FUNDAÇÃO GETULIO VARGAS
ESCOLA BRASILEIRA DE ADMINISTRAÇÃO PÚBLICA E DE EMPRESAS MESTRADO EXECUTIVO EM GESTÃO EMPRESARIAL
THE IMPACT OF ENVIRONMENTAL CUES ON CUSTOMERS’
QUALITY PERCEPTION AND WILLINGNESS TO PAY AND THE
MODERATING ROLE OF CONSUMER MOOD AND MOTIVES
SILVIA MARCOMINI
Rio de Janeiro – 2016DISSERTAÇÃO APRESENTADA À ESCOLA BRASILEIRA DE ADMINISTRAÇÃO PÚBLICA E DE EMPRESAS PARA OBTENÇÃO DO GRAU DE MESTRE
Ficha catalográfica elaborada pela Biblioteca Mario Henrique Simonsen/FGV
Marcomini, Silvia
The impact of environmental cues on customers' quality perception and willingness to pay and, and the moderating role of consumer mood and motives / Silvia Marcomini. – 2016.
71 f.
Dissertação (mestrado) - Escola Brasileira de Administração Pública e de Empresas, Centro de Formação Acadêmica e Pesquisa.
Orientador: Eduardo Bittencourt Andrade. Inclui bibliografia.
1. Comportamento do consumidor. 2. Marketing.I. Andrade, Eduardo
Bittencourt. II. Escola Brasileira de Administração Pública e de Empresas. Centro de Formação Acadêmica e Pesquisa. III. Título.
CDD – 658.834
SILVIA MARCOMINI
THE IMPACT OF ENVIRONMENTAL CUES ON CUSTOMERS’ QUALITY PERCEPTION AND WILLINGNESS TO PAY AND THE MODERATING ROLE OF
CONSUMER MOOD AND MOTIVES
Master’s thesis presented to Corporate International Master’s Program, Escola
Brasileira de Administração Pública, Fundação Getulio Vargas, as a requirement for obtaining the title of Master in Business Management.
EDUARDO BITTENCOURT ANDRADE
Rio de Janeiro 2016
INDEX
1. Introduction... 1
2. Bibliographic Review……….. 3
2.1 Design cues………. 4
2.2 Ambience cues – scent……… 5
2.3 Human variables……… 6
2.4 The effects of mood on behavior………... 7
2.5 Shopping motivation………... 9 3. Problem to be discussed... 11 3.1 Research objectives……… 11 3.2 Research hypothesis……… 12 4. Research method………... 16 5. Analysis results ……….. 19 6. Discussion ………... 26 7. Implications ……….... 31
8. Limitations and future developments ……….. 32
9. Appendix………. 33
9.1 Appendix A………. 33
9.2 Appendix B……….. 39
TABLE OF FIGURES Figure 1……….. 15 Figure 2……….. 19 Figure 3……….. 20 Figure 4……….. 21 Figure 5……….. 22 Figure 6……….. 22 Figure 7……….. 24 Figure 8……….. 25
Abstract
The literature shows that shopping environment has an impact on various consumer behaviors, and that an elegant environment is associated with higher customers’ quality perception and willingness to pay. I investigated and found that this is true only when consumers are in a positive mood. When they are in a negative mood, consumers infer higher quality from a discount-looking shop.
A between-design experimental survey has been conducted to analyze the impact of shopping environment, mood and shopping motivation on customers’ perception of quality and willingness to pay. Two mood conditions (positive/negative) have been created and induced to respondents at the beginning of the survey, along with two shopping environment conditions (upscale-looking/discount-looking) based on design, scent and sales personnel factors.
Results show that shopping environment does not impact significantly the dependent variables but it interacts significantly with mood to determine quality perception; shopping motivation impacts significantly both quality perception and willingness to pay.
Keywords: consumer behavior, marketing, environmental cues, consumer moods, shopping motivation, quality perception, willingness to pay, store environment.
Acknowledgements
I would like to thank my thesis advisor Prof. Eduardo B. Andrade and PhD Candidate Lucia Salmonson Guimarães Barros of EBAPE-FGV for the guidance throughout the development of the research project, and Catolica Business School and FGV – EBAPE for the high quality teaching provided during the course of this Master.
I also would like to express sincere gratitude to my parents for the ongoing supports during these years of study and during the process of writing this thesis.
1. INTRODUCTION
The use of atmospherics in stores has been examined largely over the years, with a literature stream dating back to the beginning of the 1960´s (Turley et al., 2000).
If once a store was required and expected to be simply clean and reasonably straightforward to navigate in order for customers to find products immediately, today a variety of atmospherics are often being employed, and they are recognized to have an impact on consumer’s perceptions, emotions and consequently behaviors, such as time spent in the store, amount of money spent, perception of store image (Yuksel, 2005, Spangenberg et al., 2006; Chebat et al. 2003; Spangenberg et al., 1996).
The term atmospherics indicates the effort to design buying environments that elicit certain emotional effects in the buyer to enhance her purchase intentions (Kotler, 1974).
Such atmospheric cues vary from the use of music and scent to the design layout and social interactions with sales personnel, and are fundamentally different from cognitive elements such as location, advertising, price, products quality that have been traditionally manipulated to influence purchase decision making (Kotler, 1974).
The effects of such cues in physical retail environments vary: Babin et al. (2004) found that if customers deem a shopping environment as “appropriate”, their perception of product quality will raise, uplift their mood and increase the chances of purchases.
An upscale environment with pleasurable facility aesthetics, ambience and sales personnel leads to increased quality perception (Ryu et al., 2007), Obermiller and Bitner (1982) observed that customers viewing retail products in an emotionally pleasant environment evaluated them more positively than those viewing them in an emotionally non-pleasant environment, Baker et al. (2002) found that cues such as design, ambience and employees impact positively customers’ quality perception and behaviors.
Whereas it is clear that favorable atmospherics tend to be positively correlated to more positive perceptions and behavioral intentions, it is not clear whether this influence is equally powerful among all consumers or it has any boundary condition determined by variables that offset or enhance such influence.
The present study contributes to the literature by firstly assessing the effect of store environmental cues – manipulated to construct either an upscale or a discount shopping environment – on two specific variables: quality perception and willingness to pay, and especially by investigating mood and shopping motivation as changing the effect of the
environment on these dependent variables.
It is shown that the effect suggested by the literature does not hold for consumers in negative mood which react to the dependent variables in a way opposite to what expected, and shopping motivation is revealed to be a good predictor of quality perception.
2. BIBLIOGRAPHIC REVIEW
Two well established theoretical frameworks, rooted in environmental psychology, paved the way for the consecutive literature on environmental cues in shopping environments. The first model claims that the relationship with the environment is described through the SOR (Stimulus-Organism-Response) paradigm: a stimulus coming from the environment elicits an internal evaluation that is followed by a behavioral response to that stimulus (Mehrabian and Russell, 1974).
