Cultural Mindsets Matter: Reexamining the End Effect in Tourism Experiences

Abstract

Understanding the relationships between momentary episodes and overall evaluation is integral to creating tourist experiences because service providers strive to maximize positive outcomes and minimize negative ones. Past work has shown that the end experience outweighs other episodes (e.g., the start experience) when forming retrospective judgments, referred to as “the end effect.” Although researchers have paid considerable attention to the end effect in tourist experience evaluation, their findings are mixed and need to be further clarified. This research reconciles the inconsistency by examining the moderating role of cultural mindsets on the weight of end experience in overall evaluation. Across three experiments, this research reveals that the end experience is heavily weighted for tourists with an individualistic mindset but less so for those with a collective mindset. These findings help to explain the inconsistency in the literature and provide practical implications for destination marketing.

Keywords

tourism experience cultural mindset the end effect the peak-end rule

Introduction

Imagine that you have just returned from a 3-day tour. You experienced some fantastic scenery and had a good time on the first 2 days. However, on the final day, the attractions did not meet your original expectations and disappointed you. How would you feel when you finished the tour? Now consider another scenario where you experienced some unappealing attractions on the first day. However, you experienced some fantastic scenery and had a good time over the following 2 days. How would you feel when you finished this tour? Do these two tours deliver the same experience?

Consumers may react differently to tours with different schedules, even though the tours’ individual activities are identical (Montgomery & Unnava, 2009). The relationships between momentary experiences and global evaluation have received considerable attention in the consumer behavior and tourism literature. Previous research has documented the end effect in retrospective experience evaluations, whereby the end experience is heavily weighted instead of the start experience, due to its easy accessibility in memory (Kahneman et al., 1993; Y. Li & Epley, 2009; Montgomery & Unnava, 2009). In the scenario above, tourists may respond more negatively when a disappointing experience occurs on the last day (vs. the first day) since, according to the end effect, experiences at the end, rather than at the beginning, largely determine how tourists evaluate the whole experience.

Due to the heterogeneous and multi-episodic nature of the tourism experiences, scholars have examined the existence of the end effect in the tourism context (J. Kim & Fesenmaier, 2015; H. Kim & Kim, 2019; Leboeuf et al., 2014; S. Li et al., 2022; Miron-Shatz, 2009). The results, however, are inconsistent. Some research supports the end effect and claims that the end experience can predict the global evaluation (H. Kim & Kim, 2019; S. Park et al., 2018). Other scholars reject this hypothesis, suggesting that the end experience is not a significantly better predictor than other episodes such as the start experience (Bastiaansen et al., 2022; Chark et al., 2022; S. Li, 2021; Strijbosch et al., 2021). No study has explained these conflicting conclusions. We argue that one plausible reason for this discrepancy involves cultural differences. In past studies, researchers have recruited participants from South Korea (H. Kim & Kim, 2019), Europe (Strijbosch et al., 2021), or China (Chark et al., 2022). However, these studies reached their conclusions without considering the role of cultural differences. Understanding how the end effect varies across cultures is essential because globalization demands destinations to attract visitors from different cultures.

Cultural mindsets are one type of cultural cognition construct. They refer to cultural-specific mental representations of content, procedures, and goals that influence one’s judgments and behavior (S. W. S. Lee et al., 2010). For example, studies have demonstrated that loose or tight social relationships in one’s cultural context influence the person’s cognitive disposition to process stimuli independently or interdependently (Markus & Kitayama, 1991; Nisbett & Masuda, 2003; Oyserman & Lee, 2008). Previous research suggests that participants from an individualistic culture often regard information in independent episodes and process them in isolation (Oyserman, 2011; Oyserman & Lee, 2008). In contrast, participants from a collectivist culture regard information as interdependent episodes and process them in connection to each other. Given that tourists from different cultures hold distinct cultural mindsets, exploring the impact of cultural mindsets on the end effect is crucial. Therefore, we propose a research question: do tourists from different cultures (individualism vs. collectivism) attach the same importance to the end experience when they form an overall evaluation?

This study aims to examine the moderating effect of cultural mindsets on the end effect in order to reconcile the mixed findings from past studies. Specifically, this research adopts an experimental design to compare the weight of the end experience in overall evaluation by switching the temporal sequence of the same individual experiences. We postulate that the end effect is pronounced for tourists with an individualist cultural mindset, but the effect is attenuated for participants with a collectivist one. In the following sections, we will review literature related to the end effect in retrospective evaluation and cultural mindsets, on which we have developed our hypotheses.

Literature Review

The End Effect in Retrospective Evaluations

Extensive research has been conducted on how the temporal location of experience influences retrospective judgments. Research on the end effect dates back to the peak-end rule proposed by Kahneman et al. (1993). They postulate that the peak experience and the final experience are the best predictors of an overall evaluation. When controlling for the intensity of experience, the end of a sequence is weighted more than other temporal locations (e.g., the start) when individuals make an overall judgment retrospectively. In one of their experiments, participants reported less discomfort when adding a moderate painful experience after an intense one, even though they suffered for a longer time. The end effect occurs because of easy memory accessibility. Previous literature suggests that, compared to the start, there is less interference in the recall of the end stimulus (Greene, 1986), and, thus, the end is easier to retrieve in memory when recalling or reconstructing the experience (Montgomery & Unnava, 2009). The end effect has been examined in multiple leisure experiences, including enjoyment of food (O’Brien & Ellsworth, 2012), video watching (S. Li et al., 2022), music listening, and game-playing (Gutwin et al., 2016).

Considering that these simple, one-dimensional experiences are different from tourism experiences, which are usually more complex and multi-episodic, many studies attempted to examine the applicability of the end effect in tourism (Miron-Shatz, 2009; Strijbosch et al., 2021). Some research provides evidence of the end effect in the tourism context (H. Kim & Kim, 2019; S. Park et al., 2018; Strijbosch et al., 2021). For example, H. Kim and Kim (2019) collected data from 187 visitors to historic sites. They found that experience at the final attraction highly predicted overall satisfaction, supporting the end effect in the tourism context. Another study showed that participants are more willing to pay for vacation experiences displayed in an improving trend than a declining trend, even though the individual activities are the same (Montgomery & Unnava, 2009). On the other hand, some scholars argue that the end is not always a better predictor than other episodes (e.g., the start) when tourists evaluate the overall experience (Chark et al., 2022; Kemp et al., 2008; S. Li, 2021; Strijbosch et al., 2019, 2021). For instance, Chark et al. (2022) surveyed visitors in Macao and found that participants did not follow the peak-end rule. In addition, Strijbosch et al. (2021) rejected the end effect when tourists regarded the experience as a whole but supported it when tourists regarded the experience as the summation of individual episodes.

