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Conceptual Framework
In this section, we first attempt to explore the extent to which key theories derived from
bricks-and-mortar retailing are relevant for exploring patronage behavior in an online setting. We
draw from the extant literature on conventional modes of shopping and identify factors that predict
consumers’ online patronage behavior. Then, we propose a competing model based on the EC
research.
The key dependent variable in both models is defined as “the probability of consumers’ online
shopping (i.e., purchasing).” In describing our dependent variable, we use the following terms as
synonyms: (a) probability of online shopping; (b) likelihood of being an Internet shopper. In this
chapter, an Internet shopper is defined as a consumer who has access to the Internet and has
previous experiences with the Internet (but not necessarily shopping experiences). That is, we
assume that the individual consumer in our model has access and inclination to use the Internet.
Our focus is on B-to-C commerce.
Figure 3-1: Proposed model of
online patronage (given that consumers have Internet access and
experiences)
Model Developed from Traditional Retailing
Literature
A conceptual model is forged on the basis of our learning from traditional retailing theory
and practice (Figure 3-1). Prospective predictor variables are chosen if they are
considered important in explaining retail patronage in an offline setting. Three factors (i.e.,
shopping motives, consumer psychographics, attraction of a retail facility) are identified as the
key determinants of online patronage. The propositions that are represented in the model are
described in more detail later. The model assumes that consumers have access to the Internet and
have prior online experiences.
Shopping Motives
There are a variety of extant models to explain shopping behavior and its underlying
motivations. A unified, comprehensive framework has much to offer in guiding retail strategy
formulation, and it also advances efforts to develop more comprehensive theories of shopping
behavior.
Shopping motives are “all those impulses, desires, and considerations of the customer that
induce the purchase of certain goods and services” (Udell, 1964-1965, p. 8). They account for the
underlying reasons why people buy what they buy. Motivational theorists have typically regarded
human behavior as the product of both internal need states and external stimuli perceived by the
individual (Westbrook and Black, 1985). Numerous attempts have been made to classify and organize
the diversity of shopping motives (e.g., Stone, 1954; Tauber, 1972; Westbrook and Black, 1985).
Regardless of classification, however, it is commonly agreed that the consummation of motive
provides subjective gratification, or satisfaction, to the individual. Thus, the motives represent
a useful indicator of resulting behaviors. A vast array of motives has been proposed, with varying
degrees of focus and specificity.
Economic Motivation
From an “economic man” perspective, a shopper will minimize the time required to accomplish
the needed shopping task. That is, there is a motivation to conserve resources. Some shoppers and
some shopping trips undoubtedly conform to this notion of resource conservation notion. Bellenger
and his colleagues (Bellenger, Robertson, and Greenberg, 1977; Bellenger and Korgaonkar, 1980)
classify shoppers, according to their shopping motivations, into two broad categories:
“functional-economic” and “recreational” shoppers. The two shopper types differ in the amount of
time and information-seeking involved in shopping. Convenience and economic shoppers dislike
shopping or are neutral toward it, and thus approach retail store selection from a time- or
money-saving point of view. Using a more extensive typology of shopping motivation, Westbrook and
Black (1985) identify economic role enactment, choice optimization and negotiation, which are all
economically based motives. Shoppers with choice optimization motivation, for example, are finding
exactly what they want to acquire in the least amount of time. The utility of an acquisition is
enhanced if it is obtained with minimal search effort.
Convenience Seeking: Consumers perceive convenience in
product acquisition as a major advantage associated with in-home shopping (Darian, 1987; Gillett,
1970). This economic orientation is expressed both in the desire for convenience (to lower the
search cost and to limit the shopping time) and for lower prices. By making a shopping trip only
when he knows specific buying objective can be met, the functional-economic shopper optimizes
choice and increases the net utility of an acquisition. Store quality, variety, and related
services are secondary considerations to perceived convenience and other economic advantages of the
store.
