The Influence of Payment Mechanisms on Pricing: When Mental Imagery Stimulates Desire for Money

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The Influence of Payment Mechanisms on Pricing: When Mental Imagery Stimulates Desire for Money夽 Xiaobing Xu a,∗ , Rong Chen b , Lan Jiang c a

Hainan University, China Tsinghua University, China c Menlo College, United States b

Abstract The present research investigates how differences in payment mechanisms, and between cash and e-payments, in particular, influence sellers’ pricing behavior. Extant finance literature predicts that cash payments prompt price discounts, yet the present research demonstrates that compared with e-payments, cash payments facilitate mental imagery processes, which increase people’s desire for money and induce higher sales prices. In a series of five experiments, we establish a basic effect of payment mechanisms on pricing (Studies 1a and 1b), then provide evidence that mental imagery and desire for money underlie the effects (Studies 2 and 3). Yet these effects emerge only when consumers focus cognitively on the prospective financial gain, not when they focus on the forgone object (Study 4). We in turn offers both theoretical insights and managerial implications. © 2019 New York University. Published by Elsevier Inc. All rights reserved. Keywords: Payment mechanism; Pricing; Mental imagery; Cognitive focus

Introduction When users seek to sell their used and unwanted items on local marketplaces, a primary decision revolves around the price to set. In some popular secondary markets (e.g., eBay, Craigslist), sellers often signal that the selling price is negotiable, and the final price commonly depends on transaction terms. For example, one potential customer might promise to pay cash when picking up the item, whereas another might offer to pay via mobile transfer. If everything else about the transaction remains the same, do these two payment methods affect the selling price? In particular, do sellers set different selling prices when they are paid in cash or by electronic mechanisms? Payment mechanism, that is, the instrument used to facilitate transactions, is one among the multiple factors that might influ-

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This work was supported by the National Natural Science Foundation of China [grant numbers 71702079, 71472104, 71772104], and Tsinghua University Initiative Scientific Research Program (20151080390). ∗ Corresponding author at: Department of Business Administration, Management School, Hainan University, Haikou, China. E-mail address: [email protected] (X. Xu).

ence sellers’ pricing behavior (e.g., Hill and Riener 1979; Ingene and Levy 1982). Cash and electronic payments (e-payment hereafter) are considered as two of the most important instruments, accounting for 31% and 56% of payments in the U.S. market by volume, respectively (Greene and Schuh 2017). E-payments entail the transfer, by electronic means, of value from a payer to a payee, whether through the Internet (e.g., PayPal, Alipay) or mechanisms such as credit or debit cards. Historically, cash payments have offered higher liquidity (Acharya and Pedersen 2005; Amihud and Mendelson 1986) and lower transaction costs (Hill and Riener 1979; Ingene and Levy 1982) and thus prompted price discounts compared with non-cash payments (e.g., credit cards). However, innovative, portable e-payment tools have eliminated these liquidity constraints and transaction costs (Bezovski 2016; Hoofnagle, Urban, and Su 2012) and are readily available in transactions between buyers and sellers. Buyers thus might choose to pay with either cash or mobile payments even when purchasing food from street vendors, for example. More importantly, payment mechanisms do not differ merely in their financial attributes, but also in the physical form, or the transparency regarding the inflow and outflow of money

https://doi.org/10.1016/j.jretai.2019.08.002 0022-4359/© 2019 New York University. Published by Elsevier Inc. All rights reserved.

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(Kamleitner and Erki 2013; Raghubir and Srivastava 2008; Soman 2003). Cash payments represent the most transparent mechanism because it is easy to see the money. In contrast, e-payments tend to be extremely opaque (non-transparent), in that people are hardly aware of the inflow or outflow of funds (Kamleitner and Erki 2013; Raghubir and Srivastava 2008; Soman 2003). Prior research has focused primarily on a particular consequence of payment transparency, namely, the pain of payment when making purchases (e.g., Prelec and Loewenstein 1998; Raghubir and Srivastava 2008; Soman 2003). We instead consider a different, novel consequence of payment mechanisms: the mental imagery generated by the prospect of receiving the payment. Specifically, we argue that a cash payment, compared with an e-payment, may facilitate mental imagery of money and increase the seller’s desire for it, which leads to higher prices for the offered items or services. We further argue that this effect may be moderated by sellers’ cognitive focus, because if they focus on the relinquished product, their limited cognitive resources may keep them from engaging in mental imagery, even in response to a cash payment. In that case, the influence of the payment mechanism on pricing may be attenuated. Across five studies, we seek to make several contributions. First, contrary to the conventional wisdom that indicates cash payments result in price discounts compared with non-cash payments, we find that cash can lead to a higher selling price than e-payments under certain conditions. Second, we contribute to literature on payment transparency (Raghubir and Srivastava 2008; Soman 2003), by showing that transparency not only increases the pain of parting with money, but also promotes mental imagery of money. Third, our research provides in-depth insights into how different payment mechanisms may affect pricing; we test the role of mental imagery and desire for money in determining this effect. The following sections present a review of the prior literature on payment mechanisms and mental imagery. Then we develop our theory about the effect of payment mechanism on pricing. After presenting the five experimental studies conducted to test the hypotheses, we discuss the managerial implications of our findings, some limitations, and future research directions. Theoretical Development A key differentiator between cash and e-payments is the physical form (Soman 2003). Cash constitutes the physical form of currency, such as banknotes and coins. When viewed as a legal tender, cash is the most transparent form (Raghubir and Srivastava 2008; Soman 2003). In contrast, e-payment mechanisms lack any physical appearance or tangible form. When people receive money electronically, such as via PayPal or credit card, the change appears only in their account balance, which they might not even be aware of. In this sense, e-payment is an opaque form of payment (Raghubir and Srivastava 2008; Soman 2003). Research has shown that the transparency of a payment increases the pain of parting with money, which hinders consumers’ tendency to spend (Prelec and Loewenstein 1998; Raghubir and Srivastava 2008).

