Master’s Thesis, Marketing Management

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Master’s Thesis, Marketing Management

“The role of surprise labeling in instigating a non-conscious threat

response”

Student Name: Alexander van Zyl Student Number: S3163083

Email: a.b.van.zyl@student.rug.nl

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Abstract

Many promotional activities rely on unexpectedness (e.g. Surprise Labels, Unexpected Discounts, Surprise Boxes). Notwithstanding the reliance of several companies on such marketing practices, much research has focused primarily on the relationship between surprise and consumer reaction during the choice stage of the consumption experience. With the intention of extending this understanding, this research aims at analysing effects of anticipated surprise on actual consumption behaviour, and potentially altering this relationship with attribution. The results of the study demonstrate the prevalence of a non-conscious threat response that occurs as a result of anticipated surprise. Additionally, the study explores the mitigating effect of surprise attribution to a benign product feature. Ultimately, theoretical and managerial implications of surprise labelling is discussed.

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Introduction

As part of its marketing campaign in 2016, Kia, a renowned automotive company, introduced into practice its “Power to Surprise” tagline (Kia, 2020). As of 2010, a company known as FabFitFun introduced into the market a monthly subscription box that provides consumers with surprise products. Although these marketing campaigns might vary in practice, process, and execution, they rely on the same basic premise of eliciting the anticipation of surprise through surprise labels in their marketing efforts. Whether your uncertain feeling stems from a disequilibrium (Piaget, 1937/1954), or dissonance (Festinger, 1957) or uncertainty itself (Van den Bos, 2001), both these companies, and many alike, rely on our key cognitive function to establish meaning by relying on expected mental representations. Violations of meaning & expectancy in the form of unexpected relations has become habitual behaviour of marketing agents. Common practices include utilizing promotional activities in the form of surprise appeals as its basis for attracting or generating customer interest. This use of surprise appeals, which derives its functionality from unexpectedness, is found across all marketing practices. Ranging from product advertisements (Pieters, Wedel, and Batra 2010), product names (Miller and Kahn 2005), ad photos (Peracchio and Meyers-Levy 1994), and logos (Henderson and Cote 1998). There exists a plethora of research both indicating favourable (Wadhwa, Kim & Wang, 2019) and unfavourable (Proulx & Inzlicht, 2012) results of using risk-based choice in promotional activity. However, given these marketing practices, an indication that surprise marketing is seemingly beneficial in one form or another endures.

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surprise can increase consumer choice (Wadhwa, Kim & Wang, 2019), and improve consumer response in expectation of retrieving the optimal outcome (Goldsmith & Amir, 2010). Yet, while the choice stage in consumer behaviour has been studied extensively (Wadhwa, Kim & Wang, 2019), it is less clear how surprise labels influence actual consumption behaviour. Few studies have addressed the notion of understanding actual consumption behaviour influenced by the anticipation of meaning-discrepant stimuli. Thus, building on this research gap, it will be argued that surprise labels may initially generate interest due to innate optimism but will ultimately negatively influence consumption behaviour due to a non-conscious threat response. Furthermore, the current research will elaborate on the relationship between surprise-labelling and non-conscious threat response by attempting to mitigate the effects through attribution. What the aforementioned companies, either deliberately or unintentionally fail to do is provide a source of surprise, creating a sense of ambiguity. It is this state of uncertainty that this study will seek to investigate.

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that rather than being neutral (Reisenzein & Meyer, 2009), or positively valanced (Valenzeula et al., 2010), label surprise is experienced as unpleasant (Elliot & Devine, 1994).

Prior to empirical examination, a thorough literature review is conducted. This is followed by an explanation of the study overview and research methodology. Subsequently, the results of the empirical examination are presented and discussed. Finally, an overall conclusion, discussion and limitations of the study is given as a basis for future research.

Theoretical Framework

Meaning and expectancies

What is meaning?

Meaning, for millennia, has been seen as implicit conceptualizations of a given reference (Lewis, 1975), the significance of a life event (Kray, George, Lijenquist et al., 2010), or made up through a pragmatic consensus (Nietzsche, 1887/1994). Regardless of the unbounded definition of meaning, a more recent psychological understanding of the concept as a relationship (Baumeister, 1991) is best allocated for this study. Meaning is thus an expected

relationship, which in turn grants us with the belief of control over our environment - a sense

of familiarity (Camus, 1942/2004). In the absence of a surprise label, individuals have a mental conceptualization, drawn from experience, as to what the expected relation will be. However, a surprise label suggests a violation of this expected relation by challenging the individual’s anticipation of the world. The surprise label relies on the tendency of individuals to first have a positive meaning of uncertainty, also known as innate or automatic optimism (Goldsmith & Amir, 2010). This is also the notion that drives the premise of increased choice due to increased product unexpectedness (Wadhwa et. al. 2019). However, once innate optimism fades, consumers are left with a surprise label that signals a prospective violation of meaning.

