Long Island University, USA
Ruby Roy Dholakia
University of Rhode Island, USA
University of Rhode Island, USA
The continued success of online shopping will be determined by the degree to which consumers utilize the Internet during their decision making process, mainly the acquisition of product information. This chapter addresses consumers’ goal-directed information search in the online marketplace. To understand consumer search behavior in this unique environment, relevant theoretical perspectives are drawn to provide a conceptual framework that provides an explanation of consumers’ online search behavior. In an environment characterized by human-computer interaction, the framework includes consumers’ choice to search information online and two sets of variables – domain and system (personal) and interruptions and information load (system), affecting information search between and within Web sites. Several implications of this conceptual framework are also discussed.
At the turn of a new millennium, the business environment has undergone a rapid transformation with the Internet, making it possible for a large number of users to access vast amounts of information through a diverse array of technical tools and services. Never before have consumers been able to shop from anywhere at anytime with a few clicks of their mouse. As a result, online shopping, an unforeseen event only a few years ago, has continued to grow. Between 1998 and 1999, business-to-consumer Internet sales in the United States grew by 120%, to approximately $33.1 billion (Shop.org & Boston Consulting Group, 2000). In 2000, Forrester Research (2001) reported that online sales to consumers amounted to $48.3 billion, representing an annual growth of 45.9%.
Despite these impressive sales growth rates, evidence suggests that many consumers search retailer Web sites intending to purchase, but subsequently abandon these purchase attempts. Jupiter Communications reported that approximately 72% of online users research products once per month (Shop.org, 2001). Such high levels of search activity should translate into similarly high purchase levels. However, it was estimated that business worldwide lost approximately $6.1 billion in 2000 due to failed purchase attempts (Blank, 2000). Conversion rates, the proportions of consumers buying from sites visited remain low, ranging between 2.8% and 3.2% according to a 2000 Boston Consulting Group study (Shop.org & Boston Consulting Group, 2000).
Moreover, a recent survey of 9,500 online shoppers conducted by BizRate.com revealed that as many as 55% of online shoppers abandon their shopping carts prior to checkout, and 82% abandon them at the point of sale (Shop.org, 2001). These statistics suggest that while the Internet has become a significant source of product information, several barriers exist that inhibit consumer movement from information search to product purchase. Among reasons commonly cited include reluctance to supply personal and credit card information, technical problems with Web sites, and difficulty in locating products.
In theory, the Internet provides vast possibilities for information search and comparisons unconstrained by time and place which traditionally restricted consumer behavior in the physical marketplace (Alba, Lynch, Weitz, Janiszewski, Lutz, Sawyer and Wood, 1997; Bakos, 1997; Sheth and Sisodia, 1999). To examine this distinctive change, several studies have adopted the economic perspective in analyzing the efficiency of the electronic market (Bailey, 1998; Bakos, 1997; Brynjolfsson and Smith, 2000) and implications for consumer information search with the focus on search costs (Degeratu et al., 1998; Hoque and Lohse, 1999; Lynch and Ariely, 2000). These studies, using conventional economic theories, have simply assumed that consumers search the same way in an online environment as they do in the physical environment. Furthermore, these studies presume a total separation of the physical and electronic marketplaces and often limit their investigation to a particular Web site and its design.
Several reasons suggest that conventional economic theories do not adequately explain consumer behavior in this new marketspace. First, the fundamental premise of economic theory is that information search will increase when search costs are reduced (Stigler, 1961). Empirical evidence, however, has shown otherwise. By examining the shopping patterns of a large panel of online users over time, Johnson et al. (2000) found that the levels of search across three product categories are fairly low, ranging from 1.1 (stores for books) to 1.8 (stores for travel-related products). Another study by Jansen et al. (2000) revealed a similar pattern from the analysis of transaction logs containing 51,473 queries posed by 18,113 users of Excite (http://www.excite.com). The results show that Web queries are short. Most users had only few queries per search. In fact, 76% of users did not go beyond their first and only query.
Second, convenience is often cited as the major reason for consumers to shop online (Burke, 1998; Jarvenpaa and Todd, 1997). When consumers perceive greater search costs in the physical marketplace, it is likely they search for information online where search costs are relatively lower. If consumers’ motivation to shop online is to reduce effort and save time, why should one expect that consumers will search for more information online even if the search cost is relatively reduced?
Third, it is cognitive, not only physical effort that affects online search behaviors. According to the Roper Starch Survey, it takes about 12 minutes on average before a user gets frustrated when searching the Internet (“Just the Facts,” 2001). Although physical efforts (e.g., going to stores) have been reduced to mouse clicks, the cognitive challenges of interacting with computers and online information remain that limit consumer information search within and between sites.
