CROSS-MODAL CORRESPONDENCES BETWEEN
HAPTIC IMAGERY AND PERCEIVED TASTE:
DOES SOFT TASTE SWEET?
MASTER THESIS
by
MIHAELA DUIA
CROSS-MODAL CORRESPONDENCES BETWEEN HAPTIC IMAGERY
AND PERCEIVED TASTE: DOES SOFT TASTE SWEET?
MASTER THESIS
University of Groningen
Faculty of Economics and Business
MSc Marketing Management
by
MIHAELA DUIA
Jupiterstraat 17
9742 ES Groningen
+31 (0)641149901
m.duia@student.rug.nl
student number s3134776
1
stSupervisor: Dr. Yannick Joye
2
ndSupervisor: Dr. Jan Willem Bolderdijk
Preface
The basis for this research originally stemmed from my interest for sensory marketing and how it engages the consumers' senses and affects their perception, judgment and behaviour. I would like to look at this thesis as “the beginning of the end” of my Master at University of Groningen. It has been an exciting journey, with ups and downs, that has taught me that only with hard work, passion and patience everything will succeed.
I would like to thank my supervisor, Dr. Yannick Joye, for his excellent guidance, valuable input and support during this thesis process. I also wish to thank all the respondents who participated in my study, without whose cooperation I would not have been able to conduct this analysis.
Abstract
The present research is a first step in examining cross-modal correspondences between haptic imagery and perceived taste, an area that holds promise for future research in sensory marketing and consumer behaviour. This study examined how priming participants with soft and hard haptic imagery can influence their taste perception (sweet, sour, salty, bitter dimensions) and liking of a fast-moving consumer good. We also addressed the individual differences in the need for touch of participants and their food involvement, factors which did not moderate the main relationship. The main results from the experiment showed that haptic imagery had an effect on neither taste perception, nor product liking. However, the exploratory analysis revealed that respondents who imagined the product being soft indicated a higher perceived sweet taste. A hedonic mechanism to explain the cross-modal matching was reviewed. Further research needs to address how the sense of touch can be incorporated into marketing messages and focus on the relative contribution of haptic imagery to online shopping in the context of food perception.
Table of Contents
Preface... 3
Introduction ... 7
Literature review ... 9
Cross-modal correspondences ... 9
Cross-modal associations affecting taste... 10
The interaction of taste and touch ... 11
Haptic imagery ... 11
The interaction of haptic imagery and perceived taste ... 12
Moderators ... 14
Need for touch index. ... 14
Food involvement ... 15
Methodology ... 16
Participants and design ... 16
Materials ... 17
Haptic imagery. ... 17
Perceived taste ... 18
Product liking ... 18
Product familiarity ... 19
Need for touch ... 19
Involvement ... 19
Procedure ... 20
Results ... 21
Haptic imagery manipulations ... 21
Haptic imagery and perceived taste ... 21
Product familiarity and liking ... 22
Moderation analysis ... 23
Need for touch. ... 23
Involvement ... 24
Exploratory analysis ... 26
Product familiarity and liking ... 26
Introduction
Every day, consumers are surrounded by plentiful visual cues and stimuli that challenge their sensory perception. The five senses are a vital way in which consumers communicate and engage with the world around them. Companies are also trying to capture consumers’ five senses in their marketing communications. Take the example of KFC’s “Finger lickin’ good” slogan and the Coca Cola “Taste the Feeling” campaign. These slogans are using one sense (touch) to emphasize another (taste). In marketing, this falls under the sensory marketing field of study, where consumers’ senses are engaged to influence their perception, judgement, and behaviour (Elder & Krishna, 2010; Krishna, 2012; Spence, 2012). Sensory marketing is a growing field and despite the need for research, a lot of work on sensory perception within marketing has only focused on the study of vision, with the other senses getting limited attention. The reason for this is self-explanatory: the sight, our visual attention, accounts for 80 percent of human perception (Jansson-Boyd, 2010).
However, senses such as touch or taste challenge marketer’s creative minds. This is beautifully displayed in Cadbury’s chocolate campaigns “Tastes like it feels” and “Have you felt silk lately?” (see Figure 1). These featured ads are using imagery that combines two senses (touch and taste) as a metaphor to evoke the unique taste sensations that their chocolate bars promise. The campaigns were successful in bringing the feeling of their chocolate bars to life and consumers got to feel the product before tasting it. Also, the silk reference displayed on their packaging highlights and builds on the creamy and smooth experience of this chocolate bar. Does the wonderful feeling of touching silk that you experience from seeing the ad image makes you perceive the taste of the chocolate differently? In the current thesis, we challenge this idea and seek to find evidence for the conditions under which haptic imagery (mental visualization of soft and hard stimuli) influences the perceived taste of products before purchasing.