In a situation in which a user functions as a seller and receives money, the payment mechanism might also have some novel implications, pertaining to the mental imagery it evokes. This processing mode involves the generation of picture-like representations in a gestalt form in working memory (Kosslyn 1976; MacInnis and Price 1987). When people decide to sell items or services, they might mentally generate pictures of receiving money from the buyer. Previous research found that stimuli vary in their ability to evoke mental imagery (Lee and Qiu 2009; Paivio, Yuille, and Madigan 1968). Cash, in its physical form with colors and even pictures, can easily activate an imagery of money, in terms of seeing the token, touching the notes and sensing the texture. Instead, it is difficult to generate mental pictures of e-payments, which are generally opaque. In line with our prediction that payment mechanisms affect mental imagery, Srivastava and Raghubir (2002) find that people recall cash payments better than those made by credit card. That is, the payment mechanism affects human recollection of earlier events, which is a typical manifestation of mental imagery (Baddeley 1990; Taylor and Schneider 1989). When a stimulus induces mental imagery, it often amplifies the benefits of owning the objects, thus increasing people’s desire for them (Bone and Ellen 1992; MacInnis and Price 1987). Extant research also shows that mental imagery enhances consumers’ attitude, purchase intentions, and desire to own an imagined object (e.g., Babin and Burns 1997; Escalas 2004; Moore and Bovell 2008). For instance, Schlosser (2003) reveals that mental imagery induced by virtual interactions with a product has a positive effect on purchase intentions. According to Harvey, Kemps, and Tiggemann (2005), instructing participants to imagine a food induction scenario increases their food cravings. Considering the generally positive views of money as an important resource that people value, pursue, and possess, mental imagery of money from the payment may increase people’s desire for it and thereby escalate the prices they demand in exchange for their products or services. That is, if cash payments facilitate mental imagery of money and increase people’s desire for it, they should lead to higher selling prices than e-payments. We formally propose: H1. Cash payment leads to a higher selling price than epayment. H2. The effect in H1 occurs because the cash payment induces a higher level of mental imagery of money, which increases people’s desire for it. In a typical selling scenario, two related processes occur simultaneously: losing goods while gaining some financial payments (Kamleitner and Hoelzl 2009; Prelec and Loewenstein 1998). In general, consumers focus on the latter aspect when they decide to sell used products, because the used products are something they no longer need or want and thus intentionally give up (Novemsky and Kahneman 2005). With regard to services, sellers also tend to focus on prospective financial gains, because the time and effort they expend are intangible and intentionally exchanged for financial gains. However, in some situations, sellers focus more on the forgone product than on the finan-

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Independent Variable Payment mechanism (cash vs. electronic payment)

Moderator 1 Guided imagery

Moderator 2 Cognitive focus

Study 3

H3 Study 4

3

H1 Studies 1a-1b Dependent Variable Selling prices Mediator 1 Mental imagery H2 Study 2

Mediator 2 Desire for money H2 Study 2

Fig. 1. Overall process model and associated studies.

cial gain (Carmon and Ariely 2000; Novemsky and Kahneman 2005), such as when they have strong emotional attachments to the product or worry about its ultimate fate (Brough and Isaac 2012). According to cognitive resource theory (Kliegel et al. 2001; Zhu and Meyers-Levy 2005), when consumers focus more on the loss aspect of a transaction, the cognitive resources left to the gain aspect decrease. In this case, the physical characteristics of payments might not significantly influence consumer cognition (i.e., mental imagery). Thus, H3. The effect of the payment mechanism on selling price is attenuated when consumers focus their cognition on the forgone product rather than the prospective financial gain.

Overview of Studies We conducted five experimental studies (Fig. 1) to test these hypotheses. In Study 1a, we demonstrate that cash payments elicit higher selling prices than e-payments. This effect remains significant even after we control for two financial attributes: perceived risk and perceived convenience. In Study 1b, we replicate this payment mechanism effect in a real service context. With Study 2 we test the underlying mechanism and specify a serial mediation model, in which cash payment (vs. e-payment) induces greater mental imagery of money, which increases people’s desire for money and ultimately leads to higher selling prices. In Study 3, we provide further evidence of the proposed mechanism by showing that the effect of the payment mechanism on pricing disappears when consumers are prompted to undertake a mental imagery process. Study 4 provides a test of the proposed interactive effect of payment mechanism and cognitive focus. By directly manipulating sellers’ cognitive focus through an importance rating task, we find that if sellers consider the impending financial gain, cash leads to a higher selling price than an e-payment, but this effect is attenuated when sellers focus on the forgone product.