Consumers are more likely to shop at home for two main reasons: motivators (e.g., the need to save time) and facilitators (e.g., a dislike of in-store shopping) (Darian, 1987). We
speculate that there are two major types of convenience that shoppers seek when choosing from their
consideration set of stores: (1) savings in time and flexibility in time management; and (2)
trouble/problem minimization during a transaction. Darian (1987) and Graham (1981) use a time
management explanation for shoppers’ patronage behavior. For instance, in-home shopping can reduce
the time spent as well as provide flexible timing for shopping.
Convenience seekers may also be inclined to bypass the trouble associated with offline
shopping. There are types of convenience that in-home shoppers could be seeking (e.g., saving the
physical effort of visiting stores, saving of aggravation) (Darian, 1987). Considering Internet
shopping as a new alternative for in-home shopping, Internet shoppers could receive many of the
benefits described by Darian. The typical popularity of the Internet can be partially attributed to
the ease with which customers can sift through vast amounts of information. The Internet brings the
marketplace to the consumer, who can purchase virtually anything ranging from groceries to cars.
Competing businesses in the world of electronic commerce are only a few mouse clicks away. Thus,
there is the potential for shopping to become less time consuming. It also eliminates the worry and
hassles associated with traffic, travel, and parking. Therefore, we offer the following
proposition:
P1: Consumers’ desire for convenience enhances the
probability of online shopping.
Deal seeking: Another factor that leads shoppers to a
store is the offer of price promotions. Various scholars (e.g., Blattberg, Buesing, and Peacock,
1978; Lichtenstein, Netemeyer, and Burton, 1990) find a segment of consumers who are deal-prone.
This group of shoppers is typically value-conscious and sensitive to premium offers. The Internet
mimics a giant-sized shopping center in the sense that many product categories (virtually anything
ranging from cars to groceries) and brands are available. Price competition on the Web is perceived
to be more intense than in the on-ground marketplace, as consumers’ search cost is substantially
reduced. Price search and price comparison can be done almost effortlessly. Various search engines,
shopping bots and intelligent agents (e.g., Copernic Shopper, DealCatcher) allow users to surf a
plethora of bargains within seconds. Therefore, deal prone consumers are likely to shop on the
Internet. Thus, we propose that:
P2: Consumers who like to search for deals are more likely
to be Internet shoppers.
Non-Economic Motivation
Hedonistic motives can be important precursors of consumer behavior (Halvena and Holbrook,
1986; Hirschman and Holbrook, 1982). Bellenger and Korgaonkar’s (1980) twofold shopper typology
differentiates the recreational shopper from the more functional-economic shopper. Unlike
functional shoppers, recreational shoppers are individuals who shop for the pleasure of the
shopping experience itself. Recreational shoppers enjoy shopping as a leisure activity, shop
impulsively, place higher importance on store décor, spend more time shopping per trip, continue
shopping after making a purchase, and prefer closed malls and department stores (Bellenger and
Korgaonkar, 1980). Convenience and economic issues are not the primary concern for this shopper
segment.
Consumers’ Affiliation Motive: McClelland’s theory on
human motivations defines the affiliation motive as the need to be with people (McClelland, 1987).
One of the most basic social behaviors is the urge for human contact and connection. That is,
people experience a strong motivation to associate themselves meaningfully with groups of kindred
spirits in order to reduce feelings of boredom and loneliness. An important issue in the study of
loneliness concerns the strategies that people adopt in order to cope with and alleviate their
feelings of loneliness. “Going shopping” is one such activity that people pursue (Graham, 1988;
Rubenstein and Shaver, 1980). Shopping centers and malls offer opportunities to drown out problems.
Malls offer escape (i.e., relief from boredom, escape from routine, and high levels of sensory
stimulation) (Bloch, Ridgway, and Dawson, 1994). On-ground retail stores also offer a chance for
human interactions, that is, some consumers enjoy talking to and socializing with others during a
shopping visit, and they are seeking “social experience outside the home” (Tauber, 1972). Some of
this interaction is with fellow shoppers and some is with sales personnel (Donovan and Rossiter,
1982). Because of the multiple opportunities for social interactions, some consumers are reluctant
to patronize nontraditional retailers (e.g., catalog shopping, home computerized shopping,
television shopping).
