Impulse buying: Modeling its precursors

Impulse Buying: Modeling Its Precursors

SHARON E. BEATTY The University of Alabama

M. ELIZABETH FERRELL Southwestern Oklahoma State University

A model of the precursors of impulse buying is presented and empirically tested with data drawn at two points in time (during pre- and post-shopping interviews) from a regional shopping mall setting. Analysis of the data, utilizing LISREL 8, supported most of the pre- dictions. Situational variables (time available and money available) and individual difference variables (shopping enjoyment and impulse buying tendency) were found to influence a set of endogenous variables, including positive and negative affect, browsing activity, felt urge to buy impulsively, and ultimately, whether or not an impulse purchase occurred. Future research and managerial implications are addressed.

INTRODUCTION

Impulse buying is a pervasive aspect of consumers' behaviors and a focal point for considerable marketing activity (Rook, 1987). In one study impulse purchases, operationalized as unplanned purchases, were found to represent between 27 and 62 percent o f all department store purchases (Bellenger, Robertson, and Hirschman, 1978). Although fraught with difficulties, this topic has generated considerable research interest for over thirty years (cf. Bellenger et al., 1978; Cobb and Hoyer, 1986; Kollat and Willet, 1967; Rook and Fisher,

Sharon E. Beatty, Miles-Rose Professor of Leadership and Professor of Marketing, Culverhouse College of Commerce and Business Administration, The University of Alabama, P. O. Box 870225, Tuscaloosa, AL 35487-0225; M. Elizabeth Ferrell, Assistant Professor of Marketing, College of Business Administration, Southwestern Oklahoma State University, Weatherford, OK 73096-3098.

Journal of Retailing, Volume 74(2), pp. 169-191, ISSN: 0022-4359 Copyright © 1998 by New York University. All rights of reproduction in any form reserved.

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170 Journal of Retailing Vol. 74, No. 2 1998

1995; Stem, 1962). However, it is surprising how little we really know about the process of impulse buying and the variables affecting its enactment.

Most of the research on impulse buying has focused on the situational aspects affecting impulse buying. For example, Rook in his early work explored the underlying nature of impulse buying (Rook, 1987) and later focused on the normative influences affecting it (Rook and Fisher, 1995). Rook and Gardner (1993) examined and discussed the influence of affect on impulse purchasing. Recently, impulse buying has been treated as an individual difference variable, which is likely to influence individuals across situations (Rook and Fisher, 1995; Weun, Jones, and Beatty, 1998).

Previous research has not focused on fully understanding the antecedents of impulse buying. For example, past studies have tended to investigate only a single situational or individual variable while failing to more fully model a set of both situational and individual variables. Thus, the objective of our paper is to more fully model important antecedents. We focus on a set of exogeneous antecedents, including two situational variables (time available and money available) and two individual difference variables (shopping enjoyment and impulse buying tendency). We propose that these variables influence a set of endogenous variables, including positive and negative affect, browsing activity, felt urge to buy impulsively, and ultimately, whether or not an impulse purchase occurs. This model is tested on data obtained from mall respondents both prior to and following their shopping trip.

We believe that beyond contributing to a fuller theoretical understanding of impulse buying, this study will provide insights to retailers about which variables influence shoppers' impulse buying urges and actions. Retailers can control many of these variables through their choices of market segments and marketing strategies. Often they can control the perception held by shoppers about these variables, as well.

IMPULSE BUYING

Early marketing literature described impulse buying simply as unplanned purchasing (cf. Cobb and Hoyer, 1986). However, this leaves much to be desired and has been criticized in the literature (cf. Rook and Hoch, 1985; Rook and Gardner, 1993). An impulse purchase by definition is unplanned but it is more, too---it involves experiencing an urge to buy. This urge is felt suddenly and strongly and is often irresistible. Rook (1987, p. 191) defined impulse buying as when "a consumer experiences a sudden, often powerful and persistent urge to buy something immediately." We extend this definition slightly. Impulse buying is a sudden and immediate purchase with no pre-shopping intentions either to buy the specific product category or to fulfill a specific buying task. The behavior occurs after experiencing an urge to buy and it tends to be spontaneous and without a lot o f reflection (i.e., it is "impulsive"). It does not include the purchase o f a simple reminder item, which is an item that is simply out-of-stock at home.

Our definition insures that the shopper did not intend to buy the item before entering the shopping area and that fulfilling a planned task, such as buying a gift for someone, is not an impulse purchase. Also, it includes the idea of impulsiveness, which involves acting spontaneously without full consideration of the consequences (cf. Gerbing, Ahadi, and Pat-

Impulse Buying 171

ton, 1987). Finally, we focus on the act of buying, while we see the felt urge to buy impulsively, which is defined below, as a precursor to the act.

IMPULSE BUYING MODEL AND HYPOTHESES

Our proposed model, which is shown in Figure 1, is a snapshot view of impulse buying behavior and its precursors taken at one point in time. All linkages are hypothesized to be positive except the linkages associated with negative affect. The endogenous variables and their influences are presented first. Then the exogenous variables and their influences are presented.

