Accidently on purpose: Action-oriented self-deception in the service of difficult-to-justify purchases

Abstract

The desire for a positive self-view can lead people to deceive themselves. Past research has demonstrated that such self-deception can take the form of selective memory search, rationalization of opposing arguments and distorted self-signaling. We postulate the existence of an action-oriented form of self-deception. We find that when people are motivated to act inconsistently with their perceived self (e.g., to purchase a newer yet difficult-to-justify version of a product they already own), they resolve this internal conflict by being more careless or less likely to protect their owned possession, increasing the likelihood of it being damaged. In so doing, they “remove” the negative interpretation of a difficult-to-justify or wasteful purchase from the desired purchase action. We demonstrate that people act more carelessly when the purchasing opportunity involves an economically difficult-to-justify product, such as a new style design, than an easy-to-justify product, such as a technological advancement.

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Introduction

A recent article in the NY Times suggested that by evaluating their existing mobile

phones as working slower than usual, Apple users may have been trying to justify a wasteful

behavior (upgrading to a new iPhone) (Mullainathan, 2014). Interestingly, this evaluation

(measured via users’ searches of the word “iPhone slow” in Google’s search engine) was

associated with the launch of a new generation of iPhones. Several explanations were suggested

for users’ complaints, including planned obsolescence by Apple (i.e., they provided an upgraded

system in the new product while hampering the performance of the previous one; Bulow, 1986;

Mullainathan, 2014) and a placebo effect (i.e., consumers perceive the performance of old

products as inferior when new ones are introduced to the market; Berns, 2005; Irmak, Block, &

Fitzsimons, 2005). In this study, we investigate the following question: if Apple users actually

wish to actively devalue their own iPhones in order to justify an upgrade to a premium version,

under which conditions are they likely to do so and which behavioral theories might underlie

these actions? More specifically, we ask how consumers who lack reasonable reasons and

justifications (Shafir, Simonson, & Tversky, 1993) to devalue products they already own are

nevertheless able to use such actions to justify a decision that they have already made (i.e., to

purchase a hard-to-justify upgrade). In the current project, we offer action-oriented self-deception

as a mechanism by which consumers justify wasteful purchases. We provide evidence to suggest

that consumers may “accidentally” risk old products they own when new ones are introduced to

the market.

People deceive themselves for various reasons. Self-deception may increase one's

influence on others (Trivers, 2002), serve self-enhancement purposes (Alicke & Govorun, 2005;

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Balcetis, 2008; Bastardi & Shafir, 1998; Dunning, 2005; Kunda, 1990; Sedikides & Gregg,

2008), or improve one’s positive self-view (Chance, Gino, Norton & Ariely, 2011; Chance,

Norton, Gino & Ariely, 2015; Festinger, 1957; 1964). Motivated individuals, for example, are

known to engage in a memory search among an array of potentially relevant self-conceptions,

eventually leading to the activation of only those attributes that are consistent with a desired view

of the self (Kunda & Sanitioso, 1989). In this study, we postulate that self-deception may go

beyond the cognitive search for self-serving attributes and the pre- (Russo, Meloy & Medvec,

1998) and post- (Festinger, 1957; 1964) decision processes of denying, justifying and

rationalizing opposing arguments or behaviors that are inconsistent with a desired self-view. We

suggest that self-deception may also result in actual behavioral modification aimed to support

future, difficult-to-justify decisions. We postulate that people may be less careful with product

they already own, or may “accidentally” damage products they own, thereby facilitating a

difficult-to-justify purchase decision.

The paper continues as follows. Firstly, we introduce a theoretical background to support

the proposed mechanism. Secondly, we conduct a field analysis to demonstrate the phenomenon,

followed by a laboratory experiment to further examine the underlying process. We conclude

with a discussion of the results and their implications.

Why might people place their own possessions in harm’s way? In this paper, we argue

that people may do so because it can leave them with no other alternative but to purchase a new

product they want, but have a hard time justifying (e.g., purchasing a more stylish version of an

iPhone). We suggest that by “closing the door” on a product in their possession, people pave the

way to purchase the difficult-to-justify (i.e., wasteful) option. The incentive for this act comes

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from the self-signaling nature of behavior and is consistent with the self-perception literature,

which indicates that people infer their own dispositions and character from observing their own

behavior (Bem, 1972; Quattrone & Tversky, 1984). By acting in a manner that increases the

likelihood that their already owned possession will be damaged, but does definitively lead to

damage, people may conveniently conclude (when the possession is damaged), that they have no

other choice but to purchase the new offering (Bodner & Prelec, 2002) and thus are less likely to

blame themselves for behaving wastefully.

