Electronic copy available at: http://ssrn.com/abstract=1086830

640

� 2008 by JOURNAL OF CONSUMER RESEARCH, Inc. ● Vol. 35 ● December 2008All rights reserved. 0093-5301/2008/3504-0007$10.00. DOI: 10.1086/592126

Focusing on Desirability: The Effect ofDecision Interruption and Suspensionon Preferences

WENDY LIU*

This research examines the phenomenon of interruptions and suspensions in de-cision making. It is proposed that information processing may change from a bot-tom-up, data-driven to a top-down, goal-directed mode after an interruption, therebyaffecting preferences. In particular, in decisions involving desirability and feasibilityconflicts, because desirability is a superordinate goal to feasibility, four studiesfound that when a decision is interrupted and later resumed, people become morelikely to favor highly desirable but less feasible consumption, such as a high-risk,high-reward option or a high-quality, high-price option. A reduced focus on fea-sibility is found to underlie this effect.

Consumers’ decisions are often interrupted or suspendedduring the course of making them. For example, con-

sider a consumer shopping at an online store: as she pondersa particular purchase, she might be interrupted by a pop-upad that informs her of the various events happening at thestore; alternatively, she may be diverted by a prompt on hercomputer to check an incoming e-mail. Similarly, a con-sumer taking a lunch break at the mall may leave a purchasedecision in suspension because she needs to go back to work.Later she returns to the store to resume this decision. Thusan intriguing question that arises is whether such interrup-tions and suspensions in decision making can affect theensuing choices: when people discontinue their decisionsand come back later, do they tend to make different decisionsthan if they had not been interrupted?

Interruptions have long been of interest in psychologicalresearch. Perhaps the best-known effect of task interruptionis the Zeigarnik effect (1927). This body of work suggeststhat people tend to have better memory and stronger mo-tivation for incomplete rather than completed tasks and in-tentions (Mantyla 1996; Marsh, Hicks, and Bink 1998; Sa-vitsky, Medvec, and Gilovich 1997; see also Butterfield

*Wendy Liu is assistant professor of marketing at the Anderson Schoolof Management, University of California, Los Angeles, 110 WestwoodPlaza, Suite B-416, Los Angeles, CA 90095-1481 (wendy.liu@anderson.ucla.edu). The author would like to thank Itamar Simonson, Aimee Drolet,and the reviewers for their helpful comments on this project.

John Deighton served as editor and Mary Frances Luce served as associateeditor for this article.

Electronically published August 29, 2008

[1964] and Goschke and Kuhl [1993] for critical reviewsof this literature). Relatedly, recent consumer research showsthat framing a task, such as earning a number of frequencyreward points for a final prize, as work in progress increasesconsumers’ motivation to earn those rewards (Kivetz, Ur-minsky, and Zheng 2006; Nunes and Dreze 2006). In ad-dition to task motivation, the broader impact of interruptionson shopping behavior has also been studied. For example,Xia and Sudharshan (2002) investigated how different typesof interruption configurations influenced consumers’ onlineshopping time and satisfaction, showing that moderate fre-quencies of interruptions and interruptions that occur earlyin the shopping process tend to be better accepted. However,while existing works have focused on the effects of inter-ruptions on people’s response to the task, they do not addresspeople’s preferences and decisions made within the task.This latter question, namely, the effect of interruptions onpreferences, is the focus of the current research.

Specifically, it is proposed that an interruption can leadto changes in preferences by changing the manner of in-formation processing in decision making; in particular, itmay make processing less bottom-up data driven and moretop-down goal directed, resulting in preferences shiftedtoward one’s primary goal dimension. Current studies ex-amine this possibility in the context of decisions involvingconflicts between desirability and feasibility goals. It ishypothesized that when a decision is interrupted, prefer-ence may systematically shift toward the more primarygoal dimension of desirability. The next sections will de-velop the theory of this interruption effect and present fourexperiments that test this effect and its underlying mech-anism.

Electronic copy available at: http://ssrn.com/abstract=1086830

DECISION INTERRUPTION 641

THEORETICAL BACKGROUND

Extensive research in consumer behavior suggests thatdecision making is often a process of information process-ing, and preferences are constructed as a result rather thansimply retrieved from memory (Bettman, Luce, and Payne1998). In a comprehensive framework of consumer decisionmaking, Bettman (1979) modeled information acquisitionand evaluation at the center of decisions, with the indi-vidual’s motivation and attention systems playing anteced-ent roles and interacting with other decision componentssuch as learning and satisfaction. Notably, this model al-lowed for the course of decision making to be interruptedand further suggested that changes to information processingmay occur after an interruption. Following this framework,this research examines the dynamic changes in informationprocessing due to an interruption. It is posited that an in-terruption may shift processing from a relatively bottom-up, data-driven mode to a more top-down, goal-directedmode.

Bottom-Up, Data-Driven versus Top-Down, Goal-Directed Processing. Cognitive theories generally dif-ferentiate between two modes of information processing,namely, bottom-up versus top-down processing (Hauser1986; Johnson 1984; Park and Smith 1989). The bottom-up mode refers to processing that is driven by the presenceof data rather than guided by one’s preexisting theories andgoals. In contrast, top-down processing is directed by theperson’s existing knowledge and goal structures. A relateddistinction exists in research on attention, contrasting in-voluntary and voluntary attention (Kahneman 1973; Payneand Bettman 2004). Involuntary attention is attention cap-tured by stimuli in the environment, especially those thatare novel, potentially threatening, as well as simply per-ceptually compelling. Voluntary attention, however, refersto selectively devoting attention to information most rele-vant to one’s goals. Thus in a consumer decision, the personcan process information in either a bottom-up manner thatattends to salient, concrete data or a top-down manner inwhich attention is guided by one’s internal structures.

Previous studies have examined conditions in which bot-tom-up versus top-down processing is used in decisions.Extant research suggests that bottom-up processing oftentakes place by default. For example, in visual processing,involuntary attention is automatically aroused by novel stim-uli (Berlyne 1960; Kahneman 1973). Relatedly, consumerresearch demonstrates that people are often sensitive to thespecific presentational features of product information (Bett-man and Kakkar 1977; Bettman et al. 1998), suggestingbottom-up processing of data at play. However, althoughbottom-up processing is often engaged, research has alsoidentified conditions in which people rely more on top-downprocessing. One factor is the salience of a top-down struc-ture. For example, if people have an explicitly articulatedgoal before entering a decision, they are likely to follow atop-down process of evaluating information against this goalrather than attending to the trade-offs within the data (Park

and Smith 1989). Another determinant is the relative needfor piecemeal understanding of new information. For in-stance, for consumers with strong expertise in a particulardomain, when information about a product matches the per-son’s prior category schema, the person may not attend tothe detailed information given, but rather rely on his/hercategory knowledge for efficiency; however, when infor-mation is discrepant from prior schema, he/she is likely toprocess the information in a piecemeal manner (Sujan 1985).Finally, top-down processing is used when bottom-up pro-cessing does not yield insight. For example, Johnson (1984)shows that when choosing among products from differentcategories (e.g., a television and a bike), because the specificattribute information is difficult to compare, people turn toa higher-level goal (fun) to evaluate the data. These resultssuggest that the use of bottom-up versus top-down pro-cessing depends at least in part on the relative salience (andusefulness) of external stimuli versus internal knowledgeand goals: when the salience of external information is re-duced, the person’s preexisting structures may play a biggerrole in guiding processing. Building on this insight, thisresearch proposes that an interruption in decision makingmay also cause processing to become more top-down goaldirected and less bottom-up data driven.