To summarize, prior work provides extensive insights into the relationships between momentary experiences and overall evaluation. However, the findings are inconsistent. In past studies, little attention was paid to cultural differences, which may lead to different cognition styles when processing information. In the present research, we introduce cultural mindsets, an essential cultural construct that cannot be neglected, especially in the international tourism context (Hosany et al., 2022), to explain inconsistent findings in the extant literature.

Another reason for the mixed findings involves methodology. Most research employs an experience tracking approach which requires tourists to report on-site experiences at each attraction, and then examines relationships between the end experience ratings and the overall ratings (Bastiaansen et al., 2022; Chark et al., 2022; H. Kim & Kim, 2019; S. Li, 2021; S. Park et al., 2018; Strijbosch et al., 2021). This method collects field data and possesses high external validity. However, the findings are limited to specific tourist destinations and can be easily confounded with other variables (e.g., the types of destinations). Therefore, it is necessary to closely examine the phenomenon in a controlled environment. The present research adopts an experimental method, allowing us to disentangle the start and end’s potential effects on overall experience evaluation to better understand the causality. The following section will review the relevant literature on cultural mindsets and develop a conceptual framework that explains the moderating effect.

Cultural Mindsets and Cognitive Processing Styles

Literature on culture psychology has demonstrated the distinction between Western culture and East Asian culture (for a review, see Briley et al., 2014), and one of the fundamental dimensions is the individualism-collectivism spectrum (Hofstede, 2001), which is defined by interdependence and independence of social relationships. Individualism is characterized by a preference for a loose social network where people are expected to care for themselves, whereas collectivism is characterized by a preference for a tight social network where people are expected to care for not only themselves but also their in-group members (Hofstede, 2001). Such difference in the value attached to social relationships across cultures is defined as a cultural mindset (Oyserman & Lee, 2008). Individualist culture takes the individual as a unit and emphasizes the independence and specialty of individuals. In such cultures, institutions and relationships promote individual well-being (Oyserman, 2011; Oyserman et al., 2009). For example, in Western countries, individuals are generally expected to develop their inner attributes and express their uniqueness. Thus, individuals view themselves as independent and autonomous (Nisbett, 2004; Nisbett & Masuda, 2003). By contrast, collectivist culture takes a group as a unit and emphasizes social harmony and interpersonal relationships. Individuals realize personal values through social engagement and relationships with others. For example, in East Asian countries, individuals are generally expected to attach great importance to social harmony. Thus, they view themselves as inseparable from others and part of the whole social network (Nisbett, 2004; Oyserman, 2011). When asked about self-knowledge, participants from East Asian cultures shared more descriptions of others while those from western cultures shared more descriptions of themselves (Greenwald & Pratkanis, 1984; Markus & Kitayama, 1991).

This difference is reflected in social influence and extends to people’s cognitive processes (Oyserman & Lee, 2008). Generally, due to a perceived connection to others, East Asian individuals with a chronic collectivist mindset tend to process information in relation to one another and assimilate informational elements holistically (holistic processing, Nisbett, 2004; Nisbett et al., 2001; Oyserman et al., 2009). When they form an overall evaluation, they rely on the perceptions that incorporate all episodes as a whole (Mourey et al., 2013). By contrast, due to the relative separation in a social context, Western individuals with a chronic individualist mindset develop a tendency to process information in relative isolation and focus on the main point (analytical processing, Nisbett & Masuda, 2003; Oyserman & Lee, 2008; Oyserman et al., 2009). When they form an overall evaluation, they rely on the most accessible information (Montgomery & Unnava, 2009). Although a cultural mindset is nurtured gradually and continuously in a society, it can also be situationally activated by priming (Oyserman, 2011, 2016).

Extensive literature has documented the evidence of cultural mindsets. For example, Lalwani and Shavitt’s (2013) study suggests that evaluating one attribute assimilates into the evaluation of other attributes when Indian participants judge product quality. Specifically, compared to United States., Indian participants are more inclined to infer product quality from price information because they perceive more interrelations between attributes of a product such as price and quality (Lalwani & Shavitt, 2013, study 2). In addition, considerable research suggests that East Asian individuals value the whole more than the summation of its parts. Mourey et al. (2013) found that, when some items in a complete set are unavailable, Latinos (collectivists) are more likely to give up their original chosen option than Anglos (individualists). The latter would rather break up the set and purchase individual items. In a similar vein, Western customers are willing to pay more if given a choice to design products by selecting preferred options from different attributes (e.g., color and size). In contrast, East Asian customers are willing to pay more if they are given a choice to design products by selecting preferred options from fully assembled models (e.g., a black and small product or a white and big product, de Bellis et al., 2019). This evidence suggests that assimilation and integration are salient for participants with a collectivist mindset, whereas separation and isolation are salient for participants with an individualist mindset.

Cognitive Processing Style and the Assimilation Effect

As discussed before, the end effect occurs due to the end’s easy accessibility in one’s memory. On the other hand, literature on the primary effect suggests that individuals allocate more attention to the first stimulus while less to latter ones. Thus, the first stimulus may be better encoded. Therefore, whether the end effect exists depends on the relative retrieval advantage of the final and the first stimuli (R. P. Bhargave & Montgomery, 2015).

