Keywords

Complex Buying Behavior, Dissonance-Reducing Buying Behavior, Variety Seeking Behavior.

Introduction

One of the fundamental starting points for sensory marketing is the fact that up to 80% of purchases are made impulsively (Satti, et al., 2021). A typical impulsive purchase takes place suddenly, unplanned and without long thought, and is accompanied by strong emotions and a desire for the product. Therefore, it can be said that most of purchasing decisions are not based on strictly rational considerations, but on emotions. Thus, the main mission of this marketing direction is to evoke the desired emotions by influencing the senses of customers (Lizbetinova, et al., 2019). A similar argument, i.e. that the still prevailing view of classical economic theory is not satisfactory in terms of explaining consumer behavior, is given mainly by the proponents of the so-called behavioral economics. Biswas et al., (2020) state that the argument of the classical theory that people behave rationally and selfishly and in spirit calculate in the interest of their greatest benefit (or at least behave as if they did) does not stand up in many respects. According to Foster et al., (2020), one of the unrealistic assumptions is perfect rationality (however, this assumption was previously modernized by the so-called theory of limited rationality), which is not possible due to the limited possibilities of the human brain. Also the argument that in experiments the deviations observed from the assumptions of classical models are negligible deviations in the long run can be challenged by the fact that the observed deviations are mostly systematic, ie most individuals "make mistakes" in a comparable way. Althagafi & Ali, (2017) state that although economists' views have shifted from the original assumption of perfect rationality to a limited rationality approach and related theories, these approaches still neglect other important factors influencing consumer choice - such as buying emotions, experiences or ideas. Thus, it is evident that the fields of science, which more significantly connect the findings of economics and psychology, represent an ideal field for contemporary scientific research.

Literature Review

One of the main reasons for the emergence of sensory marketing can be identified by the growing competition on the supply side. As competitive pressure intensified, it became apparent that it was not enough to provide added value in the form of new / improved product features. It was necessary to go further, to offer an unusual experience for the customer. According to Haase & Wiedmann, (2018), this is a natural development of the economy at a time when services are already becoming "commodities" that the customer finds in every producer. A similar view is held by Chongvisal (2020), who also considers the emergence of experiential marketing as a consequence of the existence of saturated global markets with mutually balanced products. However, it cannot be said that the concept of "creating experiences" is a purely modern matter. As early as the 1970s, Philip Kotler claimed that the customer viewed the product not only as a tangible thing, but as part of a "total product" in which advertising can be also found, after-sales or customer service, and the like (Garbarova, et al., 2017). He describes the "atmosphere" of the point of sale, which significantly influences the purchase decision, as one of the essential components of the overall product.

An important starting point for understanding the concept of sensory marketing is several theoretical models that were created to understand the customer's behavior as an imperfect individual, who, in addition to rational impulses, is also controlled by emotions and other psychological variables (Labrecque, 2020). Probably the most important theoretical concept in this research area is the Mehrabian-Russell model of stimulus-response, which assumes a crucial role of emotional states in consumer behavior, and which is the most frequently cited and used model (Bastiaansen, et al., n.d.). The concept of Howard and Sheth looks at the process of consumer behavior more comprehensively, which does not neglect the role of other variables - attitudes, motives and attention; thus suitably complementing the knowledge of the M-R model (Jimenez-Marin, et al., 2019). The Foote Cone Belding model can also be used, which emphasizes the different approach of customers to buying different types of products (and classifies them according to the priority of emotional or rational purchasing decisions), and especially its knowledge using the model of Petty and Cacciop (Krishna, et al., 2016). It develops the process of changing attitudes (customer) in situations of low and high involvement.