Study 1a Study 1a tests H1 in a transaction setting involving used goods. Study 1a participants had to imagine that they were about to sell a used object, namely, a handbag, through a flea market. They indicated the selling prices they would be willing to accept when paid in cash versus via mobile card transfer. Because people generally do not need products they sell anymore and tend to focus more on receiving the money than on losing the used items, we predict that these participants will set a higher price when they are paid in cash rather than by e-payment. We also attempt to rule out an alternative explanation, namely, that cash payments might be considered less secure or convenient than epayments (Bezovski 2016), so sellers would set higher prices to compensate for these drawbacks of cash payments. We test for this possibility by measuring the perceived risk and convenience associated with both payment mechanisms. Method Participants and design Eighty-two female undergraduate students from a university in North China voluntarily participated in the experiment in return for a small gift. They were randomly assigned to one of two conditions in a single-factor (cash payment vs. e-payment) between-subjects design. Procedure All participants first read a scenario about selling a used handbag. Those in the cash payment condition read: Imagine that you are going to graduate this July. Since you will move to another city for a job, you have begun to clear out your rented room. There was a handbag that you won as a prize in a megamall anniversary promotion one year ago. However, its design is out of date, and the color seems tasteless. Over the last year, you seldom used it. Now, you have decided to sell it. After doing some research, you found

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Table 1 Means and analysis of variance of main measures (Study 1a).

Cash payment E-payment F value

Selling price

Perceived risk

Perceived convenience

Mood

266.8 RMB 230.0 RMB 4.16*

4.12 4.27 0.23NS

4.54 4.83 0.84NS

4.96 4.85 0.16NS

Note: * Sig < .05, NS > .05.

that the secondhand market price of the same model was between 100 RMB and 400 RMB. You list the handbag on a local, Internet-based flea market. Shortly after posting the information, you received a message from someone expressing strong interest in the handbag and asking to check its condition in person. The sender also indicated that if the handbag condition was satisfying, she would immediately pay you in cash. Participants in the e-payment condition read the same scenario, except that the last line indicated, “she would immediately pay you via mobile card transfer.” To strengthen the manipulation, participants answered two questions related to either cash or mobile card transfer (for a similar manipulation, see Prelec and Simester 2001). Participants in the cash payment condition indicated whether “they have ready access to a local ATM or bank” and “cash could be used in their university canteen.” Those in the e-payment condition were asked to identify the type of card (credit card, debit card) that would be used to receive the money and the length of time they had been holding the card. After the manipulation questions, all participants indicated the price they would be willing to accept for their handbag and rated how risky and convenient they perceived the cash payment (mobile card transfer) to be (1 = not at all, 7 = very much). They also described their mood (1 = bad, 7 = good). Finally, the participants were thanked and dismissed. Results A one-way ANOVA on selling prices revealed that participants in the cash payment condition (M = 266.8, SD = 82.6) required more than participants in the e-payment condition (M = 230.0, SD = 80.8; F(1, 80) = 4.16, p < .05). No difference emerged between the two conditions for perceived risk, perceived convenience, and mood (ps > .1). Table 1 presents the means of all these measures. Importantly, the effect of payment mechanism on pricing remained marginally significant even if we included perceived risk, perceived convenience, and mood as the covariates (F(1, 77) = 3.39, p = .07). No other effect was observed. Discussion Contrary to the popular belief that cash payments prompt discounts, Study 1a showed that sellers set even higher prices when they were paid in cash rather than mobile card transfer. In addition, the results did not reveal any difference in perceived risk or convenience between cash payments and mobile card trans-

fer, which ruled out an alternative explanation that people might require higher payments to offset the financial or convenience drawbacks of cash payments. We have previously argued that sellers focus more on the prospective financial gains than on the used items after they decide to sell them. To confirm our arguments, we conducted a posttest (N = 40) in which female participants from the same university read the scenario from the main study, except without any information about payment methods. Participants then completed a cognitive focus scale, in which they indicated their agreement (1 = strongly disagree; 7 = strongly agree) with two statements pertaining to how much they focus on (1) gaining the prospective income and (2) losing the handbag. The results revealed that participants focused more on gaining the prospective income (one-sample t-test: M = 5.33, SD = 1.82; t(39) = 4.61, p < .001) and less on losing the handbag (onesample t-test: M = 2.55, SD = 1.47; t(39) = −6.25, p < .001). Thus, sellers appear mainly focused on financial gains when selling their used products. Study 1b The objective of Study 1b is to replicate the findings in Study 1a in a real service context and in an incentive-compatible setting. Consumers often face situations in which they provide some services in exchange for some financial gains (e.g., work as a MTurk worker). In such a trade, consumers generally concentrate on the financial gains, because earning these gains is their primary goal. With Study 1b we test whether consumers ask a higher price for their services when they are paid in cash (vs. through mobile payment). Method Participants and design Seventy-nine undergraduate students from a large public university in North China participated in the experiment. The experimenter approached the students in a teaching building and invited them to participate in a proofreading project for payment. A preliminary analysis showed that 59.5% of the subjects were women and 40.5% men, ranging in age from 18 to 30 years (Mage = 20.6 years, SD = 2.39). They were randomly assigned to either the cash payment or the mobile payment condition. Procedure Participants arrived at the behavioral lab in groups of four or five. The experimenter explained that a very important document required no language errors, so they were being invited to proofread it simultaneously. The 15-page Chinese document was translated from a business textbook. The participants had to underline any possible faulty wording that made the document hard to read. After they finished the proofreading task, participants responded to a series of measures. Specifically, they read that we would pay them in cash (through mobile payment) and had to indicate the price of their proofreading service, on a scale ranging from 5 RMB to 20 RMB. To strengthen the manipulation, participants were presented with either a cash-

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Fig. 2. Posters for the cash payment and e-payment (Study 1b). Table 2 Means and analysis of variance of main measures (Study 1b).