In order to provide a clearer understanding of online information search behavior, one needs to recognize that the Internet is not an isolated channel. It coexists, complements and competes with other conventional channels used by consumers to search for information and make decisions (Peterson et al., 1997). What remains unexplored is the impact of consumer choices of these established channels on subsequent information acquisition online, and how the process of information search occurs – not only within a Web site but also between different Web sites in an environment characterized by human-computer interaction. This chapter maintains that a consumer’s decision to search for information in a particular channel is likely to influence subsequent information acquisition. Therefore, when investigating online consumer search behavior, it is necessary: (1) to incorporate consumers’ online information search in reference to conventional channels, that is consumers’ motivation to search information online, and (2) to recognize consumers’ perceived search costs in the context of online environment. This chapter provides a systematic examination and a conceptual framework for online consumer information search behavior.
In the consumer behavior literature, the purchase decision process encompasses several steps. The process starts with a recognition of needs, which generates an information search. Through an information search, consumers are able to make purchasing decisions after evaluating alternatives. Although this flow of buying decision making may seem to be habitual and predictable, it is actually quite dynamic and implications for the process of information search cannot be ignored. A thorough understanding of how consumers search is critical for effective marketing communication strategies because information search represents a primary stage at which marketing can provide information and influence consumers’ decisions. Consequently, it is not surprising that marketing has a long tradition of research on consumer information search behavior and that there has been a considerable number of empirical studies in this area (Beatty & Smith, 1987; Carlson and Gieseke, 1983; Moorthy et al., 1997; Newman, 1977; Punj and Staelin, 1983; Srinivasan and Ratchford, 1991; Urbany et al., 1996).
Several perspectives have been adopted to investigate consumers’ information search processes. This chapter draws on multiple streams of literature, each of which will be reviewed. The first part will provide the background on the information search process. Extant research on information search will be then discussed from the economics of information literature. The last part of this section will focus on the properties of information processing from the psychology literature and “way-finding” paradigm.
Information search is a stage of the decision making process in which consumers actively collect and utilize information from internal and/or external sources to make better purchase decisions. Internal search occurs when consumers access information previously stored in memory. It is the primary source used for habitual and limited decision making. On the other hand, external search, which is the focus of this study, involves seeking information from sources outside of memory because the required information was not previously acquired or cannot be recalled from memory (Schmidt and Spreng, 1996). Sources such as friends, packaging or other in-store displays, advertisements, and magazines such as Consumer Reports are often utilized by consumers to facilitate their decision making. Lately, the Internet has joined other traditional media and has become a major source of information about many products and services.
Past studies also distinguish between two types of information search — pre-purchase and ongoing search (Schmidt and Spreng, 1996). Information acquired but not specifically related to an imminent purchase is regarded as ongoing search (Bloch, Sherrell, and Ridgway, 1986). In contrast, pre-purchase search is initiated when a purchase problem is recognized and ends with an actual purchase (Punj and Staelin, 1983; Srinivasan and Ratchford, 1991). Others have ignored such distinctions. For example, Schmidt and Spreng (1996) believe that ongoing and pre-purchase search are difficult to separate in practice. In this chapter, we maintain the distinction between ongoing and pre-purchase search.
In the online environment, the distinction between browsing and goal-directed behavior is necessary because browsing behavior, like window shopping (Bloch et al., 1986) may be a form of entertainment or time-filling activity. This distinction is particularly important because the attractiveness of links may be a factor for browsing, often referred to as Web surfing (Duchastel, 1998), rather than the information itself.
Consumers seeking external information face tasks such as destination selection (i.e., information source selection) and movement to the desired destination (i.e., the information source) before the analysis of the information can be undertaken (Hodkison et al., 2000). Destination selection and movement to the desired location are tasks inherent to active information search by a task-oriented consumer in any environment. Hoffman and Novak (1996) characterized this goal-directed behavior as intentional and selective search for contents.
The present chapter on consumer search for information on the Internet is guided by the following definition:
Information search is the effort expended by a consumer to acquire information in a Web-based marketspace that is directed by a specific purchase under consideration.
The online environment is characterized as a non-broadcast electronic medium requiring an active consumer (Hodkison, Kiel and McColl-Kennedy, 2000) to efficiently locate and process information. Consumers need to develop this ability and nurture it because it directly affects online information search (Hodkison et al., 2000; Spence, 1999). Two main tasks that consumers face in an online environment include: (1) location of Web sites of interest and the movement to and between those sites (inter-site search), and (2) the acquisition of information within sites of interest (intra-site search) (Hodkison et al., 2000). A typical search process incorporates both types of tasks. Consumers often alternate between inter-site and intra-site search.
Figure 1-1 delineates the process of goal-directed information search and the scope of this chapter. When consumers recognize a purchase problem, internal search is the primary source for habitual decision-making. When information stored in memory is insufficient, consumers are likely to engage in external information search. The emergence of the Internet has provided consumers an additional option for their information search activities. These activities could either take place exclusively in an online, off-line or combined environment. This chapter only deals with online information search that includes intra- and inter-sites as well as pure-play and brick-and-click sites.
Figure 1-1: Process of goal directed information search
Traditionally, information search literature has been built on the theory of economics of information (also called cost-benefit model) (Stigler, 1961). The theory hypothesizes that in searching for information, a consumer would search only up to the point where the perceived marginal gain from the search equals the perceived marginal cost of that search. In other words, when searching for information such as price, a particular buyer may not be willing to search for a small amount of savings in price, but may find greater search worthwhile if the amount of money saved is large.
