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Impulse buying: a meta-analytic review

Impulse buying: a meta-analytic review Impulse buying by consumers has received considerable attention in consumer research. The phenomenon is interesting because it is not only prompted by a variety of internal psychological factors but also influenced by external, market-related stimuli. The meta-analysis reported in this article integrates findings from 231 samples and more than 75,000 consumers to extend under- standing of the relationship between impulse buying and its determinants, associated with several internal and external factors. Traits (e.g., sensation-seeking, impulse buying tendency), motives (e.g., utilitarian, hedonic), consumer resources (e.g., time, money), and marketing stimuli emerge as key triggers of impulse buying. Consumers’ self-control and mood states mediate and explain the affective and cognitive psychological processes associated with impulse buying. By establishing these pathways and processes, this study helps clarify factors contributing to impulse buying and the role of factors in resisting such impulses. It also explains the inconsistent findings in prior research by highlighting the context-dependency of various determinants. Specifically, the results of a moderator analysis indicate that the impacts of many determinants depend on the consumption context (e.g., product’s identity expression, price level in the industry). . . . . . Keywords Meta-analysis Impulse buying Impulsivity Self-control Mood states Marketing stimuli Consumers spend $5,400 per year on average on impulse pur- impulse buying, defined as episodes in which “a consumer ex- chases of food, clothing, household items, and shoes (O’Brien periences a sudden, often powerful and persistent urge to buy 2018). Thus, there is considerable need to investigate consumer something immediately” (Rook 1987, p. 191). Products pur- chased impulsively often get assigned to a distinct category in marketing texts, yet decades of research reveal that impulsive Mark Houston and John Hulland served as Special Issue Editors for this purchases actually are not restricted to any specific product cat- article. egory. As Rook and Hoch (1985,p.23) assert, “it is the individ- Data were coded and analyzed by the second and third authors. uals, not the products, who experience the impulse to consume.” Academic research that explores the various triggers of * Markus Blut impulse buying consists of three main schools of thought. m.blut@aston.ac.uk First, some scholars argue that individual traits lead con- sumers to engage in impulse buying (e.g., Verplanken and Gopalkrishnan R. Iyer giyer@fau.edu Herabadi 2001). For example, people who are impulsive are more likely to engage in impulse buying (Rook and Hoch Sarah Hong Xiao hong.xiao@durham.ac.uk 1985), whereas those who do not display this trait may be less likely to engage in spontaneous behaviors while shopping. Dhruv Grewal Among the psychological factors that might evoke impulse dgrewal@babson.edu buying, researchers have explored the traits of sensation seek- College of Business, Florida Atlantic University, 777 Glades Road, ing, impulsivity, and representations of self-identity. Second, Boca Raton, FL 33431, USA both motives and resources might drive impulse buying. Aston Business School, Aston University, Aston Triangle, Researchers have identified the effects of two types of motives Birmingham B4 7ET, UK (hedonic and utilitarian), as well as subjective norms, and Durham University Business School, Durham University, Mill Hill argued that mere impulsiveness is often not strong enough to Lane, Durham DH1 3LB, UK trigger impulse buying. Instead, the availability of resources Babson College, 213 Malloy Hall, Babson Park, MA 02457, USA coupled with a failure of self-control also is required to enact J. of the Acad. Mark. Sci. (2020) 48:384–404 385 impulse buying (Baumeister 2002; Hoch and Loewenstein primarily on main effects, whereas we examine moderators 1991). Considerable research has investigated the specific in- and mediators, in addition to the main effects. This scrutiny fluences of different types of resources, including psychic, of the moderating effects also allows us to consider individual time, and money resources (Vohs and Faber 2007), with the relationships rather than pool the effect sizes of all antecedents assumption that resource-based motives, availability, and (Amos et al. 2014) and thus identify stronger and weaker constraints impact consumer impulse buying. Third, some effects. Third, by examining mediating effects, we can test studies focus on the role of marketing drivers, highlight- alternate theory-based relationships of the various antecedents ing how impulse buying can result from store or shelf on impulse buying. The resulting insights help provide a more placements, attractive displays, and in-store promotions. inclusive understanding of impulse buying as compared with This view holds that impulse buying can be influenced, the use of only one theoretical perspective. so retailers invest in marketing instruments designed to trigger it (Mattila and Wirtz 2001). Although these diverse research streams approach impulse Conceptual framework buying from different angles and have established consider- able insights into its triggers, a unified and comprehensive Several determinants of impulse buying appear in prior re- view of the drivers of impulse buying would further enhance search. In line with Dholakia (2000), we explore the effects our understanding. We perform a meta-analysis on an accu- of trait determinants, motives, resources, and marketing stim- mulation of prior empirical research, focusing on disparate uli on impulse buying. Beyond these categories of main ef- drivers and the most impactful antecedents, and the substan- fects, our integrated model explores their impacts through the tive insights obtained from the estimation of effect sizes. Our mediation of self-control and individual emotional states as study can guide further research and the results also could aid well (Mehrabian and Russell 1974). We also account for con- managers in crafting strategies to stimulate impulse purchases textual differences in effects by examining the moderating by targeting the most receptive customers and investing in influences of industry-related characteristics. Furthermore, effective marketing campaigns. In addition to the direct effects we consider the possible influence of study characteristics of various antecedents on impulse buying, our proposed (i.e., impulse buying measure, sample composition, and pub- framework identifies several mediating mechanisms, includ- lication year) on the effects obtained. Our conceptual model is ing self-control (Vohs and Faber 2007) and positive and neg- in Fig. 1, and we offer a summary of the predicted relation- ative emotions (Rook and Gardner 1993). We test the joint ships in Table 1. effects of emotions and self-control, which enables us to spec- ify their concurrent mediating roles, as well as the potential for Determinants of impulse buying serial moderation (i.e., self-control influences emotions). Apart from the typical study moderators, we examine industry Trait and related determinants Several individual traits and moderators—namely, the average price level, advertising, and self-identity may serve as internal sources of impulse buying. distribution intensity in the industry, as well as the identity Psychological impulses strongly influence impulse buying expression capacity of the product category—in line with (Rook 1987;Rook and Hoch 1985), and prior research shows Rook and Fisher’s(1995,p.312) call for “abetter understand- that people who score high on impulsivity trait measures are ing of various contextual factors that are also likely to contrib- more likely to engage in impulse buying (Beatty and Ferrell ute to this relationship [between determinants and impulse 1998; Rook and Fisher 1995; Rook and Gardner 1993). buying].” The precise roles of these moderating variables have Moreover, other traits are also associated with impulse buying not been explored in prior impulse buying studies, and a better and studies in the past have attempted to study their impacts as understanding of their influence can provide new insights and well (e.g., Mowen and Spears 1999;Sharmaetal. 2010). spur further in-depth research. First, we examine the role of sensation-seeking as having a Our use of a meta-analysis is in line with calls in recent direct impact on impulse buying. Sensation-seeking, variety- research (Grewal et al. 2018b; Palmatier et al. 2018)highlight- seeking, novelty-seeking, and similar dispositions are argu- ing the importance of such integrative reviews. An earlier ably distinct from other traits such as impulsivity and reported meta-analysis by Amos et al. (2014) summarized the impacts as contributing to impulse buying (Punj 2011; Sharma et al. of various factors on consumer impulse buying; our review 2014; Van Trijp and Steenkamp 1992). Second, an impulse extends on their work in several ways. First, we recognize the buying tendency, which includes the trait of impulsivity, re- diverse perspectives on impulse buying and the need to obtain flects an enduring disposition to act spontaneously in a spe- a more comprehensive understanding by combining insights cific consumption context. This well-recognized concept cap- from different research streams. To this end, we have sourced tures a relatively enduring consumer trait that produces an extensively and include 186 papers in our meta-analysis, com- urge or motivation for actual impulse buying (Rook and pared with 63 in Amos et al. (2014). Second, Amos et al. focus Fisher 1995). Impulse buying tendencies, are easier to observe 386 J. of the Acad. Mark. Sci. (2020) 48:384–404 Moderators Industry characteriscs Method • Identy-expression of product � Measurement (Rook, non-Rook) Traits (high, low) � Sampling (student, non-student) Sensaon-seeking � Price level in industry (high, low) � Year of study � Adversing intensity (high, low) Impulse buying tendency � Distribuon intensity (high, low) Self-identy Moves Mediang Mechanisms Hedonic moves Ulitarian moves Posive moods Norm Impulse buying Self-control Resources Psychic Negave moods Time/Money Age Gender Markeng Markeng smuli Fig. 1 Meta-analytic framework than other traits and are also highly predictive of impulse Resources Customers with greater psychic resources or inter- buying (Beatty and Ferrell 1998;Rookand Gardner 1993). est in a product category are more likely to engage in impulse Third, buyer-specific beliefs about self-identity and its deficits buying, whereas those who lack the necessary resources (time, influence impulse buying decisions (Dittmar et al. 1995). money) engage less in impulse buying (Hoch and Impulse purchases are more likely to involve items that are Loewenstein 1991; Jones et al. 2003;Kacen andLee 2002). symbolic of a preferred or ideal self as well as products that Age and gender might capture shopping-related resources, offer high identity-expressive potential, to compensate for the such that impulse buying tendencies often are more prevalent buyer’s own identity deficits (Dittmar et al. 1995; Dittmar and among specific social or demographic cohorts (Kacen and Lee Bond 2010). However, contextual factors may play a role on 2002; Tifferet and Herstein 2012; Wood 1998). Drawing from the impacts of such perceptions of identity deficits (e.g., prior research, Kacen and Lee (2002) offer that younger shop- Dittmar et al. 2009). pers may be more likely to buying impulsively while older adults may be better able to regulate their emotions and en- Motives and norms Consumers’ motives, such as hedonic or gage in self-control. utilitarian motives, are important internal sources of impulse Several research and practical observations have highlight- buying that reflect goal-directed arousal, leading to specific ed gender differences in shopping (e.g., Underhill 2000). beliefs about consumption. For example, consumers may be- Dittmar et al. (1995) find that men and women are likely to lieve that buying objects will provide emotional gratification, buy different products to buy impulsively and also use differ- compensation, rewards, or else minimize their negative feel- ent buying considerations when buying on impulse. Also, it ings. Such beliefs may be especially relevant if the objects are has been found that women are more likely as compared to unique and feature a marked opportunity cost, such that they men to experience regret or a mixture of pleasure and guilt need to be purchased immediately (Rook and Fisher 1995; (Coley and Burgess 2003). Vohs and Faber 2007). Norms invoked by consumers about their own impulsiveness Marketing stimuli Marketers deliberately design external stim- also might affect impulse buying decisions. As Rook and Fisher uli to appeal to shoppers’ senses (Eroglu et al. 2003). (1995, p. 307) explain, “consumers’ own prior impulse buying Managers expend substantial time and effort in designing re- experiences may serve as a basis for independent, internalized tail environments and the resulting retail interactions to in- evaluations of impulse buying as either bad or good.” From a crease shoppers’ psychological motivation to purchase self-regulation perspective, when prior impulse buying evokes (Berry et al. 2002; Foxall and Greenley 1999). It has been positive experiences, consumers likely engage in it again, as a estimated that about 62% of in-store purchases are made im- promotion-focused strategy (Verplanken and Sato 2011). pulsively and online buyers are more likely to be impulsive J. of the Acad. Mark. Sci. (2020) 48:384–404 387 Table 1 Expected relationships with impulse buying Variables Expected Relationships Direction Representative Studies Trait-Related Determinants Sensation-seeking Individuals with higher desire to seek novel experiences + Olsen et al. (2016); Sharma et al. (2010) (e.g., sensation seeking, variety seeking, novelty-seeking) are more likely to engage in impulse buying. Impulse buying tendency Traits that reflect urges to act spontaneously, such as + Rook and Fisher (1995); Vohs and impulsivity, have a significant positive effect on impulse Faber (2007) buying. Self-identity Self-identity and its deficits positively influence impulse + Dittmar and Bond (2010) buying behavior. Motives Hedonic motives Hedonic motives have positive effects on consumer impulse +Parketal.(2012); Ramanathan buying behavior. and Menon (2006) Utilitarian motives Utilitarian needs significantly influence impulse buying behavior. ± Park et al. (2012); Norms Normative evaluations influence consumer impulse buying behavior. ± Luo (2005); Rook and Fisher (1995) Resources Psychic Consumers with greater psychic resources towards a product +Jonesetal.(2003); Peck and category are more likely to engage in impulse buying. Childers (2006) Time/Money The availability of time and money influence consumer impulse + Kwon and Armstrong (2002); buying behavior. Stilley et al. (2010) Age Age negatively influences impulse buying behavior. – Verplanken and Herabadi (2001); Thompson and Prendergast (2015) Gender Women are more likely to engage in impulse buying behavior + Coley and Burgess (2003) than men. Marketing Marketing stimuli Marketing stimuli such as discount price, promotion, store + Mattila and Wirtz (2001); ambience, and merchandise have positive effects on impulse Park et al. (2012); Verhagen buying behavior. and van Dolen (2011) Mediators Self-control Self-control mediates the effects of (a) traits, (b) resources, and (c) ± Sultan et al. (2012); Vohs marketing stimuli on impulse buying behavior. Self-control and Faber (2007) influences consumers’ shopping emotions. Verhagen and Positive moods Positive moods mediate the effects of (a) traits, (b) resources, ± Silvera et al. (2008); and (c) marketing stimuli on impulse buying behavior. van Dolen (2011) Negative moods Negative moods mediate the effect of (a) traits, (b) resources, ± Silvera et al. (2008); Verhagen and and (c) marketing stimuli on impulse buying behavior. van Dolen (2011) (Chamorro-Premuzic 2015). Thus, impulse buying can be Self-control as a mediator Countering prior arguments that triggered by various marketing stimuli such as merchandise, impulse purchases stem from irresistible urges, Baumeister communications, store atmospherics, and price discounts (2002) has argued that individuals’ self-control can and do (Mohan et al. 2013). resist such urges. Muraven and Baumeister (2000; p. 247) submit that self-control, or the “control over the self by the Mediators of impulse buying self,” involves attempts by individuals to curb their desires, conform to rules and change how think, feel or act. Also, Baumeister (2002) has established the importance of motives individuals differ in self-control leading to the view that self- and resource depletion for driving impulse buying; therefore, control is an inherent strength or trait (Baumeister 2002). It we also consider whether self-control and emotions might be has also been argued that a failure of self-control could occur triggered. By including these mediating mechanisms in our me- due to conflicting goals, reduction in self-monitoring or de- ta-analysis, we avoid over- or underestimating the importance pletion of mental resources (Baumeister 2002; Verplanken and of various impulse buying triggers. In particular, we assess the Sato 2011). The depletion of mental resources, or “ego deple- joint effects of emotions and self-control, which enables us to tion,” may also be temporal, i.e., more likely to occur at the specify their concurrent mediating roles, as well as the potential end of the day (Baumeister 2002; p. 673). The “ever-shifting for serial mediation (i.e., self-control influences emotions). conflict between desire and willpower” (Vohs and Faber 2007, 388 J. of the Acad. Mark. Sci. (2020) 48:384–404 p. 538) demonstrates the importance of self-control as a key impulsively. Store environments and circumstances such as mediator in the impacts of various antecedents noted in our time and money resources also might prompt negative emo- model and impulse buying. tional reactions (Lucas and Koff 2014; Vohs and Faber 2007), suggesting the need for more empirical evidence to determine Emotions as mediators Environmental psychology research, which emotions are more prominent. and particularly the stimulus–organism–response model pro- The serial mediation of self-control and emotions also de- posed by Mehrabian and Russell (1974), highlights experi- serves examination. The motivational role of self-control also enced emotions as potential mediating constructs. Input vari- suggests that a successful exercise of self-control may also ables such as environmental stimuli or individual traits jointly contribute to positive affect; in other words, individuals with influence individual affective responses, which then induce higher self-control not only resist temptations successfully but response behaviors (Baker et al. 1992). Verplanken and may experience other consequent states such as fewer emo- Herabadi (2001) explain that customers engaging in impulse tional problems and greater life satisfaction (Baumeister 2002; buying tend to display emotions at any point of time during Baumeister et al. 2008; Hofmann et al. 2012;Ticeetal. 2001). the purchase (i.e., before, during, or after). Extant findings are The conceptualization of self-control as a strength and self- somewhat inconsistent though. It has been argued that impulse control failure as ego-depletion (c.f., Baumeister 2002)also buying behavior relates strongly to positive emotions and feel- paves the way for understanding how the exercise of self- ings such that impulse buyers experience more positive emo- control and the unpleasant consequence of self-regulation of tions such as delight and consequently spend more (Beatty a pleasant task may contribute to seeking other pleasurable and Ferrell 1998). Impulse buyers have a strong need for pursuits (Finley and Schemichel 2018). Thus, individuals arousal and experience an emotional lift from persistent repet- may counter the distasteful after-effects of a self-control act itive purchasing behaviors (O'Guinn and Faber 1989; by pursuing opportunities that would contribute to positive Verplanken and Sato 2011). Such arousal even might be a emotions (Finley and Schemichel 2018). This view of self- stronger motive for impulse buying than product ownership control views ego-depletion as a process, whereby the exer- (Dawson et al. 1990). cise of self-control in one time period leads to the individual Rook and Gardner (1993) acknowledge that while pleasure seeking subsequent positive experiences (Finley and is an important precursor, negative mood states such as sad- Schemichel 2018). Another view of self-control offers that ness, can also be associated with impulse buying. For exam- self-control may not be all about inhibitions and restrictions; ple, various studies suggest self-gifting to be a form of retail the trait of self-control may also engage in a promotion focus therapy that helps customers in managing their moods (Mick and thereby engage in initiatory behaviors towards achieving and Demoss 1990;Rook and Gardner 1993; Vohs and Faber the same goal (Cheung et al. 2014). While the above discus- 2007). Other researchers concur that impulse buying can serve sion sheds light on the relationship between self-control and to manage or elevate negative mood states but also suggest positive emotions, there is a lack of clarity in current literature that this influence occurs through a self-regulatory function on the precise direction of the relationship between self- (Rook and Gardner 1993; Verplanken et al. 2005). Thus, emo- control and emotional states relative to impulse buying as well tional states—whether positive or negative—likely affect im- as the impact of self-control on negative emotions. pulse buying, but we find no consensus about whether or how negative moods, positive moods, or both determine impulse Contextual moderators buying uniquely. Finally, research rooted in environmental psychology as- We seek novel insights by examining industry characteristics serts that exposure to environmental stimuli, consumers’ per- as potential contextual moderators. Based on extant studies, sonalities, and personal motives can cause specific (positive or we identify the price levels, advertising, and distribution in- negative) emotional reactions (e.g., Babin et al. 1994; tensity within the industry context as moderators that may Donovan and Rossiter 1982; Mehrabian and Russell 1974). influence the effects of other factors on impulse buying. The These in turn mediate the impacts of personal, situational, and identity expression capability of the products themselves external factors on impulse buying (Parboteeah et al. 2009; could moderate the impacts of the various determinants too. Verhagen and van Dolen 2011). The limited empirical evi- Prior impulse buying studies do not test the effects of these dence on the mediating role of emotions refers to specific moderators; to derive our predictions, we thus turn to relation- contexts; for example, Adelaar et al. (2003) show that plea- ship marketing research that reveals how industry-level vari- sure, dominance, and arousal triggered at the moment of ables determine effectiveness (Fang et al. 2008). Product price purchase mediate the effect of a media format on impulse levels matter, because financial constraints suppress impulse buying intentions online. Verhagen and van Dolen (2011) purchases (Rook and Fisher 1995), and impulse buying trig- found that positive emotions mediate the effects of consumer gers are less effective in more expensive product categories. In beliefs about online stores and their likelihood of buying their meta-analysis, Samaha et al. (2014) find that advertising J. of the Acad. Mark. Sci. (2020) 48:384–404 389 intensity in a specific industry reduces the effectiveness of a sociology, and