Online Impulse Purchases 1

Electron Commerce Res (2007) 7: 367–379DOI 10.1007/s10660-007-9011-8

Factors influencing impulse buying during an onlinepurchase

Scott A. Jeffrey · Rebecca Hodge

Published online: 24 October 2007© Springer Science+Business Media, LLC 2007

Abstract Using actual purchasing behavior by visitors to a High School Reunionweb store, this study examines the factors that lead to an increased willingness by on-line consumers to purchase impulse items. Consistent with mental accounting and thepsychophysics of prices, we find that people’s purchase of the impulse item increaseswith the total amount spent on other items. We also find that linking a US $1 donationto the impulse item, thereby providing a reason to purchase, increases the frequencyof the impulse purchase.

Keywords Impulse buying · E-commerce · Reason based choice · Mentalaccounting

Between 1945 and 1959 impulse purchases, those purchases which a shopper makesbut did not plan in advance, rose from 38.2 percent to 50.9 percent of the total pur-chases in supermarkets [1]. In the late 1970s researchers found that impulse purchasesaccounted for between 27 and 62 percent of purchases in department stores [2]. Morerecently, Annie Seeley, a Food Commission nutritionist stated that “seventy percentof confectionary is bought on impulse” [3, p. 23]. A more extreme result was foundby the POPAI (point of purchase industry body) which indicated that 75 percent ofbuying decisions are made in-store [4]. Since a large portion of spending can be cat-egorized as unplanned or impulse, understanding the psychological drivers of thisbehavior is of critical importance.

S.A. Jeffrey (�)Department of Management Sciences, University of Waterloo, 200 University Ave. West, Waterloo,ON N2L 3G1, Canadae-mail: [email protected]

R. HodgeE-XYN Web Solutions, P.O. Box 1042, Guelph, ON N1H 6N1, Canadae-mail: [email protected]

368 S.A. Jeffrey, R. Hodge

Previous research on impulse purchasing has led to improvements in point-of-saledisplays at the checkout, better location of products on shelves, and an increase inunderstanding of product packaging and bundling to appeal to the impulse drive.While there has been significant research on impulse purchasing in traditional “brickand mortar” stores, very little research exists on impulse purchases in e-commerce.This is an important gap to address, because consumer expenditure on the worldwide web (WWW) has grown from US $15B in 1999 to US $69B in 2004; a CAGRof over 40% [5, 6]. While the growth is expected to slow, the short term forecasts arefor 20% to 25% increases over the next few years. This is far above the anticipatedgrowth in overall retail figures [6]. If online retailers could gain a better understandingof the factors that encourage impulse purchases online, even a 1 percent increasein sales from impulse purchases would lead to an additional US $690 million inrevenues. With such a lucrative opportunity available to online retailers it is difficultto understand why little rigorous research in this field exists. We hope this studyprovides a first step towards addressing this gap in the literature, and encouragesother scholars to study this field.

1 Impulse purchases

Stern [1] wrote that impulse buying is synonymous with “unplanned buying” and de-fined it as “any purchase which a shopper makes but has not planned in advance.”This definition is fairly consistent among other impulse purchasing literature [7, 8].More recently, researchers have extended this definition beyond a simple unplannedpurchase to include an emotional element or an urge to make the purchase. Rook [9,p. 191] defined impulse buying as “when a consumer experiences a sudden, oftenpowerful and persistent urge to buy something immediately”. Piron [10] conducted athorough survey of impulse purchasing literature and proposed a more specific andcomprehensive definition for impulse buying that includes four components: the pur-chase is unplanned, it is the result of an exposure to stimulus, it is decided “on-the-spot”, and it involves an emotional and/or cognitive reaction. This is the workingdefinition that will be used for this study. In this paper, we will use the terms “impulsebuying” and “impulse purchase” interchangeably.

Previous research has classified impulse purchasing into four types: pure, sugges-tion, reminder, and planned [1, 4]. Pure impulse buying signifies a situation wherethe purchase is outside of the normal purchase behavior and is initiated by emotionalappeal. For example, a consumer who rarely buys magazines might see a Peoplemagazine at the checkout while waiting in line at the grocery store and want it basedon the cover story or pictures. In this case, the purchase of the magazine would beconsidered pure impulse because it is outside of the normal purchase behavior andit satisfies an immediate desire initiated by an emotional appeal. Suggestion impulsebuying occurs when the consumer sees the product, visualizes an application for it,and decides that they need it. This is not a pure impulse purchase because the userhas determined a rational or functional purpose for the item, whereas during the pureimpulse transaction the user is fulfilling an emotional desire. It is these two types ofimpulse buying we will consider in this study.

