Abstract This research examines how people’s mental accounting is influenced by their thinking style (analytic vs. holistic). Mental accounting literature shows that people mentally allocate their resources into certain accounts and track expenses against them. The current research, however, finds that while analytic thinkers show such “mental labeling effect,” the holistic thinkers’ mental accounting system is flexible. Specifically, analytic thinkers limit their expenses of rebate money to similar category purchases, whereas holistic thinkers show preference for both similar and dissimilar category items (studies 1 and 2). Study 3 shows the mental accounting divergence across analytic- and holistic-thinking groups by examining how they use mental accounting rules in spending gift cards (vs. cash). Study 4 exhibits the underlying psychological process in showing that this effect is attributed to differences in categorization flexibility between the analytic- and holistic-thinking groups. In addition, the above effects are moderated by product type. The divergence in mental accounting between analytic and holistic thinkers is mostly evident in utilitarian (vs. hedonic) consumption instances. Study 5 provides further insights into the moderation effect. The implications of these findings include divergence in cross-category effects of price promotions, and the effect of cross-market discounts between analytic and holistic thinkers. thinking style, analytic thinking, holistic thinking, mental accounting, rebate, categorization Cognitive operations involving the organization, evaluation, and tracking of financial information are termed “mental accounting” by Thaler (1980, 1985). The theory of mental accounting (Thaler 1980) implies that, as with financial accounting systems, people assign labels to sources and uses of funds (Heath 1995; Heath and Soll 1996; Shefrin and Thaler 1988; Thaler 1980, 1985, 1999), and track expenses within their mental accounting system (Henderson and Peterson 1992; Thaler 1980). When a mental account is established, purchases that are compatible with the mental account find favor over noncongruent options. Prior research documents such tendencies in showing that: consumers prefer retailer-specific items while shopping with retailer-specific gift cards (Reinholtz, Bartels, and Parker 2015); affective tags of money influence subsequent expenses (Levav and McGraw 2009); consumers balance expenses to enhance self-control (Heath and Soll 1996; Helion and Gilovich 2014); the temporal separation of consumption from purchase influences product evaluation (Shafir and Thaler 2006); the perception of cost of waiting is influenced by the integration and the segregation of outcomes (Leclerc, Schmitt, and Dubé 1995); consumption decoupling influences the enjoyment of consumption episodes (Prelec and Loewenstein 1998); and that people like to spend windfalls (as opposed to regular income) on hedonic purchases (Milkman and Beshears 2009). Collectively, the evidence suggests that people attempt to institute structure in their mental account by following the norm of mentally allocating resources into certain accounts, and subsequently evaluating expenses in reference to those accounts. While prior research adequately exhibits mental accounting’s behavioral outcomes, and why mental accounting matters, little effort has been invested in understanding which factors stimulate allocation and organization of resources within the mental accounting system. By assigning tags to resources and subsequently tracking expenses against these tags, consumers follow a norm that keeps organization within their overall mental accounting systems. Such reliance on logic and norms, however, evidently varies with the activation of various mindsets. For example, prior research shows a fundamental divergence in categorization between analytic and holistic thinkers (Choi, Nisbett, and Norenzayan 1999; Escalas and Bettman 2005; Markus and Kitayama 1991). While evaluating objects, analytic thinkers assign them to unique categories and evaluate them in reference to category-specific attributes. Holistic thinkers, on the other hand, emphasize relationships across categories and events, demonstrating flexibility in categorization (Jain, Desai, and Mao 2007; Masuda and Nisbett 2001; Monga and John 2010; Munro 1985; Nisbett et al. 2001; Zhang 1985). In my research, utilizing a cross-category consumption context, I demonstrate that analytic thinkers’ rule-based evaluation tendencies empower them to institute a well-defined structure within their mental accounting systems, resulting in an enhanced susceptibility to the mental labeling effect. Holistic thinkers’ connected-thinking orientation, on the other hand, induces flexibility (Choi and Choi 2002; English and Chen 2007) and deviation from mental accounting norms, resulting in an attenuated susceptibility to the mental labeling effect. My findings thus fill an ostensible gap in the literature related to both mental accounting and thinking style (analytic vs. holistic). In addition, I find that the above effect is moderated by product type. The divergence in exhibiting the mental labeling effect across analytic and holistic thinkers is mostly prevalent in utilitarian (vs. hedonic) consumption instances. I conjecture that this effect takes place mainly due to people’s greater reliance on cognitive norms when pursuing instrumental goals as prevalent in utilitarian (vs. hedonic) consumption instances. Below, I review the relevant literature on mental accounting and thinking style to develop my hypotheses. I then present five studies designed to test my proposed hypotheses. In these studies, thinking style (analytic vs. holistic) was situationally induced by different priming instruments as well as measured within participants. Studies 1–3 present a corpus of evidence on the existence of the proposed phenomenon and its robustness across various consumption contexts. Study 4 reveals its underlying psychological process. Study 5 provides important insights into the moderation effect by product type. In closing, I discuss the theoretical and practical implications of my findings. THEORETICAL FRAMEWORK Mental Accounting and the Labeling Effect The prevalence of a mental accounting system influences a wide array of behaviors (Heath 1995; Heath and Soll 1996). For example, mental budgeting is often used as a self-control mechanism; consumers are reluctant to spend more on entertaining events when they have already spent money on entertainment (Heath and Soll 1996). Moreover, consumers spend their resources differently depending on how those resources are labeled. When a portion of wealth is labeled as “frivolous,” that wealth generates frivolous (rather than virtuous) expenses. Henderson and Peterson (1992) find an enhanced likelihood of spending money for a vacation when respondents received $2,000 as a gift (carrying a hedonic label) rather than as a work bonus (carrying a more functional label). Other related research finds that people tend to spend more when they categorize their income as “unexpected,” rather than “expected,” and they are more likely to spend unexpected windfalls on fun activities (as these windfalls are more affect-arousing and hedonic in nature) than they would expected windfalls of the same size (Arkes et al. 1994). Epley, Mak, and Idson (2006) find that differential tendencies of spending windfalls depend upon whether the windfall is framed as a gain from one’s current state or a return to a previous wealth state. Finally, mental accounting influences people’s attitude toward risk (Barberis and Huang 2001). More recent evidence of people’s mental accounting of expenses is particularly motivating for the current research. Reinholtz et al. (2015) find that purchases that are congruent with the purpose of the mental account are favored more than those that are less congruent. When people shop with retailer-specific gift cards, they possess a retailer-specific mental account, which leads to their enhanced preference for product items that are more typical of the retailer. Levav and McGraw (2009) find that when monetary resources possess negative tags, people tend to avoid spending them for fun activities. Along similar lines, Helion and Gilovich (2014) find that consumers assign “nonserious” mental labels to gift cards and prefer paying for hedonic items using gift cards instead of cash. All this evidence collectively suggests that people’s tendencies to mentally categorize expenses and to track those expenses against the category labels is a phenomenon that is widely prevalent across a number of decision-making contexts. However, people differ in their disposition to categorization. Analytic thinkers possess a greater predilection to assign objects into categories than holistic thinkers do (Nisbett et al. 2001). Therefore, the mental labeling effect (assigning money to categories and making category-consistent purchases) should be stronger among analytic-thinking individuals than holistic-thinking individuals. I propose that individuals with two divergent thinking styles—the analytic thinkers and the holistic thinkers—differ in the prevalence of their mental accounting systems. This difference can be explained by their rule-based versus relations-based thinking orientations. Analytic versus Holistic Thinking: Orientation to Rules versus Relations Prior research shows that analytic thinking is characterized by viewing the world as composed of isolated elements, while holistic thinking is characterized by viewing the world as composed of connected elements (Lalwani and Shavitt 2013; Masuda and Nisbett 2001; Monga and John 2007, 2008; Nisbett et al. 2001). For example, when provided with an Embedded Figures Test (EFT), holistic thinkers, due to their connected-thinking orientation, found it difficult to isolate elements embedded within a context (Monga and John 2007). Holistic thinkers also tend to connect objects to their context when describing them, whereas analytic thinkers can engage in context-independent thinking (Masuda and Nisbett 2001). Moreover, when asked about the degree of association among objects, holistic thinkers reported greater degrees of association than analytic thinkers (Ji, Peng, and Nisbett 2000). The discrete versus connected nature of cognition—as evidenced across analytic and holistic thinkers—differentially impacts marketplace decisions such as evaluation of brand extension fit. Relative to analytic thinkers, holistic thinkers perceive greater fit among a parent brand and the extended product category (Monga and John 2007), even when such connections are more difficult to ascertain (Monga and John 2010). Analytic versus holistic thinking also differentially influence consumers’ price-quality judgments and reactions to negative publicity. Due to their connected-thinking habits, holistic thinkers demonstrate a greater predilection to use price as a signal of quality, relative to analytic thinkers (Lalwani and Shavitt 2013). Moreover, holistic thinkers show weaker reactions to negative publicity of a brand, as their reliance on contextual information leads to little or no revision of beliefs about the parent brand in the face of negative publicity (Monga and John 2008). Such concerns of connectedness and separateness, embedded in holistic- versus analytic-thinking mindsets, are reflected in consumers’ categorization tendencies as well. A narrow subordinate categorization tendency is evident among analytic thinkers, whereas holistic thinkers possess a broad superordinate categorization tendency (Jain et al. 2007). Norenzayan et al. (2002) show that analytic thinking induces the application of formal reasoning strategies, which follow