Non-store retailers may inadvertently create a sense of isolation and a feeling of loneliness
among their customers (Farmer, 1988). Even though technological innovations may potentially create
consumer advantages (e.g., speed, accuracy, economy, convenience), they have the effect of
insulating and detaching consumers from their fellows. In an attempt to offset this isolating
effect, some e-stores strive to create communal effects by fostering community sentiments and
encouraging collective action. Nonetheless, one can argue that compared with the Internet,
brick-and-mortar stores offer greater opportunities to socialize due to the presence of physical
surroundings and face-to-face interactions. Hence, we have:
P3: Need for affiliation (i.e., consumers’ need to
socialize) has a negative influence on the probability for online shopping.
Shopping Pleasure: Personal motives are influential in
shopping behavior. Among the most prominent satisfactions obtained from shopping include: (1)
experiencing self-gratification; (2) learning new trends; (3) experiencing physical exercise;
and
(4) receiving sensory stimulation from the retail environment.
A desire for power, authority over salespeople, and stimulation from the shopping environment are
related experiences (Westbrook and Black, 1985). Recreational shoppers do not view store shopping
as a waste of time (Sproles and Kendall, 1986). Instead, they shop with a feeling of gratification,
fulfillment, and satisfaction.
Arousal induced by the store environment would intensify pleasure or displeasure such that
time and spending behavior would be increased in pleasant environments and decreased in unpleasant
environments (Donovan et al., 1994). Malls are viewed by consumers as a place not only for
shopping, but also for other activities, such as entertainment (Bloch et al., 1994). A number of
other studies argue that the central reason many people visit malls is for the excitement of the
experience (e.g., Cockerham, 1995; Graham, 1988; Stoltman, Gentry, and Anglin, 1991). As opposed to
bricks-and-mortar store shopping, online shopping cannot satisfy the desire for immediate
gratification. Moreover, the inability for consumers to physically inspect products and the absence
of sensory stimulation from the store environment may drive some consumers away from the virtual
marketplace. Hence:
P4: Recreational shoppers are less likely to be Internet
shoppers.
Consumer Psychographics
Psychographic segmentation may provide a more refined
tool for the understanding of shopping behavior (Darden and Perrault, 1976). However, the
relationship between psychographic characteristics and adoption of emerging retailing alternative
(e.g., the Internet) is not expected to be strong, since a substantial body of research has found
that although some relationships between personality characteristics and purchase behaviors are
statistically significant, they are small in magnitude (Kassarjian, 1971).
Risk Averseness
The willingness to purchase products is inversely related to the type and amount of perceived
risk associated with a purchase decision (Bauer, 1960; Bettman, 1973, 1975; Korgaonkar, 1982; Peter
and Tarpey, 1975). A number of risk facets have been identified as potential inhibitors to
purchase. These dimensions include: performance, social, psychological, convenience, physical, and
financial risks (Jacoby, Kaplan, and Szybillo, 1974; Peter and Tarpey, 1975; Peter and Ryan, 1976).
In-home shoppers tend to be more adventurous, cosmopolitan and self-confident in their shopping
behavior (Cunningham and Cunningham, 1973; Gillett, 1976). As predicted by these studies, Internet
shoppers, as one group of in-home shoppers, should be more tolerant of purchase risk than store
patrons. We therefore propose that:
P5: Risk averse consumers are less likely to shop on the
Internet than those who are risk takers.
Consumer Innovativeness
Here, consumer innovativeness is defined as the degree to which consumers possess a favorable
attitude towards trying new ideas or different practices. At the most basic level, this preference
motivates a search for new experiences that stimulate the mind and/or the senses (Hirschman, 1984;
Pearson, 1970; Venkatraman and Price, 1990). Outshoppers (i.e., people who shop outside their
residential areas) tend to be more innovative and to know more about the world outside their
community (King, 1965). Cognitive innovators (who prefer new experiences that stimulate the mind)
are thinkers and problem solvers (Venkatraman, 1991). Since they seek new experiences, they are
likely to consider newness of the innovation important in the purchase decision.