The Influence of In-Store Browsing and Felt Urge to Buy Impulsively

In-store browsing is the in-store examination of a retailer's merchandise for recreational and~or informational purposes without an immediate intent to buy (Bloch, Ridg-

FIGURE 1

Proposed Impulse Buying Model


way, and Sherrell, 1989, p. 14). The notion of browsing has received minimal attention in the literature (cf. Bloch et al., 1989; Bloch, Sherrell, and Ridgway, 1986). Babin, Darden, and Griffin (1994) devote considerable attention to the hedonic value of shopping, suggest- ing it reflects shopping's potential entertainment and emotional worth. It has been suggested, in fact, that browsing, or shopping without specific intent, may be more significant than the actual acquisition of products and can provide a highly pleasurable "vicarious buying" experience (Maclnnis and Price, 1987; Sherry, 1990). Thus, browsing tends to produce positive feelings for many shoppers. These positive feelings can be conceptualized as positive affect, which reflects the extent to which a person feels enthusiastic, active, and alert. It is a state of high energy, full concentration, and pleasant engagement. Low positive affect involves sadness and lethargy (Watson, Clark, and Tellegen, 1988). The opposite of positive affect is negative affect, which involves a feeling of distress and non- pleasurable engagement that subsumes a variety of aversive mood states, including anger, disgust, guilt, fear, etc. Low negative affect suggests calmness and serenity. Both positive and negative affect will be addressed in more detail below.

Jarboe and McDaniel (1987) found browsers made more unplanned purchases than non- browsers in a regional mall setting. As a form of on-going search, in-store browsing is a central component in the impulse buying process. As an individual browses longer, she or he will tend to encounter more stimuli, which would tend to increase the likelihood of experiencing impulse buying urges.

The felt urge to buy impulsively derives from Rook's focus on the sudden, spontaneous urge or impulse felt to buy something. However, an urge or desire (Hoch and Loewenstein, 1991; Rook and Hoch, 1985), although often powerful and sometimes irresistible, is not always acted upon (Rook and Fisher, 1995). In fact, individuals use a myriad of strategies to gain some control over this desire (Hoch and Loewenstein, 1991).

Weinberg and Gottwald (1982, p. 44) say "it appears feasible to consider decision and behavior separately." We agree. Thus,felt urge to buy impulsively is a state of desire that is experienced upon encountering an object in the environment. It clearly precedes the actual impulse action. Consistent with the literature, it is spontaneous and sudden. The impulse purchase is the final dependent variable in our model. It involves the actual purchase of this product or fulfillment of the urge. Obviously, as more urges are experienced, the likelihood of engaging in an impulse purchase increases.

Much of the rationale behind our linking of browsing to urge and urge to impulse buying are drawn from the idea of physical proximity. Rook (1987) suggested that consumers have the most difficult time resisting the urge in the moments following their encounter with the object. Further, Hoch and Loewenstein (1991) suggest that once desire occurs, the consumer's reference point changes (that is, they partially adapt to the notion of owning or consuming the product). Thus, in-store browsing produces encounters with desirable products, whose encounter produces an urge to buy, which is difficult to resist due to the physical proximity of the product. Further, Hoch and Loewenstein (1991) suggest that buying may beget more buying, having "fallen off the wagon," so to speak. This suggests a form of momentum in which additional urges are acted upon more quickly than previous urges. Thus, the first set of hypotheses follow:

Impulse Buying

HI: The greater the level of in-store browsing (a) the greater the level of positive affect and ( b ) the greater the frequency of felt urges to buy impulsively.

The higher the frequency of felt urges to buy impulsively, the greater the likelihood of making an impulse purchase.

H2:

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The Influence of Positive and Negative Affect

Affect or mood has been identified as a variable that strongly influences a number of actions including impulse purchasing (Gardner and Rook, 1988; Rook, 1987; Rook and Gardner, 1993). Watson and Tellegen (1985) indicate that positive affect and negative affect are two distinguishable dimensions, which are orthogonal to one another. Thus, we utilize the orthogonal constructs of positive and negative affect in this study and view them as similar to the positive and negative moods addressed in Rook and Gardner (1993). Their definitions appeared earlier in the paper.

An individual's positive affect is influenced by his/her pre-existing mood, affective dis- position, and reaction to current environmental encounters (e.g., desired items and sales encountered, etc.). Thus, this variable is a complex communion of individual and situational variables. In this study we focus on the affect created in the environment, although the pre-shopping mood effect is also likely to be meaningful, if it could be successfully distinguished from affect in the environment and did not influence the later measurement of affect (Jeon, 1990).

The psychological literature suggests that when one is in a good mood (i.e., experiencing positive affect), one is more likely to engage in approach behavior than avoidance behavior. Laboratory findings suggest that positive moods cause people to reward themselves more generously, to feel as if they have more freedom to act, and will produce behaviors aimed at maintaining a positive mood state (Cunningham, 1979; Isen 1984; Isen and Levin, 1972).

However, negative affect, experienced simultaneously, may negatively affect one's urge to buy impulsively, that is, negative moods may decrease approach behavior. The effects of negative moods on behavior are unclear. Sometimes they produce effects similar to those produced by positive moods, while at other times they produce opposite effects (Clark and Isen, 1982).

The importance of affect in this process is in keeping with the literature on the effect of mood on impulse buying. Rook and Gardner (1993) found 85 percent of their survey respondents indicated a positive mood would be more conducive to impulse buying than a negative mood. Respondents felt that in a positive mood they have an unconstrained feeling, the desire to reward themselves, and higher energy levels.

In an observational study, Weinberg and Gottwald (1982) found that impulse buyers exhibited greater feelings of amusement, delight, enthusiasm, and joy while Donovan and Rossiter (1982) found that pleasure was positively associated with a likelihood of over- spending in the shopping environment. We, however, view affect as working primarily on


impulse buying through the experiencing of greater numbers of urges to buy (i.e., the initial approach behavior).