a logical structure and an observance of rules, while holistic thinkers rely on intuitive reasoning. Therefore, analytic thinkers’ categorization relies on formal application of rules, whereas holistic thinkers rely on exemplars in their categorization. In sum, while analytic thinking promotes rule-based thinking, holistic thinking promotes relations-based thinking. This divergence will be reflected in both groups’ nature of mental accounting. That is, due to their rule-based and discrete-thinking orientation, analytic thinkers will engage in narrowly defined inflexible mental accounting. Norms pertaining to mental accounting govern people’s allocation of resources into particular accounts, leading people to spend them on account-consistent purchases (Thaler 1999). The mental accounting norm for spending rebate money would be to spend it on purchases similar to the source of the rebate (i.e., spending a rebate obtained from Blu-ray players on digital entertainment products). Since analytic thinkers are more inclined toward following rules and exhibiting inflexibility in their mental accounting, for these individuals, spending the rebate money on dissimilar category purchases represents a violation of mental accounting norms. As a consequence, they will keep their expenditures from the rebate within the boundaries of similar category purchases. On the other hand, holistic thinkers engage in broadly defined mental accounting. Due to the connected nature of their thinking and their flexible mental accounting, holistic thinkers will easily find connections among various product categories. As a result, they will be tolerant of supporting multiple category purchases with rebates, since the money will be mentally assigned to a broadly defined mental account. Therefore, I posit that: H1: The mental labeling effect will be exhibited (vs. voided) when an analytic- (vs. holistic-) thinking mindset is activated. H2: The above effect is attributable to greater flexibility (vs. inflexibility) within mental accounting systems as promoted by holistic (vs. analytic) thinking. Moderating Role of Product Type (Hedonic vs. Utilitarian) Hedonic consumption primarily relates to the emotive aspects of consumers’ experience with the consumption, whereas utilitarian consumption involves greater use of cognition (Alba and Williams 2013; Havlena and Holbrook 1986; Hirschman and Holbrook 1982; Mano and Oliver 1993; Pham and Avnet 2004; Shiv and Fedorikhin 1999). The hedonic/utilitarian literature provides substantial evidence that utilitarian evaluation of consumption is closely aligned with cognitive functioning, whereas hedonic evaluation is associated with arousal and enjoyment from experiences with the consumption (Khan, Dhar, and Wertenbroch 2005; Mano and Oliver 1993; Millar and Tesser 1986). The preference for affect-rich hedonic items is elicited based on intuition—a fluent realization of liking or disliking—whereas preference for utilitarian items is elicited through analytical rule-based thinking and deliberate assessments (Khan et al. 2005). A number of prior research findings attest to this statement. For example, consumers’ preference for hedonic items is enhanced when their cognitive resources are constrained (Shiv and Fedorikhin 1999); rational (emotional) attitudes are more prevalent in utilitarian (hedonic) consumption instances (Kronrod, Grinstein, and Wathieu 2012); and price endings that require greater cognitive capacity to process generate processing fluency for utilitarian consumptions (Wadhwa and Zhang 2015). I posit that categorization inflexibility, induced by mental accounting norm following, will be enhanced in utilitarian consumption instances, as they provide greater scope for rule-based thinking. That is, since utilitarian (vs. hedonic) consumption instances provide greater scope for rule-based thinking, analytic thinkers will demonstrate stronger cognitive inflexibility, and subsequently a stronger mental labeling effect in such consumption instances. Moreover, flexibility in categorization, as evidenced among holistic thinkers, induces norm ignorance tendencies (Huang 1981; Murray et al. 1990; Walker and Gibbins 1989). Such norm ignorance exerts a disinhibiting influence, facilitating hedonic choice (Khare and Chowdhury 2015). People’s preference for hedonic items is inhibited when positive associations with such choices (affect richness) are subdued and negative associations (being a less thoughtful choice) become salient. In the presence of the disinhibiting effect, as evidenced among cognitively flexible holistic thinkers, the salience of negative associations will be attenuated, dissolving barriers to hedonic choice. In the case of my current research, the source of inhibition would be the mental labeling effect, as exercised when people adhere to rule-based thinking (i.e., analytic thinking), and amplified when they are provided greater scope for cognitive deliberation. The mental accounting norm will prohibit spending of consumer savings (e.g., rebates) on dissimilar category items. Analytic thinkers’ inflexible categorization will induce this norm following, and the mental labeling effect will inhibit dissimilar category purchases with their rebate money. However, this inhibition will be stronger in utilitarian (vs. hedonic) consumption instances. Such contexts provide greater scope of rule-based thinking relative to hedonic consumption contexts, leading to an enhanced inhibition effect among individuals with inflexible categorization tendencies (i.e., analytic thinkers). This effect will consequently suppress their pro-hedonic preference when shopping with “utilitarian” money. Since holistic thinkers possess flexible categorization tendencies, they will overlook mental accounting norms, allowing the spending of rebate money on dissimilar product categories. The combined effect will lead to a stronger divergence in the mental labeling effect between the analytic- and holistic-thinking groups in utilitarian consumption instances, relative to hedonic ones. The foregoing discussion leads to the following hypothesis: H3: The effect of thinking style on mental labeling will be moderated by product type, such that the divergence in the mental labeling effect across analytic- and holistic-thinking groups will be more prominent for utilitarian (vs. hedonic) consumption episodes. While I suggest hypothesis 3 as above, one may offer a theory relying on fit or processing fluency. That is, one may argue that analytic thinkers rely on rules in their decision processes, and utilitarian consumption contexts evoke rule-based decision making, introducing a fit between the consumption contexts and thinking style. This fit or fluency explains a stronger mental labeling effect among analytic thinkers for utilitarian (vs. hedonic) consumption instances. If this fluency-based explanation is indeed plausible, then one may wonder whether fluency-based choice will emerge for holistic thinkers while spending money with hedonic labels rather than functional (cognitive) labels (i.e., choice share of hedonic items being enhanced when spending rebates from affect-rich hedonic purchases). That is, since holistic thinkers are immune to rule adherence, they rely on “affective fluency” in choice tasks. While prior research provides evidence of differences in rule-based thinking between analytic- and holistic-thinking groups, holistic thinkers’ reliance on affective fluency is difficult to predict given prior findings. Moreover, this line of reasoning supports the assertion that avoidance of rule-based thinking effectively induces reliance on affective criteria in decision tasks. This argument finds minimal support in prior literature. However, as mentioned above, prior research indicates that categorization flexibility, an inherent cognitive trait of holistic thinkers, induces a disinhibition effect, which facilitates hedonic consumption. This disinhibition does not necessarily imply that categorization flexibility will induce affect-based decision making. It merely suggests that categorization flexibility, as evidenced among holistic thinkers, will dissolve barriers to hedonic consumption. Therefore, I believe that the divergence in rule-based thinking, and subsequent difference in categorization flexibility between the analytic- and holistic-thinking groups, is a more plausible basis for the effect theorized in hypothesis 3. The proposed hypotheses were tested in a series of five studies. Study 1 provides the preliminary evidence in support of my prediction that analytic thinkers exhibit a greater mental labeling tendency than holistic thinkers. This effect is shown in the context of spending rebate money. A labeling effect will be observed when a consumer intends to spend the rebate money on products belonging to a similar category to that of the initial purchase. For example, consumers will show the mental labeling effect if they intend to spend the rebate money obtained from a digital entertainment item on other items that belong to a similar category (e.g., spending the rebate obtained from the purchase of a Blu-ray player on products such as headphones and/or a sound bar). My expectation is that such behavior will emerge when an analytic-thinking style is situationally activated. This effect will not be manifested when holistic thinking is situationally activated. Similarities and Differences between Self-Construal and Analytic/Holistic Thinking Individual differences in analytic/holistic thinking and self-construal are both rooted in people’s cultural orientation. While analytic thinkers think in discrete terms and engage in objective evaluation of objects, holistic thinkers establish connections among objects and engage in integration with contexts in their evaluation. Therefore, both analytic/holistic thinking and self-construal explain an important cultural aspect: connected- versus separated-thinking orientations (Nisbett et al. 2001; Oyserman and Lee 2008). Lalwani and Shavitt (2013) find that interdependents engage in holistic (vs. analytic) thinking and perceive interrelations among factors, which explains their greater use of price information to judge product quality. Moreover, priming tasks (e.g., the pronoun-circling task) and ethnicity measures that activate or determine possession of self-construal also activate analytic/holistic thinking (Lalwani and Shavitt 2013; Monga and John 2007). Despite such similarities, the concepts differ in their scope of explaining people's behavioral outcomes. While analytic/holistic thinking mainly explains people’s differences in cognitive styles, self-construal impacts factors in addition to cognition, such as their values, self-concept, and relational orientations (Markus and Kitayama 1991; Oyserman, Coon, and Kemmelmeier 2002; Triandis 1995). In some of my studies I have used a priming technique, the pronoun-circling task (Gardner, Gabriel, and Lee 1999), which has been used in the self-construal literature to prime respondents into analytic/holistic thinking. Oyserman and Lee (2008) show that among various instruments for priming self-construal that are used in prior literature, the strongest impact on cognition (analytic vs. holistic) is exerted by the pronoun-circling task (please see the web appendix for further discussion on this topic). In another study, I have used an Embedded Figures Test, which induces analytic versus holistic thinking by activating context-dependent versus context-independent thought processes. STUDY 1 Calculation of Choice Share In studies 1, 4 and 5, where the study design allowed respondents to choose items from multiple categories, I calculated choice share of items in the target category using the formula: (number of items