Pleasure or utility? Time planning style and Web usage behaviors

PLEASURE OR UTILITY? TIME PLANNING STYLE AND WEB USAGE BEHAVIORS JUNE COTTE, TILOTTAMA G. CHOWDHURY, S. RATNESHWAR, AND LISA M. RICCI

T

he present research focuses on time planning style, an individual’s habit-

ual approach to time management, in relation to the use of the Web. We theorize and provide empirical evidence that highly analytic versus sponta-

JUNE COTTE is Assistant Professor of Marketing and the MBA 1983 Faculty Fellow, Ivey Business School, University of Western Ontario, Canada; e-mail: [email protected]

neous planners are more likely to seek utilitarian rather than hedonic benefits from Web use. This pattern is associated with downstream relationships

TILOTTAMA G. CHOWDHURY is Assistant Professor of Marketing,

between the types of benefits sought and various Web usage behaviors (e.g., exploratory, entertainment, information search, and electronic shopping).

Lender School of Business, Quinnipiac University, Hamden, CT; e-mail: [email protected]

A notable finding is that both planning styles are positively associated with electronic shopping, but due to different types of benefits that are sought.

S. RATNESHWAR holds the Bailey K. Howard Chair of

Implications are discussed for marketers’ customization of Web page content based on segmenting the possible audience on time planning styles.

Marketing at the University of Missouri-Columbia; e-mail: [email protected]

© 2006 Wiley Periodicals, Inc. and Direct Marketing Educational Foundation, Inc.

LISA M. RICCI JOURNAL OF INTERACTIVE MARKETING VOLUME 20 / NUMBER 1 / WINTER 2006 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/dir.20055

is an independent marketing researcher in West Chester, PA

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The unique characteristics of the World Wide Web afford new ways for consumers to interact with each other, with firms, and with the electronic environment itself (Alba et al., 1997; Burke, 1997, 2002; Hoffman & Novak, 1996; Novak, Hoffman, & Yung, 2000; Parasuraman & Zinkhan, 2002; Peterson, Balasubramanian, & Bronnenberg, 1997; Varadarajan & Yadav, 2002). Accordingly, the Web can be used as a medium for engaging in many diverse types of behaviors: merely exploring, searching for specific information, entertaining oneself, or shopping (Parasuraman & Zinkhan, 2002). Such Web usage behaviors, in turn, are likely to be motivated by the benefits from using the Web, hedonic as well as utilitarian (Childers, Carr, Peck, & Carson, 2001; Korgaonkar & Wolin, 1999). Notwithstanding, prior empirical research has generally focused either on consumer motivations for using the Web (e.g., Childers et al., 2001) or on the actual behaviors exhibited by consumers while on the Web (e.g., Emmanouilides & Hammond, 2000), but not on the link between them (for an exception, see Korgaonkar & Wolin, 1999). Recently, researchers are beginning to recognize the role of individual-difference variables in the benefits sought from Web usage as well as Web usage behaviors (see, e.g., Burke, 2002). For example, Novak et al. (2000) considered individual-level issues of skill, control, and challenge in using the Web while Mathwick and Rigdon (2004) investigated constructs such as flow and perceived play. Although not much empirical research has been done in this area, it is becoming obvious that individual differences among consumers may help explain many important aspects of Web behavior. Our research examines what we believe to be an important explanatory variable in understanding such individual differences; namely, how people habitually manage their time. Specifically, we examine individual propensity to engage in extensive time planning, a construct we term time planning style (see Cotte & Ratneshwar, 2000, 2001, 2003; Cotte, Ratneshwar, & Mick, 2004). The present research objective is to explore the relationships between variations in individuals’ time planning styles and how and why they use the Web. We develop hypotheses for relationships between time planning style and Web usage benefits sought, and then between Web usage

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benefits and Web usage behaviors. Using survey data, we propose and test a fully mediated model. In the final section of the article, we review the contributions and implications of our work, and propose areas for future study.

TIME PLANNING STYLE The starting point for our theorizing is the observation that all behavior takes time, and online behavior is no exception. But when it comes to time management, people vary considerably in how they approach (or avoid) advance planning (Bond & Feather, 1988; Cotte & Ratneshwar, 2000, 2001). We define time planning style as the habitual manner in which an individual organizes and plans his or her time. Time planning style is conceptualized to vary on a continuum from a highly analytic style where time management occurs in terms of small, discrete time units and the individual has a strong preference for time organization, to a more spontaneous orientation where temporal categories are loose and unstructured (see Cotte & Ratneshwar, 2000; Cotte et al., 2004). Highly analytic planners tend to keep strict account of their time and often pre-allocate future discretionary time. Thus, for example, such people might strongly prefer to plan their weekend activities several weeks ahead of time; in contrast, other individuals might opt for last-minute spontaneity. As a result, time planning style could influence not just the scheduling of activities but even the choice of one’s activities. As an illustration of possible relationships between time planning style and Web usage, consider two individuals, Jack and Mary. Jack is at the analytic end of the time planning style continuum, valuing time as a limited resource that should be planned and used carefully. While making an online purchase, Jack’s motivations for use of the Web are based on utilitarian benefits; he plans his time extensively, and probably would not surf the Web for intrinsic enjoyment of the process itself but would prefer to finish his predetermined task in a time-efficient manner. In contrast, Mary has a spontaneous time planning style. Once Mary begins Web shopping, she may be easily distracted from her task as she clicks on interesting and fun hyperlinks to other sites. While she does want to make a purchase, and ultimately might, she also wants to enjoy her online shopping experience.

