The Influence of Sleep Images on Impulsive Purchase Behavior and
Perceived Risk Towards Purchases
Submitted by: Berlesu Kerimoglu Student Number: 10395113
Name of Supervisor: Dr. Andrea Weihrauch
Name of Institution: University of Amsterdam – Amsterdam Business School
Final Master Thesis Submitted in Partial Fulfilment of the Requirements for the Degree of MSc. in Business Administration – Marketing Track
Date of Submission: 23-06-2017 Word Count: 18,146
S
TATEMENT OFO
RIGINALITYThis document is written by Berlesu Kerimoglu who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the supervision of completion of work, not for the contents.
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ABLE OFC
ONTENTS STATEMENT OF ORIGINALITY ... I LIST OF TABLES ... IV LIST OF FIGURES ... IV ABSTRACT ... V ACKNOWLEDGEMENTS ... VI 1. INTRODUCTION ... 7 2. CONCEPTUAL FRAMEWORK ... 10 3. LITERATURE REVIEW ... 113.1WHAT IS IMPULSIVE BEHAVIOUR? ... 11
3.1.1. The Reflective-Impulsive Model (RIM) ... 13
3.1.2 How Does RIM Relate to Consumer Behavior? ... 15
3.1.3 What are the Factors That Can Influence Impulsive Purchasing Behavior? ... 17
3.1.4 Reflection on Impulsive Purchasing Behavior ... 21
3.2WHAT ARE LAY BELIEFS? ... 22
3.2.1 What are Lay Beliefs Related to Sleep? ... 23
3.2.2 How Can We Evoke Sleep-related Lay Beliefs and Accordingly Influence Impulsivity? ... 25
3.3. HOW IS IMPULSIVE BEHAVIOR RELATED TO RISK-TAKING BEHAVIOR? ... 28
3.3.1. How Can Impulsive Purchase Behavior Affect Perceived Risk Towards Purchases? ... 29
4. DATA COLLECTION AND METHODOLOGY ... 33
4.1SETTING ... 33
4.2THE VARIABLES ... 34
4.2.1 Manipulation of the Independent Variable of Sleep Images ... 34
4.2.2 The Measurement of the Dependent Variable of Impulsivity ... 38
4.2.3 The Measurement of the Dependent Variable of Perceived Risk ... 39
4.2.4 Control Variables ... 43
4.3DATA COLLECTION ... 46
4.4METHODOLOGY ... 48
5. RESULTS ... 50
5.1DESCRIPTIVE AND FREQUENCY STATISTICS ... 50
5.1.1 Perceived Sleepiness ... 50
5.1.2 Impulsive Purchasing Behavior ... 51
5.1.3 Perceived Risk ... 55
5.2CORRELATIONS BETWEEN THE VARIABLES ... 56
5.3.RELIABILITY ANALYSES ... 57
5.3.1 Sleep Questions ... 57
5.3.2 Impulsive Purchasing Scale ... 57
5.3.3. Buying Impulsiveness Trait Scale (BIS) ... 58
5.3.4 Perceived Risk Scale ... 58
5.4.PERCEIVED SLEEPINESS ... 59
5.4.2 ANCOVA ... 60
5.5.IMPULSIVE PURCHASE BEHAVIOUR ... 62
5.5.1. Independent Samples T-Test ... 62
5.5.2 ANCOVAs ... 64
5.6PERCEIVED RISK ... 66
5.6.1 MANOVAs ... 66
6. DISCUSSION ... 68
6.1DISCUSSION ... 68
6.2LIMITATIONS AND ACADEMIC RECOMMENDATIONS ... 72
6.3MANAGERIAL IMPLICATIONS ... 75
REFERENCES ... 77
APPENDICES ... 93
APPENDIX 1:OBJECT-IMAGES FOR CONTROL CONDITION ... 93
APPENDIX 2:SLEEP-IMAGES FOR MANIPULATION CONDITION ... 93
APPENDIX 3:IMPULSIVE PURCHASING SCALE ... 94
APPENDIX 4:ORIGINAL PERCEIVED RISK SCALE BY JACOBY &KAPLAN (1972) ... 95
APPENDIX 5:ORIGINAL BUYING IMPULSIVENESS SCALE BY ROOK &FISHER (1995) ... 96
APPENDIX 6:ONLINE QUESTIONNAIRE ... 97
APPENDIX 7:INFORMED CONSENT ... 103
APPENDIX 8:MEANS,STANDARD DEVIATIONS, AND CORRELATIONS ... 104
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ABLESTable 1: Sample Plan ... 48
Table 3: Results of Independent Samples T-Test of Perceived Sleepiness Questions per Condition ... 59
Table 4: Results of Independent Samples T-Test of SSS per Condition ... 60
Table 5: ANCOVA between Conditions and SSS ... 61
Table 6: Descriptive Statistics for ANCOVA Conditions and SSS ... 61
Table 7: Results of Independent Samples T-Test of Impulsivity Items and Conditions ... 63
Table 8: ANCOVA Between Conditions and Muesli Bar Item ... 65
Table 9: ANCOVA Between Conditions and Heater Item ... 65
Table 10: ANCOVA Between Conditions and Headset Item ... 65
Table 11: MANCOVAs Between Conditions, Headset & Heater Item, and Perceived Risk ... 67
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IST OFF
IGURES Figure 1: Conceptual Framework ... 11Figure 2: Reliability Estimates for Original Perceived Risk Scale ... 41
Figure 3: Contribution to Overall Risk per Type ... 42
Figure 4: Overall Perceived Risk per Product Category ... 43
Figure 5: ANCOVA Between Conditions and SSS ... 62
A
BSTRACTThis study aimed to investigate whether exposing participants to sleep-related images could stimulate perceived sleepiness and therefore affect their impulsive purchase behavior and perceived risk towards purchases. Sleep images were used to activate the lay belief that lack of sleep can alter self-control. When individuals believe that their self-control is limited, they use this knowledge as a justification to engage in impulsive behaviors. Impulsive purchase behavior is when consumers experience a sudden and uncontrollable urge to purchase a product to achieve immediate gratification. Whereas, perceived risk towards purchases refers to when consumers assess the value of benefits over the costs of purchasing a product. This study hypothesized that the participants who were exposed to sleep images would display higher levels of impulsive purchase behavior, and hence demonstrate lower levels of perceived risk towards purchases. An online experiment was constructed in the format of a survey, and was distributed through an online link. The hypotheses were not supported. This study is highly relevant to marketing practices, as the explored constructs are determinants of consumers’ initial and repeated purchase intentions. It is in the interest of marketers to gain knowledge on how to increase impulsive purchasing behavior and reduce perceived risk towards purchases. Future research should focus on bridging the gap between impulsive purchase behavior and perceived risk towards purchases, as well as explore hedonic and utilitarian dimensions of consumer attitudes towards product categories and how it can influence impulsive purchasing behavior and perceived risk towards purchases.
A
CKNOWLEDGEMENTSI would like to thank my supervisor Dr. Andrea Weihrauch for providing her guidance, expertise, and time throughout this process.
1.
