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1、Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids Gerald Haubl Valerie Trifts Faculty of Business, University of Alberta, Edmonton, Alberta, Canada T6G 2R6 gerald.haeublualberta.ca triftsdatanet.ab.ca Abstract Despite the explosive growth of electroni
2、c commerce and the rapidly increasing number of consumers who use interactive media (such as the World Wide Web) for prepurchase infor- mation search and online shopping, very little is known about how consumers make purchase decisions in such set- tings. A unique characteristic of online shopping e
3、nviron- ments is that they allow vendors to create retail interfaces with highly interactive features. One desirable form of inter- activity from a consumer perspective is the implementation of sophisticated tools to assist shoppers in their purchase de- cisions by customizing the electronic shoppin
4、g environment to their individual preferences. The availability of such tools, which we refer to as interactive decision aids for consum- ers, may lead to a transformation of the way in which shop- pers search for product information and make purchase de- cisions. The primary objective of this paper
5、 is to investigate the nature of the effects that interactive decision aids may have on consumer decision making in online shopping environments. While making purchase decisions, consumers are often unable to evaluate all available alternatives in great depth and, thus, tend to use two-stage process
6、es to reach their de- cisions. At the rst stage, consumers typically screen a large set of available products and identify a subset of the most promising alternatives. Subsequently, they evaluate the lat- ter in more depth, perform relative comparisons across prod- ucts on important attributes, and
7、make a purchase decision. Given the different tasks to be performed in such a two-stage process, interactive tools that provide support to consumers in the following respects are particularly valuable: (1) the initial screening of available products to determine which ones are worth considering furt
8、her, and (2) the in-depth com- parison of selected products before making the actual pur- chase decision. This paper examines the effects of two deci- sion aids, each designed to assist consumers in performing one of the above tasks, on purchase decision making in an online store. The rst interactiv
9、e tool, a recommendation agent (RA), al- lows consumers to more efciently screen the (potentially very large) set of alternatives available in an online shopping environment. Based on self-explicated information about a consumers own utility function (attribute importance weights and minimum accepta
10、ble attribute levels), the RA generates a personalized list of recommended alternatives. The second decision aid, a comparison matrix (CM), is de- signed to help consumers make in-depth comparisons among selected alternatives. The CM allows consumers to organize attribute information about multiple
11、products in an alternatives attributes matrix and to have alternatives sorted by any attribute. Based on theoretical and empirical work in marketing, judgment and decision making, psychology, and decision support systems, we develop a set of hypotheses pertaining to the effects of these two decision
12、 aids on various aspects of consumer decision making. In particular, we focus on how use of the RA and CM affects consumers search for product information, the size and quality of their consideration sets, and the quality of their purchase decisions in an online shop- ping environment. A controlled
13、experiment using a simulated online store was conducted to test the hypotheses. The results indicate that both interactive decision aids have a substantial impact on consumer decision making. As predicted, use of the RA reduces consumers search effort for product information, decreases the size but
14、increases the quality of their consid- eration sets, and improves the quality of their purchase de- cisions. Use of the CM also leads to a decrease in the size but an increase in the quality of consumers consideration sets, and has a favorable effect on some indicators of decision quality. In sum, o
15、ur ndings suggest that interactive tools de- signed to assist consumers in the initial screening of available alternatives and to facilitate in-depth comparisons among se- lected alternatives in an online shopping environment may have strong favorable effects on both the quality and the ef- ciency o