The Internet, as an emerging mode of retailing, has characteristics very different from more
traditional retail operations (e.g., it creates remote buying experiences; computerized transaction
empowers the consumer with a sense of control). Because of this “freshness,” it tends to attract
innovative consumers. Therefore, we propose that:
P6: Innovative consumers are more likely to shop on the
Internet.
Self-Confidence
In marketing, the traditional retailing literature
identifies self-confidence as a predictor variable for consumer shopping-channel choice. Boone
(1974) posits that innovative buyers have greater self-confidence. His finding is supported by
Reynolds (1974), who finds that self-confident people tend to shop more frequently at home. In-home
shoppers belong to a higher-than-average socio-economic group, measured by education, income,
social class, and occupational status (Gillett, 1976; Salste, 1996). These socio-economic
differences may become especially pronounced among Internet shoppers, who are more willing to take
risks and try new things and less conservative than their store-prone counterparts. In an online
setting, shoppers do not have face-to-face interaction with a salesperson. The resulting lack of
real-time service and help, in a sense, demands consumers to be self-reliant. Hence:
P7: The higher a consumer’s self-confidence, the more likely
that consumer is to shop on the Internet.
Attitude Toward Local Shopping Conditions
Out-shopping behavior is determined by unique socioeconomic, lifestyle, and economic factors,
as well as by the quality of local retail facilities (Darden, Lennon, and Darden, 1978). Attitude
about local shopping (i.e., shopping within the consumer’s residential area) is the most salient
psychographic variable in differentiating between different patronage groups. The typical
out-shopper is seen as an innovator, an on-the-go, cosmopolitan person who is generally
dissatisfied with local retail facilities (Papadopoulos, 1980). Consumers who are expected to
benefit from in-home shopping are those who have difficulty getting to local stores or who have
limited local retail facilities (Berkowitz, Walton, and Walker, 1979; Cox and Rich, 1964). People
in these circumstances are more likely to shop at home. Samli and Uhr (1974) find that moving
across the spectrum from loyal in-shoppers to heavy out-shoppers indicates that the level of
satisfaction with the following characteristics of local shopping facilities decreases: quality,
selection, prices of goods offered; courtesy, product knowledge of salespeople; ease of shopping;
appearance of retail facilities; and store hours of retail facilities.
Internet shoppers, unrestricted by geographical boundaries, are essentially one type of
out-shoppers, i.e., consumers who shop outside the residents’ trading area. Based on the above
discussion, local retailing inadequacies may prompt out-shopping such as Internet shopping. For
instance, shoppers may want to avoid some of the unpleasant aspects of shopping in stores by
turning to another trading alternative — online shopping. The advantages of Internet buying must
outweigh those of the customary methods of local shopping, at least from Internet shoppers’
perspective. Hence:
P8: Negative attitudes toward local shopping conditions
enhance the probability of online shopping.
Attraction of a Retail Facility
Location: Location Theory
In the traditional retailing literature, location has
always been treated as an important factor in attracting patrons to a shopping area. The most
widely accepted location theory is central place theory (Craig, Ghosh, and McLafferty, 1984), which
views shopping areas as commerce centers to which consumer households travel to obtain needed goods
and services. Generally speaking, central business districts and regional shopping centers that
offer higher-order goods and services or an agglomeration of both attract customers from greater
distances than neighborhood centers that offer only lower-order goods and services. Customers
seeking to maximize their shopping time will often drive past weaker malls to reach destination
malls that have the best variety of stores and merchandise (Ashley, 1997). The breadth (number of
brands) and depth of assortment (number of stock-keeping units) offered in a shopping center helps
a retailer to cater to the heterogeneous tastes of his customers (Dhar, Hoch, and Kumar, 2001).