Factors influencing impulse buying during an online purchase 369

We will not consider reminder impulse buying which occurs when a purchaseis made based upon something reminding the consumer to make the purchase. Incontrast to a pure impulse purchase, the item is something that the user normallypurchases but is not necessarily on their current shopping list. For example, a shoppermight walk down the cereal isle and realize that they are almost out of Cheerios. If thisconsumer chose to purchase cheerios, it would technically be an impulse purchase asit was unplanned, but it something that is generally purchased by the shopper. We willalso not consider planned impulse buying which occurs when the consumer buys aproduct based on price and/or product specials. For example, someone who consumesa great deal of orange juice may see a special price on it and buy them, even if it wasnot an intended purchase for that trip to the market.

As mentioned earlier, most existing research on impulse buying has focused onbrick-and-mortar stores [7, 8, 11–15] and television infomercials [16]. Previous re-search on e-commerce has traditionally focused on improving the user experience[17], advertising [18, 19], and identifying factors that lead to an initial purchase ona web site [20]. Only limited work has been done on impulse purchases in an onlineenvironment and any results with respect to impulse purchases were inconclusive [21,22]. In addition, most of the previously studied antecedents to impulse purchases havebeen emotional. In this paper we take a more cognitive approach by analyzing howthe concept of purchase justification plays a role in impulse decision.

Before discussing our contribution to this literature, we analyze the other an-tecedents to impulse purchases. Previous research has mostly discussed emotionalantecedents to impulse purchases, in particular, the effect of mood and positive vs.negative affect. Rook and Gardener [23] looked at moods and found that they droveovert behavior. Pleasure, arousal, and dominance are all associated with the encour-aging or suppression of impulse purchases. Positive affect can encourage increasebrowsing behavior which was also found to lead to higher levels of impulse purchases[23, 24].

Exploratory research by Madhavaram and Laverie [22] showed a number of self-reported stimuli that led their subjects to purchase impulse items on the Internet.Consistent with research on brick and mortar purchases, many of the same visceralinfluences led to impulse purchases such as appeal of the product, advertisements,and compelling presentation. In addition, their participants also confirmed that thosepeople in a good mood were more likely to purchase impulse items and doing recre-ational browsing.

Rather than examine the more emotional antecedents, we want to explore a morecognitive process that might lead people to purchase impulse items; that of ease ofjustification of the purchase. While we are not discounting the fact that the creationof an impulse to buy is generally emotional, we believe that only if cognitive forcesimpinge on the decision, will the actual purchase be made. In this paper, we willanalyze how mental accounting [25–27] and providing a reason to purchase increasethe likelihood that someone will make an impulse purchase.


2 Cognitive factors leading to impulse purchases

As has been shown in previous research [28], people like to have reasons to do things.This is particularly true for the purchase of items viewed as more frivolous [29]. Inthis section, we will propose two potential justifications for purchasing an impulseitem on the web. Specifically, we will look at the role mental accounting plays indiminishing people’s sensitivity to additional purchases as well as the provision of aspecific reason to purchase.

2.1 Mental accounting and impulse purchases

Rather than treating money as a fungible commodity, consumers often segregate dif-ferent sources and uses of cash into various mental accounts [25–27, 30, 31]. Theseaccounts generally have relative firm barriers between them, making it a non-trivialprocess to reassign expenses to a different account. Rather than choosing the itemsthat maximize overall expected utility, people often base their consumption decisionson the total amount budgeted and the amount remaining in these mental accounts.This implies that someone may buy clothing rather than tickets to a movie even ifthe movie would be more enjoyable, simply because there is some budget left forclothing but no more money left to spend in the “entertainment” account.

Beyond the categorization system, mental accounting has its own specific arith-metic system for tabulating the accounts. This arithmetic is based on the ProspectTheory value function [32]. Rather than looking at overall wealth states, people eval-uate income and expenditures as gains and losses from a neutral reference point. Thisneutral reference point is often current wealth, but can be a target amount, or anyother salient basis of comparison. Next, income and expenditures are affected by di-minishing sensitivity to these changes. For example, the 100th dollar spent in a store,“feels” like less of an expenditure than the 10th dollar spent.