As seen in the campaign above, touch is not always available for consumers. For instance, when consumers shop online, they are unable to touch the products prior to purchase. Given the rapid spread of online web shops and consumer’s reliance on online buying, the absence of a haptic sensory input can make consumers experience greater buying uncertainty. When one is deprived of the actual tactile element, haptic imagery can fill in this gap. Haptic imagery is known as the ability to form a mental image of the properties of an object/product (examined by touch) such as the weight, texture, hardness, temperature, shape, or volume of the product (Hollins, 1986; Lederman & Klatzky, 1987). At this instance, this field has not received so much attention, with only a few studies evaluating the role of imagery in haptic processing (Elder & Krishna, 2010; Slobodenyuk, Jraissati, Kanso, Ghanem, & Elhajj, 2015). To our knowledge, no research has yet examined the impact of haptic imagery on taste perception for fast moving consumer goods (non-durable goods that sell quickly such as processed and dry foods, beverages, cosmetics etc.). Thus, this paper contributes to the research by taking into consideration the recent online developments and the incapability to touch products before purchasing, and how by only imagining touching, a product’s taste can be enhanced and/or influenced.
Furthermore, is it possible that haptic imagery that generates certain types of tactile interaction (soft versus hard) changes the way in which taste of a product is perceived? When one’s receives sensory information from one sense (e.g. touch) by stimulating another sense, this may indeed affect the consumer’s response (e.g. perceived taste). Taste perception is multi-sensory and is comprised of more than just chemical sense of gustation. Thus, it can be influenced by matches in modalities which are not necessarily related to taste, such as haptic stimuli.
In consumer behaviour literature these matches between attributes of stimuli in different sensory modalities are documented as cross-modal correspondences (Spence, 2011). The importance of sensory stimuli of this kind is becoming more and more significant to marketing scholars; with recent literature emphasizing the need for more research on this topic (Krishna & Morrin, 2008; Slobodenyuk et al., 2015). According to Peck and Childers (2003), from all the 81 sensory studies in consumer behaviour focusing on the five senses, only 28 have been published within the last years.
to use haptic pictures to define the tactile features of a product, to enhance the taste of a product or to emphasize on unique characteristics (low fat, low sugar products).
In order to address the literature gap and managerial contributions, we would like to explore the following research questions: To what extent can haptic imagery influence taste perception? What haptic interactions lead to different taste perceptions?
Literature review
We begin our literature review with an overview of the constructs used in the conceptual model and discuss the cross-modal correspondence literature addressing the relationship between senses, namely touch (haptic) and taste.
Cross-modal correspondences
Our visual perception does not operate in a vacuum and academic scholars have discovered various compatibilities between attributes and levels of sensory stimuli, which they refer to as cross-modal correspondences (Hagtvedt & Brasel, 2016). Cross-modal correspondences can be generally defined in terms of non-arbitrary associations across perceptual modalities (Slobodenyuk et al., 2015). Spence (2011) observed how people match high-pitched sounds with small, bright objects that are located high up in space. In the study of Ramachandran and Hubbard (2001, 2003), the majority (95%) of participants matched the nonsense word “Bouba” with the shape B and “Kiki” with shape A (Figure 2). In this way, respondents matched the sharp sound of the word “Kiki” with the edgy shape. These two studies investigated non-arbitrary associations between auditory and visual dimensions, namely speech sounds and the visual shape of an object.
Figure 2. Picture of Kiki and Bouba shapes (Ramachandran & Hubbard 2001, 2003)
2004), and smell and haptics (Krishna, Elder, & Caldara, 2010). Therefore, it appears that cross-modal correspondences are likely to exist between all possible pairings of senses.
A key assumption used across this type of research is that such cross-modal correspondences are shared by a large number of people and some of them might be even universal (Spence, 2011). The underlying mechanism behind this sensory analogy received different explanations. Some researchers agree that these stimuli dimensions are correlated in nature and people form a mental link between, for example, size and pitch. On the other side, it is not yet clear if these effects are automatic or not. Recent research has claimed that this question remains unresolved and that previous studies showed that both automaticity and later decisional processes can be found in cross-modal interactions (Evans & Treisman, 2010; Klapetek, Ngo, & Spence ,2012; Marks, 1987; Spence, 2011).
Cross-modal associations affecting taste
Taste is multidimensional, and the chemical sense of taste involves the detection of five basic taste categories of sweet, sour, bitter, salty and umami or savoury (Chaudhari & Roper, 2010). When thinking of perception of taste, one immediately thinks of the sensations produced on the tongue. However, it was shown that we have significant difficulty in differentiating one taste from another with only relying on our taste buds (Spence, 2015). In other words, the way we perceive taste can be the result of many other stimuli interactions. Taste perception and evaluation are multi-sensory, it involves other senses and can be easily influenced by changes in modalities unrelated to taste (e.g. temperature, sound, colour, and texture).
Figure 3.Picture of angular and round shapes (Velasco et al., 2016)
As seen in the studies above, taste is not made out only of taste buds, it relies on many other intrinsic or extrinsic factors. If you imagine a handful of popcorn, the simple visual appearance of the food (intrinsic cue) generates expectations and perceptions of taste. Also, seeing an ad about this product (extrinsic cue) can elicit positive sensory thoughts and affect the perceived taste (Dubose, Cardello, & Maller, 1980) (Hoegg & Alba, 2007).