Individuals can react with two opposite behaviors, either approach (desire to stay longer, research, come back to the environment) or avoidance (desire to leave, not explore, not come back to the environment, boredom), and such behaviors are mediated by three basic emotions that are Pleasure (feeling satisfied), Arousal (feeling stimulated) or Dominance (feeling in control of the situation) and that compose the so called PAD model (Donovan and Rossiter, 1982 and Mehrabian and Russell, 1974).
Research studies have manipulated a large number of atmospheric variables – mostly taken individually, but also applied jointly - and tested the effects on consumers in terms of various attitudes and behaviors, such as purchase intentions, sales, impulse purchasing, store image, emotional states (Mattila and Wirtz, 2001; Fiore et al., 2000; Kahn and Wansink, 2004; Baker et al., 2002; Hausman et al., 2009; Grewal et al., 2003; Babin et al., 2003; Babin et al., 2004; Jang and Namkung, 2008; Mattila and Wirtz, 2008; Petr, 2006; Chang et al., 2011; Babin and Attaway, 2000; Morrison et al., 2009; Madzharov et al., 2015).
Environmental stimuli have been categorized into four main groups (Berman and Evans, 1995): external variables (e.g. surrounding area), general interior variables (e.g. scents), layout and design variables (e.g. furniture), point of purchase and decoration variables (e.g. price displays). One more category has been added by Turley and Milliman (2000), human variables (e.g. employee characteristics and uniforms). The relational flow between atmospherics and customers goes as follows: the physical environment interacts with individual customer characteristics to provoke a response, and also with employees, which in turn interact with customers, with the two groups influencing one another (Donovan and Rossiter, 1982; Turley et al., 2000).
Because emotionality varies from individual to individual, the environment’s influence on consumer emotions and consequently behaviors can be varied, with different customers exposed to the same variable but reacting differently (Donovan and Rossiter, 1982).
The present study will manipulate two general interior variables in an offline retail environment, design and scent, and one human variable, employee’s appearance and friendliness.
A brief literature review for each of these elements is presented below.
2.1 Design factors
Design factors have been investigated in several studies, with various findings, outlined below. The store environment has an informational role, conveying hints to customers about products and service quality (Gardner and Siomkos 1985, Olson 1977, Zeithaml 1988). Items in the physical environment can be seen as symbols that transmit implicit or explicit messages about the place to its users (Becker, 1977). Everything – floors, materials used, objects - helps consumers create a general aesthetic impression and transmits more or less explicit cues about the meaning of the place (Bitner, 1992)
Pictures of a store interior were second only to brand name in being the most heavily recalled of many cues that customers could pick to judge merchandise quality (Mazursky and Jacoby, 1986). More recently, Chebat et al. (2003) found that the mall perception in their studies strongly influences product quality perception, as if the mall was a “global packaging” for the products sold.
While Baker (1984) did not find a significant influence of store design on merchandise quality perception, with customers not displaying relevant differences on quality perception in upscale-looking stores versus simple-upscale-looking environments; Garden and Siomkos (1985) had different findings. A perfume was assessed more favorably when it was displayed in an environment with a prestige image, characterized by soft lighting, mood music, nicely dressed salespeople than when it was sold in an environmental with a discount image, characterized by no music, harsh lighting, poorly dressed salespeople.
Moreover, Obermiller and Bitner (1982) noticed that the participants of their study who viewed retail products in emotionally pleasant environments evaluated them more positively than those viewing them in an emotionally non-pleasant environment. Another significant example is the color used within a store, which was found to have an impact on customer’s idea of store image and the merchandise it carried (Bellizzi, Crowley and Hastey, 1983). More recently, Van Rompey et al. (2010) found that store color and store layout operate quite independently from each other and rather they depend on consumers’ shopping motivation. Task-oriented shoppers do not display significant differences in dealing with a red-colored rather than a blue-colored store environment, but are significantly impacted in their behavioral intentions by a more spacious store layout. Opposite results were found for recreational shoppers. A good layout
encourages longer in-store exploration (Mohan et al., 2012) and leads to higher perceived variety (Kahn B. et al., 2004), and a store windows’ display has a strong impact on consumers’ clothing impulse buying behavior (Karbasivar et al., 2011). Baker et al. (2002) proved how as customers' perceptions of store design elements become more positive, customers will perceive the mental stress associated with the shopping activity to be lower, and service quality to be higher.
Overall store image is significantly tied to perceived product quality (the higher the store image, the higher the perceived quality) and willingness to buy (Champion et al., 2010).
2.2 Ambience cues - scent
An ambient scent is “a scent that is not emanating from a particular object but is present in the environment” (Spangenberg et al., 1996). The olfactory system is connected to anatomic components fundamentally involved in emotions and memory, the amygdala and hippocampus (Mouly and Sullivan, 2010), and it was found that about 75% of human emotions are subject to the influence of smell (Lindstrom, 2005).
Spangenberg et al. (1996), who investigated how ambient scent influenced store and product evaluations, found no main or interactive effects regarding scent on mood. Chebat and Michon (2003), on the other hand, found that ambient scent contributes to the building of a favorable perception of the mall environment, and indirectly of product quality, which in turn strongly affects sales. In a later study, Spangenberg et al. (2005) found how scent enhanced product evaluations in a retail store when combined with other congruent cues (specifically, music) and the seasonal time (Christmas).
Knasko (1989) found out that ambient aroma led consumers to spend more time at a jewelry counter.
A study on restaurant customers found that lavender smell, considered relaxing, had a positive effect on consumer behavior, with clients spending more time and money at the restaurant. On the other hand, a lemon scent, considered stimulating, led to no significant effect on consumers (Guéguen et al., 2006).
Doucé et al. (2011) reinforced the idea of an impact of scent on consumers through their findings: the presence of a pleasant ambient scent in a fashion store impacted pleasure, evaluation of the store environment, evaluation of the products and intention to revisit the store. Specifically, individuals with higher affect intensity were more sensitive to the presence of a scent in the shopping environment, and were more strongly impacted by it.
Fiore et al. (2000) found also that adding a pleasant and appropriate scent to product display results in greater levels of purchase intentions and willingness to pay a higher price for the product. Customers’ evaluation of store environment was found to be more positive in the presence of an ambient scent rather than in the no-scent condition, and similarly mood was positively impacted (Bambauer-Sachse, 2012)..
2.3 Human variables
Salespeople can be an effective tool for retailers to create a positive relational bond with customers, and the quality of such bond has a significant weight in determining the probability of continuing interchange in the future (Crosby et al., 1990).
