Option framing for upselling tourism services: Does cognitive availability prevent irrational choices?

Abstract

This article examines the effect of option framing and cognitive load on consumer choices of tourism services. Previous literature has shown that consumers tend to choose more options and spend more money when they begin the choice process from a complete set of options (downgrade/delete framing) than when they start choosing from a more basic set of options (upgrade/add framing). To exam this irrational behavior, we conducted two experimental studies with 561 consumers of leisure travel. The results of the two experiments provided robust evidence on the effect of the downgrade framing strategy on upselling tourism services and revealed that cognitive availability did not prevent consumers from making irrational choices. These findings indicate that decisions involving leisure trips may be even more susceptible than previously thought to cognitive biases and contextual influences due to their emotional and hedonic aspects, extending the existing literature on behavioral economics in tourism.

Keywords

behavioral economics cognitive load consumer behavior decision process option framing upselling tourism services

Introduction

The evolution of technology and management strategies has led companies to abandon the paradigm of standardized products and services in favor of one that allows them to make offers that more closely match the preferences of each consumer (Gilmore and Pine, 1997; Piccoli et al., 2017). Currently, companies in the travel industry are able to offer flexible sets of services to their customers, such as multiple options of hotel amenities, and dynamic packaging (Buhalis and Law, 2008). This flexibility can improve the perceived value of a purchase, reduce price sensitivity, and increase levels of customer satisfaction and loyalty, making this approach a significant tool for succeeding in a highly competitive field (Jin et al., 2012).

Service providers often adopt upselling techniques, trying to influence customers to choose more expensive items, thus increasing revenues per purchase (Denizci Guillet, 2020; Heidig et al., 2017; Norvell et al., 2018). Considering the need to present flexible offers (Steffen et al., 2019) and ensure higher profitability through upselling strategies (Ayvaz-Cavdaroglu et al., 2019), a question that arises for travel agencies and other distribution channels for tourism services concerns the design of an offer: Which is the best combination of services to present to customers as a starting point for the customization process?

As long as the same options are available at the starting point of the decision-making process, rational choice theory predicts that the initial set of items will have no effect on the final choice. However, behavior economics theory and evidence have shown that consumers frequently make inconsistent choices that are irrational, thus challenging the prediction of rational choice theory (Gilovicet al., 2002; McCabe et al., 2015; Tversky and Kahneman, 1974, 1981; Wattanacharoensil and La-ornual, 2019). One particular condition where irrational choices have been studied is called option framing, a circumstance where consumers may add/upgrade or exclude/downgrade items from a set of options that are initially presented (Biswas, 2009; Lu and Jen, 2016; Park et al., 2000). Research has shown that consumers tend to choose higher quality, more complete, and expensive sets of items when they start the customization process from superior sets (i.e. downward framing) than when they start from a lower quality, smaller, and cheaper set of items (i.e. upward framing) (Biswas, 2009; Biswas and Grau, 2008; Herrmann et al., 2013; Jin et al., 2012; Levin et al., 2002; Park et al., 2000; Steffen et al., 2019). Experiments investigating option framing over the last 20 years have revealed how option framing affects consumer choices of durable and consumption goods, such as automobiles, computers, treadmills, and pizza and salad toppings (Biswas, 2009; Biswas and Grau, 2008; Herrmann et al., 2013; Levin et al., 2002; Park et al., 2000).

The effects of option framing for tourism services has not yet been explored through rigorous experimental studies. To date, the few studies conducted on this topic used quasi-experimental and nonexperimental methods (Jin et al., 2012; Steffen et al., 2019). We therefore conducted two experiments to provide stronger evidence on the relationship between option framing and tourism consumption choices, and whether the relationship is causal.

The tendency to choose more options and spend more money in downward framing (downgrade/delete) and to choose less options and spend less money in upward framing (upgrade/add) can be explained by the influence of the initially suggested offer and the effect of loss aversion (Biswas, 2009; Biswas and Grau, 2008; Herrmann et al., 2013; Jin et al., 2012; Levin et al., 2002; Park et al., 2000; Steffen et al., 2019). This behavior is associated with the system of intuitive, affective, and heuristic choices. Consistent with this idea, Biswas and Grau (2008) showed that the effect of option framing is greater for subjects who make choices under conditions of higher cognitive load (i.e. performing a simultaneous task, such as memorizing a big number) when selecting options for an automobile.