Research has found that information processing styles impact information encoding and retrieval (R. P. Bhargave & Montgomery, 2015). The assimilation effect happens when contextual information unconsciously serves as a comparative standard in evaluative judgments (Bless & Schwarz, 2010; Schwarz & Bless, 2007). That is, the perception and evaluation of a product are convergent with its context. For instance, consumers evaluate a product higher in naturalness when the product is displayed on a wood table instead of a glass table (Zhu & Meyers-Levy, 2009). When tourists hold a holistic processing style, they assimilate initial episodes when encoding the latter ones. Thus, the initial experience receives enhanced encoding (R. Bhargave & Montgomery, 2013). As a result, holistic processing also increases the likelihood of recalling initial episodes in the retrieval. In research by D. C. Park et al. (1999), an investigation involving a recall task suggested that context information is more accessible to recall for holistic processors than analytical processors. Therefore, holistic processing increases the weight of the initial experience in overall evaluation. On the other hand, analytical processors encode the end experience without the assimilation effect because they tend to process information in isolation. Consequently, the end experience outweighs others due to its retrieval advantage in a person’s memory.

Consistent with our reasoning, one study revealed that the end experience is a good predictor of overall evaluation when experiences are viewed in isolation, while rejecting this effect when experiences are viewed as a whole (Strijbosch et al., 2021). R. Bhargave and Montgomery (2013) also found that, when evaluating a series of temporal sequences, individuals are more likely to integrate other episodes (e.g., the first episode) into the evaluation in a joint context (vs. a solo context), and this facilitates holistic processing (R. P. Bhargave & Montgomery, 2015; Ramanathan & McGill, 2007).

How Do Tourists’ Cultural Mindsets Influence the End Effect and the Assimilation Effect?

As discussed earlier, tourists’ cultural mindsets influence their cognitive processing style. Take tourists with a collectivist mindset as an example. Assuming that a negative experience occurs at the end, the earlier positive experiences are assimilated into the final experience. Thus, they may evaluate the final negative experience as “not that bad.” Similarly, when a negative experience occurs at the start, the earlier negative experiences are assimilated into the latter. Thus, tourists evaluate the later positive experiences as “not that good.” In this way, both initial experiences and final experiences are incorporated into the judgments of collectivist tourists. Thus, the advantage of the end is offset by the start.

On the other hand, tourists with an individualist mindset are less likely to assimilate the initial experience when encoding later episodes. Since the final stage is the most accessible memory in retrospective judgments, overall evaluation largely depends on the final episode of experience. Assuming that a negative experience occurs at the end, individualist tourists are less likely to incorporate the earlier positive experience into the final negative episode. Therefore, their evaluations of the final experience are likely worse than those with a collectivist mindset. Similarly, when a negative experience occurs at the start, the earlier negative experiences are unlikely to be assimilated into the latter. Thus, their evaluations of the final experience are better than those of collective cultural mindsets.

Following this line of reasoning, we propose that tourists’ cultural mindsets moderate the impact of negative experiences on their overall evaluation. Specifically, tourists with an individualist mindset will evaluate each episode in isolation and present no assimilation effect. They rely on the most salient episode for judgments. Considering that the final activity is the most recent in the memory, it is easy for tourists to recall. Therefore, the final activity is the most salient and takes more weight when tourists make a retrospective judgment. That is, the end effect is evident in their evaluation. By contrast, tourists with a collectivist mindset will perceive inherent connections between travel episodes and present the assimilation effect. They integrate all experience episodes into their whole judgments and the final activity takes less weight for collectivist tourists. Thus, their overall evaluations are more convergent no matter which location a negative experience occurs.

Taken together, we hypothesize the following:

H1: Cultural mindsets moderate the end effect in overall evaluation.

H1a: Tourists with an individualist mindset are more likely to evaluate the experience as worse when a negative experience occurs at the end (vs. at the start).

H1b: This effect is attenuated for tourists with a collectivist mindset.

Methodology

Experiments are often used to test causality between constructs, since highly controlled environments can effectively eliminate interfering variables and improve methodological quality (Levine & Parkinson, 1994). Three scenario-based experiments were conducted to examine the proposed hypotheses. The data of this research was collected after the outbreak of COVID-19 from January to October, 2022 and analyzed with SPSS 26. Study 1 and 2 used nationality (China vs. U.S.) as a proxy variable to test whether cultural mindsets moderate the influence of the timing of a bad experience on overall experience evaluation across two scenarios—that is, theme park and seaside vacation destinations, respectively. In study 2, we also examined the existence of assimilating effect, providing the empirical evidence for our reasoning. However, Chinese participants and U.S. participants differ in many aspects (e.g., social status) except cultural mindset. Therefore, study 3 employed a direct manipulation to replicate the moderation effect of cultural mindset. Through three studies, we found that participants with an individualistic mindset tend to make a worse retrospective evaluation when a negative experience occurs in the final stage of a journey rather than the first stage. The framework is illustrated in Figure 1.

Study 1: Cross-Cultural Difference in the End Effect

The goal of study 1 was to examine the end effect across cultures. Extant literature shows that Americans lean toward more individualism-oriented culture, whereas the Chinese are collectivism-oriented (Eid & Agag, 2020; Hofstede, 2001; Lin et al., 2022; Wei et al., 2023). Hofstede Insights (https://www.hofstede-insights.com/country-comparison/) is based on Hofstede 6-D models (Hofstede et al., 2010). According to the website, the individualism index on a scale from 0 to 100 of America and China is 91 and 20, respectively. Given that a country with a score under 50 can be considered as “collectivist” and above 50 considered as “individualist,” we took a person’s country of residence as a proxy variable of cultural mindset, comparing the end effect in U.S. and Chinese samples. In study 1, we designed a theme park tour scenario that combined positive and negative experiences. We expected that, if the end experience was disproportionately weighted in an individual cultural mindset, U.S. participants would incline to evaluate the overall experience as worse when a negative experience occurred at the end (vs. the start). However, the effect would be attenuated in a Chinese sample.

Procedure

Study 1 employed a 2 (temporal location: start vs. end) × 2 (cultural mindset: individualism vs. collectivism) between-subjects design. We recruited our U.S. sample from Prolific and Chinese sample from Credamo. Participants were randomly assigned to two conditions: the bad start or the bad end. All participants were instructed to read a scenario about a tour to a theme park. In the bad start condition, participants were asked to imagine that the attitude of the service staff at the entrance was very rude and indifferent, but they had a great time after that. In the bad end condition, participants were asked to imagine having a great time in the start period of a amusement park visit. However, the service staff at the exit treated them rudely and indifferently (see Supplemental Appendix A). After participants completed the scenario reading, they went through a manipulation check. We asked participants to rate which stage of experience was the worst on a seven-point scale(1 = start, 7 = end, a number close to 1/7 means a stage closing to start/end). After that, they were instructed to evaluate the overall tourism experience on a seven-point Likert scale (1 = negative,7 = positive). Participants’ attention was checked using one item: “This is an attention check. No matter what the questions is, please choose the last option.” Finally, we measured respondents’ familiarity with the type of tourist attractions in the survey and collected demographic information. We also added an open-ended question at the end so that participants to express their opinions if they had any confusion in the process.