In terms of physical characteristics, sales personnel’s appearance was found to influence consumers’ emotions. Attributes such as professional appearance, friendly facial expression, and appealing overall appearance were found to generate positive emotions in customers. On the other hand, careless appearance, a messy hairstyle, or an unemotional facial expression generate negative emotions. Consistency between the salespersons’ appearance and the store image is an important influence for customers in developing their own store image (J.E. Kim et al., 2009). A study conducted by Yan et al. (2011) in a lab setting, shows how the formality of salespeople’s clothing was used by consumers to infer the service quality level they expected to be granted, and proportionally impacted the customers’ store image (the greater the formality, the higher the store image).
Berman and Evans (1989) suggested that a prestige-image store would have helpful, collaborative salespersons, while a discount image-store would have unhelpful salespersons. Gardner and Siomkos (1985) found that salespeople´s dress influenced quality evaluations of a perfume, and Baker (1994) confirmed that the prestige of a social environment raise subjects’ inferences of product quality.
A study conducted by Baker and Parasuraman (1994) examined the effects of sales personnel wearing aprons and greeting customers on the perceptions of service quality in a retail store. It was found that the store with the prestige-image social elements was perceived as granting higher service quality than did the store with the discount-image social elements (no use aprons, no greetings of customers).
In terms of interaction with customers, Jacob et al. (2011) found that salespeople mimicking the verbal and non-verbal behavior of clients raised their buying behavior and also the overall judgment of the store.
A study by Jieun (2014) in the context of a luxury fashion retail found how a relationship of friendship with the salesperson, and the degree to which customers perceive the salesperson to be fun and easygoing to interact with, is important for customers to build loyalty to the salesperson, which in turn positively influences store loyalty. Ahearne et al. (2007) found that sales personnel showing empathy - defined as a strong desire to help and an effort to understand and collaborate with customers - affects share of customer (i.e. measure of the “share of wallet” of a customer) and, in an upscale retail context customer's loyalty to the salesperson is significantly related to share of purchases, word of mouth and competitive advantage (Reynolds et al., 2000) .Reinforcing these findings, a qualitative study focusing on young consumers (Yip et al. 2012) found how salesforce characteristics were the second main reason of distinction between average-rated shops and favorite shops, with characteristics such as friendliness, professional suggestions, responsiveness and extra effort being particularly appreciated. After examining these three cues, the literature seems to suggest that favorable design, scent and sales personnel cues tend to positively impact customers, in terms of perceptions, approach behaviors, and also shopping behaviors.
2.4 The effects of mood and environment on behavior
Mood has been defined as a “pervasive affective state” (Isen, 1984), a generalized, diffuse and transitory condition changing with circumstances (Swinyard, 1993).
Knowledge about how shopping behavior of potential customers can be impacted by their emotional states can be of great importance: as the current focus is creating more lasting bonds with customers, the role of store environments and what can stimulate or maintain pleasant emotional reactions becomes strategic (Sherman et al., 1997).
Environmental psychology proposed that three dimensions – pleasure (joy), arousal (stimulation) and dominance (perceived control) – describe emotional states (Mehrabian and Russell, 1974), eliciting different reactions in consumers. A variety of such responses have been observed in various studies relating moods with environmental cues, outlined below.
Donovan and Rossiter in a subsequent research (1994), found that pleasure experienced within the store is positively correlated with unplanned time spent in the store and unplanned purchasing, arousal intensifies pleasure and causes extra unplanned time and purchasing in the case of pleasant environments, and pleasure and arousal also contributes to extra time spent in the store and unplanned spending independently of perceived merchandise quality, variety, and value for money.
Pleasure experienced in-store was found to have a positive influence on money spent and liking the store, and arousal was found to have a positive impact on money spent in the store, time spent in the store, and the number of products acquired in the store (Sherman et al., 1997). Research has shown how positive mood makes it easier for consumers to take decisions (Babin et al., 1992) and builds a positive store image (Darden and Babin, 1994).
Babin and Darden (1996), found that negative mood among shoppers, although not affecting spending, reduces patron satisfaction much more than a positive mood increases it: negative consumer emotions were observed to have a stronger impact than positive emotions.
The research on the effects of mood on behaviors has been extended also to the online environment: in the context of an online retailer, the pleasure elicited in customers by a website cues increases positive attitude towards the website and purchase intent (Jung-Hwan et al., 2009) and positive moods lead to positive online clothing browsing, less perceived risk, and higher purchase intention (Park et al., 2005).
There are mechanisms through which mood can alter the perception of external stimuli. Mood congruency theory claims that mood states seem to bias evaluations and judgments in mood congruent directions; a good mood would be the equivalent of looking at one’s world through rose-colored glasses, while a bad mood would impact evaluations in an opposite way (Clark and lsen 1982).
A study by Babin and Attaway (2000) confirms this theory by proving how ambient atmospheric conditions contributing to a positive affect enhance the perception of shopping value (i.e. overall assessment of worth of the shopping activity) and help build customer share. In contrast, ambient atmospheric conditions contributing to negative affect reduce perceived shopping value and customer share.
Additionally, people in good moods tend to sustain their mood through mood-protection mechanisms: disruption of good moods is determined by cognitive elaboration, that requires effort, so individual in positive moods might avoid or lower cognitive elaboration in order to protect their positive emotional state (Isen and Levin 1972; Swinyard, 1993). In fact, control theory states that people have a desired subjective state to which they constantly compare the current emotions, and when differences are detected, strategies are used to reduce them: the underlying assumption is that people are bound to feel more pleasant than unpleasant affect, to establish and sustain positive emotional states (Larsen, 2000). This was also claimed by Zillmann in a prior study on mood management through entertainment cues (1988): individuals arrange environmental stimuli to minimize dissaatisfaction and maximize pleasurable emotions. In particular, they accidentally make either arrangements during negative states that
lower their negative affects by moving towards a more pleasurable condition, or arrangements during positive affects that extend the positive experience: such arrangements are later retrieved in the memory, which facilitates their repetition in similar situations and this process makes individuals able to manage and regulate their moods.
These two behavioral streams – mood congruent evaluation and mood regulation – can also interact with each other when there is either a mood-lifting or mood-threatening cue linked to an anticipated behavior: a U shape pattern occurs in the lifting condition due to mood-congruent evaluation in the positive mood condition, and mood regulation in the negative mood condition. An inverted U shape pattern occurs with a mood-threatening cue due to mood regulation in the positive mood condition and mood-congruent evaluation in the negative mood condition (Andrade, 2005).
No known study has manipulated both mood and environmental cues in a shopping environment, therefore it is interesting to note whether and how mood will interact with external atmospheric stimuli and how quality perception and willingness to pay will be impacted.
2.5 Shopping motivation
Tauber (1972) claimed how shopping behavior is caused by a variety of underlying psychosocial needs beyond those related to the products being acquired, the shopping motivation is therefore provided by the utility of the product itself but also by the satisfaction arising from shopping activities.