The interaction of taste and touch
Equally important for taste perception is the sense of touch and how this can act as an intrinsic cue. The way a product feels can affect how we perceive taste. Previous research has shown that the evaluation of taste components can also be influenced by the tactile quality of the food (Slocombe, Carmichael, & Simner, 2016). In this case, actual touch affected the characteristics of food. In the study of Piqueras-Fiszman and Spence (2012), the texture of packaging was found to influence the perceived taste of consumed food. Furthermore, haptic stimuli could further enhance consumer perceptions. Research found that the haptic quality of the container, for example, a cup or bottle, can alter the taste perception of water; when placed in a firm versus flimsy container, the taste becomes superior (Krishna & Morrin, 2008). Most of the above studies looked into the actual touch and taste, where participants had the chance to physically touch and taste the product. The findings showed that the packaging texture (rough or smooth), product design and the visual shape of a product can all affect taste (Piqueras-Fiszman & Spence, 2012; McDaniel & Baker, 1977; Slocombe, Carmichael, & Simmer, 2016). However, the aim of this research is to investigate whether the effect appears on taste perceptions when using haptic imagery and not actual touch.
Haptic imagery
defined as forming mental representations of touch information (Hollins, 1986; Kaski, 2002). While little is known about haptic imagery, there is some indication that visual imagery includes haptic elements (Campos, López, & Pérez, 1998; Zhang, Weisser, Stilla, Prather, & Sathian, 2004). In the absence of the product, consumers form positive mental images. When stimuli undergo an imagery building process, this results in the consumer imagining the affective experiences associated with the product (Compeau, Grewal, & Monroe, 1998). For instance, imagining the taste of a hedonic product (ice cream) turned out to be a more affective experience than actually eating the product (Compeau, Grewal, & Monroe, 1998). Imagining is defined as a cognitive process in which sensory information is represented in working memory (MacInnis & Price, 1987). When there is no actual physical touch, a consumer can imagine the sense of touch (how it feels) by only looking at an image. The process of imagining may operate as a mental recreation of experience involving multiple senses. For example, senses such as sight, taste, smell and tactile sensations might be involved (Bone & Ellen, 1992).
Moreover, when consumers attempt to evaluate haptic product information, their visual perception works in conjunction with the haptic imagery (Rinaldo, 2008). For one thing, products can include tactile stimuli, which can exert the same ownership power as perceived ownership through either mere touch or with imagery encouraging touch. When touch becomes unavailable, haptic imagery may result in an increase of one’s perceived ownership of an object (Peck & Shu, 2009). It should be clear that images are able to contain tactile factors, and these can have the same power of ownership as haptic imagery (Campos, López, & Pérez, 1998; Zhang et al., 2004). The tactile stimuli can be included and assessed through haptic imagery and include features such as softness, hardness, or weight. While some attributes can be more vivid than others, the study of Peck, Barger and Webb (2013) suggested that “softness” may be easier to imagine than for example, weight.
The interaction of haptic imagery and perceived taste
between taste and sound, shape and serving plate shape (Biggs, Juravle, & Spence, 2016; Crisinel & Spence, 2009; Slobodenyuk et al., 2015).
Table 1
Cross-modal correspondences between various stimuli based on hedonic association theory
Sweet Sour Bitter Salty
Sound High pitched High pitched Low pitched -
Shape Round Angular - -
Serving Plate shape Round shaped - - -
Tastes which are known to be pleasant (sweet) map to “pleasant” sounds, such as smooth vowel sounds, while a high-pitched sound is associated with unpleasant tastes (bitterness) (Simner, Cuskley, & Kirby, 2010). Another study looked into how pleasant odours (lemon) led people to rate fabrics as softer than when they were exposed to unpleasant odours (scent of animals) (Dematte, Sanabria, & Spence, 2006). In this way, the hedonic properties of a stimulus can seemingly explain the way in which people form these associations. By finding the common hedonic property- pleasantness- the haptic stimuli can be associated with a certain perceived taste. A way to test cross-modal correspondence by using hedonic associations can be to prime participants with a hedonic valence (either pleasant or unpleasant). There is evidence showing that sweet is hedonically pleasant and that sour and bitter are indeed considered to be hedonically negative (Pandey et al., 2010; Glendinning, 1994; Lindemann, 2001).
Furthermore, the association with stimuli that have positive or negative valence is likely to activate a positive feeling. In evaluative conditioning, a neutral stimulus is presented with stimuli which are positively or negatively evaluated. The positive effect created by the positive stimuli transfers to the other stimuli through evaluative conditioning. The liking of the first stimuli will benefit the neutral stimuli resulting in greater liking (Barone, Miniard, & Romeo, 2000; Dedonder, Corneille, Bertichamps, & Yzerbyt, 2014). This theory is backed up by the Hedonic fluency model which shows that if the ease of processing is experienced as pleasant, this positive affect will be used as information in the evaluation of the stimulus (Fennis & Stroebe, 2016).
with the hard stimulus. Would the fact that people react more positively to soft stimuli and more negatively to hard stimuli explain their differences in perceived taste? Based on the supporting literature presented in this chapter, the following hypotheses were introduced in accordance with the conceptual model:
H1: Haptic imagery can influence the perceived taste of a product.
H1a: Participants who will experience haptic imagery with soft stimuli will evaluate the taste differently than the ones with hard stimuli. Soft stimuli will be hedonically paired with sweet(er) perceived taste.