Offering more variety can help a retailer attract more consumers to visit the store as well as
entice them to make purchases in the store. Research based on central place theory employs economic
utility models that incorporate factors such as distance or travel time and the size of a center to
express the relationship between costs and benefits of shopping area choice (Ghosh, 1986; Huff,
1962; Louviere and Gaeth, 1987; Weisbrod, Parcells, and Kern, 1984). A central place can reduce the
transaction cost associated with a shopping visit (e.g., transportation cost, time spent on
shopping). The Internet is very often likened to a virtual shopping center which is easily
accessible, especially for consumers in geographically restricted areas. The ability to purchase
virtually anything ranging from groceries to cars, the ease and convenience of shopping from home
at any time of day are appealing allurements for shoppers. Therefore, the Internet has the
characteristics of a central shopping area with a wide selection of products. Based on the central
place theory, we propose that:
P9: A sizeable segment of consumers perceive the Internet to
be an easily accessible (e.g., by offering savings in travel time) shopping channel. This
perception enhances the likelihood of online shopping.
P10: A sizeable segment of consumers perceive the Internet
to be a central shopping location that offers a wide selection of goods. This perception enhances
the likelihood of online shopping.
In addition, we propose that there is an online parallel to the central shopping mall. For
instance, some online organizations are perceived to be “centrally located” in virtual space (e.g.,
those retailing sites associated with popular Web portals such as AOL or Yahoo!). Also, some sites
are more easily accessible by popular search engines or else appear nearer to the top of such
search outputs.
Store Image
Over the years, some researchers have challenged the
basic utilitarian premise of location models by arguing that the attraction of a retail facility
involves dimensions other than distance and mass. For instance, the drawing power of a retail site
is also influenced by consumers’ image perceptions of the store or shopping area (Bucklin, 1967;
Finn and Louviere, 1996). Consumers make judgments about and selections of stores based on
subjective ratings on various image dimensions. Site location research is further extended when
store image is incorporated as a component of attraction to shopping areas (Gentry and Burns, 1977;
Nevin and Houston, 1980). Academic research on mall shopping has revealed that many consumers are
prone to make a decision as to where to shop based on their attitude toward shopping center
environment (Finn and Louviere, 1990, 1996; Gentry and Burns, 1977). In their study of
bricks-and-mortar stores, Berman and Evans (1995) divide atmospheric stimuli into four categories:
the exterior of the store, the general interior, the layout and design variables, and the
point-of-purchase and decoration variables. As in physical shopping, buyers may prefer to
consummate and repeat shopping experiences in an e-store that induces pleasant and rewarding
feelings (Lynch, Kent, and Srinivasan, 2001). Here, Web-based retail environmental variables
include the layout and design of an e-store Web site, ease of use, the download speed, and the ease
of navigation within the e-store. We propose that:
P11: Consumers’ image perception of an online store affects
their purchase behavior. Specifically, a favorable image perception is associated with an increased
likelihood of online patronage.
Service Quality
In a traditional retail setting, service is always counted as an important factor
contributing positively to the shoppers’ overall experience (e.g., Klassen and Glynn, 1992; Solomon
et al., 1985). When shoppers interact with a faceless, non-personal entity as in the case of a
virtual store, service quality seems particularly important. Needless to say, service offered in an
online store takes a slightly different form. Online shoppers very often draw clues about service
quality based on intangible attributes such as store operations policy. For instance, lenient
return policy, provision of 24/7 1-800 service hotline, among others, are market cues for online
service quality. Note that many online services are enabled by technological advances. For
instance, software agents installed at a store Web site may allow consumers to more efficiently
screen the set of alternatives available in an online shopping environment.
P12: Good service is associated with an increased likelihood
of online patronage.