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Note that time planning style is different from selfregulatory ability, as outlined in Kuhl’s (1994a, 1994b) action control theory. Kuhl posited a trait affecting one’s ability to maintain and enact behavioral intentions that pertains to how well a person (a) avoids procrastination, (b) blocks out alternative paths of actions, and (c) perseveres with a task once undertaken (for a marketing application, see Babin & Darden, 1995). In comparison, time planning style refers to the amount of advance planning a person undertakes on a regular basis, not whether the individual sticks with these plans once made; thus, conceptually time planning precedes self-regulation.

BENEFITS SOUGHT FROM WEB USE The benefits people seek from using the Web can be broadly categorized into (a) hedonic consumption benefits obtained when the Web is used for the enjoyment of the online experience itself, and (b) utilitarian consumption benefits resulting from consciously achieving a specific task via interaction with the Web. Hedonic consumption benefits are often defined by the experiential view, which argues that consumers seek fun, amusement, and sensory stimulation in return for expending resources such as time and money; this view considers consumption in terms of the experience itself rather than the object of consumption (Holbrook & Hirschman, 1982). The hedonic benefits of using the Web are more subjective and personal than their utilitarian counterparts; the former are based on fun and playfulness via interacting with the Web whereas the latter focus on objective accomplishments (Babin, Darden, & Griffin, 1994; Holbrook & Hirschman, 1982). Indeed, it has been shown that pleasure-oriented consumers typically enjoy interacting with the Web just for the sake of the interaction itself (Childers et al., 2001). Web interactions thereby become a type of consumer play (Deighton & Grayson, 1995; Grayson, 1999). This may be the case especially in Web-based games, or to a lesser extent, with e-mail or chat. Unlike the enjoyment and playfulness implicit in hedonic benefits, utilitarian benefits are based on a more rational view of consumer behavior. Utilitarian consumer behavior is thought to be task-focused, with ultimate satisfaction coming from task achievement

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rather than the nature of the experience itself (Babin et al., 1994). Consumers seeking utilitarian benefits would tend to use the Web for what they perceive as objective reasons, and would often have preconceived expectations of what they wish to accomplish when they go online. As discussed further in a subsequent section, we adapted the shopping values scale developed by Babin et al. (1994) to assess hedonic and utilitarian benefits sought from Web use. Note that our hedonic and utilitarian benefits constructs pertain to the use of the Web in general whereas the original Babin et al. construct and scale focused specifically on shopping and purchase situations. Conceptually, therefore, the present framework assumes that both time planning style and Web usage benefits sought not only impact purchase situations but also influence nonpurchase use situations (e.g., obtaining news or playing games online). Further, and consistent with Babin et al. (1994), our research conceptualizes hedonic and utilitarian benefits as two different types of benefits, not as the opposite extremes of a single continuum. Both types of benefits may be sought in a given situation, although at times the presence of one may inhibit the other (Babin et al., 1994; Griffin, Babin, & Modianos, 2000). For example, television-program content is often either mainly educational (i.e., it affords utilitarian benefits) or mainly entertainment-oriented (i.e., it affords hedonic benefits), such that the two benefits are likely to be somewhat negatively correlated in the television-viewing environment. Still, there are many exceptions to this pattern (e.g., the award-winning program Sesame Street on public television that manages to entertain as well as educate children), thereby implying that the two types of benefits are distinctly different in nature, not mere opposites.