Meaning and Expectancy Violations

When a contradiction occurs within our expected relations, this is known as a meaning

violation (Proulx & Inzlicht, 2012), and thus puts the individual in a state of unfamiliarity.

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the consumers (Heine et al. 2006). Due to the fact that a surprise label reduces the control that people have over the expectations of their outcomes, anticipation of an unexpected reward as such will lead to a proposed violation of expectancy (Wadhwa et. al. 2019). However, regardless of the experience, a violation of expected relations i.e. meaning, evokes aversive arousal, which subsequently motivates compensation efforts to relieve this arousal (Proulx & Inzlicht, 2012). Therefore, it is proposed that a surprise label will signal a prospective violation of an individual’s expected relations and evoke a state of aversive arousal. As established by Heine et al. (2010), an expectancy violation allows for unconsciously experienced arousal to signal the detection of an anomaly (Proulx & Heine, 2008; Kay, Moscovitch, & Laurin, 2010). This unconsciously experienced arousal we will refer to as a non-conscious threat response.

Non-conscious Threat Response

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In the study of Lowe et al. (2018) a non-conscious threat response is elicited through ambient noise which is not consciously recognised, which ultimately leads to altered consumer behaviour. Following in this notion, a surprise label, a trivial suggested meaning violation, activates a syndrome of aversive arousal in response to expectancy violations in the absence of any conscious, subjective awareness of the arousal (Winkielman & Berridge, 2004). This is why people, who initially are confronted with a surprise label, experience innate optimism, but subsequently alter their behaviour through meaning maintenance efforts in the absence of any conscious understanding. Through provoking an implicit inconsistency i.e., the surprise logo, it provokes explicit non-conscious consumption changes. A surprise logo, or a discrepancy as such, ultimately announces a lack of meaning/meaning violation, and thus results in a non-conscious threat response by consumers. In summary, even though consumers initially perceive a surprise label positively, their implicit response may still be negative. It must be clarified that for the interest of this paper, we examine how the conscious awareness of the surprise label results in non-conscious behaviour. Put formally;

Hypothesis 1: Surprise labels, compared to regular labels, trigger a non-conscious threat response which manifests in the form of anxiety.

State-Based Anxiety

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threats activate the amygdala, which consequently results in a heightened emotional anxiety (Blanchard, Griebel & Pobe et al., 2011).

Research has shown that such an emotional state of anxiety can be processed below cognitive consciousness. As we are looking at the effect of conscious awareness of the surprise label through a non-conscious threat response, it is important to understand that Robinsons (1998) found that emotional states of fear and anxiety - but not other emotions - can be stimulated by unconscious cognitive processing. This state-based response is curated through an automatic physiological response to nonsensical experiences that manifests as arousal-induced anxiety (Proulx & Heine, 2008; Proulx & Inzlicht, 2012). Following the Meaning Maintenance Model (MMM), it is proposed that the arousal-induced anxiety that stems from an anticipated violation of expectancy commences a non-conscious need to regain meaning (Proulx & Heine, 2008). It is further established in literature that individuals who have a high trait-based anxiety personality experience more frequent and intense state-based anxiety emotions when confronted with a threat (Spielberger & Reheiser, 2009). Thus, it leads us to believe that a possible interaction between trait-based anxiety and consumption can take place, namely that individuals with a higher trait-based anxiety would experience the highest non-conscious threat response; and subsequent need for meaning maintenance.

Meaning Maintenance

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in a process aiming at eliminating the expectancy violations; a meaning maintenance process. The meaning maintenance efforts stem from a state of aversive arousal (Proulx & Inzlicht, 2012), which will be initiated by the expectancy of a meaning violation via the surprise label.

A surprise label, which violates expected relations, will evoke a common syndrome of aversive arousal, which in turn, motivates efforts to counter it. However, it is in the absence of conscious awareness of a meaning threat that individuals will engage in meaning maintenance efforts. Thus, alternatively to fluid compensation efforts, when exposed to a surprise label suggestive of a meaning violation, individuals will engage in a non-conscious strategy aimed at reducing the state of aversive arousal that stems from the anticipation of surprise (Major & Townsend, 2012). Individuals will refrain from reaffirming alternative schema, but rather engage in meaning maintenance of the current schema. Strengthening this line of reasoning, research states that arousal induced anxiety predicts a specific need to affirm meaning (McGregor et al., 2012). Collectively, these findings point to the intriguing possibility that attributing the surprise to a benign product feature would assist in the non-conscious process of meaning maintenance.