Competing Model Developed from E-Commerce
Literature
In this section, a competing model is forged on the
basis of our learning from the emerging EC literature (see
Figure
3-2). Potential predictor variables are drawn based on our review of studies published in
the EC field, many of which specifically deal with online shoppers and e-tailing. Four factors
(i.e., shopping motives, personality variable, Internet knowledge and experience, shopping
incentives) are identified as the key determinants of online patronage. The propositions that are
represented in the model are described in more detail in the rest of the chapter. As in the first
model, this competing model also assumes that consumers have access to the Internet and have prior
online experiences. Note that some variables appear in both baseline and competing models (e.g.,
self-confidence, recreational motive, convenience seeking), and these overlaps are indicated in the
figures. This is not uncommon, since the Internet is simply another retail outlet that consumers
can choose from their consideration set of possible places to go shopping. Not surprisingly,
e-tailing bears a lot of resemblances to its counterpart in an off-line setting. What is more
interesting is how our knowledge about traditional retailing can contribute to our study of
e-tailing. In this following section, we propose a second model (based on EC research). We attempt
to identify the similarities shared by the two models (derived from largely independent) research
streams and also identify key differences or contrasts.
Figure 3-2: Proposed model of
online patronage (given that consumers have Internet access and
experiences)
Online Shopping Motivations
Information Seeking
The Internet provides an archive of product and company information. If the Web is good at
anything, it is good at presenting tons of information and involving people in the process of
sorting through it (Schwartz, 1997). The Web also organizes information for consumers. It learns
about consumers’ preferences, based on past visits and reorganizes the information content and the
way it is presented. For instance, Amazon.com groups customers based on their previous purchases,
and then tailors suggested books to a consumer’s preferences once he embarks on a new search. The
information seeking orientation led to the earlier popularity of the Web and now starts to draw the
online population to the virtual market. The online medium facilitates utilitarian behavior as
search costs for product information are dramatically reduced (Wolfinbarger and Gilly, 2001). With
a few clicks, online shoppers can find relevant information (e.g., competitive brands, best price
offers, product specifications, consumer word-of-mouth) on a product of interest in a fast fashion.
Furthermore, online buyers feel that they can more fully investigate options than they can offline.
Price comparisons in an information-rich environment are fairly easy, and thus the potential for
savings significant, the economic motivation to shop on the Web could be strong (Anders, 1998).
Hence, we offer the following proposition:
P13: Shoppers’ information-seeking tendency increases the
probability of online shopping.
Convenience Seeking
Goal-oriented or utilitarian shopping has been described as task-directed, efficient,
rational, and deliberate. Thus, goal-focused shoppers are transaction-oriented and want to
accomplish a deal quickly and without distraction. Online consumers tend to be goal-focused rather
than experiential (Wolfinbarger and Gilly, 2001). One attribute that attracts goal-oriented
shoppers to e-tailing is convenience. In a recent research report, Greenfield online finds that
some Internet users prefer online shopping over in-store shopping because of its convenience and
that the consumers who value convenience are more likely to buy over the Internet (Li, Kuo, and
Russell, 1999). Li and his colleagues (1999) discover a noticeable pattern that consumers value
shopping convenience more highly as their Web shopping frequency increases.
The Internet enables consumers to have the world at their fingertips. The Internet
facilitates comparison shopping and speeds up the finding of item. The ease and convenience of
shopping from home at any time of day or night is an appealing allurement for shoppers in virtual
reality (Donthu and Garcia, 1999; Pastore, 2000). Many find it convenient, local and
thrifty.
One of the key aspects of human life in the 21st century is the
paucity of time (Watson et al., 2000). Marketers who find ways to save time for consumers (e.g.,
through the successful application of the Internet) have the potential for great success and a
chance to attract loyal customers. The Web comes in handy since this medium allows people to shop
at stores not available in their geographic area (Edenkamp and Czark, 2000). This would suggest
that online shopping may save fuel costs and travel risks. Geographic restricted areas where the
distance of conventional retail stores can reach over eighty miles one way, benefit from the
virtues of online shopping. In addition, the availability of “24-hour shopping” is a bonus.
Consumers can avoid hitting rush hour traffic and waiting in long checkout lines by simply clicking
a few buttons on their home computer. Based on the above argument, we offer the following
proposition:
P14: Consumers’ convenience seeking tendency enhances the
probability of online shopping.