Cash payment E-payment F value

Selling price

Task difficulty

Perceived risk

Perceived convenience

Mood

11.72 RMB 9.20 RMB 4.66*

3.05 3.50 2.19NS

2.87 3.15 0.60NS

3.38 3.75 0.83NS

4.64 4.85 0.52NS

Note: * Sig < .05, NS > .05.

related poster, which depicted many RMB currency notes, or a mobile payment-related poster, which featured the Alipay icon (see Fig. 2; for a similar manipulation, see Su and Gao 2014). They then noted the difficulty of the proofreading task (1 = not at all, 7 = very much). Next, participants rated how risky and convenient the cash (mobile) payment was (1 = not at all, 7 = very much), described their mood (1 = bad, 7 = good), and reported their gender and age. Finally, participants received the money they asked for, through the specific payment method, and were thanked and dismissed. Results We conducted a one-way ANOVA on prices with payment mechanism as the independent variable. As predicted, participants in the cash payment condition offered a higher price (M = 11.72, SD = 5.52) than those in the mobile payment condition (M = 9.20, SD = 4.83; F(1, 77) = 4.66, p < .05). No difference emerged between the two conditions in terms of task difficulty, perceived risk, perceived convenience, and mood (ps > .1). Table 2 presents the means of all these measures. We next ran an ANCOVA on prices with task difficulty, perceived risk, perceived convenience, and mood as covariates. The results showed a marginal effect of task difficulty (F(1, 73) = 3.09, p = .08). Importantly, the effect of payment mechanism on pricing remained significant (F(1, 73) = 6.21, p = .01). No other effects were observed. Discussion Study 1b replicated Study 1a’s findings in a real service context. Participants promised a cash payment required more money for their proofreading services than those who knew they would

receive a mobile payment. Consistent with Study 1a, we did not find any significant differences in perceived risk or convenience across the two payments, suggesting the effect of the payment mechanism on pricing results from physical attributes, not financial ones. In a service selling context, consumers generally focus on the prospective financial gain, because they intended to give up their time or effort to obtain some financial earnings. As in Study 1a, we ran a posttest to check whether participants concentrated on the financial gains. Students from the same university (N = 28) participated in exchange for 10 RMB. As in the main study, the participants first had to complete a proofreading task, after which they responded to a cognitive focus scale, different from the one we used in Study 1a. Specifically, participants reviewed three pairs of words, each of which contained one word related to a gain aspect (“gain,” “income,” and “happy”) and another to a loss aspect (“loss,” “time,” and “sad”). In each pair, participants were asked to choose the word that better described what they had in mind. For each participant, we calculated the total number of words related to the gain aspect. The results affirmed that the participants in this service-providing context selected more gain-related words (one-sample t-test: M = 1.89, SD = .88; t(27) = 2.38, p < .05), indicating that they focus more on financial gains than on the time and effort spent. Study 2 The objective of Study 2 is to replicate the payment mechanism effect and test its underlying drivers. We have hypothesized that mental imagery and desire for money explain why cash payments (vs. e-payments) increase selling prices. Thus, we predict a serial mediation effect, such that a cash payment (vs. e-payment) induces a higher level of mental imagery of

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Fig. 3. Posters for the cash payment and e-payment (Study 2).

money, which in turn increases sellers’ desire for money and leads them to charge higher selling prices (i.e., payment mechanism → mental imagery → desire for money → selling price). We also examined a plausible alternative explanation on the effect. Prior research has shown that the cash payments, compared with credit card payments, increase the pain of payment and thus restrains spending (Prelec and Loewenstein 1998; Raghubir and Srivastava 2008). When the person instead is receiving money, a cash payment, with its visible physical appearance, might bring more “joy of receiving” to sellers than an e-payment. As a result, consumers who encountered cash payment might be more motivated to set a higher price than those who are paid through e-payments. Although neither Study 1a nor Study 1b revealed any difference in mood across conditions, we directly examined the potential role of “joy of receiving” in this study. Method Participants and design One hundred and twenty-four participants were recruited from Amazon MTurk (49.2% women; Mage = 34.9 years, SD = 10.3) for this experiment, in exchange for a small monetary incentive. Participants were randomly assigned to one of the two conditions: cash payment or e-payment. Procedure Participants were first asked to read a scenario about selling a used product, which prompted them to imagine they had previously purchased a laptop for USD 849 that they were planning to sell through a local online secondary market. Participants also learned that once they had reached an agreement, they would meet the potential buyer to complete the trade. After having read the scenario, participants were asked, “Given that similar models are sold in the range of USD 400–650, how much are you willing to accept for your laptop if someone pays you cash (pays you via PayPal)?” To strengthen the manipulation, each participant was presented with either a cash-related poster, which depicted many currency notes, or a PayPal-related poster, featuring the PayPal icon (see Fig. 3).

