It has been found that risk perceptions affect consumers’ attitudes toward counterfeits [BLO 93; WEE 95; NIA 00]. The literature suggests that regardless of the type of risk (social, financial, physical, temporal, or performance), consumers only buy counterfeits of those products where risks are perceived to be low. In China, counterfeit products can be found openly displayed in many street markets as well as in small- and medium-sized businesses. Consumers of counterfeits face the possibility of being arrested on charges of criminal activity. However, enforcement of China’s anti-counterfeit laws is still a concern for local and global brand owners [CHO 00]. By extension, consumers who have a weak perception of being caught and charged will exhibit more positive attitudes toward the purchase of these
products. The level of perceived risk is a function of the consumer’s perception of what is at stake and his or her certainty that the consequences will be favorable or unfavorable [CLO 96]. Therefore, the following hypothesis is proposed:
H1: There is a positive relationship between low-risk perception towards counterfeits and a positive attitude towards counterfeits.
13.2.2. Brand parity
Brand parity is defined as the “overall perception held by the consumer that the differences between the major brand alternatives in a product category are small”
[MUN 96: 411]. In other words, brand parity determines how similar, or different, various brands in the same category are perceived to be. Brand parity varies widely from one category to another. For example, in the banking industry, brand parity is high as most customers do not see much difference between brands within this category and yet for perfume, brand parity is quite low. In addition, it has been found that when two brands appear similar, positive word-of-mouth recommendations concerning the follower brand increases the likelihood of consideration while it decreases the choice probabilities of the early brand [GRE 03]. In China, since counterfeiting consumption is a common practice which is viewed as normal [MOG 02; KAP 06], we expected that Chinese consumers would perceive a high brand parity between the real brand and the fake one within a product category. Therefore, in our proposed model, we expected that when consumers viewed a brand and its counterfeit as similar, parity would be high and so the attitude toward counterfeits would be high as well. Therefore, our next hypothesis claims:
H2: There is a positive relationship between brand parity and a positive attitude towards counterfeits.
13.2.3. Susceptibility to Normative Influence (SNI)
Earlier research suggested that product evaluation is obtained by consulting with referent peers. Festinger [FES 54] claimed that an individual needs to compare himself or herself with other persons to prove his or her own beliefs. A normative group might have a high- or a low-opinion of a foreign product depending on the product category; for example, a German car, a French wine and Italian shoes might be highly acceptable, but an American car, a Spanish wine and Chinese shoes might
not be [CHO 95]. Whether a consumer is highly influenced by a normative group might depend on his susceptibility to interpersonal influence [BEA 89].
Susceptibility to interpersonal influence is a general trait that varies between individuals and a person’s relative susceptibility in one situation tends to have a significant positive relationship to his or her susceptibility in a range of other social situations [BEA 89]. Generally, susceptibility to normative influence has to do with the status that a consumer may perceive that he or she acquires among the consumer’s reference group after acquiring a determined product. In particular, Slama and Singley [SLA 96] claim that value-expressive types of influence are very likely to be exerted by the group of reference or target audience of the consumer’s self-presentation. Consistently, Escalas and Bettman [ESC 05] concluded that consumers report higher self-brand connections for brands with images that are consistent with the image of an in-group whereas consumers reject the social meanings of brands that arise from out-group brand usage. Therefore, the following hypotheses are posited:
H3: There is a positive relationship between “SNI” and “brand parity”.
H4: There is a positive relationship between “SNI” and “value expressive”.
13.2.4. Value-expressive function
The value-expressive function is related to the individual’s desires to enhance his or her self-concept in the eyes of others [PAR 77]. Grewal, Metha and Kardes [GRE 04] found that consumers are reluctant to abandon the products that fulfill the value- expressive function. This results in longer inter-purchase intervals, in addition to greater liability for publicly-consumed rather than privately-consumed products.
Moreover, status-conscious consumers have been found to be more likely to be affected by brand symbolic characteristics (high/low status) and by the degree of congruency between the brand user’s self-image and the brand’s image [OCA 02].
By extension, we assume that the more reluctant the consumers are, the more risks they are willing to take and the less they are influenced by the differences between the major brand and its alternatives. Therefore, the following hypotheses state:
H5: There is a positive relationship between “value expressive” and “risk perception”.
H6: There is a negative relationship between “value expressive” and “brand parity”.
13.2.5. Conceptual model
In an attempt to better understand the application of what is suggested in the literature, we propose a model that exhibits the relationship among the variables and the purchasing behavior for counterfeits in China; see Table 13.1.
Construct X² X²/df p-level RMSEA GFI AGFI RMR TLI Price Consciousness 5.42 1.35 .246 .034 .992 .973 .020 .990
Risk Perception 21.13 2.34 .012 .078 .970 .91 .049 .980 Brand Parity 1.50 .754 .470 .034 .997 .987 .051 .999 SNI .567 .28 .752 .000 .999 .995 .009 .999 Value Expressive 6.58 1.64 .159 .046 .991 .969 .023 .960
Table 13.1. Results of single-construct measurement models