psychology. We also obtained some unpub- firm’s communication activities. We posit that similarly, im- lished studies from their authors. We sent 159 emails to au- pulse buying triggers may be less effective in industries in thors of published papers seeking at least minimally relevant which all firms invest heavily in advertising, because con- statistics for conducting the analysis. After excluding theoret- sumers are less likely to recognize and consider these various ical papers, qualitative studies, book reviews, studies that triggers. In addition, distribution intensity in an industry might mention but do not measure impulse buying, and studies that influence impulse buying, because the urge to purchase likely do not report the necessary effect sizes, we pared down the list increases when products are rare or exclusive (Troisi et al. of 386 articles to a final data set of 186 articles reporting 2006). Finally, some products are more prone to impulse pur- empirical results. chases, especially if they symbolize a preferred or ideal self We coded each effect size according to the relationship of (Dittmar et al. 1995; Dittmar and Bond 2010). Thus, we an- the independent variables (traits, motives, resources, and mar- ticipate differing effectiveness of impulse buying triggers ac- keting stimuli), the mediators (self-control, positive emotions, cording to the product. and negative emotions) and impulse buying. We also coded the industry and method moderator variables, such that we Method moderators assessed industry characteristics (i.e., product-identity rela- tion, price level, advertising intensity, and distribution inten- Meta-analyses frequently consider the influence of the sity) using the industry description reported by the studies. We methods adopted by the included studies, such as how they similarly coded the method moderators (i.e., study year, mea- measure key constructs, on the strength of the focal relation- surement of impulse buying, and student sample) using infor- ships. Impulse buying studies frequently use different mea- mation provided in each study. Two coders achieved agree- sures for similar constructs; we use the scale for buying im- ment greater than 90% and discussed any inconsistencies, pulse developed by Rook (1987) as a baseline to assess wheth- using the construct definitions in Table 2 to classify all the er other measures perform differently. Meta-analyses also can variables. reveal whether the use of specific samples influences the find- We included studies that reported (1) correlations (r) be- ings (Orsingher et al. 2009). In particular, student samples tween the variables of interest, (2) the standardized regression tend to be more homogeneous than non-student samples and coefficients (beta coefficients), (3) F- or t-values, or (4) fre- thus produce stronger effect sizes. Finally, we assess the quencies, to calculate as as many effect sizes, so as to enhance influence of the study period. The emergence of the the generalizability (Peterson and Brown 2005). Internet and advanced communication technologies have left customers more knowledgeable, with altered expecta- Integration of effect sizes tions of retailers (Blut et al. 2018). Accordingly, we con- sider whether customers’ impulse buying behaviors might Correlation coefficients were used as effect sizes in our meta- have changed over time. analysis. If such coefficients were not reported in the collected studies, we transformed alternative statistics, such as regres- sion coefficients, into correlations (Peterson and Brown Method 2005). Following Peterson and Brown (2005), we imputed correlations from the beta coefficients using the formula: Data collection and coding r = .98β +.05λ with λ =1 when β > 0 and λ = 0 when β <0. Some studies also report more than one correlation for the We collected the data for this study by searching electronic same relationship between two constructs, in which case, we databases, including EBSCO, Proquest, Ingenta Journals, averaged the two correlations and treated them as if they were Elsevier Science Direct, Google Scholar, the web, and several from a single study (Hunter and Schmidt 2004). We did not pertinent leading journals (e.g., Journal of the Academy of have enough effect sizes to include some determinants in all Marketing Science, Journal of Consumer Research, Journal analyses, such as the four marketing stimuli of communica- of Marketing, Journal of Marketing Research). We also iden- tion, price stimuli, store ambience, and merchandise. We tified relevant articles by examining the reference lists of the therefore examined these determinants separately when pos- collected articles. Our search used various terms, including sible and merged them as necessary to include them in other “impulse buying” and “impulsive buying,”“impulsivity,” analyses. If a study had measured more than one of the four “compulsive buying,” and “unplanned buying,” and instruments, we calculated an average effect size for the ag- encompassed titles, abstracts, and keywords. The document gregate marketing stimuli variable. This approach ensures the types included articles and reviews (c.f., book review); the language was English; and the subject areas spanned market- The complete list of studies used in this meta-analysis is available from the ing and advertising, management, business, economics, authors. 390 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 2 Description of constructs in the meta-analysis Determinant Description Aliases Representative Studies Example Operationalization Sensation-seeking A person’s disposition to seek novel experiences sensation-seeking trait, variety seeking Billieux et al. (2010); Lucas Sensation-seeking trait can be measured using Zuckerman’s and sensations regardless of the risks and Koff (2014) (1994) 5-point, 12-item SSS scale that became one factor of involved (Zuckerman 1994). the UPPS scale of Whiteside and Lynam (2001)(e.g., “I will try anything once,” and “I quite enjoy taking risks”); Billieux et al. (2010). Impulse buying tendency An enduring disposition to act impulsively in a impulse buying tendency, Rook and Fisher (1995); Buying impulsiveness uses a 5-point scale containing 9 items given context (Rook and Fisher 1995). impulsiveness, impulsivity Vohs and Faber (2007) (e.g., “I often buy things spontaneously”); Rook and Fisher (1995). Self-identity The subjective concept (or representation) that a self-concept, self-discrepancies (r), Dittmar and Bond (2010); Identity deficit was measured with a participant-generated person holds of her- or himself (Vignoles identity deficits (r) Kwon and Armstrong self-discrepancy index on a 5-point, 5-item scale (e.g., “Iam et al. 2006). (2002) ..., but I would like to be ...”; “I worry about this so much that it is ruining my life”); Dittmar and Bond (2010). Hedonic motives Affective gratification derived from the sensory adventure shopping, experience Herabadi et al. (2009); Park Experience-based shopping motives, measured on 7-point, attribution of a product or service (Hirschman shopping, gratification shopping et al. (2012) 4-item scale (e.g., “I look around at items on the Internet and Holbrook 1982). just for fun.”); Park et al. (2012). Utilitarian motives An inner drive toward direct value seeking, price consciousness Kukar-Kinney et al. (2012); Utilitarian motives, measured on a 7-point, 5-item scale (e.g., economic/functional/practical benefits and Park et al. (2012) “I browse the shopping websites to gather information values (Foxall 2007). about products.”); Park et al. (2012). Norms Informal guideline about what is considered normative beliefs, conformity, Luo (2005); Rook and Fisher Normative beliefs were measured with 10 bipolar adjective normal social behavior in a particular social isolation, peer influence (1995) pairs (e.g., good-bad, rational-crazy, wasteful-productive) unit (Rook and Fisher 1995). for impulse buying scenarios; Rook and Fisher (1995). Psychic resources Degree of thoughts and energy devoted to a product involvement, social Davis and Sajtos (2009); Involvement used an inventory of 10 semantic differential purchase process (e.g., Andrews et al. 1990). involvement, fashion involvement, Jones et al. (2003); items about a product (“Important–Unimportant,”“Matters need for touch to me–doesn’t matter”); Jones et al. (2003). Time/Money Role of resources, such as time and money time availability, time pressure, money Lin and Chen (2013) Time pressure was measured on a 5-point, 3-item scale (e.g. “I availability (e.g., Wood 1998). availability, financial well-being, feel pressured to complete my shopping quickly”); Lin and time pressure Chen (2013). Age Age of the consumer – Zhang et al. (2010) Self-reported age; Zhang et al. (2010). Gender Gender of the consumer – Adelaar et al. (2003); Zhang Self-reported gender; Zhang et al. (2010). et al. (2010) Marketing Degree of persuasion offered by marketing advertising, direct sales, sales person, Park et al. (2012); Zhou and The effect of POP ads was measured on a 7-point scale with 5 stimuli – Communication communication mix (Abratt and Goodey pop-up ads; salesperson; in store Wong (2004) bipolar evaluation items (e.g., “Please describe your 1990) promotional display impression of the in-store POP posters based on your shopping experience today”); Zhou and Wong (2004). Marketing stimuli – Price Price and price promotion organized by firms to lower prices and discounts; sales Kukar-Kinney et al. (2012); Lower prices and discounts used 7-point, 3-item scales (e.g., trigger impulse buying (Grewal and promotion; price/quality ratio Park et al. (2012) “Discounted prices are very cheap in the shopping Marmorstein, 1994) website”); Park et al. (2012). Marketing stimuli – Store Visual and sensory stimuli in online and offline layout and display, sensory attributes, Mohan et al. (2013); Morrin Store layout was measured on a 7-point, 9-item scale referring ambience stores, as perceived by consumers (Sharma visual appeal; and Chebat (2005) to light, music, and layout (e.g., “The store has attractive and Stafford 2000) displays”); Mohan et al. (2013). Marketing Product variety and attributes offered to the variety of selection; attractiveness; new Liu et al. (2013); Park et al. Product availability was measured on a 7-point, 3-item scale stimuli – Merchandise consumer (Park et al. 2012) products; retail offers (2012) (e.g., “There are a sufficient variety of products available for me in online group shopping websites.”); Liu et al. (2013). Self-control Ability to control urges, conform to norms and self-monitoring, self-regulatory Sharma et al. (2014); Vohs Self-monitoring was measured on a 7-point, 5-item scale (e.g., change behavior (Baumeister 2002). resources, lack of self-control and Faber (2007) “I have found that I can adjust my behavior to meet the requirements of any situations I find myself in”); Sharma J. of the Acad. Mark. Sci. (2020) 48:384–404 391 use of only one aggregate marketing stimuli effect size for each study. After transforming and averaging the effect sizes, the total data set in the meta-analysis consists of 968 effect sizes, extracted from 231 samples obtained from 186 articles. The total combined sample includes 75,434 respondents. We used a random-effects approach (Hunter and Schmidt 2004) to calculate the average correlations. Effect sizes were corrected for measurement error in the dependent and independent variables using the coded reliability coefficients. We followed the Hunter and Schmidt (2004)rec- ommendation of dividing the correlations by the product of the square root of the respective reliabilities of the two con- structs involved. Further, reliability-adjusted correlations were weighted by sample size to adjust for sampling error. It has been recommended that reliability-adjusted effect sizes should be transformed into Fisher’s z coefficients before weighting them by sample size (Kirca et al. 2005). This transformation is not without controversies, and some studies suggest that Fisher’s z overestimates true effect sizes by 15%–45% (Field 2001). However, when we compare the results of both ap- proaches, we find no significant differences. Next, for each sample size–weighted and reliability- adjusted correlation, we calculated standard errors and 95% confidence intervals. We used a chi-square test and applied a 75% rule-of-thumb to assess the homogeneity of the effect size distribution (Hunter and Schmidt 2004). To assess the robustness of our results and potential publication bias, we estimated Rosenthal’s(1979) fail-safe N; in other words, the estimation of the number of studies that had null results and therefore not published before the Type I error probability can be brought to a barely significant level (p = .05). We also tested the influence of sample size and effect size outliers on integrated effect sizes, but the results remained largely the same (Geyskens et al. 2009). To assess the practical relevance of the different determinants, we calculated the shared vari- ance with impulse buying for each predictor, as well as the binomial effect size display (BESD) (Grewal et al. 2018b), which indicates the likelihood that a customer (e.g., female) would purchase impulsively compared with a reference group (e.g., male customers). Avalue greater than 1 indicates a great- er relative likelihood, whereas a value lower than 1 signals a lower likelihood. Results Descriptive statistics Direct effects As Table 3 indicates, the averaged effect sizes for most motives, resources, and trait predictors are signifi- cant; however, socio-demographic predictors seem to matter less for impulse buying. We find strong support for the im- pacts of the three trait-related predictors on impulse buying. Table 2 (continued) Determinant Description Aliases Representative Studies Example Operationalization et al. (2014). Positive moods states Intense positive feelings directed at someone or happiness, excitement, pride, pleasure, Cohen and Andrade (2004); Positive moods states, measured on a 6-point, 6-item scale something (Fishbach and Labroo 2007). arousal, joy, glee Weinberg and Gottwald (e.g., stimulating, exciting, inspiring enthusiasm); Weinberg (1982) andGottwald(1982). Negative moods states Intense negative feelings directed at someone or sadness, depression, anger, irritation; Mohan et al. (2013); Negative moods states, measured on a 7-point, 3-item scale something (Fishbach and Labroo 2007). anxiousness, boredom, hurt Weinberg and Gottwald (e.g., “I felt lethargic while shopping today”); Mohan et al. (1982) (2013). Impulse buying Spontaneous purchases made without planning self-reported frequency of impulse Mohan et al. (2013); Rook Impulse buying behavior used two items: “total number of and/or reflecting on consequences (Rook and buying; observed impulse buying and Fisher (1995) items bought on impulse” and the “proportion of items Fisher 1995) behavior bought on impulse”; Mohan et al. (2013). 392 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 3 Descriptive statistics and correlations of predictors with impulse buying Determinants of Impulse Buying Number of Total N Min. z Max. z Sample-Weighted −95% CI +95% CI R BESD Q-Statistic for p File-Drawer N r r Raw Effects Reliability Based lift Homogeneity Adjusted r Test Traits Sensation-seeking 10 2,290 .03 .63 .23* .12 .33 5.2% 59.7% 57 .00 323 Impulse buying tendency 51 14,095 −.46 1.29 .36* .26 .45 12.8% 112.5% 2,172 .00 24,743 Self-identity 12 1,656 −.33 .52 .10† −.03 .23 1.1% 22.2% 82 .00 – Motives Hedonic motives 24 6,979 −.37 1.00 .34* .23 .45 11.7% 103% 602 .00 7,340 Utilitarian motives 10 2,599 −.11 1.10 .36* .06 .60 12.9% 112.5% 479 .00 731 Norm 28 5,953 −.95 1.05 .27* .14 .38 7.1% 74% 707 .00 4,506 Resources Psychic resources 24 5,647 −.27 .69 .18* .08 .27 3.3% 43.9% 328 .00 1,292 Time/Money 21 5,718 .00 1.83 .28* .08 .45 7.7% 77.8% 1,195 .00 2,185 Age 11 3,153 −.44 .19 −.05 −.19 .09 .2% 10.6% 154 .00 – Gender (1 = female) 15 3,687 −.10 .42 .09* .00 .18 .9% 19.8% 114 .00 142 Marketing Marketing stimuli 50 13,910 −.19 .97 .27* .21 .32 7.1% 74% 646 .00 13,952 Communication 18 6,423 −.03 .97 .33* .22 .44 11.0% 98.5% 403 .00 3,302 Price stimuli 13 2,730 −.50 1.26 .27* .07 .44 7.2% 74% 386 .00 1,259 Store ambience 42 10,013 −.05 .97 .23* .17 .28 5.2% 59.7% 405 .00 6,806 Merchandise 11 2,687 −.29 .73 .17* .05 .28 2.8% 41% 77 .00 251 Mediators Self-control 20 3,330 −.83 .55 −.12† −.28 .04 1.5% 27.3% 448 .00 – Positive moods states 30 7,144 .00 1.13 .30* .21 .38 8.8% 85.7% 426 .00 4,173 Negative moods states 15 4,657 −.29 .46 .09* .00 .19 .9% 19.8% 124 .00 149 † p < .10. * p < .05. Notes: The confidence intervals and the file-drawer Ns are based on two-tailed tests. The number of effect sizes of all stimuli combined is lower than the sum of the separate instruments, because we averaged the marketing stimuli per independent sample J. of the Acad. Mark. Sci. (2020) 48:384–404 393 As expected, an individual's tendency to act impulsively has a into one determinant variable and examined its influence in stronger effect than other traits, reflecting its stronger link to the SEM; if a study included two or more marketing stimuli the behaviorofinterest. effects, we averaged them. The proposed model with both Utilitarian and hedonic motives show about equal impacts mediators and the effect of self-control on emotions performs on impulse buying; further research should pay more attention well and displays a good fit (Fig. 2). to these determinants. We find support for gender effects but observe no differences for age. The former results are in line Positive moods The SEM results suggest that positive moods with prior research that suggests women generally are more are important mediators (Fig. 2). Customers with stronger he- likely to purchase impulsively than men (Dittmar et al. 1995). donic motives are more likely to experience positive feelings; However, the insignificant results for age suggests there are customers with utilitarian motives are less likely to experience not many differences between older and younger customers such feelings. Those with favorable subjective norms and high with regard to spending money impulsively. Moreover, we self-control also experience positive moods. These effects are find that marketing stimuli exert a direct influence on cus- new to extant impulse buying literature. Similarly, customers tomers’ impulse buying behavior. When examining the spe- who are generally high in impulsivity experience positive feel- cific marketing instruments, we find the strongest effects for ings. Finally, marketing stimuli relate significantly to positive communication and price stimuli and weaker effects for store feelings, though the effect is relatively weak. ambience and merchandise. Negative moods Negative mood states relate significantly to Mediators We uncover significant effects for emotions and impulse buying, and each of the determinants link to this me- self-control (Table 4). Descriptive statistics were also exam- diator, with the exception of marketing stimuli and self-con- ined to gauge the impact of the predictors on the mediators trol. Customers high in hedonic and utilitarian motives are less (Table 4); 30 of the 39 predictor–mediator relationships (77%) likely to experience negative moods. Favorable subjective are significant. Thus, we obtain a preliminary indication of the norms increase the likelihood of negative feelings. Impulse mediating roles of emotions and self-control, and we can pro- buying tendency is positively related to the experience of neg- ceed to test the proposed mediating effects in the SEM. ative moods. The insignificance of marketing stimuli suggests The shared variances and BESD give some indication of that the stimuli do not trigger negative moods in customers. the practical relevance of different determinants. Using these Self-control also does not reduce the experience of negative criteria, we observe strong effects of impulse buying tenden- emotions. cies, utilitarian motives, and communication. All the signifi- cant relationships are robust to publication bias because the Self-control Unlike mood states, self-control reduces the like- lihood of impulse purchases. This cognition intervenes when file-drawer N is many times greater than the tolerance levels proposed by Rosenthal (1979). We also examined funnel plots customers experience an urge to buy impulsively. According and do not find any indication of publication bias. In all cases, to the SEM results, several predictors either trigger individual the significant chi-square tests of homogeneity suggest awareness of the long-term consequences of spending or re- moderation. assure consumers that spending is acceptable. For example, customers high in impulsivity are less likely to exhibit self- Evaluation of structural equation model control. Subjective norms that encourage impulse buying low- er self-control perceptions, but marketing stimuli serve to in- We tested the mediating effects using structural equation crease self-control. Finally, hedonic and utilitarian motives modeling (SEM) and included variables for which correla- increase self-control perceptions. The positive effect of mar- tions with all other variables could be identified. The complete keting stimuli on self-control suggests that customers are correlation matrix includes correlations between the most of- aware of how firms try to influence them to make them im- ten studied variables in prior research (Table 5). It served as pulsive purchases. the input to LISREL 8.80 and the harmonic mean of all sam- Similar to Pick and Eisend (2014), we tested the impor- ple sizes (N = 1726) was used as input. Since the harmonic tance of mediation effects using two approaches. First, we mean is lower than the arithmetic mean, SEM estimations are examined the ratio of indirect effects to total effects as more conservative (Viswesvaran and Ones 1995). Note that displayed in Table 6. We find significant indirect effects and since each construct had only a single indicator and since high ratios for most determinants, including self-control measurement errors were taken into account when estimating (20%), impulse buying tendency (46%), utilitarian motives the mean effect sizes, the error variances in the SEM could be (34%), norms (49%), and marketing stimuli (39%). Only the set to 0. The different marketing instruments could not be indirect effect of hedonic motives is insignificant, leading to a individually included in the SEM, due to the small number low ratio of indirect effects to total effects (8%). The direct, indirect, and total effects differ for some determinants; self- of effect sizes, so we aggregated all marketing instruments 394 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 4 Descriptive statistics and correlations of predictors with mediators Determinant Number of Total N Min. z Max. z Sample-Weighted −95% CI +95% CI R BESD Q-Statistic for p File-Drawer N r r Raw Effects Reliability Adjusted r Homogeneity Test DV:Self-control(SC) Impulse buying tendency ➔ SC 21 11,110 −1.19 .56 −.12† −.29 .05 1.5% 27.3% 1,567 .00 – Hedonic motives ➔ SC 7 1,820 −.18 .89 .16† −.02 .33 2.6% 38.1% 85 .00 – Utilitarian motives ➔ SC 3 899 .00 .52 .25† −.13 .56 6.0% 66.7% 12 .00 – Norm ➔ SC 3 601 −.78 −.02 −.32† −.63 .09 10.1% 94.1% 53 .00 – Psychic resources ➔ SC 2 538 .01 .34 .18 −.14 .47 3.2% 43.9% 12 .00 – Time/Money ➔ SC 2 2,047 .04 .08 .06* .02 .10 .3% 12.8% 1 .37 3 Age ➔ SC 3 2,142 .00 .33 .24* .13 .34 5.7% 63.2% 10 .01 124 Gender (1 = female) ➔ SC 2 1,196 −.05 .00 −.05† −.10 .01 .2% 10.5% 0 .64 – All marketing stimuli ➔ SC 4 317 .27 .68 .39* .21 .55 15.6% 127.9% 8 .05 52 Communication ➔ SC 1 167 .29 .29 .28* .14 .41 7.8% 77.8%–– 4 Price stimuli ➔ SC 1 90 .27 .27 .26* .06 .44 6.8% 70.3%–– 1 Merchandise ➔ SC 2 60 .68 .68 .59* .40 .73 34.8% 287.8% 0 1.00 13 DV: Positive moods states (PM) General traits ➔ PM 2 570 .47 1.05 .64* .19 .87 40.5% 355.6% 28 .00 112 Impulse buying tendency ➔ PM 25 7,826 −.40 .79 .26* .17 .35 6.8% 70.3% 501 .00 4,681 Self-identity ➔ PM 2 570 −.01 .03 .00 −.08 .08 .0% 0 .71 – Hedonic motives ➔ PM 8 1,979 .25 1.07 .57* .40 .70 32.2% 265.1% 132 .00 1,034 Utilitarian motives ➔ PM 4 899 .25 .62 .30* .20 .38 8.8% 85.7% 4 .21 88 Norm ➔ PM 5 1,036 .05 .73 .27* .04 .47 7.2% 74% 53 .00 84 Psychic resources ➔ PM 7 1,684 .04 .65 .18* .08 .27 3.1% 43.9% 21 .00 94 Time/Money ➔ PM 2 730 .10 .12 .12* .05 .19 1.4% 27.3% 0 .85 4 Gender (1 = female) ➔ PM 1 842 .00 .00 .00 −.07 .07 .0% –– – Marketing stimuli ➔ PM 12 3,289 .01 .69 .40* .27 .50 15.6% 133.3% 152 .00 1,731 Communication ➔ PM 4 1,383 .09 .66 .29* .04 .51 8.6% 81.7% 57 .00 161 Price stimuli ➔ PM 1 401 .60 .60 .54* .47 .61 29.2% 234.8%–– 43 Store ambience ➔ PM 11 3,229 .01 .69 .38* .25 .49 14.3% 122.6% 190 .00 1,751 Merchandise ➔ PM 5 1,205 .15 .62 .34* .21 .46 11.8% 103% 17 .00 188 Self-control ➔ PM 5 1,705 −.06 .85 .37* .09 .59 13.5% 117.5% 108 .00 459 DV: Negative moods states (NM) Impulse buying tendency ➔ NM 15 5,633 −.04 .78 .21* .09 .33 4.5% 53.2% 320 .00 1,704 Hedonic motives ➔ NM 4 1,367 −.73 .07 −.19† −.40 .03 3.7% 46.9% 32 .00 – Utilitarian motives ➔ NM 3 647 −.39 −.15 −.18* −.26 −.09 3.2% 43.9% 2 .35 14 Norm ➔ NM 3 419 −.37 .68 .17 −.50 .71 2.8% 41% 99 .00 – Psychic resources ➔ NM 2 582 −1.38 .01 −.59 −.97 .59 34.7% 287.8% 88 .00 – J. of the Acad. Mark. Sci. (2020) 48:384–404 395 control has a negative direct effect on impulse buying, yet the indirect effect through mediators is positive, which mitigates the total negative effect. Impulse buying tendency has positive direct and indirect effects on impulse buying, such that the total effect is nearly twice as strong as the direct effect. Utilitarian motives have a positive direct effect on impulse buying and a negative indirect effect that lowers the total ef- fect. Norms display a negative direct effect and a positive indirect effect; we observe the opposite effects for marketing stimuli. The mediation model thus provides a clearer view of how these determinants influence impulse buying. Second, we compare the proposed model, which assumes partial mediation effects, with two models with only indirect effects of the determinants through moods and self-control (full mediation). As suggested by Pick and Eisend (2014), we compare the models using a chi-square difference test (Δχ /df). Both full mediation models exhibit significantly worse model fit than the proposed model (mood: Δχ /df = 630.51/6, p < .01; self-control: Δχ /df = 755.28/8, p <.01). Thus, the mediating effects of moods and self-control are par- tial rather than full. Moderator analysis results The need for a moderator analysis was assessed through the chi-square test of homogeneity and a 75% rule (Hunter and Schmidt 2004). The 75% rule indicates that if the proportion of variance in the distribution of effect sizes attributed to sam- pling error and other artifacts is less than 75%, a moderator analysis is warranted. In our results, the chi-square value is significant in all cases, and the 75% rule suggests values lower than 75%, in support of a moderator analysis. We coded sev- eral moderators in our random effects regression model as dummy variables, including the four industry moderators: product identity relation (1 = high expressive, 0 = low expres- sive), price level (1 = high, 0 = low), advertising intensity (1 = high, 0 = low), and distribution intensity (1 = high, 0 = low). For the two method moderators, impulse buying measure (1 = Rook, 0 = non-Rook) and sample (1 = student, 0 = non-stu- dent), we used dummy codes. The year of the study came directly from the articles. Using meta-regression procedures suggested by Lipsey and Wilson (2001) and the provided macros, we assess the influence of the moderators in our model with random- effects regression (Hunter and Schmidt 2004). Using reliability-corrected correlations as the dependent variable, we conducted tests of the moderators for 18 predictor vari- ables and regressed correlations on four industry variables and For example, grocery retailing involves low product identity relation, low price level, high advertising intensity, and high distribution intensity; the lux- ury car industry was coded as high product identity relation, high price level, low advertising intensity, and low distribution intensity. Table 4 (continued) Determinant Number of Total N Min. z Max. z Sample-Weighted −95% CI +95% CI R BESD Q-Statistic for p File-Drawer N r r Raw Effects Reliability Adjusted r Homogeneity Test Gender (1 = female) ➔ NM 1 842 .01 .01 .01 −.06 .08 .0% 2% –– – Marketing stimuli ➔ NM 6 1,529 −.63 .81 −.06 −.37 .26 .4% 12.8% 152 .00 – Communication ➔ NM 3 937 −.20 .81 .18 −.49 .71 3.2% 43.9% 139 .00 – Store ambience ➔ NM 4 1,302 −.51 .07 −.13† −.27 .01 1.8% 29.9% 26 .00 – Merchandise ➔ NM 3 592 −.63 .10 −.27 −.67 .26 7.0% 74% 24 .00 – Self-control ➔ NM 7 1,917 −.74 .02 −.29* −.50 −.05 8.5% 81.7% 156 .00 166 Positive moods states ➔ NM 11 4,251 −.71 .21 −.23* −.37 −.08 5.3% 59.7% 227 .00 420 † p < .10. * p < .05. Notes: The confidence intervals and the file-drawer Ns are based on two-tailed tests. PM = positive mood; NM = negative mood; SC = self-control. The table only displays predictors for which effect sizes can be calculated 396 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 5 Correlations among latent constructs Construct Impulse Buying Hedonic Utilitarian Norm Marketing Self-Control Positive Negative Impulse Tendency Motives Motives Stimuli Mood Moods Buying States States 1. Impulse buying [.88] 31 12 26 34 21 25 15 51 tendency 2. Hedonic motives .36 [.89] 9 6 14 7 8 4 24 3. Utilitarian motives .16 .42 [.94] 2 6 3 4 3 10 4. Norm .33 .39 .55 [.87] 8 3 5 3 28 5. Marketing stimuli .29 .33 .38 .21 [.91] 4 12 6 50 6. Self-control −.12 .16 .25 −.32 .39 [.91] 5 7 20 7. Positive moods states .26 .57 .30 .27 .40 .37 [.91] 11 30 8. Negative moods states .21 −.19 −.18 .17 −.06 −.29 −.23 [.90] 15 9. Impulse buying .36 .34 .36 .27 .27 −.12 .30 .09 [.94] Harmonic mean across all collected effects is 1,726. Entries on the diagonal in brackets are weighted mean Cronbach’s alpha coefficients. Entries in the lower half are sample-weighted reliability adjusted correlations; the upper half shows the number of effect sizes. The marketing stimuli effects were averaged three method variables. To test moderation effects, we ensured greater advertising intensity, but norms, psychic resources, that at least 10 effect sizes were available (Samaha et al. 2014). and store ambience matter less. Product identification We confirm a moderating influence of Distribution intensity Product availabilityinanindustryde- product identification (Table 7). If a product’s expressiveness pends on its distribution intensity. For example, Dholakia is high (i.e., product identity is coded as 1 for high expressive- (2000) explains that physical proximity is essential for the ness), some predictors lose their relevance, including self- experience of an impulsive urge, but a product that is unusu- identity and subjective norms. Products that facilitate consum- ally difficult to purchase may be more appealing to customers er self-expression are more likely to be bought impulsively, than products that are available everywhere. We anticipated because they represent a preferred or ideal self (Dittmar et al. and find that at least some impulse buying predictors, such as 1995; Dittmar and Bond 2010). Products with high expres- utilitarian motives, psychic resources, merchandise, and neg- siveness also suppress the effects of norms. In these condi- ative mood states, become less effective when a product is tions, other determinants become less effective. However, more widely available. Moreover, communication gains rele- some determinants related to communication and negative vance with greater distribution intensity. feelings gain importance, because consumers are very sensi- tive with regard to their self-perceptions. Method moderators When examining the moderating influ- ence of the method adopted in the different studies, we find Price level As expected, the average price level of products in an that several predictors, such as impulse buying tendency and industry buffers the impacts of several predictors. Most predic- utilitarian motives, gain importance over time. We do not ob- tors lose some relevance when prices are high (i.e., price level is serve a specific pattern for the measures employed. The results coded as 1), including sensation-seeking, impulse buying ten- with regard to the measures used in the studies suggest that the dency, hedonic motives, utilitarian motives, psychic resources, widely employed Rook scale performs as well as alternative and positive moods. Only self-control gains importance, in line impulse buying measures. We also find generally weaker ef- with our reasoning. Higher prices alert consumers to the finan- fects in studies using student samples. In further meta- cial consequences of their urge to buy impulsively, making these regression models, we assessed the influence of country cul- determinants less effective (but self-control more effective). ture and emerging markets but do not find notable differences. Advertising intensity The influence of advertising is quite in- teresting. On the one hand, it appears to increase desire for Implications and directions for further certain products, so some predictors gain relevance. On the research other hand, the predictors may lose relevance, because prod- ucts seem less unique when they are advertised everywhere. This meta-analysis aims to provide a comprehensive and co- Negative moods and merchandise gain importance with herent understanding of impulse buying behavior, by J. of the Acad. Mark. Sci. (2020) 48:384–404 397 .11* .14* .07* Impulse buying -.14* tendency Posive moods .24* .33* .41* Hedonic moves .17* .43* -.29* -.20* -.53* .43* Ulitarian moves Self-control Impulse buying -.28* .32* .19* Norms -.65* .34* .09* Negave moods .35* Markeng smuli .17* .54* -.44* Fig. 2 Results of the structural equation model. Notes: A dotted line indicates that the path is not significant. Model fit: χ /1 = 67.74; confirmatory fit index = .99; goodness-of-fit index = .99; root mean residual = .02; standardized root mean residual = .02 synthesizing previous research. Our meta-analytic review buying and highlight the context-dependency of impulse buy- seeks deeper insights into impulse buying, and our compre- ing research. These meta-analysis results in turn suggest sev- hensive model of impulse buying integrates constructs and eral implications for practice and directions for further relationships from studies over the past four decades of em- research. pirical research on impulse buying. The results from our meta- analysis provide new insights into the impacts of various an- Managerial implications tecedent factors and call particular attention to the tensions between the inherent urge to buy impulsively and the con- Consumer buying on impulse has long been an area of interest straints and control on such buying impulses. Also, the results for managers; even a small proportion of impulse purchases clarify the impacts of marketing stimuli on consumer impulse on each shopping trip or a small base of impulse shoppers can Table 6 Direct, indirect, and total Determinants of Impulse Buying Direct Indirect Total Indirect/Total (%) effects Positive moods states .33 – .33 – Negative moods states .19 – .19 – Self-control −.53 .13 −.40 20% Impulse buying tendency .14 .12 .26 46% Hedonic motives .11 .01 .13 8% Utilitarian motives .54 −.28 .25 34% Norm −.44 .42 -.02 49% Marketing stimuli .17 −.11 .06 39% Average 33% Not significant (p > .05); all other effects were significant at p < .05. Notes: D = direct effect; I = indirect effect; T = total effect; % = relative importance of indirect effects 398 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 7 Results of moderator analysis Determinants of Impulse Product- Identity Price Advertising Distribution Year Controls R Buying Relation Level Intensity Intensity Rook Student (non-Rook) (non-student) kB B B B B B B Traits Sensation-seeking 10 .18 −.63* −.22 .35 .11 .40† −.82* 65% Impulse buying tendency 48 .09 −.45* .11 −.19 .35* −.09 −.21† 38% Self-identity 12 −.50* −.35 −.39 .04 −.56* 47% Motives Hedonic motives 24 .19 −.43* .31 −.16 .17 −.03 .24 34% Utilitarian motives 10 .34 −.81* .38 −.88* .61* −.53 69% Norm 28 −.52* .07 −.33† .16 −.12 .37 −.04 45% Resources Psychic resources 24 −.14 −.87* −.38* −.36* .11 −.29* −.23* 68% Time/Money 21 −.17 −.16 .38 −.02 .38 −.17 .16 23% Age 11 −.51 .20 .43 .43 −.40 .13 .32 18% Gender (1 = female) 15 −.29 .28 .31 −.46 .06 .34† .55* 42% Marketing Marketing stimuli 50 .01 −.03 −.16 −.07 .18 −.08 −.11 6% Communication 18 .96* .17 −.16 .77* .32† −.35† .00 46% Price stimuli 13 .41 −.27 −.66 .65 .51 −.11 −.49* 44% Store ambience 42 −.13 −.04 −.36* −.09 .09 .06 −.13 19% Merchandise 11 −.25 −.26 .49* −.94* −.07 −.41 44% Mediators Self-control 20 .11 −.41* −.30 −.14 .28 −.34 −.17 33% Positive moods states 28 −.15 −.87* .08 −.29 .64* .85* −.26 36% Negative moods states 13 .61* .06 .20* −.30* −.11 .71* −.40* 86% * p < .05. † p < .10. The table shows standardized coefficients. For some relationships, advertising intensity and distribution intensity moderators were tested in two separate regression models, together with all other moderators. The table reports the averaged results across these models, as suggested by Samaha et al. (2014) for cases of high correlations between moderators. A positive (negative) coefficient indicates that the effect size is stronger (weaker) for studies with high (low) values of the moderator. For example, impulse buying tendency has a positive effect on impulse buying; the negative coefficient indicates that this relationship is weaker in industries with high price levels. When interpreting the moderating effects for self-control, note that the main effect is negative. A dash (―) indicates that a moderator could not be tested due to the low number of available effect sizes for a specific study characteristic. Similar to Samaha et al. (2014), we tested moderators that appeared with 10 or more effect sizes contribute significant annual incremental sales (Rostoks so retailers should devise new, unique marketing stimuli to 2003). It is therefore important to identify not just which con- convey the value of their offerings and encourage impulse sumers may be more inclined to purchase on impulse but also buying. Yet not all marketing stimuli are equally effective. specific environmental factors that may prompt and encourage Communication and price stimuli are more effective in impulse buying. Impulse purchases can increase retail sales prompting impulse buying than are store ambience and mer- (top-line) and profits (bottom-line), especially for high-margin chandise. Although retailers often devote considerable ex- products. As summarized in Table 8, our results suggest penses to store design, store atmosphere, store layout, and employing a variety of marketing strategies. merchandise placement, they may be better off investing more In their attempt to devise strategies to encourage impulse in price promotions and advertising, which likely have stron- shopping and/or promote impulse buying behaviors, retailers ger impulse buying effects. have not been averse to making large investments in market- An important practical insight from this meta-analysis is ing stimuli, such as merchandising, displays, lighting, music, that though marketing mix stimuli have positive impacts on and other environmental factors that might trigger impulse impulse buying, they also heighten awareness of such tenden- purchases (Mattila and Wirtz 2001). Our review acknowl- cies and thus may curb impulse buying overall. This finding edges that impulse buying can be triggered by external factors, suggests consumers are becoming increasingly familiar with J. of the Acad. Mark. Sci. (2020) 48:384–404 399 Table 8 Summary of managerial Issues Implications implications Marketing Stimuli • Retailers need to devise new, unique marketing stimuli to convey the value of their offers and encourage impulse buying. • Communication and price stimuli are more effective than store ambience and merchandise, so managers should invest more in price promotion and advertising campaigns. Traits, Motives and Resources • Identification of the impulse buying–prone customers is possible, and appropriate promotional offers could be devised to attract them. • Likelihood of impulse buying is shaped by traits such as impulsivity and other factors internal to consumers, not as much by readily observable characteristics such as age and gender. Therefore, primary research is required to identify impulse buying customers. • Motivational factors are much more important than controllable marketing stimuli, and therefore, stores and offers need to be designed to match shopper motives. • Consumer resources such as time and money affect impulse buying, so encouraging impulse buying may require reducing the impacts of resource constraints. Mechanisms • Self-control mechanisms can curb impulse buying. Public policy makers need to understand the types of marketing messages and labels that can be designed to curb unhealthy impulse buying. • Norms affect impulse buying, so managers can focus communication strategies on social norms to reassure customers of impulse purchases. • Positive emotions increase impulse buying, so attractive store environments and merchandise cues are important to stimulate impulse buying. • Negative emotions also affect impulse buying; impulse buying that does not stretch consumer resources could be promoted to lift consumer moods. Context • The impacts of consumer traits, motives, and resources are moderated by industry characteristics; managers should understand how their industry context would affect consumer impulse buying. • When product–identity relationships are strong, a greater focus should be on communications, among the various marketing stimuli. Prompts for impulse buying are less effective in industries with higher price levels. • The determinants of impulse buying such as impulse buying tendency and self-identity gain and lose relevance over time, so managers should revisit their assumptions and strategies periodically. firms’ tactics to persuade them to buy impulsively and skep- also specify situations that enable it. That is, marketers could tical of various marketing practices. For practitioners, these identify a distinct impulse buying segment and then design the findings may be somewhat discouraging; impulse buying is shopping environment to make their impulse buying more not simply a response to marketing stimuli, and psychological, likely. In some challenging findings though, we show that social, and situational variables also have impacts. Additional demographics such as age and gender matter less for research is warranted to understand how shopper skepticism predicting impulse buying, so retailers likely need to under- evoked by marketing tactics might inhibit impulse buying. take deeper research into consumer psychographics to identify Retailers may need to try harder to devise unique or new an impulse buying segment. marketing stimuli that can get past consumers’ defenses and Shopping motives, whether hedonic or utilitarian, also convey the value of their offers. matter when it comes to impulse buying. These motives The identification of an impulse buying segment of cus- are inherent to the consumer, so marketers should de- tomers would be of great importance to retailers that currently sign stores and offers to evoke and facilitate appropriate rely solely on marketing stimuli. But if impulse buying were motives. Yet consumers’ resource constraints (e.g., time, only trait driven, marketing strategy would have no effect on money) curb their buying impulses, so marketers also impulse purchases. The good news from our meta-analysis is could focus on devising tactics to reduce the impacts that impulse buying is triggered by both factors internal to of resource constraints. For example, access to speedy consumers and external marketing stimuli. Thus, it may be financing and faster checkouts likely help mitigate credit possible to identify consumers prone to impulse buying but and time constraints. 400 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 9 Impulse buying research Issues Research Directions agenda Main Effects • It would be beneficial to explicitly test and quantify the magnitude of the effects of specific marketing stimuli factors. For example, store effects are driven by a host of store elements, such as display, lighting, and music. • Effects of different marketing stimuli should be tested not only against one another but also assessed for uniqueness within the industry. Different stimuli appear online (e.g., social media) versus offline (e.g., retail store). • The meta-analysis indicates a rather weak effect of self-identity. Scholars should assess different identity scales and examine different types of consumer identities. • Positive moods are more influential than negative moods. Future studies could explore if negative moods might be stronger than positive moods in some cases, such as when trait variables exert direct effects on moods but also have moderating effects. • We could not differentiate types of norms, but certain social groups such as family and friends could be more influential than others. Furthermore, some social groups (e.g., friends) might encourage impulse buying, while others discourage it (e.g., family). • We assessed time and money constraints in aggregate but lacked data to assess differential effects of time and money. Research on the “time versus money effect” could explain differences between time and money constraints, as well as when time dominates money effects and vice versa. • We examine the impacts of various factors on impulse buying; further meta-studies could examining its consequences (e.g., cognitive dissonance, regret). Interactive Effects • The meta-analysis demonstrates the importance of the main effects of the various factors. It would be helpful to gain more insights on the interactive effects of traits, motives, resources, and marketing stimuli. Mechanisms • The mediating role of other mechanisms, such as greater in-store attention and sensory mechanisms (e.g., greater visual and tactile responses), on the effects of the selected independent variables on impulse buying needs to be explored. Contextual Cues • Other contextual cues, such as type of trip, stage (beginning vs. end), and the decision stage (search vs. purchase), all need to be tested. • The role of private versus public consumption could be an important moderator. • Other demographic variables (e.g., education, household size, number of children) warrant additional research, because they could drive the magnitude of impulse buying. • Most current studies do not consider whether shoppers are alone or accompanied by somebody. Further research could explore this individual shopping context to determine the effects on impulse buying. Type of Methodology • A majority of studies use surveys and examine correlational data. The effects of various marketing stimuli factors, motives, and resources on impulse buying could be explored using experimental designs, to support causal inferences. • Research needs to explore effects using longitudinal, as opposed to cross-sectional, data. The use of panel data sets might provide enhanced insights. • Eye-tracking could be used to understand impulse buying and obtain greater insights into the role of marketing stimuli, attention, and impulse buying. Do marketing stimuli result in greater impulse buying due to greater or lesser attention devoted to the stimuli (e.g., less attention to price, labels)? • Qualitative research could shed light on why some of our findings conflict with theoretical predictions. Consumers with high self-control and those influenced by impulsive purchases that may lead to later regret and consum- social norms also may be less prone to impulse buying, be- er dissatisfaction. Ultimately, marketers must choose between cause the uninhibited urge to buy