16、f purchase decisionsshoppers can make much better decisions while expending substantially less effort. This suggests that interactive decision aids have the potential to drastically transform the way in which consumers search for product information and make purchase decisions. (Decision Making; Onl
17、ine Shopping; Electronic Commerce; De- cision Aids; Recommendation Agents; Consumer Behavior; Infor- mation Search; Consideration Sets; Information Processing) Marketing Science 2000 INFORMS Vol. 19, No. 1, Winter 2000, pp. 421 0732-2399/00/1901/0004/$05.00 1526-548X electronic ISSN Marketing Scienc
18、e/Vol. 19, No. 1, Winter 2000 5 CONSUMER DECISION MAKING IN ONLINE SHOPPING ENVIRONMENTS Introduction The popularity of interactive media such as the World Wide Web (WWW) has been growing at a very rapid pace (see, e.g., GVU 1999). From a marketing perspec- tive, this has manifested itself primarily
19、 in two ways: (1) a drastic increase in the number of companies that seek to use the WWW to communicate with (potential) customers, and (2) the rapid adoption of the WWW by broad consumer segments for a variety of purposes, including prepurchase information search and online shopping (Alba et al. 19
20、97). The combination of these two developments provides a basis for substantial growth in the commercial use of interactive media. The focus of this paper is on one specic type of commercial use of interactive media: shopping in online environments. We conceptualize this behavior as a shopping activ
21、ity performed by a consumer via a computer-based interface, where the consumers com- puter is connected to, and can interact with, a retailers digital storefront (implemented on some computer) through a network (e.g., the WWW). A consumer can engage in online shopping in any location, but our con- c
22、eptualization is based on the assumptions that the products of interest are not physically present at the time and that no face-to-face assistance is available to the shopper. A unique characteristic of online shopping environ- ments is that they allow for the implementation of very high degrees of
23、interactivity. The latter is a multidi- mensional construct, the key facets of which include reciprocity in the exchange of information, availability of information on demand, response contingency, cus- tomization of content, and real-time feedback (Alba et al. 1997, Ariely 2000, Zack 1993). In the
24、context of computer-mediated communication, a distinction has been made between person interactivity and machine interactivity. While the former describes the ability to communicate with other individuals, the latter refers to the ability to interactively access information in an online database (Ho
25、ffman and Novak 1996, p. 53). Given our conceptualization of shopping in online en- vironments, the concept of machine interactivity is of particular interest. While it has been hypothesized that consumers shopping behavior in online stores may be fundamen- tally different from that in traditional r
26、etail settings (Alba et al. 1997, Winer et al. 1997), theorizing about the nature of these differences has been sparse. We propose that consumer behavior in an online shopping environment is determined largely by the degree and type of machine interactivity that is implemented in such a setting. Spe
27、cically, we hypothesize that the way in which consumers search for product informa- tion and make purchase decisions is a function of the particular interactive tools available in an online shop- ping environment. We refer to such tools as interactive decision aids for consumers. In this paper, we i
28、dentify two types of interactive decision aids that, in light of established notions about purchase decision processes, seem particularly valu- able to consumers. Based on theoretical and empirical work in marketing, judgment and decision making, psychology, and decision support systems, we develop
29、a set of hypotheses pertaining to the effects of each of these tools on consumers search for product infor- mation, the size and quality of their consideration sets, and the quality of their purchase decisions in an online store. The results of a controlled experiment indicate that each of the inter
30、active decision aids has a substan- tial impact on consumer decision making, thus provid- ing a demonstration of how the availability of such tools may transform the way in which individuals search for information and make purchase decisions in online environments. The paper is organized as follows.