How is consumers’ information search conceptualized and measured? In a survey by Newman (1977), the most common measure is the number of retail stores visited before purchase. Other measures of information search include number of information sources visited, number of types of information sought, number of product/brand alternatives considered, purchase decision time, and various indices of information-seeking activities.
The literature has also attempted to identify variables categorized by search costs and benefits that affect the amount of information search and their interrelationships. These variables include market (e.g., number of alternatives, price range), product (e.g., price, differentiation), consumer (e.g., perceived risk, education, income), and situational (e.g., time availability) characteristics. Approximately sixty variables have been studied empirically as determinants of information search (Srinivasan and Ratchford, 1991).
Despite the wide set of determinants affecting consumers’ information search, past studies have consistently shown that most consumers only engage in modest pre-purchase search for durable goods and do even less price-comparison shopping (Beatty and Smith, 1987). This could be attributed to the higher search cost in the physical environment because of factors such as limited time and mobility constraints (Putrevu and Ratchford, 1997; Urbany et al., 1996). As Stigler has proposed, higher search costs do lead to less searching. Is the same likely to be true for the online market where the search costs have been reduced? Do consumers search for more information online? Recent empirical studies seem to suggest that instead of searching more online, search activity is relatively low (Jansen et al., 2000; Johnson et al., 2000). Therefore, although the Internet reduces external search costs, the amount of information searching does not seem to increase. Certainly, this argument is contrary to Stigler’s proposition that lower search cost will lead to more information searching.
The economics of information identifies two types of search costs that influence information search — external and cognitive. The costs of resources consumers invest in search, such as monetary costs to acquire information, or opportunity costs of time during acquisitions, are external search costs. Such costs are influenced by factors beyond consumers’ direct control. They are exogenous and depend on situational influences. On the other hand, cognitive search costs are internal to the consumer and reflect the cognitive effort consumers must engage in to direct search inquiries, sort incoming information and integrate it with stored information to form decision evaluations (Goldman and Johansson, 1978; Hauser, Urban and Weinberg, 1993). They are influenced by consumers’ ability to cognitively process incoming information.
An alternative and complementary perspective to the economics of information is the information-processing paradigm drawn from psychology literature (Bettman, 1979; Bettman and Park, 1980; Darke et al., 1995). In this approach, consumers are viewed as information processors, interacting with a choice environment, acquiring and processing information and making a decision from alternatives (Bettman, 1979). This process is often guided by goals and developed constructively (Bettman, Luce and Payne, 1998). Bettman et al. (1998) outlined four of the most important goals in the decision making process which capture many motivational aspects of information search — the accuracy of decision, minimizing the cognitive effort required for the decision, minimizing the experience of negative emotion while making the decision, and maximizing the ease with which a decision can be justified — all influencing the amount of information acquired.
Bettman and Park (1980) theorized that information search depends on both one’s ability and one’s motivation. Either determinant without the other inhibits information search. The notion that both ability and motivation are required to process information is consistent with Bettman’s (1979) model and with Cacioppo and Petty’s (1982) Elaboration Likelihood Model (ELM) that suggests that both the ability and motivation to process information are necessary before someone engages in effortful cognitive processing. Similarly, it is logical to posit that both motivation and ability are required to acquire information via effortful search. In dealing with the question how consumers search for information, Darke et al. (1995) proposed the heuristic-systematic approach to information search behavior and argued that consumers use various heuristic cues often encountered in the process of searching.
Since the online environment possesses several spatial characteristics, researchers have applied the way-finding paradigm to analyze online navigation (Hodkison et al. 2000; Spence, 1999). Downs and Stea (1977) define way-finding as “the process of solving one class of spatial problems, the movement of a person from one location on the earth’s surface to another” (p. 55). Passini (1984) equated way-finding with the concept of spatial orientation, which he defined as the ability of a person to determine where they are within a physical setting. Concepts such as landmarks and routes associated with physical navigation were evaluated and applied in these new spaces (Darken and Sibert, 1996).
When users engage in goal-directed navigation, they usually use three methods: landmark, route and survey knowledge (Hodkison et al., 2000; Wickens, 1992). Each method is used under different conditions and depends on the navigator’s familiarity with the environment. First, landmark (Dillion, McKnight and Richardson, 1993) or place knowledge (Garling and Golledge, 1989; Gopal, Klatzky and Smith, 1989) refers to the salient familiar sights at intermittent points along the route of travel. When a person navigates by landmarks, it is critical that distinctive markers be used in the display to aid both in finding the route to the goal site as well as in determining where the navigator is currently located along the path to the site.
Second, route knowledge is the ability to navigate that guides a user from one point to another by using landmark knowledge (Dillion et al., 1993). This allows users to string together a series of landmarks that determines the route to be followed. It only works when the user is on a familiar route through extensive experience with a particular environment. Finally, survey knowledge requires sufficient knowledge by the user to form a cognitive map of the navigational space (Tolman 1948) and represents a “world frame of reference rather than an egocentric one” (Dillion et al., 1993, p. 74). It is the most sophisticated form of spatial knowledge.