Based on our literature review, it is reasonable to suggest that the major effect of affect will come from its positive dimension rather than its negative. However, some research suggests that impulse purchases may be a result of one' s attempt to relieve depression (Bel- lenger and Korgaonker, 1980) or to cheer oneself up (Mick and DeMoss, 1990), thus sug- gesting a possibly weak positive linkage between negative affect and the experience of buying urges. Thus, there appears to be both a positive and negative influence of negative affect at work on approach behavior, which may produce only a minimal overall influence of this variable on urge, which may be negative. Thus, the next two hypotheses are offered.

1-13: The greater the positive affect, the greater the felt urge to buy impulsively.

1-14: The greater the negative affect, the less the felt urge to buy impulsively.

The Influence of the Exogenous Individual Difference Variables

Two individual difference variables are predicted to influence the endogenous variables: shopping enjoyment and impulse buying tendency. The first one has not been previously linked to impulse purchasing, while the second one has been. Shopping enjoyment is defined as the pleasure one obtains in the shopping process. Given that a shopper may enjoy some shopping contexts more so than others, this variable is assessed within a shopping mall context.

This variable is conceptualized as an individual difference variable. For example, Bel- lenger and Korgaonkar (1980) referred to individuals who enjoyed shopping as recreational shoppers. They found that these shoppers spent more time shopping and shopped longer after making a purchase. Westbrook and Black (1985) found that recreational shoppers obtained more gratification from the process of shopping than from the merchandise purchased. Thus, if a person enjoys the act of shopping generally, s/he is likely to browse longer and enjoy it more for any specific shopping occasion.

The second individual difference variable, impulse buying tendency (IBT), addresses the differential proclivity of individuals to buy on impulse (Rook, 1987). The literature sup- ports the idea that individuals do differ on this variable (Rook and Fisher, 1995; Weun, Jones, and Beatty, 1998 ). IBT has been viewed as a sub-trait of the general impulsivity construct, which was defined by Gerbing et al. (1987, p. 357) as "a tendency to respond quickly to a given stimulus, without deliberation and evaluation of consequences." Again, we note that the literature does not distinguish between the action and the urge. Thus, we define IBT as both the tendencies (1) to experience spontaneous and sudden urges to make on-the-spot purchases and (2) to act on these felt urges with little deliberation or evaluation of consequence. We further note that it is the action that is the most critical element to exhibition of this trait. This is consistent with Hoch and Loewenstein's (1991) discussion about how consumers can actually deflect the urge to buy by executing various desire- and willpower-based strategies.

Impulse Buying 175

Due to the generally positive reinforcement received immediately upon exhibiting the behavior, the high IBT individual is likely to engage in greater in-store browsing as a shopping strategy. We believe that impulse purchasing produces positive reinforcement because most consumers feel better after making an impulse purchase. For example, Rook and Gardner (1992) found that 75 % of their sample, upon reflecting on a previous impulse purchase, reported feeling better after that purchase, while only 8% reported feeling worse.

Further, Bellenger and Korgaonkar (1980) learned that recreational shoppers were more likely to go on shopping trips without a pre-planned purchase in mind and Rook and Hoch (1985) suggest that some people "plan on being impulsive" as a shopping approach. As Punj and Stewart (1983, p. 192) suggest, individuals develop characteristic patterns of shopping "as reflections of their efforts to control their own behavior by designing a particular task environment." Thus, high IBTs are likely to use browsing as a shopping strategy.

Almost by definition, the high IBT individual is likely to experience more urges to buy impulsively and will tend to act more frequently on those urges. The "almost" appears in the previous sentence because the variables can be distinguished. Impulse buying tendency is an individual difference variable, while felt urge and impulse buying refer to what occurs on a particular shopping trip, which may or may not reflect the trait. That is, the single- occasion measurements of both urges experienced and behavior in regard to impulse buying may be unreliable because they will reflect elements of the situation not captured by the other variables in the model (cf. Epstein, 1980; Lastovicka and Joachimsthaler, 1988). In addition, most of the work in the past on impulse buying has focused on it as situational behavior, i.e., something we all do in the appropriate situation. This further suggests the difficulty of linking IBT to any one specific buying situation. We believe that the IBT variable will primarily influence the felt urge variable rather than directly influencing the impulse purchase. We can, of course, test for the possibility of a direct effect in our model testing procedure. Thus, we offer the following hypotheses:

1t5: Individuals who enjoy shopping more will (a) tend to engage in more in- store browsing and (b) tend to experience more positive affect in the shopping environment.

H6: The higher the impulse buying tendency (IBT) (a) the greater the level of in- store browsing, and (b) the greater the frequency of urges felt to buy impulsively.

The Influence of Exogenous Situational Variables

We offer two situational variables important to the impulse buying behavior scenario. The first variable is the amount of time the shopper feels s/he has available that day (time available). It is the opposite of time pressure. Iyer (1989) found that time pressure reduced unplanned purchases in an experiment while time availability has been positively linked to search activity in a retail setting (Beatty and Smith, 1987). Thus, all other things being equal, individuals with more available time will browse longer. Fur-


ther, possessing limited time to shop, browse, or accomplish planned tasks could produce frustration and a negative reaction to the environment. This idea is related to the non-attainment of one's goals, which has been found to be positively associated with negative affect (Babin, Darden, and Griffen, 1994; Dawson, Bloch, and Ridgway, 1990; Gardner and Rook, 1988).

A second situational variable that is likely to positively influence impulse purchasing is the amount of budget or extra money the individual perceives she or he has to spend on that day (i.e., money available). For example, Jeon (1990) found a marginal association between perceived extra money and impulse purchasing (p < .06). We connect available money directly with impulse purchasing rather than with browsing or felt urge because we see it as a facilitator for purchasing the desired object. Additionally, we connect it indirectly with impulse buying through urges experienced. That is, we believe that available money will produce more positive affect (i.e., excitement) and less negative affect (i.e., frustration) in the shopping environment, which will impact on urges experienced. These ideas produce the following hypotheses:

H7: The more time an individual feels s/he has available, (a) the higher the level of in-store browsing; and, (b) the lower the degree of negative affect.