Tourism, however, is a different kind of product. The consumption of tourist goods and services is inherently hedonic and experiential (Decrop and Snelders, 2004; Walls et al., 2011). As such, the choices made for leisure travel may be naturally more affective than choices of utilitarian goods such as automobiles. Decisions involving leisure travel tend to be based on intuitive, affective, and heuristic judgments, a mode of information processing that is more susceptible to cognitive biases (Stanovich and West, 2000). Hence, the availability of cognitive resources may have a different impact in the context of option framing for tourism than for autos. We, therefore, conducted a second experiment to test the influence of cognitive load on option framing in the tourism sector.

The outline of this article is as follows: We first review previous studies on the option framing effect, discuss theoretical explanations for the phenomenon, and consider the way cognitive load may moderate the option framing effect, thereby establishing the foundation for our hypotheses. We then describe the design and results of our two experiments. We conclude with a discussion of our findings, their implications, and possibilities for future research.

Literature review

Option framing

When consumers make buying decisions in general and travel decisions in particular, they consider a set of options presented to them by service providers. In these situations, rational choice theory predicts that if the same options are made available during the decision-making process, the initial set of items presented will not affect the consumer’s final choice.

However, behavioral economics theory and previous evidence have shown that consumers may be influenced by the initial options presented, frequently making incongruous choices that are irrational, thus not conforming to rational choice theory (Gilovic et al., 2002; McCabe et al., 2015; Tversky and Kahneman, 1974, 1981; Wattanacharoensil and La-ornual, 2019).

Indeed, the same problem and the same set of choices can be presented to consumers in different ways, leading them to make a selection of one particular formulation rather than other possibilities. This phenomenon has been called framing on the behavioral economics literature (Tversky and Kahneman, 1981). The concept of framing and its biasing effect on judgments has been applied to different aspects of tourist choices, such as temporal booking decisions (Rahman et al., 2018), and variety-seeking in bundled tourism services (Kim et al., 2018). A special form of framing, which Park et al. (2000) called option framing, is one in which a set of options is presented in two ways. In upward framing, an inferior set is initially presented to the consumer, who can then add or upgrade items. In downward framing, a superior set is presented and items can be excluded or downgraded.

In both types of option framing, the set of options offered is the same, so that all final combinations available in one framing are also available in the other. Consumers are free to choose the options they consider to be closer to their preferences. The rational theory of behavior predicts that the final set of options chosen would be the same in either framing.

Nonetheless, existing studies have consistently shown that downward framing leads subjects to choose a larger number of items and higher quality items than in upward framing. This conclusion has been tested and confirmed for several kinds of purchases, such as cars, condominiums, treadmills, computers, and pizza and salads toppings (Biswas, 2009; Biswas and Gra, 2008; Cheng et al., 2013; Herrmann et al., 2013; Levin et al., 2002; Park et al., 2000; Peng et al., 2016; Pornpitakpan, 2009).The same effect of option framing was found when consumers made choices among tourism services (Jin et al., 2012; Steffen et al., 2019).

Some moderators of the framing effect have been identified by previous studies. The effect of option framing was amplified, with even higher consumer spending, in downward framing under the influence of different conditions, such as anticipation of regret over a purchase (Park et al., 2000) or the presence of cognitive restrictions (Biswas and Grau, 2008). Other conditions reduced or eliminated the framing effect, for instance, when consumers were highly committed to the product category (Park et al., 2000) or when they were more attentive to the monetary aspects of their choices (Biswas, 2009). The presence of recommendations from other consumers in descriptions of available options was found to promote expenditures that were equivalent in both upward and downward framing (Herrmann et al., 2013). In addition, the influence of demographic and personal traits of consumers has also been investigated, revealing that different age-groups are equally subject to option framing, although consumers’ focus in self-regulation (e.g. being promotion-focused or prevention-focused) may change the strength and direction of the effect (Cheng et al., 2013). However, results related to decisions made in an experiential processing mode or with an emotional focus have been inconsistent (Biswas, 2009; Peng et al., 2016).

Table 1 presents a summary of studies on option framing in different contexts.

Table 1.

Studies on the option framing effect and consumer choices.