WEB USAGE BEHAVIORS This research focuses on four prevalent Web usage behaviors: exploratory behavior, entertainment, electronic shopping, and information search (see Korgaonkar & Wolin, 1999). Exploratory behavior can be categorized as curiosity-based, variety-seeking, or risk-taking (Raju, 1980); the first two are the ones that are most consistent with our definition of exploratory behavior on the Web. Our construct refers

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to the manner in which a person actively seeks out new experiences on the Web as a form of cognitive stimulation (see Baumgartner & Steenkamp, 1996). Consumers who engage in exploratory behavior on the Web enthusiastically seek out new sites to explore and readily click on links to check out unfamiliar areas of the Web (Hoffman & Novak, 1996; Novak et al., 2000). The use of the Web for entertainment behavior implies leisure activities such as participating in chat rooms, playing online games, and so on. The use of the Web for electronic shopping refers to the one-time purchase of a product in a specific category as well as repeated commercial transactions with a firm. Finally, online information search behavior refers to the use of the Web to find very specific information (e.g., to help make an offline purchase decision, to catch up on the news, etc.). The Web reduces search costs for both price and quality information, and can make comparisons of choice alternatives easier and more transparent (Alba et al., 1997; Lynch & Ariely, 2000; Varadarajan & Yadav, 2002).

HYPOTHESES Relationships Between Time Planning Style and the Benefits Sought From Web Use We propose that time planning style is an important antecedent to benefits sought through the use of the Web. Consumers who are hedonically motivated to use the Web are enjoying use of the Web for the sake of the experience itself; the Web affords playful behavior. Achieving a truly intrinsic, hedonic experience through Web usage on any given occasion may even require losing one’s sense of time spent in the activity (Novak et al., 2000). Accordingly, such a hedonic experience would be relatively unlikely for people who are at the analytic end of the time planning style continuum; such individuals highly value discrete time allocations and regard time as a resource to be managed carefully (Cotte & Ratneshwar, 2000, 2001, 2003). Analytic planners tend to focus on specific tasks, and they strongly desire a feeling of certainty and closure when it comes to time-consuming activities. Such consumers are unlikely to find intrinsic enjoyment in the use of the Web or seek out the Web as a medium of playful consumption.

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Time planning style also is relevant in considering utilitarian benefits from Web usage. Being highly time conscious, analytic consumers are likely to preplan their Web tasks prior to going online, and only accomplish those planned tasks while online. Given their task-oriented mentality and conscientious use of time, people with highly analytic time planning styles will likely want to use the Web mainly for utilitarian benefits (Cotte & Ratneshwar, 2001, 2003). H1: Individuals with an analytic (vs. spontaneous) time planning style will be (a) less likely to seek hedonic benefits from Web use and (b) more likely to seek utilitarian benefits from Web use.

Relationships Between the Benefits Sought From Web Use and Web Usage Behaviors Investigation of the relationships between time planning style and the hedonic as well as utilitarian benefits sought from Web use is one of the two main objectives of this research. The complementary objective is to empirically examine downstream links between these two types of benefits and specific Web usage behaviors. Broadly stated, the present research position assumes that consumers who actively seek a sense of playfulness and other hedonic experiences from using the Web are likely to behave differently online when compared to those who are motivated by a utilitarian, “get-things-done” orientation (Childers et al., 2001; Hoffman & Novak, 1996). Specifically, those who approach the Web for a pleasurable experience and regard the online experience of the Web as an end in itself will be more prone to explore unfamiliar and novel sites and click-through to an increasing variety of new sites. Further, consumers who desire playfulness and hedonic gratification will be more inclined to approach the Web as an opportunity to engage in games or other sorts of social interaction with others (e.g., instant messaging, participating in chat rooms). In addition, as Childers et al. (2001) noted, there are a variety of types of electronic shopping available to consumers, from very basic, order-form style sites to heavily interactive and sensory-laden sites. For example, the Lands’ End site (www.landsend.com) allow one to virtually try on clothing and also integrate friends into the shopping process. Sites that integrate these types of sensory

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and social aspects recognize the importance they can have to some consumers, especially those who are motivated by hedonic benefits. Thus, summarizing: H2: Hedonic benefits sought from Web use will be positively related to (a) exploratory behavior, (b) entertainment usage behavior, and (c) electronic shopping behavior on the Web. Next, the downstream effects of seeking utilitarian benefits are considered. Consumers looking for utilitarian benefits will likely regard the Web simply as a means of accomplishing specific tasks. They go online in a purposeful manner and would not likely be diverted by miscellaneous hyperlinks and clickthrough banner ads that are tangential to their original purpose. Thus, consumers who are motivated by utilitarian considerations are unlikely to be curious about novel Web sites and may have little desire to explore the Web simply on the off chance that something useful might turn up. Similarly, utilitarian consumers for whom the Web is primarily a medium for getting things done (e.g., paying bills, buying or selling stocks) may have difficulty in viewing the Web as an entertainment vehicle (Childers et al., 2001). Thus, a utilitarian orientation to using the Web may be antithetical to entertaining oneself while online. Further, with respect to electronic shopping, some consumers buy products online simply in the interests of efficiency and low price (Burke, 2002; Childers et al., 2001; Mathwick, 2002). Thus, consumers who seek such utilitarian benefits might shop on the Web not because of the sensory experience but because online shopping affords convenience and/or saves them money. For example, utilitarian consumers may primarily patronize sites that enable comparison shopping, speedy transactions, or low prices. Recall we hypothesized earlier that seeking hedonic benefits would be positively related to online shopping. In keeping with our previous assertion that hedonic and utilitarian benefits are separate constructs, not opposite ends of a continuum, we reason that utilitarian benefits also may be positively related to electronic shopping. Thus, electronic shopping can be motivated by hedonic as well as utilitarian considerations. Finally, since utilitarian benefits from Web use are task-related, and finding information on a specific topic is one such task, such benefits should be linked