The emotional world of people is an extremely rich environment that has not yet been fully explored and understood. However, not only for the purposes of scientific work, over the years, a number of theories and ways of classifying emotions have emerged, which try to satisfactorily describe this world (Kampf, et al., 2017). Emotions significantly affect the way consumers perceive. Perception is a selective process during which not all but only selected information enters the consciousness. It is at this stage that emotions prove their power, which will influence what information will be taken into account at a given moment. Humans subconsciously try to perceive the world around us in such a way that it is in accordance with the given emotion, while less weight is given to other information. According to Kim et al., (n.d.), sensory experiences can even be directly described as a specific type of emotion, with each of the five senses having a specific "emotion." It can therefore be argued that it is extremely important for the marketer to evoke emotions in the consumer that will harmonize with the brand / product image and help to "bring" the customer closer in the decision-making process to buy (Petit, et al., 2019). Emotions form the core of the interest of emotional and sensory marketing and significantly influence consumer choice. It is known that dozens of different emotions play a role not only in shopping, but also in everyday life, to which the marketing communication of many companies tries to appeal (Soleimani, et al., 2021). The basic emotions are surprise, sadness, resentment, anger, fear, and positive emotions. However, there are a number of so-called higher emotions such as love, trust or national pride, which are related to the role in society. Emotions are also closely related to motivation, memory and the process of perception itself. They play a role in trying to attract the customer's attention and motivate him to buy. They also reinforce and "color" memories - evoking the desired emotional response in the consumer then has a beneficial effect on remembering the marketing message, motivation to buy and creating associations with the brand. Influencing emotions also contributes to the creation of cognitive abbreviations and attitudes that significantly influence purchasing decisions.

Contemporary research shows that thoughtful use of sensory stimulation from any sensory area can have a positive effect on customers' shopping behavior (Narayan & Singh, 2019). In the case of additional visual stimulation, the illumination of the product or its color, for example, has a similar effect. Of the sound perceptions, the purchase is influenced by the very presence of the musical undertone, as well as its tempo, volume and selected genre. According to Jang & Lee (2019), the presence of a suitably chosen scent also has a positive effect on the dimensions of consumer behavior (especially emotions and evaluation), but it is necessary to carefully choose its intensity. Of the haptic perceptions, it seems that the very positive possibility of touching, palpable when buying a product seems to be the most positive. Regarding the effect of tastes, previous research has usually focused on examining the effect of other sensory stimulation on the perception of product taste. It is obvious that sensory perceptions can influence each other, and their mutual harmony plays a role here (Marin Duenas & Gomez Carmona, 2021).

Emotions go hand in hand with brand building (Sukalova & Ceniga, 2017). Emotions are the main reason why consumers prefer specific brand products. The vast majority of popular products have their equivalent substitutes on the market. They often differ only in brand and price. They are defined through the brands that consumers buy. They share similar values or hobbies and by buying branded products, they let the neighborhood know. The stronger the customer's bond with the brand, the less sensitive he is to price changes. Sometimes the relationship is so strong that the emotions are at a maximum - affection for Coca-Cola evokes contempt for Pepsi and vice versa (Kim, et al., 2020). Emotional activation requires less attention and active interest in the product. In the short term, purchasing responses are weak, but because the feelings are remembered longer, this strategy is effective mainly in the long term. Repeated exposure to advertising deepens these feelings and grows the strength of the brand (Jakubanecs, et al., 2019). On the other hand, rational reasons work in the short term. It is ideal to use them just before the moment of purchase to have the strongest response. But because these types of messages are quickly forgotten and consumers stop paying attention to them after shopping, the effects are rapidly diminishing (Kohli, et al., 2021). On brand perception, long-term sales or price elasticity has little effect. Ideally designed campaigns provoke both reactions. Emotional activation causes consumers to perceive more and more rational reasons, thus amplifying short-term reactions (Yung, et al., 2021). Rational activation, in turn, allows to unlock the value of the brand that leads to the purchase. Advertisers should spend more on brand promotion in rational categories. The opposite is true for emotional purchases. It is much easier to change brand perceptions when consumers follow their feelings. Nevertheless, it is harder to get an immediate response. Emotional connections play an important role in consumer choice. Functional magnetic resonance imaging shows that consumers use emotions (personal feelings and experiences) rather than information (attributes, characteristics and facts) when evaluating brands (Danilwan, et al., 2020). Deciding what emotions a business wants to evoke through its promotional activities is as important as choosing a logo or website design logo because it determines how it wants to reach its target audience. The emotions he wants to evoke should correspond to the company's values. Of course, the bond with the brand is most strengthened by positive emotions. If the company creates a pleasant and strong enough emotional bond with a brand or product, the probability increases that a consumer would choose exactly what evoked these emotions when making a purchase decision. Nevertheless, emotions must be handled with care. The challenge is to recognize what customers feel and want (Hong, et al., n.d.).