Authors	Types of option framing	Consumption decision	Variables tested
Park et al. (2000)	Add vs. delete	Customization of automobiles, treadmills, and computers	Types of pricing; regret; commitment with product category
Levin et al. (2002)	Add vs. delete	Choice of pizza and salad toppings	Types of food; cultural differences (USA vs. Italy)
Biswas and Grau (2008)	Add vs. delete	Customization of automobiles	Availability of cognitive resources; redundant product information
Biswas (2009)	Add vs. delete	Customization of automobiles	Consumers’ processing modes (rational vs. experiential); cognitive constraints
Pornpitakpan (2009)	Add vs. delete	Condominium purchase	Decision difficulty; decision time
Jin et al. (2012)	Upgrade vs. downgrade; add vs. delete	Travel packages	Quality conscious vs. promotion-focused consumers; peripheral service vs. core service attributes
Herrmann et al. (2013)	Add vs. delete	Customization of automobiles	Customer recommendations
Cheng et al. (2013)	Add vs. delete	Customization of automobiles	Consumer’s goal orientation (promotion vs. prevention focus)
Peng et al. (2016)	Add vs. delete	Customization of automobiles	Age and purchase motivations
Steffen et al. (2019)	Upgrade vs. downgrade	Board and lodging in travel packages	Couples vs. solo travelers

Foundations of option framing

Until a few decades ago, the dominant thought in behavioral and social sciences, influenced by the ideas of neoclassical economists such as Jevons, Menger, and Walras, was that individuals tend to behave consistently and rationally. However, evidence from behavioral economics has repeatedly shown that individuals are susceptible to a number of cognitive biases that lead them to make inconsistent and irrational choices (Gilovic et al., 2002; Tversky and Kahneman, 1974, 1981). This sort of behavior has been studied in several fields, including tourism (McCabe et al., 2015; Wattanacharoensil and La-ornual, 2019).

The option framing effect can be explained through Prospect Theory (Kahneman and Tversky, 1979). According to this theory, the judgment of an element’s value depends on the reference point used. The result of a decision is coded as a gain or a loss in comparison with the reference point (Kahneman, 1992). In addition, people feel the loss of a value more intensely than they feel a gain of the same value. In other words, there is a discrepancy between the evaluation of gains and losses, since losses have greater psychological weight than the corresponding amount of gains. This increased sensitivity to loss leads to the phenomenon called loss aversion.

While the original concept of loss aversion was studied in contexts of uncertainty, the application of this notion to contexts involving costs and benefits of riskless choices was called the endowment effect (Kahneman et al., 1990; Thaler, 1980; Tversky and Kahneman, 1991). The concept of the endowment effect helps to explain the bias resulting from option framing (Biswas and Grau, 2008; Levin et al., 2002; Park et al., 2000). Incurred costs are mentally coded as losses, while avoided costs are coded as gains. On the other hand, the addition or upgrade of an item to a consumer’s shopping cart is perceived as a gain, while the removal or downgrade of the item is seen as a loss.

In upward framing (Figure 1), the reference point is an inferior set of options. In this context, an addition/upgrade of a superior option is coded as a benefit, while the higher expenditure it requires is coded as a monetary loss. Due to loss aversion, the perceived gain of a benefit tends to be insufficient to offset the perceived monetary loss, resulting in resistance to add or upgrade items.

Figure 1.

Upward framing and loss aversion.

By contrast, downward framing (Figure 2) establishes a superior set of options as the reference point. In this context, a deletion/downgrade of a superior option is coded as the loss of a benefit, while the lower expenditure it requires is coded as a monetary gain. The perceived monetary gain tends to be insufficient to offset the perceived loss of a benefit, resulting in resistance to delete or downgrade items.

Figure 2.

Downward framing and loss aversion.

In sum, since losses are more valued than gains of an equivalent amount, consumers tend to show low willingness to give up what they currently have, whether it is money, a product, or a service (Park et al., 2000). Therefore, the choice decision to abandon the reference point tends to be infrequent.

Option framing in tourism services: Upgrade or downgrade

Jin et al. (2012) studied option framing in consumer choices of tourist services based on a sample of 201 Chinese graduate students. Participants were asked to choose a set of tourism services that might or might not include certain options (e.g. types of transfers). They were also asked to choose the level of quality they wanted in certain services (e.g. hotels with different star ratings). The results indicated that individuals who were presented with options in terms of downward framing ended up with higher total price than those presented with the options in terms of upward framing. However, Jin et al.’s study (2012) overlooked two relevant points. In the first place, the study was unable to prove the causal nature of the relationship between option framing and choices, since the participants were not randomly assigned to different framing conditions. In fact, they chose their own framing condition, which may have had a significant impact on results. Moreover, by examining only the total price of the chosen set of services without discriminating among services, the study was unable to distinguish between the effects of adding versus deleting options or of upgrading versus downgrading.

The effects of upgrade/downgrade option framing on the choice of tourism services were examined by Steffen et al. (2019). One study focused on the level of quality in hotel rooms, while another study examined the level of quality in meals offered through holiday packages. Both studies were conducted in actual conditions of consumption and had a quasi-experimental design with rigorous controls. In the first study, the effect of option framing was marginally significant, while the second study showed stronger effects. The authors also concluded that the option framing effect was not relevant for solo travelers, although this claim does not appear to be supported by their results, which suggested that the difference in the option framing effect between solo travelers and the reference group was not statistically significant.