Hodkison et al. (2000) elaborate these concepts in the online environment. Landmarks are stable and conspicuous in an environment (Dillion et al., 1993) and could include search engines and a user’s frequently visited sites from bookmarks or manual entry of a URL. Route knowledge consists of instructions that must be followed to arrive at the desired destination. These instructions enable navigation although the user does not really know much about the environment.
Online navigation follows a series of routes. For example, a consumer using Yahoo with route knowledge may follow these steps to reach the destination for travel-related shopping activities – upon arrival at Yahoo, click on Yahoo! Shopping, click on “Travel,” and so on. Route knowledge only works when the user is on a known route and does not preclude the user from getting lost if a wrong turn is taken (Wickens, 1992). In an online environment, users can retrace their steps to a familiar landmark by hitting the “back” button on the browser. Survey knowledge consists of a cognitive map of cyberspace. An online user may be aware of a large number of search engines and their strengths and weaknesses, including their method of data acquisition. Similarly, users with survey knowledge may have imaginary representations of the Web sites that enable a seamless navigation.
In summary, the economics of information focuses on external factors such as market characteristics influencing consumer information search at the macro level. The psychological approach focuses on internal factors such as motivation and ability at the micro level. Way-finding paradigm focuses on users’ spatial knowledge which could facilitate information search in an online environment. Although conceptually distinct, these theoretical perspectives are complementary and can be integrated to examine consumers’ information search behavior in the online environment.
“Human rational behavior is shaped by a scissors whose two blades are the structure of task environments and the computational capabilities of the actor.” (Simon, 1990, p. 7)
As the opening quote illustrates, consumer behavior is determined by the interaction between the properties of personal information processing systems and the properties of task environments. Consumer decision processes are constructive in nature — constructed by the decision makers themselves (Bettman et al., 1998) as well as the context of the particular external environment (e.g., information presentation format, time pressure) in which the decisions are made (Bettman, Johnson, Luce and Payne, 1993; Bettman and Kakkar, 1977; Coupey, 1994; Payne, 1982).
From the perspective of consumers, the Internet has changed their relationship with sellers because of the unprecedented increase in the number of choices and levels of control over the message (Sheth and Sisodia, 1999). It has also changed the decisionmaking environment by the amount, type, and format of information available to consumers (Alba et al., 1997; Bakos, 1997) because it provides tools for information storage, for information search and for decision analysis. Tools such as bookmarks, search engines, and decision aids (shopbots) are likely to influence consumer information search behavior. In addition, the Internet has transformed consumer behavior in two ways: (1) transformation of the consumers into online shoppers that requires the usage of computers, and (2) transformation of the physical stores into a marketspace that is information technology intensive (Koufaris, Kambil and LaBarbera, 2001). In order to understand online consumer behavior, it is necessary to include the interaction between the combined roles of consumer/computer user and information technology provided by the online stores. Personal factors such as domain and system expertise as well as system factors such as information load and interruptions will impose certain search costs on consumers and influence online information search.
As a market discontinuity (Mahajan and Wind, 1989), the Internet is likely to have a profound effect on how consumers construct and adjust their decision-making processes appropriately to the new decision-making environment. How are expectations about changes in consumer search behavior being realized in an online environment? The remainder of this chapter presents a conceptual framework to understand consumer search behavior in an online environment.
Figure 1-2 proposes a conceptual framework of consumer information search in an online environment. In the consumer decision process, information search begins when consumers recognize a purchase problem. To solve this problem, consumers have the choice of searching for information from two channels. They can search for information exclusively online or off-line, or in combination (Peterson et al., 1997). The specific choice of information channels is likely to influence the amount of information searched in the Web-based market (Peterson et al., 1997). The process of online information search is characterized by the human-computer interaction termed navigation, which is influenced by system and personal factors. Consequently, these factors will affect the amount of information in an online environment.
Figure 1-2. Conceptual framework of online search behavior
With the Internet as an additional option, consumers can choose (1) whether to focus on a product or service category, or a brand at any stage of the information acquisition process, (2) whether to use the Internet or a conventional retail channel for information acquisition, and (3) whether to use the Internet or a conventional retail channel for the final transaction and brand acquisition (Peterson et al., 1997). There are four possible choice outcomes:
This chapter only focuses on consumers’ decision to search for information and purchase online.
Purchasing online requires consumers to change their conventional behavior. Behavioral change is difficult and often requires incentives such as explicit monetary savings or increased convenience. Several empirical studies have attempted to provide some insights on the factors influencing consumers to engage in online shopping (Bellman et al., 1999; Degeratu et al., 1999; Jarvenpaa and Todd, 1997).