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to information search behavior. For example, consumers who need information, whether it be information for its own sake (e.g., lottery results, sports results) or information to be used in another decision (e.g., expert product ratings, price or store comparisons) can go to the Web to get quick and efficient answers. H3: Utilitarian benefits sought from Web use will be negatively related to (a) exploratory behavior and (b) entertainment usage behavior, and positively related to (c) electronic shopping behavior and (d) information search behavior on the Web. Our model, which is depicted in Figure 1, implies a fully mediated set of relationships. Time planning style has no direct effect on Web usage behaviors, but affects these behaviors through influence on the types of benefits sought from going online. That is, we posit that hedonic and utilitarian benefits sought mediate the relationships between (a) time planning style and (b) exploratory behavior, entertainment behavior, information search behavior, and electronic shopping. Benefits sought (hedonic and utilitarian) are the key “why” variables in our model. Simply demonstrating direct links from time planning style to various Web usage behaviors might be descriptive, in the sense that we might conclude, for example, that analytic planners are less likely to go online for entertainment; however, in that instance we would not have an understanding of why this relationship exists. Hence, our argument for a mediated model makes an important theoretical point: The benefits sought from Web usage likely explain the relationship between individual differences in time planning style and Web usage behaviors.

METHOD Survey Sample, Instrument, and Measures Survey respondents were 310 residents of the northeastern United States. They included undergraduate students, evening MBA students, and office staff; 39% were male and the average age was 25.5 years (range ⫽ 18–54). Self-reported hours of Web usage per week was: 6.5% of respondents, 1 hr or less; 30%, 1 to 5 hr; 30.3%, 5 to 10 hr; and 33.2%, more than 10 hr.

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y1

x7

x6

x5

x4

Exploratory Behavior

y3 .73***

Hedonic Benefits Sought

x2

y4

.57***

.18*

x1

y2

-.31***

Entertainment

y5

Information Search

y6

Time Planning Style .41***

-.32*** -.50***

x3 Utilitarian Benefits Sought

.49***

.21* x8

x9

Electronic Shopping

y7 y8

Notes: 1. Asterisks denote *p < .05; ** p < .01; *** p < .001. 2. The scale for time planning style is scored such that higher numbers indicate a more analytic (vs. spontaneous) time planning style.

FIGURE 1 Hypothesized Model of the Relationships Among Time Planning Style, Types of Benefits Sought from the Web, and Web Usage Behaviors.

Respondents filled out survey items on 9-point scales (see Table 1). Whenever possible, existing literature was used as the source of measures. These measures and others developed specifically for this study were pretested with 9 respondents using a preliminary version of the questionnaire. Section 1 of the questionnaire assessed use of the Web for information search, entertainment, and electronic shopping behaviors in terms of behavioral frequency on a scale of 1 (Never) to 9 (All of the time). Section 2 contained measures for exploratory behavior and benefits sought from Web use. These measures used agree–disagree Likert scales, and the items for different measures were interspersed. Section 3 of the questionnaire contained measures for time planning style (agree–disagree Likert scales). Demographics

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were collected in Section 4. Note that we deliberately measured all variables in a sequence opposite to the direction implied in the hypotheses to minimize any demand effects (e.g., time planning style was measured after judgments of behavioral frequency and benefits sought). Time Planning Style. Time planning style was measured with a three-item scale adapted from two sources (Bond & Feather, 1988; Calabresi & Cohen, 1968). The scale efficiently captures time management behaviors including making lists, sticking to a schedule, and planning one’s time carefully. Higher scores on the scale mean a more analytic time planning style. One item in the scale is reverse-ordered (i.e., “I do things when I am ready, not on a schedule.”).

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TABLE 1

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Means, SD, and Standardized Loading Estimates

MEAN

SD

LOADING ESTIMATEa

I make lists of things to do each day. I plan my time carefully. I do things when I am ready, not on a schedule. (R)

5.16 6.67 5.33

2.55 2.09 2.05

0.67 0.62 0.64

Hedonic Benefits Sought (adapted from Babin et al., 1994) X4 Using the Web is truly a joy

ITEM

DESCRIPTION

Time Planning Style (adapted from Bond & Feather, 1988; Calabresi & Cohen, 1968) X1 X2 X3

X5 X6 X7

5.34

1.91

0.68

Compared to other things I can do, my time spent using the Web is truly enjoyable. Using the Web truly feels like an escape.

