of this research was based on two focus groups, followed by a pilot study and four main study experiments.

Findings

The results show that decoy pricing escalates consumers’ choices of more expensive product bundles in both restaurant and hotel cancellation policy contexts. However, decoy pricing does not increase the selection of more expensive hotel product bundles.

Originality/value

While decoy pricing has been utilized as an effective revenue maximization strategy for product placement in retail stores, less is known about how promotional advertisements with decoy offers influence hotel and restaurant customers to choose more costly options. Specifically, this is the first study that explores whether decoy pricing and product/service bundling can encourage customers to select more expensive offers in hotel and restaurant contexts, considering the types of hospitality bundles that may limit this effect.

Citation

Bujisic, M., Bujisic, V., Parsa, H., Bilgihan, A. and Li, K. (2024), "Anchoring decisions: the role of decoy pricing in consumer choices", International Hospitality Review, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IHR-04-2024-0023

Introduction

Consumers buy things to fulfill their physiological needs and to satisfy their psychological desires. While there is no magical marketing formula to reveal those desires, commonalities in human behavior can help explain the motivations behind consumer purchasing decisions. One key aspect of these decisions involves consumers using price as a perceptual cue to compare products and services, judging their relative value for money and quality (Boz, Arslan, & Koc, 2017). In industries like hospitality, where services often lack tangible elements for consumers to anchor their price judgments, establishing an effective pricing strategy is critical for success (Kimes, Phillips, & Summa, 2012).

From a business perspective, a well-executed pricing strategy can lead to increased profitability as individuals tend to overconsume to meet their psychological needs (Larson, 2014). Classical rational theory posits that consumers make logical choices to maximize benefits (Coleman & Fararo, 1992). These consumers seek to optimize utility by purchasing products or services when perceived value exceeds price (Thaler, 1980). While behavioral economics acknowledges consumers' interest in value maximization, it also recognizes that rational and utility-maximizing decisions do not always dictate consumer behavior, as psychological utility plays a role (Ariely, 2008). Research indicates that factors such as menu presentation and pricing can impact customer demand for food and beverages (Naipaul & Parsa, 2001). For instance, Iglesias and Yague Guillen (2002) found that restaurant patrons' choices were influenced by reference points, or the prices of other items on the menu. Decoy items can serve as these reference points and influence consumer choices.

Decoy pricing has emerged as an effective reference point strategy, often used in menu bundling to entice consumers to choose options that appear superior in value and generate higher profits for businesses (Schwartz & Cohen, 1999; Shomaker, 1993). Restaurants frequently utilize decoy pricing to make certain menu items seem more attractive (Kimes et al., 2012). Similarly, hotels can shift demand by offering additional amenities, such as complimentary breakfast or Wi-Fi, at the same room price, highlighting the importance of bundling strategies in the hospitality and tourism industry (Nicolau & Sellers, 2012).

Firms develop pricing strategies that consider not only economic factors, such as cost-based pricing, but also psychological mechanisms in consumer decision-making, ultimately leading to improved financial performance. Despite the importance of decoy pricing as a marketing tool and perceptual cue, its application within the hospitality industry has received limited attention (Josiam & Hobson, 1995; Schwartz & Cohen, 1999), with only a few recent studies addressing the topic (e.g. Attwood, Chesworth, & Parkin, 2020; Gomez, Martínez-Molés, Urbano, & Vila, 2016; Ronayne & Brown, 2017). In response to this research gap, our study investigates the impact of decoy pricing on consumer choices across various foodservice and hotel industry contexts. Specifically, this research examines whether decoy pricing and product/service bundling can motivate customers to choose more costly options and determines the types of hospitality bundles that may mitigate this effect. To address these research questions, a pilot study followed by four main studies were conducted. In Studies 1 and 2, the impact of decoy pricing on purchasing decisions was analyzed within the context of promotional advertisements that offered different hotel service bundles, such as amenities and cancellation policy bundles. In Studies 3 and 4, the influence of decoy pricing on customer purchasing decisions for advertised menu specials (individual menu items versus meal combos) at various price points was investigated.