In their survey, Jarvenpaa and Todd (1999) found that convenience was the single most salient benefit of online shopping. Similarly, Degeratu et al. (1999) found online shoppers to have higher incomes and higher opportunity costs. They are likely, therefore, to be more convenience sensitive and less price sensitive. Bellman et al. (1999) also found that online buyers have “wired lifestyles,” are “time starved,” and “seek new ways to find information and buy things that are faster and more convenient.” In summary, these studies suggest that consumers who decide to shop online often expect minimal external search cost. Therefore, when consumers perceive that shopping off-line is inconvenient, they are likely to use the Internet for information acquisition. In other words, for consumers to search for information online, the perceived external search cost is lower in an online environment than in the physical market.
In the online environment, external search costs have been significantly reduced to mouse clicks. However, information in such an environment is highly visual and perceptual. It is likely to increase cognitive search costs that affect consumers’ search for information. In addition, information search online is characterized by human-computer interaction requiring consumers’ ability and knowledge to acquire information (Hodkison et al., 2000; Spence, 1999). In order to search online, consumers must not only be able to locate the Web sites of interest and move between sites but also to acquire information within the sites. There are several ways to identify the location of Web sites: (1) via search engine, (2) via manual entry of a URL, and (3) via memory-aid of a browser such as bookmarks. Given the vast amount of information available on the Internet, these search techniques will affect consumer information search (Hodkison et al., 2000). As a result, the Internet imposes a certain degree of cognitive search cost on consumers, negatively impacting the amount of information searched.
In the information-rich online environment, consumers need to be transformed as computer users as well (Koufaris et al., 2001). They must be able to identify the location of information and employ efficient search techniques, hence, personal variables such as domain and system expertise are likely to affect consumers’ search for information. Further, coupled with personal variables, system factors such as interruption and information load are likely to impose search costs on consumers and influence the amount of information search.
Domain expertise involves knowledge that allows consumers to solve problems quickly and effectively. It is defined as the ability to identify, evaluate and exploit marketplace opportunities, and consists of mental representations which guide consumer search behavior. The way-finding paradigm suggests that consumers have a cognitive map built on three types of spatial knowledge — landmark, route and survey knowledge (Hodkison et al., 2000; Spence, 1999). This cognitive map consists of a form of “general knowledge of the world that aids humans in navigation tasks” (Dillion et al., 1993, p. 172). For example, consumers may have some knowledge of the use of search engines and of the specific portal sites for a variety of product offerings. Because of this cognitive map, consumers are able to “plan routes, avoid becoming lost, or identify shortcuts” (Dillion et al., 1993, p. 173) during information search. Consumers with broader cognitive maps are able to identify information easily and efficiently.
Apart from the way-finding paradigm, both the economics and psychology literature conceptualize knowledge as product-related knowledge including objective and subjective knowledge (Brucks, 1985). Objective knowledge is conceptualized as what a consumer actually knows, whereas subjective knowledge is defined as the consumer’s perception of the amount of information he/she knows about the product category.
The conceptual relationship between ability and external information search activity is similar (Cacioppo & Petty, 1986). Perceived ability to search is defined as “the perceived cognitive capability of searching for and processing information” (Spreng and Schimt, 1996, p. 248). It involves cognitive processing ability, knowledge of procedures for searching, and knowledge of sources of information (Brucks, 1985). Empirical studies have found knowledge to be positively related with information search in the physical environment (Alba and Hutchinson, 1987; Putrevu and Ratchford, 1997; Urbany, Dickson and Kalapurakal, 1996).
It is necessary to note that knowledge of the electronic environment could precede the knowledge of product categories and thus play an important role in the process of information search in an online environment. In order to search for information online, consumers must know where to search for product category information of interest. In this research, knowledge is broadly defined to include knowledge of electronic markets as well as product categories. Unlike the familiar physical environment, where consumers are exposed to the location of stores in a myriad of ways, exposure to Web sites occurs from more active browsing or bookmarking behaviors. Since the Internet, particularly online shopping, is a new phenomenon, identifying online stores is often aided by directories from portals or advertising media. Therefore, consumers with a higher level of domain expertise will search for more information between sites because they are able to effectively locate the information and evaluate the information in the search process.
In order to search for information in an online environment, consumers must possess a basic capacity to manipulate and interact with the physical interface of a search system. For example, the abilities to begin and end, to read from the screen, to make selections from various types of menus, and manage various functions on the computer are characteristics of system expertise. It is defined as skills needed to use computers as well as navigate the WWW. As Ratchford et al. (2001) point out, fixed cost to using the Internet is high. Not only do consumers need access to a computer system and the Internet but also a considerable amount of knowledge is required.
Similarly, Hodkison et al. (2000) noted that consumers’ search techniques will seriously affect their decision processes. Expectedly, computer skills as well as search techniques are likely to influence consumers’ ability to efficiently locate and search for information and will thus impact the level of perceived search cost.
The distinctive capability of the Internet is to provide access to a tremendous amount of information, including information of low value to the consumer, such as inaccurate search queries, recommendations based on the consumer’s previous purchase, unorganized information, etc. These may increase information load and impose a cognitive processing burden on consumers. Information overload has been found to influence the consumer decision process (Jocoby, 1974; Jocoby, Speller and Berning, 1974) and decrease the amount of information search (Cook, 1993).