To illustrate, consider a situation where a consumer is making a US $39,000 ve-hicle purchase and wants to add a new stereo to this vehicle. When the consumer isalready spending US $39,000, an additional US $500 for the stereo relative to the to-tal purchase seems insignificant. If the consumer purchases the car stereo with the US$39,000 car, then the US $500 is added to the ‘car’ account which already containsthe US $39,000 the car purchase amount. Spending “just another” $500.00 or 1.3%seems like a small purchase due to diminishing sensitivity. If however, the consumerpurchased the car stereo by itself at an electronics store, the spending of this $500would feel quite different; it would ‘feel’ like a bigger amount of money than whenit was paired with the purchase of the vehicle. If the car stereo were purchased on itsown, it would be the first $500 the consumer spent and in terms of mental accounting,the US $500 would be allocated to a “stereo” account rather than the “car” account.As a result, upon making this purchase, the value of this category starts at $0 andmoves to $500 instead of moving from $39,000 to $39,500. When consumers aggre-gate spending, diminishing sensitivity makes it much less painful to spend additionalfunds in the presence of a more expensive item.

We believe that consumers aggregate all purchases in a single online purchasingevent, very similar to a visit to a brick and mortar store. Thus, the more someone is


spending on a website, the less “painful” additional spending will be. Thus, higherspending in advance of seeing the impulse item will lead to a higher likelihood ofpurchasing the impulse item.

2.2 Specific reason to purchase

Research on reason based choice has shown that people like to have good reasonsfor their purchase decisions. For example, researchers asked people to either choosewhich of two options to receive or which of two options to reject. They found thatan enriched option, the item with more extreme attribute values, was more likelyto be chosen and rejected than an option with less extreme attribute values [28].They claimed that this phenomenon occurred because when deciding which optionto accept, people were seeking reasons to choose but when deciding which option toreject, decision makers were seeking reasons to reject.

Other marketing research has shown that the existence of a compromise choicewill lead consumers to be more willing to make a choice rather than wait for moreinformation [33]. The existence of a compromise item provides a reason to choosethe middle option. Research on asymmetric dominance is another example of havinga reason to purchase [34]. These researchers provided a choice between product X(lower price, lower quality) and product Y (higher price, higher quality). Participantswere then told about a 3rd product (the decoy) that would be dominated by one ofthe two products but not the other. The research showed that the market share of thetarget (the item which dominated the decoy) rose depending on which item the decoytargeted. These researchers claimed that the provision of a dominated alternative gavea reason to purchase the item that was better on both attributes, since the non-targetedoption still required trade-offs.

Recent research by Strahilevitz and Myers [35] showed another way to providepeople a reason to purchase items and to encourage shoppers to visit a store. In theirresearch, they tied the purchase of specific items to a donation to charity. They pro-posed that the donation provided a reason to purchase an item that would otherwisenot be purchased due to justification concerns. In line with this research, we believethat the provision of a reason to purchase an impulse item during an online purchasingtransaction will increase the likelihood that item will be purchased.

3 Data

We tested our hypotheses by offering real consumers the opportunity to purchase animpulse item during the checkout process of a real on-line purchasing transaction.Visitors to the official website of the Huntsville High School (HHS) 100th reunionused this site to get information about the reunion, purchase their passes to the re-union, and purchase souvenirs. Items available were clothing, household, and sport-ing goods items which ranged between US $6 for a glass coffee mug and US $45 fora hooded sweatshirt. All items were marked with the Huntsville High School reunionlogo. We believe that consumers making purchases on the HHS Reunion websitewere placing these purchases in a single ‘Reunion’ expense category and thereforeall purchases each person makes on this website would be evaluated in an aggregatemanner.


3.1 Procedure

Visitors to the site initiated a transaction by placing the products they wanted in avirtual “shopping cart” by clicking the “Buy Now” button. If a chosen product hadattributes (e.g. color and size for a T-shirt), the users had to specify their choices.When done shopping, the visitors proceeded to the checkout by clicking the “Check-out” button. The system then asked the customers to either sign in to an existing ac-count or create a new account by entering contact information on a single page. Oncesigned in, the “checkout” page showed a summary of contact information, shoppingcart contents and the total amount owed.

When the users viewed the checkout page they were offered the opportunity topurchase one of three “add-on” impulse items all costing US $5.00: a mouse pad,eyeglass clips, or a box of chocolate truffles. This price point allowed for the flexi-bility to offer quality products at an amount high enough to have different impactson the expected sales amounts of US $30, $60 and $110. The US $5 price for ourimpulse items represented a 16.7 percent increase in amount spent for a consumerwho bought the US $30 blue pass, an 8.3 percent increase in the amount spent fora consumer who bought the US $60 gold pass and a 4.5 percent increase in amountspent for a consumer who bought the US $110 principle’s pass. These items were notoffered in the souvenirs section of the website, therefore this item should not havebeen part of the initial mental budget, making it a true “additional” impulse buy.