In the analysis that follows, we focus on the relevance of the upgrade/downgrade framing effect on tourism consumption choices. We measure participant responses in two ways: (1) the probability of choosing superior services, and (2) the total price of the set of selected services. The first hypothesis to be tested is the following:

H1: Individuals tend to choose (a) superior services and (b) sets of services with a higher total price in the context of downgrade framing than in the context of upgrade framing.

Cognitive load

People whose minds are involved in various activities, thus working under conditions of high levels of cognitive load, are induced to rely on an intuitive, affective, and heuristic processing of information rather than on an analytical processing (Fedorikhin and Shiv, 2014; Gilbert, 1991; Pelham et al., 1994; Scarabis et al., 2006). When people are in such conditions and begin to pursue another cognitive task, their analytical capabilities begin to deplete, leading them to be more susceptible to heuristics and biases. Thus, it is expected that under conditions of high cognitive load, the effect of option framing will be stronger than under a low cognitive load. In fact, Biswas and Grau’s study (2008) on the choice of options for an automobile found that the effect of option framing was greater for subjects who were under conditions of high cognitive load than for those with a low load. Bringing this proposition to our study of consumer choices of tourist services, hypothesis 2 of this study states that:

H2₀: The effect of option framing on (a) the quality level of services and (b) the total price of the chosen set of services is stronger when the individual’s cognitive load is higher.

However, despite the theoretical and empirical support for H2₀, an alternative hypothesis can be considered due to the hedonic and experiential nature of tourism services. Biswas (2009) analyzed the effect of option framing on rational and experiential decision modes under conditions of low and high cognitive demand. For subjects stimulated to make an experiential decision guided by affect, without paying much attention to the rational and monetary aspects of the choice, the effect of option framing was greater for the group having a low cognitive demand.

The explanation for the inversion of the moderating effect of cognitive demand on the effect of option framing may lie in the fact that experiential choices tend to be made through intuitive and heuristic reasoning. Deep analytical reasoning is not normally used in these decisions, so creating a high cognitive demand may not alter the result of the choice. This perspective constitutes the alternative hypothesis 2:

H2_a: The effect of option framing on (a) the quality level of services and (b) the total price of the chosen set of services is not affected by the individual’s cognitive demand.

Study 1: Option framing

The first experiment tested H1, the central hypothesis of option framing, in the choice of a set of tourism services. The between-subjects experimental design of the study was inspired by the one created by Jin et al. (2012). The participants were given the task of choosing the composition of a 7-day travel package to a popular destination in Brazil, the city of Salvador. This package included accommodation, meals, transportation, and travel insurance.

For a randomly selected group of participants, the initial package included services of an inferior quality level and lower price. Upgrade alternatives were presented, such that the four inferior services could be exchanged for services of superior quality and price. The initial value of the package in this condition was R$2700 (about US$700), and it could go up to R$4060 (about US$1050) if all four services were upgraded from inferior to superior.

For the other experimental group, the initial package included services of superior quality and price. Such services could be downgraded to services of inferior quality and price, which would lead to a discount on the total price of the package. In this case, the initial price of the package for the downgrade group was R$4060 (about US$1050), which could go down to R$2700 (about US$700) if all four superior services were exchanged for their inferior alternatives. Each of the two experimental groups was thus given the appropriate variant of the following introductory text:

The price of the basic [complete] travel package is R$2,700.00 [R$4,060.00] per person and it includes air transportation, accommodation, meals, transfers, and travel insurance. If you wish, you can customize your package by choosing upgrades [downgrades], that is, you can choose a superior [inferior] service for each item in the package.

For the upgrade group, the inferior services were presented as included, which was reinforced by highlighting that choosing them would imply an increase of R$0 in the total price of the package. By contrast, choices of superior services were associated with total price increases (Figure 3).

Figure 3.

Example of a pair of choices in an upgrade scenario.

For the downgrade group, the superior services were presented as included in the package, associated with increases of R$0 to the total price, while the inferior services were presented as alternatives that involved price reductions (Figure 4).

Figure 4.

Example of a pair of choices in a downgrade scenario.

For all groups, the choice of either the included or the alternative service required subjects to click on an item in the questionnaire. The introductory text of the experiment indicated that all choices were available, so that the subject could keep all, some, or none of the suggested services.