Results

Data Cleaning

In summary, 181 U.S. participants and 185 Chinese participants registered in our study. We excluded two responses from the U.S. sample and one from the Chinese sample because they failed the attention check. We also excluded one U.S. response because it did not complete all the questions. A final sample of 362 responses (U.S. sample: N = 178, 48.3% male, mean age: M = 32.02 years, SD = 13.28; Chinese sample: N = 184, 44.0% male, mean age: M = 28.33 years, SD = 7.04) were used in analysis. Demographic information was presented in Table 1.

Table 1.

Demographic Information.

	Demographic information	American sample	Chinese sample
Study 1	Gender
	Male	N = 86 (48.3%)	N = 81 (44%)
	Female	N = 92 (51.7%)	N = 103 (56%)
	Age	M = 32.02	M = 28.33
	Education
	Junior school or below	N = 0	N = 2 (1.1%)
	High school	N = 73 (41.0%)	N = 13 (7.1%)
	Bachelor’s Degree	N = 81 (45.5%)	N = 131 (71.2%)
	Master’s Degree	N = 24 (13.5%)	N = 35 (19.0%)
	Doctor’s Degree	N = 0	N = 3 (1.6%)
Study 2	Gender
	Male	N = 87 (49.7%)	N = 106 (59.2%)
	Female	N = 88 (50.3%)	N = 73 (40.8%)
	Age	M = 30.70	M = 25.24
	Education
	Junior school or below	N = 0	N = 1 (0.6%)
	High school	N = 76 (43.4%)	N = 16 (8.9%)
	Bachelor’s Degree	N = 79 (45.1%)	N = 132 (73.7%)
	Master’s Degree	N = 18 (10.3%)	N = 17 (9.5%)
	Doctor’s Degree	N = 2 (1.1%)	N = 13 (7.3%)
Study 3	Gender
	Male		N = 118 (32.9%)
	Female		N = 241 (67.1%)
	Age		M = 28.47
	Education
	Junior school or below		N = 0
	High school		N = 54 (15.0%)
	Bachelor’s Degree		N = 248 (69.1%)
	Master’s Degree		N = 53 (14.8%)
	Doctor’s Degree		N = 4 (1.1%)

Manipulation Check

We checked for manipulation with an independent samples t-test to examine the positive/negative experiences. The results showed that participants in the bad start condition considered the initial experience worse, while those in the bad end condition considered the final experience significantly worse (M_start = 2.03, SD = 1.890, M_end = 6.50, SD = 1.104, t(360) = −27.546, p < .001). The result suggested that our manipulation was successful.

The Overall Experience

To investigate the moderation effect of participants’ cultural mindsets, we conducted an ANOVA with the overall experience as dependent variables and the country of participants’ residence as well as temporal location as independent variables. Consistent with our expectation, the result revealed a significant main effect of temporal location (F(1,358) = 12.91, p < .001) and a non-significant main effect of country of residence (F(1,358) = 1.63, p = .203). More importantly, the interaction effect was significant (F(1,358) = 10.91, p = .001), suggesting a significantly systematic difference between U.S. and Chinese participants in the end effect. Next, we further explored the proposed effect with control variables. Considering that there were significant differences in demographic information between two samples (an independent samples t-test on age: M_U.S. = 38.02, SD = 13.28, M_China = 28.33, SD = 7.04, t(360) = −3.32, p = .001; Chi-square analysis in education level: (χ² = 61.50, p < .001), we added age and education level into our analysis as control variables. Although there is no significant difference in gender between two samples (χ² = 0.67, p = .461), previous literature reveals a gender difference in processing style (Dube & Morgan, 1996). Therefore, we also controlled the gender effect. When controlling for gender, age, education level and familiarity to amusement parks, the interaction effect was still significant (F(1,358) = 11.42, p = .001).

To further compare the end effect in two samples, we conducted an independent samples t-test on the overall evaluation in each sample. As predicted, U.S. participants evaluated the overall experience as significantly worse when a rude service occurred in the final stage than in the initial stage (the means of the overall experience ratings for conditions: M_start = 5.85, SD = 1.01, M_end = 5.08, SD = 1.20, t(176) = 4.66, p < .001)). However, this pattern did not emerge in the Chinese sample. An independent samples t-test showed no significant difference in the overall evaluation in the Chinese sample, whether the negative experience occurred at the start or the end (M_start = 5.34, SD = 0.96, M_end = 5.30, SD = 1.09, t(182) = 0.22, p = .830).

Discussion

Studies 1 shows that the temporal location of negative experience leads to diverged overall evaluations, depending on the sample population. We found that U.S. tourists rated the experience significantly worse when encountering rude service staff at the end, but this was not the case for Chinese participants. Study 1 provided possible preliminary evidence for the moderation role of tourists from different cultural mindsets. Some scholar may question our assumption that there is a significant difference in individualism-collectivism between U.S. and Chinese in our samples, we conducted a post hoc test to address this issue. The individualism-collectivism was measured with Triandis and Gelfand’s (1998) scale. To keep the questionnaire short, we selected eight items with the highest loading factors from the horizontal dimension. This dimension focuses on the interdependence and independence, which is much closer to our definition of cultural mindset. We recruited 50 Chinese participants on Credamo and 50 U.S. participants on Prolific. They were instructed to rate each items on a seven-point Likert scale (1 = completely disagree, 7 = completely agree). One U.S. participant did not complete the questionnaire and was excluded from the data. A final sample of 49 U.S. participants (51% male, M_age = 30.55 years, SD = 4.23) and 50 Chinese participants (54% male, M_age = 27.60 years, SD = 1.70) was used in analysis. A paired samples t-test revealed that scores of individualism is significantly higher than collectivism in the U.S. sample (M_{individualism} = 5.65, SD = 0.82, M_collectivism = 4.15, SD = 0.84, t(48) = 8.56, p < .001), suggesting that individualist mindset dominates in the U.S. sample. The result was reversed in the Chinese sample (M_{individualism} = 4.50, SD = 1.21, M_collectivism = 5.63, SD = 1.15, t(49) = −3.90, p < .001).