To illustrate, consider a consumer who is contemplatinga product choice. The person learns the available infor-mation regarding the purchase and evaluates the options. Assuggested above, if the situation is relatively novel, pro-cessing is likely to be bottom-up and data driven as theperson seeks to understand the information. Consequently,the person attends to the data in detail, noticing any salientfeatures within the data. After processing the informationunder this bottom-up focus, unless an interruption occurs(or difficulty arises; Johnson 1984), the person is likely tocontinue to deliberate and reach a decision, all the whilerelying on the current, bottom-up view of the situation.

However, consider the case in which the decision is in-terrupted. That is, the person learns the available informationand is contemplating the choice; at this point, the decisionis suspended because of an intervening event. Later theperson returns to make the decision. How does this inter-ruption affect the decision? It is likely that upon returning,the person will continue the decision by reviewing the sit-uation. Interestingly, however, the manner of informationprocessing may now be different in this review. Specifically,because the person has already learned the information be-fore, the data appear less novel and thus would attract lessinvoluntary attention. Further, because the person has al-ready acquired a piecemeal understanding of the data, he/she is less likely to feel the need to relearn the informationin the same piecemeal manner. Instead, as the focus oninformation learning is reduced, attention becomes morevoluntary, and the person’s internal structures may becomemore prominent and exert greater influence. In particular,because decisions generally involve conflicting goals, theperson’s inherent goal structure may guide his/her process-ing of different information. Specifically, information re-

642 JOURNAL OF CONSUMER RESEARCH

garding the person’s high-level, primary goals in the de-cision may become the focus of one’s attention, whereasinformation pertaining to low-level, secondary goal dimen-sions may be relatively less attended to. In other words,attention becomes more top-down and selective accordingto one’s goal construal (rather than driven by data) after aninterruption, resulting in systematic shifts in preferences. Forinstance, in the context of decisions involving conflicts be-tween desirability and feasibility attributes, because desir-ability is a more primary goal dimension than feasibility inpeople’s goal construal (Liberman and Trope 1998), an in-terruption may lead to greater preference for desirabilityover feasibility.

Desirability and Feasibility of Actions. Theories ofgoals generally distinguish between two types of values as-sociated with goal-directed action, namely, desirability andfeasibility values (Bagozzi and Dholakia 1999; Kruglanski1996; Liberman and Trope 1998; Trope and Liberman 2003).Desirability refers to the value of the end state of an action,whereas feasibility refers to the ease or likelihood that theaction will achieve the desired outcome. Thus in the lan-guage of action identification theory (Vallacher and Wegner1987, 1989), desirability corresponds to the “why” of anaction, namely, the rewards of the action that motivate theperson to pursue it, whereas feasibility refers to the “how”of the action, which involves the costs and constraints as-sociated with the action. Therefore, actions can be charac-terized by varying degrees of desirability and feasibility. Forexample, a backpacking trip in the mountains may be highlydesirable to a person, providing fun and excitement; how-ever, sometimes it may not be very feasible, such as whenextensive travel is involved or when the person lacks thephysical preparation. Similarly, working for a potentiallywildly successful start-up company has high desirability, butif the probability of success is low, the option is also of lowfeasibility (Sagristano, Trope, and Liberman 2002).

In deciding among different actions, people often haveto balance the dual goals of desirability and feasibility. In-terestingly, however, despite the equal role of desirabilityand feasibility in affecting the actual decision outcome, re-cent research has demonstrated differences in people’s psy-chological representation of them. Specifically, theories ofmental representation show that people organize theirknowledge around concepts in a hierarchical structure(Medin 1989; Trope and Liberman 2003), whereby certainattributes are identified as high-level, primary features ofthe concept, whereas others are low-level, secondary infor-mation. High-level attributes are generally essential in de-fining the values and meaning of the concept (e.g., the ge-netic traits of an animal), whereas low-level features relateto incidental details that do not pertain to the core meaningof the concept (e.g., the specific variations in behavior foran animal). In the case of one’s representation of goal-directed action, it is found that because the desirability val-ues of an action define the meaning of the action (why takeaction), they are represented as the high-level, primary di-mension associated with the action. However, although fea-

sibility values describe the specific conditions for the action,they do not identify the meaning of the action and henceare construed as the low-level, subordinate dimension (Lib-erman and Trope 1998; Trope and Liberman 2003). Con-sequently, when thinking about an action, people tend towant to identify the desirability values first before the fea-sibility values (Liberman and Trope 1998; Vallacher andWegner 1987).

This hierarchical construal of desirability and feasibilityvalues in turn affects how people attend to desirability versusfeasibility information. For example, when one is under themind-set to form a high-level view of an event, he/she fo-cuses on the primary constructs in the situation and hencefocuses on desirability; however, when the person wishesto form a close, detailed view of the situation, he/she willattend to the low-level features of feasibility. In particular,research finds temporal distance to be a significant deter-minant of the level of representation sought (Trope and Lib-erman 2000, 2003). When making decisions regarding theimmediate (far) future, people form low-level (high-level)representations and attend to the feasibility (desirability) ofactions. Thus in deciding whether to attend a concert, peoplemay pay much attention to the price of the ticket (feasibility)when the concert is in the near future; however, when theconcert is in the distant future, they focus on how muchthey like the band (desirability) rather than the ticket cost(Liberman and Trope 1998). Similarly, when people arechoosing between financial gambles, the amount of winning(desirability) is emphasized over the probability of winning(feasibility) when the payout is in the distant rather than thenear future (Sagristano et al. 2002).

Importantly, this hierarchical relationship between desir-ability and feasibility goals suggests that the differentialprocessing modes employed in interrupted versus uninter-rupted decision making may also affect the relative focuson desirability versus feasibility information. Specifically,bottom-up processing in uninterrupted decisions focuses onconcrete data, thereby forming a low-level view that attendsto both desirability and feasibility information. In contrast,in top-down processing after an interruption, attention ismore selectively directed toward the primary, high-levelgoal defining the actions. Consequently, focus will shift to-ward the desirability dimension, thereby affecting the en-suing choice. This effect of decision interruption is presentedin figure 1.

This research therefore proposes the following hypothe-sis:

H1: In a decision with a desirability-feasibility trade-off, interruption will increase the preference forthe high-desirability, low-feasibility option, com-pared to if the decision is made without interrup-tion.

Evidence for this hypothesis and its underlying mechanismis provided next in four studies.

DECISION INTERRUPTION 643

FIGURE 1

THEORETICAL MODEL

STUDY 1: CHOOSING A HIKINGDESTINATION

Overview and Design

Study 1 tests the basic premise that an interruption indecision making may lead to a greater preference for de-sirability over feasibility (hypothesis 1). To this end, par-ticipants are asked to make a hypothetical decision betweentwo destinations for a hiking trip. To identify the desirabilityand feasibility features, a pretest ( ) asked partici-N p 39pants two open-ended questions—“What are your maingoals for selecting a hiking destination?” and “What are themain constraints for selecting a hiking destination?”—aimedat revealing the common desirable end states and difficultiesassociated with going hiking. Scenery (62% mentioning)and personal challenge (28%) were named as the main goals,whereas physical ability (51%) and travel (28%) were themain constraints. Scenery and travel are thus chosen as thedesirability and feasibility attributes (personal challenge andability are not used because a positive challenge for somemay be a physical constraint for others). In particular, parkA is described as having scenery with waterfalls and creeks,but it is 70 miles away from home and has limited parking.Park B, however, has scenery with boulders and bushes, butit is 40 miles from home with plenty of parking. A pretestconfirmed that park A is of higher desirability whereas parkB is of higher feasibility. It is predicted that when peopleare interrupted (vs. not) during this decision, they wouldbecome more likely to choose park A. Thus study 1 has aone-factor design in which the presence (vs. absence) ofinterruption is manipulated between subjects.