Literature review

Psychological pricing and decoy pricing

Rational pricing strategies are typically derived from mathematical formulas, such as cost-plus, gross-profit, break-even, and marginal cost pricing, competitive prices, geographic location or product category price levels (Kreul, 1982). Although such formula-based pricing strategies are easy to apply, they neglect to account for a customer’s willingness to pay for the given price; in other words, the price may not be psychologically appropriate for the customer (Kreul, 1982). Without considering the qualitative, subjective and psychological dimensions of consumers’ decision-making, a purely quantitative pricing approach is not sufficient (Pavesic, 1989). Unlike rational pricing, psychological pricing is referred to as intuitive, and rule-of-thumb pricing (Kreul, 1982). However, the rule-of-thumb psychological pricing is not irrational—it is based on consumer behavior and pricing customs instead of strict mathematical formulas (Kreul, 1982). Restaurateurs utilize psychologically appealing prices to maximize profits and create favorable evaluations among customers (Kreul, 1982). Customers seem to develop “price illusion[s]” (Collins & Parsa, 2006; p. 95) which further shapes their decision-making and in turn can increase or decrease the profitability of a restaurant establishment.

Moreover, restaurant customers prefer menu items with lower prices when the price difference between the lowest- and the highest-priced items is relatively large (Kreul, 1982). However, when an in-between, in some way inferior option that signals lower value than the higher-priced option is added to the mix, it acts as a “decoy” and makes the higher-priced option more attractive for consumers. This decoy effect, also known as the attraction effect, is when a new inferior option is added to a set of choices, a customer is more likely to choose an option that represents “a better deal” (Kim, Kim, Lee, Kim, & Hyde, 2019). The decoy effect has been examined in economics (e.g. Castillo, 2020; Crosetto & Gaudeul, 2016; Gomez et al., 2016), marketing (e.g. Dominique-Ferreira, 2017; Dominique-Ferreira, Vasconcelos, & Proença, 2016; Dominique-Ferreira & Antunes, 2020; Lichters, Bengart, Sarstedt, & Vogt, 2017), and psychology (e.g. Farmer, Warren, El‐Deredy, & Howes, 2017; Hadar, Danziger, & Hertwig, 2018; Li, Sun, & Chen, 2019) literature. The purpose of adding the new inferior option is to draw attention to a more profitable item (the “target”) rather than to generate direct sales of the inferior option (Huber, Payne, & Puto, 1982). The effect of decoys on customer preferences differ when all options are presented at the same time compared with when each option is presented individually to the customer (Park & Kim, 2005). Although decoys have been used in the hospitality industry, existing research indicates contradictory findings. To make certain items more attractive, restaurateurs will use decoy pricing to design their menus (Boz et al., 2017). However, Attwood et al. (2020) found that decoys on food menus had no effect on diners’ food selection. Hospitality establishments also utilize bundling to combine several items together and set a price that is lower than the sum of the components to increase sales (Boz et al., 2017). To illustrate the decoy effect, in the lodging industry context, Kim et al. (2019) found that in the presence of a decoy hotel option, guests exhibit a preference toward the targeted hotel option. On the contrary, Frederick, Lee, and Baskin (2014) found no evidence for an attraction effect in a hotel setting: the less attractive decoy option did not increase the choice share of the option it most closely resembled (the target option); surprisingly, the decoy reduced the choice share of the target option, a phenomenon called “repulsion effect”. Moreover, the attraction effect differs across consumer segments; the effect is more salient when a consumer is more concerned about quality than about price (Gomez et al., 2016).

Nudge theory proposes indirect suggestions as ways to influence the behavior and decision making (Thaler & Sunstein, 2008). From a theoretical perspective, applying the decoy effect to a menu by offering an option that is high-priced and low-value option compared to other alternatives in the choice set is expected to manipulate people’s choices. Following Mussweiler and Strack’s (1999) theorizing, we propose a two-phase anchoring and adjustment process in the decoy pricing context. In the first phase, consumers choose an anchor based on its availability at the time of decision-making. A decoy will strongly affect customers’ thinking because it brings their attention to the relative advantage of the superior offering (Zheng et al., 2019). If consumers are presented with product choices that include a decoy item that offers less value for money than another high-priced item, they tend to choose the high-priced item. However, consumers’ tendency to choose the high-priced item is lower when the decoy item is absent (Heath and Chatterjee, 1995). This theorizing leads to the following hypothesis:

H1.