Previous research has demonstrated that people experience conflict when faced with a

purchase opportunity that is desirable, but, at the same time, could be perceived as “wasteful”.

Next, we describe the prior literature that is most relevant to our current study and we discuss

how the phenomenon of choice elimination might be extrapolated from that research.

The idea that people respond less negatively to the loss of options associated with

already-missed opportunities (options that are no longer available) than to future missed

opportunities (options that are still available) was documented recently (Shani, Danziger &

Zeelenberg, 2015). The research demonstrated that people prefer to avoid acting on purchase

opportunities that are likely to cause regret when future options become available. Thus,

participants who had to purchase a product at full price (i.e., a wasteful purchase) preferred to

purchase it from sellers that had offered the product for a discounted price in the past than from

sellers that intended to offer it at a discounted price in the future. Having to pay full price for a

product that will be discounted in the future is likely to make the current purchase feel extra

wasteful and painful. Already-missed discount opportunities provoke regretful counterfactuals (“I

know I could have made a better decision!”), as the alternative choice has already been

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eliminated. On the other hand, opportunities that will be missed in the future are linked with pre-

factual thoughts (“I am responsible for having to pay full price for a product that will be

discounted!”), as the alternative is still available (i.e., has not been eliminated). Thus, of the two

scenarios, individuals experience less difficulty paying full price for a product that is associated

with a past discount, as they do not have to consider letting go of a future discount, they feel less

responsible for missing out on the promotion (see also Caruso, 2010), and they feel more

comfortable purchasing the product at full price (Shani et al., 2015).

In this research, we propose a choice elimination mechanism. Similarly to Shani et al.

(2015), we suggest that people tend to prefer situations in which some of the choice alternatives

are no longer available (i.e., continuing to use the product in my possession). However, here we

propose that rather than simply preferring such situations, people sometimes actively bring them

about by eliminating the undesired option (i.e., the product in my possession).

We already know that consumers may feel uncomfortable when having to choose between

purchasing a “less desired yet justified” and a “more desired yet difficult-to-justify” (i.e.,

“wasteful”) product (Arkes, 1996; Okada, 2005; Bolton & Alba, 2012), e.g., paying $10 for a

regular seat in the theater versus $50 for a VIP seat. Similarly, consumers may find it difficult to

justify the purchase of a premium item when already owning a basic or previous version at home

(Okada, 2001; 2005). In such situations, people may search for a means that would help them to

justify the new purchase. For instance, they may emphasize the differences and dissimilarities

between the options (Okada, 2001) or they may invest different resources that makes the

purchase seem less wasteful (i.e., time and money for acquiring hedonic versus utilitarian

products (Okada, 2005). We propose that when consumers face such a dilemma (e.g., the option

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of purchasing a newer version of iPhone than the one they currently own), and the difference

between the options in the choice set is not obvious (e.g., the newer version consists solely of a

style upgrade), or is difficult to justify, they may eliminate the dilemma by altering one of the

options (i.e., the product they own). Such a prediction is counterintuitive to the notions that

people (a) generally prefer having the choice to reverse their decisions (Gilbert & Ebert, 2002;

Kirkebøen & Teigen, 2011), and (b) are attracted to choice variety (Iyengar & Lepper, 2002).

These would suggest that people would rather keep all options available for as long as possible

(Shin & Ariely, 2004). Why, then, would they eliminate a choice option?

Self-deception requires vagueness

How can people act carelessly (rather than recklessly) without feeling as though they are

deceiving themselves? Recent research clarified the components of self-deception, suggesting

that in order for self-deceptive behavior to exist, some level of vagueness regarding individuals’

ability to interpret their own behavior is required (Sloman, Fernbach, & Hagmayer, 2010).

Consistent with this self-signaling view and the requirement for vagueness, Quattrone and

Tversky (1984) showed that participants who were asked to put their hands in a cold bucket of

iced water, believing that a painful experience indicates weakness of their cardiovascular system,

kept their hands in the bucket for a longer duration than participants who were told that the

absence of a painful experience indicates weakness. The difference in time duration between

these two conditions suggests that participants manipulated the time they kept their hand in the

iced-water to infer that their cardiovascular system was strong. Thus, the individuals faced two

possible interpretations of their actions – strong versus weak cardiovascular system – and were

willing to trade some physical pain in exchange for a positive self-perception.