I
NTRODUCTIONNowadays, we enjoy an ease of reach to every possible product or service imaginable. In our homes, we own a vast amount of products that we barely use, and when we shop for food or other necessities, we purchase other products that we did not initially intend to acquire. Even though we realize the negative consequences of this type of behavior, such as unnecessary costs or clutter, we find ourselves engaging in the same behavior again. This type of behavior is caused by impulsive decision-making. During shopping, we develop a sudden and uncontrollable desire to own the product, which leads to purchasing it to achieve an immediate gratification (Rook, 1987). The positive feelings that we attained from the previous purchase makes us repeat the same behavior again (Strack & Deutsch, 2006).
Every time consumers impulsively purchase a product, the product becomes associated with the physical senses, and the positive and cognitive feelings that they have experienced (Strack & Deutsch, 2006). This suggests that if marketing practitioners can stimulate the factors that have led to the composition of such feelings, consumers might be more likely to engage in impulsive purchase behaviors (Adaval, 2003; Cacioppo, Priester, & Bemtson, 1993; Chan, 2005; Gardner, 1985; Ronis, Yates and Kirscht, 1989). A way to influence consumers’ impulsive purchase behavior is through altering their thought processes. When an individual is involved in a purchase-related decision-making, he or she either deliberates and evaluates the consequences of the choices, or acts on his or her emotions to make the purchase judgment (Strack & Deutsch, 2006). Thus, it appears to be that the goal for the marketing practitioners would be to limit deliberation and increase the chances of consumers using emotions to guide their purchase decisions.
One of the ways that thought processes of consumers could be influenced is through lay beliefs. Lay beliefs refer to the individuals’ idea of an event and how they would respond to that event (Vohs, Glass, Maddox, Markman, 2010). In essence, if one believes that a particular event or a situation causes him or her to behave in a certain way - when that situation is taking place - the individual will adjust his or her behavior so it fits with the event. Thus, when the relevant lay beliefs related to impulsiveness are triggered in a purchasing situation, the individual might adjust their behavior to act in an impulsive manner. There is substantial research suggesting that if individuals feel that their self-control is limited due to a particular situation, then they are less likely to suppress their urges (McFerran & Mukhopadhyay, 2013; Mukhopadhyay & Johar, 2005; Wilson & Gilbert, 2003). Thus, if the consumers are led to believe that they lack self-control due to a situation, then they might be more likely to engage in an impulsive purchase behavior.
Firstly, this study aims to investigate whether the thought processes of consumers can be altered through lay beliefs to influence impulsive purchase behavior. For this study, lay-beliefs related to lack of sleep were chosen to influence impulsive purchase behavior. This decision was based on the lay belief that lack of sleep can impair self-control (Gray, Eagleston, Gibson, & Thoresen, 1984; Morin, Vallieres, & Ivers, 2007; Vohs, Glass, Maddox, Markman, 2010; Vohs and Baumeister, 2016). This is relevant to marketing practitioners because if consumers are made to believe that they lack sleep and in return lack self-control, they will be more likely to engage in an impulsive purchase behavior. In this study, lay beliefs related to lack of sleep are activated by repeatedly exposing a group of participants to images of sleeping individuals to stimulate feelings of sleepiness. The premise is that the individuals who are exposed to these images will have higher levels of perceived
sleepiness, and due to lay-beliefs related to lack of sleep (e.g. low self-control), they will demonstrate higher levels of impulsive purchase behavior.
If consumers’ lay beliefs can be evoked by images and can influence them to behave in a certain manner, then the marketing practitioners can optimize the content and context of the images in their advertisements to stimulate certain lay beliefs that would lead to higher likelihoods of purchase. The researchers in the field of consumer behavior have not yet examined the relationship between lay beliefs specifically related to self-control and its influence on impulsive purchase behavior. Thus, this research can contribute to this field by providing additional insight into consumers’ underlying thought processes and how these thought processes can reflect on consumers’ buying behavior.
Secondly, this study will investigate the relationship between impulsive purchase behavior and perceived risk towards purchases. This is because the two behaviors are interrelated (Zuckerman & Kulhman, 2000). When an individual has a sudden urge to buy a product to achieve a potential reward (e.g. satisfaction), he or she is likely disregard the potential punishment (e.g. high costs) of their purchase decisions, thus making riskier purchase choices (Zuckerman & Kulhman, 2000). Moreover, when an individual believes that they lack self-control and uses this belief as an excuse to engage in an impulsive purchase, they are essentially engaging in a risk taking behavior (Bicket et al., 2007). This is because risk-taking behavior occurs when impulsivity overpowers the influence of self-control (Bicket et al., 2007). The influence of impulsive purchase behavior on perceived risk towards purchases is relevant to marketing practitioners as perceived risk is a determinant of initial and repeated purchase intention and is related to advertising effectiveness, brand loyalty,
behavior is widely discussed in the field of individual differences in personality, the relationship between the two concepts is not yet widely approached from a marketing perspective. Additionally, the literature that addresses perceived risk is fairly outdated, suggesting a need for fresh insight into this concept.
Therefore, the aim of this study is to examine the impact of perceived sleepiness - triggered by the images of sleeping individuals - on impulsive purchase behavior, and whether the resulting impulsive purchase behavior has an effect on perceived risk towards purchases.
In the following section, the conceptual framework will be presented to outline interrelationships between the relevant variables. Afterwards, the status quo on the topics between the concepts: impulsive purchase behavior, lay beliefs, and perceived risk will be discussed. After the literature review, the setting, data collection plan and methodology will be discussed. Subsequently, the findings will be reported. The last section of this study will include the discussion of the findings, limitations and will close with providing managerial and academic recommendations.
2.
C
ONCEPTUALF
RAMEWORKThe research question of this study is “To what extent does consumers’ perceived sleepiness influence impulsivity in their purchase behavior, and how does this affect their perception of risk towards purchases?” The conceptual framework in Figure 1 provides a summary of the interrelationships between the relevant variables utilized to answer the research question. The independent variable is the two conditions: sleep images and object images. The dependent variables that will be measured are perceived sleepiness, impulsive purchase behavior, and perceived risk towards purchases.
The conceptual model proposes that the conditions will have a differential effect on the level of perceived sleepiness. The existence or abundance of perceived sleepiness will have an effect on individuals’ impulsive purchase behavior due to lay beliefs related to lack of sleep and its effects on self-control. Lastly, the impulsive purchase behavior will have an effect on perceived risk towards purchases, due to the interrelationship between the concepts of impulsive and risk-taking behavior.
FIGURE 1: CONCEPTUAL FRAMEWORK
3.
L
ITERATURER
EVIEWThis chapter will provide the status quo on the relevant variables explored to answer the research question. Firstly, the concept of impulsive behavior is investigated. Afterwards, the theory of lay beliefs, and its possible link to impulsive behavior is examined. Lastly, the association between risk-taking behavior, perceived risk and impulsive purchase behavior is discussed. The hypotheses outlining the relationship between the variables will be presented after the status quo for each variable is discussed.
3.1
W
HAT ISI
MPULSIVEB
EHAVIOUR?