Procedure

Participants ( , mean age p 34, 26% male) wereN p 128ordinary consumers recruited from all over the countrythrough a Web service to take part in online studies foracademic purposes. The 10-minute session consisted of thecurrent hiking study as well as several other unrelated stud-ies. Participants were told at the beginning of the sessionthat the researchers were interested in people’s behavior inmultitasking environments. Thus during the session theymight be asked to switch between different types of tasks:when they see such instructions, they should simply switchtasks as instructed.

Nested in the unrelated studies, the decision interruptionparadigm consisted of two components: the hiking decisionand a filler task. The key manipulation was that half of theparticipants were asked to switch to the filler task duringthe hiking decision (thus the hiking decision was interrupted)and were later told to resume the decision upon completingthe filler task. In contrast, the other half of the participantsencountered the same filler task before they started the hik-ing decision; thus the hiking decision was not interrupted(see fig. 2 for an illustration of the procedures). Therefore,participants in both the uninterrupted and interruption con-ditions completed the same tasks, but in one case the fillertask preceded the decision whereas in the other case thefiller task interrupted the decision.

The filler task was a “count backward” procedure usedin previous research to keep individuals cognitively occu-pied (Carlyon et al. 2003). In this study, participants weretold to count backward by 7 from 175 to 105, typing downeach step as they go. This task was chosen because it waseasy to perform yet required concentration and thereforekept participants from thinking about any other issues. Theinterruption was inserted in the following manner: partici-

644 JOURNAL OF CONSUMER RESEARCH

FIGURE 2

ILLUSTRATION OF THE DECISION INTERRUPTION PROCEDURE

pants were asked to imagine that they were choosing a des-tination for a hiking trip during the weekend. The optionswere presented on the screen with the scenery and acces-sibility information for each park described in a table. Belowthe table, participants in the uninterrupted condition wereasked, “Which park would you choose?” followed by tworadio buttons on which they could indicate their decision.However, participants in the interruption condition read (un-expectedly), “Which park would you choose? Now pleasestop thinking about this decision for a moment, and switchto the task on the next page” followed by a “continue” buttonthat took them to the next page containing the count back-ward task. After they finished the counting task, they weretaken back to the hiking decision with the same informationpresented as before, along with the headline “Now pleasecome back to the hiking decision.” This time they made thedecision and went on to the next study.

In both conditions, after the participants gave theirchoices, they were asked two pairs of process questionsaimed at examining the focus of attention in each condition:first, “In making the decision, how much did you focus on/emphasize the scenery of the parks?” (combined to form anindex of focus on scenery, ) and then “How muchr p .95did you focus on/emphasize the accessibility of the parks?”(combined to form an index of focus on accessibility,

). In addition, each participant’s time spent on ther p .88decision (in one interval in the uninterrupted condition andtwo intervals in the interruption condition) was recorded bythe computer.

Results

A logistic regression with park choice as the dependentvariable, decision interruption as the independent factor, and

gender and age as covariates revealed no significant effectof the covariates (henceforward, nonsignificant covariateswill not be mentioned) but a significant effect for interrup-tion: when uninterrupted, 65% of the participants chose parkA with better scenery; after an interruption, 84% chose thisoption ( , ).B p 1.14 p p .01

Next, the focus of attention during the decision was ex-amined. There were three possibilities consistent with theproposed shift in focus toward desirability after interruption:(a) increased attention on desirability, (b) decreased atten-tion on feasibility, and (c) both. Results revealed that thesecond was the case. An analysis of covariance with focuson scenery as the dependent variable, interruption as theindependent factor, and gender and age as covariates showedthat interruption did not have a significant effect on theamount of focus given to scenery (Munint p 5.74, Mint p5.97; ). However, interruption did lead to a significantF ! 1decrease in attention to accessibility (Munint p 4.53, Mint p3.98; , ). This result is consistentF(1, 124) p 4.04 p p .05with the proposed switch to a top-down mode of processingafter interruption, whereby attention becomes selectively fo-cused on the primary goal dimensions but the secondarydimensions are overlooked. Therefore, as theorized, an in-terruption changed the relative focus between desirabilityand feasibility; in particular, the locus of the effect is areduced attention to feasibility. Further, adding focus onaccessibility to the original binary logistic regression onchoice showed that with both this term and interruptionincluded in the model, focus on accessibility turned out tobe a significant predictor of choice ( ,B p �1.42 p !

); in contrast, the previously significant effect of in-.0001terruption became nonsignificant ( , ). ThusB p .64 p p .26the reduced focus on accessibility fully mediated the effect

DECISION INTERRUPTION 645

of decision interruption on preference (Baron and Kenny1986).

Finally, I examined the decision time in each condition.When uninterrupted, participants spent on average 28 sec-onds on the decision; when interrupted, participants spent22 seconds prior to the interruption and another 10 secondsupon returning to the decision. The total time did not differsignificantly between conditions (28 vs. 32 seconds; F(1,

, ). Further, when decision time was123) p 1.05 p p .31used as a covariate in the regression, interruption remaineda significant predictor of choice ( , ), butB p 1.13 p p .01time did not have a significant effect ( ,B p �.002 p p

). These results suggest that decision interruption did not.52affect the overall amount of processing people gave to adecision; however, it created a discontinuation in processing,which changed preferences.

Discussion

Study 1 provided initial evidence for the decision inter-ruption effect: when trading off desirability and feasibility,people became more likely to choose the high-desirability,low-feasibility consumption after an interruption. Further,this effect was driven by a reduced focus on the feasibilitydimension.

However, this finding notwithstanding, questions remainregarding the results. Most notable, even though desirabilityand feasibility are contrasted in the situation, an alternativeaccount of the interruption effect may be that after an in-terruption, participants chose on the basis of which attributethey considered to be more important rather than processedaccording to their implicit goal construal. Thus if goal con-strual primacy and subjective importance coincide, the na-ture of the effect is indeed muddled. However, previousresearch in construal level theory shows that goal construallevel and judgment of importance are conceptually distinct,and in many situations they can diverge whereby the fea-sibility dimension is deemed more important (Trope andLiberman 2003). Thus studying such situations can helpdisentangle the two accounts and provide evidence that theshift in preference relies on goal-directed processing. To thisend, study 2 is conducted.

STUDY 2: REWARD VERSUS RISK

Overview and Design

The objective of study 2 is to tease apart the role of goalconstrual and attribute importance and to generalize the de-cision interruption effect to another context, namely, theconflict between risk and reward. Previous research showsthat when one is choosing between an option that has asmall probability for a large reward and another with a largeprobability for a small reward, the level of reward is a de-sirability dimension because it defines the meaning of theaction, whereas the probability of the reward is a feasibilitydimension since it relates to when the reward can be realized.Consequently, when people are under a mind-set to focus

on primary goal dimensions, such as when thinking abouta distant future, they tend to emphasize reward over riskand choose the high-risk option (Sagristano et al. 2002).Therefore, this research proposes that an interruption maysimilarly lead to a focus on the primary goal of reward and,hence, greater risk taking.

H2: In a decision involving risky options, interruptionwill increase the preference for the high-risk,high-reward option.

Also important, despite the primacy in goal construal ofreward compared to risk, reward may not be perceived asmore important than risk. Normatively, both dimensionscontribute equally to the final outcome of the decision. Fur-ther, because of people’s general tendency for risk aversion,risk may even be subjectively perceived as a more importantdimension than reward—a conjecture confirmed in the pre-tests below.