After a schema-incongruent experience, individuals tend to try and establish mental representations of the expected relations (Heine et. al. 2006). A perceived anticipated discrepancy in their mental representations set on by a surprise label provokes the strongest efforts to reconstruct meaningful associations. When a prospective meaning violation occurs through the presence of a surprise logo, consumers engage in this meaning seeking endeavour (Hagtvedt, 2011). By engaging in the discrepancy elimination behaviour consumers tend to commence in the analysis, the evaluation (causal search and attribution), and if required the updating of the relevant schema. Thus, it is plausible that through attribution of the surprise label, the meaning threat can be mitigated as discussed in the following section.

Attribution and Misattribution of Surprise

Attribution of Surprise

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imposed by the surprise aspect. The attribution would connect one aspect to another in expected ways, in effect generating meaning (Heine et. al. 2006). Based on the previous findings of Taylor et. al. (2019) the attribution of the surprise label would aid in the affective response of the individual by resolving the product within an existing frame of reference. Due to the fact that aversive arousal activates all meaning maintenance behaviours (Proulx, Inzlicht, & Harmon-Jones, 2012), an intervention in this process through surprise label attribution is made possible.

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Misattribution of Surprise

The premise of including an attribution moderator derives from the misattribution of

arousal theory (Cotton, 1981). The theory states that when there is an opportunity to allow

individuals to attribute their arousal to something other than its original source, subsequent compensation efforts are eliminated (Zanna & Cooper, 1974). By attributing the surprise to a benign product feature, rather than the surprise label itself, it provides individuals with the opportunity to misattribute their arousal to an obsolete attribute. This follows in the reasoning of Lowe et al. (2018) where consumers' anxious state was attenuated when information was provided about the non-conscious threat and attributed to a benign source. Thus, for the interest of this study, we propose that the relationship between surprise labelling, anxiety and non-conscious threat response can be attenuated when information is provided through explicitly attributing the surprise to a benign product feature. This will ultimately remove any threat associated with the surprise label, allowing the consumer to misattribute their aversive arousal to a benign product feature. In terms of meaning maintenance, attribution acts as an alternative meaning framework which seeks to diminish, rather than resolve meaning violations (Proulx & Inzlicht, 2012). This palliative behaviour of meaning maintenance is why it is believed that attribution can work as it does not look at addressing the root cause of the aversive arousal, but rather acting as a conduit to avoid it. This misattribution of arousal as a means of diminishing meaning maintenance behaviour and subsequently compensatory efforts is in line with certain stems of literature (Zanna and Cooper 1974; Proulx & Heine 2008). The attribution of the surprise label to a benign product feature will allow the individual to become consciously aware of their anxious state and ultimately diminish it using the benign feature as misattributed reasoning. Ultimately, by experiencing a conscious anticipation of schema violation through a surprise label, we are able to mitigate the non-conscious response through benign attribution of the surprise label, dampening its effects (Heine & Proulx, 2013).

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Study Overview

To preface, the purpose of this study is to investigate whether the attribution of a surprise label would alter the interaction between surprise labelling and a non-conscious threat response. In other words, whether attributing non-conscious anxiety to a benign product feature would eliminate extensive meaning maintenance efforts. Specifically, we predict that attributing the surprise to a benign product feature, such as the angle at which the picture is taken, would reduce the effect between surprise labelling and non-conscious threat response. When the surprise label is present, participants would engage in the shortest viewing time, conversely, when there is no surprise label, consumers would engage in the longest viewing time. If the aforementioned theoretical framework holds, attribution would mitigate the effect between surprise label and average viewing time of the participants. Additionally, in order to establish the moderating role of attribution, the study will foremost seek to establish the relationship between surprise and non-conscious threat response.

Conceptual Model

The relationship between Surprise and Non-Conscious threat response, moderated by Attribution

Surprise label vs Regular Label

Non-Conscious threat response Attribution (No source

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Method

Participants and Design

The survey was conducted and distributed entirely online due to current health restrictions. This meant that respondent demographics ranged drastically. There was a total of 364 survey participants who took part in exchange for a lottery chance. All incomplete answers were filtered out on the bases of >97% progress. This was done on the analysis that the 2 participants who had 98% and 97% progress only failed to answer trivial questions, all test-relevant questions were answered. Based on only eliminating incomplete surveys the sample pool accumulated to (N=231; 65% females; 𝑀_!"# = 25.34).