chosen from the target category) / (total number of products chosen). For example, if a person chose two products, all from category A, his/her choice share of category A items would be 100%. If a person chose one product from category A and 1 from category B, then his/her choice share of category A products would be 50%. I believe this metric accurately represents the preference structure that I intended to measure. For my purpose, it was important to know if the rebate from a product similar to category A products (e.g., Blu-ray player) is spent on items belonging to category A (e.g., digital entertainment items) or if the rebate is used in purchasing category B products (e.g., cleaning accessories) as well. If the entire expenditure using the rebate amount is spent on category A products, then it is the strongest representation of a narrow definition of mental account regardless of the number of products chosen within the category. That is, if a respondent spent the rebate amount only on category A products, then the respondent is adhering to mental accounting norms by spending the rebate money on label-consistent purchases, regardless of whether he/she chose one item or all five items from the category. Design and Procedure Study 1 utilized a 2 (thinking style: analytic vs. holistic) × 2 (rebate from: more hedonic product [Blu-ray player] vs. less hedonic product [vacuum cleaner]) design. Respondents were first randomly assigned to either the analytic or the holistic version of the pronoun-circling task (Gardner et al. 1999). Prior research shows that the pronoun-circling task effectively manipulates analytic versus holistic thinking (Monga and John 2007). Following the priming task, respondents were assigned to either the digital entertainment condition or the cleaning accessories condition. In this study, the purchase of items from an affect-rich hedonic category (digital entertainment) was contrasted with the purchase of items from a utilitarian category (cleaning accessories), introducing a hedonic/utilitarian dichotomy. In one of the rebate conditions, respondents imagined receiving a rebate from a Blu-ray player and were contemplating using the rebate money on the purchase of digital entertainment items (digital music, MP3/MP4 player, sound bar, digital camera, and headphones) or cleaning accessories (carpet shampooer, microfiber blind duster, all-purpose cleaner liquid, sweeper, and angle broom). Respondents could also choose “none.” A pretest was conducted to confirm that digital entertainment items and cleaning accessories, although rated similarly in attractiveness, differed on hedonicity (please see the web appendix for details). Everything remained the same in the other rebate condition, except that respondents imagined receiving a rebate from their purchase of a vacuum cleaner. Please see the appendix for further details on the stimuli. Data was collected in two waves. Initially, 96 respondents were recruited through Amazon Mechanical Turk (MTurk) in exchange for monetary payments (mean age = 35.48, 49% females). One hundred ten respondents (mean age = 35.45, 64% females) were recruited in the second wave of data collection for replication purposes. Participants in wave 1 were not allowed to participate in wave 2. The two waves returned the same outcomes. Both the datasets were combined into one dataset for analysis. Two respondents were excluded from the analysis because their responses were incomplete. I controlled for the two waves of data collection in my analysis. Results and Discussion Manipulation Check Monga and John (2007) show that when a particular aspect of self is primed (individualism/collectivism), the style of thinking (analytic/holistic) associated with it also activates. To ensure such activation of thinking styles by the pronoun-circling task, I asked respondents to complete an Embedded Figures Task following the pronoun-circling task (N = 45). In line with my expectation, respondents who received the analytic version of the pronoun-circling task found more embedded figures than those who received the holistic version (Manalytic = 2.65; Mholistic = 1.86; F(1, 43) = 4.31, p < .05, d = .63). In a separate test, 80 respondents rated the similarity of hedonic items (digital entertainment items such as digital music, MP3/MP4 player, sound bar, digital camera, and headphones) and utilitarian items (cleaning accessories such as carpet shampooer, microfiber blind duster, all-purpose cleaner liquid, sweeper, and angle broom) with a vacuum cleaner (a seemingly utilitarian product) (1= very similar, 9= very dissimilar). As expected, analytic thinkers showed a narrowly defined category structure by rating the digital entertainment items (vs. cleaning accessories) more dissimilar (vs. similar) to cleaning accessories such as a vacuum cleaner (Mdigital entertainment = 6.76; significantly above the midpoint 5, p <.01; Mcleaning accessories = 4.01; significantly below the midpoint 5, p = .013). On the other hand, holistic thinkers showed a broad categorization tendency (Mdigital entertainment = 5.31; nonsignificant difference from the midpoint 5, p = .58; Mcleaning accessories = 5.10; nonsignificant difference from the midpoint 5, p = .79). Mental Labeling Effect A mental labeling effect emerged when respondents were primed with analytic thinking rather than holistic thinking, providing support for hypothesis 1. A two-way ANOVA revealed a significant interaction between thinking style and rebate conditions (F(1, 199) = 9.75; p < .01, d = .44). The interaction effect showed that analytic thinkers’ choice share of digital entertainment (hedonic) items was significantly enhanced (62% vs. 32%) when they imagined spending rebate money obtained from their earlier purchase of a Blu-ray player (a hedonic product) relative to when they imagined spending the same rebate obtained from a vacuum cleaner (a utilitarian product) (F(1, 199) = 18.56; p < .001, d = .61). Holistic thinkers showed a similar preference (55% vs. 56%) in their choice share of digital entertainment items across both the rebate conditions (F(1, 199) = .004; p = .948, d = .009) (figure 1). There was a main effect for thinking style in that holistic thinkers showed a stronger preference for the hedonic items (digital entertainment) relative to analytic thinkers (55% vs. 46%; F(1, 199) = 2.96, p = .087, d = .24). A significant main effect was observed for product type (F(1, 199) = 9.18, p = .003, d = .43) in that the choice share of digital entertainment items was higher in the Blu-ray player condition than the vacuum cleaner condition (58% vs. 45%). No effect was observed for waves of data collection (F(1, 199) = .203, p = .653, d = .06). These findings provide preliminary support for my prediction that the mental labeling effect is prevalent in presence of analytic-thinking styles and weakened by holistic thinking. FIGURE 1 View largeDownload slide STUDY 1: RELATIVE TO HOLISTIC THINKERS, ANALYTIC THINKERS SHOWED A GREATER PREDILECTION FOR SIMILAR CATEGORY PURCHASES WITH THEIR REBATE MONEY. FIGURE 1 View largeDownload slide STUDY 1: RELATIVE TO HOLISTIC THINKERS, ANALYTIC THINKERS SHOWED A GREATER PREDILECTION FOR SIMILAR CATEGORY PURCHASES WITH THEIR REBATE MONEY. Product Type A product type difference emerged in that the divergence in the mental labeling effect across analytic and holistic groups was more pronounced when participants were contemplating how to spend the rebate obtained from a utilitarian source (vacuum cleaner) rather than from a hedonic source (Blu-ray player). In the vacuum cleaner condition, choice share of digital entertainment items was significantly lower among the analytic group (32%) than the holistic group (56%) (F(1, 199) = 11.74; p = .001, d = .49). In the Blu-ray player condition, choice share of digital entertainment items was higher among the analytic group (62%) than the holistic group (55%), but the difference was not significant (F(1, 199) = .979; p> .90, d = .14). I conducted an additional analysis to see how the choice share in each of the four conditions differed from 50%. Results show that analytic thinkers’ choice share of digital entertainment items was significantly below 50% in the vacuum cleaner condition (t = –4.27, p < .001). Their choice share of digital entertainment items was significantly above 50% (t = 2.58, p = .013) in the Blu-ray player condition. However, a stronger effect was observed in the vacuum cleaner (utilitarian) condition (effects size r = .51) than in the Blu-ray player (hedonic) condition (effects size r = .35). For holistic thinkers this difference was nonsignificant in both the vacuum cleaner and Blu-ray player conditions (vacuum cleaner: t = 1.08, p = .287; Blu-ray player: t = 1.07, p = .288). These results supported hypothesis 3 in showing that utilitarian consumption instances provide greater scope for rule-based thinking than hedonic consumption instances, which contributes to a stronger divergence in the mental labeling effect across the analytic and holistic groups relative to hedonic consumption instances. These findings also suggest that it is unlikely that a fluency- or fit-based account will explain the moderation effect by product type. If fluency had driven this effect, holistic thinkers would have exhibited enhanced preference for hedonic items while spending hedonic (vs. utilitarian) rebate money. This study revealed no such preference among holistic thinkers. Rather, it showed that holistic thinkers exhibited similar preference for hedonic items across the rebate conditions, irrespective of whether they were spending rebate money from hedonic or utilitarian items. Therefore, although it may sometimes be plausible that in the absence of strict category structure holistic thinkers would prefer more affect-rich options, their reliance on fit or fluency in the case of my current research is unlikely. Replication Findings from study 1 were also replicated in two separate studies. The first study was a pen-and-paper study conducted among undergraduate students at Southern Connecticut State University. The second study was conducted among MTurk workers. These studies utilized a similar design to that of study 1, but the instrument for priming thinking style (replication study 1) and the product categories that were contrasted were different (replication studies 1 and 2). Details pertaining to both the studies are presented in the web appendix. In my next study, I attempted to replicate the effect observed in study 1, utilizing an experimental paradigm that is likely to alleviate any remaining concern related to the influence of product-category-specific confounds on my results. I kept the products the same across the two product conditions, but manipulated consumption goals (utilitarian vs. hedonic). My expectation was that while analytic thinkers would spend rebates from utilitarian (hedonic) consumption on utilitarian (hedonic) items, holistic thinkers would be equally likely to spend such rebates on hedonic and utilitarian items. STUDY 2 Design and Procedure Two hundred eighty-three respondents were recruited through MTurk (41% female: mean age = 35.56). After completing the thinking style prime (pronoun-circling task), the respondents were provided with the definition of both hedonic and utilitarian products, and were then asked to write the name of a hedonic and a utilitarian product that had a retail value of $20. The order in which the respondents wrote a hedonic and a utilitarian product was counterbalanced. Some examples of utilitarian products that respondents listed included: blender, shaving razor, floor sweeper, toaster, and microwave. Some examples of hedonic products that respondents listed included: video games, movie tickets, Blu-ray