Among many motivation theories, two main shopping motivations have been delineated: shopping for utilitarian value, aiming at a utilitarian outcome as a consequence of a rational, conscious pursuit of a goal, and shopping for a hedonic value, aiming at an outcome related to spontaneous hedonic responses, not necessarily directed toward satisfying a functional, physical or economic need (Babin et al., 1994). All consumers but especially lower-income consumers are found to appreciate increased hedonic cues in the shopping environment (Allard et al., 2009).
Hedonism and utilitarianism have been studied on a number of variables.
Hedonic shoppers interested in keeping up with trends tend to be innovative, hedonic shoppers purchasing to relieve stress, uplift a negative mood or for stimulation are found to be subject to time distortion during the shopping activity, and hedonic shoppers on a whole are sensitive to aesthetic cues in the retail environment (Arnold et al., 2003). Hedonic aspects of shopping seem
to influence satisfaction with the retailer, word of mouth, and repatronage intentions more strongly than utilitarian motivation (Jones et al., 2006).
Positive mood appears to interact with shopping motivation: it is positively correlated to both utilitarian value (it increases task efficiency) and hedonic value, and negative mood distracts from utilitarian tasks and is negatively correlated also with hedonic value (Babin et al., 2000). In the context of an online environment, both hedonic and utilitarian value were linked to a preference for online retailers, however utilitarian value more strongly pushes customers to turn to e-commerce (Overby et al, 2011). Another study shows similar findings: highly hedonic consumers tend to avoid online shopping, they associate it with higher risks and lesser benefits, as they cannot touch the merchandise or have a personal interaction with sales personnel (Sarkar, 2011). Moreover, whereas utilitarian value is significant for both frequent and infrequent shoppers, hedonic was found to be significantly relevant for infrequent shoppers only (Overby et al., 2006). Utilitarian shoppers would react more strongly to the usefulness of a website as a predictor of attitude towards the website itself, whereas hedonic shoppers would value enjoyment as the main predictor (Childers et al., 2002).
Other relevant factors influencing utilitarian shoppers towards e-commerce are convenience, cost saving, information availability, whereas the factors influencing hedonic shoppers are adventure, and authority coming from a sense of control over technology, with utilitarian motivation being more important than hedonic motivation in terms of influencing search or purchase intention (To et al., 2007).
Whether in brick and mortar stores or online, it is clear that the very same environment can be perceived very differently by hedonic shoppers and utilitarian ones, as their perceptions are guided by opposite goals and lead to different behaviors and evaluations.
3. PROBLEM TO BE DISCUSSED
While there are a significant number of studies analyzing the individual effect of environmental cues on consumer behaviors, there is a more limited literature analyzing the joint effects of various atmospheric elements on customers (Baker et al., 2002, Michon et al., 2005).
In fact, although individuals perceive discrete stimuli, it is the total configuration of stimuli that determines their responses to the environment (Holahan, 1982).
For example, Mattila and Wirtz (2001) found out that a total configuration of cues influence consumer responses - rather than environmental stimuli in isolation - in particular, when the arousal level of ambient scent and music background match, consumers react more positively to the shopping experience.
The results of a study by Morrison et al. (2009) revealed an unexpected interaction between two environmental cues - aroma presence and loud music - in a fashion retail environment, resulting in a significantly higher level of reported pleasure, which in turn influenced time and money spent.
Babin et al. (2004) found that many congruent environmental have positive effects on customers’ approach behaviors, arguing that a single element that can be per se positive can spoil the positive effect the context can exert on consumers if it is not congruent with other cues present in the environment.
The present study manipulates two shop conditions – prestige-image store and discount-image store – created through the combination of three atmospheric cues, design, scent and sale personnel’s appearance.
It contributes to the atmospheric cues research in the following ways:
- After measuring the impact of environmental condition on quality perception and willingness to pay, interaction effects between environment, mood and shopping motivation are investigated.
Whereas the literature predicts a general effect, it will be explored whether it is actually valid across all consumers or if there are boundary conditions, and what determines them.
3.1 Research Objectives
The aim of the present study is to understand how the influence of environmental cues taken holistically modifies customers’ judgments of a product, whether this occurs proportionally (more comfortable shopping environment leads to more favorable evaluations) or non-proportionally, and if it follows the same pattern for both dependent variables (quality
perception and willingness to pay). The objective is also to go a step forward and investigate whether emotional states interfere with the shopping environment perception and the two dependent variables, and whether shopping motivation (utilitarian or hedonic) plays a role in the measure of the two dependent variables.
The shopping environment selected is the interior of a fashion retail store. As Kotler (1974) pointed out, atmosphere influences are not equally important to all sellers, and they are a significant marketing tool mainly when the seller has control over store design: it is highly important for retailers and much less relevant for manufacturers, for instance.
Moreover, atmospherics is a more relevant marketing tool in industries where product and/or price differences are small (Kotler, 1974). The mass apparel industry exemplifies these characteristics, with a tight density, very high competitivity and negligible switching costs for customers (Datamonitor, 2010). In such industries, differentiating through price and product is not sufficient for a sustainable competitive advantage, therefore sellers have to use other discrimination elements, such as atmospherics.
3.2 Research Hypothesis
The first hypothesis examines the relationship between the shopping environment manipulations and the dependent variables.
Grewal and Baker (1994) found that consumers inferred higher merchandise quality in a prestige-image card and gift store rather than in a discount-image one; Gardner and Siomkos (1985) reported that a perfume was rated more highly when placed in a prestige-looking environment as opposed to a discount-looking one, and Richardson et al. (1996) found that store aesthetics can enhance customer perception of the quality of the products sold.
Zhao and Kling (2001) suggest willingness-to-pay should increase when consumers are more sure about a good’s value, and perceived product quality was found to be a strong determinant of perceived product value (Snoj et al., 2004).
Moreover, Baker (2002) found that a high image store design leads to correspondingly higher expected prices, Grewal and Baker’s (1994) report that more positive store environment perceptions increase the acceptability of a higher price, and Sethuraman and Cole’s (1999) observed that perceived product quality is the most important variable influencing customers’ willingness to pay price premiums. Taking into account these premises, the first hypothesis expands the assumptions in the following way:
H1a: in the context of a fashion retailer, matching environmental stimuli contributing to a prestige-looking store environment (distinctive design, delicate scent, presence of an elegantly dressed shop assistant) will enhance customers’ perception of quality.
H1b: in the context of a fashion retailer, matching environmental stimuli contributing to a prestige-looking store environment (distinctive design, delicate scent, presence of an elegantly dressed shop assistant) will enhance customers’ willingness to pay.
The second hypothesis attempts to predict the relationship between mood and shopping environment and its effect on the dependent variables.