The presence of a decoy product/service offer in promotional advertising increases the likelihood that customers would select a higher-priced bundle offer over a lower-priced individual offer.

When presented with bundled products or services, customers may not be aware of the individual prices of each product and service (i.e. the pure components) that comprise a bundle. Founded on the prospect theory (Kahneman & Tversky, 1979), a consumer’s purchase decision is dependent on whether the price paid is perceived as fair with respect to her reference price point (Wu and Cosguner, 2020). For the consumer to judge whether the price of a bundle option fair or not depends on whether she can assess the prices of individual items that make up the bundle. Schwartz and Cohen (1999) have argued that an “unintentional decoy price effect occurs whenever a mixed bundle is offered on the menu” (p. 25). For an unintentional decoy effect to occur, consumers need to be aware of the prices of components, and the total bundled price should be lower than the sum of the pure components’ prices. When the prices of all the components are unknown (i.e. pure bundling), unintentional decoy pricing might not work. Instead, a company could create an intentional decoy to guide customers’ choices toward the more expensive offer. Specifically, when the prices of all the components are unknown, customers’ likelihood of choosing a more expensive offer (i.e. a bundle over individual items) is greater when an intentional decoy is present vs absent. If the prices of the components that form a bundle are known, having an intentional decoy will not affect the selection of a more expensive offer, since an unintentional decoy would accomplish the same effect. Thus, we expect that consumers would exhibit equal likelihood toward a more expensive bundle offer, regardless of the presence of an intentional decoy. Formally, the following hypothesis is proposed:

H2.

Component price (simple vs itemized) moderates how a decoy offer (absent vs present) affect customers’ likelihood to select a higher-priced bundle offer (vs a lower-priced offer). Specifically, when the prices of bundle components in promotional advertising are unknown (i.e. simple component price), the presence of the decoy offer increases the likelihood that customers would select a higher-priced bundle offer over a low-priced individual offer. When the prices of the bundle components are known (i.e. itemized component price), the presence of the decoy offer does not increase the likelihood that customers would select the higher-priced bundle offer.

Methods

Procedures

This study was based on a sequential exploratory mixed method design that was completed in five steps. The qualitative part of this research was based on two focus groups, followed by a pilot study and three main study experiments.

Focus groups

Two focus groups with eight participants each were conducted to select restaurant and hotel product bundles that the potential customers are most familiar with. Focus group participants were recruited from undergraduate students, graduate students, and a faculty population of a large US university (i.e. Public land-grand R1 university with over 60,000 students). Participants were introduced to the concept of product bundling and asked to talk about their experiences in the restaurant and hotel contexts. The results for the first, restaurant-focused group, indicated that the majority of participants were familiar with multiple menu bundling options especially in the quick-service context.

The second focus group discussed bundling in the hotel context (e.g. accommodation and meals, room upgrades/late checkouts/early check-ins, event and stay packages etc.). This group was overall less familiar with the hotel bundling strategies in promotional advertising. The type of bundle that was recognized by several participants was regarding different types of cancellation policies. The data from focus groups were coded and used to develop the experimental scenario manipulations.

Pilot study

In the pilot study, we pre-tested restaurant menus to identify adequate price points and examine the proposed effect from Hypothesis 1. A student sample from a large US university was used. A total of 81 students responded to the survey. Participants were randomly assigned to two experimental conditions: a control condition (no decoy offer) and a decoy condition. Participants in each group received a promotional menu for a made-up restaurant. The control condition contained two promotional menu offers (1) burger - $3.99 (lower-priced, individual offer), and (2) burger + soda + fries - $6.99 (higher-priced, bundle offer). The decoy condition included the same offers as the control condition, with the addition of an intentional decoy (burger + soda - $6.99), strategically placed in between the previous two offers.