impulsively is curbed by making an immediate sale that might produce consumer dis- self-control and social norms. Understanding these restrictions satisfaction and exhibiting concern for the consumer to en- can help ethical marketers develop stimuli that both facilitate courage future patronage. Similarly, both positive and nega- unplanned purchases but discourage purely uninhibited, tive emotions enhance impulse buying, and ethical marketers J. of the Acad. Mark. Sci. (2020) 48:384–404 401 should leverage affective strategies to encourage impulsive as consumer decision stage, whether consumption is pri- purchases that align with available consumer resources. vate or public, demographic variables, and whether the Public policy makers also might take heed of self-control, shopper is alone or accompanied by someone (Table 9). norms, and emotions to devise policies to reduce unhealthy Such contextual cues should function as moderators in impulse buying. future studies to help reveal how various antecedent fac- Because industry characteristics also matter in impulse tors affect impulse buying. buying, managers need to understand how the industry con- Studies exploring impulse buying also tend to use sur- text moderates the impacts of various consumer traits, mo- veys and examine correlational data. Such descriptive tives, and resources on impulse buying. Even if impulse buy- analyses provide generalizable insights, though manipula- ing is common in industries with low price levels, our findings tions of various marketing stimuli, motives, and resources caution that it is not the only relevant industry context; rather, in experiments also could enable causal inferences. impulse buying also occurs when product–identity relation- Longitudinal research that relies on panel data could also ships are strong. In such contexts, marketers should place reveal how consumer motives and resources interact with due emphasis on communications that encourage impulse the context to prompt impulse buying. New technologies, buying. such as eye-tracking methods, could demonstrate the spe- cific impacts of marketing stimuli (e.g., product place- Directions for research ments) and how consumers’ attentionpaidtovarious de- tails in the shopping environment contributes to their im- Our meta-analysis, while revealing, was restricted given the pulse buying. Finally, we find some evidence that is con- lack of sufficient studies testing and/or reporting all possible tradictory with theoretical predictions, so qualitative re- effects in all possible contexts using multiple methods. In ex- search would be helpful to explain why. ploring the main effects of various factors on impulse buying (Fig. 1), we had to use aggregations in several cases, due to the Conclusion insufficient number of effects available in prior research. Future studies should undertake explicit examinations of each effect, Our meta-analytic review aims to provide empirically gener- especially specific marketing stimuli, self-identity, positive and alizable, robust findings pertaining to the impacts of various negative moods, specific types of social norms, and consumer antecedents of impulse buying, its potential mediators, and the resources. The most glaring deficiencies in prior research pro- moderators of these relationships. As a unique feature, our vide the bases for our recommendations for further research, meta-analysis includes a test of alternate theoretical perspec- which we detail in Table 9 and summarize briefly here. tives that previously have sought to explain impulse buying. We indicate the effects of various individual drivers, in- As Palmatier et al. (2007) attest, on the basis of their compar- cluding marketing stimuli, on impulse buying in Table 3, ative consideration of multiple theoretical perspectives on in- which suggests an important facilitating role for impulse buy- terorganizational relationships, various perspectives could re- ing. We test the individual impacts of traits, motives, re- ceive empirical support individually, but their relative impacts sources, and stimuli on impulse buying, but interactions cannot be determined unless all explanatory perspectives are among these antecedents also could be influential. For exam- subjected to a comparative test. With the greater number of ple, experimental research might determine how the effects of effects sizes available for each model, achieved by compiling traits, motives, and resources on impulse buying are moderat- data for the meta-analysis, our comparative test of various ed by marketing stimuli (e.g., communication, price, store perspectives on impulse buying brings the relative impacts ambience, merchandise elements). The size of the motive ef- of various dominant explanatory factors in each perspective fects (r = .34 for hedonic, r = .36 for utilitarian) implies their into sharper relief. potential significance; they could be activated by communica- In summary, our meta-analysis explores the direct effects of tions delivered to customers in stores, using digital displays consumer traits, motives, and resources and marketing stimuli (Roggeveen et al. 2016) or mobile devices (Grewal et al. on impulse buying, along with the mediating impacts of self- 2018a). Furthermore, the synergistic effects of various com- control and positive and negative emotions. Our joint exami- munication and promotional elements on impulse buying war- nation of these mediators reveals the inner affective and cog- rant further exploration. nitive psychological processes of impulse buying and their Most studies make assumptions about the context, rath- relations. Industry and method moderators also influence im- er than actively manipulating or exploring its effects. In pulse buying. This meta-analysis provides a comprehensive most cases, the context refers solely to the product cate- summary of extant research, underlying various implications. gory (e.g., food, beauty products), shopping environment We hope it also sheds some new lights on directions for re- (e.g., retail store, online), or industry (grocery, apparel). search that can continue to enhance our understanding of im- But various other contextual cues could be relevant, such pulse buying. 402 J. of the Acad. Mark. Sci. (2020) 48:384–404 Open Access This article is distributed under the terms of the Creative Dholakia, U. M. (2000). Temptation and resistance: An integrated model Commons Attribution 4.0 International License (http:// of consumption impulse formation and enactment. Psychology & creativecommons.org/licenses/by/4.0/), which permits unrestricted use, Marketing, 17(11), 955–982. distribution, and reproduction in any medium, provided you give appro- Dittmar, H., & Bond, R. (2010). I want it and I want it Now': Using a priate credit to the original author(s) and the source, provide a link to the temporal discounting paradigm to examine predictors of consumer Creative Commons license, and indicate if changes were made. impulsivity. British Journal of Psychology, 101(4), 751–776. Dittmar, H., Beattie, J., & Friese, S. (1995). Gender identity and material symbols: Objects and decision considerations in impulse purchases. Journal of Economic Psychology, 16(3), 491–511. References Dittmar, H., Halliwell, E., & Stirling, E. (2009). Understanding the im- pact of thin media models on Women’s body-focused affect: The Abratt, R., & Goodey, S. D. (1990). Unplanned buying and in-store roles of thin-ideal internalization and weight-related self-discrepan- stimuli in supermarkets. Managerial and Decision Economics, cy activation in experimental exposure effects. Journal of Social and 11(2), 111–121. Clinical Psychology, 28(1), 43–75. Adelaar, T., Chang, S., Lancendorfer, K. M., Lee, B., & Morimoto, M. Donovan, R. J., & Rossiter, J. R. (1982). Store atmosphere: An environ- (2003). Effects of media formats on emotions and impulse buying mental psychology approach. Journal of Retailing, 58(1), 34–57. intent. Journal of Information Technology, 18(4), 247–266. Eroglu, S. A., Machleit, K. A., & Davis, L. A. (2003). Empirical testing of Amos, C., Holmes, G. R., & Keneson, W. C. (2014). A meta-analysis of a model of online store atmospherics and shopper responses. consumer impulse buying. Journal of Retailing and Consumer Psychology & Marketing, 20(2), 139–150. Services, 21(2), 86–97. Fang, E., Palmatier, R. W., & Steenkamp, J. E. M. (2008). Effect of Andrews, J. C., Durvasula, S., & Akhter, S. H. (1990). A framework for service transition strategies on firm value. Journal of Marketing, conceptualizing and measuring the involvement construct in adver- 72(5), 1–14. tising research. Journal of Advertising, 19(4), 27–40. Field, A. P. (2001). Meta-analysis of correlation coefficients: A Monte Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Carlo comparison of fixed- and random-effects models. Measuring hedonic and utilitarian shopping value. Journal of Psychological Methods, 6,161–180. Consumer Research, 20(4), 644–656. Finley, A. J., & Schemichel, B. J. (2018). Aftereffects of self-control on Baker, J., Levy, M. L., & Grewal, D. (1992). An experimental approach to positive emotional reactivity. Personality and Social Psychology make retail store environmental decisions. Journal of Retailing, Bulletin, 45, 1011–1027. https://doi.org/10.1177/ 68(4), 445–460. 0146167218802836. Baumeister, R. F. (2002). Yielding to temptation: Self-control failure, Fishbach, A., & Labroo, A. A. (2007). Be better or be merry: How mood impulsive purchasing, and consumer behavior. Journal of affects self-control. Journal of Personality and Social Psychology, Consumer Research, 28(4), 670–676. 93(2), 158–173. Baumeister, R. F., Sparks, E. A., Stillman, T. F., & Vohs, K. D. (2008). Foxall, G. R. (2007). Explaining Consumer Choice. Basingstoke: Free will in consumer behavior: Self-control, Ego depletion, and Palgrave Macmillan. choice. Journal of Consumer Psychology, 18(1), 4–13. Foxall, G. R., & Greenley, G. E. (1999). Consumers' emotional responses Beatty, S., & Ferrell, M. E. (1998). Impulse buying: Modeling its precur- to service environments. Journal of Business Research, 46(2), 149– sors. Journal of Retailing, 74(2), 169–191. 158. Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service Geyskens, I., Krishnan, R., Steenkamp, J. E. M., & Cunha, P. V. (2009). A convenience. Journal of Marketing, 66(3), 1–17. review and evaluation of meta-analysis practices in management Billieux, J., Gay, P., Rochat, L., & Van der Linden, M. (2010). The role of research. JournalofManagement, 35(2), 393–419. urgency and its underlying psychological mechanisms in problem- Grewal, D., & Marmorstein, H. (1994). Market price variation, perceived atic behaviours. Behaviour Research and Therapy, 48(11), 1085– price variation, and consumers' price search decisions for durable goods. Journal of Consumer Research, 21(3), 453–460. Blut, M., Teller, C., & Floh, A. (2018). Testing retail marketing-mix Grewal, D., Ahlbom, C., Beitelspacher, L. S., Noble, S. M., & Nordfalt, J. effects on patronage: A meta-analysis. JournalofRetailing,94(2), (2018a). In-store Mobile phone use and customer shopping behav- 113–135. ior: Evidence from the field. Journal of Marketing., 82(4), 102–126. Chamorro-Premuzic, T. (2015), The Psychology of Impulsive Shopping, Grewal, D., Puccinelli, N., & Monroe, K. B. (2018b). Meta-analysis: The Guardian,November26, https://www.theguardian.com/media- Integrating accumulating knowledge. Journal of the Academy of network/2015/nov/26/psychology-impulsive-shopping-christmas- Marketing Science, 46(1), 9–30. black-friday-sales [Accessed March 13, 2019]. Herabadi, A. G., Verplanken, B., & Van Knippenberg, A. (2009). Cheung, T. L., Gillebaart, M., Kroese, F., & Ridder, D. D. (2014). Why Consumption experience of impulse buying in Indonesia: are people with higher self-control happier? The effect of trait self- Emotional arousal and hedonistic considerations. Asian Journal of control on happiness as mediated by regulatory focus. Frontiers in Social Psychology, 12(1), 20–31. Psychology, 5(July). https://doi.org/10.3389/fpsyg.2014.00722. Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: Cohen, J. B., & Andrade, E. B. (2004). Affective intuition and task- Emerging concepts, methods and propositions. Journal of contingent affect regulation. Journal of Consumer Research, Marketing, 46(Summer), 92–101. 31(2), 358–367. Hoch, S. J., & Loewenstein, G. F. (1991). Time-inconsistent preferences Coley, A., & Burgess, B. (2003). Gender differences in cognitive and and consumer self-control. JournalofConsumerResearch, 17(4), affective impulse buying. Journal of Fashion Marketing and 429–507. Management, 7(3), 282–295. Hofmann, W., Baumeister, R. F., Förster, G., & Vohs, K. D. (2012). Davis, R., & Sajtos, L. (2009). Anytime, anywhere: Measuring the ubiq- Everyday temptations: An experience sampling study of desire, con- uitous Consumer's impulse purchase behavior. International flict, and self-control. Journal of Personality and Social Psychology, JournalofMobile Marketing,4(1), 15–22. 102(6), 1318–1325. Dawson, S., Bloch, P. H., & Ridgway, N. M. (1990). Shopping motives, Hunter,J.E., &Schmidt,F.L.(2004). Methods of meta-analysis: Correcting error and Bias in research findings. Thousand Oaks: emotional states, and retail outcomes. Journal of Retailing, 66- Sage Publications. (winter), 408–427. J. of the Acad. Mark. Sci. (2020) 48:384–404 403 Jones, M. A., Reynolds, K. E., Weun, S., & Beatty, S. E. (2003). The Palmatier, R. W., Houston, M. B., & Hulland, J. (2018). Review articles: Purpose, process, and structure. Journal of the Academy of product-specific nature of impulse buying tendency. Journal of Business Research, 56(7), 505–511. Marketing Science, 46(1), 1–8. Kacen, J. J., & Lee, J. A. (2002). The influence of culture on consumer Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of impulsive buying behavior. Journal of Consumer Psychology, website characteristics on a Consumer's urge to buy impulsively. 12(2), 163–176. Information Systems Research, 20(1), 60–78. Park, E. J., Kim, E. Y., Funches, V. M., & Foxx, W. (2012). Apparel Kirca, A. H., Jayachandran, S., & Bearden, W. O. (2005). Market orien- tation: A meta-analytic review and assessment of its antecedents and product attributes, web browsing, and E-impulse buying on shop- impact on performance. Journal of Marketing, 69(2), 24–41. ping websites. Journal of Business Research, 65(11), 1583–1589. Kukar-Kinney, M., Ridgway, N. M., & Monroe, K. B. (2012). The role of Peck, J., & Childers, T. L. (2006). If I touch it I have to have it: Individual Price in the behavior and purchase decisions of compulsive buyers. and environmental influences on impulse purchasing. Journal of Journal of Retailing, 88(1), 63–71. Business Research, 59(6), 765–769. Kwon, H. H., & Armstrong, K. L. (2002). Factors influencing impulse Peterson, R. A., & Brown, S. P. (2005). On the use of Beta coefficients in buying of sport team licensed merchandise. Sport Marketing meta-analysis. Journal of Applied Psychology, 90(1), 175–181. Quarterly, 11(3), 151–163. Pick, D., & Eisend, M. (2014). Buyers’ perceived switching costs and Lin, Y. H., & Chen, C. F. (2013). Passengers' shopping motivations and switching: A meta-analytic assessment of their antecedents. Journal commercial activities at airports–the moderating effects of time pres- of the Academy of Marketing Science, 42(2), 186–204. sure and impulse buying tendency. Tourism Management, 36,426– Punj, G. (2011). Impulse buying and variety seeking: Similarities and 434. differences. Journal of Business Research, 64(7), 745–748. Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Ramanathan, S., & Menon, G. (2006). Time-varying effects of chronic Thousand Oaks: Sage. hedonic goals on impulsive behavior. Journal of Marketing Liu, Y., Li, H., & Hu, F. (2013). Website attributes in urging online Research, 43(4), 628–641. impulse purchase: An empirical investigation on consumer percep- Roggeveen, A. L., Nordfalt, J., & Grewal, D. (2016). Do digital displays tions. Decision Support Systems, 55(3), 829–837. enhance sales? Role of retail format and message content. Journal of Lucas, M., & Koff, E. (2014). The role of impulsivity and of self- Retailing, 92(1), 122–13 perceived attractiveness in impulse buying in women. Personality Rook, D. W. (1987). The buying impulse. Journal of Consumer Individual Differences, 56(January), 111–115. Research, 14(2), 189–199. Luo, X. (2005). How does shopping with others influence impulsive Rook, D. W., & Fisher, R. J. (1995). Normative influences on impulsive purchasing? JournalofConsumerPsychology, 15(4), 288–294. buying behavior. Journal of Consumer Research, 22(3), 305–313. Mattila, A. S., & Wirtz, J. (2001). Congruency of scent and music as a Rook, D. W., & Gardner, M. P. (1993). In the mood: Impulsive Buyings’ driver of in-store evaluations and behavior. Journal of Retailing, antecedents. In J. Arnold-Costa & R. W. Belk (Eds.), Research in 77(2), 272–289. consumer behavior (pp. 1–28). Greenwich: JAI Press. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental Rook, D. W., & Hoch, S. J. (1985). Consuming Impulses. In E. C. psychology. Cambridge: MIT Press. Hirschman & M. B. Holbrook (Eds.), Advances in consumer Mick, D. G., & Demoss, M. (1990). Self-gifts: Phenomenological in- research (pp. 23–27). Chicago, IL: Association for Consumer sights from four contexts. Journal of Consumer Research, 17(3), Research, 23-27). 322–332. Rosenthal, R. (1979). The 'File drawer Problem' and tolerance for null Mohan, G., Sivakumaran, B., & Sharma, P. (2013). Impact of store envi- results. Psychological Bulletin, 86(3), 638–641. ronment on impulse buying behavior. European Journal of Rostoks, L. (2003). Tapping into the shopper impulse. Canadian Grocer, Marketing, 47(10), 1711–1732. 117(October), 34–35. Morrin, M., & Chebat, J. C. (2005). Person-place congruency: The inter- Samaha, S. A., Beck, J. T., & Palmatier, R. W. (2014). The role of culture active effects of shopper style and atmospherics on consumer ex- in international relationship marketing. JournalofMarketing, 78(5), penditures. Journal of Service Research, 8(2), 181–191. 78–98. Mowen, J. C., & Spears, N. (1999). Understanding compulsive buying Sharma, A., & Stafford, T. F. (2000). The Effect of Retail Atmospherics among college students: A hierarchical approach. Journal of on Customers' Perceptions of Salespeople and Customer Persuasion: Consumer Psychology, 8(4), 407–430. An Empirical Investigation. Journal of Business Research, 49(2), Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion 183–191. Sharma, P., Sivakumaran, B., & Marshall, R. (2010). Impulse buying and of limited resources: Does self-control resemble a muscle?. Psychological Bulletin, 126(2), 247–259. variety seeking: A trait-correlates perspective. Journal of Business Research, 63(3), 276–283. O’Brien, S. (2018). Consumers Cough Up $5,400 a Year on Impulse Purchases. CNBC.com, February 23, Retrieved July 30, 2018 from Sharma, P., Sivakumaran, B., & Marshall, R. (2014a). Looking beyond impulse buying: A cross-cultural and multi-domain investigation of https://www.cnbc.com/2018/02/23/consumers-cough-up-5400-a- consumer impulsiveness. European Journal of Marketing, 48(5/6), year-on-impulse-purchases.html. Accessed 30 Jul 2018. 1159–1179. O'Guinn, T. C., & Faber, R. J. (1989). Compulsive buying: A phenome- Silvera, D. H., Lavack, A. M., & Kropp, F. (2008). Impulse buying: the nological exploration. Journal of Consumer Research, 16(2), 147– 157. role of affect, social influence, and subjective wellbeing. Journal of Consumer Marketing, 25(1), 23–33. Olsen, S. O., Tudoran, A. A., Honkanen, P., & Verplanken, B. (2016). Stilley, K. M., Inman, J. J., & Wakefield, K. L. (2010). Planning to make Differences and similarities between impulse buying and variety seeking: A personality-based perspective. Psychology & unplanned purchases? The role of in-store slack in budget deviation. Journal of Consumer Research, 37(2), 264–278. Marketing, 33(1), 36–47. Orsingher, C., Valentini, S., & Angelis, M. (2009). A meta-analysis of Sultan, A. J., Joireman, J., & Sprott, D. E. (2012). Building consumer self-control: The effect of self-control exercises on impulse buying satisfaction with complaint handling in services. Journal of the Academy of Marketing Science, 38(2), 169–186. urges. Marketing Letters, 23(1), 61–72. Palmatier, R. W., Dant, R. P., & Grewal, D. (2007). A comparative lon- Thompson, E. R., & Prendergast, G. P. (2015). The influence of trait affect and the five-factor personality model on impulse buying. gitudinal analysis of theoretical perspectives of Interorganizational relationship performance. Journal of Marketing, 71(4), 172–194. Personality and Individual Differences, 76,216–221. 404 J. of the Acad. Mark. Sci. (2020) 48:384–404 Tice, D. M., Bratslavsky, E., & Baumeister, R. F. (2001). identity construction. Journal of Personality and Social Psychology, 90(2), 308–333. Emotional distress regulation takes precedence over impulse control: If you feel bad, do it! Journal of Personality and Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psy- Social Psychology, 80(1), 53–67. chometric meta-analysis and structural equations modeling. Personnel Psychology, 48(4), 865–885. Tifferet, S., & Herstein, R. (2012). Gender differences in brand commit- Vohs, K. D., & Faber, R. J. (2007). Spent resources: Self-regulatory ment, impulse buying, and hedonic consumption. Journal of resource availability affects impulse buying. Journal of Consumer Product and Brand Management, 21(3), 176–182. Research, 33(4), 537–547. Troisi, J. D., Christopher, A. C., & Marek, P. (2006). Materialism and Weinberg, P., & Gottwald, W. (1982). Impulsive consumer buying as a money spending disposition as predictors of economic and person- result of emotions. Journal of Business Research, 10(1), 43–57. ality variables. North American Journal of Psychology, 8(3), 421– Whiteside, S. P., & Lynam, D. R. (2001). The five factor model and impulsivity: Using a structural model of personality to under- Underhill, P. (2000). Why we buy: The science of shopping.New York: stand impulsivity. Personality and Individual Differences, Simon and Schuster. 30(4), 669–689. Van Trijp, H. C. M., & Steenkamp, J. E. M. (1992). Consumers' variety Wood, M. (1998). Socio-economic status, delay of gratification, and im- seeking tendency with respect to foods: Measurement and manage- pulse buying. Journal of Economic Psychology, 19(3), 295–320. rial implications. European Review of Agricultural Economics, Zhang, Y., Winterich, K. P., & Mittal, V. (2010). Power distance belief 19(2), 181–195. and impulsive buying. Journal of Marketing Research, 47(5), 945– Verhagen, T., & van Dolen, W. (2011). The influence of online store beliefs on consumer online impulse buying: A model and empirical Zhou, L., & Wong, A. (2004). Consumer impulse buying and in-store application. Information and Management, 48(8), 320–327. stimuli in Chinese supermarkets. Journal of International Consumer Verplanken, B., & Herabadi, A. (2001). Individual differences in impulse Marketing, 16(2), 37–53. buying tendency: Feeling and no thinking. European Journal of Zuckerman, M. (1994). Behavioral expressions and biosocial bases of Personality, 15(1), 71–83. sensation seeking. Cambridge: Cambridge University Press. Verplanken, B., & Sato, A. (2011). The psychology of impulse buying: An integrative self-regulation approach. Journal of Consumer Policy, 34(2), 197–210. Verplanken, B., Herabadi, A. G., Perry, J. A., & Silvera, D. H. (2005). Consumer style and health: The role of impulsive buying in un- Publisher’snote Springer Nature remains neutral with regard to healthy eating. Psychology & Health, 20(4), 429–441. jurisdictional claims in published maps and institutional affiliations. Vignoles, V. L., Regalia, C., Manzi, C., Golledge, J., & Scabini, E. (2006). Beyond self-esteem: Influence of multiple motives on http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the Academy of Marketing Science Springer Journals

Impulse buying: a meta-analytic review