Thus, the issues of sensory and emotional marketing goes hand in hand with modern theories of brand value building and management. Many authors synonymize these terms, many authors perceive them as causally strongly connected where without sensory marketing there shouldn´t be emotional marketing as its logic consequence. However, other research presumption is built on the basis of the need of respecting product specifics. When traditional typology of buying behavior is taken into account, it shouldn´t be applied uniform approach to the issue of sensory resp. emotional marketing involvement into the theory and practice of brand management. This quadratic typology recognizes complex buying behavior, dissonance-reducing buying behavior, variety seeking behavior and habitual buying behavior. These buying behavior patterns are specific for specific types of products. Complex buying behavior is typical for products, where exists high involvement of consumers and significant differences between brands. Dissonance-reducing buying behavior is typical for products, where exists high involvement of consumers and few differences between brands. Variety seeking behavior is typical for products, where exists low involvement of consumers and significant differences between brands. Habitual buying behavior is typical for products, where exists low involvement of consumers and few differences between brands.

Traditionally, sensory and emotional marketing are connected and recommended for the products, which are typical by low involvement of consumers – i.e. where the concept of behavioral economy dominates the phenomenon of neoclassical Homo Oeconomicus. However, or research presumption lies in the need of distinguishing sensory and emotional marketing as two autonomous tools of brand value building and management. In such a concept, sensory marketing would be appropriate for products with low involvement of consumers (variety seeking behavior and habitual buying behavior) while emotional marketing would be appropriate for products with high involvement of consumers (complex buying behavior and dissonance-reducing buying behavior).

Methodology and Data

To fulfil the aim of the research primary data were obtained via own questionnaire research provided on the statistically relevant sample of Slovak consumers older than 15 years. This research has been realized electronically in the first quarter of year 2021.

The demographic profiles of the sample are exhibited in Table 1. Based on the number of frequencies, it can be conclude that the representation of individual traits is in the context of the entire population and with such a large sample size, distribution of sample approximates a normal distribution, which can be proved by a central limit theorem (Kwak & Kim, 2017). The data may therefore be considered suitable for further statistical investigation.

Table 1 Demographic Characteristic of the Sample
Demographic Categories	Frequency	Percentage
Gender
Female	327	54.5
Male	273	45.5
Age
74-56 (Generation BB)	104	17.33
55-40 (Generation X)	190	31.67
39-24 (Generation Y)	217	36.17
23-15 (Generation Z)	89	14.83
Disposable income
< 10 000	78	13
< 15 000	134	22.33
< 20 000	219	36.5
< 25 000	116	19.33
> 25 000	53	8.83
Employment status
Employed	195	32.5
Unemployed	52	8.67
Self-employed	188	31.33
Student	139	23.17
Retired	26	4.33
Total	600	100

The factor analysis has been chosen as a basic pillar of statistical evaluation of primary data obtained. Factor analysis is a multidimensional statistical method aimed at creating new unobservable variables, the so-called factors that will reduce and simplify the original amount of data while preserving a substantial amount of information. The linear combination of factors approximates the original observation, capturing the hidden relationships between the original variables.

Factor analysis is based on the existence of correlations between the observed variables and on the assumption that within these variables there are independent dimensions (factors) that contribute to the implementation of the correlations. Its basic idea is to reduce redundant (duplicate) information contained in several correlated variables. Thus, factor analysis provides a statistical model of data that reproduces correlations between variables through more general dimensions. These dimensions significantly contribute to the variability of the set of variables. In real data, however, part of this variability remains unexplained by the given dimensions (Child, 1990).

The basic task of factor analysis is to estimate the factor loads of individual variables, which express correlations between these variables and common factor dimensions. Based on the values of factor loads, it is possible to determine for each dimension the group of variables that most closely correlate with it. Thus, using the factor loads of individual variables, the degree of influence of this dimension on the variable is assigned in the identified factor dimension. The variables that weigh the most in the individual factor dimensions are then also authoritative in the interpretation of the dimensions obtained (Pett, et al., 2003).