H1b: Participants who will experience haptic imagery with hard stimuli will evaluate the taste differently than the ones with soft stimuli. Hard stimuli will be hedonically paired with (more) sour and/or bitter perceived taste.
H2: The participants who will experience the soft-haptic imagery will have significantly higher product liking scores as opposed to the ones who will participate in the hard-haptic imagery conditions.
Moderators
Need for touch index. As individuals, consumers differ greatly in the amount of touch they exhibit while shopping. Some consumers touch products only when they put them in the shopping carts, while other consumers spend time exploring products with their hands before making a purchase. It seems likely that the information available through the sense of touch can differ in its impact depending on one’s need for touch. As these individual differences across subjects have to be considered, the “Need for Touch” (NFT) scale will be used as a moderator. The NFT scale (Peck & Childers, 2003) was designed to measure individual differences in preference for haptic (touch) information. Haptic orientation is defined as an individual variable which reveals the motivation of a person to or preference for touch. Thus, consumers with a high NFT are more confident when they judge products when they can touch them, and they get more frustrated when they cannot touch them (Peck & Childers, 2003).
the other hand, the autotelic one is initiated by affective, compulsive thoughts, feelings intrinsic to an activity (e.g., “touching products can be fun” or “when browsing in stores, I like to touch lots of products”) (Krishna & Morrin, 2008). Thus, this dimension is preference driven. While the instrumental one is relevant to purchase occasions, the latter one emphasizes one’s general liking for haptic input regardless of the purchase goal.
In essence, the NFT seems to be a possible moderator of the main relationship between haptic imagery and how people will perceive taste. High (versus low) NFT individuals are more inclined to touch objects and more likely to use haptic stimuli to gather information. Also, they are more prone to form rich mental product representations (imagining) that consist of haptic properties. The underlying mechanism behind this is that these haptically oriented consumers possess higher chronical accessibility to store haptic information while using less of their cognitive processing capacity. Likewise, they are able to recognize more easily haptic stimuli(Peck & Childers, 2003).
H3: The impact of haptic stimuli on consumers’ taste perception will be moderated by NFT haptic orientation, such that the more haptically oriented individuals will be more likely to exhibit the impact of such stimuli on taste perception.
Food involvement. When a person perceives an object or a stimulus as important and
relevant to one’s personal needs, values and interests, then they experience a certain level of involvement. Food involvement consists of the level of importance placed on food by an individual. In other words, the extent to which consumers enjoy speaking about food, think of food all day and engage in food related activities. Individuals with a high level of food involvement are known to make finer taste discriminations in their sensory evaluation and hedonic rating (Bell & Marshall, 2003). In contrast with high involved individuals, the low involved people pay less attention to sensory characteristics of foods and find food experiences less important. (Bell & Marshall, 2003). Same authors have also developed a scale to measure food involvement. In this case, food involvement of the participants in this study acts as a moderator. This is expected to affect the strengths of the relations between the independent and dependable variable.
To sum up, the conceptual model shown in Figure 4 illustrates the main variables and their relationships resulted from the literature review above.
Figure 4. Conceptual model with main relationships and moderators
Methodology Participants and design
The data was collected using an online survey given to a random sample of participants to test and observe the relationship among variables. This survey was designed using Qualtrics. The survey link was distributed on social media and by email. Participation was voluntary, and no compensation was offered. The sampling method used was convenience and snowball sampling. The study had a between-subjects design, where participants were exposed to only one of the conditions and not both at the same time. The independent variable was haptic imagery (soft versus hard) and dependent variables were perceived taste, followed by product liking.
(28.7%, n = 101). More women (67.3%, n = 101) participated in the study than men (32.7%, n = 101). The sample consisted of many different nationalities with the majority of respondents holding Dutch (33.7%), Romanian (17.8%) and German (9.9%) nationality.
Materials
Haptic imagery. Participants were randomly assigned to look at two products to eliminate
bias by giving all individuals an equal chance to be chosen (Malhotra, 2009). The product used was either a soft cotton blanket or hard burlap blanket. This was displayed in black and white images to discount any colour influence. The pictures (soft: 921 x 517; hard: 872 x 360) were collected from Google images and modified in Photoshop (see Figure 5). In order to assure the products in the scenario portray the right stimuli, the study of Zhang (2004) was used. For the soft stimuli, any object made of velvet, fleece or leather can be used. For the hard stimuli, it could be carpet backing, burlap or sandpaper. The pictures were accompanied by a text briefly describing the product. From all respondents, 50 were exposed to the Soft stimuli and 51 to the Hard stimuli.
a b
Perceived taste. The second part of the survey started with introducing a fast-moving
consumer good, namely a bottle of white wine, to all the participants. The white wine was presented after the haptic imagery manipulations due to the recency effect, were the soft or hard stimuli were still present in the sensory/short term memory of the participants. To account for any extraneous factors, the product chosen had to be the same for both participant groups and satisfy a quite challenging condition: the product stimulus needed to be capable of producing significant taste perceptions, from sweet to sour to bitter.). The product used was wine, participants got to see an image (1280 x 720) of a plain bottle of white wine with a wine glass, no brand or label was used to rule out any branding influence (see Figure 6). The instruments used to measure the perceived taste have previously been used and tested in other studies that researched the perceived taste of food such as level of sweetness(Elder & Krishna, 2010) (Slocombe et al., 2016). The participants had to rate the taste of the wine on four dimensions (sweet, bitter, sour and salty) by using a four-point Likert slide bar from “Not at all” to “Very”.