Further data reduction included filtering out participants based on an attention check, individuals who have participated in a similar previous study, mobile users and those with technical issues. To ensure scale validity an attention check was also included (Berinsky, Margolis, & Sances, 2014; Curran, 2016; Huang, Liu, et al., 2015). The n=58 participants who failed the attention check were excluded from analysis to eliminate careless respondents (Maniaci & Rogge, 2014; Schmitt & Stults, 1985). Furthermore, n=38 of participants were excluded from the analysis based on the notion that they have participated in similar previous studies. The progress (progress>97%) elimination also inadvertently eliminated all mobile completions. Due to all technical issues being related to the word identification task (WIT) measure, these participants were only eliminated when analysing WIT dependent measure.

Ultimately the participant pool accumulated to (N=142; 69% females; 𝑀_!"#=25.44; appendix 1a). Participants were randomly assigned to one of three conditions in a 1 factor 3

conditions (regular label, surprise label no attribution & surprise label attribution) between-subjects factorial design. The target consumption experience chosen was viewing pictures of beach destinations.

Independent measure

The independent measure was coded as follows. (0=surprise no attribution; 1=surprise

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Procedures and Dependent Measures

Participants were first told that the study they were participating in consisted of a slide show and a word identification task. Participants then were asked to respond to a subset of the State-Trait Personality Inventory (STPI; Spielberger & Reheiser, 2009; see also Noseworthy et al., 2014). The State-Trait Anxiety Inventory (STAI) is a commonly used measure of trait and state anxiety (Spielberger, Gorsuch, Lushene, 1970). The subset consisted of a 20-item state anxiety scale with measures such as “I am tense; I am worried” and “I feel calm” on a 5-item Likert scale ranging from “1=very slightly or not at all” to “5=extremely” in efforts to measure participant’s current state of anxiety. This measure was recorded to isolate the effects of state-based anxiety. For the purpose of brevity, we conducted a scale reliability analysis. For state-anxiety measures, items were reverse coded where necessary (e.g. “I feel interested” for state anxiety scale). The reliability analysis showed a Cronbach’s 𝛼= 0.81(𝛼 > 0.7). Furthermore, Cronbach’s alpha if item is removed was analysed. This showed that if the variable “I feel alert” is removed, the Cronbach’s alpha would increase to 𝛼= 0.845. A subsequent factor analysis indicated that a 2-component factor design explains 50% variance, and thus could explain the weak correlations of some items, indicating that 2 underlying constructs might be measured. This would also explain why some inter-item correlations were negative.

Subsequently, implicit-anxiety was manipulated or controlled by assigning individuals either to the surprise-label slide show or the regular-label slide show (see data collection

procedure 1 a & b). The use of the surprise label as a schema-incongruity follows in line with

previous studies that defines it as discrepant or inconsistent with the currently activated general schema (Smedslund, 1990; Meyer et al., 1991; Ekman, 2003). Participants in the surprise-label attribution condition are explicitly told that “The surprising feature in this slide show is that

the perspective from which the picture is taken is always different”. This follows in line with

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Dependent Measures

Implicit Anxiety Measures

Both the dependent measures of subliminal activation of anxiety are conducted on an implicit basis through a Word Identification Task and a photo slideshow. Consequently, the implicit measure will allow for the circumvention of the introspective limits of participants; the ability to report on the intended content domain (Egloff, Schwerdtfeger & Schmukle, 2005). Thus, when participants partook in the survey, the implicit measures ensured that they are unaware of the way in which conclusions are drawn from the anxiety indicators and which construct is actually being measured (Egloff, Schwerdtfeger & Schmukle, 2005).

Activation of implicit anxiety as a result of perceived surprise was evaluated by means of a word identification task with subliminal priming (i.e. participants were unaware of the word which they were presented with during the priming phase of the task). The word identification task was utilized to eliminate chances of response factors such as self-presentation, demand characteristics and willingness of participants to report on themselves (Egloff, Schwerdtfeger & Schmukle, 2005). A word identification task also allows for capturing the intended information that is processed outside of subjective awareness (Epstein, 1994; Greenwald et al., 2002; McClelland, Koestner, & Weinberger, 1989). Once participants had the chance to view the first 2 photos of their conditioned slide show, they were instructed that the rest of the slide show would load while they conducted a word identification task. Prior to starting the word identification task, and to ensure that participants do not try and guess for a “right” answer, they were instructed that “you should rely on your gut feeling when

subsequently identifying the word you feel you have seen.” Participants were then shown a