H8: The more available money the individual feels s/he has, (a) the higher the degree of positive affect; (b) the lower the degree of negative affect; and (c) the higher the likelihood of making an impulse purchase.

METHOD

Preliminary Efforts

After a number of initial exploratory interviews with non-students aimed at model development, we conducted in-class student surveys with undergraduate business students (n = 154). We asked students to respond to items based on a recent shopping trip they had taken to a mall. We pretested the in-store browsing, felt urge, time available, money available, positive affect, and negative affect scales. The IBT scale, impulse buying questions, and shopping enjoyment were not assessed because of their performance in previous studies in which the first author was involved (Weun, Jones, and Beatty, 1998; Jeon, 1990; Ellis, 1995, respectively).

Next, based on these in-class surveys, traditional scale development procedures, including exploratory factor analysis, coefficient alphas, and item-to-total correlations, were used to eliminate items that did not adequately contribute to the reliability and validity of the proposed scales.

Impulse Buying

Data Collection

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First, we conducted a thorough pre-test in the mall for two hours the week prior to planned data collection. Everything was conducted in a manner similar to the full study with the authors acting as supervisors and graduate students acting as data collectors. We determined that no major problems existed in the method and minor problems were cor- rected through instruction changes.

Short pre- and post-shopping interviews with customers at a large regional mall in a south- eastern city constituted the primary data collection effort. A regional shopping mall was cho- sen because of the high degree of in-store browsing. The two-stage approach allowed us to ask questions in the appropriate temporal sequence, minimizing problems of forgetting and generalizing across occasions, while providing for defensible temporal associations.

The data were collected over a ten-day period including two weekends during the month of October. The locations of the interviews, the times of the day and the days of the week were rotated in accord with the recommendations of Bush and Hair (1985) to make the final sample as representative of the population who shops at this particular mall as possible.

The interviewers approached each person entering the mall, asked whether he or she would participate, and recorded all refusals. Respondents who completed both phases of the research were entered into a drawing for several sizable gift certificates (i.e., mall money). The interviewers were upper division students in a Marketing Research class who received course credit for participation in the project. Five graduate students and/or one of the two primary researchers supervised the interviewers at all times. All participants attended a training session using the Dillman training process (Dillman, 1978) and engaged in four hours of actual data collection.

During the pre-shopping interview, a shopper was asked to identify his or her initial shopping plans (both specific items and tasks). This information and the shopper's name were recorded by the interviewer. Next, the shopper was asked to fill out the scale items on shopping enjoyment, the time and money resources available during this particular shopping trip, and the demographic questions. The shopper was then asked to return to the table at the end of the shopping trip for further questioning. Upon their return, purchases were compared with the indicated plans one by one. For each item identified as planned or unplanned, the interviewer double-checked with the shopper to insure proper categoriza- tion of the purchase. For example, the interviewer would say: "This skirt you purchased appears to be an unplanned purchase. Did you plan to shop for this today?" Also, reminder- type items were eliminated by the following question: "When you saw this item, were you reminded that you were out of this item and needed it?" Only purchases that were clearly unplanned and could not be classified as "reminder" items were recorded as potential impulse purchases. Finally, shoppers responded to questions regarding the level of impulsivity (i.e., how impulsive was it?) involved in up to three impulse purchases; the time spent browsing; the urges experienced to make impulse purchases; the level of positive and negative affect experienced during the shopping trip; and their general tendency to engage in impulse buying (IBT).

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Sample

Journal of Retailing Vol. 74, No. 2 1998

During the ten days of data collection, 2391 initial contacts were made; 878 (37%) agreed to participate, and completed the first set of forms. Of these, 551 (62.75%) returned and completed the second set of forms. Cleaning of the data and eliminating respondents with excessive missing values, resulted in a final sample of 533, 153 of who made purchases that could potentially be classified as impulsive.

The demographic profile of this sample is similar to previous studies that had been conducted at this mall, and, with the exception of age, similar to the community within which the study was conducted. Demographics are presented in Table 1.

TABLE 1

Demographics of the Sample

Characteristic Frequency Percentage

Gender Female 369 68.0 Male 174 32.0

Race Caucasion 394 74.1 African-American 119 22.4 Asian 8 1.5 Other 9 1.7 Unable to tell 2 0.4

Age Under 18 14 2.6 18-22 182 33.2 23-30 117 21.4 31-40 96 17.5 41-50 78 14.2 51-60 35 6.4 61 or over 26 4.7

Marital Status Single 285 51.8 Widowed 9 1.6 Married 218 39.6 Divorced 38 6.9

Education Less than High School 23 4.2 High School 98 17.2 Some College 261 47.5 College Graduate 91 16.5 Post Graduate Work 77 14.0

Income Under $15,000 129 25.4 $15,000-$30,000 129 25.4 $30,001-$45,000 70 13.8 $45,001 -$60,000 66 13.0 $60,001 -$75,000 42 8.3 $75,001 or over 72 14.2

Impulse Buying

Measures

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Items in all scales used seven-point agree-disagree statements with the exception of the impulse purchase measure. We decided to treat this variable as a three-point measure, in which a '3 ' clearly represented an impulse purchase, a '2 ' represented an unplanned purchase involving less impulsiveness (i.e., low spontaneity and non-reflectiveness), and a ' 1' represented a reminder purchase, a planned purchase, or no purchase. The level of impulsiveness was measured with an impulsivity scale (Jeon, 1990). This seven-point agree-disagree scale had five items, all of which were retained, with a coefficient alpha of .70. Examples of the items include, "When I bought (the item), I felt a spontaneous urge to buy it," and, "When I saw (the item), I just couldn't resist buying it." This scale was not included in the measurement or structural model. A mean score of 4 or above represented positive impulsivity.