According to the “feelings-as-information” theory, moods have an informative function when individuals make evaluations (Forgas, 1995; Bless et al., 1996, Schwarz, 1990), that is, positive mood communicates that the circumstances are favorable and that little vigilance and monitoring are necessary, whereas bad mood indicates that the circumstances present a problem or a possible danger. Accordingly, negative affective states encourage the use o f detail-oriented, analytical processing strategies, whereas positive affective states encourage the use of simpler heuristic strategies (Schwarz, 1990). This is supported by other studies finding that individuals in positive mood tend to rely more strongly on general knowledge structures (that is, a form of simplified processing) when making a judgment with respect to individuals in a sad mood (Bless et al., 1996), they are more subject to halo effects when judging a person (Sinclair, 1988), and when exposed to persuasion techniques they don’t elaborate and analyze the arguments as much as sad individuals (Bless et al., 1990).
Based on these findings, the second Hypothesis predicts the following:
H2a: Respondents in a positive mood will display less difference between the quality perception measured in the upscale and discount store environment, whereas respondents in a negative mood will display greater difference between the quality perception measured in the two shopping manipulations, reflecting the tendency of engaging in more detailed judging processes when in a sad mood.
H2b: Respondents in a positive mood will display less difference between willingness to pay measured in the upscale and discount store environment, whereas respondents in a negative mood will display greater difference between the
willingness to pay measured in the two shopping manipulations, reflecting the tendency of engaging in more detailed judging processes when in a sad mood.
Regarding the impact of shopping motives on the dependent variables, hedonic shoppers on a whole are sensitive to aesthetic cues in the retail environment (Arnold et al., 2003). For shoppers who value the environmental quality of a shopping encounter, it is more likely that the store atmosphere will lead to the affective states it is designed to produce. On the other hand, for those who do not have great sensitivity to their surroundings, the effect of the environmental cues on their emotional reactions would be less significant (Eroglu et al., 2003).
Better designed store environments were found to move customers towards a more relaxed mood and increase the perceived product quality (Baker et al., 2002), and product quality is one of the primarily influencers of consumer spending (Chebat et al, 2003).
Therefore, it is hypothesized that:
H3a: Hedonic shoppers will display a higher gap in perceived quality between the upscale-looking environment condition and the discount-looking environment condition, with respect to non-hedonic shoppers - as they have an enhanced sensitivity for the environmental cues they are being subject to and respond accordingly.
H3b: Hedonic shoppers will display a higher gap in willingness to pay between the upscale-looking environment condition and the discount-looking environment condition, with respect to non-hedonic shoppers - as they have an enhanced sensitivity for the environmental cues they are being subject to and respond accordingly.
Figure 1: A conceptual model of the impact of environment cues on customers' perception of quality, willingness to pay and the moderating role of mood and shopping motivation during the shopping
4. RESEARCH METHOD
It will be tested whether the perceived quality and willingness to pay for a product vary in response to environmental cues, measuring the perceived quality and willingness to pay for the same clothing product in a discount-looking environment versus in a sophisticated-looking environment in which environmental stimuli related to design, ambience (scent) and personnel are present.
Specifically, it will be tested through a between-subject design experimental survey whether the dependent variables interact with customers’ moods – which will be manipulated through a video at the very beginning of the test, either positively or negatively - and how the induced moods enhance, offset or have no impact on the reactions to environmental cues.
The use of mood-induction videos in research has proven to be quite successful due to the general appeal of these stimuli (a low participation motivation is required), their easy-to-determine valence, and a higher intensity compared to written or audio stimuli (Cohen et al., 2006).
A summary of the variables is presented below:
Independent Variables:
1) Shopping environment. Two treatments:
- Sophisticated store environment with favorable atmospheric cues: distinctive design, delicate scent, presence of an elegantly dressed shop assistant proactively interacting with customers; - Plain store environment with less favorable atmospheric cues: neat but anonymous design, no scent, presence of a plain dressed shop assistant minimally interacting with customers.
The treatments are presented in the form of a detailed and neutral verbal description at the beginning of the survey.
2) Customers’ mood. Two treatments:
- Negative mood, induced by a sad video presented at the beginning of the survey; - Positive mood, induced by a positive video presented at the beginning of the survey. The four different treatments will be randomly assigned to survey respondents.
3) Shopping motivation. Respondents have been divided in two groups, hedonic and non-hedonic, based on the scores obtained in Q16_3 “Shopping is a relaxing experience to me: I want to feel nurtured and take the time to explore whatever I find appealing” with 1 = hedonic
respondents, i.e. respondents scoring >4 (median value) in Q16_3 and 2 = non-hedonic respondents, i.e. respondents scoring =<4 in Q16_3.
Dependent Variables:
- Quality perception and willingness to pay for a clothing product - either a male or female shirt that will be displayed to respondents through a picture.
The product is characterized by plain design, neutral color (white or light blue) and no particular differentiating factor, in order to control for any possible association and stimulus in the consumers’ mind referring to inherent distinctive product characteristics, as this is not the scope of the study.
Two experimental surveys have been elaborated.
The first survey – whose answers where gathered before spreading the second - is a manipulation check to assess whether the two videos effectively elicit positive and negative emotional states. The videos have been selected with the following criteria: possessing a significant emotional impact on the watchers and having a reasonable length, sufficient to create an emotional state but not excessive to divert the respondents’ attention or bore the participants. It was preferred to not insert the manipulation check in the second and main survey to not alert respondents to the fact that their mood was being tested, which could have inhibited their responses. The diffusion of the first survey was done through different channels with respect to the second survey, that is, the respondents of the first questionnaire did not participate in the second. Specifically, to make sure no contamination was present, the first survey was spread indirectly to unknown friends of friends, whereas the second questionnaire was spread to personal acquaintances, friends and relatives.
The videos are two commercials of length between 1 minute and a half and 2. The first video is an ad promoting the role of mothers and praising their dedication, perseverance and support amidst the difficulties, with specific reference to the winning athletes of the Rio 2016 Olympic Games.
The second video is a British ad aimed at creating awareness over a severely invalidating neurologic condition, showing crudely its sudden symptoms and effects on regular individuals. The videos were randomly assigned to respondents (between subject design), which were later asked to rate on a 1-7 Likert scale a few statements on their feelings.
The structure of the second survey is outlined below:
- Display of the manipulations, randomly assigned to each person: first, display of the video, then description of the environmental context along with a matching picture of a store interior
environment,
- Collection of Dependent Variables: display of clothing item and questions related to its perceived quality and willingness to pay for it,
- Other variables: utilitarian and hedonic shopping motivation, - Demographics.
Please refer to Appendix A for the full bodies of both questionnaires.
The first questionnaire received 108 answers, all complete, with a dropout rate of 0%.
Origin of respondents vary, with different locations worldwide. The second questionnaire received 178 total answer, 120 of which complete and 58 incomplete. Given that response was forced on every question, the dropout rate is 32.5%, much higher than the first questionnaire probably due to the second being significantly longer.