The consumer confirmed the content of the shopping cart and accuracy of the con-tact information by clicking on the “Checkout” button again and proceeded to pay forthe order. Following payment the user was asked to answer demographic questions.To encourage participants to enter their demographic information, we offered theman entry into a lottery for HHS Reunion souvenirs.

To test for the effect of providing a reason to purchase, a randomization scriptassigned participants to either a donation condition or a control condition (no dona-tion). Those in the donation condition a saw that a US $1.00 donation to the steppingstone foundation1 would accompany the purchase of the impulse item, while the othergroup of participants saw only the items for sale. Note that price of the item was stillUS $5.00, in the donation condition. If the customer purchased the impulse offer, itwas added to the shopping cart, the checkout page was refreshed, and the same dona-tion condition was generated again. While it could be argued that people purchasedthe item just so that they could make a donation, we ruled out this alternative expla-nation by providing a separate place on the website to make a donation without anattached purchase.

3.2 Measures

The dependent variable for this experiment was whether or not visitors to the web-site purchased an impulse item. To test this, we collected information regarding howmuch was spent prior to seeing the impulse item, as well as whether or not a donation

1The stepping stone foundation was organized by Huntsville High School to give university scholarshipsto needy and deserving HHS students, making it a highly salient donation for alumni of the school.


was linked to the purchase. Because other factors might affect the willingness to pur-chase an impulse item, we also gathered information regarding household income,age, and gender information. We believed that higher income visitors would be morelikely to purchase an impulse item because of the additional disposable income theyhave available. We expected no effect for age or gender.

4 Results

Data were collected on actual purchase transactions on the HHS Reunion websitefrom March 13, 2004 to May 19, 2004. During this period 60,413 pages were viewed,3,488 unique visitors attended the site and 771 transactions were approved andprocessed. Of these, 349 orders were submitted in person or by mail and processedusing a separate interface and therefore were not exposed to the impulse item. Of the422 remaining purchase transactions, two of these transactions were test transactionsthat were performed to confirm that the data collection and online payment process-ing were functioning properly. As a result, these two records were removed from thedata set leaving 420 records.

To test for the effect of money spent, we required demographic information, par-ticularly regarding income. One hundred and eight consumers visiting the site did notreply to the demographic questions which reduced the number of usable data pointsto 312.2 Upon further inspection of the demographic responses, one visitor indicatedthat he was age 18 or less with 47 children under the age of 12 and 74 people liv-ing in the household on an income of under US $20,000. This record was eliminatedfrom the data set for the first hypothesis leaving 311 purchase transactions whichwere used in the final data analysis. Table 1 shows the mean, standard deviation, andcorrelations of the control variables for the final data set.

Table 1 Descriptive statistics and correlations of independent variables

Variable Mean Standard Amount Age Household

deviation spent income

Amount spent 90.8 48.36

Age 48.4 9.80 0.282

Household income 77.0 21.17 0.164∗∗ –0.075

Gender Male n = 128 –0.210∗∗∗ –0.111 –0.236∗∗∗Female n = 183

∗ p < 0.05∗∗ p < 0.01∗∗∗ p < 0.001

2There was no difference in the frequency of impulse purchase between those who responded to the de-mographic questions and those who did not, t (420) = 0.93, p = 0.35.


4.1 Responsiveness to money spent

We used a logistic regression to test the effects of prior spending on the likelihood ofimpulse purchase. The empirical model shown as (1) is

log

(p

1 − p

)= α + β1 · amount spent + βT · control variables + ε, (1)

where p represents the probability of purchasing the impulse item, amount spent isthe amount of money spent on purchases prior to being exposed to the impulse item,and the control variables are age, income, and gender as outlined above.

The initial model reported in Table 2 is the full model with all of the variablesincluded while the final model retains only the coefficients significant at p < 0.05. Inthe final model, the amount spent prior to seeing the impulse item had a significantand a positive effect on the likelihood to purchase, β = 0.0114, t (308) = 2.79, p <

0.01. This coefficient translates into a 1% increase in purchase likelihood for eachUS $10 increase in prior spending. Household income also had a significant effect onthe likelihood to purchase, β = −0.0253, t (308) = 2.28, p < 0.05.