Thus, in the sample, 101 individuals, classified as making an impulse purchase, had made at least one unplanned purchase that was rated above the mean on the impulsivity scale. They received a score of '3. ' Fifty-two individuals were classified as having made an unplanned purchase that was rated below the mean on the impulsivity scale. They received a score of '2.' The final group, composed of 380 individuals, did not make an unplanned purchase and received a score o f ' 1' Given the categorical nature of this variable, the poly- choric correlation matrix was used for these analyses (J6reskog and S6rbom, 1993).

The shopping enjoyment items were from Ellis (1995). Four items remained after our item deletion process based on the measurement model. The IBT scale came directly from Weun, Jones, and Beatty (1998). Three items remained after item elimination.

The time available items were drawn from Jeon (1990), Beatty and Smith (1987), and Iyer (1989). The money available items were a modification of items from Beatty and Tal- pade (1994). The felt urge items were drawn from discussion in the literature (e.g., Jeon, 1990; Rook, 1987; Weun, Jones, and Beatty, 1998). Three items remained in both the time and money available scales, while four remained in the felt urge scale after item deletion based on pretest results and the measurement model.

In-store browsing items were drawn from Jeon (1990), as well as from the conceptual discussion in Bloch et al. (1986, 1989), since there were no browsing scales available. Three items remained after elimination procedures based on pretest results and the measurement model. The affect items were drawn directly from the PANAS scale (Watson et al., 1988). After item deletion, four items remained for positive affect and three for negative affect.

RESULTS

Measurement Properties

The properties of the items of the nine scales (four exogenous and five endogenous) in the model and the hypotheses were assessed using the LISREL 8 structural equation analysis package (J6reskog and S6rbom, 1993), in combination with the processes recom-


mended by Sethi and King (1994) and Anderson and Gerbing (1988). The adequacy of the individual items and the composites were assessed by measures of reliability and validity. The composite reliability, as calculated with LISREL estimates, is analogous to coefficient alpha and is calculated by the formula provided by Fornell and Larcker (1981). In this instance, the unidimensionality of each construct was assessed individually (Sethi and King, 1994), and then submitted to the overall measurement model of Anderson and Gerb- ing (1988).

Further, convergent validity was assessed by the significance of the ~ij loadings (Ander- son and Gerbing, 1988), while discriminant validity was assessed by comparing the variance extracted to the square of the correlation (~2) between the two latent variables. Evidence of discriminant validity is provided when the variance extracted estimate exceeds the indicated correlation coefficient.

After assessing the individual characteristics of the constructs, assessments of the initial measurement model were as follows: ~2399 = 812.77 (p = 0.0); GFI = .91; AGFI = .89; CFI = .92, and the NNFI = .91. As suggested by Anderson and Gerbing's (1988) two-stage process in model analyses, items were deleted to improve the measurement model fit before moving on to test the structural parameters hypothesized.

The items that remained after this step are indicated in Table 2. All composite retiabili- ties were above .7 with the exception of time available. The overall fit of this final measurement model was X2315= 561.94 (p = 0.0); GFI = .93; AGFI = .91; CFI = .95, and NNFI = .93. Further, the indicators of residuals, RMR (root mean square) and RMSEA (root mean square error of approximation) were .042 and .038, respectively. Additionally, discriminant validity was established for all pairs of scales by comparing the variance extracted to the square of the correlation between the two latent variables.

In summary, although some of the indicators fall below desirable levels, this research clearly falls into the category of initial, more exploratory work, where greater flexibility is permitted and lower levels of reliability and validity are to be expected (Bollen, 1989; Nun- nally, 1978). We, therefore, concluded that the data were sufficient to permit reasonable conclusions to be drawn on the basis of the structural model.

The Structural Model

Figure 2 presents the final model with the path coefficients and the associated t-values for each of the hypothesized paths. In the analysis, the correlations between time and money available, and between shopping enjoyment and IBT constructs were allowed to be estimated in the • matrix. Further, one cell in 08, that between the second time variable and the third money variable, was freed. The cells in the ~ matrix were freed for conceptual reasons; that is, time and money available represent situational variables, and shopping enjoyment and IBT are individual characteristics. The cell in 08 was freed because the initial diagnostics indicated a relationship between these two items. The actual correlation between them was only .17; although significant (t-value = 4.76), not large enough to be the result of response effects.

Impulse Buying

TABLE 2

Item Measurement Properties

181

Item~Construct Standardized Loading T-Value Composite Reliability

Urge to purchase I experienced a number of sudden urges to buy things I had not planned to purchase on this trip. On this trip I saw a number of things I wanted to buy even though they were not on my shopping list. I experienced no strong urges to make unplanned purchases on this trip. a On this trip, I felt a sudden urge to buy something Positive Affect Excited Enthusiastic Proud Inspired Negative Affect Distressed Upset Irritable Browsing The percent of t ime I spent just looking around on the trip was fairly high. I would say that I was primary "just looking around" on this trip. I devoted most of my attention to the items I planned to buy on this trip. a Shopping Enjoyment Shopping is a waste of time. a Shopping is not a way I like to spend any leisure time. a Shopping is not entertaining to me. a Shopping is not one of my favorite activities, a Time Available I have l imited t ime available to me for this particular shopping trip. a I am not rushed for t ime on this shopping trip. The amount of t ime pressure I feel on this shopping trip could be characterized as: ab Money Available I do not feel I can afford to make any unplanned purchases on this trip. a I am on a tight budget whi le on this shopping trip. a I feel that I have enough extra money on this shopping trip so that I can splurge a little if I find something I really like. Impulse Buying Tendency When I go shopping, I buy things that I had not intended to purchase. I am a person who makes unplanned purchases. It is fun to buy spontaneously.