Factor dimensions can be extracted from a set of original variables by several methods. The most commonly used method is the Principal components method (Dumitrescu, et al., 2013). It happens that the extracted factor dimensions (weakly) correlate with a larger number of original variables. This makes their interpretation practically impossible. This problem can be solved by rotating the factor dimensions. This is such a transformation of the extracted dimensions (geometrically factor dimensions are the axes of the rectangular coordinate system) so that the original variables are as factor as pure as possible (geometrically - as close as possible to the axes representing the factor dimensions). As a result, each factor correlates relatively highly with a small number of original variables, allowing for a better interpretation of the factors. The most commonly used method is the Varimax (scatter-maximizing rotation) method, which minimizes the number of variables that are highly correlated with individual dimensions (Nabelková & Hitka, 2007).

The initial conditions of factor analysis include a) high correlations of a large number of variables and b) low partial correlations. Whether the correlation and partial correlation matrices satisfy the assumptions is therefore tested by various coefficients and indices, usually Kaiser-Meyer-Olkin measure (KMO) and Bartlett's test of sphericity. The KMO measure provides an approach to comparing the zero-order correlations to the partial correlations (Munro, 2005). High KMO values (close to 1, at least 0.6) and the significance of the Bartlett test (p<0.001) indicate that the mentioned initial assumptions of factor analysis are statistically sufficient (Bracinikova & Matusinska, 2020). Kaiser-Meyer-Olkin measure is the measure of the adequacy of the selection is given by the equation:

where r² (x_j, x_j’) are simple correlation coefficients and r² (x_j, x_j’ · other x) are partial correlation coefficients under the condition of statically constant remaining p-2 variables (x₁, x₂, ..., x_j − 1, x_j + 1, ..., x_j’ − 1, x_j’ + 1, x_p). Bartlett test of sphericity is designed to verify the hypothesis of equal variances for normal distributions. The Bartlett test is given by the equation:

where S_i² is the variance of the i^th group, N is the total sample size, N_i is the sample size of the i^th group, k is the number of groups, and S_p² is the pooled variance. The pooled variance is a weighted average of the group variances and is defined as:

Based on the performed factor analysis for different types of products, it is possible to determine the conformity, or possible differences between them within the importance of sources of brand value. This will be a decisive opinion on whether or not to apply a uniform approach to the issue of sensory or emotional marketing involvement in the theory and practice of brand management. These representative types of products were chosen: 1) passenger cars, 2) banking services, 3) cola drinks and 4) sportswear.

To provide research of brand value sources of consumers, traditional quadratic typology of its composition has been chosen. In scope of this theory, these are the main brand value sources: 1) imageries 2) attitudes 3) attributes 4) benefits. These brand value sources and their elements are summarized in the Table 2. Respondents were asked to what extent they would be affected by each element of brand value sources during buying process. They were able to express their attitude using a 7-point scale, where 1 was very strong influence and 7 was very weak influence.

Table 2 Elements of Brand Value Sources
Brand Value Sources	Elements of Brand Value Sources
Imageries	Happiness Pleasure Satisfaction Certainty Enthusiasm
Attitudes	Targeted buying branded products Regular interest in branded products Attention of branded products because of considering them to be better Attention of branded products because of considering them to be more prestigious
Attributes	Awaiting quality from a branded product Awaiting availability from a branded product Awaiting image making from a branded product Awaiting innovativeness from a branded product Awaiting creative advertising from a branded product
Benefits	Branded product makes me happier Branded product increases my social status Branded product makes it easier for me to make friends Branded product attracts the attention of others Branded product belongs to my lifestyle

Results and Discussion

The Table 3 contains the values of the Kaiser-Meyer-Olkin test (KMO) and the Bartlett test for sphericity. With a KMO values of 0.940, 0.929, 0.935 and 0.935, the data can be classified as useful for the application of factor analysis. The Bartlett test tests the null hypothesis that the data comes from a population in which all variables are uncorrelated. Since the test is significant, the null hypothesis can be rejected. There are therefore sufficient correlations, so a factor analysis can be used.