The results reveal that in the control condition 35% of respondents selected the lower-priced offer (burger) and 65% of people selected the more expensive item (burger + soda + fries), whereas in the long menu scenario (with the decoy item present) 4.9% of people selected the less expensive item (burger) and 95.1% of people selected the more expensive items. The chi-square test indicated a statistically significant difference in the proportions of the choice of the higher-priced menu offer, across the two conditions (χ²(1) = 11.589; p = 0.001). Based on these results it seemed that price points for the manipulations were adequate and were used as a base point for two of the main study experiments.

Main studies methods and findings

The targeted population for the four main studies was U.S. adult customers. The modified web-based questionnaires were distributed through Amazon Mechanical Turk during a two-day period to U.S. residents 18 years of age or older who regularly stay in hotels (study 1) or frequent restaurants (study 2 and 3). The total sample for the four studies was 463 respondents.

Study 1: procedure

Study 1 explored the decoy pricing effect on hotel cancellation policy bundles. A hundred and two participants were randomly assigned to one of two experimental conditions. The participants were asked to imagine that they were looking to book a room in a midscale hotel that belonged to a major national chain. Next, they reviewed a promotional ad with a hotel room picture and were asked to select an option from the list that they were most likely to book in real life. In the control ad, the hotel offered two types of cancellation policies: (1) No refund cancellation - $119; and (2) Open cancellation - $129. In the second scenario, a decoy ad that included one additional cancellation policy (48-h cancellation - $129) was placed between the other two offers. After they reviewed the promotional ad and selected one of the options, participants indicated their demographic characteristics.

Study 1: results

In Study 1, both conditions were randomly assigned equal numbers of 51 participants. The results indicate that in the control condition, 64.7% of people selected the lower-priced hotel offer (no refund cancellation) and 35.3% of people selected the higher-priced offer with an open cancellation policy. In the decoy condition, 35.3% of people selected the lower-priced offer (no refund cancellation) and 64.7% of people selected the more expensive offers with cancellation policies (Table 1). A chi-square test showed a significant difference in the proportions of the choice of the higher-priced hotel offer across the two conditions (χ²(1) = 8.894; p = 0.003), providing support for Hypothesis 1.

Study 2: procedures

Study 2 employed a 2 (decoy offer: absent vs present) × 2 (component price: simple vs itemized) full-factorial experimental design to examine the interplay between decoy pricing and the presentation of component prices in the restaurant menu specials promotional ad. One hundred and sixty participants were randomly assigned to one of four groups. The decoy offer (absent vs present) used the same manipulations from the pilot study but was priced at $7.99 for bundle offers, which was higher than reference point price that was used in the pilot study. The manipulation of the component price involved two conditions: (1) simple (unknown component) prices with only total price displayed, and (2) itemized (known component) prices with the total price and individual prices for each component in a bundle displayed. Therefore, participants were asked to choose among the following four menu specials:

• (1)

  (1) burger - $3.99; (2) burger + soda + fries - $7.99

• (2)

  (1) burger - $3.99; (2) burger + soda - $7.99; (3) burger + soda + fries - $7.99

• (3)

  (1) burger – TOTAL $3.99; (2) burger + soda ($4.00) + fries ($4.00) – TOTAL $7.99

• (4)

  (1) burger – TOTAL $3.99; (2) burger ($3.99) + soda ($4.00) – TOTAL $7.99; (3) burger + soda ($4.00) + fries ($4.00) – TOTAL $7.99

Study 2: results

We first tested the main effect of the decoy offer. A Simple chi-square test results indicated that after seeing the ad without a decoy condition, 55.3% of people selected the lower-priced offer (burger) and 44.7% of respondents selected the higher-priced offer (burger + soda + fries) In the decoy condition, 28.6% of people selected the lower-priced offer (burger) and 71.4% of people selected the higher-priced offer This difference in proportions was statistically significant (χ²(1) = 11.730; p = 0.001), thus providing further support for the main effect of decoy pricing, as reflected in Hypothesis 1.