Interactive Control
The Internet, as a new medium, is two-sided, active and
timely. It obviates the need for sales personnel. Many sales clerks are order takers at best and
many actually offend shoppers with poor manners and service. Many online buyers revel in the fact
that they can get the transaction done without having to go through a salesperson. The ability to
find what they need and to complete a transaction without having to go through third party is
associated by online buyers with increased freedom and control. The interactive element of the Web
puts the users in charge of the medium (Korgaonkar and Wolin, 1999) as well as the transaction. The
user can choose which Web site to view, when to view it, or even exchange product information in
specialized chat rooms. The interactive feature of the Web allows consumers to personalize and
customize their experience by choosing among its huge selection. Therefore, it is not surprising
that heavy users of the Internet tend to have a strong internal locus of control (Wolfinbarger and
Gilly, 2001). Online shoppers enjoy their increased sense of control in the cyberstore compared to
other purchase situations. Therefore, we propose that:
P15: A desire for interactive control enhances the
probability of online shopping.
Shopping Experience
Shopping can be a social and very often recreational experience for many. Purchasing via the
Web may be convenient and time-efficient, but it can also be isolating, unsatisfying and boring.
Moreover, online shopping cannot satisfy the desire for immediate gratification (Rosen and Howard,
2000). For large-ticket, non-standardized, highly differentiated items, consumers would like to
physically inspect them prior to purchase. Empirical studies have ascertained these anticipations.
One of the research findings of Greenfield Online is that consumers who prefer experiencing
products are less likely to buy online (Li, Kuo, and Russell, 1999). At present, the Web has large
capacity for demonstrating product information, including some search attributes of products such
as sizes, colors, models and prices, even sound (e.g., consumers can check out digital products
such as CD by downloading a trial version). Some online stores offer chat rooms, auctions, or other
functions to enhance the shopping experience or facilitate communications among shoppers. Though it
allows consumers to experience to some degree the pleasure of shopping, the Internet is still not
as sufficient as the off-line storefronts to provide consumers the “hands-on” experience. For
consumers who shop out of social or recreational motives, the virtual marketplace cannot compete
with retail stores to meet their needs (Li, Kuo, and Russell, 1999). On the other hand, online
buyers largely like the relative lack of social interaction while buying online (Wolfinbarger and
Gilly, 2001). Simply put, the desire for human interaction, the social aspect of shopping, and the
ability to pick up and sample products are impossible to replicate online. Hence:
P16: Experiential shoppers are less likely to be Internet
shoppers.
P17: Recreational shoppers are less likely to be Internet
shoppers.
Psychographics and Personality Traits
Self-Confidence
Most Internet shoppers evidence a rich, active, and
diverse lifestyle (Chang and McFarland, 1999). Many travel, attend sporting events, participate in
sports, and have health club memberships. Those who are more open to technological advances are
able to exercise better control over emerging tech-related challenges, and hence likely to have
more personal confidence (Pan and Crask, 2001). These people tend to dominate in online shopping as
they are not easily turned away by the technology and risk involved. Hence, we have:
P18: The higher a consumer’s self-confidence, the more
likely that consumer is to shop on the Internet.
Risk Averseness
Internet users have the innovator and risk-taker personality type (Donthu and Garcia, 1999).
Fifty percent of the Internet population belong to the Actualizer segment (active, discriminating,
and adventurous), and eighteen percent belong to the Experiencers segment (innovative, stimulation
seekers, and fashionable) (SRI International, 1995). Internet
shoppers are more willing to try new things and are less concerned with the risk involved with
their purchases (Donthu and Garcia, 1999). The aversion of risk among online shoppers is below
average. We propose that:
P19: Risk averse consumers are less likely to shop on the
Internet than risk takers.