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How could people allow themselves to behave in such a self-serving manner? Couldn’t

they infer that they were simply deceiving themselves by suggesting different time durations to

reach maximum pain? Sloman et al. (2010) suggested that imprecision in the environment allows

leeway to interpret one's own actions as either intervention (a deliberate choice) or observation

(the external perception of an outsider), thereby allowing a self-deceptive behavior (in this case,

an intervention viewed as an observation) to appear. Thus, participants may have conveniently

confused (interpreted) a ‘diagnostic’ phenomenon with a ‘causal’ one, while the exact definition

of painfulness was subjective and therefore somewhat elusive. As noted by Quattrone and

Tversky (1984), holding one’s arm for more (or less) time in the water is merely diagnostic of

whether one has a healthy heart; it does not cause a change in your heart's type. Yet people

(perhaps subconsciously) behave as if they can actually change their heart's type.

The same principles that allow participants to believe that they are inferring (observing)

the strength of their cardiovascular system from their behavior should apply to consumers who

wish to dispose of products (eliminate choice options). We suggest that consumers do not

intentionally break products they own. Instead, products are “accidentally” destroyed by users

who act less carefully with them. Vagueness regarding how the accident occurred allows

consumers to act carelessly without feeling as though they are deceiving themselves. This way,

consumers cannot be perceived, or perceive themselves, as behaving wastefully.

One question remains open though. Does the phenomenon of damaged products following

the introduction of superior, yet unjustified versions, exist? If so, under which conditions is the

phenomenon most pronounced? How can we uncover evidence for the existence of this deceptive

behavior? Consider, for example, a situation where a new product is launched and the difference

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between the new product and the previous version is minimal. In this situation, it might be

difficult for consumers to justify an upgrade. If we can observe this behavior in a large-scale field

setting, we might be able to uncover initial evidence for the existence of the proposed

phenomenon. We consider as a case study the introduction of multiple models of the Apple

iPhone in the year 2011.

Study 1: Naturalistic Setting - Demonstrating the phenomenon in the field

Companies work very hard to communicate to their clients why the benefits associated

with new products should overcome consumers’ sense of wastefulness (Arkes, 1996; Okada

2005; 2006) and endowment (Kahneman, Knetsch, & Thaler, 1990; Okada, 2001). When Apple

launched the iPhone 4 on June 24, 2010, it was offered only in the color black. In the year that

followed, two major, related launches were announced. First, on April 27, 2011, Apple

announced the launch of a white iPhone 4. This model was practically identical to the black one,

only offered in white (See Figure 1A). The white version was already available for purchase one

day later on April 28, 2011. While consumers may have a substantial feeling of ownership

towards their current device (the iPhone 4 in black), the introduction of the white version may

pose a dilemma for these consumers. Purchasing a new device just for its color may be perceived

as particularly wasteful (Arkes, 1996).

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Figure 1A. iPhone 4 versions offered in the colors white and black.

Second, iPhone 4S, the successor of iPhone 4, was announced on October 4, 2011. Apple

claimed that this version, although identical in appearance to the iPhone 4, would be seven times

faster (see Figure 1B). The iPhone 4S was launched on October 14, 2011. Purchasing a new

device for its advanced technology is likely to be perceived as justified and less wasteful.

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Figure 1B. iPhone 4S (left) versus iPhone 4 (right).

Consider the consumers who own the original, black iPhone 4. Within a period of less

than six months from the purchase of their device, they face two product launches of an upgraded

version. In one case, they see a device that differs only in color; as one reporter wrote: “There's

nothing special about it except that it's white. No new features, no more storage space -- aside

from the color of its case and home button, the white iPhone 4 will be exactly the same as the

black iPhone 4.” (Jackson, 2011). Note, however, that the color is unique and that there was a lot

of buzz about how good the phone looked (Jackson, 2011; Ong, 2011; Stevens, 2011). Quoting

from Apple’s own press release: “The white iPhone 4 has finally arrived and it’s beautiful”

(Harrison & Kerris, 2011). For a consumer considering an upgrade, this description poses a

difficult-to-justify upgrade choice. We hypothesize that, under these circumstances, consumers

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may be inclined to “accidentally” damage the black iPhone 4 that they already own in the hope of

eliminating the choice dilemma.

In the second case, consumers are facing the introduction of a newer version of the

iPhone, the 4S, which offers a much faster device with more features (e.g., digital personal

assistant, superior camera and memory; GSMArena, 2011). In this case, the upgrade decision

should be easier to justify, and we hypothesize that consumers will prefer to sell their black

iPhone 4 as used, rather than (“accidentally”) damaged.

