Measure Application

Making product purchase decisions is a risky endeavor. Therefore, in order to handle perceptions of deterrent risks, consumers typically search for information (Bettman, 1973; Srinivasan & Ratchford, 1991). Here, they are not limited to internal information gathered through prior consumption experiences and mirrored by existing knowledge, but consumers are eager for external information, especially when the purchasing task is new and not a routine. While, in earlier times, access to product information was limited to particular sources (e.g., newspapers, television), nowadays the rapid development of the Internet grants consumers a new opportunity to find such information in a previously unexpected depth (Jepsen, 2007). Actual market reports, as well as earlier research studies, demonstrate that consumers have been actively using the Internet when looking for purchase-relevant information for more than ten years (Fallows, 2005; Peterson & Merino, 2003). Moreover, the Internet seems to increase its importance in the eye of the consumer from year to year, as we are entering a new era of consumer interaction and cooperation. Research has shown that certain characteristics of the Internet as an information channel have modified consumers’ information search patterns, as well as the outcomes of the purchase decision process in general. The medium enables consumers to fall back on individualized information with minimal effort and cost, whenever and wherever they want (Peterson, 1997). Further, the opportunity to get access to information that was previously inaccessible to the shopper community (Kraut et al., 1998) is another critical aspect of the Internet that helps consumers to increase their decision-making efficiency (Alba et al., 1997; Widing & Talarzyk, 1993) - and to potentially become “smarter shoppers”.

However, the difficulty of selecting adequate information out of an apparent endless amount of available online information is an obstacle for improved decision making. Consumers are not in the possession of systematic filters that help them to access the quality of online information at face value (Eysenbach & Diepgen, 1999). Rather, they have to evaluate different kinds of information sources based on generalized attitudes and personal dispositions. Here, a pivotal concept is the matter of trust in information. It is the tenor of this thesis that trust represents an important psychological construct that reflects consumers’ dependence on the trusting object and triggers its personal relevance. Consequently, trust has a critical role in evaluating information quality, as well as subsequent market information usage (Park et al., 2009).

While information on the Internet is manifold, actual studies demonstrate that consumers typically source information from two major origins: (1) consumer-to-consumer communication (i.e., C2C, online customer reviews) (see Chapter 1), and (2) business-to- consumers communication (i.e., B2C, online advertising). Within recent years, online advertising has lost its static character. Nowadays simple banner advertising and websites are still instruments of the online marketing portfolio; however, the development also led to more innovative advertising models, as well as online channels, including on-demand advertising with ads customized to search engine enquiries and personalized offers via newsletters. Online advertising has expanded to a diverse field, as can be seen from its definition. In this thesis, online advertising is defined as any form of corporate market communication via the Internet. Therefore, it includes corporate websites, banner ads, video clips, but also e-mail messages or interactive games with corporate sponsorship (Schlosser et al., 1999). All these approaches stem from the new opportunities offered by the Internet to facilitate interaction between the consumer and the marketer (Breuer & Brettel, 2012; Rappaport, 2007). The industry’s expectations about the positive outcomes of online advertising, such as increased customer influenceability, led to continuous increases in the share of marketing expenditures. While in 2003 Internet advertising made up $12.6 billion, worldwide total expenditures had already reached $120.4 billion in 2012, and is further predicted to increase to $132.4 billion by 2015 (ZenithOptimedia, 2012). Hence, online advertising is expected to account for more than 23% of all global ad expenditures.

In awareness of this global trend, advertising effectiveness as well as accountability are both topics of continuous interest among marketing researchers and practitioners (Clark, 1999; McDonald, 2010; Rust et al., 2004). Hence, for various marketers, the analysis of advertising channel effectiveness and tied consumer behaviour (e.g., ad persuasiveness, impact) are regarded as the key areas of concern of the professional marketing community (Brettel & Spilker-Attig, 2010). As a consequence, numerous studies have attempted to assess the determinants of advertising effectiveness by demonstrating which advertisements or channels are influential, when, under which circumstances, and for which kind of consumers (Shamdasani et al., 2001; Tellis et al., 2005). A key insight of this research is that advertising achieves its highest impact when it is target-group specific and differentiates between various consumer groups (e.g., in terms of the selected advertising channel) (Iyer et al., 2005; Reutterer et al., 2006; Zeithaml et al., 2001). It is the guiding tenor of contemporary marketing endeavors that the application of marketing instruments should depend on the kind of relationship between the company and its customers (e.g., Bolton et al., 2004; Homburg et al., 2008; Verhoef & Donkers, 2005). Therefore, it is important to profoundly understand which information sources specific groups of consumers place their emphasis on/trust in. Or, in other words, as consumers are likely to trust some information sources more than others, it is crucial to understand which kinds of trusted sources are most likely to influence online as well as offline purchase decisions (Cheema & Papatla, 2010). This is also well supported by research, which regards the presence or absence of trust as key to communication effectiveness (e.g., Cheema, 2008; Gauzente, 2010; Urban et al., 2000). A deeper investigation into this sphere enables marketers to figure out how to maximize outcomes of online strategies, for example by better allocating the billions of advertising dollars, and to anticipate the consequences of consumer information gathering - be it from marketer- (B2C communication) or consumer-provided information (C2C communication) sources. The identification of the most responsive/trusting market segments is hence key.

By adopting the definition provided by Soh (2007), trust in online advertising (AdTrust) is defined as “a consumer’s confidence that [online] advertising is a reliable source of product/service information and one’s willingness to act on the basis of information conveyed by [online] advertising” (p. 29). In order to derive a meaningful grouping of online communication recipients, the present thesis addresses the following question:

RQ 13: (a) Can online consumers be meaningfully segmented according to their trust in online customer reviews (eWOMTrust) and online advertising (AdTrust)? (b) How can the segments be profiled?

Answers to this question should fill the still-existing research gap concerning the lack of knowledge about consumer beliefs and attitudes towards online market information. More precisely, this research should help to gain a better insight into observable differences in information-seeking behaviours related to online advertising, as well as online customer reviews and attitudinal and socio-demographic covariables. Amongst other considerations, this research sheds light on the question of who accesses the large arsenal of unofficial product information and who is likely to be influenced by positive or negative information available on the Internet. But it also provides insight into the characteristics of consumer groupings which are most responsive to the company’s online advertising arsenal, thus furnishing the company with the opportunity to control at least some of the product communication sent to the consumer. Therefore, this research provides answers to several still-unanswered calls of the research community on the role of different information sources for purchasing decisions (e.g., Bucklin et al., 2002; Cheema & Papatla, 2010; Ratchford et al., 2003; Ward & Ostrom. 2003).

In order to evaluate the above-mentioned series of research questions and hypotheses, a multi- stage/multi-study research approach is proposed. The reader will find the details concerning the research process and the methods applied in each stage and study in the next chapter, before the research results are presented in Chapter 5.

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