In addition, research by Jansen et al. (2000) with the Excite search engine found that consumer queries on the Web are brief. Most users did not go beyond their first and only query. Based on these findings, it is likely that high information load increases external search costs and thus prevents consumers from accessing more information.
The Internet is an interactive information search and decision environment for consumers, providing them with greater control over information. Features such as banner ads, pop-up windows, and intelligent agents that make purchase recommendations are being used frequently by marketers to push information, to attract consumer attention, and to promote sales. Other interactive features such as surveys and user registration act as distractions to the consumers’ search process and further affect their decision performance and satisfaction (Xia and Sudharshan, 2000).
Empirical studies on interruptions indicate they distract subjects from the current activity, and demand the allocation of cognitive capacity for processing the interruption (Kahneman, 1973). An interruption leads to extra time needed for the original task (Laird, Laird and Fruehling, 1983). Additionally, Norman and Bobrow (1975) suggest that interruptions distract attention and place great demands on cognitive processing. In order to keep the consumer motivated, there must be an appropriate level of interruption (Xia and Sudharshan, 2000). Beyond a certain threshold, interruptions may become seriously dysfunctional. As the frequency of interruptions increases, cognitive demand may become very high and the task may become onerous, causing severe frustration. Therefore, it is likely to increase consumers’ perceived search cost and reduce external information search.
The chapter focuses on understanding the implications of the Internet on consumer information search at theoretical and managerial levels. Theoretically, most of the overall literature on information search examines the context of the physical marketplace. The focus is on information search at the level of product categories or brands in order to determine how consumers process information as well as the determinants of the amount of information search. This emphasis on products or brands and search costs is imposed by the physical market, a context where the geographical characteristics confine consumers to a certain area. For instance, choices of stores are limited by distance. In the electronic market, physical distance is irrelevant. Theoretically, consumers can visit a large number of online stores. Therefore, it is necessary to expand the scope of information search to include store and product levels.
Managerially, understanding consumer search in an online environment can have a direct impact on a firm’s capability to meet customer needs. An understanding of online consumer search behavior will add to the firm’s knowledge of the effects of the Web-based environment in a number of areas. For example, in this environment where consumers have the control over and access to vast amounts of information, a significant challenge is determining how to prolong the consumers’ visits and turn them from browsers to buyers; in other words, how to get consumers to make their purchase decision online after they have gathered information. Since any online activity (e.g., abandoning the shopping cart or visiting other competing retailers) is only one click away, it is vital for online retailers to ensure that consumers complete their transaction.
Reducing search costs, while at the same time reducing the number of clicks, has an important implication for marketing objectives of online retailers. For example, Hoque and Lohse (1999) examined the effects of changes in interface design on search cost. Their results suggest that consumers are more likely to choose advertisements near the beginning of the list from online directories than from traditional paper directories. A business located further down from the top of the list is less likely to be considered. Similarly, Lynch and Ariely (2000) found that making price information more accessible on the Internet does not necessarily increase consumers’ price sensitivity. Thus, increasing transparency of the information environment seems to reduce buyers’ search cost, and increase consumer shopping enjoyment and customer retention. Speeding the checkout process, as in Amazon.com’s “one-click shopping,” could also significantly facilitate consumers’ buying process.
Moreover, many online retailers employ features such as banner ads and pop-up windows to generate additional revenues and promote sales. These features also increase interruption of the search process, distracting and disorienting consumers in this highly visual and perceptual environment. By understanding the effects of interruption, online retailers could prevent consumers from getting lost in this information space and guide them to the information destinations of interest.
In conclusion, the online market offers consumers vast opportunities because it reduces physical efforts of information search and provides access to a large amount of information and choices. What may have been substituted, however, is the cognitive effort required by the consumers to interact with computers. This effort may prevent consumers from taking advantage of the opportunities to search for more information. In this information age, organization of consumer activities have become more complex with the availability of fast, efficient and powerful means of communication that can have a significant impact on the way consumers organize the environment they live in and interact with. With these opportunities, however, accompany with additional burdens of search techniques that undoubtedly affect consumers’ search behavior. The uncertainty with regard to the location of information, along with the complex system factors, adds to the possible change of consumer behavior that deserves further investigation.
Alba, J., & Hutchinson J. (1987, March). Dimensions of consumer expertise. Journal of Consumer Research, 13, 411-454.
Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz. R., Sawyer. A., & Wood, S. (1997, July). Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. Journal of Marketing, 61, 38-53.
Bailey, J. P. (1998). Electronic commerce: Prices and consumer issues for three products: books, compact discs, and software. Organisation for Economic Cooperation and Development, 98(4).
Bakos, J. Y. (1997, December). Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 43, 1676-1708.
Beatty, S. E., & Smith, S. M. (1987, June). External search effort: An investigation across several product categories. Journal of Consumer Research, 14, 83-95.