As noted, we expect to find more damaged versions of the iPhone 4 offered for sale when

the “upgrade” is difficult to justify (i.e., buying the iPhone 4 in the color white) than when it is

more reasonable (i.e., buying the iPhone 4S, which offers advanced technology). We use the

second-hand market for mobile phones to observe the phenomenon, as will be described in the

following section, hypothesizing that:

H1: Following the introduction of the white iPhone 4, we expect an increase in the number of damaged (relative to used) products offered for sale, compared to baseline values (i.e., before the white iPhone 4 was launched).

H2: Following the introduction of the iPhone 4S, offering advanced technology, we expect an increase in the number of used (relative to damaged) products offered for sale, compared to baseline values.

Results

To follow the number of iPhones that were offered for sale on the market, we scraped the

data on all of the listings of iPhones offered for sale from a large e-commerce website. The data

were collected between January 1, 2011 and December 31, 2011, at a daily level. When a

customer lists an item on this website, they must indicate the item status (new, used or broken), 11

as well as the price requested. While collecting the sales data for the iPhone 4, we also collected

the data on its two predecessors, the iPhone 3 and the iPhone 3GS. Note that versions 3 and 3GS

are older versions relative to which both the iPhone 4 white and the iPhone 4S offer advanced

technology. This means that for owners of these older models, the purchase of either iPhone

model would be likely to be perceived as justified, as both models provide a significant

advantage in utility and functionality compared to the 3 and 3GS.

In total, we collected the data on 1,193,490 iPhones listed in 2011. In Table 1, we

summarize the data by phone type and condition.

Table 1: Data summary. The number of iPhones listed for sale on a large e-commerce website, subdivided by iPhone model (i.e., 3, 3GS or 4) and the item status (new, used or broken).

Condition

Model

New Used Broken Total

iPhone 3 8,749 248,024 47,246 304,019

iPhone 3GS 26,608 308,545 42,384 377,537

iPhone 4 99,532 382,036 30,366 511,934

Total 134,889 938,605 119,996 1,193,490

Methodology - difference in difference analysis:

In the spirit of Meyer (1995), we ran a difference in difference analysis in which the

relative difference between broken and used iPhone 4 models that were listed online was

compared before and after each of the following events: the introduction of the white iPhone 4

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and the introduction of the iPhone 4S. For each of these model introductions, we considered both

the launch announcement as well as the actual first date of sales as our point of interest, resulting

in four quasi-experiments. For the difference in difference analysis of each of the scenarios

depicted above, we used four-week time windows, one prior to the event and the other following

the event.

In figures 2A and 2B, we respectively show the time series for broken and used iPhone 4

models listed in 2011, where each point reflects the relative sales for that date. To control for

scale, we standardized each time series (by subtracting each observation by the mean of the series

and dividing the result by the standard deviation). Our main interest here is to study the temporal

variation in the difference between the number of used and broken iPhones offered for sale.

Which of these devices is offered relatively more frequently during each of the time windows?

Figure 2A: Standardized time series for broken iPhone 4 models

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Figure 2B: Standardized time series for used iPhone 4 models

To examine this question, we propose a difference in difference analysis. We examine the

difference between the two series (used and broken) over a similar time window (four weeks)

before and after an event (i.e., a launch or announcement of a new device). We wish to establish

whether there is a significant change in the difference between the two series within the time

windows of interest; thus, we also control for the day of the week in the analysis. In our

difference in difference analysis, we use Δyt, which is the difference between the standardized

series (used minus broken). According to Meyer (1995), this method yields smaller standard

errors than regressing on yit with series dummies for used and broken data. The regression is as

follows:

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Δy t= y (used )t− y (broken)t=β0+β1⋅Event Dummy t +ε it

We can interpret the resulting coefficients as:

β0 - The average difference in the standardized series (used minus broken) in the time window before the event

β1 - The difference-in-difference, i.e., the change in used compared to broken iPhones in the time window after the event - this is our focal coefficient

In Figure 3, we plot the differenced series (positive values mean that more used phones

were sold and negative values mean that more broken phones were sold), as well as the dates of

each of the scenarios.