In this study, the risk-reward trade-off is operationalizedin two decisions. In the first, participants are asked to choosebetween two financial gambles. Option A has a 70% chanceof winning $40 (30% chance of not winning anything),whereas option B has a 40% chance of winning $120. Asa conceptual replication, in the second decision, participantsare told they are purchasing a printer and are choosing be-tween two options differing by print quality (reward) andreliability (risk, defined as the chance of malfunction). Bothattributes are presented on a 1–10 scale, where 1 p badand 10 p good. Printer A is lower in risk (print quality p8, reliability p 9), and printer B is higher on reward (printquality p 9, reliability p 8).

A pretest ( ) examined the perception of impor-N p 35tance between reward and risk. When asked “When takingon a gamble [in the above ranges of attribute values], howimportant is the amount of winning?” and “How importantis the probability of winning?” (1 p not at all, 7 p verymuch), a within-subject t-test showed a significant differencewhereby people considered the probability of winning moreimportant than the amount of winning ( ,M p 4.66amount

; , ). Similarly, for print-M p 5.60 t(34) p 3.05 p p .004prob

ers (in the above attribute ranges), people assigned greaterimportance to printer reliability ( ) than to printM p 6.26quality ( ; , ). Thus if afterM p 5.69 t(34) p 2.07 p p .05an interruption people think about attribute importance, theyshould be more likely to choose the low-risk option. How-ever, if attention becomes goal directed, they would be morelikely to choose the high-risk option. Therefore, study 2 hasa one-factor (interruption: absent, present) design with twowithin-subject replications.

Procedure

Participants ( , mean age p 21, 46% male) wereN p 99college students at Stanford University. They were paid $5to participate in a study on “multitasking behavior” in acomputer lab. The session consisted of the two target de-cisions and other unrelated tasks. The interruption paradigm

646 JOURNAL OF CONSUMER RESEARCH

for each decision was similar to that used in study 1: afterparticipants were given the information about the decision,half of them received an instruction to switch tasks and laterto resume the decision. One departure from study 1 washow the interruption was introduced. One potential concernwith the study 1 procedure was that because the interruptioninstruction appeared on the same page as the decision de-scription (at the end of the description), there is a chanceparticipants in the interruption condition may have first no-ticed this instruction even before starting the decision,thereby making the interruption expected rather than un-expected. This expectation for interruption in turn may haveplayed a role in the effect. In study 2, this concern is ad-dressed by controlling the timing of the introduction of in-formation and interruption. Specifically, information for adecision was built on the screen gradually (a new line wasadded every 5 seconds on the basis of a pretest of readingspeed). After the last sentence (“Which option would youchoose?”) appeared, those in the uninterrupted group werealso given the buttons they could click for their choice, andthey could take as long as they liked to indicate an answer.However, those in the interruption condition were auto-matically taken to a new screen that instructed them to workon a filler task (counting backward); after the filler task, thetarget decision automatically reappeared and participantstook their time to finish the decision. Thus in study 2, allparticipants spent an equal amount of time learning aboutthe options before an interruption was introduced for halfof them. However, both groups took as long as they wishedto make a decision. The interruption manipulation was coun-terbalanced within subjects such that if the financial decisionwas interrupted for a participant, the printer decision wasnot, and vice versa. The financial decision always precededthe printer decision, but they were spaced apart by unrelatedstudies. The decision time was recorded by the computer.

Results

Results in both the financial and printer decisions weresupportive of hypothesis 2. A logistic regression with fi-nancial choice as the dependent variable, interruption as theindependent factor, and age, gender, and ethnicity as co-variates revealed a significant effect for interruption (B p

, ): choice of the high-risk gamble increased from.92 p p .0448% to 71% when the decision was interrupted. Similarly,choice of the high–print quality, low-reliability printer in-creased from 32% to 53% when interrupted ( ,B p 1.13

).p p .04Next, the recording of decision time was analyzed. In

corroboration of study 1 results, both groups spent a similaramount of time in reaching a decision (time spent after thepoint of interruption: financial decision: Munint p 8.3 sec-onds, Mint p 7.4 seconds; , ; printer decision:F ! 1 p p .71Munint p 7.1 seconds, Mint p 6.8 seconds; , ).F ! 1 p p .83Further, in each decision, when decision time was added asa covariate in predicting choice, interruption remained asignificant factor ( ), but decision time was not ap ! .04significant predictor ( ).p 1 .30

Discussion

Despite the fact that risk was perceived to be a moreimportant attribute than reward, across two decision con-texts, decision interruption led to greater choice of thehigh-risk option. Therefore, goal construal level rather thanattribute importance likely underlies the decision afterinterruption.

Thus the first two studies provided converging supportfor the effect of decision interruption on a preference fordesirability. Further, study 1 showed evidence that a shiftin focus mediated the effect. After an interruption, peopletended to selectively attend to the desirability attribute butdid not focus as much on the lower-level dimension of fea-sibility. However, an important question still remains re-garding the mechanism of the effect, namely, what is theimpetus for this shift in focus? It is posited that this shiftoccurs as a result of a change in the person’s processingmind-set: from bottom-up data driven to top-down goal di-rected. The next study seeks to provide evidence for thisprocess. Specifically, if the interruption effect relies on adeparture from the bottom-up mode toward a top-downmode after the interruption, a manipulation that reintroducesthe bottom-up mode of processing when the person resumesfrom interruption may eliminate the interruption effect. Inother words, if after the interruption people are preventedfrom switching to a top-down, goal-directed mode as theynaturally would have been, the interruption effect would be“undone.” Study 3 tests this possibility.

STUDY 3: ELIMINATING THE DECISIONINTERRUPTION EFFECT

Overview and Design

The objective of study 3 is to examine whether explicitlyinstructing people to adopt a bottom-up, data-driven pro-cessing mode after an interruption would eliminate the de-cision interruption effect, thereby providing evidence for thechange in processing mode underlying the effect. To thisend, this study looks at another case of a desirability-feasibility trade-off, namely, price-quality conflicts in con-sumer purchases. When faced with a decision between ahigh-quality, high-price (HQHP) and a low-quality, low-price (LQLP) option, consumers are often sensitive to thefeasibility dimension of price and hence choose to sacrificedesirability (quality). However, if an interruption in the de-cision reduces the focus on feasibility, it may lead to greaterchoice of the HQHP option.

H3: In a purchase decision involving a price-qualitytrade-off, interruption will increase the preferencefor the high-quality, high-price option.

In this study, participants are asked to imagine that theyare purchasing a new set of bed linen for themselves. Spe-cifically, they can choose between a high-quality sheet setwith 350-count premium cotton, costing $79, and anotherone with 250-count standard cotton, costing $39. Half of

DECISION INTERRUPTION 647

the participants are interrupted during this decision. Impor-tantly, in addition to the interruption manipulation, a secondfactor is introduced; namely, half of the participants aregiven an instruction on how to process the information: “Forthis decision, please first form a concrete, detailed view ofthe information and then make the decision.” Thus this in-struction directs participants to focus on learning the externalinformation by following its specific details, thereby pro-cessing the information in a bottom-up manner. A pretestshowed that indeed this instruction creates a bottom-up focusin processing: 42 participants were shown the bed linendecision with this instruction and were asked, on a 5-pointscale (1 p not at all, 5 p very much), “To what extentdoes the instruction ask you to (1) focus on each piece ofinformation given to you closely” and to check against top-down processing (and undifferentiated responding) and “(2)focus on the information that’s more closely linked to yourgoals for the decision.” A within-subject t-test showed thatindeed participants understood the instruction to have a bot-tom-up focus on data ( ) and to be neutral onM p 4.261

having a top-down focus on data ( ; a significantM p 2.902

difference between the two items, ,t(41) p 5.64 p !