When individuals engage in decision- making, there is an unconscious battle occurring within, which is whether to base decisions on one’s desires or whether to suppress
resist the temptation caused by one’s desires is referred to as control or self-regulation. The failure to do so, suggests that one’s desires are stronger than their ability of self-control (Hoch & Loewenstein, 1991).
An example of a self-control failure is engaging in impulsive behaviors. In relation to consumer behavior, impulsive purchasing behavior can be explained as a sudden and an overwhelming urge that is felt by consumers to purchase a product (Rook, 1987). This urge is powerful and uncontrollable, wherein consumers make spontaneous decisions based on an anticipation of arousal and positive affect. The lack of self-control causes one to disregard the consequences of decisions and rather makes him or her focus on immediate gratification (Rook, 1987). Moreover, acting on impulses is an unplanned and an unconscious process, which occurs when an individual encounters a particular stimulus (Wolman, 1973). A study conducted by Thompson, Locander, and Pollio (1990) supported the irresistibility of impulsive purchasing, where consumers expressed conscious knowledge of losing control of their behavior but still indulged in excessive purchasing.
What is the underlying process of impulsive behavior that makes it irresistible and how does it lead to disregarding the consequences of one’s choices? The two-system model developed by Strack and Deutsch (2006) termed the reflective and impulsive model (RIM) provides a detailed explanation on the mental process that constitutes the impulsive mechanism.
3.1.1.THE REFLECTIVE-IMPULSIVE MODEL (RIM)
A two-system model constructed by Strack and Deutsch (2006) outlines the impulsive and reflective mechanisms, which contributes greatly to understanding the reasons behind impulsive behaviors. The impulsive mechanism entails a fast and automatic activation of a network of associations based on an affective-response system. In contrast, the reflective mechanism is focused on rule-based reasoning.
3.1.1.1THE IMPULSIVE MECHANISM
The network of associations in the impulsive system represents the regularities in one’s environment. The links between the associations are strengthened when an individual is in close temporal or spatial proximity to the stimulus that matches the existing regularities (Strack & Deutsch, 2006). Moreover, the behavioral response and the affective reaction to the stimuli in the environment are registered and combined together to create associative clusters to represent simple concepts (e.g. buying a cake in a bakery and feeling happy). These clusters can serve as a simple memory system, where over time they form the basis of typical properties of a particular environment e.g. bakeries are happy places (Johnson & Hirst, 1991).
Even though, impulsive behavior is described as being irresistible and uncontrollable, one can have awareness that they are engaging in an impulsive behavior. When an individual is confronted with a stimulus, they can experience three feelings: physical senses, positive or negative affective feelings, and cognitive feelings (Strack & Deutsch, 2006). Firstly, feelings related to the physical senses, which might be sounds, colors, tastes, or smells are stimulated. Secondly, positive or negative feelings are activated depending on the associative links in the impulsive mechanism. Lastly, cognitive feelings such as familiarity or ease of the stimulus are triggered
and uncontrollability of impulsive behavior, individuals are aware of the feelings that originate from engaging in such a behavior. This is due to the activation of the affective structures within the impulsive mechanism.
To summarize the impulsive mechanism, whenever an individual finds oneself in a situation that resembles the existing environmental regularities, corresponding network of associations becomes activated, causing the individual to develop anticipatory affective responses. These anticipatory affective responses (e.g. positive feelings) can pose as a reason to why individuals make impulsive purchases, especially if they do not possess the motivation and the capacity to process the information (Strack & Deutsch, 2006).
3.1.1.2THE REFLECTIVE MECHANISM
If individuals deliberately consider the consequences of their actions based on evaluating the information, this suggests the activation of the reflective mechanism. The reflective system creates re-representations of the concepts stored in the clusters in the impulsive mechanism. Therefore, the reflective mechanism does not operate separately to the impulsive mechanism. It generates judgments based on the goals of the individual to make sure to overcome unwanted habits and develops plans to avoid these habits in the future (Lieberman, 2003). A shortcoming of this mechanism is that the processing is slow. This is because it needs to generate new representations from the new information while combining the existing representations from its own mechanism and the impulsive mechanism (Hummel & Holyoak, 2003). This indicates that the representations in the reflective mechanism could be inconsistent to each other. Overall, the reflective mechanism represents the state of awareness of one’s knowledge and goes beyond the feeling of knowing.
3.1.1.3THE FINAL COMMON PATHWAY
The reflective and impulsive mechanism model (RIM) includes a third element, which is referred to as the final common pathway to behavior. The pathway combines the information from the reflective and impulsive mechanisms, such as feelings and judgments and organizes them according to cognitive and affective structures. These two structures combine and form an individual’s behavioral schemata, which are used to guide overt behavior. Furthermore, the behavioral schemata differ in their spread of activation and activation potential (Strack & Deutsch, 2006 p. 208). This suggests that information received from the impulsive and reflective mechanisms can activate different behavioral schemata.
A particular behavioral schema leads to an overt behavior if it has the strongest activation. The impulsive mechanism is dominant when the behavior is evoked through the spread of activation to behavioral schemata, where one association leads to another. On the other hand, the reflective mechanism is more dominant if the different behavioral schemata compete with each other to formulate a decision that creates the conditions for and satisfies the individuals’ future goals.
Overall, reflective and impulsive mechanisms work together to elicit a particular behavior. In relation to consumers’ purchase behavior, how can one know which mechanism will dominate during a purchase decision?
3.1.2HOW DOES RIMRELATE TO CONSUMER BEHAVIOR?
Strack & Deutsch (2006) suggests that it is possible to deduce which mechanism takes on the more dominant role when faced with a purchase decision. Firstly, if the stimulus requires high levels of reflection due to its importance, then an individual is more likely to elicit a behavior based on their reflective system. An example of this is
when deciding to buy a house or new toothpaste (Ben-Zur, 1998). Secondly, if the individuals are held responsible for their purchase decision (e.g. tell others why they made such a decision) they are more likely to deliberate and evaluate the consequences of their choices (Tetlock, 1999). On the other hand, if the individuals are expected to bear no accountability on their decision, they are less likely to evaluate and form judgments.
A study conducted by Ronis, Yates and Kirscht (1989) argues that if the purchase behavior is based on habits, then the impulsive mechanism can be activated by the use of three feelings discussed in the previous section. This suggests that if purchasing a particular product, e.g. mints, is a habit, the product can be placed prominently in the visual field (physical senses) with an ease of reach (cognitive feelings) to trigger the impulsive mechanism. An example of this is items placed near the cash registers or suggested items during online checkouts.
Further, the valence of the product is also of significance. According to the motivational orientation theory, if the product valence is positive then consumers are more likely to be motivated to approach the product and evaluate the product more positively due to experiencing positive affect (Cacioppo, Priester, & Bemtson, 1993; Neumann & Strack, 2000). The approach orientation can be an imaginary or real closeness of the distance between the individual and the product. However, if the product valence is negative, then the consumers will adopt the avoidance approach towards the product and will judge the product more negatively due to experiencing negative affect (Cacioppo, Priester, & Bemtson, 1993; Neumann & Strack, 2000). The avoidance orientation is the imaginary or real increase in the distance between the individual and the product. Overall, this suggests that the attractiveness of the product is an important determinant to trigger the impulsive mechanism.