Another issue involves an alternative explanation for our result. For example, sensitivity to interaction in service, instead of the temporal location of a bad experience, lead to divergent results in two samples. It is possible as a Chinese participant commented in an open-ended question, “I’d rather not to be exposed under the scorching sun for two hours than experience the attitude of the staff at the entrance.” This might indicate that Chinese tourists may pay less attention to personal interactions than the attractions themselves. In the next study, we will directly manipulate travel activities to further test the effect’s validity.

Study 2: Cross-Cultural Difference in Response to Different TRENDS

Study 2 intends to replicate study 1 and explore the end effect and the assimilation effect in a vacation scenario between respondents from different cultures. In studies 2, we tested whether there is a difference in the end effect in different temporal sequences. Specifically, we designed a vacation scenario where participants experienced activities in an improving trend or a declining trend. We expected that U.S. tourists would perceive a significantly worse evaluation when experiences were presented in a declining trend (vs. an improving trend) due to the easier accessibility of the end experience. However, we expected the effect to disappear for Chinese participants.

Pretest

The aim of the pretest was to create the tour activities used in study 2. Drawing on R. Bhargave and Montgomery (2013), we created vacation episodes displayed in a temporal sequence during a seaside tour. Specifically, we recruited 140 participants online to evaluate 16 hypothetical tour activities. For example, one activity described, “we came to the seaside in the morning and enjoyed a beautiful sunrise.” Participants were assigned to four conditions, and each condition was presented with four activities. After reading the short description of each activity, they were asked to rate the valence on an eleven-point scale (1 = extremely negative, 11 = extremely positive).

Results

Seven vacation episodes were chosen based on their affect intensity and variance (see Table 2, activities presented in a declining order). In the bad start condition, these episodes were presented in an improving trend from the most unfavorable to the most favorable. In the bad end condition, these episodes were presented in a declining trend from the most favorable to the least favorable.

Table 2.

Mean and Standard Deviation in Pretest in Study 2 Pretest.

Activities description	Affective intensity
Activities description	Mean	SD
Came to the seaside and saw a beautiful sunrise on the sea.	10.17	0.763
Bought some interesting tourist souvenirs in the local folk culture street.	8.778	1.506
Visited the Ship Museum and learned about the local ship culture.	7.667	1.481
Waited for a long time for lunch in a well-known restaurant.	5.148	4.645
Visited a small sand sculpture park which is not so attractive nor interesting.	6.704	3.023
Walked along the coastline with the sand blowing in the wind, so, unfortunately, you didn’t see the beautiful beach and walked with great difficulty.	3.333	1.926
Took a boat out to sea with local fishermen. You got seasick and vomited on the way. It was really painful.	2.467	1.382

Main Study

Study 2 followed a 2 (trend: improving vs. declining) × 2 (cultural mindset: individualism vs. collectivism) between-subjects design. Similar to study 1, a participant’ country of residence serve as a proxy for cultural mindset. We recruited our U.S. sample from Prolific and Chinese sample from Credamo.

We instructed the subjects to read a short description and imagine that they had finished a tour to the beach, including seven activities. They were then assigned to one of two tour conditions randomly. We manipulated the negative experience’s temporal location by changing the sequence of activities. Participants in the declining condition viewed seven activities in a declining trend, and participants in the improving condition viewed seven activities in an improving trend. When participants viewed activities one by one, they were asked to rate their experience as we did in the pretest. After participants viewed all the activities, they were asked to rate their overall experience and satisfaction with the tour on a seven-point Likert scale. We also added two attention check questions to screen effective responses. At last, participants completed a familiarity measure and demographic information.

Results

Data Cleaning

We received 190 responses from Prolific and 195 responses from Credamo.

In total, 15 U.S. participants and 15 Chinese participants failed the attention check, and 1 Chinese participants did not report demographic information. These responses were excluded from the final sample. In sum, 354 responses (U.S. sample: 175 responses, 49.7% male, mean age: M = 30.70, SD = 11.31; Chinese sample: 179 responses, 59.2% male, mean age: M = 25.24, SD = 5.85) were used in analysis.

Overall Evaluation

Similar as study 1, we conducted an ANOVA with the overall evaluation as a dependent variable and the country of residence and trend as independent variables. The result showed a main effect of country (F(1,350) = 85.24, p < .001), and a main effect of trend (F(1,350) = 4.33, p = 038). More importantly, the interaction effect is marginally significant interaction effect (F (1, 350) = 3.64, p = .057), indicating a systematic difference in sensitivity to negative experience temporal locations between the two samples. When we controlled for demographic information (e.g., age, gender and education level), and familiarity with seaside attractions, the interaction were still significant (F (1, 346) = 4.80, p = .029). Further, We conducted an independent samples t-test in each sample to examine whether there was a difference in the overall experience rating between the improving condition and the declining condition. As predicted, the result showed a significant difference in the overall evaluation of travel experience in the U.S. sample (M_improving = 4.46, SD = 1.07, M_declining = 3.96, SD = 1.35, t(173) = 2.71, p = .007). Specifically, the U.S. participants showed a significantly lower evaluation on travel experience when negative experiences occurred during the final activities. On the other hand, an independent samples t-test showed no significant difference in the overall evaluation in the Chinese sample (M_improving = 5.38, SD = 1.17, M_declining = 5.36, SD = 1.11, t(177) = 0.13, p = .898). In summary, we only found significant difference in overall travel evaluation between the two trends in the U.S. sample but not in the Chinese sample.

The Assimilation Effect

We adopted two methods—an ANOVA on the fourth activity and Spearman correlation analysis to further examine the existence of assimilation effect.