.77 19.52

.70 17.14

.55 12.82

.80 20.55

.73 18.11

.83 21.31

.68 16.51

.66 15.94

.65 14.64

.76 17.16

.75 16.80

.67 14.13

.75 15.65

.60 12.75

.62 14.30

.68 16.19

.79 19.50

.75 18.25

.70 13.48

.56 11.11

.62 12.22

.71 15.08

.78 16.42

.53 11.29

.85 21.60

.86 22.09

.58 13.77

.82

.76

.72

.80

.66

.72

.81

Notes: a. Item was reversed scored. b. Response format was "None" to "Very High."


FIGURE 2

Final Structural Model

Twelve of the fourteen hypothesized paths were statistically significant and in the direction predicted. The overall model fit statistics indicate that the model fits the data within established guidelines: E2335 = 607 (p-value > 0.0); GFI = .92; AGFI = .91; CFI = .94; NNFI = .93; RMR = .05; and, RMSEA = .04. Based on an examination of the modification indices, we found that there was only one unspecified linkage that proved to be significant. This path is the path between negative affect and impulse purchase (13 = -.12; t- value = -2.46). This relationship will be addressed in the discussion section.

There were five paths hypothesized among the endogenous variables in the model, four of which were predicted to be positive, and one negative. All but one of these paths was in the expected direction and that one, from negative affect to felt urge is not statistically significant (H4; 1~ = .04). As expected, in-store browsing increases the felt urge to buy impulsively (Hlb; 13 = .25; t-value = 4.60), as does one's positive affect (H3; [3 = .29; t-value = 5.74). Positive affect is also directly affected by in-store browsing, as predicted by H la (13 = .14; t-value = 2.62). And, as expected, felt urge had a significant effect on making an impulse purchase (H2; 13 = .42; t-value = 8.51).

Next, results related to the effect of the exogenous variables will be discussed. Enjoy- ment of shopping, an individual difference variable, was hypothesized to increase both positive affect and in-store browsing. Both direct effects are positive; the path from shopping enjoyment to positive affect is y = .30 (t-value = 5.70) while that from enjoyment to

Impulse Buying 183

in-store browsing (y = .03) did not have a significant t-value associated with it. Thus, the data support H5b, but not H5a. The tendency to purchase impulsively was hypothesized to have positive paths to both in-store browsing (H6a) and the felt urge to buy impulsively (H6b). Both of these hypotheses were supported. The path from the IBT to in-store browsing was .20 (t-value = 3.33) and from IBT to felt urge, the path was .30 (t-value = 6.12). Analysis of the modification index for the path directly from IBT to the impulse purchase construct demonstrated that a direct path would be of insignificant magnitude (the modification index was 0.14).

We had hypothesized that the time available for this particular shopping trip would impact the amount of time spent browsing (H7a), and time available did have a positive and significant, direct effect on the amount of in-store browsing (y = .21; t-value = 3.40), while also decreasing one's negative affect (H7b; y = - . 15; t-value = -2.39).

The final exogenous variable, the perception of having money, or financial resources, available for this shopping trip was hypothesized to increase both the impulse purchase itself (H8c) and the perception of positive feelings (H8a), while it was predicted to have an inverse relationship with negative affect (H8b). Each of these relationships was supported, with each of the specified paths being statistically significant: from money available to impulse purchase (y =. 16, t-value = 3.41 ); from money available to positive affect (y =. 18, t-value = 3.47); and, from money available to negative affect (y = -. 17, t-value = - 2.83).

Each of the dependent variables has associated with the structural equation that predicts it, an R 2 value, reflecting the proportion of variance in that variable explained by the equation. The R 2 for our ultimate dependent variable, the prediction of impulse purchasing was .20. As we pointed out in our literature review, however, the prediction of a single behavior is difficult. The R 2 for felt urge to buy impulsively, perhaps a truer measure of this model, was .32, leading us to conclude that this model does provide considerable insight in regard to impulsive purchase behavior.

DISCUSSION

General Discussion

Our objective was to model the impulse buying process, focusing on important precursors. Drawing from current literature and theory in the area, we proposed a series of hypotheses involving 14 paths. Using data collected in the shopping environment, both before and after a shopping experience, all but two of these paths were supported and the model fit within established criteria.

We were unable to find previous work in the literature that attempts to model the impulse buying process. Thus, this study provides some preliminary groundwork for future studies examining this important issue. The superior performance of the model when felt urge to buy impulsively was the final variable, rather than the actual impulse purchase, attests to the difficulty of presuming that behavior at any one point in time can be accurately mod- eled. However, since much of the past research in the area focused on respondents' recall


of previous impulse buying experiences, we believe that the measurement of actual behavior in this study provides real-world relevance to this research area.