4.34 3.34

1.89 2.04

0.68 0.51

I enjoy using the Web for its own sake, not just for the information I find or the items I purchase.

4.52

2.14

0.69

5.50 6.05

2.37 1.78

0.70 0.60

4.60 4.28 5.33 6.11

2.18 2.12 2.27 2.28

0.70 0.88 0.67 0.58

4.70

2.56

1.00

3.52

2.21

0.67

4.17

2.33

0.89

6.89

1.50

1.00

Utilitarian Benefits Sought (adapted from Babin et al., 1994) X8 I accomplish just what I want to when I use the Web, and then I log off. X9 When I use the Web I know exactly what I am looking for. Exploratory Behavior (adapted from Novak et al., 2000) Y1 Y2 Y3 Y4

When I hear about a new Web site, I’m eager to check it out. I like to browse the Web and find out about the latest sites. I enjoy visiting unfamiliar Web sites just for the sake of variety. Surfing the Web to see what’s new is a waste of time. (R)

Entertainment Usage Behavior Y5 When I use the Web, it is for entertainment or to have fun (e.g., participate in chat rooms, play online games). Electronic Shopping Behavior Y6 When I use the Web, it is to conduct a transaction with a source or retailer with whom I do business on a regular basis (e.g., make travel arrangements, shop for clothing, buy books). Y7 When I use the Web, it is to purchase an item in a specific category. My purchase could be from any source or retailer that gives me the best deal or otherwise satisfies my purchase criteria (e.g., send flowers to someone, purchase computer hardware or software). Information Search Behavior Y8 When I use the Web, it is to search for very specific information (e. g., search for information on products to assist in making a purchase decision, access the latest news or weather, get the latest sports results).

Note. All items were measured on 1–9 scales. (R) indicates reverse-scored items. All parameter estimates are significant (p’s ⬍ .001). a

Column entries are estimates of the hypothesized relationships between the items and the constructs.

Hedonic and Utilitarian Benefits Sought. To the best of our knowledge, no validated scales are available for measuring specifically the extent to which hedonic and utilitarian benefits are sought from Web

use. Therefore, the scale items used in the present study were adapted from the scales published by Babin et al. (1994) for measuring hedonic and utilitarian shopping values. The items used for assessing

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hedonic benefits sought were based on 4 of the 11 items contained in Babin et al.’s hedonic shopping value scale. For example, one of their items, “This shopping trip was truly a joy,” was amended to “Using the Web is truly a joy.” Similarly, the scale utilized for utilitarian benefits was derived from two of the four items in Babin et al.’s utilitarian shopping value scale. One example is their item “I accomplished just what I wanted to on this shopping trip,” which was modified to “I accomplish just what I want to when I use the Web, and then I log off.” Web Usage Behaviors. Novak et al. (2000) assessed exploratory behavior with an eight-item scale. To keep the questionnaire length reasonable, four of their eight items that seemed to have good face validity were used. Regarding entertainment and information search usages, since these refer to very specific behaviors rather than relatively abstract concepts, singleitem measures were used. Finally, for electronic shopping, a two-item scale was used. One of these items focuses on buying from firms with whom the consumer has ongoing purchase relationships. The other item is oriented toward one-time-purchase transactions.

RESULTS The data analyses were conducted in two phases. First, the factor structure, measure reliability, and

TABLE 2

Time Planning Style

discriminant validity of all the latent constructs in the model were verified. Subsequently, the parameters of the structural model depicted in Figure 1 were estimated.

Confirmatory Factor Analysis, Reliability, and Discriminant Validity The measurement model with all nine constructs was subjected to confirmatory factor analysis. The model fit was found to be satisfactory. The Comparative Fit Index (CFI) was .99, the Normed Fit Index (NFI) was .98, and the Tucker Lewis Index (TLI) was .98; ␹2(101) ⫽ 227.6, p ⬍ .001. All factor loadings were highly significant ( p’s ⬍ .001). Further, as shown in Table 1, the standardized factor loadings for all items exceeded the minimum level of .50. Measure reliabilities and latent construct intercorrelations are depicted in Table 2. Regarding internal consistency reliability, Cronbach’s a for three of the five multi-item constructs exceeded the desired level of .70 (Nunnally, 1978). For one of the other two multi-item constructs, time planning style, the a was .68 and thus came very close to the desired level. Regarding the last construct, utilitarian benefits, the a was a modest .58. When assessed by Bagozzi’s (1980) measure of composite reliability (r), three