69.34% of participants are women, 49.6% fall within 20-25 years old age range and 24.8% within the 52-62 years old range, the prevalent education level is Bachelor’s degree (58.5%) and the prevalent income is up to 800 euros/monthly (58.46%), reflecting the high percentage of young peers as respondents of the survey. Origin of respondents vary, with different locations worldwide.
Given that the environmental cues will be presented in the form of verbal description, I expect it to not impact the participants as much as a real life situation would: there will be no actual involvement of senses, just an imagination and recreation of the situation in their mind, induced by a detailed description in the beginning of the survey, to which they will be asked to pay particular attention. I therefore assume that a carefully analyzed detailed description – method used in several studies on environmental cues in store environments (Pinto et al., 1994; Ward et al., 1992; Edwards and Shackley, 1992; Bateson and Hui, 1987) - will still elicit some reactions in the participants, so that their answers during the survey can still be considered significant and coherent although in a virtual context.
5. ANALYSIS – RESULTS Manipulation check
To verify that the two mood-inducing videos were actually going to produce the intended affective states, a survey was created showing either video followed by a seven-item Likert scale asking respondents to agree with statements referring to either positive or negative emotions (please refer to Appendix A for further details). The variable “condition_video” was created with 1= negative mood-inducing video and 2= positive mood-inducing video.
A factor analysis was run with all the statements in order to merge the emotions and one factor has been extracted. Negative emotional states have been recoded and reversed to get a scale where high numbers indicate positive mood and low numbers indicate negative mood. Cronbach’s Alpha was calculated and shows that the scale is reliable (.975), so all indicators measure the same construct.
A new variable was created as the average of the three positive mood statements and the three reversed negative mood statements, and a T-test was performed between the variable and the video manipulation.
People who watched the positive video reported more positive emotions (M = 5.85, SD = 0.57) than those who watched the negative video (M = 1.97, SD = 0.37, t(87) = -37.56, p < .001)
Main survey
H1a: a T-test was performed.
A “Condition_shop” variable was created, with 1 = upscale looking shop and 2 = discount looking shop. No significant difference between the means of quality perception in the different shopping environment conditions was found (t(115) = .653, p = .515; M = 4.26, SD = 1.22 vs M = 4.10, SD = 1.37), therefore H1 is not supported.
H1b: a T-test was performed.
No significant difference between the means of the two dependent variables in the different shopping environment conditions was found (t(115) = .925, p = .357; M = 46.31, SD = 33.29 vs M = 40.75, SD = 31.75), therefore H1b is not supported.
H2a: a factorial ANOVA was performed.
There is a significant moderating effect of mood on perception of quality (F(3,113) = 3.215, MSE = 5.12, p = .026).
H2a is not supported: the video and shopping environment conditions interact significantly (F(1,113) = 8.05, MSE = 12.82, p = .005) but not in the way predicted by H2a. Instead, positive mood induction seem to enhance the perceived differences in quality perception in an upscale looking versus discount looking environment (M = 4.52, SD = .26 vs M = 3.69, SD = .22), with higher quality rating in the upscale-looking environment, whereas in the negative mood condition respondents rate the discount-looking environment as higher in quality (M = 4.59, SD = .24 vs 4.08. SD = .21).
Fig. 3: Means and SDs of quality perception of respondents when the interaction between mood and environment is added to the model.
H2b: a factorial ANOVA was performed.
Willingness to pay is not influenced by any significant interaction between mood and the shopping environment (F(1,113) = 1.513, MSE = 1602.16, p = .221), and the model is not significant (F(3,113) = .931, MSE = 985.17, p = .428.). H2b for willingness to pay is not supported.
Fig. 4: Means and SDs of willingness to pay for respondents when the interaction between mood and environment is added to the model.
The relationship between shopping motivation and the dependent variables has been explored firstly through One-way ANOVA between shopping motivation and quality perception and willingness to pay.
Creation of a “Condition_hedonic” variable, with 1 = hedonic respondents, i.e. respondents scoring >4 (median value) in Q16_3 “Shopping is a relaxing experience to me: I want to feel nurtured and take the time to explore whatever I find appealing” and 2 = non-hedonic
respondents, i.e. respondents scoring =<4 in Q16_3.
There is a significant difference in quality perception and willingness to pay between hedonic and non-hedonic shoppers (F(1,115) = 7.703, MSE = 12.256, p = .006; F(1,115) = 15.580,
MSE = 14625.519, p < .001). Hedonic shoppers display higher quality perception and higher willingness to pay (M = 4.57, SD = 1.25 vs M = 3.9, SD = 1.27 and M = 57.15, SD = 38.12 vs M = 34.34, SD = 24.41).
Fig. 5: Means and SDs of quality perception of respondents with different shopping motivations.
To test H3a, a Factorial ANOVA between condition_hedonic, condition_shop and quality perception has been performed.
No significant interaction has been found between the store condition and the shopping motivation (F(1,113) = 2.788, MSE = 4.391, p = .098).
The overall model is significant (F(3,113) = 3.646, MSE = 5.743, p = .015) shopping motivation again results significant in the model (F(1,113) = 7.681, MSE = 12100, p < .001) but the shopping environment condition is not (F(1,113) = .854, MSE = 1.346, p = .357) nor their interaction (F(1,113) = 2.788, MSE = 4.391, p = .098). This means that although shopping motivation influences quality perception – as proven also by the previous one-way ANOVA test, it does not interact with the shopping environment.
Hedonic shoppers score higher in quality perception in upscale-looking environments (M = 4.875, SD = .256 vs M = 3.824, SD = .215) and this happens also in the discount-looking condition (M = 4.26, SD = .26 vs M = 4.0, SD = .21) and, in fact, independently of the store environment.
H3a is not supported: the means of quality perception behave as predicted (M = 4.875-4.261 = 0.614 > M = 3.824 – 4.000 = -017) but not because of any interaction between the store environment and shopping motivation. It is interesting to note how non-hedonic shoppers have a slightly lower quality perception in the upscale-looking store environment rather than in the discount-looking store environment (M = 3.824, SD = .21 vs M = 4.00, SD = .21).
A regression was also run, treating the independent variable as a continuous variable, and the result remains the same: when quality perception was predicted it was found that shopping motivation (β = .642, SD = .209, p = .03) was a significant predictor, whereas shopping environment (β = .161, SD = .544, p = .446) and the interaction between shopping environment and shopping motivation (β = -.405, SD = .128, p = .248) were not. The overall model fit is R2 = 0.116.
Fig.7 : Means and SDs of quality perception of respondents when shopping motive and environment interact.
To test H3b, a Factorial ANOVA between condition_hedonic, condition_shop and willingness to pay has been performed. No significant interaction has been found between the store condition and the shopping motivation (F(1,113) = .036, MSE = 33.995, p = .850).
