Teltzrow et al.:Multi-Channel Consumer Perceptions
perceived size on trust at Internet-only retailers. According to Doney and Cannon , size also turned out to be a significant signal of trust in traditional buyer-seller relationships. Large companies indicate existing expertise and resources, which may encourage trust. A large store network indicates continuity as stores may not instantly disappear [Goersch 2003]. In a multi-channel context, we assume that the consumer perception of a retailer’s physical store presence may also have a positive influence on the perception of consumer trust in the same merchant’s e-store. Thus, we hypothesize:
H1: A consumer’s trust in an Internet shop is positively related to the perceived size of its physical store network.
Reputation is defined as the extent to which buyers believe a company is honest and concerned about its customers [Ganesan 1994]. Consumers may have more trust in a retailer with high reputation because a trustworthy retailer is less likely to jeopardize reputational assets [Jarvenpaa, Tractinsky and Vitale 2000]. Several empirical studies support the hypothesis that the reputation of an e-shop has a strong influence on consumer trust in that shop [De Ruyter, Wetzels and Kleijnen 2001, Heijden, Verhagen and Creemers 2001, Jarvenpaa 1999, Jarvenpaa, Tractinsky and Vitale 2000]. A study of traditional buyer-seller relationships also provided support that reputation is an important antecedent of trust [Doney and Cannon 1997]. We assume that the effects observed for a single sales channel may also prove true for the influence of perceived reputation of physical stores on trust in the same retailer’s e-shop.
H2: A consumer’s trust in an Internet shop is positively related to the perceived reputation of its physical store network.
Concerns of online privacy have increased considerably and are a major impediment to e-commerce [Tang and Xing 2001]. Consumer privacy concerns are particularly elevated on the Internet. A measurement scale for perceived privacy towards an e-shop has been suggested by Chellappa  where privacy has been described as the anticipation of how data is collected and used by a marketer. The author also found empirical support that perceived privacy towards an e-shop is significantly related to consumer trust. We are interested in replicating this effect in a multi-channel setting.
H3: A consumer’s trust in an e-shop of a multi-channel retailer is positively related to the perceived privacy at the e-shop.
Trust is closely related to risk [Hawes, Mast and Swan 1989]. Jarvenpaa et al.  refer to risk perception as the “trustor’s belief about likelihoods of gains and losses” (p. 49). The hypothesis has been confirmed that the more people trust an e-shop, the lower the perceived risk perception [Heijden, Verhagen and Creemers 2001, Jarvenpaa 1999, Jarvenpaa, Tractinsky and Vitale 2000]. We also test this hypothesis in our model:
H4: Consumers’ trust in an e-shop of a multi-channel retailer negatively influences the perceived risk at an e- shop of a multi-channel retailer.
The theory of planned behavior [Ajzen 1991] suggests that a consumer is more willing to buy from an Internet store which is perceived as low risk. The trust-oriented model by Jarvenpaa et al.  suggests that consumers’ willingness to buy is influenced by perceived risk and attitude towards an e-shop. In the studies of Bhattacherjee  and Gefen , a direct influence between trust and willingness to buy has been suggested. Gefen, Srinivasan Rao, and Tractinsky  summarize related work focusing on the relationship between trust, risk and willingness to buy. They come to the conclusion that e-commerce researchers overwhelmingly subscribe to the mediating role of risk in the relationship between trust and behavior [Blair and Stout 2000, Cheung and Lee 2000, Limerick and Cunnington 1993, Morgan and Hunt 1994, Noorderhaven 1996, Stewart 1999]. In this way, we base our model on this established relationship in an Internet-only context and state:
H5: The lower the consumer’s perceived risk associated with buying from an e-shop of a multi-channel retailer, the more favorable are the consumer’s purchase intentions towards shopping at that e-shop.
It should be noted that although only hypotheses one and two directly seek to analyze connections between different channels in multi-channel retailing environments, hypotheses three through five are also specific to multi- channel retailing because they explicitly target established connections between features in multi-channel environments. The interrelations between the latent variables have so far been only established for environments with only one channel. The hypotheses are summarized in Figure 1.