Construct Reliabilities and Latent Construct Intercorrelations

TIME

HEDONIC

UTILITARIAN

PLANNING STYLE

BENEFITS SOUGHT

BENEFITS SOUGHT

EXPLORATORY BEHAVIOR

ENTERTAINMENT

ELECTRONIC SHOPPING

(.68, .68)a

Hedonic Benefits Sought Utilitarian Benefits Sought

⫺.27b .35

Exploratory Behavior Entertainment

⫺.30 ⫺.25

.81 .50

⫺.62 ⫺.43

Electronic Shopping

⫺.07

.11

.07

.09

⫺.14

(.75, .76)

⫺.002

.28

⫺.11

⫺.24

.21

Information Search

INFORMATION SEARCH

.17

(.73, .74) ⫺.49

(.58, .60)

a

(.79, .80) .41

(1) (1)

The diagonal entries are reliability estimates. The first entry inside the parenthesis is Cronbach’s index of internal consistency reliability (a), and the second is Bagozzi’s composite reliability (r). A reliability of 1.00 was assumed for the single-indicator constructs.

b

The off-diagonal entries are intercorrelations among the latent constructs.

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latent constructs were .70 or better, one was .68 (time planning style), and the last one (utilitarian benefits sought) was .60. Thus, with one exception, measure reliability was satisfactory. Discriminant validity was assessed in two ways. First, the authors verified that all intercorrelations among the latent constructs (off-diagonal entries in Table 2) were significantly less than 1.00 ( ps ⬍ .001). Second, we ascertained whether the shared variance (i.e., squared intercorrelation) between each pair of constructs was less than the average variance extracted from the items by each individual construct (see Fornell & Larcker, 1981). Of the 36 possible pairs of constructs, only one case did not conform to Fornell and Larcker’s (1981) norm. Specifically, the shared variance between hedonic benefits sought and exploratory behavior (.66) exceeded the average variance extracted by each of these two latent constructs from their respective items (.42 and .51, respectively). The measurement model thus showed satisfactory discriminant validity, with this one possible exception. Further, with regard to the discriminant validity between hedonic benefits and utilitarian benefits sought, their shared variance was only .24 whereas the average variance extracted by these latent constructs from their respective items was .42 and .43, respectively. Therefore, these data confirm our conceptualization of hedonic benefits and utilitarian benefits sought as distinctly different constructs.

Structural Model and Hypotheses Tests Since the measurement model was found to be satisfactory, the hypothesized structural model shown in Figure 1 was estimated. The model fit the data quite well (CFI ⫽ .99, NFI ⫽ .98, TLI ⫽ .98), ␹2(113) ⫽ 281.3, p ⬍ .000. The loadings for the single item measures were fixed to 1. The standardized parameter estimates for the relationship paths in the model are shown in Figure 1. The model revealed significant support for the relationships hypothesized between time planning style and the two types of benefits sought from Web usage. Specifically, the data confirmed a significant negative relationship between time planning style and hedonic benefits sought (H1a; p ⬍ .001), and a significant positive relationship

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between time planning style and utilitarian benefits sought (H1b; p ⬍ .001). Further, the pursuit of hedonic benefits from Web usage had reliable positive relationships with both exploratory behavior as well as entertainment usage behavior (H2a and H2b; ps ⬍ .001). There also was significant support for the predicted positive relationship between hedonic benefits sought and electronic shopping behavior (H2c; p ⬍ .05). Finally, regarding the four relationships hypothesized between utilitarian benefits sought and Web usage behaviors, the model confirmed statistically significant support in all cases (H3a–d). Specifically, utilitarian benefits sought had reliable negative relationships with exploratory behavior and entertainment usage behavior ( ps ⬍ .001). In addition, utilitarian benefits sought had significant positive relationships with electronic shopping ( p ⬍ .05) and information search ( p ⬍ .001).

Proportion of Variance Explained by Predictor Variables in Hypothesized Model Time planning style accounted for 9 and 17% of the variance in hedonic and utilitarian benefits sought, respectively. These seem to be fairly sizable effects, considering that time planning style is only one of many individual-difference variables that might affect the benefits a person seeks from using the Web. Regarding the final outcome variables, the model accounted for a substantial amount of the variance in exploratory and entertainment use behaviors (69 and 64%, respectively). Additionally, the model also explained 24% of the variance in information search behavior. Finally, the model explained a modest amount of variance (7%) in the use of the Web for electronic shopping.