Internet Knowledge and Experience
Internet Literacy
The Internet can perform multiple functions as a communication, transaction, and/or
distribution channel. For consumers, shopping via the Web can be a slow, frustrating venture,
especially for those unfamiliar with navigation through it. Actual use of the Internet as a
shopping channel requires knowledge about the Web or what is normally referred to as “Internet
literacy.” We speculate that consumers with different levels of channel knowledge tend to feel
differently about using the Web for shopping purposes. Channel knowledge is the strongest predictor
in Li, Kuo, and Russell’s (1999) model of online buying behavior. The authors notice that
knowledgeable consumers tend to perceive more positively of the online channel’s utilities, which,
in turn, will have a positive impact on purchase behavior. Hence, we have:
P20: Consumers who consider themselves knowledgeable about
the Internet, as a channel, are more likely to purchase online than those who do not.
Prior Online Experiences
A “customer life cycle” approach presumes that consumers
are on a continuum of online experiences. They have different levels of knowledge and experiences
about the Internet. A consumer’s prior online experiences (e.g., online purchase and subsequent
consumption experiences, interactions with e-stores, information acquisition via the Web) play a
crucial role in shaping his overall judgment of Web-based transactions. Consumers’ positive prior
online experiences contribute to build their trust in conducting transactional exchanges through
this new medium. In the case of positive prior online experiences, the probability of the consumer
revisiting the previous Web site(s) or visiting a limited number of Web sites with which the
consumer has no negative associations, increases (Maity, Zinkhan, and Kwak, 2002). Therefore, we
propose that:
P21: Consumers’ positive prior online experiences increase
the probability of online patronage.
Monetary Purchase Incentives
As in the physical world, e-tailers are developing sales promotions and purchase incentives.
For example, ClickrewardsTM offers frequent flyer air miles when
purchasing from certain online stores. Mypointsâ offers bonus points that can be redeemed for
purchases online (Walsh and Godfrey, 2000). Cyberstores occasionally feature some advertised
products at premium prices. These promotional activities may give shoppers an incentive to
patronize the online store. In their empirical study on Internet retail store design, Lohse and
Spiller (1999) find that promotion on the cybermall entrance screen generates traffic and sales. In
a focus-group discussion, online shoppers mention that one big reason they browse is bargain
hunting (Wolfinbarger and Gilly, 2001). Another motivator for shopping online is avoiding sales
taxes. All these discussion lead to the following proposition:
P22: Purchase incentives offered on the Internet (e.g., no
sales tax, sales promotions, bonuses, price discount) increase the probability of online
patronage.
Summary of Predictors of Online Patronage
Combining both traditional and e-commerce research streams, we set forth a list of factors
that seem to contain explanatory power for predicting online patronage. These factors are grouped
as either buyer-related factors (i.e., shopping motives, consumer psychographics, Internet
knowledge/experience) or seller-related factors (i.e., e-tailer characteristics).
Shopping motives: info-seeking; convenience seeking;
interactive control; experiential motive; recreational motive; affiliation motive; deal
seeking
Consumer psychographics: self-confidence; risk averseness;
consumer innovativeness; attitude toward local shopping conditions
Internet knowledge/experience: Internet literary; prior
online experiences
E-tailer characteristics: shopping incentives (e.g., low
price offers, free delivery); accessibility; wide selection of products; store image/atmosphere;
service quality
Interactions
Note that there might be interactions among some predictor variables, though they are not
highlighted in the proposed models. For instance, we have sound reasons to believe that a
connection can be established between prior online experiences and Internet literacy. When people’s
online experiences increase, their knowledge about the Internet as a channel, and the channel’s
utilities, will also increase naturally. In addition, possible interactions in the two models
(Figures
3-1 and 3-2) include:
Interaction between store image and product selection.
Stewart and Hood (1983) found that consumers had distinct images of each store, and
these images could serve as the basis for segmenting store customers. For instance, shoppers at the
low-priced stores were primarily concerned with convenience, price, and product selection.
Interaction between experiential and recreational shopping.
The recreational side of shopping experiences may in itself include the physical
inspection of products, or the “hands-on” experiences. There might be no clear distinction between
shoppers’ experiential and recreational motivation.
Interaction between convenience seeking and accessibility.
The attraction of a retail facility in terms of location may be more pronounced in the eyes of a
convenience seeker.