Estimates based on final model shown in Table 2:

log

(p(impulsebuy)

1 − p(impulsebuy)

)

= −2.202 + 0.013 · amount spent − 0.027 · household income.

Table 2 Logistic regression results

Dependent variable: Log odds of buying impulse item

(Standard Error in parentheses)

Variable Initial model Final model

Amount spent 0.014∗∗∗ 0.013∗∗∗(0.004) (0.004)

Age 0.176

(0.245)

Household income –0.025∗ –0.027∗(0.012) (0.011)

Gender 0.465

(0.583)

Constant –4.072∗ –2.202∗(2.035) (0.820)

χ2(4,N = 312) = 13.7 χ2(2,N = 312) = 12.6

R2 = 0.12 R2 = 0.11

∗ p < 0.05∗∗ p < 0.01∗∗∗ p < 0.001


Fig. 1 Estimated likelihood ofpurchase for specific householdincome levels (35 K, 65 K,95 K)

To illustrate the effect of income and prior expenditures, we estimated the like-lihood of impulse purchase based on the final model shown in Table 2. These esti-mates are shown in Fig. 1. By looking at this figure, the positive impact of amountspent can be seen at all levels of income. This table also shows the negative influenceof household income, as the intercept of the estimate is dropping with income at allexpenditure levels.

4.2 Reasons to purchase

In our initial experimental design, we wanted to test the effects of presenting theimpulse item in a pop-up window vs. presenting the impulse offer embedded in thecheckout page. We found no effect for this manipulation and so these conditionswere dropped from further analysis. This left 221 observations which presented theimpulse item embedded in the checkout page, 105 with the donation, and 116 withoutthe donation. We used these observations to test whether linking the purchase to adonation increased the likelihood of an impulse purchase. When no donation waslinked to the purchase, 2 people (1.7%) offered the impulse item purchased it. Ashypothesized, this rose to 9 people (8.6%) when a donation was linked, t (220) =2.33, p < 0.05.

5 Discussion

This experiment found that as the amount spent on other purchases during an on-linetransaction increases, consumers are more likely to purchase an additional item thatthey did not intend to purchase when they first visited the site. While this is certainlyconsistent with many experiments on mental accounting, this has additional externalvalidity as it was performed on visitors to an active e-commerce site, spending theirown funds. Since the impulse item was offered after all purchases were made, theseresults provide evidence that impulse purchases can incrementally increase onlinesales without cannibalizing other products. As a result, impulse buying in the onlineenvironment is an important issue that should be studied further. It also suggests


another important reason why website designers should try to maximize consumerpurchases while on the web site. As web site visitors spend more money, they areless resistant to spending even more.

We believed that those with higher incomes would be more likely to buy impulseitems, since their discretionary income would be higher. However, we found that in-come actually had a negative effect on impulse purchases; as incomes rose, peoplebecame less likely to buy on impulse. One theory that could potentially explain whythis occurred is that higher income consumers do not buy ‘junky’ US $5 items, theymay be more likely to buy a higher priced, higher quality souvenirs. High incomeconsumers may also see limited value in a mouse pad, eyeglass clip, or chocolatetruffles. While this is speculation, we believe it is important for future research to ex-amine the impact of income on impulse purchases. This finding is consistent howeverwith the speculation that wealthy individuals achieved their financial status by livingwithin their means and avoiding impulse purchases such as the one we offered [36].

This study also shows that offering a reason to purchase is an effective way toincrease impulse purchases. Linking a US $1 donation to the impulse item, therebyproviding a reason to purchase, increased the frequency of the impulse purchase fromaround 2% to almost 9%. It may seem that the baseline impulse purchase of 2% seemsquite low, especially considering work by Stern [1] that showed that almost 50%of purchases are done on impulse. We believe this is a reasonable number for tworeasons. First, we are only studying “pure” and “suggestion” impulse purchases [1,4]. Other types of impulse purchases, notably reminder and planned might account fora large number of impulse purchases. In addition, other research has shown that lessimpulse purchases are made online due to the absence of a sales person to pressurethe sale [22]. While the increase from 2% to 9% may appear small, this is a potentialincrease of US $5B in total revenue, given the US $69 Billion spent online in 2004[6].

Although we studied this phenomenon in an online environment, we see no com-pelling reason why we would not see the exact same results in a traditional retail en-vironment. The diminishing sensitivity to additional expenditures may even be morepronounced, since a trip to a store may be more clearly segregated in a consumer’smind. We also believe linking a donation to impulse items displayed at the regis-ter should also inspire increased purchase of those items in brick and mortar retaillocations. In fact, this is probably why donation boxes are generally located at thecheckout.