After the participants specified their selling prices, they proceeded to a mental imagery measure adopted from Elder and Krishna (2012). In particular, participants rated the extent to which they felt that the images of money came to their mind (1 = not at all; 7 = to a great extent), the number of such images that came to mind (1 = few or no images; 7 = lots of images), and the extent to which they could imagine the money (1 = not at all; 7 = to a great extent). The means of all three items were used to form a mental imagery index (␣ = .91). We also evaluated sellers’ desire for money by asking the participants about the extent to which they agreed that “money is important to me,” “frankly speaking, having money is something that I value,” and “to get the most of life, people need money” on 7-point Likert scales (1 = strongly disagree, 7 = strongly agree). The average of these three items formed the desire for money index (α = .61). To measure the “joy of receiving,” we used a measure from prior research (Thomas, Desai, and Seenivasan 2005) and asked participants, “How do you feel about receiving money in this trade?” Participants indicated their responses on a 5-point nonverbal facial scale, with a sad face ( ) at the lower end of the scale and a happy face ( ) at the higher end. Pretests In the main study, we measured both mental imagery and desire for money after participants offered their selling prices, which implies that the two mediators could be influenced by the prices offered (potential carryover effect). To establish the direct influences of payment mechanisms on mental imagery and desire for money, we conducted two separate pretests. In the first, MTurk participants (N = 72) were randomly assigned to either the cash or e-payment condition and read the same scenario as in the main study. Then they had to imagine that a potential buyer showed interest in their laptop and would pay them cash (pay them via PayPal) if he decided to purchase it. Each participant also saw the cash-related or PayPal-related poster, depending on the group assignment. Next, participants completed the mental imagery measure as in the main study. As predicted, participants in the cash payment condition indicated a higher level of mental imagery (M = 4.76, SD = 1.15) than those in the e-payment condition (M = 4.13, SD = 1.42, F(1, 70) = 4.39, p < .05). The second pretest (N = 73) is similar to the first one except that participants

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␤

SE

95% CI

PM → SP PM → MI MI → DM MI → SP DM → SP PM → MI → SP PM → DM → SP PM → MI → DM → SP PM → DM → MI → SP

−29.98 −.68 .14 10.17 26.59 −5.76 −8.87 −1.72 −1.01

11.83 .28 .05 3.78 7.07 3.50 4.47 1.23 .91

[−53.41, −6.56] [−1.23, −.13] [.05, .23] [2.69, 17.64] [12.60, 40.59] [−13.65, −.33] [−19.12, −1.77] [−4.89, −.14] [−3.36, .11]

Note: SE = standard error; CI = confidence interval; PM = payment mechanism; SP = selling price; MI = mental imagery; DM = desire for money.

completed the desire for money measure after the scenario. The results also confirmed that participants in the cash payment condition had a stronger desire for money (M = 5.72, SD = 1.00) than those in the e-payment condition (M = 5.21, SD = 1.11, F(1, 71) = 4.29, p < .05). Results Selling price We submitted the selling prices to a one-way ANOVA with payment mechanism as the independent variable. The results revealed a significant main effect of payment mechanism (F(1, 122) = 6.42, p < .05). Specifically, when participants were promised a cash payment, the average amount of money they asked for their laptop was USD 517.5, which was significantly higher than the selling price of USD 487.5 when participants were promised an e-payment. Mental imagery and desire for money As predicted, payment mechanism also had an effect on mental imagery. A one-way ANOVA on mental imagery revealed a significant effect of payment mechanism (F(1, 122) = 6.05, p < .05). A planned contrast confirmed that cash payments induced a higher level of mental imagery (M = 5.10, SD = 1.51) than e-payments (M = 4.42, SD = 1.56). In a similar way, a one-way ANOVA on desire for money showed a significant effect of payment mechanism (F(1, 122) = 6.89, p < .01). Specifically, participated in the cash payment condition reported a stronger desire for money (M = 5.75, SD = .77) than those in the e-payment condition (M = 5.37, SD = .82).

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nism → desire for money → mental imagery → selling price) was nonsignificant (β = −1.01; 95% CI [−3.36; .11]), suggesting that the predicted serial mediation model best explained our data. Discussion By using a different product (laptop), Study 2 further confirmed the hypothesis that a cash payment, compared with an e-payment, increases sellers’ required price. Moreover, a serial mediation analysis provided evidence of the proposed mechanism. In particular, cash payments (vs. e-payments) induce greater mental imagery of money, which increases people’s desire for money and the prices they charge to sell their product. An independent posttest also addresses whether participants focused mainly on the prospective financial gain in this experimental setting. Thirty-four participants from Amazon MTurk (50% women; Mage = 32.32 years, SD = 10.9) read the scenario from the main study and completed a cognitive focus measure, similar to the posttest in Study 1b. The data showed that participants chose more gain-related words (one-sample t-test: M = 2.09, SD = .97; t(33) = 3.55, p < .001), indicating that they generally focus more on prospective gains than on losing the laptop. A plausible alternative explanation for the results may stem from the “joy of receiving.” We tested this possibility by conducting a one-way analysis of variance on the “joy of receiving.” The results revealed no significant differences in the joy of receiving across conditions (Mcash = 3.77, SD = 0.75; Me-payment = 3.86, SD = 0.71; F < 1), suggesting that the effect of the payment mechanism on pricing could not be explained by the affective account of joy of receiving. Study 3 We designed Study 3 to provide more evidence of the proposed mechanism. In particular, Study 2 showed that a cash payment induces a mental imagery process, which drives the effect of the payment mechanism on pricing. If a mental imagery cue is explicitly provided, the effect of the payment mechanism on pricing then should be attenuated. Manipulating an alternative cue provides stronger and more direct evidence of the causal chain by demonstrating mediation through moderation (Bullock, Green, and Ha 2010). Method