Figure 3: Standardized differenced time series for used and broken iPhone 4 models, along with the dates of the announcement and launch of the white iPhone 4 and the iPhone 4s

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The results are shown in Table 2. Supporting H1, we find that both the announcement

(i.e., introduction), as well the actual launch of the white version influence the number of

damaged products offered online. Specifically, more damaged (rather than used) products were

offered for sale in the period following the introduction of the white iPhone 4 than in the period

preceding it. These findings imply that consumers might be more careless with their iPhones,

following the introduction of the white version, in order to justify a difficult-to-justify purchase

(a style upgrade).

When looking at the announcement and launch of the iPhone 4S, which offers advanced

technology, we find a strong positive coefficient, supporting H2. We find an increase in the

number of used products offered online relative to the number of broken products. These results

are consistent with the assumption that it is easier to justify the purchase of a new version when

the functional benefits are clear.

In our mechanism description, we proposed that when finding an upgrade difficult to

justify, consumers may not actively seek to damage their products, but they are less likely to

protect them from harm. However, this process is not immediate and may require some time to

occur (see the increase in the rate of broken phones offered for sale after the launch of the white

iPhone 4 in Figure 3). We therefore seek to test whether the number of damaged iPhones offered

for sale increases as a function of the time elapsed since the introduction of the new white

version. This is evaluated by comparing two new time windows in our difference in difference

analysis, namely one of 14 days (two weeks) and one of 42 days (six weeks) from the date of the

announcement(see Table 3). We indeed find that after 14 days, the rate of damaged iPhones

offered for sale does not increase significantly above the rate of used iPhones, suggesting that a

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two-week period might not be sufficient to demonstrate the phenomenon. However, after 42

days, the effect is much stronger. This pattern supports the assumption that individuals may

inadvertently increase the hazard of damaging the products that they own rather than damaging

them intentionally. In six weeks, enough iPhones are listed that the effect size is almost doubled.

In contrast, for the launch of the iPhone 4S, we see a significant effect of more used

iPhones being sold even when using the shorter, 14-day time window. In this case, consumers

clearly do not need to justify listing their devices.

We find additional indirect evidence that accidentally damaging a device is associated

with a difficult-to-justify purchase when examining the products offering inferior technology

(i.e., iPhone versions 3 and 3GS) (see Table 4). We find that for both older models, there was no

significant increase in the number of damaged (relative to used) products offered online either

when the iPhone 4S or the white iPhone 4 became available. In fact, following the launch of the

iPhone 4S, a greater number of used rather than broken devices were offered for sale, supporting

H2.

Table 2: Difference in difference regression results for a 28-day time window

EventWhite

Announced

WhiteLaunch

4SAnnounce

d

4SLaunch

Intercept 0.22 0.20 -0.21 0.46

Event Dummy -0.42** -0.37* 2.30** 1.29**

Sunday 0.24 0.24 0.05 -0.03Monday -0.30 -0.30 -0.25 -0.19Tuesday -0.57 -0.57 -0.08 0.01Wednesday -0.81** -1.03** -0.27 -0.10Thursday -0.39 -0.39 -0.25 -0.03Friday -0.92** -0.92** 0.17 0.14

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* p-value < 0.05, ** p-value < 0.01

Table 3: Difference in difference regression results for 14- and 42-day time windows

Event WhiteAnnounced

WhiteLaunch

4SAnnounced

4SLaunch

Time Window(days) 14 42 14 42 14 42 14 42

Intercept 0.35 .26 0.30 .26 0.03 -.18 1.23* .21

Event Dummy -0.03 -.66** 0.07 -.66** 2.59** 2.03** 1.10* 1.24**

Sunday -0.15 .28 -0.15 .28 -0.18 -.10 0.01 .06Monday -0.56 -.12 -0.56 -.12 -0.30 -.26 -0.23 -.13Tuesday -0.98* -.57* -0.98* -.57 -0.60 -.24 0.35 -.02

Wednesday -0.91* -.67* -1.39** -1.06** -0.76 -.28 -0.21 -.07

Thursday -0.41 -.59* -0.41 -.59 -0.87 -.26 0.02 -.05Friday -0.81 -.83** -0.81 -.83** 0.38 .02 0.41 .09

* p-value < 0.05, ** p-value < 0.01

Table 4: Difference in difference regression results for older models (iPhone 3 and iPhone 3GS) for a 28-day time window