player, wine, and headphones. Next, the respondents imagined purchasing a spa massage service (either as a reward for hard work or as a remedy for back pain). This manipulation was adapted from Botti and McGill (2011, study 2). Following the scenario, respondents were asked how they would have liked to use the rebate money and were given the choice between the hedonic and utilitarian options that they had generated in the previous screen (the text was generated from the earlier screen where respondents listed the names of hedonic/utilitarian items). Specifically, respondents indicated their preference on a seven-point scale where 1= will definitely choose “the utilitarian option” (generated from the previous page where they listed this option) and 7 = will definitely choose “the hedonic option” (generated from the previous page where they listed this option). Thus the choice options were generated by the respondents themselves. Therefore, this study utilized a 2 (thinking style: analytic vs. holistic) × 2 (rebate from: spa massage service when the goal of the massage was hedonic vs. spa massage service when the goal of the massage was utilitarian) design. Results and Discussion No respondent was excluded from analysis. I submitted the dependent variable (the intention to choose the hedonic option) and the independent variables (thinking style, rebate conditions, and their interaction) to a two-way ANOVA. The analysis revealed no main effect either for thinking style (F(1, 279) = .354, p = .552, d = .07) or for rebate conditions (F(1, 279) = .543, p = .502, d = .08). However, in accordance with my expectation, the analysis revealed a significant interaction effect of thinking style and rebate conditions (F(1, 279) = 4.13, p = .043; d = .24). The interaction effect indicated that respondents who were primed with an analytic-thinking style indicated a greater intention to choose the hedonic product in the hedonic rebate condition (M = 4.14, SD = 2.07) than in the utilitarian rebate condition (M = 3.46, SD = 1.97; F(1, 279) = 3.65, p = .057, d = .23). Conversely, respondents who were primed with a holistic-thinking style indicated similar intentions in choosing the hedonic option in the utilitarian rebate condition (M = 4.12, SD = 2.27) to that in the hedonic rebate condition (M = 3.78, SD = 2.11; F (1, 279) = .93, p = .33, d = .11) (figure 2). These results support hypothesis 1. Using a more conservative experimental design, these results exhibit the robustness of the effect that: analytic thinkers demonstrate the mental labeling effect, while holistic thinkers discard it. FIGURE 2 View largeDownload slide STUDY 2: ANALYTIC THINKERS’ INTENTION TO CHOOSE THE HEDONIC OPTION OVER THE UTILITARIAN OPTION IS GREATER IN THE HEDONIC REBATE CONDITION THAN IN THE UTILITARIAN REBATE CONDITION FIGURE 2 View largeDownload slide STUDY 2: ANALYTIC THINKERS’ INTENTION TO CHOOSE THE HEDONIC OPTION OVER THE UTILITARIAN OPTION IS GREATER IN THE HEDONIC REBATE CONDITION THAN IN THE UTILITARIAN REBATE CONDITION A marginal product type difference was observed in this study as well. The effect was more pronounced for rebates from utilitarian consumption (F(1, 279) = 3.51, p = .062, d = .22) than those from hedonic consumption (F(1, 279) = 1.01, p > .31, d = .12). Further probing into the moderation effect of product type showed that in the utilitarian rebate condition, analytic thinkers’ intention to choose the hedonic option was significantly below the midpoint (t = –2.29, p = .025), whereas their intention to choose the hedonic option was nonsignificantly above the midpoint (t = .58, p = .57) in the hedonic rebate condition. For holistic thinkers, intention to choose the hedonic option was indifferent from the midpoint in both the hedonic and utilitarian rebate conditions (utilitarian rebate: t = –.85, p = .395; hedonic rebate: t = .47, p = .64). These results support hypothesis 3. Therefore, similar to study 1, this study exhibits a stronger divergence in mental labeling effect in utilitarian (vs. hedonic) consumption instances. My next study replicates the divergence in mental labeling effect across analytic- and holistic-thinking groups by contrasting expenses preferred for two different payment methods (gift card or cash). Prior research has established that consumers encode gift cards into relatively more frivolous mental accounts than cash. Therefore, when adhering to mental accounting norms, consumers use gift cards (vs. cash) for buying frivolous (vs. functional) items (Helion and Gilovich 2014). I use this experimental paradigm in my next study and show that this mental accounting phenomenon weakens with an increase in people’s degree of holism. STUDY 3 Design and Procedure For this study I recruited 116 respondents from MTurk (50% females; mean age = 36.71). Data was collected in two separate batches of 76 and 40 respondents. Participants in batch 1 were not allowed to participate in batch 2. Both the batches returned similar outcomes and analysis was conducted on the combined dataset. As in Helion and Gilovich (2014, study 1A), respondents were asked to imagine that they were going to a bookstore to purchase two books: a novel from a favorite author and a reference book on how to do taxes at home. They were informed that both items cost the same amount of money and that they were planning to use a gift card for one book and cash for the other. After reading the scenario, respondents indicated which payment method they wanted to use for the novel (the hedonic item) and which one they wanted to use for the tax book (the utilitarian item) (1= will certainly use cash and 9 = will certainly use gift card). Respondents’ higher intention to use the gift card (vs. cash) to pay for the novel (vs. tax book) is demonstrative of a stronger mental labeling effect, which is expected to prevail to a lesser extent among individuals with a higher degree of holistic thinking (please see the web appendix for further details on the stimuli). Respondents then completed Choi et al.’s (2003) 10-item measure of holistic tendency. A higher score on the scale indicates greater holism (Cronbach’s alpha = .764). Results and Discussion One respondent was excluded from the analysis due to the response being incomplete. I created a mental labeling index by summating the items measuring the intention to use gift card/cash to purchase the novel or to purchase the tax book (reverse-coded) (r = .79). Higher values on this index measured higher propensity of showing the mental labeling effect. I performed a regression analysis where the dependent variable was the mental labeling index and the independent variable was the degree of holism. As expected, lower degrees of holism were associated with an enhanced mental labeling effect (b = –.574, t = –2.44, p = .016), supporting hypothesis 1. There was no effect of waves of data collection (b = –.873, t = –1.608, p = .111). I also performed regression on each of the two items comprising the mental labeling index. The analysis revealed that the mental labeling effect was more pronounced for the utilitarian consumption (b = –.702, t = –2.87, p = .005) than for the hedonic consumption (b = –.445, t = –1.759, p = .081), supporting hypothesis 3. There was no effect for waves of data collection for either of the regressions (utilitarian consumption: b = –.858, t = –1.516, p = .132; hedonic consumption: b = –.889, t = –1.518, p = .132). Having amassed substantial evidence for the existence of my proposed effect across a variety of decision contexts, my next study attempts to offer a cleaner test of the underlying psychological process. In my theorization I had argued that due to the connected nature of their thinking, holistic thinkers possess a flexible cognitive system, whereas analytic thinkers’ affinity for rules and logic infuses inflexibility in their cognitive systems. Due to such inflexibility in mental accounting, analytic thinkers spend their monetary resources on purchases that carry similar labels to the mental account in which the monetary resource is allocated. On the contrary, holistic thinkers’ flexible mental accounting system enables them to override mental labeling norms and spend their resources on dissimilar category purchases. My next study shows that when the categorization scheme for two categories of products (e.g., cooking accessories and laptop accessories) is altered to be more inclusive (as if items from both the categories of products belonged to a single category), spending rebates from laptop accessories on cooking accessories is not perceived to be a violation of the mental labeling norm, and analytic thinkers prefer product items from both of the categories. That is, when analytic thinkers are asked to focus on similarities between product categories, category labels for both categories of products will be assimilated within the same mental account where the rebate money has already been allocated. On the other hand, when a categorization scheme is more exclusive, spending savings from the purchase of laptop accessories on cooking accessories is perceived to be a violation of the mental labeling norm, and analytic thinkers’ preference remains confined within the laptop accessories category. Due to their flexible cognitive systems, holistic thinkers possess a broad mental accounting system, so for them, spending rebates obtained from one category on different category purchases is not deemed a violation of mental accounting norms. These results provide confirmatory evidence that it is the inflexible, norm-following nature of cognitive style that is responsible for analytic thinkers’ demonstration of the mental labeling effect. Holistic thinkers’ mental accounting is broadly defined, which permits cross-category expenditure of rebate promotions. STUDY 4 Design and Procedure One hundred two undergraduate students from Southern Connecticut State University participated in this study in exchange for course credits (mean age= 20.75, 45% females). This study utilized a 2 (thinking style: analytic vs. holistic) × 2 (categorization flexibility: similarities vs. differences) design. Respondents first completed an Embedded Figures Task (EFT), which primed them into either analytic or holistic thinking. The EFT was similar to the one utilized in prior research in this domain (Monga and John 2007, 2008). Respondents in the analytic-thinking condition were asked to find objects embedded in a scene, whereas those in the holistic-thinking condition were asked to write about what they saw in the scene, considering the background of the picture. Prior research shows that the task of identifying images embedded in a figure stimulates an analytic-thinking style. On the other hand, describing the same figure considering background images stimulates a context-dependent holistic style of thinking (Nisbett et al. 2001). Respondents were then randomly assigned to either a similarity condition or a differences condition. In the similarity condition, respondents learned that they just obtained a rebate from their earlier purchase of a Chromebook. They learned that they could spend this rebate money on items either from the kitchen accessories category (category A) or the computer accessories category (category B). Next, they were asked to write a few sentences about the similarities between the two product categories. This design was adapted from Murray et al. (1990, study 1). After responding to this task, participants indicated which items they wanted to buy with their rebate money. In the differences condition, everything remained the same except that respondents were asked to write a few sentences about the differences between the two product categories. In both the conditions, products