Mediation We then tested the proposed pathway (payment mechanism → mental imagery → desire for money → selling price) using a serial mediation model (Model 6; Preacher and Hayes 2008). Unstandardized coefficients for the effects and their confidence intervals are presented in Table 3. Consistent with our hypothesis, the effect of payment mechanism (cash payment was coded as 1 and e-payment was coded as 2) on selling price through mental imagery and desire for money was significant (β = −1.72; 95% CI [−4.89; −.14]). However, additional analyses indicated that the “reverse” model (payment mecha-

Two hundred and six students from a university in North China participated in this study for 15 RMB. They were randomly assigned to one of four conditions in a 2 (payment mechanism: cash vs. e-payment) × 2 (guided imagery: yes vs. no) between-subjects design. The payment mechanism was manipulated using a verbal priming task, without any pictures. The participants saw a list of word sets, each containing five words, and were instructed to unscramble and use four words to create a sentence. In the cash payment condition, the extraneous word that should not be used was cash-related, whereas

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tion (M = 1260.6, SD = 261.3; F < 1). In addition, the results also revealed that guided imagery increased the selling prices for e-payment (Mguided imagery = 1260.6, SD = 261.3, Mno guided imagery = 1153.8, SD = 239.4; F(1, 202) = 5.61, p < .05), but not for cash payment (Mguided imagery = 1239.8, SD = 173.4, Mno guided imagery = 1270.6, SD = 235.2; F < 1). Discussion

1050 1000

guided imagery cash-payment

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Fig. 4. Guided imagery weakens the effect of payment mechanism on pricing (Study 3).

in the e-payment condition, it was e-payment-related. To identify appropriate words for this sentence-unscrambling task, we asked 48 undergraduates to generate four words related to cash or e-payments in a separate pretest (Bargh and Chartrand 2000). The 11 words related to cash payment or e-payment with the highest frequencies then entered the main study. For example, participants in the cash condition had to construct a sentence out of the word set “room, one, Mary, opens, currency” and those in the e-payment condition were presented with the word set “room, one, Mary, opens, iBank.” Each participant completed all eleven possible sentences. After the priming task, all participants were asked to read a same scenario as in Study 2, except that the product for sale was a smartphone with a purchase price of 2800 RMB, and similar used models were priced in the range of 900 RMB–1400 RMB. Next, those participants in the guided imagery condition were asked to close their eyes, relax, and concentrate on generating images of receiving money from the payment (for a similar manipulation, see Bone and Ellen 1992); in the no guided imagery condition, they were not presented with any such information. Finally, all participants indicated the price they would be willing to accept for their used smartphone. Results Selling prices were analyzed with a 2 (payment mechanism) × 2 (guided imagery) ANOVA. Results showed that neither the main effect of payment mechanism (F(1, 202) = 2.24, p = .14) nor that of guided imagery was significant (F(1, 202) = 1.41, p = .24). Central to our prediction, the interaction between payment mechanism and guided imagery was significant (F(1, 202) = 4.61, p < .05). Planned contrasts indicated that, as showed in Fig. 4, participants who encountered cash payment asked a higher selling price (M = 1270.6, SD = 235.2) than those who encountered e-payment (M = 1153.8, SD = 239.4; F(1, 202) = 6.64, p = .01) when participants did not proceed to a guided imagery process. However, when participants were asked to generate images of receiving money form the payment, there was no difference in selling price between the cash (M = 1239.8, SD = 173.4) and the e-payment condi-

The study results aligned with our proposed theory that the effect of the payment mechanism on pricing is driven by the physical features of the different payment methods. Cash payments are more transparent than e-payments and more easily induce mental imagery of money, which increases people’s desire for it. Study 3 establishes this link by showing that the effect of the payment mechanism on pricing gets switched off when people are asked to mentally imagine the process of receiving money. Throughout this article, we have suggested that our results are restricted to conditions in which participants focus on the prospective financial gain. With the next study, we test this boundary condition. Study 4 With Study 4, we examine the role of cognitive focus as a critical moderator. When sellers focus on the prospective financial gain, the payment mechanism should affect their mental imagery of money and further increase their desire for money and pricing. However, when sellers’ cognitive focus is on the product, it limits their cognitive resources, which should attenuate the effect of payment mechanism on the selling price. Method This study employed a 3 (cognitive focus: control vs. product vs. money) × 2 (payment mechanism: cash vs. e-payment) between-subjects design. Two hundred and seventy-four Amazon MTurk participants (59.1% women, Mage = 36.66 years, SD = 11.92) participated in the online experiment. All participants first read a scenario, essentially the same as the one in Study 3, except that we changed the original purchase price of the smartphone to USD 549. To manipulate the participants’ cognitive focus on the product or money, we asked them questions about the smartphone they would lose or the money they would gain (for similar manipulations, see Carmon and Ariely 2000). In the focus-onproduct condition, they were asked to think about and rate the importance of some smartphone-related factors that might influence their selling decisions (e.g., “the smartphone offers a good user experience,” “the smartphone maintains a good cosmetic situation”). In the focus-on-money condition, the statements related to money (e.g., “money is indispensable to modern life,” “with money, I can buy other products in need”). The participants received no such information in the control condition. This manipulation was pretested among 90 MTurk participants (42.5% women; Mage = 36.68 years, SD = 11.65), randomly