The prices of the service alternatives included in the package reflected current prices of actual offers available on the market. Each service was illustrated by an image. The image of travel insurance highlighted the coverage of the service. Figure 5 shows the descriptions and images illustrating each alternative in the experiment.

Figure 5.

Service alternatives presented to respondents in the experiment.

In addition to the experiment itself, the survey questionnaire included an initial section with sample filter questions. The questionnaire was administered only to individuals who had taken at least one leisure trip out of their home state in the 12 months prior to the survey. In this way, the subjects who were surveyed constituted a sample that was qualified by virtue of their actual consumption of leisure travel. To reduce the effects of variables associated with their place of residence, only individuals residing in the states of Rio de Janeiro and São Paulo were surveyed.

The final section contained questions related to the participants’ satisfaction with the choices made in the experiment, as well as their actual experiences of buying tourist packages and their sociodemographic variables. Each type of satisfaction was measured by three items on a five-point scale.

Data collection

Data collection was carried out at the domestic-flights airport in the city of Rio de Janeiro. The questionnaire was developed in web programming language and presented to participants on tablets. The stimuli, questions, and answers were collected through an electronic platform. Subjects were randomly selected. After the initial filter questions, the tablets were handed to the participants for self-administration. The purpose of using this strategy of survey administration was to offer better conditions for presenting the stimuli and to collect responses at the participants’ own pace. A final sample of 217 subjects was obtained.

All data collection procedures had been tested with a preliminary sample of 216 tourists. This test was valuable for training the field team and refining the research instrument.

Results

Almost half (49.8%) of the participants had traveled three times or more outside their home state in the 12 months prior to the survey. In addition, the majority of respondents reported having previously purchased at least one travel package in their lives (59.4%). These characteristics of the sample indicate its representativeness for the analysis of the participants’ on-screen behavior.

Total package price

In the upgrade framing, the average price of the service arrays chosen by subjects was R$3125.32 (about US$809.70), while in the downgrade framing the average price was R$3261.32 (about US$844.90). Therefore, the results indicate that consumers presented to the downgrade framing spent an average of R$136 (about US$35.20) more than consumers in the upgrade framing group. This amount represents 10% of the total possible difference in price between the inferior and the superior travel packages.

Since the distribution of the total price in the experiment was truncated by the values defined for each of the services, its normality may be contested. Assuming the normality of the distribution, the t-test reveals that the difference is statistically significant (t = 2.034; p = 0.043). When normality is not assumed, the conclusion is the same, since the Mann–Whitney U test suggests that the difference between the two experimental groups is significant (p = 0.021). Therefore, the experiment provides preliminary support to the H1 when evaluated from the perspective of total package price.

Individual service choices

Although previous research findings suggest that the total price is a valid variable for testing option framing (Biswas, 2009; Biswas and Grau, 2008;Herrmann et al., 2013; Levav et al., 2010; Park et al., 2000), such an analysis may not be appropriate when the characteristics and prices of items are different. It is possible that the choice of a hotel follows a different mental process than the choice of travel insurance due to the discrepancies in price and nature of these services. In addition, the results of the analysis of total price are biased in favor of decisions made about the most expensive services. In our experiment, for example, the hotel upgrade represents 67% of the total possible increase in the package price.

Therefore, a more robust test of the option framing hypothesis was conducted, using the choice of the most expensive option as dependent variable. From this perspective, each participant provided four observations of the same dichotomous dependent variable (Y_ij, 1 ≤ j ≤ 4). The main explanatory variable was a dummy variable indicating the downgrade framing condition (F_i). The four different services were represented by three dummy variables (D_ij). A random-effect term was included to deal with the correlation between the four observations made by the same subject (ε_i). Therefore, u_ij being the error term, the value of the most expensive alternative for individual i is given as:

Assuming that u is Gumbel distributed, the probability of selecting the most expensive alternative is given by a logit binary-panel model (Arellano, 2003; Baltagi, 2008), and the β parameters can be estimated by maximum likelihood. Estimates of this model are presented in Table 2.

Table 2.

Model estimates in experiment 1.

Variable	Coefficient	Std. Err.	z	p > \|z\|
Downgrade	0.375	0.205	1.83	0.067
Hotel	−0.832	0.223	−3.73	0.000
Meals	−0.653	0.219	−2.98	0.003
Transfer	0.535	0.213	2.51	0.012
Travel insurance*
Constant	−0.768	0.347	−2.21	0.027
σ ²	0.970	0.145
ρ	0.222	0.052

* Reference group.