“non-word” that flashed below their conscious threshold. Once the word flashed across the screen participants were then asked to identify from a list of 4 words (1 anxiety related word

and 3 emotional-neutral words) which they saw. Although, implicit memory performance for

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Hedonic Consumption Measure

The second dependent measure of implicit anxiety is a slide show experience. The slide show experience was included to be in line with the cover story. Similarly, a measure of actual consumption had to be included, as based on our theorizing, the implicit anxiety response - induced by a surprise label - should only be evident during an ongoing consumption experience and not prior to it. The participants, upon completion of the word identification task, were presented with the slide show experience (see data collection information 2). All photos shown were identical across all three conditions. For each photo presented, participants had the choice to “continue browsing album” or “stop browsing album”. In total, there were 24 photos that could be viewed for an indefinite time period if chosen so by the participant. The dependent variable is calculated as the average viewing time of the slide show per participant. Based on this dependent measure, we checked for outliers. This was done visually through identifying star-outliers in the box-and-whiskers plot (Appendix 2a). Based on these 3 cases (ID=43,

ID=76, ID=225) were detected. In order to determine whether the outliers would influence

results, a standardized Z score was used. The cut-off point of Z=3.67 was used in order to remove outliers above 95% of all values. Only ID=76 (Z=5.01) and ID=225 (Z=4.21) exceeded the cut-off point, and thus were excluded from analysis. Comparing the 5% trim mean and the sample mean reaffirmed the notion that including ID=43 in subsequent analysis would not alter results. Therefore, sample pool accumulated to N=140; 69% female; Mage=25.21when outliers were excluded.

To further extend the basis of this research, participants were asked at the end of the survey to fill in a subset of the State-Trait Personality Inventory (STPI; Spielberger & Reheiser, 2009; see also Noseworthy et al., 2014). However, this subset consisted of a 10-item trait anxiety scale with measures such as “I am a steady person”; I feel like a failure” and “I feel secure” on a 4-item Likert scale ranging from “1=Almost Never to “4=Almost Always” in efforts to measure participant general trait-based anxiety. This is because individuals who have a high trait-based anxiety experience more frequent and intense state-based anxiety emotions when confronted with a threat (Spielberger & Reheiser, 2009). Therefore, including it as a potential moderator further extends the premise of the current research. Once again, for brevity, a scale reliability analysis was conducted after appropriate variables were reverse coded. This resulted in a Cronbach’s alpha score of =0.891. Furthermore, all inter-item correlations were positive indicating that all items measure in the correct direction. All correlations are r>0.3,

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p<0.001); “I feel steady” and “I wish I was as happy as others” (r=0.231, p<0.001) and “I am

confident” and “I am steady” (r=0.255, P<0.001). Due to weak correlations on 2 items, we also checked for the corrected item-total correlation value of the variable “I feel steady”. Although it had the weakest corrected item-total correlation value (r=0.539), it did not improve the Cronbach’s alpha score if removed.

Results

Hedonic Consumption (Slide show) as dependent variable

To preface, the assumption of homogeneity of variance was not met (p=0.024), and thus subsequent analysis is based on establishing directional trends. An ANOVA analysis was conducted using Surprise Label as the independent variable, Average Viewing Time as the dependent variable and attribution as the moderator. The ANOVA indicated that the combined between group variation was insignificant F(2,137)=1.52, p=0.223. This indicates that there is no significant difference between average viewing time and the condition group (0=surprise

no attribution; 1=surprise attribution, 2=Regular label) (Appendix 3a).

To understand the means of the respective conditions, a planned contrast analysis and Post-Hoc tests were conducted. The contrast statistics used were based on “Does not assume equal variance” as the assumption of homogeneity of variance was not met (Appendix 3b). For the first contrast analysis of comparing surprise label to regular label the value of contrast indicates that the direction of average viewing time for the surprise group was in the right negative direction compared to the regular label, although insignificant ( t(137)=-.267, p=0.760). The second contrast illustrates that surprise attribution has a longer average viewing time and approaches statistical significance ( t(137)=1.79, p=0.114). To look at the effect size, Cohen's D was also calculated comparing the group “Surprise Label no Attribution” to “Surprise Label Attribution”. A value of 0.326, although insignificant, might indicate that the effect size is still present between “Surprise Attribution” and “Surprise No Attribution” albeit

small (0.2<effect size small<0.5). Therefore, it leads us to assume that if a more viable sample

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difference (µdif=-0.397, p=0.202) compared to both “Surprise Attribution” and “Regular

Label”. The surprising aspect is the comparison between “Regular Label” and “Surprise Label Attribution”, in which the regular label condition had a lower average viewing time than the

surprise label with attribution (µdif=--0.255, p=0.527). Furthermore, when looking at the

average view time of the homogeneous subsets “Surprise No Attribution” has the lowest view

time (N=48, AVT=1.171) and “Surprise Attribution” has the highest view time (N=48,

AVT=1.567) (Appendix 3d).