from category A were presented above products from category B. Since this was a pen-and-paper survey, the order of presentation of product categories was not randomized. Please see the web appendix for the exact stimuli. After indicating their choice, respondents attended to several items from the “locus of attention” dimension of Choi, Koo, and Choi’s (2007) Analysis-Holism Scale (Cronbach’s alpha= .692). In addition, respondents indicated their degree of interest in the priming task (1 = not interesting at all, 9 = extremely interesting), effort exerted in the task (1 = not so much, 9 = a lot), and mood (1= sad, 9 = happy). It is likely that respondents will find the task of identifying hidden objects in a picture (vs. describing the scene considering its background) to be more interesting and effortful. Therefore, it is important to examine the possible influence of these factors on my findings. Equally important is to rule out possible confounds created by mood since people’s mood influences cognitive flexibility and categorization (Murray et al. 1990). Results and Discussion Manipulation Check The priming instrument was effective in priming analytic versus holistic thinking. Respondents thought more holistically in the holistic-thinking condition (M = 5.42) than in the analytic-thinking condition (M = 4.91) (F(1, 100) = 5.40; p = .022, d = .46). In addition, their degree of interest in the task and their degree of effort were lower in the holistic-thinking condition relative to the analytic-thinking condition (interest: Manalytic = 5.58, Mholistic = 4.06, F(1, 100) = 11.015, p = .001, d = .66; effort: Manalytic = 6.56, Mholistic = 4.28, F(1, 100) = 28.07, p < .001, d = 1.05). However, the priming task did not impact respondents’ mood (Manalytic = 5.90, Mholistic = 5.96, F(1, 100) = .041, p = .841, d = .04). Categorization Flexibility Since this study is a test of the underlying psychological process of the mental accounting phenomenon observed in earlier studies, I believe that it is imperative to focus first on respondents who chose at least one option from the list of options provided to them. It is certain that this group of respondents engaged in some sort of mental accounting. On the other hand, respondents who chose none of the items presented may or may not have engaged in mental accounting, since it is difficult to determine which specific factors contributed to their rejection decision. Therefore, I conducted my first analysis excluding 19 respondents who chose none of the product items. I applied a two-way ANOVA where the dependent variable was respondents’ choice share of items listed in the kitchen accessories category and the independent variables were thinking style and the categorization flexibility conditions. As expected, analytic thinkers’ choice share of the kitchen accessories was different across the similarities and differences conditions. Their choice share of the kitchen accessories was significantly higher in the similarities (61%) condition relative to the differences condition (28%) (F(1, 79) = 12.79, p = .001, d = .80). No such difference was observed for holistic thinkers (44% vs. 45%) (F(1, 79) = .013, p = .911, d = .03). The two-way interaction between thinking style and categorization flexibility conditions was significant (F(1, 79) = 6.87, p = .010, d= .59). A significant main effect of categorization flexibility was observed, in that choice share of kitchen accessories was significantly higher in the similarities condition (52%) relative to the differences condition (36%), indicating stronger prevalence of mental labeling in the differences condition (F(1, 79) = 6.07, p = .016, d = .55). Since this analysis was conducted excluding respondents who did not make a choice, the same analysis with the choice share of computer accessories mirrored these findings. These results provide support for hypothesis 2. An additional analysis including respondents who chose none revealed a similar pattern of results. For analytic thinkers, choice share of the kitchen accessories was significantly higher in the similarities (53%) condition relative to the differences condition (23%) (F(1, 98) = 10.77, p = .001, d = .66). Holistic thinkers showed a similar preference for kitchen accessories across the categorization flexibility conditions (31% vs. 38%) (F(1, 98) = .583, p = .447, d = .13). The two-way interaction between thinking style and categorization flexibility was significant (F(1, 98) = 8.47, p = .004, d = .59). Moreover, similar results were obtained after I controlled for respondents’ interest in the priming task, their degree of effort in the task, and mood (thinking style × categorization flexibility: (F(1, 98) = 9.29, p = .003, d= .62). That is, although respondents’ effort level and interest varied across the analytic and holistic prime conditions, these factors did not have any influence on my findings. My next study reveals the psychological process underlying the moderation effect by product type as observed in studies 1–3. In this study, I externally infused either a strong norm-following tendency or a strong norm-avoidance tendency through a manipulation of cognitive deliberation. Then, I manipulated respondents’ focus on benefits obtained from the consumption of a hedonic item (Blu-ray player) on either functional benefits or emotional benefits. My earlier studies show that analytic thinkers demonstrate a weaker mental labeling effect in hedonic (vs. utilitarian) consumption instances. The next study shows that even for hedonic products, when the focus is shifted to functional benefits, analytic thinkers demonstrate a stronger mental labeling effect than when the focus remains on emotional benefits. This effect takes place only when strong rule-following tendencies are externally induced by a previously activated deliberate processing mode. When a quick feeling-based processing mode is activated, which attenuates norm adherence, the above effect disappears. In this manner, this study exhibits that it is the scope for cognitive deliberation and rule following, as generally induced by utilitarian (vs. hedonic) consumption instances, that leads to a stronger divergence in the mental labeling effect across the analytic- and holistic-thinking groups. No such interaction between rebate conditions (functional vs. emotional) and thinking style emerges when rule following is situationally impaired by inducement of quick feelings-based thinking. STUDY 5 Design and Procedure This study was conducted among 297 respondents. Data was collected in three batches. The first batch comprised 117 undergraduate students from Southern Connecticut State University, who participated in a pen-and-paper study in exchange for course credits (mean age = 21.27; 40% females); the second batch comprised 80 college students who were recruited through an online panel in exchange for monetary payments (mean age = 27.06; 63% females); and the third batch comprised 100 respondents recruited from a national pool of respondents in exchange for monetary payments (mean age = 36.64; 58% females). All three batches returned similar outcomes, and I conducted analysis on the combined dataset of all three batches, controlling for waves of data collection. Two incomplete responses were excluded from the analysis. The study featured a 2 (processing mode: cognitive deliberation vs. gut feelings) × 2 (focus on: functional benefits vs. emotional benefits) × 2 (thinking style: analytic vs. holistic) design, where processing mode and rebate conditions were manipulated between-subjects, and thinking style was measured within-subjects. Respondents first attended to the processing mode manipulation. The instrument for this manipulation was adapted from Nordgren and Dijksterhuis (2009) (please see the web appendix). After attending to the priming instrument, respondents were randomly assigned to either the “focus on functional benefits” or the “focus on emotional benefits” condition. In the rebate scenarios, respondents learned that they bought a Blu-ray player on a rebate offer. They imagined they had bought the item two months ago and had just received the rebate money. In the “focus on functional benefits” condition, respondents were shown the picture of a Blu-ray player and were asked to write about the functional benefits of the player. Respondents then imagined buying the Blu-ray player on a rebate offer two months ago. They were asked to contemplate which category of products they wanted to spend their rebate money on: digital entertainment or cooking accessories. Please see the web appendix for further details on the stimuli. Everything remained the same in the “focus on emotional benefits” condition except that instead of writing about functional benefits of a Blu-ray player, respondents wrote about its emotional benefits. In this manner, focus on benefits from the same product (a Blu-ray player) was shifted from emotional to functional across the two rebate conditions. After completing the choice task, respondents attended to the 10-item measure of holistic tendency (AHL) (α = .75) (Choi et al. 2003). Results and Discussion Manipulation Check A manipulation check for the processing mode manipulation (cognitive deliberation vs. gut feelings) was conducted among 56 respondents. After attending to the priming task, respondents completed a scale adapted from Novak and Hoffman (2009) that measures people’s situation-specific experiential and rational cognition. I calculated a difference score by subtracting respondents’ score on the feelings dimension of the scale (α= .93) from their score on the cognition dimension (α= .96), such that a higher score on the index indicated greater exercise of cognition relative to feeling. As expected, respondents exercised greater cognition in the cognition condition than in the feeling condition (Mcognition = 2.16, Mfeeling = .26; F(1, 54) = 10.11, p = .002, d = .86). Moreover, respondents’ score on the thoughtfulness dimension was higher in the cognition condition than in the feeling condition (Mcognition = 7.17, Mfeeling = 6.16; F(1, 54) = 6.85, p =.011, d = .71). Their score on the feeling dimension was higher in the feeling condition than in the cognition condition (Mcognition = 5.01, Mfeeling = 5.91; F(1, 54) = 3.37, p =.072, d = .49). These results establish validity of the priming instrument. Mental Labeling All independent variables were mean-centered prior to analysis. There was no evidence of multicollinearity upon mean centering (VIF values ranged from 1.005 to 1.047, tolerance values ranged from .955 to .995). Choice share of digital entertainment items was the dependent variable in this analysis. The three-way interaction between processing mode (cognition vs. affect), rebate conditions (focus on functional benefits vs. focus on emotional benefits), and thinking style was significant (b = –.25, t = –2.49, p =.013). A significant two-way interaction effect emerged between rebate conditions (focus on functional benefits vs. focus on emotional benefits) and thinking style (b = .11, t = 2.25, p =.025). This interaction effect revealed that among analytic thinkers the choice share of digital entertainment items was higher in “focus on functional benefits” condition than in the “focus on emotional benefits” condition. On the contrary, among holistic thinkers the choice share of digital entertainment items was higher in “focus on emotional benefits” condition than in the “focus on functional benefits” condition. The interaction effect between processing mode (cognitive deliberation vs. gut feelings) and thinking style was nonsignificant (b = .005, t = .100, p = .920). Similarly, the interaction effect between processing mode and rebate conditions was nonsignificant (b = .001, t = .017, p = .987). The main effects of thinking style (b = .016, t = .669, p = .504), rebate conditions (b = .015, t = .376, p = .707), and processing mode (b = .017, t = .401, p = .689) were nonsignificant. There was no effect of waves of data collection (b = –.028, t = –1.100, p = .272). I conducted a further analysis of the three-way interaction to examine the support for hypothesis 3. In breaking down the three-way interaction effect, I found a significant two-way interaction between thinking style and rebate conditions (focus on functional benefits vs. focus on emotional benefits) when a cognitive processing mode was situationally activated (b = .25, t = 3.43, p < .001). The interaction between thinking style and rebate condition was nonsignificant when an affective processing mode was situationally activated (b = .0073, t = .11, p = .91). I conducted two separate floodlight analyses (Spiller et al. 2013) within the cognition and the affective conditions, which provided further clarity into the two-way interaction effects. The floodlight analysis is appropriate for my analysis purposes since the two-way interactions within the respective cognition and affective conditions involves a dichotomous variable (rebate conditions) and a continuous variable (AHL). The floodlight analysis applies the Johnson-Neyman technique, which provides computation of the region of significance. That is, the analysis indicates at what levels of the continuous moderator variable (AHL) the mental labeling effect (as in the case of the current investigation) is significantly positive, nonsignificant, and significantly negative. According to my expectation, when cognitive deliberation is induced, analytic thinkers’ choice share of digital entertainment items (products from a category similar to a Blu-ray player) was more enhanced in the “focus on functional benefits” condition than in the “focus on emotional benefits” condition. This is indicated by a significant effect in the expected direction at lower values of mean-centered AHL (–3.772 to –.7057). Interestingly, a reversal of the effect was observed at high values of AHL (holistic thinkers). For mean-centered AHL values ranging from .5138 to 2.23, choice share of digital entertainment items was enhanced in the “focus on emotional benefits” condition relative to that in the “focus on functional benefits” condition (please see the web appendix for the floodlight tables). It is possible that the external inducement of cognitive deliberation strengthens respective cognitive habits. For analytic thinkers, it further reduces flexibility in categorization; for holistic thinkers, it enhances cognitive flexibility. Preference for hedonic items increases among cognitively flexible individuals as disinhibition to such consumption is enhanced (Khare and Chowdhury 2015). Drawing respondents’ attention explicitly to the hedonic benefits of the source product (Blu-ray player) provided such enhancement in disinhibition, and cognitively flexible holistic thinkers demonstrated a stronger preference for affect-rich digital entertainment items in this condition relative to the condition where their focus was explicitly drawn to functional benefits. SINGLE-PAPER META-ANALYSIS Meta-analysis is effective in synthesizing knowledge within a specific domain of interest (Hunter and Schmidt 1990). Recently, researchers have started to acknowledge the value of conducting small-scale meta-analysis, including studies reported in a single research paper. Although some researchers have questioned the value of small-scale meta-analysis in advancing cumulative knowledge (Sakaluk 2016), others have recommended its use, stating that such analysis provides critical overview of findings from studies of a research paper (McShane and Böckenholt 2017). Presented below are findings from a small-scale meta-analysis that I conducted, including studies 1–3 in this article and replication studies reported in the web appendix (five studies in total). These studies establish the divergence in mental labeling across the analytic- and holistic-thinking groups and provide evidence of moderation by product type. While McShane and Böckenholt (2017) present an effective tool for single-paper meta-analysis, given that I varied the dependent variable measure across studies, and that I have both manipulated and measured thinking style across studies, the meta-regression approach is better suited in my case (Lipsey and Wilson 2001; Wilson 2005). For the first wave of analysis, with the interaction effects, I applied MeanES macro developed by D. B. Wilson (Wilson 2005). Prior to my analysis, I converted each test statistic (interaction effects for studies 1 and 2 and two replication studies, and the main effect on mental labeling for study 3) to a correlation coefficient (Hunter and Schmidt 2002; Lipsey and Wilson 2001), which was then converted to a Fisher’s z-value (Lipsey and Wilson 2001). That is, the analysis was conducted on Fisher’s z-transformed effects sizes. Effects sizes were weighted by sample size (inverse variance), as weighted methods are recommended for meta-analysis estimates (Hedges and Olkin 1985; Steel and Kammeyer-Mueller 2002). The output returned by the MeanES procedure includes the mean effects size, the homogeneity test, confidence intervals, and the z-test. Both the fixed- and random-effect models showed prevalence of a significant effects size (fixed effect: mean effects size = .17, p < .001; random effect: mean effects size = .17, p < .001), ensuring divergence in metal labeling across the analytic and holistic groups as observed in my studies. The homogeneity statistic was not statistically significant (Q(4) = 2.15, p > .70), indicating that the set of studies were homogeneous. I conducted a second meta-analysis where the effects sizes were obtained from the product type difference (i.e., a stronger mental labeling difference across the thinking groups in the utilitarian vs. hedonic conditions) across studies. I applied an ANOVA analog to meta-regression (method of moments random effects) using the MetaF macro developed by D. B. Wilson (Lipsey and Wilson 2001; Wilson 2005). For each study, the effects size for the analytic/holistic difference in the utilitarian condition and the hedonic condition were coded. That is, there were two entries for each of the studies. In this analysis, product conditions (hedonic vs. utilitarian) were coded as the moderator variable. The analysis revealed that the effects size for both the utilitarian and hedonic conditions was significant (utilitarian condition: mean effects size = .18, p < .001; hedonic condition: mean effects size = .06, p = .031). Importantly, the effects size for the utilitarian condition was stronger than that for the hedonic condition (mean effects size = .18 vs. mean effects size = .06). The between-group homogeneity statistic shows that the difference between the utilitarian and hedonic conditions was statistically significant, reflecting the product type moderation as observed across the studies (Q(1) = 6.49, p = .011). Please see the web appendix for the forest plot and another small-scale analysis of study 1 and its replications using McShane and Böckenholt’s (2017) procedure. GENERAL DISCUSSION Prior research provides considerable evidence of how an analytic- versus holistic-thinking style influences people’s decision-making processes. Research shows that thinking style influences people's preferences for connected versus separate appeals (Wang and Chan 2001), spatial judgments (Krishna, Zhou, and Zhang 2008), brand extension evaluation (Monga and John 2007, 2010), reaction to negative publicity (Monga and John 2008), and price-quality judgments (Lalwani and Shavitt 2013). Complementing this growing body of literature, the current research shows that thinking style influences people's mental accounting systems. The mental labeling effect amplifies in a situational activation of analytic thinking, but attenuates in holistic-thinking contexts. I have shown this effect in a series of studies that utilized different decision contexts, various measures of thinking styles, and a diverse pool of respondents. My studies also demonstrate a moderating role of product type in exhibiting that the divergence in mental labeling effect across analytic- and holistic-thinking groups is stronger for utilitarian (vs. hedonic) consumption instances. These results carry significant theoretical and practical implications. Mental Accounting People’s booking, posting, and tracking of resources into mental accounts is a cognitive phenomenon. Therefore, the system should be differentially influenced when different types of cognitive structures are situationally activated. Despite such a possibility, prior research does not provide any direct empirical demonstration of the effect. Analytic and holistic thinking are two divergent cognitive habits that are shown to differentially affect a wide array of behaviors. My findings, on how the analytic and holistic nature of people’s cognition influences their spending behavior, advance our understanding of how different mental accounting systems can prevail based upon the nature of cognition being activated. Cross-Category Effects of Promotions and Cross-Market Discounts Promotions in one product category may induce demand in other categories (Leeflang and Parreno-Selva 2012). With in-depth understanding of cross-category effects of promotions, retailers may better position their private label brands and coordinate their marketing efforts across numerous product categories (Fader and Lodish 1990; Leeflang and Parreno-Selva 2012; Walters 1991; Wedel and Zhang 2004). Even though extant research, in general, finds smaller cross-category effects of marketing promotions relative to own-category effects (Leeflang et al. 2008; Manchanda, Ansari, and Gupta 1999; Song and Chintagunta 2006; Walters and MacKenzie 1988), my research finds that own-category effects may amplify among analytic-thinking individuals. Since the prevalence of analytic thinking is stronger among certain ethnic groups than others (Lalwani and Shavitt 2013; Lechuga et al. 2011), retailers may expect divergence in cross-category effects of price promotions across various ethnic groups. Manufacturers selling products in multiple categories (e.g., Procter & Gamble) should consider the general nature of consumer segments before applying price promotions. Moreover, many grocery chains have been successfully implementing cross-market discounts (Goic, Jerath, and Srinivasan 2011). Under such discounting strategies, consumers can accumulate discounts from their grocery purchases for purchasing gasoline. My findings suggest that such programs will find greater favor among analytic thinkers than among holistic thinkers. My research also implies that price promotions may facilitate the consumption of products with positive categorical dependence (e.g., washers and dryers; Chintagunta and Haldar 1998) among analytic thinkers, but not among holistic thinkers. Analytic thinkers may also prefer investing gains from one investment into similar ventures, thereby ending up with less diversification within their portfolio. Moreover, in analytic-thinking countries and regions with a greater Caucasian population, freebies from a similar product category are likely to find greater favor among consumers than freebies from dissimilar product categories. Culture and Reasoning Style Culture-based, shared-knowledge structures play an imperative role in shaping people’s cognition (Nisbett and Norenzayan 2002; Schank and Abelson 1977). Since collectivistic cultures promote holistic thinking and individualist cultures promote analytic thinking (Nisbett et al. 2001), my