In the second step, the moderating effect of the component price (simple vs itemized) on the relationship between decoy pricing in ads and menu item selection was examined. When the ad displayed simple component prices, in the decoy absent condition, 61% of participants selected the lower-priced offer and 39% selected the higher-priced offer. In the decoy present condition with simple component prices, 30.2% of participants selected the lower-priced offer, while 69.8% selected higher priced offers.

When the ad displayed itemized prices, we expected that the effect of decoy pricing would be negligible. However, the results indicated that decoy pricing still resulted in an increased selection of the higher-priced offer (73.2%) compared to the decoy absent condition, where 51.4% selected the higher-priced offer. Such results indicate that even when ads incorporate transparent (i.e. itemized) pricing, a larger percentage of participants tends to select a high-price option without a decoy (51.4%), compared to a simple pricing situation (39%). This finding provides partial support that bundled products with itemized component prices could act as unintentional decoys; however, their effect is not as strong as the effect of real intentional decoys (Table 2).

The results from the logistic regression failed to provide additional support for the significant interaction effect between the decoy offer and component price on customers’ choice of a higher-priced vs lower-priced menu offer. The predictive accuracy of the model was acceptable based on a classification table (64.4%), with Nagelkerke R Square = 0.106 and Cox & Snell R Square = 0.79. Additionally, a Hosmer and Lemeshow test indicated that the correspondence between the actual and predicted values of the dependent variable is high (χ²(2) = 0.000, p = 1.000). However, the regression coefficient for the interaction effect was not significant (β = −3.336, p = 0.617), thus failing to provide support for Hypothesis 2.

Study 3: procedures

To provide more robust support and replicate the findings from Study 2, Study 3 was designed to test the consistency of the effect of decoy pricing in ads across different price points for bundled offers. Study 3 employed the same two manipulations as study 2, namely 2 (decoy offer: absent vs present) × 2 (component price: simple vs itemized). A total of 201 participants were randomly assigned to the four groups.

Whereas in Study 3 the price for bundled offers was $7.99, in Study 3 we decreased the price for bundled offers to $5.99. This price point was lower than the $6.99 price used in our pilot study. The following four conditions were used:

• (1)

  (1) burger - $3.99; (2) burger + soda + fries - $5.99

• (2)

  (1) burger - $3.99; (2) burger + soda - $5.99; (3) burger + soda + fries - $5.99

• (3)

  (1) burger – TOTAL $3.99; (2) burger + soda ($2.00) + fries ($3.00) – TOTAL $5.99

• (4)

  (1) burger – TOTAL $3.99; (2) burger ($3.99) + soda ($2.00) – TOTAL $5.99; (3) burger + soda ($2.00) + fries ($3.00) – TOTAL $5.99

After selecting one of the menu items, the participants reported their demographic information.

Study 3: results

The effect of decoy pricing in this study was not as pronounced as in Study 2 but it was still statistically significant (χ²(1) = 5.653; p = 0.017), thus providing further support for Hypothesis 1. When the decoy offer was absent, 18% of respondents selected the lower-priced offer (burger) and 82% selected the higher-priced offer (burger + soda + fries). However, in the decoy present condition, only 6.9% of people selected the lower-priced offer (burger) and 93.1% selected the higher-priced offers.

In contrast to Study 2, there was no evidence of the moderating effect of component price on the effect of the decoy offer. Contrary to the expectation that itemized prices would counter the effect of the decoy offer, Table 3 shows that the percentage of participants who selected a higher-priced offer in the decoy absent situation was higher when the prices were simple (86%) vs itemized (78%). Moreover, the percentage of participants who selected higher prices in the decoy offer condition was relatively similar across both simple (92.3%) and itemized prices (93.9%).

The results from the logistic regression failed to support Hypothesis 2. A Hosmer and Lemeshow test indicated that the correspondence between the actual and predicted values of the dependent variable is high (χ²(2) = 0.000, p = 1.000). Finally, the regression coefficient for the interaction effect (decoy × component price) was not significant (β = −0.795, p = 0.404).