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pants’ cognitive focus was on the forgone smartphone, there was no difference in selling price between the cash (M = 205.3, SD = 68.7) and the e-payment condition (M = 214.5, SD = 84.5; F < 1).

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focus-on-product

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Fig. 5. Cognitive focus moderates the effect of payment mechanism on pricing (Study 4).

assigned to the control, focus-on-product, and focus-on-money conditions. The measures of cognitive focus were identical to the one used in the posttest in Study 2. The manipulation of cognitive focus proved successful, such that participants in the focus-onproduct condition chose fewer gain-related words (M = 1.45, SD = .85) than those in the control (M = 2.03, SD = .93; F(1, 59) = 6.53, p < .05) and focus-on-money (M = 2.14, SD = .83; F(1, 58) = 9.95, p < .01) conditions. We found no significant differences in the number of gain-related words between the control and focus-on-money conditions (F < 1). We manipulated the payment mechanism using a priming task. In particular, participants were asked to “generate three or four of the thoughts at the forefront of your mind when it comes to cash (electronic payments) in the following text box”. Then, participants were asked “Given that similar models are priced in the range of USD 100–350 on the market, how much are you willing to accept for your smartphone if someone pays you cash (pays you electronically)?” In addition, participants completed the mental imagery and desire for money measures, as in Study 2. Results Selling price Responses to the selling price were analyzed with a 3 (cognitive focus) × 2 (payment mechanism) ANOVA. The results revealed a main effect of payment mechanism (F(1, 268) = 6.03, p < .05), indicating that cash payments in general lead to a higher selling price (M = 232.1, SD = 70.9) than e-payments (M = 212.3, SD = 71.6). The main effect of cognitive focus was marginally significant (F(2, 268) = 2.50, p = .08). Importantly, the results showed a significant interaction (F(2, 268) = 3.20, p < .05). Planned contrasts indicated that, as showed in Fig. 5, participants who encountered cash payments asked a higher selling price (M = 250.3, SD = 66.6) than those who encountered e-payments (M = 213.6, SD = 60.2; F(1, 268) = 6.43, p < .05) when cognitive focus was not manipulated. Participants in the cash condition also required more (M = 243.5, SD = 70.0) than those in the e-payment condition (M = 208.5, SD = 69.6; F(1, 268) = 5.28, p < .05) when they were guided to focus on the money that they were going to gain. However, when partici-

Mental imagery The same ANOVA on mental imagery revealed a main effect of payment mechanism (F(1, 268) = 7.16, p < .01), indicating that cash in general induced a higher level of mental imagery (M = 4.49, SD = 1.39) than e-payments (M = 4.03, SD = 1.48). No other effects were observed. Importantly, planned contrasts revealed that cash induced more mental imagery than e-payments both in the control (Mcash = 4.51, SD = 1.35, Me-payment = 3.85, SD = 1.61; F(1, 268) = 4.87, p < .05) and the focus-on-money condition (Mcash = 4.74, SD = 1.27, Me-payment = 4.14, SD = 1.42; F(1, 268) = 3.70, p = .06). However, no significant difference in mental imagery between the cash and the e-payment condition was reveled in the focus-on-product condition (Mcash = 4.26, SD = 1.51, Me-payment = 4.12, SD = 1.40; F < 1). Desire for money The same ANOVA on desire for money revealed only a main effect of payment mechanism (F(1, 268) = 7.96, p < .01), indicating that participants encountered cash payments generally showed a higher level of desire for money (M = 5.47, SD = 1.07) than those in the e-payment condition (M = 5.11, SD = 1.10). No other effects were revealed. Importantly, planned contrasts showed that the payment mechanism had a significant effect on desire for money both in the control (Mcash = 5.57, SD = 0.87, Me-payment = 5.06, SD = 1.10; F(1, 268) = 5.04, p < .05) and the focus-on-money condition (Mcash = 5.67, SD = 1.02, Me-payment = 5.13, SD = 1.13; F(1, 268) = 5.31, p < .05), but not in the focus-on-product condition (Mcash = 5.20, SD = 1.23, Me-payment = 5.14, SD = 1.11; F < 1). Mediation We then tested the specific predicted pathway using a moderated mediation model (Model 85, Preacher and Hayes 2008). We entered price as the dependent variable, payment mechanism as the independent variable, mental imagery and desire for money as the mediators, and cognitive focus as the moderator. A bootstrapping analysis with 10,000 samples revealed that the serial mediation was significant both in the control (β = −2.16; 95% CI [−4.75; −.29]), and the focus-on-money condition (β = −3.22; 95% CI [−7.45; −.42]), but not in the focus-on-product condition (β = −1.09; 95% CI [−4.05; 1.46]). Discussion The results from Study 4 demonstrated that cognitive focus moderates the effect of the payment mechanism on selling prices. In particular, when sellers focus their cognitive resources on the money they can gain, cash payments led to higher selling prices than do e-payments. In contrast, when sellers focus on the forgone product, the effect of the payment mechanism on selling prices becomes attenuated.