Event WhiteAnnounced

WhiteLaunch

4SAnnounced

4SLaunch

InvestigatediPhone version 3 3GS 3 3GS 3 3GS 3 3GS

Intercept -.22 -.07 -.29 -.08 -.95** -.79* -.81** -.69**

Event Dummy .04 .34 .17 .35 1.00** 2.32** 1.09** 2.87**

Sunday .42 .22 .42 .22 .32 -.34 .35 -.45Monday -.27 -.64 -.27 -.64 .00 -.33 .00 -.44Tuesday -.56* -1.35 -.56* -1.35** .09 -1.18* .12 -.79

Wednesday-

1.08** -.83* -1.13** -.85* .06 -.32 .23 -.13

Thursday -.93** -1.15** -.93** -1.15** -.08 -.47 -.07 -.15Friday -.83** -1.06** -.83** -1.06** .07 -.43 -.11 -.43

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* p-value < 0.05, ** p-value < 0.01

It is interesting to note that a new iPhone 4 was listed for $436 on average (black and

white models cost the same for the same amount of data storage), while used ones were offered

for $340. Owners of the black iPhone 4 would have therefore needed to justify paying over $100

for a new color. However, the damaged iPhone 4 was offered online for $217 on average. This

suggests that if consumers do damage their products, they are willing to sacrifice over $100 (i.e.,

the difference between $340 and $217) so as to justify the upgrade. This interpretation, of course,

does not hold for the owners of older models, as they can justify the upgraded version by the

technology it offers rather than the design.

In summary, the field data seem to confirm the existence of the hypothesized

phenomenon, namely that there is an increase in the number of damaged products offered online

following the introduction of a difficult-to-justify purchase option. Nevertheless, it remains to be

shown whether phenomena of this nature arise because consumers are indeed less likely to

protect products they own when faced with a difficult-to-justify purchase option (compared with

a “reasonable” purchase option). The following study is designed to test this.

Study 2: Do consumers act carelessly when a difficult-to-justify purchase option is

available?

Our study below is designed to clarify whether the behavior found on the online e-

commerce website, namely that the ratio of damaged to used iPhones offered for sale increases

following the launch of a new, yet difficult-to-justify version of the iPhone (e.g., a shift from the

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black iPhone 4 to white), can be attributed, at least partially, to deceptive behavior by individuals

who act carelessly with products they own.

Ninety five university students (48 women; Mage = 22.1), all of whom were iPhone

owners, were invited to participate in a lab study in return for course credits and 10 NIS1. They

were asked to view a short introductory video presenting a new iPhone “to be launched”,

followed by several questions assessing the new features the iPhone offers. Half the participants

watched a video emphasizing style modifications and the other half watched a video emphasizing

additional technological modifications.

Participants were asked to indicate which version of the iPhone they currently owned (3,

3GS, 4, 5, 5S, or 6), the extent to which they felt that the new iPhone offered improved

technological modifications relative to those existing in the market, and the likelihood that they

would purchase the new iPhone (the latter two responses being expressed as ratings ranging from

0 = Not at all to 7 = Very much). To assess whether the introduction of a difficult-to-justify

purchase option (i.e., an iPhone offering only a newer design) encourages careless behavior,

participants were offered (“as a token of appreciation”) to purchase raffle tickets for a protection

case (see figure 4) fitting the iPhone they already owned. The case was stated to be worth 140

NIS and was described as guaranteeing best protection for their device, including water damage.

Each raffle ticket cost 1 NIS and participants could purchase up to 10 tickets, thereby

communicating their degree of motivation to protect the iPhone they already owned.

1 $1 was worth 3.8 NIS at the time of the study.20

Figure 4: Protection case participants could win in the raffle.

To exclude alternative explanations for participants devaluing the iPhone they already

owned, and to provide further insight into stated purchase intentions as well potential careless

behavior, participants were also asked to indicate: (a) the extent to which they were satisfied with

the iPhone model they currently owned (0 = Not at all, 7 = Very much) and (b) the minimal

amount of money they would request for the iPhone they owned if offered a trade-in deal.

Breaking a product to justify the purchase of a new one is not, in general, an intentional act, nor

is it socially accepted. Nevertheless, in case it would provide some additional information,

participants were asked to bluntly indicate whether they would intentionally damage the phone

they owned in order to justify the purchase of the new one (YES/NO). Finally, participants

reported their monthly income (relative to the average income in Israel in March 2015, namely

9769 NIS) on a five-point rating scale: 1 = Under average, 5 = Above average.

Following H1, we expect the participants who do not have a good enough justification to

purchase the new iPhone (i.e., those shown an iPhone that offers only a new design) to buy fewer

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lottery tickets than the participants who have a better justification to upgrade (i.e., those shown an

iPhone that offers both a new design and new technology). The fewer tickets a participant

purchases, the less motivated they are perceived to be to protect the phone they currently own.