Figure 6. Picture of the product (a bottle of white wine) used in the survey for measuring perceived taste.
Product liking. Furthermore, three questions were presented to the participants to rate the
A factor analysis was used to assess the correlation between the items of the construct- product liking. The Bartlett’s Test was significant (p < .05) with a KMO value of 0.583, which is considered acceptable. This means all the of the elements (product interest, hedonic scale, willingness to try) were treated as a construct. The construct was a reliable measure of the extent to which respondents liked or disliked the product introduced in the study (Cronbach’s α = 0.753).
Product familiarity. Product familiarity was introduced as a control variable. For this
experiment, any change in the control variable would invalidate the correlation of dependent variable (perceived taste) to the independent variable (haptic imagery). In the case of existing products, it is much more likely that previous experience will guide consumer perception of tactile input (Jansson-Boyd & Marlow, 2007). When consumers are familiar with the type of product or its category, they might use this prior knowledge to determine the expected taste. To measure how familiar the respondents were with the white wine, we used a construct made of two items (“I am familiar with white wine”, “I regularly drink white wine”). The items were adapted from a study by Schlinger (1979) and were a reliable measure of product familiarity (Cronbach’s α = 0.739).
Need for touch. The current research focused on the autotelic dimension of the Need for
Touch Index, which captures the individual’s general liking for haptic input from products regardless of whether or not they face an immediate purchase goal (Peck & Childers, 2003). The full scale (see Appendix A) consisted of six items (Cronbach’s α = 0. 943) and represented a reliable measure of people’s need for touch (Peck & Childers, 2003). For this variable, a seven-point Likert scale (1 = Strongly disagree to 7 = Strongly agree) was used to measure the respondents’ need for touch (sample item: “When walking through stores, I cannot help touching all kinds of products.”).
Involvement. The questions probing involvement for the survey were adapted according
and scales were found reliable (Cronbach’s α = 0.801) and sufficient to measure respondents’ involvement.
Procedure
Results Haptic imagery manipulations
There was a significant and positive correlation between the blanket feeling soft and the respondents being able to imagine the blanket in their hands (r = 0.57, p = 0.000). The more they were able to imagine the blanket and feeling the texture in their hands, the more they agreed that the blanket was soft. This did not happen in the hard stimulus condition, where the correlations were insignificant and negative (r = -0.014, p = 0.921). Despite the picture depicting a blanket made of a hard and rough material (burlap), blankets made from this material are rarely encountered and used. Thus, respondents might have experienced troubles imagining such a product and material. Furthermore, all participants for both conditions had to write down their thoughts about how the blanket felt in their hands. On average (MSoft = 6.2, SD = 1.178; MHard =
5.7, SD = 1.372) participants agreed that the blankets on the pictures felt soft, and respectively hard when they imagined touching them. This can be seen also in Figure 7, where the words and thoughts of participants perfectly reflect the condition they were exposed to.
a b
Figure 7. Pictures of the most common words respondents wrote when evaluating how the soft (a) and hard (b) blanket felt after imagining it
Haptic imagery and perceived taste
To test the influence of soft versus hard haptic imagery on taste perception (sweet, sour, bite and salty), I conducted an independent samples t-test. Levene’s test for equality of variances indicated that the variance between the two groups (i.e., soft versus hard) was equal (Fsweet = 0.849,
equal variances. This test showed that there was not a significant difference between the soft and hard condition (Table 2, Figure 8). Specifically, participants who were exposed to the soft haptic stimuli did not perceive the taste much different than the ones exposed to the hard stimuli. Thus, haptic imagery did not influence significantly the perceived taste of the wine. Overall, the sweet taste seemed to dominate across both conditions.
Table 2.
T-test results comparing soft and hard haptic imagery on perceived taste
Note: M = mean, SD = standard deviation
Figure 8. Mean ratings of perceived taste for soft and hard haptic imagery
Product familiarity and liking
In order to check if the product familiarity differed between the conditions, an independent t-test was performed. Levene’s test for equality of variances indicated that the variance between the two groups was equal, F = 0.088, p = .76. There was an insignificant difference between the scores for Soft (M = -0.06, SD = 0.97) and Hard (M = 0.06, SD = 1.03) conditions; t (99) = -0.586, p = .55 (see Table 3). Explicitly, participants’ familiarity with the product did not significantly differ between the Soft and Hard manipulations.
Same as with the product familiarity, an independent-samples t-test was conducted to compare product liking across the two conditions. Levene’s test for equality of variances indicated
2.61 2.31 1.69 1.12 2.7 2.36 1.78 1.22 0 1 2 3 4 5
Sweet Sour Bitter Salty
Me an Sco res Taste Perception HARD SOFT
Soft (n=50) Hard (n=51) t-test
M SD M SD t-value df p
Sweet 2.70 1.11 2.61 1.16 0.406 99 .68
Sour 2.36 1.06 2.31 0.99 0.226 99 .82
Bitter 1.78 1.01 1.69 0.99 0.470 99 .64
that the variance between the two groups was equal, F = 0.561, p = .45. There was not a significant difference in the scores for Soft (M = 0.06, SD = 1.02) and Hard (M = -0.06, SD = 0.98) conditions; t (99) = 0.564, p = .57 (see Table 3). Specifically, participants who were exposed to the soft haptic condition did not like the product more than the ones exposed to the hard haptic one.