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Business and Management; Business and Management, general; Marketing; Social Sciences, general
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Abstract

Impulse buying by consumers has received considerable attention in consumer research. The phenomenon is interesting because it is not only prompted by a variety of internal psychological factors but also influenced by external, market-related stimuli. The meta-analysis reported in this article integrates findings from 231 samples and more than 75,000 consumers to extend under- standing of the relationship between impulse buying and its determinants, associated with several internal and external factors. Traits (e.g., sensation-seeking, impulse buying tendency), motives (e.g., utilitarian, hedonic), consumer resources (e.g., time, money), and marketing stimuli emerge as key triggers of impulse buying. Consumers’ self-control and mood states mediate and explain the affective and cognitive psychological processes associated with impulse buying. By establishing these pathways and processes, this study helps clarify factors contributing to impulse buying and the role of factors in resisting such impulses. It also explains the inconsistent findings in prior research by highlighting the context-dependency of various determinants. Specifically, the results of a moderator analysis indicate that the impacts of many determinants depend on the consumption context (e.g., product’s identity expression, price level in the industry). . . . . . Keywords Meta-analysis Impulse buying Impulsivity Self-control Mood states Marketing stimuli Consumers spend $5,400 per year on average on impulse pur- impulse buying, defined as episodes in which “a consumer ex- chases of food, clothing, household items, and shoes (O’Brien periences a sudden, often powerful and persistent urge to buy 2018). Thus, there is considerable need to investigate consumer something immediately” (Rook 1987, p. 191). Products pur- chased impulsively often get assigned to a distinct category in marketing texts, yet decades of research reveal that impulsive Mark Houston and John Hulland served as Special Issue Editors for this purchases actually are not restricted to any specific product cat- article. egory. As Rook and Hoch (1985,p.23) assert, “it is the individ- Data were coded and analyzed by the second and third authors. uals, not the products, who experience the impulse to consume.” Academic research that explores the various triggers of * Markus Blut impulse buying consists of three main schools of thought. m.blut@aston.ac.uk First, some scholars argue that individual traits lead con- sumers to engage in impulse buying (e.g., Verplanken and Gopalkrishnan R. Iyer giyer@fau.edu Herabadi 2001). For example, people who are impulsive are more likely to engage in impulse buying (Rook and Hoch Sarah Hong Xiao hong.xiao@durham.ac.uk 1985), whereas those who do not display this trait may be less likely to engage in spontaneous behaviors while shopping. Dhruv Grewal Among the psychological factors that might evoke impulse dgrewal@babson.edu buying, researchers have explored the traits of sensation seek- College of Business, Florida Atlantic University, 777 Glades Road, ing, impulsivity, and representations of self-identity. Second, Boca Raton, FL 33431, USA both motives and resources might drive impulse buying. Aston Business School, Aston University, Aston Triangle, Researchers have identified the effects of two types of motives Birmingham B4 7ET, UK (hedonic and utilitarian), as well as subjective norms, and Durham University Business School, Durham University, Mill Hill argued that mere impulsiveness is often not strong enough to Lane, Durham DH1 3LB, UK trigger impulse buying. Instead, the availability of resources Babson College, 213 Malloy Hall, Babson Park, MA 02457, USA coupled with a failure of self-control also is required to enact J. of the Acad. Mark. Sci. (2020) 48:384–404 385 impulse buying (Baumeister 2002; Hoch and Loewenstein primarily on main effects, whereas we examine moderators 1991). Considerable research has investigated the specific in- and mediators, in addition to the main effects. This scrutiny fluences of different types of resources, including psychic, of the moderating effects also allows us to consider individual time, and money resources (Vohs and Faber 2007), with the relationships rather than pool the effect sizes of all antecedents assumption that resource-based motives, availability, and (Amos et al. 2014) and thus identify stronger and weaker constraints impact consumer impulse buying. Third, some effects. Third, by examining mediating effects, we can test studies focus on the role of marketing drivers, highlight- alternate theory-based relationships of the various antecedents ing how impulse buying can result from store or shelf on impulse buying. The resulting insights help provide a more placements, attractive displays, and in-store promotions. inclusive understanding of impulse buying as compared with This view holds that impulse buying can be influenced, the use of only one theoretical perspective. so retailers invest in marketing instruments designed to trigger it (Mattila and Wirtz 2001). Although these diverse research streams approach impulse Conceptual framework buying from different angles and have established consider- able insights into its triggers, a unified and comprehensive Several determinants of impulse buying appear in prior re- view of the drivers of impulse buying would further enhance search. In line with Dholakia (2000), we explore the effects our understanding. We perform a meta-analysis on an accu- of trait determinants, motives, resources, and marketing stim- mulation of prior empirical research, focusing on disparate uli on impulse buying. Beyond these categories of main ef- drivers and the most impactful antecedents, and the substan- fects, our integrated model explores their impacts through the tive insights obtained from the estimation of effect sizes. Our mediation of self-control and individual emotional states as study can guide further research and the results also could aid well (Mehrabian and Russell 1974). We also account for con- managers in crafting strategies to stimulate impulse purchases textual differences in effects by examining the moderating by targeting the most receptive customers and investing in influences of industry-related characteristics. Furthermore, effective marketing campaigns. In addition to the direct effects we consider the possible influence of study characteristics of various antecedents on impulse buying, our proposed (i.e., impulse buying measure, sample composition, and pub- framework identifies several mediating mechanisms, includ- lication year) on the effects obtained. Our conceptual model is ing self-control (Vohs and Faber 2007) and positive and neg- in Fig. 1, and we offer a summary of the predicted relation- ative emotions (Rook and Gardner 1993). We test the joint ships in Table 1. effects of emotions and self-control, which enables us to spec- ify their concurrent mediating roles, as well as the potential for Determinants of impulse buying serial moderation (i.e., self-control influences emotions). Apart from the typical study moderators, we examine industry Trait and related determinants Several individual traits and moderators—namely, the average price level, advertising, and self-identity may serve as internal sources of impulse buying. distribution intensity in the industry, as well as the identity Psychological impulses strongly influence impulse buying expression capacity of the product category—in line with (Rook 1987;Rook and Hoch 1985), and prior research shows Rook and Fisher’s(1995,p.312) call for “abetter understand- that people who score high on impulsivity trait measures are ing of various contextual factors that are also likely to contrib- more likely to engage in impulse buying (Beatty and Ferrell ute to this relationship [between determinants and impulse 1998; Rook and Fisher 1995; Rook and Gardner 1993). buying].” The precise roles of these moderating variables have Moreover, other traits are also associated with impulse buying not been explored in prior impulse buying studies, and a better and studies in the past have attempted to study their impacts as understanding of their influence can provide new insights and well (e.g., Mowen and Spears 1999;Sharmaetal. 2010). spur further in-depth research. First, we examine the role of sensation-seeking as having a Our use of a meta-analysis is in line with calls in recent direct impact on impulse buying. Sensation-seeking, variety- research (Grewal et al. 2018b; Palmatier et al. 2018)highlight- seeking, novelty-seeking, and similar dispositions are argu- ing the importance of such integrative reviews. An earlier ably distinct from other traits such as impulsivity and reported meta-analysis by Amos et al. (2014) summarized the impacts as contributing to impulse buying (Punj 2011; Sharma et al. of various factors on consumer impulse buying; our review 2014; Van Trijp and Steenkamp 1992). Second, an impulse extends on their work in several ways. First, we recognize the buying tendency, which includes the trait of impulsivity, re- diverse perspectives on impulse buying and the need to obtain flects an enduring disposition to act spontaneously in a spe- a more comprehensive understanding by combining insights cific consumption context. This well-recognized concept cap- from different research streams. To this end, we have sourced tures a relatively enduring consumer trait that produces an extensively and include 186 papers in our meta-analysis, com- urge or motivation for actual impulse buying (Rook and pared with 63 in Amos et al. (2014). Second, Amos et al. focus Fisher 1995). Impulse buying tendencies, are easier to observe 386 J. of the Acad. Mark. Sci. (2020) 48:384–404 Moderators Industry characteriscs Method • Identy-expression of product � Measurement (Rook, non-Rook) Traits (high, low) � Sampling (student, non-student) Sensaon-seeking � Price level in industry (high, low) � Year of study � Adversing intensity (high, low) Impulse buying tendency � Distribuon intensity (high, low) Self-identy Moves Mediang Mechanisms Hedonic moves Ulitarian moves Posive moods Norm Impulse buying Self-control Resources Psychic Negave moods Time/Money Age Gender Markeng Markeng smuli Fig. 1 Meta-analytic framework than other traits and are also highly predictive of impulse Resources Customers with greater psychic resources or inter- buying (Beatty and Ferrell 1998;Rookand Gardner 1993). est in a product category are more likely to engage in impulse Third, buyer-specific beliefs about self-identity and its deficits buying, whereas those who lack the necessary resources (time, influence impulse buying decisions (Dittmar et al. 1995). money) engage less in impulse buying (Hoch and Impulse purchases are more likely to involve items that are Loewenstein 1991; Jones et al. 2003;Kacen andLee 2002). symbolic of a preferred or ideal self as well as products that Age and gender might capture shopping-related resources, offer high identity-expressive potential, to compensate for the such that impulse buying tendencies often are more prevalent buyer’s own identity deficits (Dittmar et al. 1995; Dittmar and among specific social or demographic cohorts (Kacen and Lee Bond 2010). However, contextual factors may play a role on 2002; Tifferet and Herstein 2012; Wood 1998). Drawing from the impacts of such perceptions of identity deficits (e.g., prior research, Kacen and Lee (2002) offer that younger shop- Dittmar et al. 2009). pers may be more likely to buying impulsively while older adults may be better able to regulate their emotions and en- Motives and norms Consumers’ motives, such as hedonic or gage in self-control. utilitarian motives, are important internal sources of impulse Several research and practical observations have highlight- buying that reflect goal-directed arousal, leading to specific ed gender differences in shopping (e.g., Underhill 2000). beliefs about consumption. For example, consumers may be- Dittmar et al. (1995) find that men and women are likely to lieve that buying objects will provide emotional gratification, buy different products to buy impulsively and also use differ- compensation, rewards, or else minimize their negative feel- ent buying considerations when buying on impulse. Also, it ings. Such beliefs may be especially relevant if the objects are has been found that women are more likely as compared to unique and feature a marked opportunity cost, such that they men to experience regret or a mixture of pleasure and guilt need to be purchased immediately (Rook and Fisher 1995; (Coley and Burgess 2003). Vohs and Faber 2007). Norms invoked by consumers about their own impulsiveness Marketing stimuli Marketers deliberately design external stim- also might affect impulse buying decisions. As Rook and Fisher uli to appeal to shoppers’ senses (Eroglu et al. 2003). (1995, p. 307) explain, “consumers’ own prior impulse buying Managers expend substantial time and effort in designing re- experiences may serve as a basis for independent, internalized tail environments and the resulting retail interactions to in- evaluations of impulse buying as either bad or good.” From a crease shoppers’ psychological motivation to purchase self-regulation perspective, when prior impulse buying evokes (Berry et al. 2002; Foxall and Greenley 1999). It has been positive experiences, consumers likely engage in it again, as a estimated that about 62% of in-store purchases are made im- promotion-focused strategy (Verplanken and Sato 2011). pulsively and online buyers are more likely to be impulsive J. of the Acad. Mark. Sci. (2020) 48:384–404 387 Table 1 Expected relationships with impulse buying Variables Expected Relationships Direction Representative Studies Trait-Related Determinants Sensation-seeking Individuals with higher desire to seek novel experiences + Olsen et al. (2016); Sharma et al. (2010) (e.g., sensation seeking, variety seeking, novelty-seeking) are more likely to engage in impulse buying. Impulse buying tendency Traits that reflect urges to act spontaneously, such as + Rook and Fisher (1995); Vohs and impulsivity, have a significant positive effect on impulse Faber (2007) buying. Self-identity Self-identity and its deficits positively influence impulse + Dittmar and Bond (2010) buying behavior. Motives Hedonic motives Hedonic motives have positive effects on consumer impulse +Parketal.(2012); Ramanathan buying behavior. and Menon (2006) Utilitarian motives Utilitarian needs significantly influence impulse buying behavior. ± Park et al. (2012); Norms Normative evaluations influence consumer impulse buying behavior. ± Luo (2005); Rook and Fisher (1995) Resources Psychic Consumers with greater psychic resources towards a product +Jonesetal.(2003); Peck and category are more likely to engage in impulse buying. Childers (2006) Time/Money The availability of time and money influence consumer impulse + Kwon and Armstrong (2002); buying behavior. Stilley et al. (2010) Age Age negatively influences impulse buying behavior. – Verplanken and Herabadi (2001); Thompson and Prendergast (2015) Gender Women are more likely to engage in impulse buying behavior + Coley and Burgess (2003) than men. Marketing Marketing stimuli Marketing stimuli such as discount price, promotion, store + Mattila and Wirtz (2001); ambience, and merchandise have positive effects on impulse Park et al. (2012); Verhagen buying behavior. and van Dolen (2011) Mediators Self-control Self-control mediates the effects of (a) traits, (b) resources, and (c) ± Sultan et al. (2012); Vohs marketing stimuli on impulse buying behavior. Self-control and Faber (2007) influences consumers’ shopping emotions. Verhagen and Positive moods Positive moods mediate the effects of (a) traits, (b) resources, ± Silvera et al. (2008); and (c) marketing stimuli on impulse buying behavior. van Dolen (2011) Negative moods Negative moods mediate the effect of (a) traits, (b) resources, ± Silvera et al. (2008); Verhagen and and (c) marketing stimuli on impulse buying behavior. van Dolen (2011) (Chamorro-Premuzic 2015). Thus, impulse buying can be Self-control as a mediator Countering prior arguments that triggered by various marketing stimuli such as merchandise, impulse purchases stem from irresistible urges, Baumeister communications, store atmospherics, and price discounts (2002) has argued that individuals’ self-control can and do (Mohan et al. 2013). resist such urges. Muraven and Baumeister (2000; p. 247) submit that self-control, or the “control over the self by the Mediators of impulse buying self,” involves attempts by individuals to curb their desires, conform to rules and change how think, feel or act. Also, Baumeister (2002) has established the importance of motives individuals differ in self-control leading to the view that self- and resource depletion for driving impulse buying; therefore, control is an inherent strength or trait (Baumeister 2002). It we also consider whether self-control and emotions might be has also been argued that a failure of self-control could occur triggered. By including these mediating mechanisms in our me- due to conflicting goals, reduction in self-monitoring or de- ta-analysis, we avoid over- or underestimating the importance pletion of mental resources (Baumeister 2002; Verplanken and of various impulse buying triggers. In particular, we assess the Sato 2011). The depletion of mental resources, or “ego deple- joint effects of emotions and self-control, which enables us to tion,” may also be temporal, i.e., more likely to occur at the specify their concurrent mediating roles, as well as the potential end of the day (Baumeister 2002; p. 673). The “ever-shifting for serial mediation (i.e., self-control influences emotions). conflict between desire and willpower” (Vohs and Faber 2007, 388 J. of the Acad. Mark. Sci. (2020) 48:384–404 p. 538) demonstrates the importance of self-control as a key impulsively. Store environments and circumstances such as mediator in the impacts of various antecedents noted in our time and money resources also might prompt negative emo- model and impulse buying. tional reactions (Lucas and Koff 2014; Vohs and Faber 2007), suggesting the need for more empirical evidence to determine Emotions as mediators Environmental psychology research, which emotions are more prominent. and particularly the stimulus–organism–response model pro- The serial mediation of self-control and emotions also de- posed by Mehrabian and Russell (1974), highlights experi- serves examination. The motivational role of self-control also enced emotions as potential mediating constructs. Input vari- suggests that a successful exercise of self-control may also ables such as environmental stimuli or individual traits jointly contribute to positive affect; in other words, individuals with influence individual affective responses, which then induce higher self-control not only resist temptations successfully but response behaviors (Baker et al. 1992). Verplanken and may experience other consequent states such as fewer emo- Herabadi (2001) explain that customers engaging in impulse tional problems and greater life satisfaction (Baumeister 2002; buying tend to display emotions at any point of time during Baumeister et al. 2008; Hofmann et al. 2012;Ticeetal. 2001). the purchase (i.e., before, during, or after). Extant findings are The conceptualization of self-control as a strength and self- somewhat inconsistent though. It has been argued that impulse control failure as ego-depletion (c.f., Baumeister 2002)also buying behavior relates strongly to positive emotions and feel- paves the way for understanding how the exercise of self- ings such that impulse buyers experience more positive emo- control and the unpleasant consequence of self-regulation of tions such as delight and consequently spend more (Beatty a pleasant task may contribute to seeking other pleasurable and Ferrell 1998). Impulse buyers have a strong need for pursuits (Finley and Schemichel 2018). Thus, individuals arousal and experience an emotional lift from persistent repet- may counter the distasteful after-effects of a self-control act itive purchasing behaviors (O'Guinn and Faber 1989; by pursuing opportunities that would contribute to positive Verplanken and Sato 2011). Such arousal even might be a emotions (Finley and Schemichel 2018). This view of self- stronger motive for impulse buying than product ownership control views ego-depletion as a process, whereby the exer- (Dawson et al. 1990). cise of self-control in one time period leads to the individual Rook and Gardner (1993) acknowledge that while pleasure seeking subsequent positive experiences (Finley and is an important precursor, negative mood states such as sad- Schemichel 2018). Another view of self-control offers that ness, can also be associated with impulse buying. For exam- self-control may not be all about inhibitions and restrictions; ple, various studies suggest self-gifting to be a form of retail the trait of self-control may also engage in a promotion focus therapy that helps customers in managing their moods (Mick and thereby engage in initiatory behaviors towards achieving and Demoss 1990;Rook and Gardner 1993; Vohs and Faber the same goal (Cheung et al. 2014). While the above discus- 2007). Other researchers concur that impulse buying can serve sion sheds light on the relationship between self-control and to manage or elevate negative mood states but also suggest positive emotions, there is a lack of clarity in current literature that this influence occurs through a self-regulatory function on the precise direction of the relationship between self- (Rook and Gardner 1993; Verplanken et al. 2005). Thus, emo- control and emotional states relative to impulse buying as well tional states—whether positive or negative—likely affect im- as the impact of self-control on negative emotions. pulse buying, but we find no consensus about whether or how negative moods, positive moods, or both determine impulse Contextual moderators buying uniquely. Finally, research rooted in environmental psychology as- We seek novel insights by examining industry characteristics serts that exposure to environmental stimuli, consumers’ per- as potential contextual moderators. Based on extant studies, sonalities, and personal motives can cause specific (positive or we identify the price levels, advertising, and distribution in- negative) emotional reactions (e.g., Babin et al. 1994; tensity within the industry context as moderators that may Donovan and Rossiter 1982; Mehrabian and Russell 1974). influence the effects of other factors on impulse buying. The These in turn mediate the impacts of personal, situational, and identity expression capability of the products themselves external factors on impulse buying (Parboteeah et al. 2009; could moderate the impacts of the various determinants too. Verhagen and van Dolen 2011). The limited empirical evi- Prior impulse buying studies do not test the effects of these dence on the mediating role of emotions refers to specific moderators; to derive our predictions, we thus turn to relation- contexts; for example, Adelaar et al. (2003) show that plea- ship marketing research that reveals how industry-level vari- sure, dominance, and arousal triggered at the moment of ables determine effectiveness (Fang et al. 2008). Product price purchase mediate the effect of a media format on impulse levels matter, because financial constraints suppress impulse buying intentions online. Verhagen and van Dolen (2011) purchases (Rook and Fisher 1995), and impulse buying trig- found that positive emotions mediate the effects of consumer gers are less effective in more expensive product categories. In beliefs about online stores and their likelihood of buying their meta-analysis, Samaha et al. (2014) find that advertising J. of the Acad. Mark. Sci. (2020) 48:384–404 389 intensity