research findings suggest that the mental labeling effect will be more prominent among individuals from individualistic cultures than from collectivistic cultures (e.g., Americans will demonstrate stronger mental labeling effects than Indians). Limitations and Future Research Limitations of my research open avenues for future research. Although study 5 reveals the psychological process underlying the moderation effect as predicted in hypothesis 3, this study does not effectively rule out or examine the possibility of a fluency-based explanation of the product type moderation within the analytic-thinking group. Since analytic thinkers adhere to rule-based thinking, and utilitarian consumption instances promote a cognitive rule-based thinking orientation, the fluency-based theorizing would predict that in this condition analytic thinkers would prefer utilitarian items over hedonic ones since these items may just feel like the right options to choose. Future research may provide deeper understanding into this phenomenon. Future research may also study whether the mental labeling phenomenon provides justification for choosing the label-consistent items, particularly when people look for justification in their choices. The hedonic/utilitarian literature demonstrates that both the limited availability of cognitive resources and the reduced need for justification promote pro-hedonic preference (Khan and Dhar 2010; Shiv and Fedorikhin 1999). However, it is not entirely clear whether people’s need to justify hedonic choices decreases with depletion of their cognitive resources. I believe there is scope for future research to provide a better understanding of how the various psychological processes leading to hedonic preference are interlinked. Several of my studies may have provided critical insights into how people’s mindsets may determine their expenditure of windfall money. However, it was not clear whether the respondents in my studies perceived the rebate money as entirely surprising income. Typically, windfall incomes carry an element of surprise due to their unexpected nature. Even if there was a surprise factor attached to the rebate income, the intensity of surprise is likely to be lower than an entirely unexpected bonus. Levav and McGraw (2009) show how individuals engage in emotional accounting with their windfall money. My findings suggest that when the nature of the windfall is such that the intensity of the surprise factor attached to it is low, then individuals who think analytically may engage in cognitive accounting (i.e., assigning category labels to rebates and spending them on similar-category purchases). Future research may vary the degree of unexpectedness of the windfall money and study how people’s nature of accounting shifts subject to variation in the element of surprise. Given the increasing number of donation platforms these days (e.g., GlobalGiving, GoFundMe), donors often encounter the decision task of choosing among a large number of charitable causes. My framework can be applied in studying if donors’ mindsets determine whether the label of donation money (e.g., vice vs. virtuous) influences their choice of the charitable cause. Moreover, since people construe temporal resources differently than monetary resources (Mogilner and Aaker 2009), future research could study my effect in the context of spending windfall time rather than windfall money. Finally, future research could extend my findings by studying whether thinking style influences consumer spending of savings obtained through marketing promotions on complementary versus substitute products, thereby influencing cross-price elasticities. DATA COLLECTION INFORMATION All data collection and analysis related to this project was performed by the sole author. Data was collected from fall 2014 to January 2018. Studies were conducted both via MTurk and among undergraduate students at Southern Connecticut State University. All respondents who participated in studies related to this project were located in the United States. This article was drafted and revised by the sole author. The author gratefully acknowledges the financial support from the School of Business Dean’s Discretionary Fund at Southern Connecticut State University. In addition, the author gratefully acknowledges the helpful input of the editor, associate editor, and reviewers Supplementary materials are included in the web appendix accompanying the online version of this article. APPENDIX STIMULI USED IN STUDY 1 (REBATE FROM MORE HEDONIC PRODUCT CONDITION) Imagine that you bought the above Blu-ray player two months ago. The price for the Blu-ray player was $150, but you bought it with a mail-in rebate offer: that is, you pay $150 now and get back a rebate of $100 two months later. Today you have received your rebate money of $100. Listed below are products that belong to two different categories, category A and category B. Items in category A include digital music, MP3/MP4 player, sound bar, digital camera, and headphones. Items in category B include carpet shampooer, microfiber blind duster, all-purpose cleaner liquid, sweeper, and angle broom. Which of the following item(s) will you buy with the $100 rebate money that you just received from your earlier purchase of the Blu-ray player? (You may choose multiple items from either of the categories.) Category A: □ Digital music □ MP3/MP4 player □ Sound bar □ Digital camera □ Headphones □ None Category B: □ Carpet shampooer □ Microfiber blind duster □ All-purpose cleaner liquid □ Sweeper □ Angle broom □ None Category A: □ Digital music □ MP3/MP4 player □ Sound bar □ Digital camera □ Headphones □ None Category B: □ Carpet shampooer □ Microfiber blind duster □ All-purpose cleaner liquid □ Sweeper □ Angle broom □ None Category A: □ Digital music □ MP3/MP4 player □ Sound bar □ Digital camera □ Headphones □ None Category B: □ Carpet shampooer □ Microfiber blind duster □ All-purpose cleaner liquid □ Sweeper □ Angle broom □ None Category A: □ Digital music □ MP3/MP4 player □ Sound bar □ Digital camera □ Headphones □ None Category B: □ Carpet shampooer □ Microfiber blind duster □ All-purpose cleaner liquid □ Sweeper □ Angle broom □ None **Order of the categories (category A, category B) was randomized. References Alba Joseph W. , Williams Elanor F. ( 2013 ), “Pleasure Principles: A Review of Research on Hedonic Consumption,” Journal of Consumer Psychology , 23 1 , 2 – 18 . Google Scholar CrossRef Search ADS Arkes Hal R. , Joyner Cynthia A. , Pezzo Mark V. , Nash Jane Gradwohl , Siegel-Jacobs Karen , Stone Eric ( 1994 ), “The Psychology of Windfall Gains,” Organizational Behavior and Human Decision Processes , 59 3 , 331 – 47 . Google Scholar CrossRef Search ADS Barberis Nicholas , Huang Ming ( 2001 ), “Mental Accounting, Loss Aversion, and Individual Stock Returns,” Journal of Finance , 56 4 , 1247 – 92 . Google Scholar CrossRef Search ADS Botti Simona , McGill Ann L. ( 2011 ), “The Locus of Choice: Personal Causality and Satisfaction with Hedonic and Utilitarian Decisions,” Journal of Consumer Research , 37 6 , 1065 – 78 . Google Scholar CrossRef Search ADS Chintagunta Pradeep K. , Haldar Sudeep ( 1998 ), “Investigating Purchase Timing Behavior in Two Related Product Categories,” Journal of Marketing Research , 35 1 , 43 – 53 . Google Scholar CrossRef Search ADS Choi Incheol , Choi Yimoon ( 2002 ), “Culture and Self-Concept Flexibility,” Personality and Social Psychology Bulletin , 28 11 , 1508 – 17 . Google Scholar CrossRef Search ADS Choi Incheol , Dalal Reeshad , Kim-Prieto Chu , Park Hyekyung ( 2003 ), “Culture and Judgement of Causal Relevance,” Journal of Personality and Social Psychology , 84 1 , 46 – 59 . Google Scholar CrossRef Search ADS PubMed Choi Incheol , Koo Minkyung , Choi Jong A. ( 2007 ), “Individual Differences in Analytic versus Holistic Thinking,” Personality and Social Psychology Bulletin , 33 5 , 691 – 705 . Google Scholar CrossRef Search ADS PubMed Choi Incheol , Nisbett Richard E. , Norenzayan Ara ( 1999 ), “Causal Attribution across Cultures: Variation and Universality,” Psychological Bulletin , 125 1 , 47 – 63 . Google Scholar CrossRef Search ADS English Tammy , Chen Serena ( 2007 ), “Culture and Self-Concept Stability: Consistency across and within Context among Asian American and European Americans,” Journal of Personality and Social Psychology , 93 3 , 478 – 90 . Google Scholar CrossRef Search ADS PubMed Epley Nicholas , Mak Dennis , Idson Lorraine Chen ( 2006 ), “Bonus or Rebate? The Impact of Income Framing on Spending and Saving,” Journal of Behavioral Decision Making , 19 3 , 213 – 27 . Google Scholar CrossRef Search ADS Escalas Edson , Bettman James R. ( 2005 ), “Self-Construal, Reference Groups, Brand Meaning,” Journal of Consumer Research , 32 3 , 378 – 89 . Google Scholar CrossRef Search ADS Fader Peter S. , Lodish Leonard M. ( 1990 ), “A Cross-Category Analysis of Category Structure and Promotional Activity for Grocery Products,” Journal of Marketing , 54 4 , 52 – 65 . Google Scholar CrossRef Search ADS Gardner Wendi L. , Gabriel Shira , Lee Angela Y. ( 1999 ), “‘I’ Value Freedom, but ‘We’ Value Relationships: Self-Construal Priming Mirrors Cultural Differences in Judgment,” Psychological Science , 10 4 , 321 – 6 . Google Scholar CrossRef Search ADS Goic Marcel , Jerath Kinshuk , Srinivasan Kannan ( 2011 ), “Cross-Market Discounts,” Marketing Science , 30 1 , 134 – 48 . Google Scholar CrossRef Search ADS Havlena William J. , Holbrook Morris B. ( 1986 ), “The Varieties of Consumption Experience: Comparing Two Typologies of Emotion in Consumer Behavior,” Journal of Consumer Research , 13 3 , 394 – 404 . Google Scholar CrossRef Search ADS Heath Chip ( 1995 ), “Escalation and De-escalation of Commitment in Response to Sunk Costs: The Role of Budgeting in Mental Accounting,” Organizational Behavior and Human Decision Processes , 62 1 , 38 – 54 . Google Scholar CrossRef Search ADS Heath Chip , Soll Jack B. ( 1996 ), “Mental Budgeting and Consumer Decisions,” Journal of Consumer Research , 23 1 , 40 – 53 . Google Scholar CrossRef Search ADS Hedges Larry V. , Olkin Ingram ( 1985 ), Statistical Models for Meta-Analysis , New York : Academic Press . Helion Chelsea , Gilovich Thomas ( 2014 ), “Gift Cards and Mental Accounting: Green-Lighting Hedonic Spending,” Journal of Behavior Decision Making , 27 4 , 386 – 93 . Henderson Pamela W. , Peterson Robert R. ( 1992 ), “Mental Accounting and Categorization,” Organizational Behavior and Human Decision Processes , 51 1 , 92 – 117 . Google Scholar CrossRef Search ADS Hirschman Elizabeth C. , Holbrook Morris B. ( 1982 ), “Hedonic Consumption: Emerging Concepts, Methods and Propositions,” Journal of Marketing , 46 3 , 92 – 101 . Google Scholar CrossRef Search ADS Huang Ming-Shiunn ( 1981 ), “Category Width and Differentiation in Semantic Categories,” British Journal of Psychology , 72 3 , 339 – 52 . Google Scholar CrossRef Search ADS Hunter John E. , Schmidt Frank L. ( 1990 ), Methods of Meta-Analysis: Correcting Error and Bias in Research Findings , Newbury Park. CA : Sage . Hunter John E. , Schmidt Frank L. ( 2002 ), “Fixed Effects vs. Random Effects Meta-Analysis Models: Implications for Cumulative Research Knowledge,” International Journal of Selection and Assessment , 8 4 , 275 – 92 . Google Scholar CrossRef Search ADS Jain S. Pratap , Desai Kalpesh K. , Mao Huifang ( 2007 ), “The Influence of Chronic and Situational Self-Construal on Categorization,” Journal of Consumer Research , 34 1 , 66 – 76 . Google Scholar CrossRef Search ADS Ji Li-Jun , Peng Kaiping , Nisbett Richard E. ( 2000 ), “Culture, Control and Perception of Relationships in the Environment,” Journal of Personality and Social Psychology , 78 5 , 943 – 55 . Google Scholar