Lastly, if individuals are deprived of basic needs, such as being thirst, hunger, or sleep, they are more likely to impulsively purchase the products that satisfy these needs. In addition to purchasing the product, they are more likely to develop positive attitudes towards the products that satisfy these needs. This can entail that over time these products can become habits. An example of this is when individuals go to the store while they are hungry and purchase excessively and recognize food products more easily (Aarts, Dijksterhuis, & De Vries, 2001).
Overall, there is an overlap between the two mechanisms. In natural situations, due to the slow processing of the reflective mechanism, affective responses stored in the impulsive mechanism can take over leading to impulsive purchase behavior (Strack & Deutsch, 2006;Adaval, 2003; Chan, 2005; Gardner, 1985). The reflective and impulsive mechanism model (RIM) provides a detailed explanation of the underlying processes of the two mechanisms. In the next section, additional factors that influence impulsive buying behavior will be discussed.
3.1.3WHAT ARE THE FACTORS THAT CAN INFLUENCE IMPULSIVE PURCHASING
BEHAVIOR?
3.1.3.1PRODUCT- RELATED FACTORS
In relation to impulsive buying, past research attempted to classify which products and services are impulsive or non-impulsive (Assael, 1985; Bellenger et al., 1978; Kollat & Willet, 1969; Shapiro 1973; Stern, 1962). However, this classification method ignores the notion that any purchase can be impulsive. If an individual does not possess the internal motivation to act on his or her impulses at a buying situation, then the assumed impulsivity of a product or service does not hold any significance (Rook & Hoch, 1985). On the contrary, it is suggested that impulsive buying applies more to
low-priced and low-involvement products (Assael, 1985). However, Rook (1987) argues that vacation cruises or a piece of furniture can be as impulsive as snack items or magazines. Thus, one cannot assume that because a product is higher-priced or low-priced, that it is less or more impulsive.
Even though, one cannot classify which products or services are more impulsive than others, products in general can be divided into two categories: hedonic or utilitarian. A hedonic product is a product that is consumed due to its affective/sensory experience and entertaining properties (Hirschman and Holbrook, 1982). While, a utilitarian product is instrumental and its purpose is to satisfy a goal with a particular function. A way to distinguish between hedonic and utilitarian products is to examine whether the items are based on “should” (utilitarian) or “want” (hedonic) preferences (Dhar & Wertenbroch, 1999). From the differences in the definitions of utilitarian and hedonic products, it can be presumed that the utilitarian option is the reflective choice, while the hedonic option is the impulsive choice. This is based on RIM proposed by Strack and Deutsch (2006), as well as on the agreement from a number of researchers that impulse buying carries a hedonic value (Cobb & Hoyer, 1986; Hausmann, 2000; Rook 1987; Rook & Fisher, 1998; Thompson, Locander & Polio, 1990). Research indicates that when individuals purchase hedonic products, their mood improves and their need for fun and entertainment is fulfilled (Cobb & Hoyer, 1986; Hausman, 2000; Rook; 1987). Thus, it is assumed that due hedonic products’ entertaining and fun properties, these products might elicit anticipation of positive affect, which might lead to the activation of the impulsive mechanism. On the contrary, utilitarian products involve a deliberate judgment process of the products’ attributes and benefits, suggesting the involvement of the reflective mechanism. It is crucial to note that a product can be both hedonic and
utilitarian (Batra & Athola, 1991). Consumer’s motive towards buying the product can be used to assess whether the product was purchased due to its hedonic or utilitarian aspects (Pham, 1998) An example of this is when an individual buys a cell phone to solely use for emergency calls (utilitarian) or to talk to friends (hedonic).
Thus, one cannot explicitly state that a product is impulsive or non-impulsive or it’s hedonic or utilitarian. However, if the consumers are presented with the hedonic and utilitarian options of the same product and consistently choose the hedonic option due its positive affect, one can assume that the individuals could be engaging their impulsive mechanism to make the purchase decisions.
3.1.3.2PERSONALITY-RELATED FACTORS
The capacity to resist impulses depends on the individual’s own impulse buying tendency (Beatty & Elizabeth Ferrell, 1998). Consumers with a high impulse buying tendency feel the urge to buy impulsively more frequently. Thus, they are more likely to engage in impulsive purchasing and are less able to resist their impulses (Beatty & Elizabeth Ferrell, 1998). Moreover, these individuals experience higher positive affect from indulging in impulsive purchasing than consumers with low impulsive buying tendency. This greater positive affect can make it difficult to resolve conflicting goals, such as deciding between saving money or purchasing a product that will make them happy (Baumeister, 2002). This latter effect is further reinforced when these individuals are uncertain of their desires, which can make them more susceptible to environmental influences such as product valence and proximity (Mischel, Ebbesen, & Raskoff-Zeiss, 1972; Neumann & Strack, 2000 Rook & Fisher, 1995).
have contributed to assessing the relationship between personality traits and impulsive behavior (Buss & Plomin, 1975; Dickman, 1990; Eysenck & Eysenck, 1985; Patton, Stanford, & Barratt, 1995; Whiteside & Lynam, 2001; Zuckerman, 1994). In their latest study, Eysenck and Eysenck (1985) divided the construct of impulsivity into two components: venturesomeness and impulsivity. The researchers suggested that the venturesomeness (to be daring to take risks) component related to extraversion (outgoing & social personality), while the impulsiveness component corresponded to psychoticism (interpersonal hostility). Moreover, a study conducted by Zuckerman (1994) developed the sensation seeking scale, which described the personality of impulsiveness as “ lack of planning and the tendency to act impulsively without thinking, experience seeking, or the willingness to take risks for the sake of excitement” (Whiteside & Lynam, 2001, p. 671). In addition, Dickman (1990) suggested that there are two different types of impulsive personalities: dysfunctional and functional. The author argues that while functional impulsivity is acting with minimal forethought at an optimal level, dysfunctional impulsivity is acting with less forethought than the optimal level. Thus, the researchers mentioned previously approached the construct of impulsivity by relating it to risk-taking behavior. They argue that if individuals are highly impulsive, they are more likely to yearn for novel experiences and take more risks to achieve excitement. This is one of the examples of the association between impulsive behavior and risk-taking behavior.
Other researchers approached the construct of impulsivity by focusing on lack of self- control. Patton, Stanford, and Barratt (1995) constructed the Barratt Impulsiveness Scale (BIS-11), in which one of the components is non-planning. The authors suggested that this component measures individual’s “self-control and cognitive complexity” (Whiteside & Lynam, 2001, p. 672). Moreover, Buss and
Plomin (1975) approached impulsivity by examining temperament and inhibitory control. The researchers proposed that individuals who are highly impulsive tend to not consider consequences of their decisions, have difficulty continuing with a task, easily feel bored and want to pursue something new. Lastly, Tellegen and Watson (1985) compared the construct of impulsivity with the ability of constraint, and suggested that if individuals are highly impulsive, then they are low in constraint.