Contribution and discussion

Across four studies and both restaurant and hotel contexts, results indicate that consumers generally use decoys as anchor points to make choices that are more lucrative for hospitality businesses. In Studies 1, 2, and 3, we consistently demonstrate that when promotional ads contain a more expensive option that offers a higher value for the money than the decoy alternative, consumers tend to choose the more expensive option in a greater percentage than another, lower-priced option. In contrast, when a promotional ad does not incorporate a decoy option, the selection of a more expensive option decreases in favor of a lower-priced option.

The results from Study 1 demonstrate that hotels can use decoy prices to increase sales of packages with cancellation policies, and consequently generate higher average daily rates and revenue. Even with a slight increase in price (from $119 to $129), the decoy option yields a greater likelihood that customers to select a higher-priced hotel product. Similarly, the results from the pilot study (burger + soda + fries - $7.99 vs burger – $3.99) and from Study 2 with the most dramatic price increase for bundled items (burger + soda + fries - $7.99 vs burger – $3.99) seem to show the strongest effect of decoy pricing. While still present, the effect of decoy pricing is not as strong when the price of the bundled items is only slightly higher (burger + soda + fries - $5.99) than the price of the single main item (burger $3.99). Such results show that decoy pricing can be an effective tool to increase sales, but its effect will depend on the specific balance between different product prices. This finding also pinpoints that price anchors can be impactful strategies, however, their effectiveness is rather selective.

Finally, the research investigated whether the presence of component prices within promotional ad bundles impacts the effects of decoy pricing. Contrary to the researchers' expectations, the utilization of component prices did not diminish the influence of decoy pricing. In fact, when decoy pricing strategies were employed, a larger proportion of participants opted for higher-priced options if the prices were itemized, as opposed to when only aggregate pricing information was provided. Specifically, in Study 2, even in the absence of a deliberate decoy, a greater percentage of respondents chose the more expensive option when individual component prices were disclosed, suggesting that transparent component pricing can act as unintentional decoys. However, this phenomenon was not replicated in Study 3, which used different price points, thus suggesting that the effectiveness of unintentional decoy prices might be context-dependent. Nonetheless, these findings underscore the utility of employing deliberate decoys as a strategy to enhance sales.

Theoretical and managerial implications

The theoretical implications of this research are multifaceted, contributing to the literature on consumer behavior, pricing strategies, and the hospitality industry. By examining the influence of decoy pricing on consumer choices, this study advances ones understanding of the decision-making process and the psychological mechanisms that underlie consumer preferences.

This research enriches the existing body of knowledge on decoy pricing and anchoring effects, offering empirical evidence that demonstrates the effectiveness of decoy pricing across various contexts in the hospitality industry. It extends the generalizability of decoy pricing theory by showcasing its impact on both restaurant and hotel contexts, highlighting its relevance and applicability in different sectors.

The study also contributes to the literature on consumer decision-making by examining the psychological mechanisms that drive the effectiveness of decoy pricing. It reveals that the presence of a decoy option can alter consumer perceptions of value, guiding them towards choices that are more profitable for businesses. This insight has significant implications for understanding how pricing strategies can shape consumer behavior and preferences, particularly in industries where product offerings are complex or where there is a high degree of perceived similarity between options.

Finally, this research also provides insights into the role of transparency in pricing strategies. By demonstrating that the inclusion of component prices in promotional ad bundles does not weaken the effect of decoys, it challenges conventional wisdom and contributes to the ongoing debate on the impact of pricing transparency on consumer decision-making.

Overall, the theoretical implications of this research are instrumental in advancing our understanding of the intricacies of consumer behavior and decision-making processes in the context of pricing strategies, particularly within the hospitality industry. The findings of Herrera and Young (2023) provide a pertinent context for considering the broader implications of dynamic pricing strategies in the hospitality sector, particularly in restaurants. They highlight the critical role of customer perceptions in the acceptance of variable pricing models, such as peak-load pricing. Similar to our observations on decoy pricing, their study suggests that transparency and customer understanding of pricing rationales are crucial for mitigating adverse reactions and maintaining customer satisfaction and loyalty. This aligns with our findings, where the clarity of pricing—whether through itemized or bundled prices—significantly influences consumer preferences and perceptions of value. Furthermore, Herrera and Young’s exploration of the moderating effects of familiarity with revenue management practices complements our discussion on the psychological mechanisms underlying effective pricing strategies. Such insights are instrumental in refining revenue management approaches that enhance profitability and align with consumer expectations and ethical marketing practices.