Table 3
T-test results comparing soft vs hard haptic imagery on product familiarity and liking
Moreover, a linear regression analysis was used to examine if product familiarity (control variable) was able to predict the perceived taste. The results showed insignificant relationships for all taste dimensions (p > .05), meaning that the prior familiarity with the product was not good in predicting the perceived taste of the white wine (Table 4). If Alpha significance level is taken at 10% (α < .10), then the bitter taste showed marginally significant results (p = 0.08, p < .10). In other words, the regression results indicate that the more familiar respondents were with the white wine, the less bitter the perceived taste was.
Table 4
Results of the regressions analysis by perceived taste for product familiarity
t p β F df p R2 Sweet -0.229 0.81 -0.026 0.052 1 .81 0.001 Sour -1.490 0.13 -0.151 2.220 1 .13 0.022 Bitter -1.729 0.08 -0.171 2.991 1 .08* 0.029 Salty -0.784 0.43 -0.037 0.614 1 .43 0.006 *p < .10
In sum, the main effects (hypothesis one and two) were not supported, and haptic imagery did not significantly influence the taste perception and liking of the product.
Moderation analysis
Need for touch. To further examine if Need for Touch Index acted as moderator of the
relationship between haptic imagery and taste perception, the PROCESS extension for SPSS developed by Hayes (2013) was used. For this single order moderation, base model one was tested for each of the taste dimensions. Overall, no moderation effect was found for either of the taste dimensions (all p’s > .05). In other words, the Need for Touch moderator did not alter the strength
Soft (n=50) Hard (n=51) t-test
M SD M SD t-value df p
Product Familiarity -0.06 0.97 0.06 1.03 -0.586 99 .55
of the causal relationship between haptic imagery and perceived taste (for full results on all items, see Table 5).
Table 5
Results for testing moderation effect of need for touch index on the haptic imagery-perceived taste relationship
Sweet β se t p LLCI ULCI
(Constant) 2.6530 0.1163 22.8103 .00 2.4222 2.8839
NFT 0.0935 0.1198 0.7809 .43 -0.1442 0.3313
Haptic imagery -0.0913 0.2325 -0.3927 .69 -0.5527 0.3701
INT -0.1887 0.2393 -0.7886 .43 -0.6637 0.2863
R2= 0.0142, F = 0.5212, p = .66
Sour β se t p LLCI ULCI
(Constant) 2.3357 0.1032 22.6437 .00 2.1310 2.5405
NFT -0.0063 0.1021 -0.0614 .95 -0.2088 0.1963
Haptic imagery -0.0463 0.2065 -0.2243 .82 -0.4561 0.3635
INT -0.3949 0.2043 -1.9330 .06 -0.8004 0.0106
R2 = 0.0380, F = 1.3050, p = .27
Bitter β se t p LLCI ULCI
(Constant) 1.7326 0.1023 16.9400 .00 1.5296 1.9356
NFT -0.0915 0.0994 -0.9199 .35 -0.2888 0.1059
Haptic imagery -0.0946 0.2046 -0.4621 .64 -0.5007 0.3116
INT -0.0151 0.1991 -0.0759 .93 -0.4103 0.3801
R 2= 0.0108, F = 0.3542, p =.78
Salty β se t p LLCI ULCI
(Constant) 1.1685 0.0475 24.5781 .00 1.0742 1.2629
NFT -0.0864 0.0552 -1.5659 .12 -0.1959 0.0231
Haptic imagery -0.1031 0.0950 -1.0852 .28 -0.2918 0.0855
INT 0.0972 0.1105 0.3814 .38 -0.1222 0.3166
R2 = 0.0531, F = 1.0846, p = .35 Note: INT = interaction effect
Involvement. After running a factor analysis, it was concluded that the involvement
Table 6
Results for testing moderation effect of wine involvement on the haptic imagery-perceived taste relationship
β se t p LLCI ULCI Sweet (Constant) 2.6526 0.1175 22.5725 .00 2.4194 2.8859 Wine Involvement -0.0592 0.1282 -0.4623 .64 -0.3136 0.1951 Haptic imagery -0.0874 0.2566 0.1639 .71 -0.5537 0.3789 INT 0.0421 0.2566 0.1639 .87 -0.4672 0.5513 R2 = 0.0045, F = 0.138, p = .93 Sour (Constant) 2.3355 0.1045 22.3456 .00 2.1281 2.5429 Wine Involvement -0.1353 0.1032 -1.3116 .19 -0.3401 0.0694 Haptic imagery -0.0354 0.2092 -0.1692 .86 -0.4506 0.3798 INT 0.0567 0.2066 0.2744 .78 -0.5645 0.3518 R2 = 0.0179, F = 0.6040, p = .61 Bitter (Constant) 1.7389 0.1024 16.9829 .00 1.5357 1.9422 Wine Involvement -0.0536 0.10.68 -0.5022 .61 -0.2656 0.1584 Haptic imagery -0.3130 0.2144 -1.4598 .66 -0.4964 0.3171 INT -0.3130 0.2144 -1.4598 .14 -0.7385 0.1125 R2= 0.0315, F = 1.1692, p = .32 Salty (Constant) 1.1693 0.0496 23.5741 .00 1.0709 1.2678 Wine Involvement -0.0341 0.0647 -0.5268 .59 -0.1626 0.0944 Haptic imagery -0.0997 0.0922 -1.0047 .31 -0.2965 0.0972 INT -0.0512 0.1298 -0.3943 .69 -0.3087 0.1829 R2 = 0.0211, F = 0.8096, p = .49 Note: INT = interaction effect
Table 7
Results for testing moderation effect of food involvement on the haptic imagery-perceived taste relationship
Note: INT = interaction effect
In short, even though the manipulations used in the study were able to represent the soft and hard stimuli, the analysis results indicated that haptic imagery did not influence significantly neither the perceive taste, nor the product liking. In general, product familiarity did not affect the perceived taste. Also, the two moderators, Need for Touch and Involvement, did not change the strength of the main relationship between haptic imagery and perceived taste. In the next section, I will introduce a few exploratory analysis representative for this study.