Firstly, we conducted an ANOVA with the fourth activity as a dependent variable. According to our theory, U.S. participants adopted analytical processing and judged each activity in isolation, Therefore, there would be no assimilation effect between activities. Following this line of reasoning, we expected that there would be no significant difference of the evaluation of the fourth activity between the two trend conditions, no matter that they experience these activities in an improving trend or in a declining trend. On the contrary, Chinese participants adopted a holistic processing and judged each activity under the assimilation of previous experiences. Specifically, because participants in a declining trend had better experiences earlier, they would tend to assimilate the positive impression with the fourth activity, leading to a higher evaluation, and vice versa. Therefore, we predicted that participants imagining activities in the declining trend would evaluate the fourth activity more positively than those in the improving trend.

As predicted, the result showed a main effect of trend and a main effect of cultural mindset. Importantly, the result showed a significant interaction effect (F (1,350) = 9.55, p = .002). The result still held when controlling demographic information and familiarity (F (1,346) = 10.08, p = .002).

To examine our expectations, we conducted an independent samples t-test on the fourth activity for the U.S. sample. As predicted, the result showed that there was no significant difference between the ratings of the fourth episode between the improving trend and the declining trend (M_improving = 5.36, SD = 1.70, M_declining = 5.36, SD = 2.36, t(173) = 0.01, p = .993), suggesting that U.S. participants were not affected by previous experience when evaluating the fourth activity. For Chinese participants, the result showed that there was a significant difference between the improving trend and the declining trend (t (177) = −4.20, p < .001). The evaluation of the fourth activity in the declining trend was higher than in the improving trend (M_improving = 6.38, SD = 2.36, M_declining = 7.81, SD = 2.17), suggesting that Chinese participants were affected by previous experience when evaluating the fourth activity.

Correlation Analysis

We also conducted a Spearman correlation analysis to examine the weight of the start and the end episode in evaluating the overall experience in two samples. We expected that there would be no assimilation among U.S. participants, and the end experience carries more weight when evaluating the whole tour. Therefore, the correlations of later experiences and overall evaluation should be stronger and more significant than that of earlier ones. However, this pattern should not emerge in Chinese sample because Chinese participants focus on the whole journey instead of specific episodes due to the assimilation effect. For the U.S. sample, the results of correlation analysis showed that the last four activity evaluations were significantly correlated with the overall experience but the first three were not. More importantly, correlation coefficients with the later four activities were higher than the earlier activities and also higher than those in Chinese sample (see Table 3), supporting our assumptions. These results supported our hypotheses and indicated that the end experiences are weighted more in the U.S. participants. For the Chinese sample, despite the temporal location, all the activities were significantly correlated with the overall evaluation. This is consistent with our assumption. Even though the latter activities are most accessible in memory when Chinese participants just finish the trip, earlier activities indirectly affect the holistic experience by assimilating to the later ones, thus improving their weight in forming the overall evaluation.

Table 3.

Correlation Analysis in Two Samples.

	The overall evaluation
Temporal location of each activity	American	Chinese
The first activity	r = −.055	r = .287***
The second activity	r = .011	r = .441***
The third activity	r = .183*	r = .409***
The fourth activity	r = .296***	r = .446***
The fifth activity	r = .518***	r = .493***
The sixth activity	r = .372***	r = .414***
The seventh activity	r = .318***	r = .285***

p < .05. ***p < .001.

To further confirm the correlation difference between the earlier experiences and the later ones, we averaged ratings of the first three activities into the indicator of the first half experience of the trip. In a similar way, we also averaged ratings of the later three activities into the indicator of the later half experience of the trip. We ran the same correlation analysis as before. As predicted, in the U.S. sample, the experience of the first half of trip was not significantly correlated with the overall evaluation but the latter half was (first half: r(175) = 0.02, p = .755; latter half: r(175) = 0.42, p < .001). However, both the experience of the first half and the latter half of the trip were significantly correlated with the overall evaluation in Chinese sample (first half: r(179) = 0.40, p < .001; latter half: r(179) = 0.40, p < .001), suggesting that compared to the U.S. participants, Chinese participants placed a higher weight of initial experience in the overall experience judgment.

Discussion

Consistent with our predictions, we found that tourists from different cultural backgrounds processed the end experience differently when forming overall evaluations. As we expected, U.S. tourists showed worse overall evaluation than Chinese tourists when activities were presented from the most to the least favorable. Studies 2 also revealed that the experience in the final stage was heavily weighted when the U.S. participants evaluated the whole experience in a vacation context. However, for Chinese participants, the impact of the final experience was attenuated. Despite the results of studies 2, which provided evidence to support our hypotheses, other alternative explanations exist, such as socioeconomic status, preferences for different types of activities, or distinct cognitive styles unrelated to cultural mindsets. To increase the generalizability of the results and eliminate alternative explanations, in the next study we will directly prime the subjects’ cultural mindsets to further test the effect’s validity.

Study 3: Priming Cultural Mindset Preceding Rural Attractions

Study 3 was designed to examine the moderation of primed cultural mindsets with direct manipulation. We expected that, if a cultural mindset drives the moderation effect, priming cultural mindsets will lead to divergent results, even within the same culture. Previous research has found that, although individuals hold a dominant cultural mindset nurtured by their society, the opposite mindset can be temporally activated by manipulation (Kwon et al., 2015; Oyserman & Lee, 2008). Therefore, in study 3, we adopted a well-established method to manipulate participants’ mindsets.

Pretest

We conducted a pretest to assess whether viewing a group of photo-based posters could manipulate the cultural mindset successfully. According to Oyserman and Lee (2008), group imagination is an effective way to prime a cultural mindset. In the pretest, we employed a one-factor between-subject design. Specifically, we designed two groups of three posters that expressed either a collectivist or individualist mindset (see Supplemental Appendix B). More specifically, one poster invited participants to imagine enjoying a dinner with their family and asked them to describe why it is important to love your family. The counterpart invited participants to imagine enjoying a cake alone and the importance of loving oneself. One hundred and twenty participants viewed one of the alternative groups of posters and then responded 16 items adapted from Singelis et al. (1995) on a seven-point Likert scale (1 = not at all, 7 = very much).