The model as a whole was significant (p < 0.001). The parameter σ² is the panel-level standard deviation, while ρ is the proportion of its contribution to the total variance. The significance of the test ρ = 0 (p < 0.001) indicates that the treatment of the correlation between the observations of the same individual contributed to the adjustment of the model. Therefore, the adjustments of the traditional logit model for panel data proved to be a necessary condition for obtaining consistent estimations of parameters.

The results show that the main effect of option framing was marginally significant (z = 1.83; p = 0.067), offering partial support to H1 when evaluated from the perspective of individual service choices. The differences in the propensity to choose the most expensive alternative among services followed a consistent pattern: the larger the price difference, the lower the propensity to choose the most expensive option.

Satisfaction with the process and the result of the decision

The composition of the initial travel package potentially has two types of consequences. On the one hand, as already discussed, it may affect the probability of choices among alternatives and, consequently, the total price of the selected package. However, a second potential effect should be considered: the variation in consumer satisfaction with the process and the result of their choice (Jin et al., 2012). In this study, it was thus relevant to investigate whether there was a difference in the levels of satisfaction between the two experimental groups.

To measure participants’ satisfaction with the process and the result of their choices, the questionnaire included two scales of three items each, the same ones used by Jin et al. (2012). An internal reliability analysis using Cronbach’s α suggested the exclusion of one item from the original scale and the aggregation of the remaining five in a single satisfaction scale (α = 0.91). The single scale of five items was confirmed by an exploratory factor analysis. A satisfaction index was calculated by the average of the five items. Since the original items were measured on a five-point scale, the final satisfaction index also varied from 1 to 5.

The average satisfaction index of the participants in the upgrade framing group was 4.31, while for the downgrade framing group the average was 4.36. The difference was not statistically significant (p = 0.58). Therefore, the results showed that the level of consumer satisfaction is the same for both the upgrade and downgrade framings.

Study 2: Moderating effect of cognitive load

The objective of experiment 2 was to examine whether there is a moderating effect of cognitive resources availability on the effect of option framing when consumers are choosing services for leisure travel. To test the moderating effect of cognitive availability on option framing, a 2 × 2 between-subjects experimental design was developed, with two framing conditions (upgrade and downgrade) and two levels of cognitive load (low and high). The manipulation of the option framing followed the same procedure as in experiment 1, using the same scenario of the choice of a 7-day leisure trip to Salvador.

The cognitive load was manipulated following the procedure used by Biswas and Grau (2008) and Biswas (2009). Before reaching the step of making a service choice, respondents in the low cognitive load condition were asked to memorize a two-digit number (12), while those in the high cognitive load condition were asked to memorize a six-digit number (389745).

The experimental design options and the manipulation of the cognitive load were subject to two preliminary tests, one with 209 undergraduate and graduate students, the other with a sample of 32 travel consumers.

Data collection

A final sample of 344 travel consumers were interviewed at the domestic-flights airport of Rio de Janeiro. Participants recorded their responses on tablets. The filters for participation in the experiment were the same as in experiment 1.

Results

The majority of participants (71%) had traveled three times or more outside their home state in the 12 months prior to the survey, and half (51%) had visited the city of Salvador at least once in their lives. In addition, more than half of respondents reported having bought at least one travel package in their lives (54.7%). Most of the subjects in the sample (53%) indicated a high or very high level of interest in the city of Salvador. Even though the travel package presented in the survey was hypothetical, a significant portion of survey respondents (38%) reported that the probability of purchasing a similar travel package would be high if it were available in the market. These data indicate that the sample surveyed was qualified for the analysis of the behavior that formed the object of this experiment.

Verification of manipulation of independent variables

An evaluation of the initial price of the travel package was included to verify the effects of manipulating the option framing. Respondents were asked three questions presented as five-point semantic differential scales on which they indicated whether they considered the total price to be high/low, unattractive/very attractive, or above the market/below the market. The results of the three questions were combined into a single scale, which when tested demonstrated a reasonable level of internal reliability (Cronbach’s α of 0.75). As expected, the individuals in the upgrade framing condition evaluated the initial package price more positively (an average of 2.02 for the three items) than the individuals in the downgrade condition (an average of 1.70). The difference was statistically significant (t = 3.219; p = 0.001).

The effectiveness of the manipulation of the cognitive load was examined through the rate of correct answers given by participants in the memorization exercise. The results showed that individuals in the low cognitive load provided the correct answer much more often (70%) than those in the condition of high cognitive load (41%). The difference was statistically significant according to Pearson’s chi-square test (χ² = 28.35; p < 0.001).

Total package price

The average total prices of travel packages in each of the four experimental groups are presented in Figure 6.

Figure 6.

Total average costs in each experimental group.

