Literature review
Rearch on the u and influence of recommendations on consumers has typically been subsumed under personal influence or word-of-mouth (WOM) rearch. In addition, as noted by Ron and Olshavsky (1987), rearch on opinion leadership and reference groups also relates to the study of ecommendations and to influence in general. Recomm
endation sources are considered primarily as information sources. Andrean (1968) propos the following typology of information sources: (1) Impersonal Advocate (e.g., mass media), (2) Impersonal Independent (e.g., Consumer Reports), (3) Personal Advocate (e.g.,sales clerks), and (4) Personal Independent (e.g., friends). Although rearch on personal influence and WOM focus on the latter two information sources, it is note worthy that impersonal independent information sources such as Consumer Reports 气门挺杆>独特的自我介绍can also rve as recommendation sources. Moreover, the Internet can provide consumers with an additional type of impersonal information source. For instance, electronic decision-making aids such as recommender systems are impersonal information sources that provide personalized information to consumers (Ansari,Esgaier,&Kohli, 2000). In an effort to extend Andrean’s (1968) typology to computer-mediated environments, we asrt that information sources can be sorted into one of four groups: (1) Personal source providing personalized information (e.g., “My sister says that this product is best for me.”); (2) Personal source providing non-personalized information (e.g., “A renowned expert says that this product is the best.”); (3)
Impersonal source providing personalized information (e.g., “Bad on my profile, the recommender system suggests this product.”); (4) Impersonal source providing non-personalized information (e.g., “According to Consumer Reports, this is the best product on the market.”).In consumer rearch, studies on personal influence, social influence, or WOM, can be categorized as studies investigating personal sources providing personalized or non-personalized information. Furthermore, studies dealing with reference groups encompass such sources as well as impersonal sources that provide non-personalized information. Thus, a new area has emerged in consumer rearch, arising mainly from information technologies such as the Internet: that of impersonal sources that provide personalized information (Alba et al., 1997; Ansari et al., 2000;Häubl & Trifts, 2000; Maes, 1999; Urban, Sultan, & Qualls,1999; West et al.,1999).Rearch on information sources suggests that personal and impersonal information sources influence consumers’ decision-making (Ardnt, 1967; Duhan et al., 1997; Gilly et al., 1998; Olshavsky &Granbois, 1979; Price & Feick,1984). For instance, Price and Feick (1984) found that consumers planned to u the following information sources for their next dura
ble good purcha: (1) Friends, relatives, and acquaintances, (2) Salespeople, (3) Publications such as Consumer Reports丝瓜的英文. However, if much is known about the relative likelihood of consumers to consider recommendations in the cour of their decision making process, little is known about how recommendations, especially in a computer-mediated environment, impact consumers’ product choices.
write的同音词Determinants of recommendation influence
mother father gentleman>piabThe current study focus on three determinants that could influence the impact of computer-mediated recommendations on consumers’ online product choices: the nature of the product recommended, the nature of the website on which the recommendation is propod, and the type of recommendation source.
Prior rearch has shown that the type of product affects consumers’ u of personal information sources and their influence on consumers’ choices (Bearden & Etzel, 1982; Childers & Rao, 1992;King & Balasubramanian, 1994). Nelson (1970) suggests that goods can be classified as posssing. either arch or experience qualities. Search qual
ities are tho that “the consumer can determine by inspection prior to purcha,” and experience qualities are tho that “are not determined prior to purcha” (Nelson, 1974,p. 730). Since it is difficult or even impossible to evaluate experience products before purcha, consumers should rely more on product recommendations for the products than for arch products. In support of this view, King and Balasubramanian (1994) found that consumers asssing a arch product (e.g., a 35-mm camera) are more likely to u own-bad decision-making process than consumers asssing an experience product, and that consumers evaluating an experience product (e.g., a film-processing rvice) rely more on other-bad and hybrid decision-making process than consumers asssing a arch product.
The nature of the website can also influence the impact of a given recommendation. Bad on previous website classifications (Hoffman, Novak, & Chatterjee, 1995; Spiller & Loh, 1998), Senecal and Nantel (2002) suggestthat recommendation sources can be ud and promoted by three different types of websites: llers (e.g., retailer or manufacturer websites such ), commercially linked third parties (e.g., co
mparison shopping websites such ), and non-commercially linked third parties (e.g., product or merchant asssment websites such as Consumerreports). More independent websites such as non-commercially linked third parties that facilitate consumers’ external arch effort by decreasing arch costs are assumed to be preferred by consumers (Alba et al., 1997; Bakos, 1997; Lynch & Ariely, 2000). By providing more alternatives to choo from and more objective information, independent websites should be perceived as more uful by consumers. In addition, prior rearch on attribution theory suggests that consumers discredit recommendations from endorrs if they suspect that the latter have incentives to recommend a product (for reviews, refer to Folkes, 1988; Mizerski, Golden, & Kernan, 1979). According to the discounting principle of the attribution theory (Kelley, 1973), which suggests that a communicator will be perceived as biad if the recipient can infer that the message can be attributed to personal or situational caus, consumers would attribute more non-product related motivations (e.g., commissions on sales) to recommendation sources that are promoted by commercially linked third parties and llers than independent third party websites. Co
nquently consumers would follow product recommendations in a greater proportion when shopping on more independent than on less independent websites.
In light of rearch on consumers’ u of relevant others in their pre-purcha external arch efforts (Olshavsky &Granbois, 1979; Price & Feick, 1984; Ron & Olshavsky,1987) and in consideration of the emergence of online information sources providing personalized recommendations (Ansari et al., 2000), Senecal and Nantel (2002) asrt that online recommendation sources can be sorted into three broad categories: (1) other consumers (e.g., relatives, friends and acquaintances), (2) human experts (e.g., salespersons, independent experts), and (3) expert systems such as recommender systems. We posit that the online recommendation sources will have different levels of influence on consumers’ online product lection. Brown and Reingen (1987) suggest that information received from sources that have some personal knowledge about the consumer have more influence on the latter than sources that have no personal knowledge about the consumer. Thus, a recommendation source providing personalized information to consumers (e.g., recommender system) should be more influ
ential than a recommendation source providing non-personalized information (e.g., other consumers).
闲逸的意思