Discussion of Specific Findings

In-Store Browsing

In-store browsing appears to be positively affected by one's available time and one's impulse buying tendency, and in turn, has a positive impact on one's positive feelings and impulse buying urges. Noting the relevance of browsing, it is surprising it has received so little attention. Perhaps this is because the variable is a perception or recall of actual behavior rather than a truly latent construct, such as an attitude. Thus, it would tend to suffer from the measurement problems of behaviors referred to earlier (Epstein, 1980). In any case, we have provided a useful operationalization of the construct, as well as showing its potential usefulness in understanding impulse buying. Jarboe and McDaniel (1987, p. 47) suggest that not only are browsers important to the study of impulse buyers, they "are also likely to be effective 'word-of-mouth' advertisers, peer influencers, and trend setters, especially for socially visible products."

Felt Urge to Buy Impulsively and Impulse Purchase

We believe that the distinction made here between urge and impulse purchase is important. Our model assessment provided evidence of the distinction between these two constructs (although highly correlated), while the literature and our definitions provide further justification for the distinction. The felt urge or desire to buy derives from the physical proximity with the object, due to in-store browsing, a tendency to engage in impulse buying, and positive feelings experienced while shopping.

Further, it is this urge which precedes the actual impulse purchase. There has been little effort put forth to describe or model urges or desires with a few exceptions (cf. Hoch and Loewenstein, 1991). Thus, our efforts should aid research in this area. Felt urge appears to be an important intervening variable between an actual impulse purchase and several precursors: browsing, positive affect, and possessing a tendency to engage in impulse buying. Further, feeling like one has adequate financial resources directly affects impulse purchasing, as well as indirectly affecting it through the influence of positive affect on felt urges.

Individual Difference Variables

Our study indicates that individual difference variables do contribute to the impulse buying process. Thus, it is important to go beyond just an examination of the situational variables affecting impulse buying. Both of our individual difference variables played important roles in this process, even though neither has received much attention in the lit-

Impulse Buying 185

erature. It is one's enjoyment of shopping that aids in producing a positive feeling in the shopping environment, which in turn influences one's felt urges to buy impulsively. One's tendency to engage in impulse buying tends to produce more in-store browsing as a shopping strategy, as well as to directly affect the number of urges experienced to buy impulsively while browsing.

The failure of shopping enjoyment to impact in-store browsing was disappointing. The- oretically, these variables should be linked. We think the problem may have been the result of several factors. First, perhaps this occurred because of the lack of a clean distinction between browsing and shopping. We operationalized browsing primarily as "just looking around." This may have a negative connotation to "true shoppers," who may feel all shopping has some purpose even if it isn't related to an immediate purchase. Further, this lack of effect indicates that one's general proclivity to shop may not predict how much one shops on any particular day, referring back to our earlier point about the difficulty of predicting single behaviors. The situational variables or various possible tasks involved in a specific shopping trip may more prominently influence browsing behavior that day.

Situational Variables

Our situational variables acted as expected. Time available, an exogenous variable, is a fairly known quantity for the individual upon entering the shopping environment. It influences the length of time the shopper will stay in the environment, and appears to especially influence his/her discretionary use of time in regards to browsing. Further, available resources tend to affect individuals' moods at the time, with lack of time and money producing negative affect (or frustration). Additionally, perception of available money produced positive feelings and a positive influence on actual impulse purchasing.

Affect Variables

It can be suggested that one comes into a shopping environment in a particular mood, engages in emotional reactions in the environment while shopping, and leaves the environment in a similar or changed mood. With our affect measures, captured after the shopping experience and asked in reference to how people felt while shopping, we tried to obtain a sense of shoppers' combined pre-shopping mood and emotional reactions in the shopping environment. We did not measure pre-shopping mood because in an earlier unpublished study by the authors and data collected for a Ph.D. dissertation (Jeon, 1990), we were unable to obtain discriminant validity between the two reference points. Also, given our concern about the possibility of an interactive testing effect on the post-shopping affect measures, we chose not to measure affect prior to the shoppers' buying experiences.

In our study positive affect was affected by one's shopping enjoyment, in-store browsing, and money available as expected, and produced more felt urges to buy impulsively, as anticipated. On the other hand, negative affect did not influence impulse buying urges. Thus, the strong effect of positive affect on urge is consistent with previous findings sug- gesting that positive moods produce greater approach behavior (in this case, the experienc-


ing of urges). As we noted in the results section, however, negative affect did have a significant and negative loading on impulse purchase in a respecified model. Thus, perhaps negative affect tends to reduce an individual's tendency to actually act on their urge. These results require further study since this linkage was not specified in the original model and thus, were not included in the final model presented here. Given the lack of clear findings in the past on negative affect, the lack of clear, interpretable results is not surprising.

Conclusions, Limitations, and Future Work

Obviously, this research has the traditional limitations associated with survey research, such as selection error, measurement error, interviewer effects, and non-response error. There are also the concerns involved with a pre- and post-measurement design, such as pre- measurement effects and mortality effects. However, this approach allowed us to capture measures at two points in time, which was critical to the study design and also was more amenable to the use of structural equation modeling.

Additionally, another concern was the time pressure of the respondents. The shopping environment is a harried environment and the scales somewhat tiresome, which could introduce considerable noise to our data. We attempted to carefully supervise the activities of our respondents and interviewers but we felt that these factors may have affected the quality of our data.

We noted potential measurement problems throughout this study. It is difficult to obtain measurements of all of these variables at the most appropriate time and in the most appropriate setting. For example, we chose not to measure pre-shopping mood, given some of our previous difficulties distinguishing this variable from affect in the shopping environment. Even then, we measured this affect after the shopping experience rather than during the shopping experience. Also, not all variables were captured. For example, we did not explore whether there were parties accompanying the respondent, how structured the tasks were for the shopping trip at hand, or the influence of important variables in the shopping environment, such as sales or helpful sales clerks. These omissions and measurement problems indicate potential problems in this study and in the study of these concepts in general. It is probably the difficulty involved in dealing with problems of this type that has discour- aged researchers from exploring these topics.

