Hypotheses

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3 METHODOLOGY

3.1 Research model

Based on Keaveney’s model of buyer regret (Keaveney et al., 2007), we simplified the model (see Fig. 3-1) and add three new constructs to verify the following research purposes:

Figure 3-1. Research model

3.2 Hypotheses

By conventional wisdom, it’s not difficult to imagine that people with more product expertise would experience less post-purchase dissonance. Since they have better understanding of product. Even they know many alternatives, they can still make their purchase decision without hesitation. This assumption is supported by literature, but in different aspect. As we choose perceived subjective knowledge to measure the product knowledge, we are not only examining the relationship between knowledge and dissonance, but the relationship between confidence and dissonance. Subjective knowledge can imply one’s knowledge level as well as one’s self-confidence. Perceived

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self-confidence is influential to decision making abilities (Park & Lessig, 1981) and it can serve as a predictor of dissonance (Bell, 1967; Montgomery & Barnes, 1993).

Consumers with high self-confidence are hard to influence and more certain to their decision. In contrast, consumers with less confidence are easier to be persuaded and have some doubt with their purchase decision (Bell 1967). Yet, consumers who are confident with their decision making ability and greater commitment to their decisions are found to be experience less dissonance. Based on these arguments, we hypothesize:

H1: Product knowledge is negatively related to post-purchase dissonance.

As mentioned in literature review, relationship between product knowledge and amount of external information search remains unclear. Some researchers proposed a positive relationship and some proposed negative. There were also researchers demonstrating an inverted U-shaped relationship. Assuming they were correct, the boundary of positive and negative relationship is obscure.

Based on Bloch’s research, ongoing search is related to the enduring involvement, and heavy ongoing searchers are likely to be heavy spenders. Consumers who conduct ongoing search mostly are the people that interested in the product class and they acquire product expertise through their pleasurable searching. Thus we speculate these heavy ongoing searchers have high possibility to be knowledgeable consumers. These knowledgeable consumers continue to search on regular basis due to their passion with the product class. However, once they need to make the purchase, pre-purchase search might not be essential because the product information bank is already built. On the other hand, consumers those do not have passion for the product, they don’t search in regular basis since they are not interested in the product. But when they need to make the purchase, they search to ensure a good decision. Due to these assumptions, we propose knowledge has positive influence toward ongoing search and has negative

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influence toward pre-purchase search. Past studies did not distinguish pre-purchase search and ongoing search. Thus we speculate that the inconsistence results of knowledge-search relationship from past studies might due to the difference of search.

This might also be the main cause that contributed to the inverted-U shaped relationship.

The critical point of inverted U-shaped might be the intersection point of ongoing and pre-purchase search (see Figure 3-2).

Figure 3-2. Conceptual graph of knowledge-search relationship

Now is the era of Internet, consumers’ searching behavior often occur on the internet, but sometimes still occur with absence of internet. The difference between online and offline searching behaviors is also an interesting topic. Thus we divided pre-purchase search into online and offline pre-pre-purchase search. We intended to compare the influence between these two. However, we didn’t intend to differentiate ongoing search. Since ongoing search is an information gathering activity from variety of sources, it already include online and offline search.

Noting that product knowledge and information search are influencing each other.

So in this study we are going to use cross sectional research method. We want to capture

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consumer’s state of mind after purchase and treat information search as independent variable. Hence we come out with following hypotheses:

H2a: Product knowledge is negatively related to online pre-purchase search.

H2b: Product knowledge is negatively related to offline pre-purchase search.

H3: Product knowledge is positively related to ongoing search.

In Keaveney, Huber and Herrmann’s (2007) research, they’ve mentioned that consumers are acquiring product information, as well as other available alternatives through the pre-purchase search process. In psychology’s perspective, thinking about other possible alternatives would evoke people’s counterfactual thinking that leads to regret (Kahneman & Miller, 1986). After purchase, by comparing with the unchosen alternatives, even consumers have made appropriate decision, they might still feel inadequate. When recalling the unchosen alternatives, customers may imagine the unchosen alternatives could have brought them better outcomes, then they start to feel regret. The more one seriously considers other options, the more likely for one to experience regret (Keaveney et al., 2007).

Though regret and cognitive dissonance are two different concepts, we suspect the circumstances that cause regret have high probability to cause dissonance as well. Since dissonance is the contradiction between beliefs, knowing there exists a better option other than the choice have made, certainly qualify the condition of dissonance.

Therefore we assert that search is followed by dissonance.

In Keaveney’s study (Keaveney et al., 2007), ongoing search had not been discussed at all. The relationship between ongoing search and regret remains unclear.

Thus it is one of our research subject. As long as consumers have made comparison between alternatives, there are possibility to experience dissonance. However, we speculate that the dissonance comes with ongoing search would not as severe as the

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dissonance comes with pre-purchase search. For the consumers that conduct ongoing search more than pre-purchase search (or do not conduct pre-purchase at all), they build their product information bank through ongoing search and use their accumulated product knowledge to make their choices. This group of consumers might not pay much effort on comparing the alternatives before purchase. They already know what to buy base on their internal information. So we assume people who conduct ongoing search more than pre-purchase search will experience less dissonance. As we’ve mentioned in previous hypothesis, Bloch’s research result demonstrated that heavy ongoing searchers are likely to be heavy spenders and heavy spenders are likely to have high new product awareness and frequent contact with retailers. So we expect people who conduct ongoing search heavily to be more knowledgeable customers and more knowledgeable consumers may experience less post-purchase dissonance. This provide another cue to our assumption. Thus we hypothesize that:

H4a: Online pre-purchase search is positively related to post-purchase dissonance.

H4b: Offline pre-purchase search is positively related to post-purchase dissonance.

H5: Ongoing search is positively related to post-purchase dissonance.

Previous studies supported that dissonant consumers tend to conduct post-purchase search to support their decisions (Schiffman & Kanuk, 2004; Fischer et al., 2008; Holbrook et al., 2005; Mittal et al., 1999). During their searching process, if customers only search and recognize the information that conform to their purchase decisions, then they are having confirmation bias toward their searches. Confirmation bias refers to the situation that consumers “seek confirmatory evidence and fail to search for disconfirming information for desired outcomes or strongly held values”

(Carter, Kaufmann & Michel, 2007). In other words, when the information they found contradict their beliefs, which are their purchase decisions, they either ignore them or

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interpret them in their desired way. In this case, consumers’ confidence toward their decisions are being enhanced and that can ease the dissonance if they have any. We can see that it’s possible for consumers to relieve their dissonance via biased post-purchased search, and biased post-purchased search might also ease the dissonance caused by knowledge level and searching. Hence we propose the following hypotheses:

H6: Post-purchase search is negatively related to post-purchase dissonance.

H7: The relationship between product knowledge and post-purchase dissonance is moderated by post-purchase search.

H8: The relationship between product information search and post-purchase dissonance is moderated by post-purchase search.

H8a: The relationship between online pre-purchase search and post-purchase dissonance is moderated by post-purchase search.

H8b: The relationship between offline pre-purchase search and post-purchase dissonance is moderated by post-purchase search.

H8c: The relationship between ongoing search and post-purchase dissonance is moderated by post-purchase search.

Completed research model with hypotheses are shown in Figure 3-3.

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Figure 3-3. Research model with hypotheses