The Table 3 shows the eigenvalues of all factors as well. The eigenvalue represents the sum of the squared factor loadings of all variables for a factor. It describes the proportion of the total variance of all items that is clarified by a factor. In our case, four factors have an eigenvalue greater than 1 and are extracted according to the Kaiser criterion for all representative types of products examined.

Table 3 Initial Conditions of Factor Analysis
	Bartlett's Test of Sphericity	Kaiser-Meyer-Olkin Measure of Sampling Adequacy	Total Cumulative Variance	Number of Components (Eigenvalues)
Passenger cars	0.000	0.940	77.346%	4
Banking services	0.000	0.929	73.722%	4
Cola drinks	0.000	0.935	76.386%	4
Sportswear	0.000	0.935	76.397%	4

As all communalities are above 0.5, none was excluded and rotation of the matrices was performed for better interpretation. These are shown in Tables 4, 5, 6 and 7.

Table 4 Rotated Component Matrix – Passenger Cars
	Component
	1	2	3	4
Happiness	.798
Pleasure	.801
Satisfaction	.807
Certainty	.814
Enthusiasm	.721
Targeted buying branded products				.777
Regular interest in branded products				.745
Attention of branded products because of considering them to be better				.802
Attention of branded products because of considering them to be more prestigious				.767
Awaiting quality from a branded product			.754
Awaiting availability from a branded product			.772
Awaiting image making from a branded product			.787
Awaiting innovativeness from a branded product			.736
Awaiting creative advertising from a branded product			.691
Branded product makes me happier		.788
Branded product increases my social status		.840
Branded product makes it easier for me to make friends		.785
Branded product attracts the attention of others		.738
Branded product belongs to my lifestyle		.704

Table 5 Rotated Component Matrix – Bank Services
	Component
	1	2	3	4
Happiness	.783
Pleasure	.800
Satisfaction	.815
Certainty	.825
Enthusiasm	.690
Targeted buying branded products				.787
Regular interest in branded products				.700
Attention of branded products because of considering them to be better				.790
Attention of branded products because of considering them to be more prestigious				.746
Awaiting quality from a branded product			.715
Awaiting availability from a branded product			.802
Awaiting image making from a branded product			.814
Awaiting innovativeness from a branded product			.673
Awaiting creative advertising from a branded product			.657
Branded product makes me happier		.758
Branded product increases my social status		.855
Branded product makes it easier for me to make friends		.750
Branded product attracts the attention of others		.741
Branded product belongs to my lifestyle		.633

Table 6 Rotated Component Matrix – Cola Drinks
	Component
	1	2	3	4
Happiness	.813
Pleasure	.802
Satisfaction	.739
Certainty	.799
Enthusiasm	.814
Targeted buying branded products				.775
Regular interest in branded products				.730
Attention of branded products because of considering them to be better				.806
Attention of branded products because of considering them to be more prestigious				.705
Awaiting quality from a branded product			.774
Awaiting availability from a branded product			.773
Awaiting image making from a branded product			.789
Awaiting innovativeness from a branded product			.732
Awaiting creative advertising from a branded product			.618
Branded product makes me happier		.769
Branded product increases my social status		.849
Branded product makes it easier for me to make friends		.757
Branded product attracts the attention of others		.737
Branded product belongs to my lifestyle		.686

Table 7 Rotated Component Matrix – Sportswear
	Component
	1	2	3	4
Happiness	.804
Pleasure	.798
Satisfaction	.730
Certainty	.789
Enthusiasm	.814
Targeted buying branded products				.771
Regular interest in branded products				.725
Attention of branded products because of considering them to be better				.807
Attention of branded products because of considering them to be more prestigious				.725
Awaiting quality from a branded product			.783
Awaiting availability from a branded product			.772
Awaiting image making from a branded product			.797
Awaiting innovativeness from a branded product			.749
Awaiting creative advertising from a branded product			.636
Branded product makes me happier		.769
Branded product increases my social status		.850
Branded product makes it easier for me to make friends		.756
Branded product attracts the attention of others		.753
Branded product belongs to my lifestyle		.674

The rotated component matrices shows a fairly clear simple structure, i.e. the individual items load high on one factor and low on the other factors. Thus, each item can be assigned to a specific factor in full compliance with composition of traditional quadratic typology of brand value sources shown in Table 2. This applies to all representative types of products examined.