Overall, individuals who are highly impulsive embody the personality traits of risk-taking. They have difficulty resisting their impulses and achieve higher positive affect when they are engaging in an impulsive behavior. However, this research study will not focus on individual differences in impulsivity. The background information is relevant because it supports the necessity to control for individual tendencies of impulsive behavior.
3.1.4REFLECTION ON IMPULSIVE PURCHASING BEHAVIOR
One of the most intriguing insights from examining the status quo of the underlying mechanisms of impulsive behavior is the ease at which the consumers’ impulsivity can be affected by mere presentation of visual stimuli. This suggests that if a visual stimulus such as an image has affective properties, it can activate associative networks in the impulsive mechanism that correspond to that image. Thus, an image could be used to shape, activate, and build upon existing beliefs through associations, which then could lead to an impulsive behavior.
The next chapter will provide information about lay beliefs, which are stored in the associative network and how they can influence behavior.
3.2
W
HAT AREL
AYB
ELIEFS?
Lay beliefs are “how people think they would respond and how they do respond when faced with an event” (Vohs, Glass, Maddox, Markman, 2010, p. 168). These lay beliefs are acquired from individuals’ daily experiences and environments, which can influence their judgments (Ross & Nisbet, 1991). To relate back to RIM, this can indicate that lay theories can affect the judgment formation in the reflective mechanism.
Lay beliefs have been related to hedonic effects (as cited by: McFerran & Mukhopadhyay, 2013; Novemsky & Ratner, 2003). Hedonic effects can be described as maintaining a relatively stable level of happiness after experiencing positive or negative feelings and consequences. One can assume that if the statement that ‘impulsivity is not irresistible’ (Baumeister, 2002) holds true, a reason that individuals repeat their impulsive behaviors might be due to the ease of returning to the same state of happiness even after having experienced negative outcomes from their impulsive purchasing e.g. guilt or high costs.
A direct link between lay beliefs and impulsivity has not been established in research. However, a study conducted by Mukhopadhyay and Johar (2005) examined the relationship between lay beliefs related to self-control and goal setting. The researchers stated that if individuals believe that self-control is flexible and limited, then they tend to set fewer goals or allocate less effort into achieving goals. Since the constructs of self-control and impulsivity are interrelated, one can assume that if individuals have a lay belief that their self-control is malleable and limited, they might be less likely to develop strategies to suppress their impulsive behavior.
Overall, lay beliefs about a particular event can guide individual’s actual goal-directed behaviors (McFerran & Mukhopadhyay, 2013). Lay belief theories have been applied to health-related issues such as obesity & drug abuse (Furnham & McDermott, 1994) causes of depression, (Lauber, Falcato, Nordt & Rössler, 2003) and sleep deprivation (Wilson & Gilbert, 2003). In their study, McFerran and Mukhopadhyay (2013) showed that if individuals believed that they lack exercise, they tended to consume more food and were overweight compared to others who believed that they had poor diet. This is due to the lay belief that lack of exercise causes obesity, hence justifying their impulsive behavior of over-eating. Moreover, another study has shown that lay beliefs about sleep deprivation can contribute to affective forecasting in decision-making (Wilson & Gilbert, 2003). The latter study is thought provoking because it is about affective forecasting, which is – “how individuals develop predictions about emotional reactions to future events” (Wilson & Gilbert, 2003, p. 131). This is easily relatable to the concept of impulsive behavior, specifically to the anticipation of positive affect similar to the preceding impulsive behavior. Thus, one can presume that lay beliefs about lack of sleep could positively or negatively influence affective predictions of future events, which can increase or decrease impulsive behavior.
Therefore, in this study lay beliefs related to sleep will be used to influence impulsive purchase behavior. The next section will outline lay beliefs regarding lack of sleep and its possible influence on impulsive purchase behavior.
3.2.1WHAT ARE LAY BELIEFS RELATED TO SLEEP?
A study conducted by Gray, Eagleston, Gibson, and Thoresen (1984) put forward five statements that are misconceptions about sleep. These statements are “(1) people need
the day, (3) if you feel tired during the day, you must not have slept well the night before, (4) if you don’t get enough sleep on a particular night, you have to make it up at another time and (5) if you know you won’t be getting enough sleep, you can prepare by sleeping more hours on preceding nights” (Gray, Eagleston, Gibson, & Thoresen, 1984, p. 380). The agreement percentages to these statements were respectively (1) 61%, (2) 96%, (3) 48%, (4) 40%, and (5) 50%. Even though, this study was conducted on 267 adolescents (13-17 years) it is not unrealistic to assume that adults might hold similar misconceptions.
A Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) was developed as a self-measure for adults to assess their sleep-related beliefs (Morin, Vallieres, & Ivers, 2007). This scale divided sleep-related beliefs into five dimensions, however the most relevant to this research study are “(a) unrealistic sleep expectations, and (b) diminished perception of control and predictability of sleep ” (Morin, Vallieres, & Ivers, 2007, p. 1548). The items in the scale that relate to these dimensions included: (1) need 8 hours of sleep, (2) cannot function without a good night sleep, (3) unable to manage consequences, and (4) lack of energy due to poor sleep. The mean averages for the items were respectively: (1) 29%, (2) 64%, (3) 24%, and (4) 48%. From these results, it can be stated that the agreement to the misconceptions are similar between adults and adolescents. Generally, the highest average belongs to the lay belief regarding sleep deprivation and its negative effects on functioning.
From a theoretical perspective, self-control is a process that relates to cognitive and behavioral functioning (Robinson, Schmeichel, Inzlicht, 2010). A study conducted by Vohs et al. (2011) has shown that individuals hold lay beliefs that sleep deprivation impairs self-control. In a recent publication, Vohs and Baumeister (2016) suggested
that this lay belief might be due to the influence of self-licensing. The authors defined self-licensing as “engaging in tempting yet undesirable behaviors due to a belief that one has earned the reward” (Vohs & Baumeister, 2016, p. 195). This indicates that if individuals are aware that sleep deprivation impairs self-control and the resulting side effects (e.g. low levels of functioning) they are more likely to engage in an impulsive behavior because they interpret their lack of self-control as a license to avoid the effort of evaluating their decision.
The next section will elaborate on how this study will attempt to evoke sleep-related lay beliefs to influence impulsive purchase behavior.
3.2.2HOW CAN WE EVOKE SLEEP-RELATED LAY BELIEFS AND ACCORDINGLY INFLUENCE IMPULSIVITY?
This study will try to influence the activation of individuals’ associative networks in the impulsive mechanism through visual stimuli. The chosen stimuli are images of sleeping individuals. The justification of using sleep-related images in particular is to stimulate the participants to think about sleep and thus generate sleep-related lay beliefs. Images can also encourage the participants to mentally practice sleeping. Mental practice is defined as “the symbolic rehearsal of a physical activity in the absence of any gross muscular movements” (Driskell, Copper, & Moran, 1994, p. 481).