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The data from Study 4 also provided evidence for the limited cognitive resource account. For cash payments, post-hoc comparisons revealed that participants in the focus-on-product condition required less (M = 205.3, SD = 68.7) than those in the control (M = 250.3, SD = 66.6; Fisher’s LSD: p < .01) and those in the focus-on-money condition (M = 243.5, SD = 70.0; Fisher’s LSD: p < .01), suggesting that when participants focus on the forgone products, the cognitive resources left for the gain aspect are insufficient for a mental imagery process.

General Discussion The present study investigates how payment mechanisms—in particular, cash versus e-payments—affect sellers’ pricing decisions about used products and services. We argue that the cash payments facilitate mental imagery of money and increases sellers’ desire for it, which leads to a higher selling price than charged for e-payments. However, cognitive focus moderates this effect. In particular, when sellers focus on the forgone objects, the payment mechanism might not affect pricing decisions. In confirming these predictions, this research makes several important contributions. First, it advances traditional economics and finance studies of payment mechanisms and pricing, which generally predict that cash payments lead to price discounts due to their low liquidity risk and transaction costs (Acharya and Pedersen 2005; Amihud and Mendelson 1986; Hill and Riener 1979; Ingene and Levy 1982). In contrast with this popular belief, we find that cash payments result in even higher selling prices in certain conditions. As a preliminary observation, we also find no difference in the assessed security or convenience associated with cash payments, as opposed to bank card transfers or mobile payments. Second, this study contributes to literature pertaining to the effects of payment transparency on consumer behavior. Extant literature has focused primarily on how payment transparency might hinder spending propensity (Raghubir and Srivastava 2008; Soman 2003). For example, Raghubir and Srivastava (2008) report that USD 50 is spent more readily when this value is stored on a gift certificate rather than if the same amount were available as cash. We focused on different influences of payment transparency on sellers’ pricing behavior. In particular, cash payments, with their greater transparency, promote mental imagery processes and increase sellers’ desire for money, assuming they already are focused on financial gains. Third, this study explores some boundary conditions of the effects. Previous research proposes that a selling situation involves two related processes: losing the products and gaining the payments (Kamleitner and Hoelzl 2009; Prelec and Loewenstein 1998). If consumers focus on one aspect, the cognitive resources they have left for the other aspect decrease (Zhu and Meyers-Levy 2005). We find that the effect of the payment mechanism on pricing only emerges when consumers focus their cognition on the pending financing gain, not the forgone used goods. Thus, mental imagery is a cognitive process that requires cognitive resources.

As is true of most research, several intriguing directions for research remain that may be worth exploring. First, we show that the use of cash (vs. e-payment) leads to higher selling prices; prior research also indicates that the use of cash (vs. credit card) leads to buyers’ decreased willingness to spend (e.g., Hirschman, 1979; Prelec and Simester 2001). In turn, continued research could combine these insights to investigate how a cash payment (vs. e-payment) might amplify endowment effects. Second, the relationship between desire for money and pricing needs further exploration. The supply-and-demand relations in the market could be an important moderator in this case. In a buyer’s market, sellers are particularly eager to sell their products, and their higher desire for money in the cash payment condition might result in a lower price, because they worry about and are more averse to missing out on the sale entirely. Third, the pricing of secondhand goods is a highly dynamic process, in which price negotiation is quite common (Srivastava and Oza 2006). In particular, sellers encounter second-round pricing, because buyers often ask for a price discount in response to the initial price. We predict that consumers’ cognitive focus might shift from the product to the money as the transaction proceeds, especially for possessions to which consumers have emotional attachments. When sellers set the initial price for a beloved product, their focus tends to be on the forgone product (Carmon and Ariely 2000). However, at the bargaining stage, sellers’ focus might shift to the money. Further research thus should examine the effect of payment mechanisms on pricing across different stages of a transaction. Finally, some practical implications follow from the present study, which may be particularly valuable to secondary market providers, such as eBay, Craigslist, or 58 Tongcheng. These platforms benefit from more transactions among their sellers and buyers. Considering the evidence we provide regarding how the payment mechanism influences price-setting decisions and the importance of the cognitive focus of sellers, we note some potentially significant opportunities for platforms to benefit from lowered product prices and boost their transactions. The present study shows that cash payments are more likely to induce high selling prices, which may hinder potential transactions, so platforms might encourage e-payments and online transaction (i.e., mail products to buyers) to reduce the possibility of cash payments. To achieve that, platforms should continue to strengthen the security and convenience of e-payments. In addition, they should avoid presenting cash-related elements, such as tokens, which may encourage sellers to reduce the selling price and thereby promote more transactions.

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