)..0001When this instruction is coupled with the uninterrupted

condition, it is given up-front at the beginning of the de-cision. When it is coupled with the interruption condition,it is given upon resuming the decision (but not before theinterruption). Upon resuming, participants read, “Nowplease come back to the previous decision. In particular,please first form a concrete, detailed view of the information,and then make the decision.” Therefore, in the interruption-with-instruction condition, participants process as usual be-fore the interruption; but after the interruption, they areforced to process in a bottom-up, data-driven mode (again)rather than being able to turn to a top-down, goal-directedmode in reprising the decision. This intervention thereforeeliminates the effect of the interruption.

H4: The effect of decision interruption is eliminatedif after an interruption people are induced to stillrely on a bottom-up mode of processing.

Thus study 3 has a 2 (interruption: absent vs. present) #2 (detail-focus instruction: absent vs. present) design. I pre-dict an interaction effect between interruption and detail-focus instruction. When the detail-focus instruction is ab-sent, interruption will increase the preference for the HQHPoption, supporting hypothesis 3; however, the interruptioneffect will be eliminated when the detail-focus instructionis given (comparing the interruption-with-instruction con-dition to either the uninterrupted-with-instruction conditionor the regular uninterrupted condition). As further support,I also predict that the uninterrupted-with-instruction con-dition will be similar to the regular uninterrupted condition,consistent with the theory that when uninterrupted, peopleprocess with a bottom-up data focus by default, regardlessof whether an explicit instruction is given.

Of note, this predicted elimination of the interruption ef-

fect may also help to rule out an additional alternative ex-planation for the decision interruption effect. Namely, theincreased preference for the high-desirability option after aninterruption may be due to an increase in the person’s ref-erence level for goal achievement (Kahneman and Tversky1979; Novemsky and Dhar 2005). That is, the initial con-sideration of a highly desirable option in the choice set mayhave led the person to adapt to a higher reference point fordesirability after the interruption. Consequently, the high-desirability option becomes more attractive because the low-desirability option has now fallen below the new reference.However, if this reference-update mechanism were at play,the detail-focus instruction would not be able to eliminatethe interruption effect because people would still choose onthe basis of the increased reference.

Procedure

Participants ( , mean age p 32, 35% male) wereN p 167ordinary consumers recruited from all over the countrythrough a Web survey service as in study 1. The 10-minutesession consisted of the current study as well as several otherunrelated studies. The interruption procedure was similar tothat used in study 1. For greater generalizability, the fillertask in this study used a different exercise than previousstudies, namely, word generation. Specifically, participantswere asked to generate five words starting with the letterN, five words starting with D, and five words starting withK. After participants completed the filler task and bed linenchoice, they went on to other unrelated portions of thesession.

Results

A logistic regression with choice of the HQHP option asthe dependent variable, the factors of detail-focus instructionand interruption and their interaction term as the independentvariables, and gender and age as covariates revealed nosignificant main effect for interruption ( ) and a mar-p p .67ginally significant effect for detail-focus instruction (B p

, ; Mw/o instr p 34%, Mw/instr p 26%). Importantly,.96 p p .06however, as predicted, there was a significant interactioneffect for detail-focus instruction and interruption (B p�1.45, ). The likelihood of purchasing the HQHPp p .05option in each condition is graphed in figure 3. Plannedcontrasts were conducted next.

When no instruction for detail focus was given, interrup-tion led to greater choice of the HQHP option (the premiumcotton sheets), supporting hypothesis 3 ( ,M p 20%unint

; , ). However, when the2M p 47% x (1) p 7.46 p p .01int

detail-focus instruction was given, interruption did not havean effect on preferences (Munint w/instr p 28%, Mint w/instr p24%; ). The interruption-with-instruction condition2x ! 1was also not different from the regular uninterrupted con-dition ( ), suggesting that the effect of interruption was2x ! 1completely “undone” by the instruction (hypothesis 4). Ad-ditionally, as predicted, the regular uninterrupted conditionwas not different from the uninterrupted-with-instruction

648 JOURNAL OF CONSUMER RESEARCH

FIGURE 3

STUDY 3 RESULTS

condition ( ), supporting the theory that those in the2x ! 1uninterrupted condition already processed in a bottom-up,data-driven mode, making the explicit instruction immate-rial.

Discussion

Consistent with hypothesis 3, study 3 found that an in-terruption increased the preference for the HQHP option ina price-quality decision. However, as posited in hypothesis4, this effect was eliminated when the interruption was ac-companied by an instruction to still adopt a bottom-up focuson data when resuming the decision. These results thereforesupport the theorized mechanism underlying the interruptioneffect, namely, a departure from a bottom-up, data-drivento a top-down, goal-directed mode in processing. Further,study 3 results are not amenable to a reference-update ex-planation: if goal reference were changed, an instruction tofocus on data would not eliminate the change in preference.

In the next study, I consider an interesting implication ofthe decision interruption effect, thereby bringing additionalsupport for the proposed mechanism. Specifically, if, as the-orized and demonstrated in study 1, an interruption de-creases the focus on the secondary goal dimension of price,then people may become less sensitive to varying price lev-els when decisions are interrupted. Thus study 4 examinesthe effect of decision interruption on price sensitivity.

STUDY 4: DECISION INTERRUPTION ANDPRICE SENSITIVITY

Overview and Design

The objective of study 4 is to examine whether after aninterruption people exhibit less price sensitivity. To test thisproposition, participants are asked to consider a rental car

decision when they are on vacation in Florida. Specifically,they can either rent a regular midsize sedan for $50 per dayor upgrade to a convertible for a higher price. In one con-dition, the upgrade costs $10 extra per day, whereas in asecond condition, the upgrade costs $20 extra per day. Fur-ther, half of the participants are interrupted when makingthe decision but the other half are not. It is predicted thatbecause of the reduced attention to feasibility due to inter-ruption, those in the interrupted condition will become lesssensitive to the level of extra cost than those who are notinterrupted. Therefore, in the interruption condition, I expectthere to be relatively little change in the likelihood of rentingthe upgraded car whether the surcharge for the upgrade is$10 or $20; in contrast, in the uninterrupted condition, be-cause people are focused on price, there will be a largedifference in response to a high versus low price for theupgrade.

H5: In a price-quality decision, interruption will de-crease price sensitivity.

Further, the change in price sensitivity would imply amoderating effect of price level on the interruption effect.Specifically, because of decreased attention to feasibility, aninterruption will generally shift preferences toward theHQHP option. However, this effect should be particularlypronounced when the extra price for higher quality is high.Interestingly, the effect may be muted, or even reversed,when the price for high quality is very low compared to theconsumer’s expectation. Specifically, as theorized, consum-ers processing information in a bottom-up manner respondto each salient feature in the data. Thus if a price for theHQHP option is much below expectation, such a surpriseis likely to produce a large favorable response; in fact, itmay even become the reason to purchase this option. How-ever, interrupted individuals process in a top-down manner;consequently, they are focused on the primary goal of de-sirability (what it means to have a convertible) rather thanthe implications of a particular price point. Thus they areless likely to take note of the “good deal” as a reason foran upgrade. Consequently, the use of good price as an addedreason for an upgrade might result in a reversal of the in-terruption effect whereby purchase of the HQHP option isgreater in the uninterrupted condition. In the current study,a pretest shows that people’s price expectation for the up-grade is $35; thus while $20 may be somewhat attractive,$10 for the upgrade is indeed a very low price. Therefore,I predict that an interruption will lead to more choice of theupgrade compared to the uninterrupted condition, but onlywhen the price of the upgrade is relatively high at $20; whenthe price is very low at $10, the effect is muted or evenreversed such that the uninterrupted group may be morelikely to upgrade.