CrossRef Search ADS PubMed Khan Uzma , Dhar Ravi ( 2010 ), “Price Framing Effects on Purchase of Hedonic and Utilitarian Bundles,” Journal of Marketing Research , 47 6 , 1090 – 9 . Google Scholar CrossRef Search ADS Khan Uzma , Dhar Ravi , Wertenbroch Klaus ( 2005 ), “A Behavioral Decision Theory Perspective on Hedonic and Utilitarian Choice,” in Inside Consumption: Frontiers of Research on Consumer Motives, Goals, and Desires , ed. Ratneshwar S. , Mick David G. , London : Routledge , 144 – 65 . Khare Adwait , Chowdhury Tilottama G. ( 2015 ), “Food Categorization Flexibility Increases the Preference for Indulgent Foods,” Journal of Consumer Psychology , 25 4 , 546 – 60 . Google Scholar CrossRef Search ADS Krishna Aradhna , Zhou Rongrong , Zhang Shi ( 2008 ), “The Effect of Self-Construal on Spatial Judgments,” Journal of Consumer Research , 35 2 , 337 – 48 . Google Scholar CrossRef Search ADS Kronrod Ann , Grinstein Amir , Wathieu Luc ( 2012 ), “Enjoy! Hedonic Consumption and Compliance with Assertive Messages,” Journal of Consumer Research , 39 1 , 51 – 61 . Google Scholar CrossRef Search ADS Lalwani Ashok K. , Shavitt Sharon ( 2013 ), “You Get What You Pay for? Self-Construal Influences Price-Quality Judgments,” Journal of Consumer Research , 40 2 , 255 – 67 . Google Scholar CrossRef Search ADS Lechuga Julia , Santos Beatriz M. , Garza-Caballero Azenett A. , Villarreal Ricardo ( 2011 ), “Holistic Reasoning on the Other Side of the World: Validation of the Analysis-Holism Scale in Mexicans,” Cultural Diversity and Ethnic Minority Psychology , 17 3 , 325 – 30 . Google Scholar CrossRef Search ADS PubMed Leclerc France , Schmitt Bernd H. , Dubé Laurette ( 1995 ), “Waiting Time and Decision Making: Is Time like Money?” Journal of Consumer Research , 22 1 , 110 – 9 . Google Scholar CrossRef Search ADS Leeflang Peter S. H. , Parreño-Selva Josefa ( 2012 ), “Cross-Category Demand Effects of Price Promotions,” Journal of the Academy of Marketing Science , 40 4 , 572 – 86 . Google Scholar CrossRef Search ADS PubMed Leeflang Peter S. H. , Parreño-Selva Josefa , Dijk Albert V. , Wittink Dick R. ( 2008 ), “Decomposing the Sales Promotion Bump Accounting for Cross-Category Effects,” International Journal of Research in Marketing , 25 3 , 201 – 14 . Google Scholar CrossRef Search ADS Levav Jonathon , Peter McGraw A. ( 2009 ), “Emotional Accounting: How Feelings about Money Influence Consumer Choice,” Journal of Marketing Research , 46 1 , 66 – 80 . Google Scholar CrossRef Search ADS Lipsey Mark W. , Wilson David B. ( 2001 ), Practical Meta-Analysis , Thousand Oaks, CA : Sage . Manchanda Puneet , Ansari Asim , Gupta Sunil ( 1999 ), “The ‘Shopping Basket’: A Model for Multicategory Purchase Incidence Decisions,” Marketing Science , 18 2 , 95 – 114 . Google Scholar CrossRef Search ADS Mano Haim , Oliver Richard L. ( 1993 ), “Assessing the Dimensionality and Structure of the Consumption Experience: Evaluation, Feeling, and Satisfaction,” Journal of Consumer Research , 20 3 , 451 – 66 . Google Scholar CrossRef Search ADS Markus Hazel , Kitayama Shinobu ( 1991 ), “Culture and the Self: Implications for Cognition, Emotion, and Motivation,” Psychological Review , 98 2 , 224 – 53 . Google Scholar CrossRef Search ADS Masuda Takahiko , Nisbett Richard E. ( 2001 ), “Attending Holistically versus Analytically: Comparing the Context Sensitivity of Japanese and Americans,” Journal of Personality and Social Psychology , 81 5 , 922 – 34 . Google Scholar CrossRef Search ADS PubMed McShane Blakeley B. , Böckenholt Ulf ( 2017 ), “Single Paper Meta-Analysis: Benefits for Study Summary, Theory Testing, and Replicability,” Journal of Consumer Research , 43 6 , 1048 – 63 . Milkman Katherine L. , Beshears John ( 2009 ), “Mental Accounting and Small Windfalls: Evidence from an Online Grocer,” Journal of Economic Behavior & Organization , 71 2 , 384 – 94 . Google Scholar CrossRef Search ADS Millar Murray G. , Tesser Abraham ( 1986 ), “Effects of Affective and Cognitive Focus on the Attitude-Behavior Relationship,” Journal of Personality and Social Psychology , 51 2 , 270 – 6 . Google Scholar CrossRef Search ADS Mogilner Cassie , Aaker Jennifer ( 2009 ), “‘The Time vs. Money Effect’: Shifting Product Attitudes and Decisions through Personal Connection,” Journal of Consumer Research , 36 2 , 277 – 91 . Google Scholar CrossRef Search ADS Monga Alokparna B. , John Deborah Roedder ( 2007 ), “Cultural Differences in Brand Extension Evaluation: The Influence of Analytic versus Holistic Thinking,” Journal of Consumer Research , 33 4 , 529 – 36 . Google Scholar CrossRef Search ADS Monga Alokparna B. , John Deborah Roedder ( 2008 ), “When Does Negative Brand Publicity Hurt? The Moderating Influence of Analytic versus Holistic Thinking,” Journal of Consumer Psychology , 18 4 , 320 – 32 . Google Scholar CrossRef Search ADS Monga Alokparna B. , John Deborah Roedder ( 2010 ), “What Makes Brands Elastic? The Influence of Brand Concept and Styles of Thinking on Brand Extension Evaluation,” Journal of Marketing , 74 3 , 80 – 92 . Google Scholar CrossRef Search ADS Munro Donald J. ( 1985 ), ed., Individualism and Holism: Studies in Confucian and Taoist Values , Ann Arbor : Center for Chinese Studies, University of Michigan , 1 – 34 . Murray Noel , Sujan Harish , Hirt Edward R. , Sujan Mita ( 1990 ), “The Influence of Mood on Categorization: A Cognitive Flexibility Interpretation,” Journal of Personality and Social Psychology , 59 3 , 411 – 25 . Google Scholar CrossRef Search ADS Nisbett Richard E. , Norenzayan Ara ( 2002 ), “Culture and Cognition,” in Stevens’ Handbook of Experimental Psychology, Third Edition, Vol. 2: Memory and Cognitive Processes , ed. Pashler Hal , Medin Douglas L. , New York : Wiley , 561 – 97 . Nisbett Richard E. , Peng Kaiping , Choi Incheol , Norenzayan Ara ( 2001 ), “Culture and Systems of Thought: Holistic versus Analytic Cognition,” Psychological Review , 108 2 , 291 – 310 . Google Scholar CrossRef Search ADS PubMed Nordgren Loran F. , Dijksterhuis Ap ( 2009 ), “The Devil Is in the Deliberation: Thinking Too Much Reduces Preference Consistency,” Journal of Consumer Research , 36 1 , 39 – 46 . Google Scholar CrossRef Search ADS Norenzayan Ara , Smith Edward E. , Kim Beom Jun , Nisbett Richard E. ( 2002 ), “Cultural Preferences for Formal Versus Intuitive Reasoning,” Cognitive Science , 26 5 , 653 – 84 . Google Scholar CrossRef Search ADS Novak Thomas P. , Hoffman Donna L. ( 2009 ), “The Fit of Thinking Style and Situation: New Measures of Situation-Specific Experiential and Rational Cognition,” Journal of Consumer Research , 36 1 , 56 – 72 . Google Scholar CrossRef Search ADS Oyserman Daphna , Coon Heather M. , Kemmelmeier Markus ( 2002 ), “Rethinking Individualism and Collectivism: Evaluation of Theoretical Assumptions and Meta-Analyses,” Psychological Bulletin , 128 1 , 3 – 72 . Google Scholar CrossRef Search ADS PubMed Oyserman Daphna , Lee Spike W. S. ( 2008 ), “Does Culture Influence What and How We Think? Effects of Priming Individualism and Collectivism,” Psychological Bulletin , 134 2 , 311 – 42 . Google Scholar CrossRef Search ADS PubMed Pham Michel Tuan , Avnet Tamar ( 2004 ), “Ideals and Oughts and the Reliance on Affect versus Substance in Persuasion,” Journal of Consumer Research , 30 4 , 503 – 18 . Google Scholar CrossRef Search ADS Prelec Drazen , Loewenstein George ( 1998 ), “The Red and the Black: Mental Accounting of Savings and Debt,” Marketing Science , 17 1 , 4 – 28 . Google Scholar CrossRef Search ADS Reinholtz Nicholas , Bartels Daniel M. , Parker Jeffrey R. ( 2015 ), “On the Mental Accounting of Restricted-Use Funds: How Gift Cards Change What People Purchase,” Journal of Consumer Research , 42 , 4 , 596 – 614 . Sakaluk John Kitchener ( 2016 ), “Exploring Small, Confirming Big: An Alternative System to the New Statistics for Advancing Cumulative and Replicable Psychological Research,” Journal of Experimental Social Psychology , 66 ( September ), 47 – 54 . Google Scholar CrossRef Search ADS Schank Roger C. , Abelson Robert P. ( 1977 ), Scripts, Plans, Goals, and Understanding , Hillsdale, NJ : Erlbaum . Shafir Eldar , Thaler Richard H. ( 2006 ), “Invest Now, Drink Later, Spend Never: On the Mental Accounting of Delayed Consumption,” Journal of Economic Psychology , 27 5 , 694 – 712 . Google Scholar CrossRef Search ADS Shefrin Hersh M. , Thaler Richard H. ( 1988 ), “The Behavioral Life-Cycle Hypothesis,” Economic Inquiry , 26 4 , 609 – 43 . Google Scholar CrossRef Search ADS Shiv Baba , Fedorikhin Alexander ( 1999 ), “Heart and Mind in Conflict: Interplay of Affect and Cognition in Consumer Decision Making,” Journal of Consumer Research , 26 3 , 278 – 82 . Google Scholar CrossRef Search ADS Song Inseong , Chintagunta Pradeep K. ( 2006 ), “Measuring Cross-Category Price Effects with Aggregate Store Data,” Management Science , 52 10 , 1594 – 609 . Google Scholar CrossRef Search ADS Spiller Stephen A. , Fitzsimons Gavan J. , Lynch John G. Jr. , McClelland Gary H. ( 2013 ), “Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression,” Journal of Marketing Research , 50 2 , 277 – 88 . Google Scholar CrossRef Search ADS Steel Piers D. , Kammeyer-Mueller John D. ( 2002 ), “Comparing Meta-Analytic Moderator Estimation Techniques under Realistic Conditions,” Journal of Applied Psychology , 87 1 , 96 – 111 . Google Scholar CrossRef Search ADS PubMed Thaler Richard ( 1980 ), “Toward a Positive Theory of Consumer Choice,” Journal of Economic Behavior and Organization , 1 1 , 39 – 60 . Google Scholar CrossRef Search ADS Thaler Richard ( 1985 ), “Mental Accounting and Consumer Choice,” Marketing Science , 4 3 , 199 – 214 . Google Scholar CrossRef Search ADS Thaler Richard ( 1999 ), “Mental Accounting Matters,” Journal of Behavioral Decision Making , 12 3 , 183 – 206 . Google Scholar CrossRef Search ADS Triandis Harry C. ( 1995 ), Individualism and Collectivism , Boulder, CO : Westview . Wadhwa Monica , Zhang Kuangjie ( 2015 ), “This Number Just Feels Right: The Impact of Roundedness of Price Numbers on Product Evaluations,” Journal of Consumer Research , 41 5 , 1172 – 85 . Google Scholar CrossRef Search ADS Walker Iain , Gibbins Keith ( 1989 ), “Expecting the Unexpected: An Explanation of Category Width?” Perceptual and Motor Skills , 68 3 , 715 – 24 . Google Scholar CrossRef Search ADS Walters Rockney G. ( 1991 ), “Assessing the Impact of Retail Price Promotions on Product Substitution, Complementary Purchase, and Interstore Sales Displacement,” Journal of Marketing , 55 2 , 17 – 28 . Google Scholar CrossRef Search ADS Walters Rockney G. , MacKenzie Scott B. ( 1988 ), “A Structural Equations Analysis of the Impact of Price Promotions on Store Performance,” Journal of Marketing Research , 25 1 , 51 – 63 . Google Scholar CrossRef Search ADS Wang Cheng Lu , Chan Allan K. K. ( 2001 ), “A Content Analysis of Connectedness vs. Separateness Themes Used in US and PRC Print Advertisements,” International Marketing Review , 18 2 , 145 – 60 . Google Scholar CrossRef Search ADS Wedel Michel , Zhang Jie ( 2004 ), “Analyzing Brand Competition across Subcategories,” Journal of Marketing Research , 41 4 , 448 – 56 . Google Scholar CrossRef Search ADS Wilson David B. ( 2005 ), “Meta-Analysis Macros for SAS, SPSS, and Stata,” http://mason.gmu.edu/∼dwilsonb/ma.html. Zhang D. L. ( 1985 ), “The Concept of ‘Tian Ren He Yi’ in Chinese Philosophy,” Beijing University Journal , 1 , 8 . © The Author(s) 2018. Published by Oxford University Press on behalf of Journal of Consumer Research, Inc. All rights reserved. For permissions, please e-mail: email@example.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)
Journal of Consumer Research – Oxford University Press
Published: Oct 1, 2018
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