in a specific industry reduces the effectiveness of a sociology, and psychology. We also obtained some unpub- firm’s communication activities. We posit that similarly, im- lished studies from their authors. We sent 159 emails to au- pulse buying triggers may be less effective in industries in thors of published papers seeking at least minimally relevant which all firms invest heavily in advertising, because con- statistics for conducting the analysis. After excluding theoret- sumers are less likely to recognize and consider these various ical papers, qualitative studies, book reviews, studies that triggers. In addition, distribution intensity in an industry might mention but do not measure impulse buying, and studies that influence impulse buying, because the urge to purchase likely do not report the necessary effect sizes, we pared down the list increases when products are rare or exclusive (Troisi et al. of 386 articles to a final data set of 186 articles reporting 2006). Finally, some products are more prone to impulse pur- empirical results. chases, especially if they symbolize a preferred or ideal self We coded each effect size according to the relationship of (Dittmar et al. 1995; Dittmar and Bond 2010). Thus, we an- the independent variables (traits, motives, resources, and mar- ticipate differing effectiveness of impulse buying triggers ac- keting stimuli), the mediators (self-control, positive emotions, cording to the product. and negative emotions) and impulse buying. We also coded the industry and method moderator variables, such that we Method moderators assessed industry characteristics (i.e., product-identity rela- tion, price level, advertising intensity, and distribution inten- Meta-analyses frequently consider the influence of the sity) using the industry description reported by the studies. We methods adopted by the included studies, such as how they similarly coded the method moderators (i.e., study year, mea- measure key constructs, on the strength of the focal relation- surement of impulse buying, and student sample) using infor- ships. Impulse buying studies frequently use different mea- mation provided in each study. Two coders achieved agree- sures for similar constructs; we use the scale for buying im- ment greater than 90% and discussed any inconsistencies, pulse developed by Rook (1987) as a baseline to assess wheth- using the construct definitions in Table 2 to classify all the er other measures perform differently. Meta-analyses also can variables. reveal whether the use of specific samples influences the find- We included studies that reported (1) correlations (r) be- ings (Orsingher et al. 2009). In particular, student samples tween the variables of interest, (2) the standardized regression tend to be more homogeneous than non-student samples and coefficients (beta coefficients), (3) F- or t-values, or (4) fre- thus produce stronger effect sizes. Finally, we assess the quencies, to calculate as as many effect sizes, so as to enhance influence of the study period. The emergence of the the generalizability (Peterson and Brown 2005). Internet and advanced communication technologies have left customers more knowledgeable, with altered expecta- Integration of effect sizes tions of retailers (Blut et al. 2018). Accordingly, we con- sider whether customers’ impulse buying behaviors might Correlation coefficients were used as effect sizes in our meta- have changed over time. analysis. If such coefficients were not reported in the collected studies, we transformed alternative statistics, such as regres- sion coefficients, into correlations (Peterson and Brown Method 2005). Following Peterson and Brown (2005), we imputed correlations from the beta coefficients using the formula: Data collection and coding r = .98β +.05λ with λ =1 when β > 0 and λ = 0 when β <0. Some studies also report more than one correlation for the We collected the data for this study by searching electronic same relationship between two constructs, in which case, we databases, including EBSCO, Proquest, Ingenta Journals, averaged the two correlations and treated them as if they were Elsevier Science Direct, Google Scholar, the web, and several from a single study (Hunter and Schmidt 2004). We did not pertinent leading journals (e.g., Journal of the Academy of have enough effect sizes to include some determinants in all Marketing Science, Journal of Consumer Research, Journal analyses, such as the four marketing stimuli of communica- of Marketing, Journal of Marketing Research). We also iden- tion, price stimuli, store ambience, and merchandise. We tified relevant articles by examining the reference lists of the therefore examined these determinants separately when pos- collected articles. Our search used various terms, including sible and merged them as necessary to include them in other “impulse buying” and “impulsive buying,”“impulsivity,” analyses. If a study had measured more than one of the four “compulsive buying,” and “unplanned buying,” and instruments, we calculated an average effect size for the ag- encompassed titles, abstracts, and keywords. The document gregate marketing stimuli variable. This approach ensures the types included articles and reviews (c.f., book review); the language was English; and the subject areas spanned market- The complete list of studies used in this meta-analysis is available from the ing and advertising, management, business, economics, authors. 390 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 2 Description of constructs in the meta-analysis Determinant Description Aliases Representative Studies Example Operationalization Sensation-seeking A person’s disposition to seek novel experiences sensation-seeking trait, variety seeking Billieux et al. (2010); Lucas Sensation-seeking trait can be measured using Zuckerman’s and sensations regardless of the risks and Koff (2014) (1994) 5-point, 12-item SSS scale that became one factor of involved (Zuckerman 1994). the UPPS scale of Whiteside and Lynam (2001)(e.g., “I will try anything once,” and “I quite enjoy taking risks”); Billieux et al. (2010). Impulse buying tendency An enduring disposition to act impulsively in a impulse buying tendency, Rook and Fisher (1995); Buying impulsiveness uses a 5-point scale containing 9 items given context (Rook and Fisher 1995). impulsiveness, impulsivity Vohs and Faber (2007) (e.g., “I often buy things spontaneously”); Rook and Fisher (1995). Self-identity The subjective concept (or representation) that a self-concept, self-discrepancies (r), Dittmar and Bond (2010); Identity deficit was measured with a participant-generated person holds of her- or himself (Vignoles identity deficits (r) Kwon and Armstrong self-discrepancy index on a 5-point, 5-item scale (e.g., “Iam et al. 2006). (2002) ..., but I would like to be ...”; “I worry about this so much that it is ruining my life”); Dittmar and Bond (2010). Hedonic motives Affective gratification derived from the sensory adventure shopping, experience Herabadi et al. (2009); Park Experience-based shopping motives, measured on 7-point, attribution of a product or service (Hirschman shopping, gratification shopping et al. (2012) 4-item scale (e.g., “I look around at items on the Internet and Holbrook 1982). just for fun.”); Park et al. (2012). Utilitarian motives An inner drive toward direct value seeking, price consciousness Kukar-Kinney et al. (2012); Utilitarian motives, measured on a 7-point, 5-item scale (e.g., economic/functional/practical benefits and Park et al. (2012) “I browse the shopping websites to gather information values (Foxall 2007). about products.”); Park et al. (2012). Norms Informal guideline about what is considered normative beliefs, conformity, Luo (2005); Rook and Fisher Normative beliefs were measured with 10 bipolar adjective normal social behavior in a particular social isolation, peer influence (1995) pairs (e.g., good-bad, rational-crazy, wasteful-productive) unit (Rook and Fisher 1995). for impulse buying scenarios; Rook and Fisher (1995). Psychic resources Degree of thoughts and energy devoted to a product involvement, social Davis and Sajtos (2009); Involvement used an inventory of 10 semantic differential purchase process (e.g., Andrews et al. 1990). involvement, fashion involvement, Jones et al. (2003); items about a product (“Important–Unimportant,”“Matters need for touch to me–doesn’t matter”); Jones et al. (2003). Time/Money Role of resources, such as time and money time availability, time pressure, money Lin and Chen (2013) Time pressure was measured on a 5-point, 3-item scale (e.g. “I availability (e.g., Wood 1998). availability, financial well-being, feel pressured to complete my shopping quickly”); Lin and time pressure Chen (2013). Age Age of the consumer – Zhang et al. (2010) Self-reported age; Zhang et al. (2010). Gender Gender of the consumer – Adelaar et al. (2003); Zhang Self-reported gender; Zhang et al. (2010). et al. (2010) Marketing Degree of persuasion offered by marketing advertising, direct sales, sales person, Park et al. (2012); Zhou and The effect of POP ads was measured on a 7-point scale with 5 stimuli – Communication communication mix (Abratt and Goodey pop-up ads; salesperson; in store Wong (2004) bipolar evaluation items (e.g., “Please describe your 1990) promotional display impression of the in-store POP posters based on your shopping experience today”); Zhou and Wong (2004). Marketing stimuli – Price Price and price promotion organized by firms to lower prices and discounts; sales Kukar-Kinney et al. (2012); Lower prices and discounts used 7-point, 3-item scales (e.g., trigger impulse buying (Grewal and promotion; price/quality ratio Park et al. (2012) “Discounted prices are very cheap in the shopping Marmorstein, 1994) website”); Park et al. (2012). Marketing stimuli – Store Visual and sensory stimuli in online and offline layout and display, sensory attributes, Mohan et al. (2013); Morrin Store layout was measured on a 7-point, 9-item scale referring ambience stores, as perceived by consumers (Sharma visual appeal; and Chebat (2005) to light, music, and layout (e.g., “The store has attractive and Stafford 2000) displays”); Mohan et al. (2013). Marketing Product variety and attributes offered to the variety of selection; attractiveness; new Liu et al. (2013); Park et al. Product availability was measured on a 7-point, 3-item scale stimuli – Merchandise consumer (Park et al. 2012) products; retail offers (2012) (e.g., “There are a sufficient variety of products available for me in online group shopping websites.”); Liu et al. (2013). Self-control Ability to control urges, conform to norms and self-monitoring, self-regulatory Sharma et al. (2014); Vohs Self-monitoring was measured on a 7-point, 5-item scale (e.g., change behavior (Baumeister 2002). resources, lack of self-control and Faber (2007) “I have found that I can adjust my behavior to meet the requirements of any situations I find myself in”); Sharma J. of the Acad. Mark. Sci. (2020) 48:384–404 391 use of only one aggregate marketing stimuli effect size for each study. After transforming and averaging the effect sizes, the total data set in the meta-analysis consists of 968 effect sizes, extracted from 231 samples obtained from 186 articles. The total combined sample includes 75,434 respondents. We used a random-effects approach (Hunter and Schmidt 2004) to calculate the average correlations. Effect sizes were corrected for measurement error in the dependent and independent variables using the coded reliability coefficients. We followed the Hunter and Schmidt (2004)rec- ommendation of dividing the correlations by the product of the square root of the respective reliabilities of the two con- structs involved. Further, reliability-adjusted correlations were weighted by sample size to adjust for sampling error. It has been recommended that reliability-adjusted effect sizes should be transformed into Fisher’s z coefficients before weighting them by sample size (Kirca et al. 2005). This transformation is not without controversies, and some studies suggest that Fisher’s z overestimates true effect sizes by 15%–45% (Field 2001). However, when we compare the results of both ap- proaches, we find no significant differences. Next, for each sample size–weighted and reliability- adjusted correlation, we calculated standard errors and 95% confidence intervals. We used a chi-square test and applied a 75% rule-of-thumb to assess the homogeneity of the effect size distribution (Hunter and Schmidt 2004). To assess the robustness of our results and potential publication bias, we estimated Rosenthal’s(1979) fail-safe N; in other words, the estimation of the number of studies that had null results and therefore not published before the Type I error probability can be brought to a barely significant level (p = .05). We also tested the influence of sample size and effect size outliers on integrated effect sizes, but the results remained largely the same (Geyskens et al. 2009). To assess the practical relevance of the different determinants, we calculated the shared vari- ance with impulse buying for each predictor, as well as the binomial effect size display (BESD) (Grewal et al. 2018b), which indicates the likelihood that a customer (e.g., female) would purchase impulsively compared with a reference group (e.g., male customers). Avalue greater than 1 indicates a great- er relative likelihood, whereas a value lower than 1 signals a lower likelihood. Results Descriptive statistics Direct effects As Table 3 indicates, the averaged effect sizes for most motives, resources, and trait predictors are signifi- cant; however, socio-demographic predictors seem to matter less for impulse buying. We find strong support for the im- pacts of the three trait-related predictors on impulse buying. Table 2 (continued) Determinant Description Aliases Representative Studies Example Operationalization et al. (2014). Positive moods states Intense positive feelings directed at someone or happiness, excitement, pride, pleasure, Cohen and Andrade (2004); Positive moods states, measured on a 6-point, 6-item scale something (Fishbach and Labroo 2007). arousal, joy, glee Weinberg and Gottwald (e.g., stimulating, exciting, inspiring enthusiasm); Weinberg (1982) andGottwald(1982). Negative moods states Intense negative feelings directed at someone or sadness, depression, anger, irritation; Mohan et al. (2013); Negative moods states, measured on a 7-point, 3-item scale something (Fishbach and Labroo 2007). anxiousness, boredom, hurt Weinberg and Gottwald (e.g., “I felt lethargic while shopping today”); Mohan et al. (1982) (2013). Impulse buying Spontaneous purchases made without planning self-reported frequency of impulse Mohan et al. (2013); Rook Impulse buying behavior used two items: “total number of and/or reflecting on consequences (Rook and buying; observed impulse buying and Fisher (1995) items bought on impulse” and the “proportion of items Fisher 1995) behavior bought on impulse”; Mohan et al. (2013). 392 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 3 Descriptive statistics and correlations of predictors with impulse buying Determinants of Impulse Buying Number of Total N Min. z Max. z Sample-Weighted −95% CI +95% CI R BESD Q-Statistic for p File-Drawer N r r Raw Effects Reliability Based lift Homogeneity Adjusted r Test Traits Sensation-seeking 10 2,290 .03 .63 .23* .12 .33 5.2% 59.7% 57 .00 323 Impulse buying tendency 51 14,095 −.46 1.29 .36* .26 .45 12.8% 112.5% 2,172 .00 24,743 Self-identity 12 1,656 −.33 .52 .10† −.03 .23 1.1% 22.2% 82 .00 – Motives Hedonic motives 24 6,979 −.37 1.00 .34* .23 .45 11.7% 103% 602 .00 7,340 Utilitarian motives 10 2,599 −.11 1.10 .36* .06 .60 12.9% 112.5% 479 .00 731 Norm 28 5,953 −.95 1.05 .27* .14 .38 7.1% 74% 707 .00 4,506 Resources Psychic resources 24 5,647 −.27 .69 .18* .08 .27 3.3% 43.9% 328 .00 1,292 Time/Money 21 5,718 .00 1.83 .28* .08 .45 7.7% 77.8% 1,195 .00 2,185 Age 11 3,153 −.44 .19 −.05 −.19 .09 .2% 10.6% 154 .00 – Gender (1 = female) 15 3,687 −.10 .42 .09* .00 .18 .9% 19.8% 114 .00 142 Marketing Marketing stimuli 50 13,910 −.19 .97 .27* .21 .32 7.1% 74% 646 .00 13,952 Communication 18 6,423 −.03 .97 .33* .22 .44 11.0% 98.5% 403 .00 3,302 Price stimuli 13 2,730 −.50 1.26 .27* .07 .44 7.2% 74% 386 .00 1,259 Store ambience 42 10,013 −.05 .97 .23* .17 .28 5.2% 59.7% 405 .00 6,806 Merchandise 11 2,687 −.29 .73 .17* .05 .28 2.8% 41% 77 .00 251 Mediators Self-control 20 3,330 −.83 .55 −.12† −.28 .04 1.5% 27.3% 448 .00 – Positive moods states 30 7,144 .00 1.13 .30* .21 .38 8.8% 85.7% 426 .00 4,173 Negative moods states 15 4,657 −.29 .46 .09* .00 .19 .9% 19.8% 124 .00 149 † p < .10. * p < .05. Notes: The confidence intervals and the file-drawer Ns are based on two-tailed tests. The number of effect sizes of all stimuli combined is lower than the sum of the separate instruments, because we averaged the marketing stimuli per independent sample J. of the Acad. Mark. Sci. (2020) 48:384–404 393 As expected, an individual's tendency to act impulsively has a into one determinant variable and examined its influence in stronger effect than other traits, reflecting its stronger link to the SEM; if a study included two or more marketing stimuli the behaviorofinterest. effects, we averaged them. The proposed model with both Utilitarian and hedonic motives show about equal impacts mediators and the effect of self-control on emotions performs on impulse buying; further research should pay more attention well and displays a good fit (Fig. 2). to these determinants. We find support for gender effects but observe no differences for age. The former results are in line Positive moods The SEM results suggest that positive moods with prior research that suggests women generally are more are important mediators (Fig. 2). Customers with stronger he- likely to purchase impulsively than men (Dittmar et al. 1995). donic motives are more likely to experience positive feelings; However, the insignificant results for age suggests there are customers with utilitarian motives are less likely to experience not many differences between older and younger customers such feelings. Those with favorable subjective norms and high with regard to spending money impulsively. Moreover, we self-control also experience positive moods. These effects are find that marketing stimuli exert a direct influence on cus- new to extant impulse buying literature. Similarly, customers tomers’ impulse buying behavior. When examining the spe- who are generally high in impulsivity experience positive feel- cific marketing instruments, we find the strongest effects for ings. Finally, marketing stimuli relate significantly to positive communication and price stimuli and weaker effects for store feelings, though the effect is relatively weak. ambience and merchandise. Negative moods Negative mood states relate significantly to Mediators We uncover significant effects for emotions and impulse buying, and each of the determinants link to this me- self-control (Table 4). Descriptive statistics were also exam- diator, with the exception of marketing stimuli and self-con- ined to gauge the impact of the predictors on the mediators trol. Customers high in hedonic and utilitarian motives are less (Table 4); 30 of the 39 predictor–mediator relationships (77%) likely to experience negative moods. Favorable subjective are significant. Thus, we obtain a preliminary indication of the norms increase the likelihood of negative feelings. Impulse mediating roles of emotions and self-control, and we can pro- buying tendency is positively related to the experience of neg- ceed to test the proposed mediating effects in the SEM. ative moods. The insignificance of marketing stimuli suggests The shared variances and BESD give some indication of that the stimuli do not trigger negative moods in customers. the practical relevance of different determinants. Using these Self-control also does not reduce the experience of negative criteria, we observe strong effects of impulse buying tenden- emotions. cies, utilitarian motives, and communication. All the signifi- cant relationships are robust to publication bias because the Self-control Unlike mood states, self-control reduces the like- lihood of impulse purchases. This cognition intervenes when file-drawer N is many times greater than the tolerance levels proposed by Rosenthal (1979). We also examined funnel plots customers experience an urge to buy impulsively. According and do not find any indication of publication bias. In all cases, to the SEM results, several predictors either trigger individual the significant chi-square tests of homogeneity suggest awareness of the long-term consequences of spending or re- moderation. assure consumers that spending is acceptable. For example, customers high in impulsivity are less likely to exhibit self- Evaluation of structural equation model control. Subjective norms that encourage impulse buying low- er self-control perceptions, but marketing stimuli serve to in- We tested the mediating effects using structural equation crease self-control. Finally, hedonic and utilitarian motives modeling (SEM) and included variables for which correla- increase self-control perceptions. The positive effect of mar- tions with all other variables could be identified. The complete keting stimuli on self-control suggests that customers are correlation matrix includes correlations between the most of- aware of how firms try to influence them to make them im- ten studied variables in prior research (Table 5). It served as pulsive purchases. the input to LISREL 8.80 and the harmonic mean of all sam- Similar to Pick and Eisend (2014), we tested the impor- ple sizes (N = 1726) was used as input. Since the harmonic tance of mediation effects using two approaches. First, we mean is lower than the arithmetic mean, SEM estimations are examined the ratio of indirect effects to total effects as more conservative (Viswesvaran and Ones 1995). Note that displayed in Table 6. We find significant indirect effects and since each construct had only a single indicator and since high ratios for most determinants, including self-control measurement errors were taken into account when estimating (20%), impulse buying tendency (46%), utilitarian motives the mean effect sizes, the error variances in the SEM could be (34%), norms (49%), and marketing stimuli (39%). Only the set to 0. The different marketing instruments could not be indirect effect of hedonic motives is insignificant, leading to a individually included in the SEM, due to the small number low ratio of indirect effects to total effects (8%). The direct, indirect, and total effects differ for some determinants; self- of effect sizes, so we aggregated all marketing instruments 394 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 4 Descriptive statistics and correlations of predictors with mediators Determinant Number of Total N Min. z Max. z Sample-Weighted −95% CI +95% CI R BESD Q-Statistic for p File-Drawer N r r Raw Effects Reliability Adjusted r Homogeneity Test DV:Self-control(SC) Impulse buying tendency ➔ SC 21 11,110 −1.19 .56 −.12† −.29 .05 1.5% 27.3% 1,567 .00 – Hedonic motives ➔ SC 7 1,820 −.18 .89 .16† −.02 .33 2.6% 38.1% 85 .00 – Utilitarian motives ➔ SC 3 899 .00 .52 .25† −.13 .56 6.0% 66.7% 12 .00 – Norm ➔ SC 3 601 −.78 −.02 −.32† −.63 .09 10.1% 94.1% 53 .00 – Psychic resources ➔ SC 2 538 .01 .34 .18 −.14 .47 3.2% 43.9% 12 .00 – Time/Money ➔ SC 2 2,047 .04 .08 .06* .02 .10 .3% 12.8% 1 .37 3 Age ➔ SC 3 2,142 .00 .33 .24* .13 .34 5.7% 63.2% 10 .01 124 Gender (1 = female) ➔ SC 2 1,196 −.05 .00 −.05† −.10 .01 .2% 10.5% 0 .64 – All marketing stimuli ➔ SC 4 317 .27 .68 .39* .21 .55 15.6% 127.9% 8 .05 52 Communication ➔ SC 1 167 .29 .29 .28* .14 .41 7.8% 77.8%–– 4 Price stimuli ➔ SC 1 90 .27 .27 .26* .06 .44 6.8% 70.3%–– 1 Merchandise ➔ SC 2 60 .68 .68 .59* .40 .73 34.8% 287.8% 0 1.00 13 DV: Positive moods states (PM) General traits ➔ PM 2 570 .47 1.05 .64* .19 .87 40.5% 355.6% 28 .00 112 Impulse buying tendency ➔ PM 25 7,826 −.40 .79 .26* .17 .35 