The overall model is significant (F(3,113) = 5.410, MSE = 5132.15 p = .002); shopping motivation again results significant in the model (F(1,113) = 15.239, MSE = 14455.04, p < .001), but the shopping environment condition is not (F(1,113) = .813, MSE = 770.78, p = .369), nor their interaction (F(1,113) = .036, MS = 33.99, p = .850). This means that although shopping motivation influences willingness to pay – as proven also by the previous one-way ANOVA test, it does not interact with the shopping environment.
Hedonic shoppers score higher in willingness to pay in upscale-looking environments (M = 60.25, SD = 6.28 vs M = 36.47, SD = 5.28), and this happens also in the discount-looking condition (M = 53.91, SD = 6.42 vs M = 32.33, SD = 5.13) and, in fact, independently of the store environment.
H3b is not supported: the means of willingness to pay behave as predicted (60.250-53.913 = 6.337 > 36.471 – 32.333 = 4.138) but not because of any interaction between the store environment and shopping motivation.
A regression was also run, treating the independent variable as a continuous variable: when willingness to pay was predicted it was found that shopping motivation (β = .438, SD = 5.137, p = .128) was not a significant predictor, nor shopping environment (β = -.045, SD = 13.355, p
= .826) or the interaction between shopping environment and shopping motivation (β = -.074, SD = 3.137, p = .828). The overall model fit is R2 = 0.151.
This contrasts what was found in the previous Factorial ANOVA, as in this case not even shopping motivation alone is significant. The different results obtained could be due to the fact that Factorial ANOVA used a dummy variable, “condition_hedonic”, whereas the regression used the original variable, Q16_3. By creating “condition_hedonic”, answers might have been simplistically grouped together in either category even though they describe different underlying behaviors (e.g. a consumer rating 4 out of 7 his hedonic motivation fell in the same category as one rating 2).
Even though the contradiction did not arise in case of quality perception, and shopping motivation results only slightly insignificant in the regression predicting willingness to pay, it is more rigorous to adhere to the results of the regression. Therefore, willingness to pay is not impacted by the environment, nor by shopping motivation or their interaction.
Fig. 8: Means and SDs of willingness to pay of respondents when shopping motive and shop environment interact.
6. DISCUSSION
The present study investigated the relationships between mood, shopping environment and shopping motivation with two dependent variables, perception of quality and willingness to pay. Several results have been obtained.
- The store environment has no impact on quality perception and willingness to pay (H1). The same result for willingness to pay is repeated with the findings on H2b and H3b - that is, willingness to pay is not significantly impacted by any of the independent variables used. In an attempt to see whether a possible driver of willingness to pay could be income – given that most respondents reported a low income, coherent with the fact that most of them are students – a regression has been run (please see Appendix B for further details) and income is found to be significant (and ANOVA states higher means for higher-income respondents), however it accounts for only a small part of the variation in willingness to pay (20.4 %). The conclusion could be therefore that, other than income, there are other influencers of willingness to pay that are not explored in this study.
According to the literature, among determinants of willingness to pay are origin of product (Hustvedt and Bernard, 2008), product attributes framing (Howard and Salkeld, 2008), brand recognition and social responsibility attributes (Hustvedt et al., 2010), laundering requirements and fit (Brookshire and Norum, 2011), brand status (O’cass and Choy, 2008), and brand name (Krystallis and Chryssohoidis, 2005).
The result of quality perception is quite surprising.
One possible explanation is that the store verbal description did not actually elicited strong enough feelings and perceptions that could impact significantly the dependent variable. Moreover, time pressure could have played a role, as many respondents might have superficially and rapidly looked at the picture without paying much attention to move on quickly with the survey. This is in line with the findings of Xu (2007) on the relationship between time pressure and shopping behavior: when the consumer experiences time pressure while subject to the store cues, no significant relationship exists between the store environment, emotional states and shopping behaviors. As respondents were subject to an emotionally impacting video just before seeing the picture of the shop, and considering that the video allows for the use of more stimuli than a textual description, a comparison effect might also have taken place and respondents could have found the textual description blander relative to the stronger impacting video. Moreover, using a picture prevents respondents to actually experience product attributes such as texture, material, fit that are relevant to the overall evaluation of a fashion
item, and Zeithaml (1988) concludes that
intrinsic product cues are in general more important to consumers in evaluating quality because they have higher predictive value than extrinsic cues, that is, the link between product attribute and quality is clear and strong (i.e. silk is known to be of higher quality than a synthetic material).
A contribution has been made by exploring whether mood and shopping environment interact and how this impacts perception quality: positive mood is linked to a higher perception of quality in upscale looking environment, negative mood to a higher perception of quality in discount looking environment.
It is possible to explain the effect of positive mood in the upscale looking environment by considering that affect can have an indirect influence on judgments through its impact on the way specific pieces of product information are treated. For example, happy individuals may weigh favorable pieces of information more heavily than unfavorable pieces when making a judgment, whereas unhappy persons may give relatively more emphasis to unfavorable pieces of information than to favorable ones: this occurs when the evaluation has also an hedonic component, and not merely an utilitarian one based on product characteristics (Adaval, 2001). In our case, there is evidence of an hedonic dimension in the product evaluation as fashion apparel is considered one of the popular culture-versions of art, which is defined as an hedonic domain capable of creating unusually strong emotional involvement (Hirschman et al., 1982). We can therefore suspect that the respondents who saw the positive video tended to consider prevalently the positive attributes of the shirt displayed, whereas the respondents who saw the sad video tended to consider prevalently the negative attributes. This is coherent also with the Affect Infusion Model, which claims how mood has a different role in influencing judgments depending on a wide range of variables; in particular when the evaluation target is simple, not personally relevant, without motivational strings and the whole situation does not demand a high level of detail - all characteristics present in the survey evaluation - a heuristic process is used to form evaluations, whose result is mood-congruent (Forgas, 1995).
A possible way to explain how the negative mood results in unexpected lower quality evaluation of product in the prestige store might be a mismatch between store image and product: being subject to an elegant environment, respondents might have expected products sold there to be more sophisticated, original and upscale than the product they actually evaluated – and of which they probably tended to notice mostly the mood-congruent negative attributes. This mismatch would cause them to feel “deceived” and overall to be uncertain as to how to feel about the
product, which inhibits the overall quality rating. On the other hand, the discount-looking environment did not create high expectations and therefore they found the product more coherent with the perceived store image or even better than expected, hence the overall higher quality rating.
This is coherent with a study by Babin et al. (2004) that investigated the effect of congruency and appropriateness on customers: it found that customers prefer environments where cues are consistent and congruent, and rate the products in these stores as of higher quality.