Alternative Structural Models To further assess and validate the hypothesized, fully mediated model, we estimated two rival alternative models. We compared these models to our original model on the following four criteria: parsimony, the number of hypothesized parameters that are statistically significant, percentage of variance explained by predictor variables, and model fit (James, Mulaik, & Brett, 1982; Morgan & Hunt, 1994). The first rival

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model differs from the original model in that it includes additional direct paths from time planning style to all four outcome behavioral variables (a total of 13 paths vs. the original 9), and therefore is much less parsimonious. When this model was estimated, four paths were statistically nonsignificant, one path was significant only at p ⬍ .10, one at p ⬍ .05, and seven were supported at p ⬍ .001. Specifically, all additional direct paths from time planning style to the four Web usage behaviors were nonsignificant (p ⬎ .10) whereas all nine paths were significant in the hypothesized model. This rival model exhibits fit indices that are very similar to the original model (CFI ⫽ .99, NFI ⫽ .98, TLI ⫽ .98), ␹2(109) ⫽ 279, p ⬍ .001, and the amount of variance in the outcome variables explained by the first alternative model was similar to our model. For a second alternative model, we examined the possibility that time planning style, hedonic benefits sought, and utilitarian benefits sought could be exogenous variables simultaneously, influencing Web usage behaviors directly. This second model has 11 paths compared to our original 9. The estimated model shows that of these 11 paths, 3 paths were statistically nonsignificant, one path was significant only at p ⬍ .10, two at p ⬍ .05, and 5 were supported at p ⬍ .001. The three nonsignificant paths were the three direct paths from time planning style to electronic shopping, information search, and exploratory behavior ( p ⬎ .10). Again, this pattern of results is inferior to the hypothesized model, where all nine paths are statistically significant. This fully exogenous model also has slightly worse fit indices than the original model (CFI ⫽ .98, NFI ⫽ .97, TLI ⫽ .98), ␹2(111) ⫽ 309.5, p ⬍ .001. Further, regarding the final outcome variables, the amount of variance accounted by this model in exploratory behavior (66%), entertainment use behaviors (62%), information search behavior (23%), and in the use of the Web for electronic shopping (8%) were not superior to our model.

DISCUSSION, LIMITATIONS, AND IMPLICATIONS The conjunction of growing consumer use of the Web and an increasingly competitive Internet marketspace has made understanding consumer behavior online an important research topic (Burke, 2002;

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Hoffman & Novak, 1996; Parasuraman & Zinkhan, 2002; Peterson et al., 1997; Stewart & Pavlou, 2002; Varadarajan & Yadav, 2002). More specifically, Novak et al. (2000) suggested that a compelling experience is critical to Web usage and to getting and keeping consumers online. Further, they argued that the factors that lend to a compelling Web usage experience are a function of both contextual and individual variables. While other researchers have focused on contextual factors (Alba et al., 1997; Ghose & Dou, 1998), Novak et al. (2000) stressed the need for research focused on the individual-difference variables that influence Web usage outcomes. The present research examined one such individualdifference variable, time planning style. Based on the prior conceptualization of time planning style (Cotte & Ratneshwar, 2000, 2001, 2003; Cotte et al., 2004), specific hypotheses were developed to link this construct to the hedonic and utilitarian benefits sought from Web use and, consequently, to specific Web usage behaviors. The results, albeit from a sample skewed toward young adults, showed that highly analytic (vs. spontaneous) planners are motivated to use the Web in a utilitarian fashion rather than for the hedonically motivated, intrinsic enjoyment of the online experience itself. Further, as hypothesized and demonstrated empirically, these differing benefits sought from Web use in turn impacted the actual Web usage behaviors reported by our respondents. Specifically, both exploratory and entertainment usage behaviors were found to be positively associated with the pursuit of hedonic benefits, but negatively associated with utilitarian benefits sought. Electronic shopping proved to be a more ubiquitous behavior that as predicted, was positively related to both types of Web usage benefits being sought. The results also confirmed that those seeking utilitarian benefits were more likely to use the Web to search for information. Most importantly, our data provided support for a fully mediated model wherein the relationships between time planning style and the four Web usage behaviors were mediated by the two types of benefits sought from Web use. Indeed, as research on individual differences in Web usage behavior becomes increasingly important and more prevalent, constructs such as hedonic versus utilitarian benefits may be key mediating variables between other consumer traits and Web usage behaviors.

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Limitations We conceptualized and operationalized time planning style deliberately as a generalized, individualdifference variable and not as a variable specifically set in the context of Web usage since the latter approach conceivably might have portrayed our hypothesized relationships with downstream variables to be tautological. Nonetheless, future research might verify whether a Web-specific measure of time planning style can account for more variance in hedonic and utilitarian benefits sought than did the present study, assuming measures with sufficient discriminant validity can be developed. Further, per our empirical results, our model accounted for considerably more of the explained variance in exploratory and entertainment use behaviors when compared to the explained variance in information search and electronic shopping behaviors. The reasons for this pattern are not clear. We noted earlier that the sample of respondents in our survey may not have been representative of the population at large. While one would expect a priori the relationships uncovered in the present research to apply to the general population as well, some caution should be taken in regard to the generalizability of the findings. The survey-based method used to conduct this study also imposes some inherent limitations on our results. Self-report measures of past behavior can be problematic in that they rely on the accuracy of respondents’ memory. Further, our survey method assumes that respondents are aware of the benefits that they seek from Web usage. Different methods and samples in future studies could verify the generalizability of the present findings.