6.8% 70.3% 501 .00 4,681 Self-identity ➔ PM 2 570 −.01 .03 .00 −.08 .08 .0% 0 .71 – Hedonic motives ➔ PM 8 1,979 .25 1.07 .57* .40 .70 32.2% 265.1% 132 .00 1,034 Utilitarian motives ➔ PM 4 899 .25 .62 .30* .20 .38 8.8% 85.7% 4 .21 88 Norm ➔ PM 5 1,036 .05 .73 .27* .04 .47 7.2% 74% 53 .00 84 Psychic resources ➔ PM 7 1,684 .04 .65 .18* .08 .27 3.1% 43.9% 21 .00 94 Time/Money ➔ PM 2 730 .10 .12 .12* .05 .19 1.4% 27.3% 0 .85 4 Gender (1 = female) ➔ PM 1 842 .00 .00 .00 −.07 .07 .0% –– – Marketing stimuli ➔ PM 12 3,289 .01 .69 .40* .27 .50 15.6% 133.3% 152 .00 1,731 Communication ➔ PM 4 1,383 .09 .66 .29* .04 .51 8.6% 81.7% 57 .00 161 Price stimuli ➔ PM 1 401 .60 .60 .54* .47 .61 29.2% 234.8%–– 43 Store ambience ➔ PM 11 3,229 .01 .69 .38* .25 .49 14.3% 122.6% 190 .00 1,751 Merchandise ➔ PM 5 1,205 .15 .62 .34* .21 .46 11.8% 103% 17 .00 188 Self-control ➔ PM 5 1,705 −.06 .85 .37* .09 .59 13.5% 117.5% 108 .00 459 DV: Negative moods states (NM) Impulse buying tendency ➔ NM 15 5,633 −.04 .78 .21* .09 .33 4.5% 53.2% 320 .00 1,704 Hedonic motives ➔ NM 4 1,367 −.73 .07 −.19† −.40 .03 3.7% 46.9% 32 .00 – Utilitarian motives ➔ NM 3 647 −.39 −.15 −.18* −.26 −.09 3.2% 43.9% 2 .35 14 Norm ➔ NM 3 419 −.37 .68 .17 −.50 .71 2.8% 41% 99 .00 – Psychic resources ➔ NM 2 582 −1.38 .01 −.59 −.97 .59 34.7% 287.8% 88 .00 – J. of the Acad. Mark. Sci. (2020) 48:384–404 395 control has a negative direct effect on impulse buying, yet the indirect effect through mediators is positive, which mitigates the total negative effect. Impulse buying tendency has positive direct and indirect effects on impulse buying, such that the total effect is nearly twice as strong as the direct effect. Utilitarian motives have a positive direct effect on impulse buying and a negative indirect effect that lowers the total ef- fect. Norms display a negative direct effect and a positive indirect effect; we observe the opposite effects for marketing stimuli. The mediation model thus provides a clearer view of how these determinants influence impulse buying. Second, we compare the proposed model, which assumes partial mediation effects, with two models with only indirect effects of the determinants through moods and self-control (full mediation). As suggested by Pick and Eisend (2014), we compare the models using a chi-square difference test (Δχ /df). Both full mediation models exhibit significantly worse model fit than the proposed model (mood: Δχ /df = 630.51/6, p < .01; self-control: Δχ /df = 755.28/8, p <.01). Thus, the mediating effects of moods and self-control are par- tial rather than full. Moderator analysis results The need for a moderator analysis was assessed through the chi-square test of homogeneity and a 75% rule (Hunter and Schmidt 2004). The 75% rule indicates that if the proportion of variance in the distribution of effect sizes attributed to sam- pling error and other artifacts is less than 75%, a moderator analysis is warranted. In our results, the chi-square value is significant in all cases, and the 75% rule suggests values lower than 75%, in support of a moderator analysis. We coded sev- eral moderators in our random effects regression model as dummy variables, including the four industry moderators: product identity relation (1 = high expressive, 0 = low expres- sive), price level (1 = high, 0 = low), advertising intensity (1 = high, 0 = low), and distribution intensity (1 = high, 0 = low). For the two method moderators, impulse buying measure (1 = Rook, 0 = non-Rook) and sample (1 = student, 0 = non-stu- dent), we used dummy codes. The year of the study came directly from the articles. Using meta-regression procedures suggested by Lipsey and Wilson (2001) and the provided macros, we assess the influence of the moderators in our model with random- effects regression (Hunter and Schmidt 2004). Using reliability-corrected correlations as the dependent variable, we conducted tests of the moderators for 18 predictor vari- ables and regressed correlations on four industry variables and For example, grocery retailing involves low product identity relation, low price level, high advertising intensity, and high distribution intensity; the lux- ury car industry was coded as high product identity relation, high price level, low advertising intensity, and low distribution intensity. Table 4 (continued) Determinant Number of Total N Min. z Max. z Sample-Weighted −95% CI +95% CI R BESD Q-Statistic for p File-Drawer N r r Raw Effects Reliability Adjusted r Homogeneity Test Gender (1 = female) ➔ NM 1 842 .01 .01 .01 −.06 .08 .0% 2% –– – Marketing stimuli ➔ NM 6 1,529 −.63 .81 −.06 −.37 .26 .4% 12.8% 152 .00 – Communication ➔ NM 3 937 −.20 .81 .18 −.49 .71 3.2% 43.9% 139 .00 – Store ambience ➔ NM 4 1,302 −.51 .07 −.13† −.27 .01 1.8% 29.9% 26 .00 – Merchandise ➔ NM 3 592 −.63 .10 −.27 −.67 .26 7.0% 74% 24 .00 – Self-control ➔ NM 7 1,917 −.74 .02 −.29* −.50 −.05 8.5% 81.7% 156 .00 166 Positive moods states ➔ NM 11 4,251 −.71 .21 −.23* −.37 −.08 5.3% 59.7% 227 .00 420 † p < .10. * p < .05. Notes: The confidence intervals and the file-drawer Ns are based on two-tailed tests. PM = positive mood; NM = negative mood; SC = self-control. The table only displays predictors for which effect sizes can be calculated 396 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 5 Correlations among latent constructs Construct Impulse Buying Hedonic Utilitarian Norm Marketing Self-Control Positive Negative Impulse Tendency Motives Motives Stimuli Mood Moods Buying States States 1. Impulse buying [.88] 31 12 26 34 21 25 15 51 tendency 2. Hedonic motives .36 [.89] 9 6 14 7 8 4 24 3. Utilitarian motives .16 .42 [.94] 2 6 3 4 3 10 4. Norm .33 .39 .55 [.87] 8 3 5 3 28 5. Marketing stimuli .29 .33 .38 .21 [.91] 4 12 6 50 6. Self-control −.12 .16 .25 −.32 .39 [.91] 5 7 20 7. Positive moods states .26 .57 .30 .27 .40 .37 [.91] 11 30 8. Negative moods states .21 −.19 −.18 .17 −.06 −.29 −.23 [.90] 15 9. Impulse buying .36 .34 .36 .27 .27 −.12 .30 .09 [.94] Harmonic mean across all collected effects is 1,726. Entries on the diagonal in brackets are weighted mean Cronbach’s alpha coefficients. Entries in the lower half are sample-weighted reliability adjusted correlations; the upper half shows the number of effect sizes. The marketing stimuli effects were averaged three method variables. To test moderation effects, we ensured greater advertising intensity, but norms, psychic resources, that at least 10 effect sizes were available (Samaha et al. 2014). and store ambience matter less. Product identification We confirm a moderating influence of Distribution intensity Product availabilityinanindustryde- product identification (Table 7). If a product’s expressiveness pends on its distribution intensity. For example, Dholakia is high (i.e., product identity is coded as 1 for high expressive- (2000) explains that physical proximity is essential for the ness), some predictors lose their relevance, including self- experience of an impulsive urge, but a product that is unusu- identity and subjective norms. Products that facilitate consum- ally difficult to purchase may be more appealing to customers er self-expression are more likely to be bought impulsively, than products that are available everywhere. We anticipated because they represent a preferred or ideal self (Dittmar et al. and find that at least some impulse buying predictors, such as 1995; Dittmar and Bond 2010). Products with high expres- utilitarian motives, psychic resources, merchandise, and neg- siveness also suppress the effects of norms. In these condi- ative mood states, become less effective when a product is tions, other determinants become less effective. However, more widely available. Moreover, communication gains rele- some determinants related to communication and negative vance with greater distribution intensity. feelings gain importance, because consumers are very sensi- tive with regard to their self-perceptions. Method moderators When examining the moderating influ- ence of the method adopted in the different studies, we find Price level As expected, the average price level of products in an that several predictors, such as impulse buying tendency and industry buffers the impacts of several predictors. Most predic- utilitarian motives, gain importance over time. We do not ob- tors lose some relevance when prices are high (i.e., price level is serve a specific pattern for the measures employed. The results coded as 1), including sensation-seeking, impulse buying ten- with regard to the measures used in the studies suggest that the dency, hedonic motives, utilitarian motives, psychic resources, widely employed Rook scale performs as well as alternative and positive moods. Only self-control gains importance, in line impulse buying measures. We also find generally weaker ef- with our reasoning. Higher prices alert consumers to the finan- fects in studies using student samples. In further meta- cial consequences of their urge to buy impulsively, making these regression models, we assessed the influence of country cul- determinants less effective (but self-control more effective). ture and emerging markets but do not find notable differences. Advertising intensity The influence of advertising is quite in- teresting. On the one hand, it appears to increase desire for Implications and directions for further certain products, so some predictors gain relevance. On the research other hand, the predictors may lose relevance, because prod- ucts seem less unique when they are advertised everywhere. This meta-analysis aims to provide a comprehensive and co- Negative moods and merchandise gain importance with herent understanding of impulse buying behavior, by J. of the Acad. Mark. Sci. (2020) 48:384–404 397 .11* .14* .07* Impulse buying -.14* tendency Posive moods .24* .33* .41* Hedonic moves .17* .43* -.29* -.20* -.53* .43* Ulitarian moves Self-control Impulse buying -.28* .32* .19* Norms -.65* .34* .09* Negave moods .35* Markeng smuli .17* .54* -.44* Fig. 2 Results of the structural equation model. Notes: A dotted line indicates that the path is not significant. Model fit: χ /1 = 67.74; confirmatory fit index = .99; goodness-of-fit index = .99; root mean residual = .02; standardized root mean residual = .02 synthesizing previous research. Our meta-analytic review buying and highlight the context-dependency of impulse buy- seeks deeper insights into impulse buying, and our compre- ing research. These meta-analysis results in turn suggest sev- hensive model of impulse buying integrates constructs and eral implications for practice and directions for further relationships from studies over the past four decades of em- research. pirical research on impulse buying. The results from our meta- analysis provide new insights into the impacts of various an- Managerial implications tecedent factors and call particular attention to the tensions between the inherent urge to buy impulsively and the con- Consumer buying on impulse has long been an area of interest straints and control on such buying impulses. Also, the results for managers; even a small proportion of impulse purchases clarify the impacts of marketing stimuli on consumer impulse on each shopping trip or a small base of impulse shoppers can Table 6 Direct, indirect, and total Determinants of Impulse Buying Direct Indirect Total Indirect/Total (%) effects Positive moods states .33 – .33 – Negative moods states .19 – .19 – Self-control −.53 .13 −.40 20% Impulse buying tendency .14 .12 .26 46% Hedonic motives .11 .01 .13 8% Utilitarian motives .54 −.28 .25 34% Norm −.44 .42 -.02 49% Marketing stimuli .17 −.11 .06 39% Average 33% Not significant (p > .05); all other effects were significant at p < .05. Notes: D = direct effect; I = indirect effect; T = total effect; % = relative importance of indirect effects 398 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 7 Results of moderator analysis Determinants of Impulse Product- Identity Price Advertising Distribution Year Controls R Buying Relation Level Intensity Intensity Rook Student (non-Rook) (non-student) kB B B B B B B Traits Sensation-seeking 10 .18 −.63* −.22 .35 .11 .40† −.82* 65% Impulse buying tendency 48 .09 −.45* .11 −.19 .35* −.09 −.21† 38% Self-identity 12 −.50* −.35 −.39 .04 −.56* 47% Motives Hedonic motives 24 .19 −.43* .31 −.16 .17 −.03 .24 34% Utilitarian motives 10 .34 −.81* .38 −.88* .61* −.53 69% Norm 28 −.52* .07 −.33† .16 −.12 .37 −.04 45% Resources Psychic resources 24 −.14 −.87* −.38* −.36* .11 −.29* −.23* 68% Time/Money 21 −.17 −.16 .38 −.02 .38 −.17 .16 23% Age 11 −.51 .20 .43 .43 −.40 .13 .32 18% Gender (1 = female) 15 −.29 .28 .31 −.46 .06 .34† .55* 42% Marketing Marketing stimuli 50 .01 −.03 −.16 −.07 .18 −.08 −.11 6% Communication 18 .96* .17 −.16 .77* .32† −.35† .00 46% Price stimuli 13 .41 −.27 −.66 .65 .51 −.11 −.49* 44% Store ambience 42 −.13 −.04 −.36* −.09 .09 .06 −.13 19% Merchandise 11 −.25 −.26 .49* −.94* −.07 −.41 44% Mediators Self-control 20 .11 −.41* −.30 −.14 .28 −.34 −.17 33% Positive moods states 28 −.15 −.87* .08 −.29 .64* .85* −.26 36% Negative moods states 13 .61* .06 .20* −.30* −.11 .71* −.40* 86% * p < .05. † p < .10. The table shows standardized coefficients. For some relationships, advertising intensity and distribution intensity moderators were tested in two separate regression models, together with all other moderators. The table reports the averaged results across these models, as suggested by Samaha et al. (2014) for cases of high correlations between moderators. A positive (negative) coefficient indicates that the effect size is stronger (weaker) for studies with high (low) values of the moderator. For example, impulse buying tendency has a positive effect on impulse buying; the negative coefficient indicates that this relationship is weaker in industries with high price levels. When interpreting the moderating effects for self-control, note that the main effect is negative. A dash (―) indicates that a moderator could not be tested due to the low number of available effect sizes for a specific study characteristic. Similar to Samaha et al. (2014), we tested moderators that appeared with 10 or more effect sizes contribute significant annual incremental sales (Rostoks so retailers should devise new, unique marketing stimuli to 2003). It is therefore important to identify not just which con- convey the value of their offerings and encourage impulse sumers may be more inclined to purchase on impulse but also buying. Yet not all marketing stimuli are equally effective. specific environmental factors that may prompt and encourage Communication and price stimuli are more effective in impulse buying. Impulse purchases can increase retail sales prompting impulse buying than are store ambience and mer- (top-line) and profits (bottom-line), especially for high-margin chandise. Although retailers often devote considerable ex- products. As summarized in Table 8, our results suggest penses to store design, store atmosphere, store layout, and employing a variety of marketing strategies. merchandise placement, they may be better off investing more In their attempt to devise strategies to encourage impulse in price promotions and advertising, which likely have stron- shopping and/or promote impulse buying behaviors, retailers ger impulse buying effects. have not been averse to making large investments in market- An important practical insight from this meta-analysis is ing stimuli, such as merchandising, displays, lighting, music, that though marketing mix stimuli have positive impacts on and other environmental factors that might trigger impulse impulse buying, they also heighten awareness of such tenden- purchases (Mattila and Wirtz 2001). Our review acknowl- cies and thus may curb impulse buying overall. This finding edges that impulse buying can be triggered by external factors, suggests consumers are becoming increasingly familiar with J. of the Acad. Mark. Sci. (2020) 48:384–404 399 Table 8 Summary of managerial Issues Implications implications Marketing Stimuli • Retailers need to devise new, unique marketing stimuli to convey the value of their offers and encourage impulse buying. • Communication and price stimuli are more effective than store ambience and merchandise, so managers should invest more in price promotion and advertising campaigns. Traits, Motives and Resources • Identification of the impulse buying–prone customers is possible, and appropriate promotional offers could be devised to attract them. • Likelihood of impulse buying is shaped by traits such as impulsivity and other factors internal to consumers, not as much by readily observable characteristics such as age and gender. Therefore, primary research is required to identify impulse buying customers. • Motivational factors are much more important than controllable marketing stimuli, and therefore, stores and offers need to be designed to match shopper motives. • Consumer resources such as time and money affect impulse buying, so encouraging impulse buying may require reducing the impacts of resource constraints. Mechanisms • Self-control mechanisms can curb impulse buying. Public policy makers need to understand the types of marketing messages and labels that can be designed to curb unhealthy impulse buying. • Norms affect impulse buying, so managers can focus communication strategies on social norms to reassure customers of impulse purchases. • Positive emotions increase impulse buying, so attractive store environments and merchandise cues are important to stimulate impulse buying. • Negative emotions also affect impulse buying; impulse buying that does not stretch consumer resources could be promoted to lift consumer moods. Context • The impacts of consumer traits, motives, and resources are moderated by industry characteristics; managers should understand how their industry context would affect consumer impulse buying. • When product–identity relationships are strong, a greater focus should be on communications, among the various marketing stimuli. Prompts for impulse buying are less effective in industries with higher price levels. • The determinants of impulse buying such as impulse buying tendency and self-identity gain and lose relevance over time, so managers should revisit their assumptions and strategies periodically. firms’ tactics to persuade them to buy impulsively and skep- also specify situations that enable it. That is, marketers could tical of various marketing practices. For practitioners, these identify a distinct impulse buying segment and then design the findings may be somewhat discouraging; impulse buying is shopping environment to make their impulse buying more not simply a response to marketing stimuli, and psychological, likely. In some challenging findings though, we show that social, and situational variables also have impacts. Additional demographics such as age and gender matter less for research is warranted to understand how shopper skepticism predicting impulse buying, so retailers likely need to under- evoked by marketing tactics might inhibit impulse buying. take deeper research into consumer psychographics to identify Retailers may need to try harder to devise unique or new an impulse buying segment. marketing stimuli that can get past consumers’ defenses and Shopping motives, whether hedonic or utilitarian, also convey the value of their offers. matter when it comes to impulse buying. These motives The identification of an impulse buying segment of cus- are inherent to the consumer, so marketers should de- tomers would be of great importance to retailers that currently sign stores and offers to evoke and facilitate appropriate rely solely on marketing stimuli. But if impulse buying were motives. Yet consumers’ resource constraints (e.g., time, only trait driven, marketing strategy would have no effect on money) curb their buying impulses, so marketers also impulse purchases. The good news from our meta-analysis is could focus on devising tactics to reduce the impacts that impulse buying is triggered by both factors internal to of resource constraints. For example, access to speedy consumers and external marketing stimuli. Thus, it may be financing and faster checkouts likely help mitigate credit possible to identify consumers prone to impulse buying but and time constraints. 400 J. of the Acad. Mark. Sci. (2020) 48:384–404 Table 9 Impulse buying research Issues Research Directions agenda Main Effects • It would be beneficial to explicitly test and quantify the magnitude of the effects of specific marketing stimuli factors. For example, store effects are driven by a host of store elements, such as display, lighting, and music. • Effects of different marketing stimuli should be tested not only against one another but also assessed for uniqueness within the industry. Different stimuli appear online (e.g., social media) versus offline (e.g., retail store). • The meta-analysis indicates a rather weak effect of self-identity. Scholars should assess different identity scales and examine different types of consumer identities. • Positive moods are more influential than negative moods. Future studies could explore if negative moods might be stronger than positive moods in some cases, such as when trait variables exert direct effects on moods but also have moderating effects. • We could not differentiate types of norms, but certain social groups such as family and friends could be more influential than others. Furthermore, some social groups (e.g., friends) might encourage impulse buying, while others discourage it (e.g., family). • We assessed time and money constraints in aggregate but lacked data to assess differential effects of time and money. Research on the “time versus money effect” could explain differences between time and money constraints, as well as when time dominates money effects and vice versa. • We examine the impacts of various factors on impulse buying; further meta-studies could examining its consequences (e.g., cognitive dissonance, regret). Interactive Effects • The meta-analysis demonstrates the importance of the main effects of the various factors. It would be helpful to gain more insights on the interactive effects of traits, motives, resources, and marketing stimuli. Mechanisms • The mediating role of other mechanisms, such as greater in-store attention and sensory mechanisms (e.g., greater visual and tactile responses), on the effects of the selected independent variables on impulse buying needs to be explored. Contextual Cues • Other contextual cues, such as type of trip, stage (beginning vs. end), and the decision stage (search vs. purchase), all need to be tested. • The role of private versus public consumption could be an important moderator. • Other demographic variables (e.g., education, household size, number of children) warrant additional research, because they could drive the magnitude of impulse buying. • Most current studies do not consider whether shoppers are alone or accompanied by somebody. Further research could explore this individual shopping context to determine the effects on impulse buying. Type of Methodology • A majority of studies use surveys and examine correlational data. The effects of various marketing stimuli factors, motives, and resources on impulse buying could be explored using experimental designs, to support causal inferences. • Research needs to explore effects using longitudinal, as opposed to cross-sectional, data. The use of panel data sets might provide enhanced insights. • Eye-tracking could be used to understand impulse buying and obtain greater insights into the role of marketing stimuli, attention, and impulse buying. Do marketing stimuli result in greater impulse buying due to greater or lesser attention devoted to the stimuli (e.g., less attention to price, labels)? • Qualitative research could shed light on why some of our findings conflict with theoretical predictions. Consumers with high self-control and those influenced by impulsive purchases that may lead to later regret and consum- social norms also may be less prone to impulse buying, be- er dissatisfaction. Ultimately, marketers