Webb, Ma, and Cheng (2023) provide a compelling framework for overcoming traditional barriers in restaurant revenue management through the Priority Mixed Bundle (PMB) strategy. This strategy effectively addresses the challenges of customer segmentation, price discrimination, and communication of price variances—areas that are also critical in the application of decoy pricing. Webb et al. (2023) emphasize the importance of strategic pricing to enhance perceived value and fairness, essential for customer retention and satisfaction. The PMB strategy’s ability to segment customers and transparently communicate pricing options parallels our findings on the effectiveness of decoy pricing in influencing consumer choices towards higher-priced options. Furthermore, Webb et al.'s assertion that their strategy leads to increased revenue while maintaining customer perceptions of fairness provides a robust foundation for considering similar strategies in other contexts of hospitality management, extending the generalizability of our results and highlighting the broader applicability of sophisticated pricing strategies in enhancing business profitability.

This study offers valuable insights for practitioners seeking to boost profits by enriching consumer behavior theories and providing practical strategies for implementing pricing techniques. Pricing strategy, a cornerstone of marketing, significantly impacts sales, perceived value and quality, and ultimately profit margins. In the hospitality industry, businesses are increasingly focused on aligning marketing strategies with customer relationship management, while also enhancing profitability.

In order to bridge customer relationship management with revenue management, as suggested by Guillet and Shi (2019), it is crucial to understand the role of price framing in shaping customers' perceptions of fairness. For instance, in the restaurant sector, price framing affects how customers perceive fairness, thereby influencing revenue management (Wirtz and Kimes, 2007). Hotel managers must also evaluate if discrepancies between customers' perceived fairness, trust, and pricing history negatively impact overall hotel performance (Baker, Eziz, & Harrington, 2020). Chen and Chen's (2024) study intersects with our findings on decoy pricing by demonstrating how strategic pricing mechanisms can serve to redirect consumer choices toward more profitable avenues—whether by enhancing the attractiveness of direct booking options over third-party alternatives or by structuring price presentations that favor higher-priced bundles in a restaurant or hotel context. Moreover, Chen and Chen’s identification of conditions under which best rate guarantees benefit both the hotel and the OTA mirrors our analysis of when decoy pricing can most effectively steer consumer decisions towards higher revenue outcomes. Their work complements our findings and broadens the scope of how pricing strategies can be optimized in the hospitality sector for both competitive advantage and consumer satisfaction.

Our study reveals that customers are more likely to opt for higher-priced offerings presented through promotional advertising when a decoy offer is included, creating the impression of a “good deal.” This pricing approach is less likely to interfere with customers' evaluations of the brand, and may even foster long-term relationships by cultivating the belief that the company offers better value compared to the decoys.

It is recommended that managers in the hospitality industry consider the potential advantages of decoy pricing, as it may be perceived as a strategy that serves broader business goals rather than merely self-serving tactics. When consumers view offerings that are promoted alongside decoys as more attractive, the relationship between the customer and the company is enhanced, which contributes to sustained profitability. The strategic inclusion of decoy items can significantly affect consumer decisions and act as an effective tool in promotional advertising to increase revenue.

Furthermore, the findings suggest that the transparency of itemized pricing in product bundles does not reduce the effectiveness of decoys. Therefore, it is encouraged that more hospitality firms integrate decoy pricing into their promotional efforts to optimize profit maximization.

Limitations and future research suggestions

This study encompasses several limitations that should be addressed in future research. Primarily, the research utilized specific price points, which could significantly influence the results. A broader variation in price options is necessary to yield more realistic and generalizable findings. Moreover, the reliance on scenario-based experiments may detract from the realism of the results, suggesting that future studies might benefit from employing field experiments to enhance ecological validity. Additionally, while this research has explored the effects of decoy pricing within specific sectors of the hospitality industry, further investigations could extend these findings across other product categories such as transportation, travel packages, events, and entertainment. Exploring the effectiveness of decoy strategies across these varied contexts would enhance understanding of their applicability and effectiveness in different service settings.