Managerial Implications and Future Research Opportunities Taken as a whole, the present findings suggest that time planning style is an important construct for marketers to consider since it impacts the specific benefits sought from Web usage, and through these benefits, the actual behaviors consumers exhibit on the Web. Therefore, rather than simplistic prescriptions of the sort that state “Web sites should do more of X,” the present data favor a strategy of tailoring both the content and the user interfaces of Web sites to individualdifference variables such as consumers’ time planning

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styles. For example, many sites, selling products ranging from fishing products (www.fishinghotspots.com) to toys (www.toyfan.com) to tools (www.us.hilti.com) give consumers the opportunity to create an individual profile that translates over time into a very unique consumer experience with each visit to the site. This online shopping experience comes complete with an individualized “store” page offering products based on past purchase preferences, along with personalized recommendations throughout the site. Similarly, Excite (www.excite.com) also offers a tailored experience; the user interface can be customized to accommodate individual preferences defined by the user. However, these sites, and others like them, base their customization of user interface and page content primarily on past click behavior, and, occasionally, stated preferences. Web-site adaptation could be taken much further if it factored an additional layer of consumer understanding based on individual-difference variables. In this vein, the findings from the present study suggest that one such direction would be to consider individual differences in time planning style, in conjunction with other descriptive data, to create a one-of-a-kind experience unique to each consumer. Indeed, given the nature of the present findings, it would seem that the investigation of a variety of individual-difference variables is a priority for a more complete understanding of how marketers can manage the consumer Web experience. For example, in the context of the current study, one can envision designing a site that very quickly assesses a consumer’s time planning style on the first visit by collecting responses to two or three simple questions. On subsequent visits to the site, a consumer profile could be accessed by the host either through password authentication or a cookie stored on the consumer’s computer. Alternative layouts and content would then be presented based on the user’s time planning style. In such a scenario, if a user is identified as an analytic planner, it would be inferred that that particular consumer is likely to be highly utilitarian in his or her motivations for Web usage; consequently, the site presented to him or her would be uncluttered, with few hedonic aspects (e.g., music clips, graphics, games, etc.) and very few links to tangential topics. Such a site might focus on providing

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information with simple, easily navigable menus, and/or facilitating quick purchase transactions with minimal distractions. While sites that appeal to a variety of users such as Amazon.com and Yahoo! might productively consider such personalized interfaces that differentiate among user segments, other Web sites might simply customize their offerings to the time planning styles of their prototypical visitors. For example, Web marketers catering to customers who are highly analytic should worry less about the “bells and whistles” and consider a more means–end driven interface to facilitate online interactions. A good example here is the Xerox Web site (www.xerox.com), which is very information driven, with minimal graphics and straight forward text links. Indeed, given a more straightforward approach to accessing information and performing online transactions, analytic planners may find more value on a particular Web site and even plan to spend more time there. In such cases, the trick to increasing the “stickiness” of a Web site is not in enhancing the colors, graphics, or other sensory aspects of the site, but in facilitating time-efficient, information-rich, yet uncomplicated interactions. Conversely, if a user is identified as a spontaneous time planner, or if the site itself appeals particularly to such a consumer set, the site would be presented quite differently. Understanding that consumers with such time planning styles tend to be more hedonically motivated, the experience delivered might include entertaining images and sounds, hyperlinks to games or other activities related to the site, and even ways to “share” the site with others to build the social aspects of the site. The site would encourage exploratory behavior by offering aspects to pique the visitor’s curiosity and prolong the time spent on the site. The Web site for Miller Brewing Company (www.millerbeer.com) provides a good example of a design appealing to a hedonically motivated Web user, perhaps one that has a spontaneous time planning style. Also note that e-marketers will value behavioral variables such as time planning style even more in segmentation and targeting decisions if the descriptive correlates of such variables are determined. Cotte and Ratneshwar (2000) suggested how descriptive variables such as age, gender, and ethnicity may prove to

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be correlated significantly with time planning style. If future research confirms such relationships in representative samples of the population, Internet marketers would be able to profile segments of individuals who have specific time planning styles. Further work that identifies other relevant individual-difference variables—and clarifies their links to the benefits sought from Web use and actual Web usage behaviors—should provide an even better basis for marketers to customize their Web-site content and behavior to suit their customers’ traits, motivations, and preferences.

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