The subjects in the downgrade framing condition chose sets of services with a higher average price than those chosen by subjects in the upgrade condition. The difference of R$290.69 (about US$75.30) represents 21% of the total possible price difference between the inferior and the superior sets of services.

The average final price was analyzed using a 2 × 2 ANOVA. The difference between the two framing conditions was highly significant (F = 31.218; p = 0.000), providing support for the hypothesis that consumers choose sets of tourist services with higher total prices in the downgrade group than in the upgrade group. This result is consistent with that obtained in experiment 1 and provides additional support for the main effect of option framing.

The interaction between option framing and cognitive load was not significant (F = 0.058; p = 0.810), leading to the rejection of H2₀ and providing support to H2_a. In other words, there was no evidence of the moderating effect of cognitive load on the effect of option framing.

Individual service choices

A binary logit panel model, such as that employed in experiment 1, was used to analyze the choice of the most expensive option as the dependent variable. An additional dummy variable was included to capture the effect of the two levels of cognitive load. The estimates of this model are presented in Table 3.

Table 3.

Model estimates in experiment 2.

Variable	Coefficient	Std. Err.	z	p > \|z\|
Downgrade	0.564	0.210	2.69	0.007
High cognitive load	−0.286	0.210	−1.36	0.173
Downgrade × High cognitive load	0.230	0.295	0.78	0.435
Service 1	−0.834	0.170	−4.90	0.000
Service 2	−0.561	0.167	−3.36	0.001
Service 3	0.458	0.168	2.73	0.006
_cons	−0.070	0.181	−0.39	0.698
/lnsig2u	−0.438	0.282
sigma_u	0.803	0.113
ρ	0.164	0.039

The model as a whole was significant (p < 0.001). The test of ρ = 0 again pointed to the need for panel data adjustments in the traditional logit model (p < 0.001). The estimated parameters showed that the downgrade variable had a positive and significant effect (z = 31.218; p = 0.000), providing support for the H1. By contrast, the interaction between the downgrade framing and high cognitive load was not significant (z = 0.78; p = 0.435), confirming the result that the cognitive load does not moderate option framing. This result leads to the rejection of H2₀ and supports H2_a.

Satisfaction with the process and the result of the decision

As in experiment 1, the participants’ satisfaction with the process and the result of their choices was measured through six indicators, each using a five-point semantic differential scales. Internal reliability analysis showed good performance of the scale (α = 0.87).

Differences across the averages of participant satisfaction in the four experimental groups were not statistically significant (F = 0.933; p = 0.425). Therefore, the results indicate that the level of consumer satisfaction did not change as a function of the option framing or the cognitive load imposed on participants.

Purchase intentions

One of the most common criticisms of experiments in consumer behavior research regards their artificiality and generalizability (Webster and Sell, 2014). In order to examine whether the situation designed for this survey was credible and could motivate participants to make a real purchase, individuals answered the following question: If you had the chance, what would be the probability of buying this travel package? Participants indicated their intentions on a five-point scale from “not at all likely” to “extremely likely.”

The results showed that a significant portion of the survey participants (38%) considered the purchase of the travel package to Salvador very or extremely likely, while about a quarter (26%) rated the purchase as somewhat likely. There was no statistically significant difference between the downgrade and upgrade groups.

Conclusion

Our research successfully tested the effect of option framing on choices of a set of tourist services for a leisure trip, revealing that the initial composition of a tourist offer has implications for the final set of services chosen by consumers, even if all options available are exactly the same in the different framing conditions. In both studies we conducted, consumers tended to choose higher quality and more expensive services when the suggested initial set of services was superior, even though inferior alternatives were available. By contrast, consumers tended to choose lower quality and less expensive services when the starting point of the choice problem presented a range of inferior services.

The results of studies 1 and 2 affirmed the robustness of option framing and are consistent with other studies that examined the effects of upward and downward framing in other contexts (Biswas, 2009; Biswas and Grau, 2008; Herrmann et al., 2013; Park et al., 2000). The results presented here also showed that the upgrade and downgrade frames have impacts on the choice of tourism services, in line with the study by Jin et al. (2012) and Steffen et al. (2019). However, unlike prior research in the field of tourism, the present study employed a truly experimental method, proving that the relationship is causal. We have dealt exclusively with upgrade/downgrade framings, clearly separating them from add/delete framings and allowing unambiguous examination.

Unlike most previous studies, this work analyzed the effect of option framing on a set of items, not just on a single product. In this way, we offer broader ecological validity (Chaytor and Schmitter-Edgecombe, 2003; Schmuckler, 2001), since tourist trips almost always include various services that can be customized separately. Finally, while most previous research analyzed choices made by respondent samples composed mainly of undergraduate and graduate students, our work observed the choices of ordinary consumers and representatives of a social group with a high rate of consumption of the product under scrutiny.