Results

We averaged eight items, measuring individualist mindset, into one composite measurement, and we averaged other items measuring collectivist mindset into another (Singelis et al., 1995). We conducted a paired samples t-test to examine whether our manipulation is successful. As we expected, participants who viewed the posters that were intended to prompt an individualist (vs. collectivist) mindset showed higher ratings on the individulism items than on the collectivism items (M_{individualism} = 5.68, M_collectivism = 5.31, t(59) = 2.816, p = .007). By contrast, participants who viewed the posters that were intended to prompt a collectivist (vs. individualist) cultural mindset showed higher ratings on the individualism items than on the collectivism items (M_{individualism} = 4.68, M_collectivism = 5.86, t(59) = 7.518, p < .001). The pretest results suggest that our manipulation of cultural mindsets was successful.

Main Study

We employed a 2 (cultural mindset: individualist vs. collectivist) × 2 (temporal location of negative experience: the start vs. the end) between-subjects design. Participants were assigned randomly to one of the four conditions. To manipulate the temporal location of experiences, we presented a hypothetical 3-day rural tour scenario and asked participants to imagine that they had just finished this tour. The tour scenario featured one unappealing tourist attraction and two nice ones. For participants in the bad start condition, we presented the lousy attraction on the first day and two nice ones on the next 2 days. For participants in the bad end condition, we presented two nice attractions first and the unappealing one on the final day (see Supplemental Appendix C). When participants finished their reading, they were asked to evaluate their overall experience of the tour. Finally, we measured participants’ familiarity to rural attractions and collected demographic information.

Results

Data Cleaning

A total of 371 participants from the Chinese mainland took part in the online study. Nine participants failed the attention check, and two responses were deleted because they took more than 28 to 31 min to complete the questionnaire, way beyond the 10 min other responses registered. One participant was excluded because he or she did not complete the demographic information. A total of 359 responses (32.9% male, mean age M = 28.47 years, SD = 7.95) were used in final analysis. Among them, 49.3% of participants (N = 177) viewed three individualist posters, and 50.7% (N = 182) viewed three collectivist posters.

Overall Experience

We conducted an ANOVA analysis with the overall experience as a dependent variable, the temporal location and cultural mindsets as independent variables. The result showed a marginally significant main effect of temporal location (F(1, 355) = 11.06, p = .001) and a non-significant main effect of cultural mindsets (F(1, 355) = 0.06, p = .814). As expected, the analysis also revealed a marginally significant interaction between temporal location and cultural mindsets (F (1, 355) = 3.42, p = .065), indicating a systematic difference in sensitivity to negative experience temporal locations between the individualist condition and the collectivist condition. When we controlled for gender, age, education level and familiarity to rural attractions, the interaction was still significant (F (1, 351) = 4.92, p = .027). Next, we conducted an independent samples t-test to compare the end effect between individualist participants and collectivists participants. The result showed that participants with individualist mindsets exhibited a significant lower evaluation when a bad experience occurred in the end than in the start (M_start = 5.53, SD = 0.78, M_end = 5.07, SD = 1.00, t(175) = 3.42, p = .001), while tourists with a collectivist mindset treatment exhibited non-significant difference when they evaluated two travel experiences (M_start = 5.38, SD = 0.74, M_end = 5.25, SD = 0.84, t(180) = 1.12, p = .263, see Figure 2). These results confirmed our previous findings.

Discussion

In study 3, we directly manipulated cultural mindsets by instructing participants to view different sets of posters and by manipulating the temporal location through swapping the initial and final attractions. The results support our contention that tourists with an individualist mindset show more negative responses when a negative experience occurs at the end of a journey. At the same time, this effect is attenuated for tourists with a more collectivist mindset. We observed that this end effect occurs when using posters to manipulate tourists’ cultural mindsets. Even within the same culture, priming different mindsets will lead to differences in sensitivity to the temporal locations of negative experience. This result validates the driving influence of cultural mindsets on the end effect.

General Discussion

In this research, we focused mainly on the moderation of cultural mindsets on the end effect in the tourism setting and attempted to address inconsistent findings in the extant literature. We conducted three experiments with cross-cultural samples to test the hypotheses. Consistent with our expectations, we found that tourists with an individualist mindset respond more negatively to bad service at the end of a tour experience than at the start. However, the effect is not significant for tourists with a collectivist mindset (study 1). The end effect also holds true in a vacation setting when the experiences are presented in an improving or declining order. Especially, we also examined the assimilation effect by comparing the evaluation of the fourth activity in the two samples, which explains the mechanism of how cultural mindset moderates the end effect (study 2). In study 3, we demonstrated that individualist cultural mindsets moderate overall evaluation, even when the participants are primed by visual and textual stimuli in a single culture (Chinese participants). Across three studies, we found that the effect is robust irrespective of whether we manipulated the temporal location by presenting experiences in an improving (vs. declining) sequence or by just swapping the start experience and the end experience, whether the negative experience is caused by rude service staff, disappointing travel activities, or unappealing tourist attractions, and whether we primed cultural mindsets in one culture or directly obtained samples from the respective cultures. The moderation of cultural mindsets occurs both across cultures and within a culture once a specific cultural mindset is activated.

This research can explain inconsistencies in prior literature. A survey conducted by Chark et al. (2022) shows that the peak-end pattern does not emerge in their sample, which consists of 20% of international visitors and 80% Chinese visitors. By contrast, Strijbosch et al. (2021) demonstrated the peak-end effect for European visitors who watched a musical show. Their research provides further evidence for the effect observed in our study. We tested the impact of momentary experience on the global experience in the tourism context and revealed the causality by comparing the impact of the start and the end experience directly.

Notably, our results suggest that the end experience dominates the whole evaluation for individualist tourists, and the relative weight of the start increased for collectivist tourists. However, our research does not mean that the impact of the start and the end makes no difference to collectivist tourists in all cases, but that the importance of the start experience in their overall evaluation is elevated. For example, prior studies demonstrated that the primacy effect occurs in the short sequence, and the recency effect occurs in the long sequence (Mantonakis et al., 2009). In a short tour (e.g., a half-day tour), the first impression may be more important for tourists from a collectivist cultural mindset. In this case, the encoding advantage for a start may outweigh the accessibility advantage for the end, and tourists will follow a primacy effect. For example, Yuya et al. (2017) found that Japanese visitors show a first impression effect after a 5-hr short tour. By contrast, in a long tour that lasts several weeks, the end effect may be more pronounced, even for collectivist tourists, because the memory of initial experience gradually fades as time passes.