must choose between cause the uninhibited urge to buy impulsively is curbed by making an immediate sale that might produce consumer dis- self-control and social norms. Understanding these restrictions satisfaction and exhibiting concern for the consumer to en- can help ethical marketers develop stimuli that both facilitate courage future patronage. Similarly, both positive and nega- unplanned purchases but discourage purely uninhibited, tive emotions enhance impulse buying, and ethical marketers J. of the Acad. Mark. Sci. (2020) 48:384–404 401 should leverage affective strategies to encourage impulsive as consumer decision stage, whether consumption is pri- purchases that align with available consumer resources. vate or public, demographic variables, and whether the Public policy makers also might take heed of self-control, shopper is alone or accompanied by someone (Table 9). norms, and emotions to devise policies to reduce unhealthy Such contextual cues should function as moderators in impulse buying. future studies to help reveal how various antecedent fac- Because industry characteristics also matter in impulse tors affect impulse buying. buying, managers need to understand how the industry con- Studies exploring impulse buying also tend to use sur- text moderates the impacts of various consumer traits, mo- veys and examine correlational data. Such descriptive tives, and resources on impulse buying. Even if impulse buy- analyses provide generalizable insights, though manipula- ing is common in industries with low price levels, our findings tions of various marketing stimuli, motives, and resources caution that it is not the only relevant industry context; rather, in experiments also could enable causal inferences. impulse buying also occurs when product–identity relation- Longitudinal research that relies on panel data could also ships are strong. In such contexts, marketers should place reveal how consumer motives and resources interact with due emphasis on communications that encourage impulse the context to prompt impulse buying. New technologies, buying. such as eye-tracking methods, could demonstrate the spe- cific impacts of marketing stimuli (e.g., product place- Directions for research ments) and how consumers’ attentionpaidtovarious de- tails in the shopping environment contributes to their im- Our meta-analysis, while revealing, was restricted given the pulse buying. Finally, we find some evidence that is con- lack of sufficient studies testing and/or reporting all possible tradictory with theoretical predictions, so qualitative re- effects in all possible contexts using multiple methods. In ex- search would be helpful to explain why. ploring the main effects of various factors on impulse buying (Fig. 1), we had to use aggregations in several cases, due to the Conclusion insufficient number of effects available in prior research. Future studies should undertake explicit examinations of each effect, Our meta-analytic review aims to provide empirically gener- especially specific marketing stimuli, self-identity, positive and alizable, robust findings pertaining to the impacts of various negative moods, specific types of social norms, and consumer antecedents of impulse buying, its potential mediators, and the resources. The most glaring deficiencies in prior research pro- moderators of these relationships. As a unique feature, our vide the bases for our recommendations for further research, meta-analysis includes a test of alternate theoretical perspec- which we detail in Table 9 and summarize briefly here. tives that previously have sought to explain impulse buying. We indicate the effects of various individual drivers, in- As Palmatier et al. (2007) attest, on the basis of their compar- cluding marketing stimuli, on impulse buying in Table 3, ative consideration of multiple theoretical perspectives on in- which suggests an important facilitating role for impulse buy- terorganizational relationships, various perspectives could re- ing. We test the individual impacts of traits, motives, re- ceive empirical support individually, but their relative impacts sources, and stimuli on impulse buying, but interactions cannot be determined unless all explanatory perspectives are among these antecedents also could be influential. For exam- subjected to a comparative test. With the greater number of ple, experimental research might determine how the effects of effects sizes available for each model, achieved by compiling traits, motives, and resources on impulse buying are moderat- data for the meta-analysis, our comparative test of various ed by marketing stimuli (e.g., communication, price, store perspectives on impulse buying brings the relative impacts ambience, merchandise elements). The size of the motive ef- of various dominant explanatory factors in each perspective fects (r = .34 for hedonic, r = .36 for utilitarian) implies their into sharper relief. potential significance; they could be activated by communica- In summary, our meta-analysis explores the direct effects of tions delivered to customers in stores, using digital displays consumer traits, motives, and resources and marketing stimuli (Roggeveen et al. 2016) or mobile devices (Grewal et al. on impulse buying, along with the mediating impacts of self- 2018a). Furthermore, the synergistic effects of various com- control and positive and negative emotions. Our joint exami- munication and promotional elements on impulse buying war- nation of these mediators reveals the inner affective and cog- rant further exploration. nitive psychological processes of impulse buying and their Most studies make assumptions about the context, rath- relations. Industry and method moderators also influence im- er than actively manipulating or exploring its effects. In pulse buying. This meta-analysis provides a comprehensive most cases, the context refers solely to the product cate- summary of extant research, underlying various implications. gory (e.g., food, beauty products), shopping environment We hope it also sheds some new lights on directions for re- (e.g., retail store, online), or industry (grocery, apparel). search that can continue to enhance our understanding of im- But various other contextual cues could be relevant, such pulse buying. 402 J. of the Acad. Mark. Sci. (2020) 48:384–404 Open Access This article is distributed under the terms of the Creative Dholakia, U. M. (2000). Temptation and resistance: An integrated model Commons Attribution 4.0 International License (http:// of consumption impulse formation and enactment. Psychology & creativecommons.org/licenses/by/4.0/), which permits unrestricted use, Marketing, 17(11), 955–982. distribution, and reproduction in any medium, provided you give appro- Dittmar, H., & Bond, R. (2010). I want it and I want it Now': Using a priate credit to the original author(s) and the source, provide a link to the temporal discounting paradigm to examine predictors of consumer Creative Commons license, and indicate if changes were made. impulsivity. British Journal of Psychology, 101(4), 751–776. Dittmar, H., Beattie, J., & Friese, S. (1995). Gender identity and material symbols: Objects and decision considerations in impulse purchases. Journal of Economic Psychology, 16(3), 491–511. References Dittmar, H., Halliwell, E., & Stirling, E. (2009). Understanding the im- pact of thin media models on Women’s body-focused affect: The Abratt, R., & Goodey, S. D. (1990). Unplanned buying and in-store roles of thin-ideal internalization and weight-related self-discrepan- stimuli in supermarkets. Managerial and Decision Economics, cy activation in experimental exposure effects. Journal of Social and 11(2), 111–121. Clinical Psychology, 28(1), 43–75. Adelaar, T., Chang, S., Lancendorfer, K. M., Lee, B., & Morimoto, M. Donovan, R. J., & Rossiter, J. R. (1982). Store atmosphere: An environ- (2003). Effects of media formats on emotions and impulse buying mental psychology approach. Journal of Retailing, 58(1), 34–57. intent. Journal of Information Technology, 18(4), 247–266. Eroglu, S. A., Machleit, K. A., & Davis, L. A. (2003). Empirical testing of Amos, C., Holmes, G. R., & Keneson, W. C. (2014). A meta-analysis of a model of online store atmospherics and shopper responses. consumer impulse buying. Journal of Retailing and Consumer Psychology & Marketing, 20(2), 139–150. Services, 21(2), 86–97. Fang, E., Palmatier, R. W., & Steenkamp, J. E. M. (2008). Effect of Andrews, J. C., Durvasula, S., & Akhter, S. H. (1990). A framework for service transition strategies on firm value. Journal of Marketing, conceptualizing and measuring the involvement construct in adver- 72(5), 1–14. tising research. Journal of Advertising, 19(4), 27–40. Field, A. P. (2001). Meta-analysis of correlation coefficients: A Monte Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Carlo comparison of fixed- and random-effects models. Measuring hedonic and utilitarian shopping value. Journal of Psychological Methods, 6,161–180. Consumer Research, 20(4), 644–656. Finley, A. J., & Schemichel, B. J. (2018). Aftereffects of self-control on Baker, J., Levy, M. L., & Grewal, D. (1992). An experimental approach to positive emotional reactivity. Personality and Social Psychology make retail store environmental decisions. Journal of Retailing, Bulletin, 45, 1011–1027. https://doi.org/10.1177/ 68(4), 445–460. 0146167218802836. Baumeister, R. F. (2002). Yielding to temptation: Self-control failure, Fishbach, A., & Labroo, A. A. (2007). Be better or be merry: How mood impulsive purchasing, and consumer behavior. Journal of affects self-control. Journal of Personality and Social Psychology, Consumer Research, 28(4), 670–676. 93(2), 158–173. Baumeister, R. F., Sparks, E. A., Stillman, T. F., & Vohs, K. D. (2008). Foxall, G. R. (2007). Explaining Consumer Choice. Basingstoke: Free will in consumer behavior: Self-control, Ego depletion, and Palgrave Macmillan. choice. Journal of Consumer Psychology, 18(1), 4–13. Foxall, G. R., & Greenley, G. E. (1999). Consumers' emotional responses Beatty, S., & Ferrell, M. E. (1998). Impulse buying: Modeling its precur- to service environments. Journal of Business Research, 46(2), 149– sors. Journal of Retailing, 74(2), 169–191. 158. Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service Geyskens, I., Krishnan, R., Steenkamp, J. E. M., & Cunha, P. V. (2009). A convenience. Journal of Marketing, 66(3), 1–17. review and evaluation of meta-analysis practices in management Billieux, J., Gay, P., Rochat, L., & Van der Linden, M. (2010). The role of research. JournalofManagement, 35(2), 393–419. urgency and its underlying psychological mechanisms in problem- Grewal, D., & Marmorstein, H. (1994). Market price variation, perceived atic behaviours. Behaviour Research and Therapy, 48(11), 1085– price variation, and consumers' price search decisions for durable goods. Journal of Consumer Research, 21(3), 453–460. Blut, M., Teller, C., & Floh, A. (2018). Testing retail marketing-mix Grewal, D., Ahlbom, C., Beitelspacher, L. S., Noble, S. M., & Nordfalt, J. effects on patronage: A meta-analysis. JournalofRetailing,94(2), (2018a). In-store Mobile phone use and customer shopping behav- 113–135. ior: Evidence from the field. Journal of Marketing., 82(4), 102–126. Chamorro-Premuzic, T. (2015), The Psychology of Impulsive Shopping, Grewal, D., Puccinelli, N., & Monroe, K. B. (2018b). Meta-analysis: The Guardian,November26, https://www.theguardian.com/media- Integrating accumulating knowledge. Journal of the Academy of network/2015/nov/26/psychology-impulsive-shopping-christmas- Marketing Science, 46(1), 9–30. black-friday-sales [Accessed March 13, 2019]. Herabadi, A. G., Verplanken, B., & Van Knippenberg, A. (2009). Cheung, T. L., Gillebaart, M., Kroese, F., & Ridder, D. D. (2014). Why Consumption experience of impulse buying in Indonesia: are people with higher self-control happier? The effect of trait self- Emotional arousal and hedonistic considerations. Asian Journal of control on happiness as mediated by regulatory focus. Frontiers in Social Psychology, 12(1), 20–31. Psychology, 5(July). https://doi.org/10.3389/fpsyg.2014.00722. Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: Cohen, J. B., & Andrade, E. B. (2004). Affective intuition and task- Emerging concepts, methods and propositions. Journal of contingent affect regulation. Journal of Consumer Research, Marketing, 46(Summer), 92–101. 31(2), 358–367. Hoch, S. J., & Loewenstein, G. F. (1991). Time-inconsistent preferences Coley, A., & Burgess, B. (2003). Gender differences in cognitive and and consumer self-control. JournalofConsumerResearch, 17(4), affective impulse buying. Journal of Fashion Marketing and 429–507. Management, 7(3), 282–295. Hofmann, W., Baumeister, R. F., Förster, G., & Vohs, K. D. (2012). Davis, R., & Sajtos, L. (2009). Anytime, anywhere: Measuring the ubiq- Everyday temptations: An experience sampling study of desire, con- uitous Consumer's impulse purchase behavior. International flict, and self-control. Journal of Personality and Social Psychology, JournalofMobile Marketing,4(1), 15–22. 102(6), 1318–1325. Dawson, S., Bloch, P. H., & Ridgway, N. M. (1990). Shopping motives, Hunter,J.E., &Schmidt,F.L.(2004). Methods of meta-analysis: Correcting error and Bias in research findings. Thousand Oaks: emotional states, and retail outcomes. Journal of Retailing, 66- Sage Publications. (winter), 408–427. J. of the Acad. Mark. Sci. (2020) 48:384–404 403 Jones, M. A., Reynolds, K. E., Weun, S., & Beatty, S. E. (2003). The Palmatier, R. W., Houston, M. B., & Hulland, J. (2018). Review articles: Purpose, process, and structure. Journal of the Academy of product-specific nature of impulse buying tendency. Journal of Business Research, 56(7), 505–511. Marketing Science, 46(1), 1–8. Kacen, J. J., & Lee, J. A. (2002). The influence of culture on consumer Parboteeah, D. V., Valacich, J. S., & Wells, J. D. (2009). The influence of impulsive buying behavior. Journal of Consumer Psychology, website characteristics on a Consumer's urge to buy impulsively. 12(2), 163–176. Information Systems Research, 20(1), 60–78. Park, E. J., Kim, E. Y., Funches, V. M., & Foxx, W. (2012). Apparel Kirca, A. H., Jayachandran, S., & Bearden, W. O. (2005). Market orien- tation: A meta-analytic review and assessment of its antecedents and product attributes, web browsing, and E-impulse buying on shop- impact on performance. Journal of Marketing, 69(2), 24–41. ping websites. Journal of Business Research, 65(11), 1583–1589. Kukar-Kinney, M., Ridgway, N. M., & Monroe, K. B. (2012). The role of Peck, J., & Childers, T. L. (2006). If I touch it I have to have it: Individual Price in the behavior and purchase decisions of compulsive buyers. and environmental influences on impulse purchasing. Journal of Journal of Retailing, 88(1), 63–71. Business Research, 59(6), 765–769. Kwon, H. H., & Armstrong, K. L. (2002). Factors influencing impulse Peterson, R. A., & Brown, S. P. (2005). On the use of Beta coefficients in buying of sport team licensed merchandise. Sport Marketing meta-analysis. Journal of Applied Psychology, 90(1), 175–181. Quarterly, 11(3), 151–163. Pick, D., & Eisend, M. (2014). Buyers’ perceived switching costs and Lin, Y. H., & Chen, C. F. (2013). Passengers' shopping motivations and switching: A meta-analytic assessment of their antecedents. Journal commercial activities at airports–the moderating effects of time pres- of the Academy of Marketing Science, 42(2), 186–204. sure and impulse buying tendency. Tourism Management, 36,426– Punj, G. (2011). Impulse buying and variety seeking: Similarities and 434. differences. Journal of Business Research, 64(7), 745–748. Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Ramanathan, S., & Menon, G. (2006). Time-varying effects of chronic Thousand Oaks: Sage. hedonic goals on impulsive behavior. Journal of Marketing Liu, Y., Li, H., & Hu, F. (2013). Website attributes in urging online Research, 43(4), 628–641. impulse purchase: An empirical investigation on consumer percep- Roggeveen, A. L., Nordfalt, J., & Grewal, D. (2016). Do digital displays tions. Decision Support Systems, 55(3), 829–837. enhance sales? Role of retail format and message content. Journal of Lucas, M., & Koff, E. (2014). The role of impulsivity and of self- Retailing, 92(1), 122–13 perceived attractiveness in impulse buying in women. Personality Rook, D. W. (1987). The buying impulse. Journal of Consumer Individual Differences, 56(January), 111–115. Research, 14(2), 189–199. Luo, X. (2005). How does shopping with others influence impulsive Rook, D. W., & Fisher, R. J. (1995). Normative influences on impulsive purchasing? JournalofConsumerPsychology, 15(4), 288–294. buying behavior. Journal of Consumer Research, 22(3), 305–313. Mattila, A. S., & Wirtz, J. (2001). Congruency of scent and music as a Rook, D. W., & Gardner, M. P. (1993). In the mood: Impulsive Buyings’ driver of in-store evaluations and behavior. Journal of Retailing, antecedents. In J. Arnold-Costa & R. W. Belk (Eds.), Research in 77(2), 272–289. consumer behavior (pp. 1–28). Greenwich: JAI Press. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental Rook, D. W., & Hoch, S. J. (1985). Consuming Impulses. In E. C. psychology. Cambridge: MIT Press. Hirschman & M. B. Holbrook (Eds.), Advances in consumer Mick, D. G., & Demoss, M. (1990). Self-gifts: Phenomenological in- research (pp. 23–27). Chicago, IL: Association for Consumer sights from four contexts. Journal of Consumer Research, 17(3), Research, 23-27). 322–332. Rosenthal, R. (1979). The 'File drawer Problem' and tolerance for null Mohan, G., Sivakumaran, B., & Sharma, P. (2013). Impact of store envi- results. Psychological Bulletin, 86(3), 638–641. ronment on impulse buying behavior. European Journal of Rostoks, L. (2003). Tapping into the shopper impulse. Canadian Grocer, Marketing, 47(10), 1711–1732. 117(October), 34–35. Morrin, M., & Chebat, J. C. (2005). Person-place congruency: The inter- Samaha, S. A., Beck, J. T., & Palmatier, R. W. (2014). The role of culture active effects of shopper style and atmospherics on consumer ex- in international relationship marketing. JournalofMarketing, 78(5), penditures. Journal of Service Research, 8(2), 181–191. 78–98. Mowen, J. C., & Spears, N. (1999). Understanding compulsive buying Sharma, A., & Stafford, T. F. (2000). The Effect of Retail Atmospherics among college students: A hierarchical approach. Journal of on Customers' Perceptions of Salespeople and Customer Persuasion: Consumer Psychology, 8(4), 407–430. An Empirical Investigation. Journal of Business Research, 49(2), Muraven, M., & Baumeister, R. F. (2000). Self-regulation and depletion 183–191. Sharma, P., Sivakumaran, B., & Marshall, R. (2010). Impulse buying and of limited resources: Does self-control resemble a muscle?. Psychological Bulletin, 126(2), 247–259. variety seeking: A trait-correlates perspective. Journal of Business Research, 63(3), 276–283. O’Brien, S. (2018). Consumers Cough Up $5,400 a Year on Impulse Purchases. CNBC.com, February 23, Retrieved July 30, 2018 from Sharma, P., Sivakumaran, B., & Marshall, R. (2014a). Looking beyond impulse buying: A cross-cultural and multi-domain investigation of https://www.cnbc.com/2018/02/23/consumers-cough-up-5400-a- consumer impulsiveness. European Journal of Marketing, 48(5/6), year-on-impulse-purchases.html. Accessed 30 Jul 2018. 1159–1179. O'Guinn, T. C., & Faber, R. J. (1989). Compulsive buying: A phenome- Silvera, D. H., Lavack, A. M., & Kropp, F. (2008). Impulse buying: the nological exploration. Journal of Consumer Research, 16(2), 147– 157. role of affect, social influence, and subjective wellbeing. Journal of Consumer Marketing, 25(1), 23–33. Olsen, S. O., Tudoran, A. A., Honkanen, P., & Verplanken, B. (2016). Stilley, K. M., Inman, J. J., & Wakefield, K. L. (2010). Planning to make Differences and similarities between impulse buying and variety seeking: A personality-based perspective. Psychology & unplanned purchases? The role of in-store slack in budget deviation. Journal of Consumer Research, 37(2), 264–278. Marketing, 33(1), 36–47. Orsingher, C., Valentini, S., & Angelis, M. (2009). A meta-analysis of Sultan, A. J., Joireman, J., & Sprott, D. E. (2012). Building consumer self-control: The effect of self-control exercises on impulse buying satisfaction with complaint handling in services. Journal of the Academy of Marketing Science, 38(2), 169–186. urges. Marketing Letters, 23(1), 61–72. Palmatier, R. W., Dant, R. P., & Grewal, D. (2007). A comparative lon- Thompson, E. R., & Prendergast, G. P. (2015). The influence of trait affect and the five-factor personality model on impulse buying. gitudinal analysis of theoretical perspectives of Interorganizational relationship performance. Journal of Marketing, 71(4), 172–194. Personality and Individual Differences, 76,216–221. 404 J. of the Acad. Mark. Sci. (2020) 48:384–404 Tice, D. M., Bratslavsky, E., & Baumeister, R. F. (2001). identity construction. Journal of Personality and Social Psychology, 90(2), 308–333. Emotional distress regulation takes precedence over impulse control: If you feel bad, do it! Journal of Personality and Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psy- Social Psychology, 80(1), 53–67. chometric meta-analysis and structural equations modeling. Personnel Psychology, 48(4), 865–885. Tifferet, S., & Herstein, R. (2012). Gender differences in brand commit- Vohs, K. D., & Faber, R. J. (2007). Spent resources: Self-regulatory ment, impulse buying, and hedonic consumption. Journal of resource availability affects impulse buying. Journal of Consumer Product and Brand Management, 21(3), 176–182. Research, 33(4), 537–547. Troisi, J. D., Christopher, A. C., & Marek, P. (2006). Materialism and Weinberg, P., & Gottwald, W. (1982). Impulsive consumer buying as a money spending disposition as predictors of economic and person- result of emotions. Journal of Business Research, 10(1), 43–57. ality variables. North American Journal of Psychology, 8(3), 421– Whiteside, S. P., & Lynam, D. R. (2001). The five factor model and impulsivity: Using a structural model of personality to under- Underhill, P. (2000). Why we buy: The science of shopping.New York: stand impulsivity. Personality and Individual Differences, Simon and Schuster. 30(4), 669–689. Van Trijp, H. C. M., & Steenkamp, J. E. M. (1992). Consumers' variety Wood, M. (1998). Socio-economic status, delay of gratification, and im- seeking tendency with respect to foods: Measurement and manage- pulse buying. Journal of Economic Psychology, 19(3), 295–320. rial implications. European Review of Agricultural Economics, Zhang, Y., Winterich, K. P., & Mittal, V. (2010). Power distance belief 19(2), 181–195. and impulsive buying. Journal of Marketing Research, 47(5), 945– Verhagen, T., & van Dolen, W. (2011). The influence of online store beliefs on consumer online impulse buying: A model and empirical Zhou, L., & Wong, A. (2004). Consumer impulse buying and in-store application. Information and Management, 48(8), 320–327. stimuli in Chinese supermarkets. Journal of International Consumer Verplanken, B., & Herabadi, A. (2001). Individual differences in impulse Marketing, 16(2), 37–53. buying tendency: Feeling and no thinking. European Journal of Zuckerman, M. (1994). Behavioral expressions and biosocial bases of Personality, 15(1), 71–83. sensation seeking. Cambridge: Cambridge University Press. Verplanken, B., & Sato, A. (2011). The psychology of impulse buying: An integrative self-regulation approach. Journal of Consumer Policy, 34(2), 197–210. Verplanken, B., Herabadi, A. G., Perry, J. A., & Silvera, D. H. (2005). Consumer style and health: The role of impulsive buying in un- Publisher’snote Springer Nature remains neutral with regard to healthy eating. Psychology & Health, 20(4), 429–441. jurisdictional claims in published maps and institutional affiliations. Vignoles, V. L., Regalia, C., Manzi, C., Golledge, J., & Scabini, E. (2006). Beyond self-esteem: Influence of multiple motives on

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