Bellman, S., Lohse, G. L., & Johnson, E. J. (1999). Predictors of online buying behavior. Communications of the ACM, 42(12), 32-38.
Bettman, J. R. (1979). An information processing theory of consumer choice. Addison-Wesley.
Bettman, J. R., Johnson, E. J., Luce, M. F., & Payne, J. W. (1993, July). Correlation, conflict, and choice. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19, 931-951.
Bettman, J. R., & Kakkar, P. (1977). Effects of information presentation format on consumer information acquisition strategies. Journal of Consumer Research, 3, 233-240.
Bettman, J. R., Luce, M. F., & Payne J. W. (1998, December). Constructive consumer choice processes. Journal of Consumer Research, 25, 187-217.
Bettman, J. R., & Park, C. W. (1980, December). Effects of prior knowledge and experience and phase of the choice process on consumer decision processes: A protocol analysis. Journal of Consumer Research, 7, 234-248.
Blank, C. (2000, December 18). Study: E-tailers must close more sales. Marketing News, 86.
Bloch, P. H., Sherrell, D. L., & Ridgway, N. M. (1986, June). Consumer research: An extended framework. Journal of Consumer Research, 13, 199-126.
Brucks, M. (1985, June). The effect of product class knowledge on information search behavior. Journal of Consumer Research, 12, 1-15.
Brynjolfsson, E., & Smith, M. D. (2000, April). Frictionless commerce? A comparison of Internet and conventional retailers. Management Science.
Burke, R. R. (1998). Real shopping in a virtual store. In S. P. Bradley & R. L. Nolan (Eds.), Sense and respond: Capturing the value in the network era. Boston: Harvard Business School.
Cacioppo, J. T., & Petty, R. E. (1982, January). The need for cognition. Journal of Personality and Social Psychology, 42, 116-131.
Carlson, J. A., & Gieseke, R. J (1983, March). Price search in a product market. Journal of Consumer Research, 9, 357-365.
Cook, G. J. (1993). An empirical investigation of information search strategies with implications for decision support system design. Decision Sciences, 24(3), 683-697.
Coupey, E. (1994). Restructuring: Constructive processing of information displays in consumer choice. Journal of Consumer Research, 21(1), 83-99.
Darke, P. R., Freeman, J. L., & Chaiken, S. (1995). Percentage discounts, initial price, and bargain hunting: A heuristic-systematic approach to price search behavior. Journal of Applied Psychology, 80(5), 580-586.
Darken, R. P., & Sibert J. L. (1996). Navigating in large virtual worlds. International Journal of Human-Computer Interaction, 8, 49-72.
Degeratu, A., Rangaswamy, A., & Wu, J. (1999). Consumer choice behavior in online and traditional supermarkets: The effects of brand name, price, and other search attributes. Working Paper, Smeal College of Business Administration, Pennsylvania State University.
Dillion, A., McKnight, C., & Richardson, J. (1993). Space – the final chapter or why physical representations are not semantic intentions. In C. McKnight, A. Dillion & J. Richardson, (Eds.), Hypertext: A psychological perspective. London: Ellis Horwood.
Downs, R,, and Stea, D. (1977). Maps in mind: Reflections on cognitive mapping. New York: Harper & Row.
Duchastel, P. (1998). Knowledge interfacing in cyberspace. International Journal of Industrial Ergonomics, 22, 267-274.
Forrester Research. (2001). NRF/Forrester online retail index. Cambridge, MA: Forrester Research, Inc. Retrieved May 28, 2001, from http://www.forrester.com
Garling, T., & Golledge, R. G. (1989). Environmental perception and cognition. In E. Zube and G. T. Moore, (Eds.), Advances in environment, behaviour, and design, 2, 203-236. New York: Plenum Publishing.
Goldman, A., & Johansson, J. K. (1978, December). Determinants of search for lower prices: An empirical assessment of the economics of information theory. Journal of Consumer Research, 5, 176-186.
Gopal, S., Klatzky, R. L., & Smith, T. R. (1989). Navigator: A psychologically based model of environmental learning through navigation. Journal of Environmental Psychology, 9, 309-331.
Hauser, J. R., Urban, G. N., & Weinberg, B. D. (1993). How consumers allocate their time when searching for information. Journal of Marketing Research, 30, 452-466.
Hodkison, C., Kiel, G., & McColl-Kennedy, J. R. (2000). Consumer web search behaviour: Disgrammatic illustration of wayfinding on the Web. International Journal of Human-Computer Studies, 52, 805-830.
Hoffman, D. L., & Novak, T. P. (1996, July). Marketing in hypermedia computer-mediated environment: Conceptual foundations. Journal of Marketing, 60, 50-68.
Hoque, A. Y., & Lohse, G. L. (1999, August). An information search cost perspective for designing interfaces for electronic commerce. Journal of Marketing Research, 36, 387-394.
Jansen, J. B., Spink, A., & Saracevic, T. (2000). Real life, real users, and real needs: A study and analysis of user queries on the Web. Information Processing and Management, 36, 207-227.