Therefore, study 4 has a 2 (interruption: absent vs. pres-ent) # 2 (price for upgrade: high vs. low) design. I predictan interaction effect between interruption and price levelsuch that the interruption effect (i.e., increased preferencefor an upgrade) will be strong when the price for an upgrade

DECISION INTERRUPTION 649

FIGURE 4

STUDY 4 RESULTS

is high, but the effect may be eliminated or reversed whenthe price is low. In addition, price sensitivity will be lowerwhen the decision is interrupted.

Procedure

Participants ( , mean age p 32, 27% male) wereN p 262ordinary consumers recruited from all over the countrythrough a Web survey service as in study 1. The 10-minutesession consisted of the current study as well as several otherunrelated studies. The interruption procedure was similar tothat of study 3. Half of the participants were assigned tothe interruption condition in which they were asked to switchto the filler task during the rental car decision, whereas theother half completed the corresponding filler task before theystarted the rental car decision. The filler task was again wordgeneration. After completing the filler and car choices, par-ticipants went on to unrelated studies.

Results

A logistic regression with choice of the HQHP option asthe dependent variable, the factors of price and interruptionand their interaction term as the independent variables, andgender and age as covariates revealed no significant maineffects for interruption ( ) or price level ( ).p p .11 p p .97However, as predicted, there was a significant interactioneffect for price and interruption ( , ). TheB p 1.00 p p .05likelihood of purchasing the HQHP option in each conditionis graphed in figure 4. To understand the interaction effect,two contrasts—one at each price level—were conductedcomparing the uninterrupted and interruption conditions. Itis found that when the price for the rental car upgrade washigh at $20, consistent with study 3, those in the interruptioncondition were significantly more likely to purchase the up-grade (Munint p .29, Mint p .42; , ).2x (1) p 5.42 p ! .025However, when the price of the upgrade was low at $10,interrupted participants were actually directionally lesslikely to purchase the upgrade than the uninterrupted group(Munint p .53, Mint p .43; , ). Therefore,2x (1) p 2.66 p ! .15as predicted, an interruption led to greater choice of theHQHP option, but only when the price differential was rel-atively large; the effect was directionally reversed when theprice for the upgrade was very small.

Further, to provide direct evidence for price sensitivity, asecond pair of contrasts were conducted. In the uninterruptedcondition, price had a significant effect on the likelihood ofchoosing the HQHP option: when the price was low, peoplewere very willing to choose it ; when the price was high,people were not willing to upgrade (M$10 p .53, M$20 p.29; , ). In contrast, when the deci-2x (1) p 16.29 p ! .005sion was interrupted, people’s choices were not significantlyinfluenced by whether the price was high or low (M$10 p.43, M$20 p .42; ). Thus hypothesis 5 was supported.2x ! 1

Discussion

Consistent with study 3, study 4 found that in a price-quality trade-off, interruption increased the preference for

the HQHP option. However, this effect was moderated bythe price level: it occurred only when the additional cost forhigher quality was relatively high, but not when the costwas low. This pattern was due to a decreased sensitivity toprice when the decision is interrupted. Thus study 4 providedfurther evidence for the selective focus on desirability andreduced attention to feasibility after an interruption.

GENERAL DISCUSSIONThis research examines the effect of interrupting a de-

cision on preferences. It is proposed that decision interrup-tion can cause the person’s information processing to changefrom a bottom-up, data-driven to a top-down, goal-directedmode, resulting in a greater preference for the primary goaldimension of desirability over the secondary goal of fea-sibility in options. Evidence for this effect was found inseveral decision contexts. For example, in the choice of ahiking destination, an interruption increased the choice of apark with good scenery but poorer accessibility. Similarly,in decisions with risk, interruption resulted in more choicesof the high-risk, high-reward option, even though risk isconsidered a more important attribute than reward. Twomore studies on price-quality trade-offs showed that an in-terruption can also increase the purchase of a high-quality,high-price option by reducing price sensitivity. Process in-sights showed that the effect of interruption was driven bya reduced focus on feasibility, due to a shift in processingfrom a bottom-up, data-driven to a top-down, goal-directedmode.

By focusing on the phenomenon of decision interruption,this research contributes to the theory of decision makingand preference construction in important ways. First, thisresearch highlights the distinct stages people may go throughin making a decision and the dynamic changes that mayoccur during extended decision-making processes. In par-ticular, when a decision is interrupted, a new stage of in-formation processing is introduced as a result of this reset;namely, a distinct stage of reconstructing the decision occursand leads to a more top-down view of the information. More

650 JOURNAL OF CONSUMER RESEARCH

broadly, the notion of “mental resets” warrants deeper re-search. One interesting direction to explore is the metacog-nitive states involved in such resets. For example, the in-terruption effect may rely on a metacognitive recognitionthat “this is a problem I have previously looked at, so nowI don’t have to process it bottom-up again”; however, an-other possibility is that the reset is automatically promptedby a “stop-go-again” sequence. One way to tease this apartmay be to introduce new information after the interruption.If the metacognitive recognition is at play, the notice of newinformation may cause people to return to a bottom-up mind-set even after interruption. However, if the reset in mind-set occurs directly as a result of a break, a top-down processwill still take place after interruption.

A second area of contribution by this research regardsmultistage decision making. Current studies complement arecent stream of works showing that the outcomes of de-cisions may be changed when decisions are broken intomultiple stages. For example, research on the “screeningeffect” (Chakravarti, Janiszewski, and Ulkumen 2006)shows that asking people to first screen a set of optionsusing a certain criterion (e.g., must meet a minimum levelof picture resolution in digital cameras) can lead to reducedweighting of this attribute in the subsequent stage of choos-ing among the options that have passed the initial screening.In another line of research by Maimaran and Simonson(2007), it is found that first asking people to choose a cat-egory and then choose within the category can lead to bolderchoices (e.g., choosing an extreme option). However, unlikethese studies and the literature on sequential choice (Dharand Simonson 1999; Drolet 2002), this research makes anovel contribution by suggesting that even without a priorchoice, the mere introduction of a discontinuation in deci-sion making may affect people’s preferences. Further, theeffect occurs through a change in general processing ori-entation rather than changes in the use of specific contentor decision rules.

Another key distinction made salient by the current stud-ies is the internal versus external focus of attention in theconstruction of preferences. Whereas involuntary attentionis directed at stimuli that are perceptually concrete and com-pelling, and thus externally driven, voluntary attention isinternally guided toward information pertaining to one’s pri-mary goal dimensions. Thus the switch from external tointernal control of attention due to interruption may lead toa broader set of consequences. For example, interruptionmay affect how people respond to contextual information.Under an external focus, people may be more susceptibleto contextual features that are perceptually salient; however,under an internal focus, people may be more prone to useinternal feelings or rules for deciding. If this were the case,one might find interruption to reduce the influence of certaincontextual cues, such as attraction and asymmetric domi-nance (Huber and Puto 1983; Simonson and Tversky 1992)and framing of references (Kahneman and Tversky 1979).However, interruption may not reduce, and could potentiallyincrease, context effects that depend on internal feelings,

such as the feeling of conflict, hence increasing the com-promise effect (Simonson and Tversky 1992). More broadly,the distinction between internal versus external focus in pro-cessing also speaks to recent research on the depletion ofone’s internal control in decision making: the ability for anindividual to exert internal control may be a limited re-source; when this resource is depleted, people exhibit greaterdependence on external context (Pocheptsova et al. 2007).Therefore, an interesting question is whether an interruptionmay counter the effect of ego depletion in certain situations,not only by creating a restorative break but also by intro-ducing a natural tendency to engage in self-directed pro-cessing after interruption. These broader implications ofchanges in processing due to interruption merit further in-vestigation.