Another critical avenue for future research lies in investigating the psychological mechanisms underlying consumer responses to decoy pricing. This study primarily focused on the basic effects of promotional advertising with decoys on choice as a dependent variable. Future research should explore the roles of other moderating and mediating variables such as consumer emotions, cognitive biases, and decision fatigue to provide a more comprehensive explanation of how decoy pricing influences consumer choices. Understanding these underlying mechanisms could offer more nuanced insights for both scholars and practitioners regarding the strategic implementation of decoy pricing.

Future studies could also explore the impact of decoy pricing across different cultural contexts to understand how cultural variations in consumer behavior might affect the effectiveness of such pricing strategies. This would enhance the generalizability of the findings and cater to a global audience, potentially increasing citations from international researchers.

There is a need for longitudinal research to assess the long-term effects of decoy pricing on consumer loyalty and brand perception. Understanding whether the initial boost in sales from decoy pricing translates into sustained customer relationships could provide invaluable insights for both academics and practitioners.

With the increasing integration of AI and machine learning in marketing practices, future research could examine how these technologies can optimize decoy pricing strategies in real-time. Such studies could provide cutting-edge insights into the dynamic interplay between technology and consumer psychology.

Finally, while this research provides foundational insights, further studies could investigate sector-specific applications of decoy pricing, such as in luxury hotels versus budget accommodations or fine dining versus casual restaurants. Each sector may exhibit unique consumer responses to decoy strategies, enriching the academic discourse.

Table 1

Decoy price hotel cancellation policy crosstabulation – study 1

Decoy * Choice crosstabulation
			Choice		Total
			Low price selected	High price selected
Decoy	No decoy	Count	33	18	51
		Expected Count	25.5	25.5	51.0
		% within Decoy	64.7%	35.3%	100.0%
	Decoy	Count	18	33	51
		Expected Count	25.5	25.5	51.0
		% within Decoy	35.3%	64.7%	100.0%
Total		Count	51	51	102
		Expected Count	51.0	51.0	102.0
		% within Decoy	50.0%	50.0%	100.0%

Source(s): Authors’ own work

Table 2

Decoy price and manipulated transparency crosstabulation – study 2

Scenario * Choice crosstabulation
			Choice		Total
			Low price selected	High price selected
Scenario	no decoy simple	Count	25	16	41
		Expected Count	16.9	24.1	41.0
		% within Scenario	61.0%	39.0%	100.0%
	decoy simple	Count	13	30	43
		Expected Count	17.7	25.3	43.0
		% within Scenario	30.2%	69.8%	100.0%
	no decoy itemized	Count	17	18	35
		Expected Count	14.4	20.6	35.0
		% within Scenario	48.6%	51.4%	100.0%
	decoy itemized	Count	11	30	41
		Expected Count	16.9	24.1	41.0
		% within Scenario	26.8%	73.2%	100.0%
Total		Count	66	94	160
		Expected Count	66.0	94.0	160.0
		% within Scenario	41.3%	58.8%	100.0%

Source(s): Authors’ own work

Table 3

Decoy price and manipulated transparency crosstabulation – study 3

Scenario * Choice crosstabulation
			Choice		Total
			Low price selected	High price selected
Scenario	no decoy simple	Count	7	43	50
		Expected Count	6.2	43.8	50.0
		% within Scenario	14.0%	86.0%	100.0%
	decoy simple	Count	4	48	52
		Expected Count	6.5	45.5	52.0
		% within Scenario	7.7%	92.3%	100.0%
	no decoy itemized	Count	11	39	50
		Expected Count	6.2	43.8	50.0
		% within Scenario	22.0%	78.0%	100.0%
	decoy itemized	Count	3	46	49
		Expected Count	6.1	42.9	49.0
		% within Scenario	6.1%	93.9%	100.0%
Total		Count	25	176	201
		Expected Count	25.0	176.0	201.0
		% within Scenario	12.4%	87.6%	100.0%

Source(s): Authors’ own work