5.1 Important differences in the online environment

There are some important differences between purchasing online and purchasing ina brick and mortar environment. Store layouts are quite different than a website’sdesign. The site must be easily navigable and the online retailer must be trustworthy[37, 38]. In addition to these basic differences, online retailers differ from their brickand mortar counterparts when it comes to impulse buying. For example, in the brick-and-mortar environment, heavy or awkward items are not typically used as impulseitems because of the difficulty consumers may envision in getting it home. Heavy orawkward items may be more effective as online impulse items because all online pur-chases are delivered to the user and therefore, the consumer would not have to worry


about the weight or awkward nature of items. As a result, the online environment mayreduce restrictions in the types of products that can be offered for impulse. However,transportation costs such as these are a double edged sword. Online consumers needto worry about shipping and handling costs which could significantly raise the costof these goods, reducing their effectiveness as an impulse item.

An additional drawback to online impulse purchases is the fact that there are noclerks to suggest impulse items. As a result, influencing the impulse purchase maybea more difficult task online [22]. In addition, the delay of receiving the purchase maydissuade shoppers from making impulse purchases online, particularly since impulsepurchases are generally designed to satisfy immediate desires. For example, whena consumer is standing in line waiting to pay for their groceries, the sight of gumat the checkout may make their mouth water, increasing the visceral desire for theitem and inducing them to buy the item on impulse [39, 40]. This is also a two-edgedsword, since even though there is no immediate reduction in the drive to consume theimpulse item, some items may increase utility through the act of savoring it prior toits arrival [41].

5.2 Limitations & future research

One limitation of this experiment was that the participants represented a restrictedsample of the population. This was a not-for-profit website for a high school reunionwhere the donation was targeted to a school-oriented fund. Because of this, it is likelythat this charity was more meaningful to the participants, increasing the likelihood ofimpulse purchase more than a less relevant donation would have done. Finding sucha salient charity for a larger audience would be more difficult, making the provisionof a reason such as this more difficult.

Furthermore, this research was not conducted on a “traditional” retail website andthis may limit the generalizability of the findings. To resolve this, similar manipula-tions should be attempted on a more permanent, e-commerce website. This researchis also limited in the types of impulse purchases studied. We studied pure and sug-gestion impulse purchasing, future research should examine the factors that lead toreminder and planned impulse purchases. Finally, we only examined mental account-ing and reason to purchase reasons for impulse purchases, and there are undoubtedlymany other causes.

We also believe that future research should consider the process by which retailweb sites select the products to use as impulse items. Large on-line retailers such asAmazon.com use past transaction history to pair up books frequently bought together,thus creating opportunities for suggestion impulse purchases. Future research shouldexamine existing work on the characteristics of impulse items in brick and mortarstores [1] and attempt to apply them to the online environment.

6 Conclusion

This paper examined impulse purchasing during online transactions with respect tothe amount spent on the site and the provision of a reason to purchase. Consistent


with mental accounting and the psychophysics of pricing, the results indicate that thelikelihood of an impulse purchase is positively correlated with the amount spent onthe website prior to seeing an impulse item. The more someone spends on a websiteprior to seeing an impulse item, the more likely they are to make an impulse purchase.In addition, the study reported here found that by linking the impulse purchase toa relevant charitable donation increased the frequency of that impulse purchase. Wehypothesize that this is because the link to a charity provided an easy to justify reasonto purchase the item, even if the item was not needed.

With spending on the web at US $69B and growing at 20% a year, we feel thatimpulse purchases in e-commerce is an area that deserves more scholarly study. Withan understanding of the factors that influence impulse purchases in the online en-vironment and minimal additional investment, online retailers can capitalize on thislucrative opportunity.

Acknowledgements The authors wish to thank the Huntsville High School 100th Anniversary organiz-ing committee for their support.

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Scott A. Jeffrey is an assistant professor in the Department of Management Sciences at the Universityof Waterloo, Canada. He has a Ph.D. in Managerial and Organizational Behavior from the University ofChicago Graduate School of Business. Dr. Jeffrey conducts research on individual decision making andemployee performance.

Rebecca Hodge MASc., received her Masters of Applied Science in 2005 from the Department of Man-agement Sciences at the University of Waterloo. She is currently a partner in the web design firm ofE-XYN Web Solutions. E-XYN assists clients by implementing more effective ways to manage businessand customers through the efficient use of technology and the web.

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