Exploratory analysis
Product familiarity and liking. A correlation analysis tested where there was statistical
evidence for a linear relationship between how familiar the respondents were with the white wine and how much they liked the product. The results showed that product familiarity and liking had a statistically significant linear relationship (p = .05) and were positively correlated (r = 0.193). This means that greater familiarity with the product is associated with greater liking.
Perceived Soft and Hard and sweetness. After imagining the blanket, all respondents for
both conditions had to express their agreement to how soft or hard they thought the blanket felt. As this is also considered an indicative of the manipulations, we decided to test if there is any significant relationship between this variable and the taste dimensions. A linear regression established that respondents thinking that the blanket felt soft could statistically significantly predict the level of sweetness (F = 6.400, p = .01) (see Table 8). The perceived taste of sweetness accounted for 11.8% of the explained variability in the dependent variable. So, for every unit increase in the degree of softness, we found an approximately 0.324-point (β = 0.324, p = .01) increase in the sweetness score, holding all other variables constant. The same linear regression for the Hard condition, established that thinking that the blanket felt hard could only marginally significantly predict the level of sweetness, (F = 17.47, p = .057.) The perceived taste of sweetness accounted for only 7.2% of the explained variability in the dependent variable. So, for every unit increase in the degree of hardness, we found an approximately 0.228-point (β = -0.228, p = .057) decrease in the sweetness score, holding all other variables constant.
Table 8
Results of the regressions analysis by perceived taste for soft and hard haptic imagery
t p β F df p R2
Blanket feels Soft 2.530 0.01 0.324 6.400 1 .01* 0.118
For all the other taste dimensions, the regression analysis indicated insignificant results. Thus, respondents thinking that the blanket felt soft and hard could not predict the level of sourness, bitterness and saltiness (for an overview of the results, see Appendix C).
Need for touch and product liking. We tested whether participants’ need for touch
moderated the effect of haptic imagery on product liking. The interaction effect showed a significant and positive result (p = .01) (see Table 10). The greater the need for touch, the more positive becomes the effect of haptic imagery on product liking (β = 0.5587, p = .01). In addition, the conditional effect of haptic imagery on product liking at values of the moderator showed significant results only for the low need for touch (p = .03). When the need for touch is low, there is a significant relationship between haptic imagery and product liking, β = -0.6702, CI [−1.2796, -0.0608], t = -2.1826, p = .03. Figure 9 indicates the direction of this effect: for the soft haptic, the higher the need for touch, the lower the product liking; for the hard haptic, the higher the need for touch, the higher the product liking.
Table 9
Results for testing moderation effect of need for touch on the haptic imagery-product liking relationship
β se t p LLCI ULCI (Constant) 0.0013 0.0980 0.0129 .98 -0.1933 0.1959 NFT 0.1271 0.1101 1.1540 .25 -0.0915 0.3457 Haptic imagery -0.1115 0.1964 -0.5679 .57 -0.5013 0.2782 INT 0.5587 0.2208 2.5305 .01* 0.1205 0.9968 R2 = 0.1032, F = 3.2178, p = .02 *p < .05
Figure 9. Impact of haptic imagery on product liking under the influence of need for touch index. -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
Low Medium High
Discussion
Inspired by insights from cross-modal correspondences literature and sensory marketing, we tested whether haptic imagery influences how consumers perceive the taste of a fast-moving consumer products. Research has paid relatively little attention to how haptic inputs affect other senses such as taste and marketing researchers tend to focus mainly on the physical product features and less on the sensory appeals of these products. Peck and Wiggins (2006) revealed that when a message has a haptic element incorporated, it is perceived more persuasive than one without, and the message containing a soft haptic element receives more positive attitudes.