Jarvenpaa, S. L., & Todd, P. A. (1997). An empirical study of determinants of attitude and intention toward internet shopping,” Working Paper, February, University of Texas, Austin, TX.
Jocoby, J. (1974). Consumer reaction to information displays: Packaging and advertising. In S. F. Divita (Ed.), Advertising and the public interest. Chicago: American Marketing Association, 101-118.
Jocoby, J., Speller, D. E., & Berning, C. K. (1974, June). Brand choice behavior as a function of information load: Replication and extension. Journal of Consumer Research, 1, 33-42.
Johnson, E. J., Moe, W., Fader, P., Steven, B., & Lohse, J. (2000). On the depth and dynamics of World Wide Web shopping behavior. 2nd Marketing Science and the Internet Conference, University of Southern California.
“Just the Facts.” (2001, March/April). Journal of Business Strategy, 22(2), 3-4.
Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice-Hall.
Koufaris, M., Kambil, A., & LaBarbera, P. A. (2001). Consumer behavior in Web-based commerce: An empirical study. International Journal of Electronic Commerce, 6(2), 115-138
Laird, D. A., Laird, E. C., & Fruehling, R. T. (1983) Psychology and Human Relations and Work Adjustment. New York: McGraw-Hill.
Lynch, J., & Ariely, D. (2000). Wine online: Search Costs and Competition on Price, Quality and Distribution. Marketing Science, 19(1), 83-103.
Mahajan, V., & Wind, J. (1989, August). Market discontinuities and strategic planning: A research agenda. Technological Forecasting and Social Change, 36, 185-199.
Moorthy, S., Ratchford, B. T., & Talukdar, D. (1997, March). Consumer information search revisited: Theory and empirical analysis. Journal of Consumer Research, 23, 263-277.
Newman, J. W. (1977). Consumer external search: Amount and determinants. In A. G. Woodside, J. N. Sheth & P. D. Bennett (Eds.), Consumer and industrial buying behavior. New York: North-Holland, 79-94.
Norman, D. A., & Bobrow, D. G. (1975). On data-limited and resource-limited processes. Cognitive Psychology, 7, 44-64.
Passini, R. (1984). Wayfinding in architecture. New York: Van Nostrand Reinhold Company.
Payne, J. W. (1982). Contingent decision making. Psychological Bulletin, 92, 382-402.
Peterson, R. A., Balasubramanian, S., & Bronnenberg, B. J. (1997, Fall). Exploring the implications of the Internet for consumer marketing. Journal of the Academy of Marketing Science, 25, 329-346.
Punj, G. & Staelin, R. (1983, March). A model of consumer information search behavior for new automobiles. Journal of Consumer Research, 9, 366-380.
Putrevu, S., & Ratchford, B. T. (1997). A model of search behavior with an application to grocery shopping. Journal of Retailing, 73(4), 463-486.
Ratchford, B. T., Talukdar, D., & Lee, M. S. (2001, Spring). A model of consumer choice of the Internet as an information source. International Journal of Electronic Commerce, 5, 7-21.
Schmidt, J. B., & Spreng, R. A. (1996). A proposed model of consumer information search. Journal of the Academy of Marketing Science, 24, 246-256.
Sheth, J. N., & Sisodia, R. S. (1999). Revisiting marketing’s lawlike generalizations. Journal of the Academy of Marketing Science, 27(1), 71-87.
Shop.org & Boston Consulting Group. (2000). State of online retailing 3.3. Washington, D.C.: National Retail Federation. Retrieved June 30, 2001, from http://www.shop.org
Shop.org. (2001). Shop.org press room. Washington, D.C.; National Retail Federation. Retrieved June 30, 2001, from http://www.shop.org
Simon, H. A. (1990). Invariant of human behavior. Annual Review of Psychology, 41, 1-19.
Spence, R. (1999). A framework of navigation. International Journal of Human-Computer Studies, 51, 919-945.
Spreng, R. A., & Schmidt J. B. (1996). A proposed model of external consumer information search. Journal of Academy of Marketing Science, 24(3), 246-257.
Srinivasan, N., & Ratchford, B. T. (1991, September). An empirical test of a model of external search for automobiles. Journal of Consumer Research, 18, 233-242.
Stigler, G. J. (1961). The economics of information. Journal of Political Economy, 72, 44-61.
Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological Review, 55, 189-208.
Urbany, J. E., Dickson, P. R., & Kalapurakal, R. (1996, April). Price search in the retail grocery market. Journal of Marketing, 60, 91-104.
Wickens, C. D. (1992). Engineering psychology and human performance (2nd ed.). New York: Harper Collins.
Xia, L., & Sudharshan, D. (2000). An examination of the effects of cognitive interruptions on consumer on-line decision processes. 2nd Marketing Science and the Internet Conference, University of Southern California.
Section I - Consumer Behavior in Web-Based Commerce
Section II - Web Site Usability and Interface Design
Section III - Systems Design for Electronic Commerce
Section IV - Customer Trust and Loyalty Online
Section V - Social and Legal Influences on Web Marketing and Online Consumers