Theoretical Contribution

This research offers several theoretical contributions. First, it clarifies the moderating role of cultural mindsets on the end effect in consumer experience and contributes to inter-cultural consumer behavior literature. Past research provides extensive insight into the relationship between moment-to-moment experiences and overall evaluation in consumer experiences; however, inconsistent results exists. Based on the literature on marketing and psychology, this research first introduces tourists’ cultural mindsets to explain this inconsistency.

Secondly, this study validates certain mechanism on how cultural mindsets moderate the overall evaluation. Previous research has examined the role of temporal location (the start vs. the end) without considering the assimilation effect among different locations. This research first examines how experiences in different locations influence each other through an assimilation mechanism when a consumer with a collective mindset holistically evaluate the overall experience not based on episodic experience in isolation but rather based on its relationships with previous episodes.

Finally, this study also contributes to the literature on culture mindset research. Cultural mindsets are one of the basic features of an individual’s traits, and they are continuously nurtured by one’s society. Previous research has demonstrated that one’s cultural mindset influences an individual’s information processing, attitude forming, and decision making (Oyserman, 2011; Oyserman et al., 2009; Oyserman, 2016). This research introduces the construct into tourism research and reveals the cultural difference in tourists’ experience evaluation.

In general, this study not only introduces the concept of cultural mindsets in tourism research, but also contributes to consumer behavior literature by clarifying the impact of cultural mindsets on the end effects, resolving past research inconsistencies.

Practical Implication

Our research identified the moderation effect of tourists’ cultural mindsets, which can benefit tourism marketing in two ways. First, as a cultural construct, cultural mindsets are an influential factor for international tourism when tourists with different cultural mindsets travel to a destination. Previous research has shown that tourists from East Asian cultures tend to be collectivistic, whereas tourists from Western cultures tend to be individualistic (Briley et al., 2014; Hofstede, 2001). Although service providers intend to deliver positive experiences, it is almost impossible to avoid negative experiences, especially in a complex and multifaceted and multi-stage tourism experience. Therefore, service providers can focus limited resources on some key moments in the journey, based on different cultural mindsets.

For example, to cater to tourists with an individual mindset, it is more important to situate the peak experience toward the end of the tour, instead of the beginning. This strategy may not work well for tourists with a collective mindset. Scheduling tour activities based on tourists’ cognitive types may also help alleviate crowding and congestion since the tourists can be distributed more evenly across different attractions.

Second, marketing communications can activate cultural mindsets temporally, such as by using posters, slogans, and advertisements. When a negative experience has already occurred, service providers can strengthen or weaken the tourists’ collectivist mindset by artificially changing their social connections and thus decrease the impact of the negative experience. For example, including more social activities to stimulate a collective mindset will likely to lessen the negative experience toward the end of the tour activity, thus, improving the overall evaluation. Considering that COVID-19 has had a huge impact on people’s lives, including work (Blahopoulou et al., 2022) and leisure (Mowatt, 2021), tourists have had to reduce social gatherings and maintain social distance, which decreases social connection and possibly facilitates an individualist mindset. Therefore, destination marketers need to strive for optimizing the end experience in order to improve overall experience evaluation.

Limitations and Future Research

This research has limitations that indicate a need for future research. First, although some extant research provides preliminary evidence to support the findings of our experimental study, field research is still needed to examine the external validity of the effect. Future studies can be done by using field methods or actual behavior to test the moderation of cultural mindsets in the real tourism context. Second, the present research only compares the importance of the start and the end in the respective overall experience without considering experiences in the middle of the journey. Future research could be extended to other temporal moments during the entire journey. For example, how do tourists respond to a tour including a wonderful start and a satisfying end but a disappointing middle moment? Third, other potential moderators are not incorporated in our frameworks, such as gender, social class, and social context. Previous research has revealed that gender difference (Dube & Morgan, 1996) and social class (J. Lee, 2018) influence one’s processing styles. Moreover, as Study 3 suggested, thinking of others may prime the collectivist mindset because the presence of others facilitates social connection. Therefore, whether tourists participate in a tour group or travel alone could also make a difference. These potential limitations also provide avenues for future research.

Supplemental Material

sj-docx-1-jtr-10.1177_00472875231190000 – Supplemental material for Cultural Mindsets Matter: Reexamining the End Effect in Tourism Experiences

Supplemental material, sj-docx-1-jtr-10.1177_00472875231190000 for Cultural Mindsets Matter: Reexamining the End Effect in Tourism Experiences by Yu Yu, Bing Pan, RanRan Cui, Jianping Liang and Jifei Wu in Journal of Travel Research

Footnotes

Acknowledgements

We thank Hongyan Yu for his constructive comments on our experimental design. We also thank Hongchao Zhang, Qinying Gao and Manqiong Shen for their many useful discussions on our ideas. We would also like to thank the anonymous reviewers for their useful suggestions, which have greatly improved our manuscript.

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: National Natural Science Foundation of China, Number 71672201. The second author acknowledges the Institute of Computational and Data Sciences (ICDS) of Penn State University for a seed grant to support this project.

ORCID iD

Yu Yu

Data Accessibility Statement

The data that support the findings of this study are available from the corresponding authors, upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Yu Yu is an Assistant Professor at School of Marxism, Sun Yat-Sen University. Her research interest includes destination marketing, tourist experience and tourist deviant behavior.

Bing Pan is a Professor in Commercial Recreation and Tourism, Department of Park, Recreation, and Tourism Management, College of Health and Human Development, Penn State University. His research interest includes big data and data analytics in tourism and parks, e-commerce, destination marketing, and well-being and tourism.

RanRan Cui is a master student at School of Business, Sun Yat-Sen University. Her research focuses on destination marketing.

Jianping Liang is an Associate Professor at School of Business, Sun Yat-Sen University. His research area includes cognitive psychology in marketing and tourist behavior.

Jifei Wu is an Assistant Professor at the School of Marxism, Sun Yat-sen University. His research interest includes tourist behavior and digital marketing.

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