Further, we have assumed causality here based on theory, analysis, and the temporal sequencing of the data. However, only experimentation provides unequivocal assessment of causality. Experimental designs, using mock stores or catalogs (i.e., where in-store browsing becomes catalog browsing), could provide additional evidence about the influence of the variables examined in this study.

Another issue of concern here is that we concentrated on the main effects of the variables examined in the model. There are a number of possible interactions, which, in fact, may be more interesting than the main effects. Our reasoning at this point was to establish a good base model from which important main effects could be assessed first (cf. Aiken and West, 1991; Keppel 1982). As several reviewers pointed out, however, there are a number of important interactions in this area worthy of study. For example, the interaction between

Impulse Buying 187

IBT and the situational variables on browsing or urge may be relevant. That is, money available may be more relevant to high IBT's than to low IBT's? How do the situational variables interact with felt urge to produce impulse buying? How do they interact with shopping enjoyment to affect browsing? Perhaps, this interaction would explain why shopping enjoyment and browsing weren't associated in the model. When we began consider- ing the number of possible interactions that could be tested in the model, we were surprised by the possibilities. Given the relevance of interactions in explaining behaviors (Punj and Stewart, 1983), we believe this is an important avenue to pursue.

Further, a number of these constructs need additional attention in regards to operationalization. Many of these constructs are relatively new to the field and need further scale development work; for example, shopping enjoyment, in-store browsing, and the felt urge variable. The impulse purchase operationalization was unique and perhaps, only slightly advanced from previous attempts. However, we believe that this measure, which incorpo- rates the psychological notion of impulsivity, is better than other current operationaliza- tions and continues to move us in the correct direction.

Additionally, our sample, conducted in one regional mall, is obviously neither truly ran- dom nor necessarily representative of any larger population. Given our interest in relationships between variables rather than population descriptions, this may not be a major problem in this exploratory, single-study effort but should be clearly noted (Calder, Phil- lips, and Tybout, 1982). Future studies need to assess the generalizability of these findings to other groups in other contexts. For example, how similar is the impulse buying process in the mall environment to the process involved in food shopping or in other contexts? Are individuals who tend to be heavy impulse buyers in the mall also heavy impulse buyers in grocery stores or other settings? Also, how does the impulse buying process differ when shopping from one's home, with a catalog, computer, or home shopping network?

There are a number of unanswered questions in this area. Rook and Gardner (1993) indicate that the study of impulse buying is in a relatively immature state compared to other areas (such as attitude research). For example, what strategies do shoppers use to repress the urges felt to buy impulsively and which strategies are most effective? Are impulse buyers more vulnerable to store atmospherics or to others in the environment (Rook and Gard- ner, 1992)? In what ways is positive affect engendered most easily in shoppers? How are the experiencing of urges and actual impulse buying influenced by companions in the shopping environment? Are high impulsives more likely to make impulse purchases regardless of mood than others, as suggested by Rook and Gardner (1993)?

Also, we need to know much more about the consequences of impulse buying. For example, what are the effects of impulse buying on one's post-shopping affect levels? When and how do guilt or negative reactions to the buying experience affect respondents' perceptions of the experience, as well as their satisfaction and future purchasing and shopping strategies?

Finally, given the relevance of in-store browsing noted here, research efforts should be focused on this behavior. Bellenger and Korgaonkar (1980) suggest an exciting shopping experience and the appropriate atmospherics are keys to greater in-store browsing. Unfor- tunately, little research attention has been devoted to what creates in-store excitement and stimulating atmospherics. Recent interest in hedonic shopping should be helpful in the further study of this topic (Babin, Darden, and Griffin, 1994).

188

Managerial Implications

Journal of Retailing Vol. 74, No. 2 1998

Finally, we think it is useful to ask what are some of the managerial implications of our findings. For example, given the strong influence of available time on in-store browsing, retailers might attempt to influence the time shoppers think they have available in the store. They might do this by making shopping more efficient, i.e., by aiding the shopper in find- ing his or her planned items more quickly. They might also positively influence the money shoppers feel that they have available to spend by providing easy credit lines or discounts tied to opening a charge card. Since consumers' windfalls can often be predicted, retailers should tie sales events to paydays or to tax return periods.

Noting the positive influence of affect and browsing on urges and impulse purchases, retailers need to constantly work at creating positive shopping environments. Interesting displays and events, appropriate aromas and lighting, and helpful, friendly salespeople encourage shoppers to browse longer and to spend more. The variables we examine here are not new, but retailers need to constantly analyze how well they are addressing these issues.

Retailers also have the opportunity to encourage shoppers with desirable individual difference scores. For example, the profiles of high impulsives or recreational shoppers may be identified, so that promotions and events can be targeted at these individuals. In current times, where time pressure is of critical importance to shoppers and shopping alternatives outside of traditional retailing are experiencing phenomenal growth, we believe these questions are of extreme relevance to traditional retailers.

Acknowledgment: This research was partially supported by a summer research grant to the first author provided by the Culverhouse College of Commerce and Business Adminis- tration, The University of Alabama. The authors wish to thank Del Hawkins, Michael A. Jones, Morris Mayer, Marsha Richins, Brian Wansink, James B. Wilcox, the editor, three anonymous reviewers for their helpful comments and suggestions during the development of this paper and Jung-Ok Jeon for his early work on this topic with the first author.

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Impulse buying: Modeling its precursors