Results

Manipulation check: Participants had a stronger impression that the new iPhone offers improved

technological features (relative to those currently on the market) when they viewed an

introductory video offering new technology (M = 5.48, SD = 1.36) versus new style (M = 4.96,

SD = 1.26), F(1,93) = 3.71, p = 0.057, η2 = .0382. Communicating the difficulty in justifying the

purchase of a product that does not offer clearly superior features, participants indicated that they

were more likely to purchase the iPhone that offered new technology (M = 4.58, SD = 1.66) than

the iPhone that offered only a new design (M = 3.89, SD = 1.76), F(1,93) = 3.86, p = 0.052, η2 =

0.04. In line with H1 that the extent to which the new product offers superior features to existing

products (i.e., “improved modification”) justifies its purchase, we find that when regressing (a)

the participants’ perception of the “improved modification” and (b) the independent variable

(type of modification, i.e., technological or style) on the likelihood of purchasing the new phone,

the former strongly predicts purchase tendencies (β = 0.454, t(94) = 4.89, p < .0001), whereas the

latter loses significance (β = 0.38, t(94) =1.19, ns). This result implies that consumers’ ability to

justify purchasing a new product by giving higher scores to the modifications offered in the new

product plays an important role in their decision to actually act on the purchase option.

2 Holding the income covariate constant did not change the results, F(1, 94) = 0.04, ns, nor was there any effect of the type of iPhone currently owned, F(1, 94) = 0.19, ns.

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We find that participants are less likely to purchase lottery tickets for a protection case

when the new iPhone offers only an advanced design (M = 1.26, SD = 1.98) than when it

additionally offers advanced technology (M = 3.08, SD = 3.66), F(1,89) = 8.25, p = 0.005, η2 =

0.083. This indicates that the former group of participants is inclined to be less careful with the

iPhone they already own. Note that neither income (F(1,89) = 1.40, ns) nor the type of iPhone the

individual already owns (F(1,89) = 1.92, ns) explains a participant’s (un)willingness to purchase

raffle tickets for a protection case.

To rule out an alternative explanation for consumers to devalue products they own when a

new phone is introduced, and to further support our conviction that participants do not justify the

possible purchase of a new product by finding conscious justifications, we investigate the

relationship between participants’ level of satisfaction with their current iPhone and the type of

promotional video they watched (new design vs. new technology), There is no difference in

satisfaction level between these two groups of participants, F(1,89) =0.17, ns. Moreover, we

analyze the data related to the amount of money an individual would request for a trade-in of

their current phone and find no effect of the type of promotional video, F(1,89) = 1.72, ns. These

findings indicate that consumers do not necessarily think less of the products they own when new

ones are introduced to the market. Furthermore, they provide indirect evidence to support our

interpretation that the careless behavior is aimed at justifying the purchase of products that are

difficult to justify.

Finally, we examined participants’ willingness to intentionally damage their existing

phone when a new one is introduced, by explicitly asking them if they would intentionally try to

get rid of their current iPhone in order to justify the purchase. We find that 16.7% of participants 3 We excluded 5 participants that were evaluated statistically as outliers.

23

(7 out of 42) introduced to a new design, and 29.2% (14 out of 48) introduced to a new

technology, admitted they would actively try to get rid of their iPhone to justify the purchase of

the new model. The difference between the groups was not significantly significant, χ2 (1, N =

90) = 1.95, ns. Importantly, when we re-analyze the purchase of raffle tickets only for those

participants that indicated they would not damage their own iPhone, we still find that participants

are less likely to purchase raffle tickets for a protection case when the new iPhone offers only an

advanced design (M = 1.40, SD = 2.11) than when it additionally offers advanced technology (M

= 2.91, SD = 3.57), F(1,67) = 4.60, p = 0.035, η2 = 0.06. This finding suggests that participants

engage in active self-deception.