Of foremost importance for this research, we examined the moderating effect of cognitive load on the effect of option framing, bringing new findings to the study of tourism services choices. In the second experiment, we examined this issue and found that there is no moderating effect of cognitive load on the option framing effect. The explanation may lie in the predominantly experiential nature of the choice of leisure travel services, a more hedonic type of choice (Decrop and Snelders, 2004; Walls et al., 2011), leading to a less rational and reflective decision in favor of one that is more intuitive, affective, and heuristic. This result corroborates the study by Biswas (2009), indicating that decision-making processes involving leisure travel may be even more susceptible to biases in judgment and contextual influences because they are decisions dominated by emotional aspects (Fedorikhin and Shiv, 2014; Knobloch et al., 2016). Our study contributes to a better understanding of how decisions are made in tourism and sheds light on an aspect that has been unclear in the literature. The perspective that low cognitive load is an indicator that the analytical processing system will control the decision (Fedorikhin and Shiv, 2014; Gilbert, 1991; Pelham et al., 1994; Scarabis et al., 2006) does not appear to be sustained in this situation. The extent to which analytical processing, which is less susceptible to bias, participates in decision-making also depends on other factors and stimuli, one of them being the type of purchase decision.

Finally, our research shows that theories in behavioral economics, generally neglected in tourism research, have great potential for application to studies related to tourists’ decision-making processes. Studies in the field of tourism are usually dominated by theoretical models that assume the perspective of traditional economics, using a model of a consumer who makes consistent decisions, has stable preferences, and rationally analyses the available alternatives (McCabe et al., 2015; Wattanacharoensil and La-ornual, 2019).

Implications and future research

The findings presented here indicate that, in principle, it would be more advantageous for travel agents to initially offer consumers packages consisting of premium services that can be reduced or simplified as opposed to packages consisting of basic services that can be improved. This approach represents an upselling technique that is both profitable and easy to be implemented (Heidig et al., 2017; Norvell et al., 2018; Steffen et al., 2019). This recommendation seems even more appropriate in light of the results indicating that using the downgrade option framing does not interfere with either consumer satisfaction levels or their purchase intentions. Nevertheless, this conclusion should be accompanied by some relevant caveats.

First, the downgrade frame involves a higher initial price for the consumers, which can trigger the perception of an expensive brand or product. This perception may alienate a portion of consumers who have a low commitment to a brand or a product category, particularly in markets dominated by strong price competition, such as the travel industry (Abrate and Viglia, 2016). However, this does not tend to occur with highly committed consumers or those with high brand loyalty (Park et al., 2000), and may even lead to more favorable results for the brand in the long run (Norvell et al., 2018). Thus, for service providers positioned in premium segments, whose customers show high levels of commitment and loyalty to certain brands, the downgrade option, which offers more complete products and high-quality options, should lead to higher levels of spending by their customers.

Secondly, the travel-package market is highly competitive in price, especially in the online environment (Abrate and Viglia, 2016), where price comparisons are made with great ease. Thus, presenting the most expensive offers from the outset may put the competitiveness of a company at risk. However, some travel agencies seek to avoid this effect by announcing cheaper initial packages as a way of attracting consumers to the negotiating table, then moving to offers of more expensive packages in response to the consumer’s initial engagement.

Our research has some limitations that are noteworthy. First, we studied stated choices instead of actual behavior. The limitations of experiments analyzing stated choices are well known. Although this type of study is still more frequent than field experiments and is widely accepted as a useful source of information (Gneezy, 2016), examining actual behavior yields results that are more representative and consistent (Viglia and Dolnicar, 2020).

Future studies could focus on other customizable services, such as air transport, tours, entertainment, and others. An examination of the relationship between the framing effect and prices or relative price changes is also needed. The moderating effect of sociodemographic and psychological characteristics of consumers should too be considered. Exploring which specific groups are more influenced or less influenced by the framing effect would yield useful information for managers.

Future research could also investigate how different levels of travel complexity, distance, duration, and costs impact consumers’ responses. For instance, it would be interesting to examine how the different choice patterns emerge from domestic and international tourism due to varying levels of cognitive resources employed in evaluating the set of options.

Footnotes

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: This work was financially supported in partial by the FAPERJ Foundation (Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro) and the CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior).

ORCID iDs

Verônica Feder Mayer

Glauber Eduardo de Oliveira Santos

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