Discussion

The results of the study utilizing Average Viewing time as the hedonic consumption variable illustrates the negative trend between surprise label and non-conscious threat response is present. Although insignificant, the results lean towards the notion that a surprise label reduces a person's average viewing time. Furthermore, attributing the surprise to the angle at which the picture was taken increased the average viewing time above that of the control group of the regular label.

Number of Anxiety Consistent words as dependent Variable

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Discussion

The results, once again, although insignificant point to a directional effect in favour of prior theoretical support. Individuals in the “Surprise No Attribution” condition demonstrated a larger number of anxiety related words (N=5, Average Anxiety Words=4.600), compared to “Surprise Attribution” (N=5, Average Anxiety words=3.00) and “Regular Label” (N=6,

Average Anxiety Related Words=4.500). This could work towards the argument of how

surprise leads to an implicit activation of anxiety which manifests as a non-conscious threat response. Following in line with the previous results, the “Surprise Attribution” condition showed fewer anxiety related words compared to the “Regular Label” condition. This could indicate that in fact attribution may have a more significant effect towards dampening a non-conscious threat response than previously thought. The level of insignificance can likely be attributed to the large number of individuals who were able to see that it was “non-words” due to poor internet connection.

Trait-Anxiety Interaction with Hedonic Consumption

In order to elaborate on the previous research on the interaction effect between state-trait anxiety (Spielberger & Reheiser, 2009), we conducted a moderated multiple regression analysis using Hayes’ process macro using 10,000 bootstrapping samples (Appendix 5). This analysis was conducted with the N=140; 69% female; Mage=25.21sample. Over all, the model was insignificant (F(3,136)=1.049, p=0.373, R2_{=0.016). Furthermore, there was no direct} effect of “Surprise Label” (b=0.077, t(136)=0.746, p=0.457) nor “Average Trait Anxiety” (b=-0.23, t(136)=-0.150, p=0.881) on non-conscious threat response. Additionally, there was no significant interaction effect (b=0.254, t(136)=1.357, p=0.177) . In addition, there are no statistically significant transition points within the observed range of the moderator found using the Johnson-Neyman test. However, looking at the conditional effects, a trend can be seen that the higher a person's trait anxiety score, the stronger the effect. Furthermore, at +1 SD (i.e.

0.611) on the centered average trait anxiety variable the relationship between surprise label and

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General Discussion

In line with previous literature, the findings of this study suggest a positive relation between surprise labels and a non-conscious threat response. Although insignificant, both dependent measures of number of anxiety words chosen and average viewing time operated in the predicted direction. Participants in the surprise condition spent on average less time on the slide show and chose more anxiety related words. This proposes that consumers who are consciously aware of a surprise label will expect a schema-incongruity that will result in a non-conscious threat response manifesting in the form of anxiety. Furthermore, the findings of the attribution moderation, although insignificant, proposes that attribution may improve consumption beyond that of the controlled no surprise condition. This could indicate that by averting the non-conscious threat response through attribution, the innate optimism (Goldsmith & Amir, 2010) experienced in the choice stage can be carried through to the consumption stage. Thus, all findings, although not approaching statistical significance, is in line with past literature indicating that attributing the surprise to a benign product feature will bring the source of threat to conscious awareness and therefore dissipate arousal-based anxiety and subsequent needs for compensatory behaviour. This study, however, fails to elude towards a significant interaction effect between trait-anxiety and hedonic consumption. However, the analysis of the trait anxiety interaction is suggestive of a relationship between trait anxiety and hedonic consumption at higher levels of trait anxiety.

This study contributes to current research in several ways. First and foremost, it is an extension to the research that focuses on non-conscious priming effects of marketing cues that individuals encounter daily (Fitzsimons et al., 2008; Breitmeyer, Ogmen, and Chen 2004). The results of the study stand as a basis in determining the directional effect of surprise labels on a non-conscious threat response. Although results remain statistically insignificant, evidence from the study suggests that using surprise labelling may cause a stronger non-conscious threat response. Ultimately, this research stands as a basis in clarifying the valence of surprise as an emotion, adding to the opposing stream of literature that inconsistencies, disruption and lack of understanding are experienced as unpleasant (Elliot & Devine, 1994), rather than neutral or pleasant.