Discussion

Previous studies presented various forms that self-deception may take, for example,

selective memory search, rationalizing opposing arguments, and distorted self-signaling (Alicke

& Govorun, 2005; Balcetis, 2008; Dunning, 2005; Kunda, 1990; Kunda & Sanitioso, 1989;

Sedikides & Gregg, 2008; Trivers, 2002). In our work, we document a new manifestation of self-

deception – “accidentally” eliminating the interpretation that poses a threat to the positive self-

perception. We suggest that when it is difficult to justify a purchase (e.g., wanting to purchase a

more stylish iPhone that was just introduced to the market while owning a previous version),

individuals may eliminate the negative interpretation of the behavior by removing one of the

choice alternatives (e.g., by increasing the odds of ruining the basic iPhone). Obviously, as

previous literature has suggested, changing the setting consciously cannot achieve this goal

(Quattrone & Tversky, 1984; Sloman et al., 2010). Thus, the change is “accidental”. Our study

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supports the interpretation that people act more carelessly with their belongings when an

opportunity to purchase an unjustified product arises, thereby increasing the odds of eliminating

choice options.

It is acceptable to work hard in order to keep doors open (Shin & Ariely, 2004). It is less

acceptable to strive to “shut doors”. Our study is consistent with previous research showing that

people are generally more averse to the idea of failing to act upon future (rather than past)

opportunities (Shani et al., 2015). However, our research extends the phenomenon by showing

that people may take action in order to “shut doors” when unable to sensibly justify a desired

outcome. Such behavior is likely to be performed “below the radar” and our results support this

interpretation. Indeed, when we analyzed the purchase of protective case raffle tickets only for

those participants that indicated that they would not purposefully damage their existing iPhone,

we still find that participants in the hard-to-justify condition (an advanced design upgrade only)

purchased less raffle tickets than participants in the easy-to-justify condition (an advanced design

and advanced technological upgrade)

The potential to accidentally change the setting is embedded in our experiment as well our

field data. We study two conditions that differ with respect to whether there is potential for the

individuals to end up with an outcome that would serve their goal of engaging in a behavior that

might appear wasteful (i.e., purchasing a more stylish iPhone versus one that offers advanced

technology). Specifically, our results demonstrate that, in general, the desired self-view is that of

a non-wasteful individual (Arkes, 1996). This would imply that the increase in the number of

damaged (relative to used) iPhones that are offered online following the introduction of a style

upgrade is a result of careless, possibly unconscious behavior.

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The interpretation of buying a premium product while still holding the basic one as

“wasteful” is embedded in the endowment effect, which suggests that the very fact of ownership

of a product increases its perceived value (Thaler, 1980; Kahneman, Knetsch, & Thaler, 1990).

The endowment effect can be attenuated by external forces such as trade-ins (Arkes, 1996;

Okada, 2001) offered by firms. In addition to such trade-ins (which effectively release consumers

from the products they own), companies work very hard to convince clients to buy new products

by communicating their superior features. In this manner, companies help consumers to

overcome their endowment and to justify letting go of the old product and acting on the new one.

All of the participants in our experiment owned a version of the same product (either

technologically inferior or of an older design), and all were introduced to a new version that was

expected to be launched. Consistent with the endowment effect, we expected all participants to

have an incentive to protect their existing iPhone. Nevertheless, we showed that some of the

participants were less protective (more careless) than others, namely those who were incentivized

to buy a product that did not seem to justify the upgrade (i.e., a product offering only a style

modification). Simply put, since these participants did not have an external means of justifying

the purchase, they acted carelessly. In contrast, participants were more likely to protect their

existing product when the new iPhone offered a major technological jump of the type that is

likely to justify acting on the new product. Indeed, participants indicated they would be more

likely to act on the product that offered new technology.

The importance and implications of this phenomenon for marketers are straightforward:

Although consumers generally prefer to purchase quality, long-lasting products, our research

suggests that despite the appealing resonance of quality products, products that are long-lasting

might “hold consumers prisoners” of their own misconceptions. Marketers therefore ought to 26

create sensible, reasonable opportunities for consumers to detach from the products or to justify

(Bastardi & Shafir, 1998) “putting out the old and bringing in the new”. This would help the

consumer to overcome the sense of waste (Arkes, 1996) and would also boost sales. We believe

that the current findings provide a basis for developing prescriptive tools to assist marketers to

follow up on consumers’ detachment-purchase needs and shed more light on individuals’

motivation to “go out with the old” before “bringing in the new”.

We believe that engaging in reckless behavior in such a way as to "accidentally" eliminate

undesired choices is not limited to products and belongings and is likely to be relevant to other

situations in life whereby a straightforward justification may not be appropriate. For example,

individuals might choose to drive to an interview for a job that is highly desirable, but which they

cannot take, via a route that is prone to traffic jams. Or they might fail to finish an important task

on time at the office and thus arrive late for dinner on exactly the same day that their in-laws are

in town. This is what we refer to as “accidentally on purpose”.

27

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