Limitations and Future Research

This research also has a number of limitations that maybe addressed in the future. First, although evidence is foundfor the change in processing mode as the mechanism un-derlying the decision interruption effect, it is also possiblethat other mechanisms are at play. One intriguing possibilityis that different systems of cognition may be involved pre-versus postinterruption, or even during interruption. For ex-ample, research by Dijksterhuis et al. (2006) suggests thatpeople may engage in nonconscious processing even whentheir (conscious) attention is diverted to focus on other tasks.Their research shows that after a period of diversion, thequality of people’s decisions is improved in that the deci-sions conform better to normative standards, and people aremore satisfied with their choices. Thus if nonconscious pro-cessing also puts greater weight on desirability over feasi-bility, it may contribute to the interruption effect.

Another possibility is that after an interruption, peopledifferentially engage in system I versus system II processing(Sloman 1996). Research suggests that people may possesstwo systems of cognition: system I processing is said to be“intuitive” in that it involves the use of well-rehearsed pat-tern matching and associations, whereas system II is a slowerprocess that relies on reasoning and computations. Thus aninteresting question is whether the focus on desirability afteran interruption relies on system I (intuition) or system II(reasoning), which also has implications for whether the shiftin focus is conscious or automatic. Further, neural imagingevidence suggests that distinct neural mechanisms are in-volved in the anticipation of gains and losses (Kuhnen andKnutson 2005). To the extent that desirability usually em-bodies gains whereas feasibility involves losses, it is worth-while to examine whether the pattern of neural activationchanges after an interruption, in particular, whether the an-ticipation of gains becomes more sensitive whereas the an-ticipation of losses becomes desensitized.

A second limitation of this research is that the presentstudies focused on relatively simple decisions involvingtrade-offs between two attributes. More research is neededto investigate the effect of interruption in more complexdecision problems involving more options and richer infor-

DECISION INTERRUPTION 651

mation. It appears that two possibilities exist: the effect ofan interruption may be stronger in complex situations be-cause there is potentially a greater difference between a top-down, big-picture view and a bottom-up, detailed view;however, it is also possible that the interruption effect mightbe weakened because in such complex situations it may bedifficult to decide on the basis of a bottom-up view. Thuseven without interruption, people spontaneously try to ab-stract a top-down view of the situation in order to make adecision (Coupey 1994; Johnson 1984). Further, in certainsituations it is also possible that people may start with atop-down process but later switch to a bottom-up process.Thus the effect of an interruption may change dependingon the nature of the default process.

Third, this research studied the effect of relatively short,simple, and neutral types of interruptions (e.g., countingbackward, generating words). Therefore, the effect of in-terruption found in this research can be seen as a “mereinterruption effect” that relies on the “restart” in discontin-uous decisions. However, more research is needed to ex-amine the effect of other types of interruptions and theirunderlying mechanisms. For example, research may look atinterruptions of different durations and interruptions thataffect people’s cognitive and affective resources.

Further, future research might look at people’s goal struc-tures more broadly. For example, research suggests that con-sumer goals are organized in a hierarchical manner rangingfrom high-level life goals to low-level projects (Huffman,Ratneshwar, and Mick 2000). Thus it would be interestingto examine whether interruptions may lead to greater pref-erence for pursuing high-level rather than low-level con-sumption goals as well as different kinds of goals, such ashedonic versus utilitarian goals. In particular, a utilitarianattribute may be viewed as a feasibility goal in itself (fa-cilitating other goals but having no value in and of itself)or merely a constraint that needs to be met; therefore, theeffect of decision interruption may be different for purelyutilitarian consumption.

Finally, it may be important to consider the effect ofinterruptions on other cognitive and affective processes suchas sensory experiences (Shiv and Nowlis 2004), creativityand artistic expressions, as well as the effect of interruptionsat a macro level, for example, whether a multitasking life-style may ultimately affect people’s general level of successand life satisfaction (Kahneman 1999; Schwarz and Strack1999).

Managerial Implications

In addition to its theoretical interest, this research alsohas important managerial implications. The dichotomy ofdesirability and feasibility is at the center of many everydaydecisions. For the consumer, one often needs to trade offquality and affordability. For the manager, business oppor-tunities can often be characterized by their potential payoffand chance of success. This research shows that the deci-sions of consumers and managers may be influenced by thedynamic course of decision making. For marketers, this re-

search has implications for designing shopping procedures.For example, the use of interrupters such as pop-up ads orsimply asking a consumer to wait during a decision mayhave a significant effect on what people eventually purchaseand their price sensitivity. Similarly, breaking a decisioninto multiple stages, such as an initial stage of learning anda later stage of deciding, may lead to different choices thana single-stage decision. Additionally, depending on whetherthe shopping experience is generally continuous or discon-tinuous, marketers may decide whether to use a “qualitylure” (e.g., enhanced features) or a “price lure” (“Sale!”) asa promotion strategy. In particular, a low-price promotionmay lose some of its effectiveness if the decision is sus-pended since people no longer focus on price after a breakin the decision.

REFERENCES

Bagozzi, Richard P. and Utpal M. Dholakia (1999), “Goal Settingand Goal Striving in Consumer Behavior,” Journal of Mar-keting, 63 (4), 19–32.

Baron, Reuben M. and David A. Kenny (1986), “The Moderator-Mediator Variable Distinction in Social Psychological Re-search: Conceptual, Strategic, and Statistical Considerations,”Journal of Personality and Social Psychology, 51 (6),1173–82.

Berlyne, Daniel E. (1960), Conflict, Arousal and Curiosity, NewYork: McGraw-Hill.

Bettman, James R. (1979), An Information Processing Theory ofConsumer Choice, Reading, MA: Addison-Wesley.

Bettman, James R. and Pradeep Kakkar (1977), “Effects of Infor-mation Presentation Format on Consumer Information Ac-quisition Strategies,” Journal of Consumer Research, 3 (4),233–40.

Bettman, James R., Mary Frances Luce, and John W. Payne (1998),“Constructive Consumer Choice Processes,” Journal of Con-sumer Research, 25 (December), 187–217.

Butterfield, Earl C. (1964), “The Interruption of Tasks: Method-ological, Factual, and Theoretical Issues,” Psychological Bul-letin, 62 (5), 309–22.

Carlyon, Robert P., Christopher J. Plack, Deborah A. Fantini, andRhodri Cusack (2003), “Cross-Modal and Non-sensory Influ-ences on Auditory Streaming,” Perception, 32 (11), 1393–1402.

Chakravarti, Amitav, Chris Janiszewski, and Gulden Ulkumen(2006), “The Neglect of Prescreening Information,” Journalof Marketing Research, 43 (4), 642–53.

Coupey, Eloise (1994), “Restructuring: Constructive Processing ofInformation Displays in Consumer Choice,” Journal of Con-sumer Research, 21 (June), 83–99.

Dhar, Ravi and Itamar Simonson (1999), “Making ComplementaryChoices in Consumption Episodes: Highlighting versus Bal-ancing,” Journal of Marketing Research, 36 (February),29–44.