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2010; Landwehr, Wentzel, and Hermann, 2013; Noseworthy et al. 2011; Noseworthy and Trudel, 2011; Roggeveen, Goodstein, and Grewal, 2014). We focus on the notion that surprise acts as a schema incongruent event that may elicit a non-conscious threat response. This contributes to the literature on the effects of emotion, specifically anxiety, on hedonic consumption behaviour. What differentiates the current research is that it acknowledges the non-conscious nature of anxiety effects, as both the activation and meaning maintenance efforts are implicit. Compared to past research that used unambiguous threat manipulations, this study elaborates on the emotional and behavioural changes as a result of surprise labelling.

Alternatively, in exploring the moderating effect of attribution, the study leans towards predicting a moderating effect of attributing the surprise label to a benign product feature in hopes of dampening the negative effects. This follows in line with previous research, indicating that a surprise label, whether attributed or not, will automatically elicit a non-conscious threat response, unless the source of the surprise is explicitly stated (Lowe et al., 2019). Therefore, this study moves in favour of the notion that when the possibility of a threat is removed, surprise labelling no longer influences an individual, supporting evidence that the perception of threat is a main instigator of the response (Lowe et al., 2019). In terms of meaning maintenance, however, the theory suggests that attribution acts as an alternative meaning framework, which seeks to diminish, rather than resolve meaning violations (Proulx & Inzlicht, 2012). Our findings, or lack of significance may point towards an understanding that attribution to a benign product feature may not suffice as an alternative meaning framework.

What is of further interest, is the fact that in both analyses of using the WIT and the slide show experience, attributing the surprise to a benign product feature dampened the effects above and beyond that of the control group; albeit statistically insignificant. This finding can build on the premise of innate optimism (Wadhwa et al., 2019), in which we propose that eliminating the possible threat through attribution can carry the innate optimism through to the consumption stage and improve the response above that of a regular label.

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Weaknesses

This research, however, is not exempt from weaknesses. The primary weakness of this study is the lack of a significant sample size. There are several reasons why the sample size is underpowered. The primary reason for such a small sample size is the large number of participants (n=57) who failed the attention check. A viable explanation for the large number of failures for this may be that the attention check was included towards the end of the survey. Past research has stated that including the attention check early on in the survey may be more beneficial (Kwok & Brown, 2017). In order to fortify this assumption, a G*power analysis was conducted to determine what the sample size would have needed to be (based on the effect size) to find significant results. With comparing the 3 label groups, 561 participants would be needed in a test with p=0.05 to achieve a statistical power of 0.95 (F(2,561)=3,0119, p=0.05). This lends explanation as to why our sample (N=140) would provide results that are insignificant.

Furthermore, due to the current health and movement restrictions as a result of Covid-19, all data collection was conducted online. This meant that online data sources used were shared amongst several participants with similar surveys. Ultimately a large portion of individuals who participated in similar previous studies also partook in this study, weakening its predictive power. The current situation also may have an indirect or direct effect on a study that analyses non-conscious behaviour, as such unprecedented times may influence implicit emotion without any explicit realization.

Future Research

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Another avenue of exploration can be intentionality of the source of discomfort. Following in the line of research (Ach 1935; Atkinson 1964; Greenberg and Frisch 1972) illustrating that knowledge of the source’s intentionality can inform observes about the degree of the source’s motivation, defining the intentionality, or lack thereof, of the surprise label may alter findings.

Additionally, building on the idea of Meyers-Levy and Tybout (1989), future research can also look into how incongruity may elicit varying results between dogmatic and pragmatic individuals. As Shaffer and Hendrick (1974) states “The open mind is regulated by a need to know and understand, whereas the closed mind is oriented to defend against anxiety and threat.”