31、 First, we briey discuss the relevant literature on human decision mak- ing and decision aids. Next, we provide an overview of interactive decision aids for online shopping and motivate the choice of the two particular tools inves- tigated in our study. We then develop a set of hypoth- eses pertaini
32、ng to how we expect each of these decision aids to affect different aspects of consumer decision making in online shopping environments. This is fol- lowed by a description of the method used to test these hypotheses. We then report the results of our empirical study. The paper concludes with a gene
33、ral discussion of the ndings. Human Decision Making and Decision Aids Humans adapt their decision making strategies to spe- cic situations and environments (see, e.g., Payne 6 Marketing Science/Vol. 19, No. 1, Winter 2000 HA UBL AND TRIFTS Consumer Decision Making in Online Shopping Environments 198
34、2). They can be described as “cognitive misers” who strive to reduce the amount of cognitive effort associated with decision making (Shugan 1980). The notion that individuals are typically willing to settle for imperfect accuracy of their decisions in return for a reduction in effort is well support
35、ed (Bettman et al. 1990, Johnson and Payne 1985) and consistent with the idea of bounded rationality (Simon 1955). Because of this trade-off between effort and accuracy, decision makers frequently choose options that are satisfactory but would be suboptimal if decision costs were zero. This is parti
36、cularly common when alternatives are nu- merous and/or difcult to compare, i.e., when the complexity of the decision environment is high (Payne et al. 1993). One form of coping with highly complex decision environments is to use decision support systems. The latter are computer-based technologies de
37、signed to as- sist an individual (or a group) in making a decision or choosing a course of action in a nonroutine situation that requires judgment (Kasper 1996). Decision sup- port systems contain one or more tools, or decision aids, that perform distinct information processing tasks or functions (e
38、.g., search a database or sort objects by some criterion). The motivating principle underlying decision aids is that resource-intensive, but standar- dizable, information processing tasks are performed by a computer-based system, thus freeing up some of the human decision makers processing capacity.
39、 De- termining an adequate “division of labor” between hu- man and computer is crucial. Human decision makers are typically good at selecting variables that are rele- vant in the decision process, but weak at integrating and retaining large amounts of information. Effective decision aids should be d
40、esigned to capitalize on the strengths and compensate for the inherent weaknesses of their users (Hoch and Schkade 1996). A standard assumption in past research on decision support systems, most of which has focused on man- agerial decisions (e.g., Pearson and Shim 1994), is that decision makers who
41、 are provided with decision aids that have adequate information processing capabilities will use these tools to analyze problems in greater depth and, as a result, make better decisions (cf. Hoch and Schkade 1996). However, behavioral decision the- ory suggests that because feedback on effort expend
42、i- ture tends to be immediate while feedback on accuracy is subject to delay and ambiguity, decision makers may be inclined to focus more on reducing cognitive effort than on improving decision accuracy (Einhorn and Hogarth 1978, Kleinmuntz and Schkade 1993). Thus, decision aids may lead individuals
43、 to merely reduce effort without improving the quality of their decisions. In fact, there is empirical evidence that the use of de- cision aids does not necessarily enhance decision mak- ing performance (cf. Benbasat and Nault 1990), and that the latter may even be reduced as a result (Todd and Benb
44、asat 1992, p. 373). Given this mixed evidence, it cannot be assumed that a consumers use of inter- active decision aids in an online shopping context will lead to increased decision quality. Rather, this repre- sents an open question, which is addressed in this paper. In the following section, we rs
45、t provide a general overview of interactive decision aids available to con- sumers for the purpose of online shopping. Based on established notions about purchase decision making and on characteristic features of online shopping en- vironments, two decision aids are selected for inclu- sion in our e
46、mpirical study. These two tools are then discussed in detail. Interactive Decision Aids for Online Shopping Overview of Tools The technology available for implementing machine interactivity in online shopping environments has the potential to provide consumers with unparalleled op- portunities to lo
47、cate and compare product offerings (Alba et al. 1997, p. 38). Such capabilities are particu- larly valuable given that online stores cannot offer physical contact with products, do not allow face-to- face interaction with a salesperson, and may offer a very large number of alternatives because of th
48、eir vir- tually innite “shelfspace,” i.e., the lack of physical constraints with respect to product display. Interactive decision aids that may be of use to con- sumers who wish to shop online include a wide variety of software tools, ranging from general-purpose search engines (e.g., , ) to sophist
49、icated agent-mediated electronic commerce Marketing Science/Vol. 19, No. 1, Winter 2000 7 HA UBL AND TRIFTS Consumer Decision Making in Online Shopping Environments systems (e.g., , ). A com- mon classication of interactive shopping agents is based on whether a tool is designed to help a consumer determine (1) what to buy or (2) whom to buy from. These two tasks may be referred to as product brokering and merchant brokering, respectively (see Guttman et al. 1998). For the pu