Dijksterhuis, Ap, Maarten W. Bos, Loran F. Nordgren, and RickB. van Baaren (2006), “On Making the Right Choice: TheDeliberation-without-Attention Effect,” Science, 311 (5763),1005–7.

Drolet, Aimee (2002), “Inherent Rule Variability in ConsumerChoice: Changing Rules for Change’s Sake,” Journal of Con-sumer Research, 29 (December), 293–305.

652 JOURNAL OF CONSUMER RESEARCH

Goschke, Thomas and Julius Kuhl (1993), “Representation of In-tentions: Persisting Activation in Memory,” Journal of Ex-perimental Psychology: Learning, Memory, and Cognition,19 (5), 1211–26.

Hauser, John R. (1986), “Agendas and Consumer Choice,” Journalof Marketing Research, 23 (3), 199–212.

Huber, Joel and Christopher Puto (1983), “Market Boundaries andProduct Choice: Illustrating Attraction and Substitution Ef-fects,” Journal of Consumer Research, 10 (June), 31–44.

Huffman, Cynthia, S. Ratneshwar, and David Glen Mick (2000),“Consumer Goal Structures and Goal Determination Pro-cesses: An Integrative Framework,” in The Why of Con-sumption: Contemporary Perspectives on Consumer Motives,Goals, and Desires, ed. S. Ratneshwar, David Glen Mick, andCynthia Huffman, London: Routledge, 9–35.

Johnson, Michael D. (1984), “Consumer Choice Strategies forComparing Noncomparable Alternatives,” Journal of Con-sumer Research, 11 (December), 741–53.

Kahneman, Daniel (1973), Attention and Effort, Englewood Cliffs,NJ: Prentice-Hall.

——— (1999), “Objective Happiness,” in Well-Being: The Foun-dations of Hedonistic Psychology, ed. Daniel Kahneman, EdDiener, and Norbert Schwartz, New York: Sage, 3–25.

Kahneman, Daniel and Amos Tversky (1979), “Prospect Theory:An Analysis of Decisions under Risk,” Econometrica, 47(February), 313–27.

Kivetz, Ran, Oleg Urminsky, and Yuhuang Zheng (2006), “TheGoal-Gradient Hypothesis Resurrected: Purchase Accelera-tion, Illusionary Goal Progress, and Customer Retention,”Journal of Marketing Research, 43 (February), 39–58.

Kruglanski, Arie (1996), “Goals as Knowledge Structures,” in ThePsychology of Action: Linking Cognition and Motivation toBehavior, ed. Peter M. Gollwitzer and John A. Bargh, NewYork: Guilford, 599–618.

Kuhnen, Camelia and Brian Knutson (2005), “The Neural Basisof Financial Risk Taking,” Neuron, 47 (September), 763–70.

Liberman, Nira and Yaacov Trope (1998), “The Role of Feasibilityand Desirability Considerations in Near and Distant FutureDecisions: A Test of Temporal Construal Theory,” Journalof Personality and Social Psychology, 75 (1), 5–18.

Maimaran, Michal and Itamar Simonson (2007), “The Effect ofChoosing to Make a Choice on Consumers’ Choices: TheMaking of Bold Decisions,” working paper, Marketing De-partment, Stanford University.

Mantyla, Timo (1996), “Activating Actions and Interrupting In-tentions: Mechanisms of Retrieval Sensitization in Prospec-tive Memory,” in Prospective Memory: Theory and Appli-cations, ed. Maria Brandimonte, Gilles O. Einstein, and MarkA. McDaniel, Mahwah, NJ: Erlbaum, 93–113.

Marsh, Richard L., Jason L. Hicks, and Martin L. Bink (1998),“Activation of Completed, Uncompleted, and Partially Com-pleted Intentions,” Journal of Experimental Psychology:Learning, Memory, and Cognition, 24 (2), 350–61.

Medin, Douglas L. (1989), “Concepts and Conceptual Structure,”American Psychologist, 44 (12), 1469–81.

Novemsky, Nathan and Ravi Dhar (2005), “Goal Fulfillment andGoal Targets in Sequential Choice,” Journal of ConsumerResearch, 32 (December), 396–404.

Nunes, Joseph C. and Dreze, Xavier (2006), “The Endowed Prog-ress Effect: How Artificial Advancement Increases Effort,”Journal of Consumer Research, 32 (March), 504–12.

Park, C. Whan and Daniel C. Smith (1989), “Product-LevelChoice: A Top-Down or Bottom-Up Process?” Journal ofConsumer Research, 16 (December), 289–99.

Payne, John W. and James R. Bettman (2004), “Walking with theScarecrow: The Information-Processing Approach to DecisionResearch,” in Blackwell Handbook of Judgment and DecisionMaking, ed. Nigel Harvey and Derek J. Koehler, Oxford:Blackwell, 110–32.

Pocheptsova, Anastasiya, On Amir, Ravi Dhar, and Roy F. Bau-meister (2007), “Deciding without Resources: PsychologicalDepletion and Choice in Context,” working paper, School ofManagement, Yale University.

Sagristano, Michael D., Yaacov Trope, and Nira Liberman (2002),“Time-Dependent Gambling: Odds Now, Money Later,” Jour-nal of Experimental Psychology: General, 131 (September),364–76.

Savitsky, Kenneth, Victoria Husted Medvec, and Thomas Gilovich(1997), “Remembering and Regretting: The Zeigarnik Effectand the Cognitive Availability of Regrettable Actions andInactions,” Personality and Social Psychology Bulletin, 23(3), 248–57.

Schwarz, Norbert and Fritz Strack (1999), “Reports of SubjectiveWell-Being: Judgmental Processes and Their MethodologicalImplications,” in Well-Being: The Foundations of HedonisticPsychology, ed. Daniel Kahneman, Ed Diener, and NorbertSchwartz, New York: Sage, 61–84.

Shiv, Baba and Steve Nowlis (2004), “Effects of Distraction WhileTasting a Food Sample: The Interplay of Informational andAffective Components in Subsequent Choice,” Journal ofConsumer Research, 31 (December), 599–608.

Simonson, Itamar and Amos Tversky (1992), “Choice in Context:Tradeoff Contrast and Extremeness Aversion,” Journal ofMarketing Research, 29 (3), 281–95.

Sloman, Steven A. (1996), “The Empirical Case for Two Systemsof Reasoning,” Psychological Bulletin, 119 (1), 3–22.

Sujan, Mita (1985), “Consumer Knowledge: Effects on EvaluationStrategies Mediating Consumer Judgments,” Journal of Con-sumer Research, 12 (1), 31–46.

Trope, Yaacov and Nira Liberman (2000), “Temporal Construaland Time-Dependent Changes in Preferences,” Journal ofPersonality and Social Psychology, 79 (6), 876–89.

——— (2003), “Temporal Construal,” Psychological Review, 110(3), 403–21.

Vallacher, Robin R. and Daniel M. Wegner (1987), “What DoPeople Think They’re Doing? Action Identification and Hu-man Behavior,” Psychological Review, 94 (1), 3–15.

——— (1989), “Levels of Personal Agency: Individual Variationin Action Identification,” Journal of Personality and SocialPsychology, 57 (4), 660–71.

Xia, Lan and D. Sudharshan (2002), “Effects of Interruptions onConsumer Online Decision Processes,” Journal of ConsumerPsychology, 12 (3), 265–80.

Zeigarnik, Bluma (1927), “Das Behalten Erledigter und Unerle-digter Handlungen,” Psychologische Forschung, 9, 1–85.