This study was designed with the aim of determining cross-modal associations between haptic imagery and perceived taste. What could be the possible mechanism underlying this relationship? In the beginning of this paper, we introduced the hedonic association theory. The literature has shown that soft, smooth surfaces are considered pleasant, while the hard, rough ones are experienced as unpleasant. The same theory holds for taste dimensions, where sweet is associated with pleasantness (Glendinning, 1994; Lindemann, 2001; Pandey et al., 2010). The soft imagined tactile pleasantness was expected to be paired up with the sweet dimension.
Firstly, the experiments used in this study intended to manipulate one modality (haptic imagery with soft and hard stimuli) while measuring another (perceived taste). In addition, we evaluated whether haptic imagery can predict product liking. Contrary to the expectations, our results suggest that haptic imagery does not have an effect on the perceived taste and product liking. Specifically, we did not find any differences between the soft and hard stimuli and the various taste dimensions (sweet, sour, bitter, salty). A plausible explanation and limitation for this result is that the respondents were exposed to a small amount of information about both products used in the study (blanket and white wine). This might have caused them filling in other types of information in that they, for instance, could not have imagined themselves touching the product based only on the image they saw. For instance, the lighter colour of the wine presented in the study could have made participants think it was a sweet wine and it is seen as a limitation.
and their individual preferences for sweet, salty, bitter or sour taste. Some people rate sweet as hedonically pleasant and others might do the opposite and choose bitter or salty.
In addition, it could also be the case that the affective and hedonic response to the haptic stimuli (soft or hard) can be moderated by other factors. The exploratory analysis showed that the need for touch moderated the relationship between haptic imagery and product liking. When exposed to the soft haptic, the higher the need for touch of participants, the less they liked the product; for the hard haptic, the higher the need for touch, the higher the product liking. Although it was expected that the soft tactile pleasantness would have a positively effect on product liking, when the relationship was moderated by the need for touch, the results showed the contrary. It is possible that some people do not respond positively to soft cues and find hard haptic hedonically positive. Another explanation for this outcome is presented in the paper of Peck and Childers (2003), where they concluded that for the high in need for touch individuals, the lack of a direct experience due to a barrier to touch (in this case imagined touch) resulted in a lack of confidence in their judgement.
Secondly, the hypothesis regarding the need for touch and involvement as moderators were not supported by the results. Hence, the effects of the haptic imagery on perceived taste were not strengthened by individual need for touch differences. A pleasure-based explanation proposes that high autotelic can get equal pleasure from touching firm or flimsy objects and hence the effects of haptic cues (soft and hard) did not affect the taste perception (Krishna & Morrin, 2008; Peck & Childers, 2003). Also, the participants’ involvement did not strengthen or weakened the relationship between the haptic imagery and taste perception. A possible explanation is that the product used (wine) is not considered a high involvement product, but a low one among the target group of the sample.
emphasize on an aspect of a product, such as low sugar products, by changing the packaging texture.
Still, we agree that the results of the current research need to be replicated with other haptic stimuli that vary in texture or weight and other types of products (consumers goods that are low versus high in need for touch). The reproduction of this study can be further researched by using a within- participants experimental design and a larger sample. This would help to research more individual differences between participants and produce significant results. Moreover, there is a need for research in studying how different senses are paired or matched and how their interactions can affect consumers’ behaviour, perceptions, and choices. We hope that further research will further explore the role of (imagined) touch in relation to other senses and investigate whether any other types of cross-modal associations exist. This topic is particularly important and encouraged by the rise of online shopping and e-commerce, where consumers buy online, and they are deprived of the opportunity to touch the product before purchase. Further research on haptics is bound to increase as many marketers are interested in how to compensate for touch when there is no option to touch (Hagtvedt & Brasel, 2016).
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Appendix A
Items Need for Touch Scale (Peck & Childers, 2003)
Need for Touch Index
When walking through stores, I cannot help touching all kinds of products. (1) Touching products can be fun. (2)
When browsing in stores, it is important for me to handle all kinds of products. (3) I like to touch products even if I have no intention of buying them. (4)
When browsing in stores, I like to touch lots of products. (5) I find myself touching all kinds of products in stores. (6)
Appendix B
Involvement Items (Bell & Marshall, 2003); (Lee & Mccole, 2016)
Involvement Items
I enjoy cooking for others and myself. (1) Excluded
When I eat out, I don’t think or talk much about how the food tastes. (2) Factor 2 Regarding the decisions I have to make on a daily basis, those related to food are the most important. (3) Factor 2 Talking about what I ate/drank or am going to eat/drink is something I like to do. (4) Factor 2
I have a strong interest in wine. (5) Factor 1
Wine is important to me in my lifestyle. (6) Factor 1
Drinking wine gives me pleasure. (7) Factor 1
Please select option "Agree" (8) Excluded
Appendix C
Results of the regressions analysis by perceived taste for soft and hard haptic imagery
t p β F df p R2
Sour
Blanket feels Soft 3.859 .33 -0.126 0.959 1 .33 0.020
Blanket feels Hard 3.677 .88 0.015 0.021 1 .88 0.000
Bitter
Blanket feels Soft 2.595 .74 -0.041 0.110 1 .74 0.002
Blanket feels Hard 3.125 -0.036 .72 0.123 1 .72 0.002
Salty
Blanket feels Soft 4.519 .27 -0.062 1.206 1 .27 0.025
