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Teltzrow et al.:Multi-Channel Consumer Perceptions

perceived size on trust at Internet-only retailers. According to Doney and Cannon [1997], 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 [2001] 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. [2000] 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. [2000] suggests that consumers’ willingness to buy is influenced by perceived risk and attitude towards an e-shop. In the studies of Bhattacherjee [2002] and Gefen [2000], a direct influence between trust and willingness to buy has been suggested. Gefen, Srinivasan Rao, and Tractinsky [2003] 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.

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