There are a number of studies that have explored the relationship between images, mental practice and its’ effects on behavioral and attitudinal responses. A study conducted by Wild, Erb, and Bartels (2001) used images of faces depicting emotions and measured its effect on actual expressed emotions. The results suggested that when individuals were exposed to images of happy or sad expressions, they
reported feelings that matched with the emotions in the picture. This indicates that the images were able to stimulate a change in the affective state, where the individuals mentally practiced experiencing the emotions. The authors proposed that the obtained effects could be explained by the theory of emotional contagion. One of the stages of emotional contagion, which is referred to as primitive contagion, is defined as ‘the tendency to automatically mimic and synchronize the movements, expressions, postures, and vocalizations with those of another person” (as cited by Wild, Erb & Bartels, 2001; Hatfied et al., 1992). This definition highlights that mimicry of others’ emotions is an unconscious process that can alter individuals’ state of being. This could mean that if individuals are exposed to images of sleeping individuals, they might mimic the content of the picture and hence become sleepier or more tired.
Moreover, a study conducted by Provine (2005) focused on yawning and its contagious nature. The author suggested that exposing participants to images of yawning could induce the participants to yawn. This is due to yawning images acting as a sign stimulus, which activates the mechanism that triggers the fixed action of yawning. Even though, the latter research is not essentially about modifying individuals’ mental being, there is nevertheless mimicry resulting from observing another person even if the stimulus is merely a picture.
On the contrary, a study conducted by Morewedge, Huh and Vosgerau (2010) proposed that, “perception and mental imagery tend to elicit similar responses” (Morewedge, Huh and Vosgerau, 2010, p. 1531). In their study, when the participants were instructed to repeatedly imagine eating a certain type of food, they tended to consume less food than participants who did not imagine eating food. These results indicate that repeated mental practice about a particular event could habituate one to that event. In comparison to the studies mentioned above, this study proposes a
contrasting view, as it suggests that the participants will not adhere to what is represented in the images, but they will habituate to the stimulus and will behave accordingly to the habituated stimulus. Thus, if one is encouraged to think about sleeping, he or she might habituate to the stimulus (sleep images) and perceive him or herself as being less sleepy or tired.
To relate mental imagery with marketing practices, a study by Babin & Burns (1997) investigated the relationship between mental imagery of non-verbal advertisements (print ads) and its influence on attitude towards the advertisement (Aad) and brand attitude (Ab). The authors hypothesized that images in advertisements have stronger impact on imagery processing and leads to higher attitudinal judgments compared to advertisements with no images. The findings of this study confirmed their hypothesis, advocating that mental imagery solely with images can be used to measure attitudes towards marketing activities.
Lastly, the assumption that evoking mental imagery can also facilitate the surfacing of lay-beliefs related to that imagery is based on the visual system and its dependence on top down processing. Top down processing is when individuals use their knowledge, such as expectations, thoughts and beliefs in order to perceive the information, which is in their environment (Kosslyn, Thompson, & Ganis, 2006).
Thus, when participants are exposed to images of sleep, and hence encouraged to mentally practice sleeping, their cognitive architecture will also take into account sleep-related lay beliefs. The participants are likely to feel sleepier following the images, and might resort to sleep-related lay beliefs to justify their impulsive purchase behavior. The lay belief that is considered to contribute to the process is the one concerning lack of sleep and its effects on self-control and functioning. This lay belief
is assumed to reduce the motivation to evaluate the consequences of one’s choices, diminishing the possibility of the activation of the reflective system, leading to impulsive behavior. Therefore, two hypotheses are formulated. These hypotheses will contribute to answering the following research questions: (1) do sleep images increase perceived feelings of sleepiness, and (2) does perceived sleepiness increase impulsive behavior through generated sleep-related lay beliefs?
Hypothesis 1: The exposure to sleep images increases perceived sleepiness in participants through lay beliefs
Hypothesis 2: If the participants are exposed (not exposed) to sleep images, then they will demonstrate higher (lower) levels of impulsivity.
The next section will provide support for the association between impulsive behavior and risk-taking behavior, and how this association could affect consumers’ purchase behavior.
3.3.
H
OW ISI
MPULSIVEB
EHAVIORR
ELATED TOR
ISK-T
AKINGB
EHAVIOR?
The concepts of risk and impulsivity have been related to each other by Zuckerman and Kulhman (2000) as “the tendency to enter into situations or rapidly respond to cues for potential reward, without much planning or deliberation and without consideration of potential punishment or loss of reward” (Zuckerman & Kulhman, 2000, p. 1000). This suggests that, if someone is basing their decisions on the impulsive mechanism, they are more likely to not consider negative consequences but will more likely focus on immediate rewards (Colet, 2007). Thus, the motivation to achieve immediate gratification can increase the likelihood of engaging in risk-taking behaviors.Moreover, a study conducted by Bickel et al. (2007) suggests that risk-taking behavior occurs when individuals lack self-control. Further, risk-taking takes place when impulsivity undermines the influence of self-control (Bickel et a., 2007). If an individual is impulsive in a particular moment, self-control is necessary for him or her to not engage in a risky behavior. Thus, when individuals are placed in a situation that encourages impulsivity, they are more likely to make riskier choices due to the absence of self-control. On the other hand, it is plausible that an individual can simultaneously experience impulsivity and self-control in a mild manner, which is when they would not choose to involve themselves in a risky behavior (Kuhn, 2013).
The current study deals with the effects of impulsive behavior on risk-taking behaviors related to purchases. More importantly, this study will focus on perceived risk due to the inability to observe participants engaging in impulsive and risky purchases in a real-life setting. Another reason to focus on perceived risk is because it is a determinant of consumer behavior (Yi & Lee, 2008). Perceived risk also contributes to “advertising effectiveness, new product adoption, word-of-mouth, brand loyalty, and store selection” (Yi & Lee, 2008, p. 73).
The following section will elaborate on the concept of perceived risk and its relation to impulsive behavior. Consequently, it will present a hypothesis of how impulsive behavior can affect perceived risk.
3.3.1.HOW CAN IMPULSIVE PURCHASE BEHAVIOR AFFECT PERCEIVED RISK TOWARDS PURCHASES?
Perceived risk towards purchases can be defined as “the expectation of losses associated with purchase, as such, acts as an inhibitor to purchase” (Peter & Ryan, 1976, p. 1985). It is concerned with uncertainty about the outcome, consequences and
importance of loss with regards to the purchase decision (as cited by: Yi & Lee, 2008; Peter & Ryan 1976; Peter and Tarpey, 1975). Dowling and Staeling (1994) suggest that perceived risk increases with higher probability of negative consequences and higher levels of uncertainty.
Moreover, perceived risk is associated with prospect theory (Kahneman & Tversky, 1979). The prospect theory suggests that individuals assess the value of a choice while taking into account the probability of positive or negative consequences of their choice. Thus, the importance of the benefits is compared to the cost of attaining such benefits. This suggests that an individual is engaging in an impulsive decision, he or she might be likely to undervalue the cost and overvalue the benefits, and thus deduce lower levels of perceived risk towards purchase.