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Data Collection Information

1. Label conditions

a. Surprise label condition

- Note: If Surprise Attribution Condition Participants read the following script: “The

surprising feature in this slide show is that the perspective from which the picture is taken is always different”

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Appendix Appendix 1

1a. Descriptive Statistics of Sample Pool

Descreptive Statistics Sample

N Range Minimum Maximum Mean

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Appendix 2

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Appendix 3

3a. One-way ANOVA comparing Mean variation amongst label means using Average Viewing Time as Dependent Measure

3b. Planned-Contrast analysis using Average View Time as Dependent Measure

Contrast Coefficient

0=surprise no attribution 1= surprise attribution 2=regular label

contrast .00 1.00 2.00

1 -1 -1 2

2 -1 1 0

Contrast Test using Average View time as Dependent Measure

Contrast Value of Contrast Std. Error

t df Sig. (2-tailed) Average View Time Assume equal

variance 1 -.1138 .41186 -.276 137 .783

2 .3968 .23090 1.719 137 .088

Does not assume equal variance

1 -.1138 .37116 -.307 105.667 .760

2 .3968 .24853 1.597 84.206 .114

N=142

ANOVA using Average View time as Dependent Measure

Dependent variable Average Viewing Time Sum of squars df Mean Square

F Sig. Between groups (combined) 3.877 2 1.939 1.515 .223

Linear term Unweighted .460 1 .460 .359 .550

Weighted .526 1 .526 .411 .523

Deviation 3.351 1 3.351 2.619 .108

Quadratic Term Unweighted 3.351 1 3.351 2.619 .108

Weighted 3.351 1 3.351 2.619 .108

Within Groups 175.293 137 1.280

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3c. Post-Hoc Multiple Comparisons using Average View Time as Dependent Measure

N=142

Multiple Comparisons using Average View Time as Dependent Measure Dependent Variable: Avg_View

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3d. Table showing Average View time for Homogeneous Subsets

Average View Time

0=Surprise No attribution, 1=Surprise Attribution, 2= Regular Label

Subset for alpha=0.05

Tukey HSD 0.00 1.171

2.00 1.312

1.00 1.567

Means for groups in homogenous subsets are displaed a. Uses Harmonic Mean Sample Size = 46.588

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Appendix 4

4a. Descriptive Statistics excluding all participants who had technical difficulties with the WIT

Descriptive Statistics Excluding Technical difficulties

N Minimum Maximum Mean Std. Deviation

Gender (1=male) 135 1 2 1.70 .462

Age 135 18.00 64.00 253.037 820.654

Valid N (listwise) 135

4b. ANOVA Using Number of Anxiety Words Chosen as Dependent Measure

ANOVA using Number of Anxiety Words Chosen as Dependent Variable

Dependent variable

Number of trait anxiety words Sum of Squares df Mean Square F Sig. Between Groups (Combined) 8.238 2 4.119 1.543 .250

Linear Term Unweighted .027 1 .027 .010 .921

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4c. Contrast Analysis using Number of Anxiety Words Chosen as the dependent measure

Contrast Coefficient

0=surprise no attribution 1= surprise attribution 2=regular label

contrast .00 1.00 2.00

1 -1 -1 2

2 -1 1 0

Contrast Test using Number of Anxiety Words Chosen as Dependent Measure

Contrast Value of

Contrast Std. Error t df Sig. (2-tailed) Number of Anxiety words chosen Assume equal variance 1 1.400 1.687 .830 13 .422 2 -1.600 1.034 -1.548 13 .146

Does not assume equal variance

1 1.400 1.739 .805 9.220 .441

2 -1.600 .979 -1.633 6.661 .149

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4d. Post-Hoc Analysis Using Number of Anxiety Words Chosen as the Dependent Measure

Multiple Comparisons using Number of Anxiety Words Chosen as Dependent Measure

Dependent Variable: Number of Anxiety Words

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Appendix 5

5a. Moderated Multiple Regression Analysis

Model Summary

R R-sq MSE F(HC4) df1 df2 p

.125 .016 1.297 1.049 3.000 136.000 .373

Model

Coeff se(HC4) t p LLCI ULCI

constant 1.358 .098 13.848 .000 1.164 1.552

Label_IV _.077 .103 .746 .457 -.127 .280

Average Trait Anxiety -.023 .151 -.150 .881 -.322 .277

Interaction .254 .187 1.357 .177 -.116 .624

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02-07-2020 1 1 | 28-06-2020| 1 28-06-2020

Master Thesis Defense

The role of surprise labelling in instigating a non-conscious threat response

Name: Alexander van Zyl Student Number: S3163083 Supervisor: Anika Schumacher Co-Supervisor: Jean-Pierre Thomassen Date: 02-07-2020 1 2 | 28-06-2020

Introduction

• Rely on the same basic premise of utilizing the anticipation of surprise through surprise labels in their marketing efforts.

• Companies rely on our key cognitive function to establish meaning by relying on expected mental representations.

• The emotion surprise entails a complex of immediate responses;

• Cognitive interruption, attention allocation, systematic processing of the surprising stimulus

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Master’s Thesis, Marketing Management