Based on the comparison of the results of rotated component matrices, it can be argued that the order, i.e., the importance of individual common factor dimensions (brand value sources) has not changed in neither case of representative product types. Imageries load to factor 1, benefits load to factor 2, attributes load to factor 3 and attitudes load to factor 4.

In a more detailed analysis, it is possible to observe a change in the order of importance of the component, but only in imageries. The variables that weigh the most in the individual factor dimensions are authoritative in the interpretation of the dimensions obtained. The differences in the perception of the importance of individual elements by consumers are shown in Table 8.

Table 8 Ranking of Main Elements
Rank	Passenger cars	Bank services	Cola drinks	Sportswear
1	Enthusiasm	Enthusiasm	Satisfaction	Satisfaction
2	Happiness	Happiness	Certainty	Certainty
3	Pleasure	Pleasure	Pleasure	Pleasure
4	Satisfaction	Satisfaction	Happiness	Happiness
5	Certainty	Certainty	Enthusiasm	Enthusiasm

The data show a parallel between the importance of the individual elements of imageries as the main brand value sources in the two product groups. The first group of products consists of passenger cars and bank services. For these products, enthusiasm and happiness have the greatest influence on consumers in the purchasing process. The second group is composed of cola drinks and sportswear. Satisfaction and Certainty are the most influential elements of consumer shopping behavior in this group.

It has been proven the statement of Labrecque (2020) about customer's behavior as an imperfect individual, which in addition to rational impulses, is also controlled by emotions and other psychological variables. The goal of sensory marketing has been verified to enhance the customer experience and evoke positive emotions and associations with the brand. Emotions and other psychological factors (e.g. attitudes) are then an essential element of most purchasing decisions, and serve as mediating variables that determine how the consumer responds to stimulation (specifically marketing communication). The influence of these factors is dealt with, among others, by the concepts of Mehrabian and Russell or the model of Howard and Sheth (Bastiaansen, et al., n.d.; Jimenez-Marin, et al., 2019). However, the type of product that the customer decides to purchase and the extent to which the customer is involved in this purchasing decision also plays a role in the purchase. Thus, we have developed the theory of Kampf et al., (2017) who state that emotions significantly affect the way consumers perceive across the product categories without identifying individual product categories and their emotional background. Similarly, the concept of Soleimani et al., (2021) raises its importance on the basis of our own research. Following the research of Narayan & Singh, (2019); Jang & Lee, (2019); Marin Duenas & Gomez Carmona, (2021) it has been clearly identified the status of sensory vs. emotional marketing activities in brand communication campaigns based on the character of branded product. Thus, the unification of theory and practice of sensory and emotional branding has been denied and the platform for further research of individual functional stimuli based on sensory resp. emotional marketing activities across product categorization has been created (Hong, et al., n.d; Danilwan, et al., 2020; Kohli, et al., 2021; Yung, et al., 2021).

Conclusion

The aim of the paper was to identify the importance of sensory and emotional marketing in the process of brand value building and management. Basically, it has been presumed, that when traditional typology of buying behavior is taken into account, it shouldn´t be applied uniform approach to the issue of sensory resp. emotional marketing involvement into the theory and practice of brand management. To fulfill the aim of the research, factor analysis has been chosen as a basic pillar of statistical evaluation of primary data obtained via own questionnaire research provided on the statistically relevant sample of Slovak consumers older than 15 years. This research has been realized electronically in the first quarter of year 2021. It has been found out that sensory marketing would be appropriate for products with low involvement of consumers (variety seeking behavior and habitual buying behavior) while emotional marketing would be appropriate for products with high involvement of consumers (complex buying behavior and dissonance-reducing buying behavior). The first group of products consists of passenger cars and bank services. For these products, enthusiasm and happiness have the greatest influence on consumers in the purchasing process. The second group is composed of cola drinks and sportswear. Satisfaction and certainty are the most influential elements of consumer shopping behavior in this group.

Acknowledgement

This research was funded by project VEGA 1/0032/21: Marketing engineering as a progressive platform for optimizing managerial decision-making processes in the context of the current challenges of marketing management.

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