Perceived risk is also associated with the concept of risk aversion, where consumers try to avoid negative consequences that may arise from purchasing a product (Bauer, 1960). This means that if perceived risk is low due to impulsive behavior, the consumer is less likely to engage in risk-aversion strategies. Generally, if perceived risk is too high, consumers will look for alternative ways and information to lower the perceived risk (Bettman, 1973). This is one of the reasons why consumers buy products from familiar brands because these brands stimulate perceptions of higher credibility, thus low levels of perceived risk.
Moreover, perceived risk varies depending on the segment of the market and the product class (Paul & Ryan, 1976). A study conducted by Jacoby and Kaplan (1972) measured perceived risk associated with 12 different consumer products. Example of products that represented highest levels of perceived risks were sports cars, life insurances, and television (Jacoby & Kaplan, 1972). The perceived risks to
these specific products were due to risk factors related to performance, financial, psychological, and social aspects. It can be assumed that encouraged impulsivity is less likely to reduce the perceived risk towards luxurious product categories, because anticipated positive affect is merely not enough for the impulsive behavior to transfer to purchase. This is because not every impulsive behavior is irresistible (Rook, 1987) and it is very much dependent on the type of stimulus (Rook & Gardner, 1993; Weun, Jones, and Beatty, 1998). Thus, the effect impulsive behavior on perceived risk depends on product category and its properties.
Regarding product categories, a study conducted by Chiu, Wang, Fang and Huang (2012) investigated the relationship between hedonic and utilitarian value of products and how it can affect repeat purchase intentions. The researchers hypothesized that perceived risk would affect repeat purchase intentions negatively, and would moderate the relationship between utilitarian and hedonic value of products and repeat purchase intentions. The results of the study suggested that perceived risk reduces repeat purchase intentions towards utilitarian products, while increasing purchase intentions towards hedonic products. Moreover, a study conducted by Bornovalova et al. (2009) suggested that if the perceived risk towards a purchase is high, but the consumers are still willing to engage in the purchase, this might cause consumers’ attention and sensitivity towards utilitarian aspects of the product to diminish. The reason why the consumers would still want to engage in the purchase is because of their desire to seek novel experiences. The latter studies are important to take into account as they establish credibility for the current study for exploring the relationship between hedonic and utilitarian product categories and perceived risk.
preference for the hedonic product choice implies a presence of impulsive purchase behavior, which can affect perceived risk towards purchases. The relationship is approached in an inverse manner because the interest of current study is to examine whether consumers’ perceived risk towards purchases could be lowered by encouraging them to act impulsively. Moreover, the premise behind the inverse approach is due to the notion that individuals, who are encouraged to behave impulsively, might be less inclined to evaluate consequences of their purchases. This is because the importance to achieve immediate gratification and positive affect might overtake the degree of losses associated with a purchase. This is based on the effect of emotional arousal on impulse behavior and its ability to increase buying intentions and spending levels (Russel & Pratt, 1980).
From a marketer’s perspective, perceived risk is relevant to take into account to minimize perceived risk amongst consumers towards their products. This is ideal to decrease risk-aversion strategies and search behavior. Moreover, the construct of perceived risk is regarded as a determinant of initial and repeated purchase intentions (Chiu, Wang, Fang & Huang, 2012).
Therefore, based on the literature provided on the interrelationship between the concepts of perceived risk and impulsive purchase behavior, the following hypothesis is formulated. This hypothesis will answer the research question of whether higher impulsivity in purchase behavior leads to lower levels of perceived risk.
Hypothesis 3: If the participants demonstrate higher (lower) levels of impulsive purchase behavior, then their perceived risk towards purchases will be lower (higher).
4.
D
ATAC
OLLECTION ANDM
ETHODOLOGYThe following sections will provide the setting of the experiment, the operationalization of the variables, the data collection plan including the sampling plan, and lastly the methodology used to analyze the outcome of the data collection.
4.1
S
ETTINGThe experiment was created in the online survey platform called Qualtrics. The link obtained from Qualtrics was used to distribute the online survey to the participants. The participants were recruited through approaching them personally via social media. The participants partake in the survey by clicking on the provided link.
The data collection was conducted in the Netherlands. Most of the participants were students, working young adults and working parents. The international background of the author enabled to reach respondents from a variety of different countries and nationalities. It was assumed that the majority of the participants would be of Dutch nationality as it is the location of the data collection and because the personal network of the author mainly consists of students of Dutch nationality. Generally, the sample consisted of participants from a variety of backgrounds and age groups to be representative of the consumers that could engage in impulsive purchase behavior and display perceived risk towards purchases.
The experiment is a simple between-subjects experimental design, which allows examining casual links between the variables. The independent variable is the two conditions (1) sleep images and the (2) control condition where the participants are shown images of objects. There are three dependent variables: (1) perceived sleepiness, (2) impulsive purchase behavior, and (3) perceived risk. The first dependent variable is to measure whether the participants in the two conditions
differed in their level of perceived sleepiness. The second dependent variable is to measure the effect of the two conditions on impulsive purchase behavior. The third dependent variable is to measure the influence of impulsive purchase behavior on perceived risk towards purchases.
The following section will provide a detailed explanation of how the relevant variables in this study were operationalized.
4.2
T
HEV
ARIABLESThis section will provide how the independent variable of the conditions and the dependent variables of perceived sleepiness, impulsive purchase behavior, and perceived risk were operationalized. It will also discuss the control variables necessary to take into account.
4.2.1MANIPULATION OF THE INDEPENDENT VARIABLE OF SLEEP IMAGES
The independent variable of this study is the two condition groups: sleep images or object images (control). The participants were randomly assigned to one of the conditions. The respondents in the sleep-images condition were exposed to images of sleeping individuals, while the respondents in the control condition were exposed to images of objects.
The independent variable of sleep images is hypothesized to affect perceived sleepiness, as images can have a contagious nature that can affect actual behavior (Provine 2005; Wild, Erb & Bartels, 2001). The study conducted by Wild, Erb, and Bartels (2001) used images of faces depicting a variety of emotions as an independent variable to measure the dependent variable of actual experienced emotions. The findings suggested that when individuals saw pictures of happy or sad expressions, they reported feelings that matched with the emotions in the picture. This indicates
that images can be used to influence the attitudes of the participants. Additionally, in his article Provine (2005) focused on yawning and its contagious nature. The author suggested that exposing participants to images of yawning induces the participants to yawn as well. Therefore, the studies conducted by Wild, Erb & Bartels (2001) and Provine (2005) provide support that images can be used as a manipulation for attitudinal or behavioral measurements.
Another justification for using sleep images is to stimulate participants to think about sleeping and thus encourage them to mentally practice sleeping. As mentioned previously, mental practice is defined as “the symbolic rehearsal of a physical activity in the absence of any gross muscular movements” (Driskell, Copper, &Moran, 1994, p. 481). Asking participants to think about or imagine sleeping can trigger a symbolic rehearsal of the physical activity of sleeping. The combination of the contagious nature of sleep images and mental practice of the physical activity of sleeping is hypothesized to increase perceived sleepiness of the participants. The authors Morewedge, Huh, and Vosgerau (2010) suggest a contrary possibility, where they argue that mental practice will result in habituation to the stimulus. Thus, if the respondents mentally practice the physical activity of sleeping by being exposed to sleep images, then they will feel less tired and sleepy. This is in opposition to the hypothesis that sleep images will increase perceived sleepiness, where the sleep images might essentially decrease perceived sleepiness. This is important to take into account during the analysis and interpretation of the results.