The merchandise sold, although it is not an atmospheric element, can be still considered a cue from which customers expect a certain level of coherence with the overall store image. A similar finding was shown also by Wheatley et al. (1977): the carpeting from a low prestige store at a low price was judged higher in quality than the low priced carpeting from a high prestige store. The psychology behind the response to this mismatch is that congruent cues are more easily processed and thus preferred: divergent cues, on the other hand, force the customer to put in extra effort to reconcile them (Babin et al., 2004).
The predicted higher gap between dependent variables in the two shop conditions in respondents with negative mood (H2) did not receive support. On the contrary, the gap was considerably higher in respondents with induced positive mood (Ms = 4.592 and 3.688 vs 4.086 and 4.597). Rather than with the amount of processing, this seems to be consistent with the level of focus theory elaborated by Clore et al. (2001), stating that people in a positive affect tend to focus on global information as opposed to people in a negative affect which tend to have a local focus. This was confirmed in a study by Gaspar and Clore (2002) that focused specifically on processing of visual information, finding that happy respondents focused on the global picture (a forest) and sad ones to the local one (trees). Baumann and Kuhl (2005) extended the findings on the matter by arguing that positive affects extends cognitive flexibility – that is, people in good mood are able to focus also on local information, however when given a choice, processing of global information is the dominant mode over local focus.
In our case, the shop environment can be considered as global information and the specific product in the shop as local information. This would explain why people in positive mood displayed higher difference between the dependent variables: they tended to focus on the environmental cues – very different in the two scenarios - rather than the product and made evaluations accordingly. Individuals in negative mood, on the other hand, focused more on the product per se and evaluated it more consistently in the two scenarios.
In terms of mood and store environment effect on willingness to pay, the present study contributed by observing that there is no significant correlation between mood and store
environment that could impact customers’ willingness to pay.
This result could be linked to the fact that most respondents claimed a very low income of up to 800 euros disposable per month, consistent with the fact that most respondent are students on a restricted budget, and in fact a significant difference between the willingness to pay among low-budget and higher-budget respondents was found. Therefore, it is possible to conclude that one influence of willingness to pay is pragmatically related to what a consumer can actually spend.
This is coherent with a study by Li et al. (2012) focusing on luxury products, who found that for consumers who have no luxury fashion brand experience - consumers without high budgets - the perceived economic value of luxury fashion brands has a significant influence on their willingness to pay. In other words, when there is some sort of financial constraint, the evaluation of the maximum amount of money a customer is able to pay comes in the first place.
Moreover, Sevdalis (2006) argues that when consumers lack a salient reference point, as in the case (like the present one) in which they are asked to evaluate items presented to them one at a time, they can easily misjudge how much money they should pay for them and that irrelevant characteristics of the product (for instance, the way it is presented) can become determinants of willingness to pay. Although it is not possible in this study to verify whether irrelevant characteristics of the product did play a role, one possible hypothesis is that if customers don’t have a salient reference point, they could tend to rely on their financial possibilities to decide how much they should pay or not.
Another contribution of the study regards the significant impact of shopping motivation on the perception quality (H3a), with hedonic shoppers showing an increased perception of quality across both store environment cues, and also displaying stronger differences in the dependent variable between the two store conditions. It is interesting to note how non-hedonic shoppers display a slightly lower quality perception in the upscale-looking store environment rather than in the discount-looking store environment. These findings remind of those in H2 about the interaction with mood and store environment, that were discussed above: this suggests that there could be an interaction between shopping motivation and mood, although the sample size in this study is too small to test for three-way interactions.
This possible explanation would be coherent with a study by Babin et al. (2000) claiming that positive affect is positively related to hedonic shopping value, and a previous one arguing that pleasure and arousal are highly correlated with hedonic shopping value (Babin et al., 1994). The positive affects induced by an hedonic shopping motive would make respondents tend to
perceive product attributes in a mood-congruent manner, weighing the positive elements more strongly (Adaval, 2001); this leads to an overall higher quality evaluation. Several studies have found congruent results: Doucé et al. (2011) showed how in a retail environment, consumers who had a high hedonic shopping motivation felt more pleasure and evaluated the store environment and the products more positively than consumers with a low hedonic shopping motivation.
Kaltcheva et al. (2006) found how arousal increases pleasure in hedonic individuals but negatively impacts it in utilitarian individuals, which feel they are distracted by stimulating environments. Hedonic individuals would then tend to increase their evaluations, whereas utilitarian shoppers would perceive the environment as less pleasant and decrease their product evaluations.
Although shopping motivation for willingness to pay is slightly insignificant in the regression, it is possible to observe that the means of willingness to pay for hedonic shoppers seem to show the same tendency than those of perception of quality (higher in both store environments, with stronger differences between the two store conditions).
The hedonic value received from shopping may include arousal and heightened involvement (Bridges et al., 2008) and consumers with increasing involvement tend to pay less attention to the price cue (Zaichkowsky, 1988; Lockshin et al., 2006).
This is in line with a study by Irani et al. (2011) which found out that price sensitivity is negatively correlated to hedonic value, which makes hedonic shoppers less sensitive to price. This would be coherent with the notion that at the base of impulse buying there is an hedonic behavior and need (Muruganantham et al., 2013), which leads to increased spending and in severe cases possible financial hardships (Rook, 1987). A study by Lee (2009) in the fashion retail context, showed that utilitarian shopping value of consumers was more sensitive in price than the hedonic shopping value and a self-using purchase was more sensitive in price than a gift-giving purchase: price-sensitive consumers are generally rational and logical shoppers who emphasize utilitarian shopping benefits.
7. IMPLICATIONS
There are several implications that retailers could draw from the present study.
Firstly, mood impacts the way customers perceive and weigh store cues. Although retailers cannot control mood states carried by customers prior to enter the store, they can operate to stimulate pleasure inside the store environment to enhance customers’ affect and elicit approach behaviors: customers in good mood tend to evaluate product quality to be higher. Pleasure can be created through several atmospheric cues, such as the use of an arousing scent (Doucé et al., 2011), well designed environments and an optimal number of employees on the store (Baker et al., 2002), congruence of atmospheric cues (Mattila and Wirtz, 2001; Babin and Attaway, 2000), use of background music (Yalch, 2000).
Hedonic motivation of customers is also related to higher product evaluations: depending on the goods sold (hedonic and aimed to be used for fun and leisure rather than utilitarian and to be used for their functional characteristics) retailers can consider paying particular attention to create proper atmospheric cues in the store, as hedonic shoppers seem to be particularly sensitive to them. Moreover, utilitarian shoppers tend to be more focused on product attributes rather than atmospherics, retailers selling utilitarian products should set fair prices, adopt promotions, carry good quality merchandise and in case of complex products, have sale personnel able to properly explain product attributes to customers.
One influence of willingness to pay seem to be income - store environment and mood do not impact how much customers would like to spend on a product, so charging high prices – no matter what sophisticated cues are applied in the store environment - will work only if target customers are high-income individuals.