Moreover, the mental practice implies a repeated rehearsal of an activity, which is to assure a change in actual performance (Morewedge, Huh and Vosgerau, 2010). Thus, single exposure to an image does not facilitate a cognitive rehearsal of
in the sleep images condition were exposed ten images, each for nine seconds, with three-second intervals between the images. The amount, the timing of the images, and the intervals between the images were identical in the control condition. The justification for the amount of images and the timing of the images and the intervals was to reduce respondent fatigue for subsequent tasks, as well as to ensure completion and response rates. When individuals (N=10) were asked about the ideal amount of sleep images, after ten images, they expressed that they were losing focus and their thoughts were drifting elsewhere.
The context of the selected images for the sleep-images condition is very similar to each other. The images are of individuals sleeping sideways on a bed and facing towards the audience. Any other sleep-related images were not chosen, as mental practice is stimulus-specific (Morewedge, Huh and Vosgerau, 2010). This means the consistency could allow the participants to solely think about the physical activity of sleeping. The random images of objects in the control condition were selected using an online random object generator. The objects are: cardboard box, clay pot, glasses, key chain, rubber bands, rubber duck, scotch tape, sharpie, table, and tweezers (Appendix 1). It was assured that the random objects did not imply any associations related to sleep, comfort or tiredness (e.g. socks, pillows, blankets). The selected ten images in the sleep-images condition included individuals from different ethnic origins and age groups (Appendix 2). This was to ensure that the images are applicable to respondents with different backgrounds and age groups.
In order to measure perceived sleepiness, the Stanford Sleepiness Scale (SSS) developed by Hoddes, Zarcone, Smythe, Philips, and Dement (1973) was used. The scale consists of a single question ‘What best represents how you are feeling right now’ and the respondents answers the question with one the seven statements. The
statements are arranged in terms of a scale in which ‘1’ represents the lowest degree of sleepiness, while ‘7’ represents the highest degree of sleepiness. These statements are (1) Feeling active, vital, alert, or wide awake, (2) Functioning at high levels, but not at peak; able to concentrate, (3) awake, but relaxed; responsive but not fully alert, (4) Somewhat foggy, let down, (5) Foggy; losing interest in remaining awake; slowed down, (6) Sleepy, woozy, fighting sleep; prefer to lie down, and (7) no longer fighting sleep, sleep onset soon; having dream-like thoughts. The Stanford Sleepiness Scale was given to the participants after they were exposed to sleep images or object images depending on their respective condition. This scale has proven to be a valid and a reliable measure in different samples (Alapin, Fichten, Libman, Creti, Bailes, & Wright, 2000; Hoban & Chervin, 2001; Kim & Young, 2005; Pilcher, Schoeling, & Prosansky, 2000).
Additionally, a manipulation check was included that consisted of two identical questions that were asked before and after the participants were randomly allocated to one of the two conditions. These questions were; (1) I feel a little sleepy right now, and (2) I would like to take a nap/get some sleep at the moment. These questions were provided to the author by the supervisor of this thesis. These two sets of questions were included in order to be able to assess whether the participants indicated different levels of perceived sleepiness before and after the manipulation. If the participants indicated a positive difference between the two sets of questions, it was presumed that their level of perceived sleepiness increased.
After the perceived sleepiness questions and the Stanford Sleepiness Scale (SSS) were administered, the participants’ impulsive purchase behavior was assessed.
4.2.2THE MEASUREMENT OF THE DEPENDENT VARIABLE OF IMPULSIVITY
In this research, impulsive behavior is approached as an opposite to rational behavior. Impulsive behavior is presumed to be more of an emotional response than a rational response. When individuals act on their impulses, they do so with high levels of excitement disregarding negative consequences (Rook, 1987). On the contrary, rational decision-making involves a calm evaluation and deliberation of the consequences (Rook, 1987).
The behavioral measures of impulsivity that have been used before include delay discounting task (Richards et al., 1999), go/no task (Newman, Widom, & Nathan, 1985), stop signal task (Logan, Schachar, & Tannock, 1997), balloon analogue risk task (BART, Lejuez et al., 2002). These tasks mainly measure impulsive choice or action. Moreover, several researchers approached impulsive behavior by investigating individual differences in impulsivity, assessing if one has more tendencies to engage in impulsive behaviors than the other. Several self-report measures of personality traits have been developed to measure impulsivity such as the Barratt Impulsiveness Scale-11 (BIS-11; Patton, Stanford, Barratt, 1995), I7 Eysenck Impulsivity inventory and (Eysenck & Eysenck, 1978), Sensation-Seeking Scale (Zuckerman, 1978), and UPPS Impulsive Behavior Scale (Whiteside & Lynam, 2001). Additionally, there are scales that have been developed to measure consumer impulsivity, such as the Consumer Impulsiveness Scale (CIS; Puri, 1996), and Behavioral Impulsiveness Scale (BIS; Rook & Fisher, 1995).
When the different behavioral measures of impulsivity are evaluated, there is an abundance of a scale that measures impulsive behavior in relation to product-related purchases. Therefore, a scale was developed which contains 10 products that are based on an assortment of household (candle, heater, shower head, light-bulb),
hygienic (shower gel, detergent), electronic (headset, laptop, phone case), and food (muesli bar) product categories. The products of laptop, and headset were adapted from a study conducted by Lu, Liu, and Fang (2016). Each product was presented in terms of its hedonic (Product A) and utilitarian option (Product B) on opposite spectrums. A hedonic product is a product that is consumed due to its affective/sensory experience, and entertaining properties (Hirschman and Holbrook, 1982). While, a utilitarian product is instrumental, and its purpose is to satisfy a goal with a particular function. From the differences in definitions of utilitarian and hedonic products, it was assumed that the utilitarian option would be the rational choice, while the hedonic option would be the impulsive choice. The participants were asked on a scale from 1 to 7 (1= very likely to purchase A, 2=likely to purchase A, 3=somewhat likely to purchase A, 4=undecided, 5=somewhat likely to purchase B, 6=likely to purchase B, 7= very likely to purchase B), how likely they are to purchase one product over the other. The scale is provided in Appendix 3.
In this study, a behavioral measure of impulsive purchase behavior is used as studies suggest that self-report scales do not do not correlate with the performance on behavioral tasks of impulsivity (Reynolds, Ortegren, Richards, Wit, 2006). However, the self-report measure called Buying Impulsiveness Scale (BIS) developed by Rook & Fisher (1995) was included as a control variable.
4.2.3THE MEASUREMENT OF THE DEPENDENT VARIABLE OF PERCEIVED RISK
The conceptual definition of perceived risk with regards to consumer behavior is still debatable among researchers (as cited by Mitchell, 1999; Bauer, 1960; Stone & Winter, 1985; Cunningham; 1967; Kogan and Wallach, 1964; Cox, 1967a; Vann, 1985). The findings from the status quo that addresses the concept of perceived risk
