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«The current issue and full text archive of this journal is available at EJM The effect of consumer confusion ...»

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The current issue and full text archive of this journal is available at

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EJM

The effect of consumer confusion

44,6

proneness on word of mouth,

trust, and customer satisfaction

Gianfranco Walsh

Institute for Management, University of Koblenz-Landau,

Received January 2008

Koblenz, Germany, and

Revised May 2008,

July 2008 Vincent-Wayne Mitchell

Accepted August 2008

Cass Business School, City University of London, London, UK Abstract Purpose – Consumer sovereignty assumes that consumers have adequate product information and are able to understand that information in order to make an informed choice. However, this is not the case when consumers are confused. Recently, Walsh et al. identified dimensions of consumer confusion proneness and developed scales to measure these dimensions. Drawing on their concept of consumer confusion proneness, this paper seeks to examine consumers’ general tendency to be confused from marketplace information and its effect on three relevant outcome variables – word of mouth, trust, and satisfaction.

Design/methodology/approach – The reliability and validity of the consumer confusion proneness scale was tested on the basis of a sample of 355 consumers, using confirmatory factor analysis. The study employs structural equation modelling to examine the hypothesised relationships.

Findings – The results show that the consumer confusion proneness scale has sound psychometric properties and that the three dimensions of similarity, overload, and ambiguity have a differential impact on word of mouth behaviour, trust, and customer satisfaction.

Practical implications – The findings have implications for marketing theory and management, as well as consumer education. Marketers may apply the consumer confusion proneness scale to their

–  –  –

Introduction In competitive environments characterized by a plethora of choice, an abundance of marketing communications, decreasing inter-brand differences, increasing complexity of information and its sources as well as increasing search costs, consumers can find information processing for some purchasing tasks confusing and taxing. Indeed, some authors contend that confusion pervades almost every decision that consumers make (Snider, 1993) and incidences of consumer confusion have been reported in many European Journal of Marketing Vol. 44 No. 6, 2010 different countries and product markets, such as watches (Mitchell and Papavassiliou, pp. 838-859 q Emerald Group Publishing Limited 1997), fashion (Cheary, 1997), telecommunications (e.g., Nanji and Parsons, 1997;

0309-0566 Turnbull et al., 2000), washing powder (Harrison, 1995), health and travel insurance DOI 10.1108/03090561011032739 The effect of (e.g., Canniffe and McMannus, 1993; Brierley, 1995) own-label brands (e.g., Balabanis and Craven, 1997; Murphy, 1997) and on the Internet (Mitchell et al., 2004). consumer Consumer confusion is relevant to marketers because confused consumers are less confusion likely to make rational buying decisions, to choose products offering the best quality or best value for money and, to enjoy the shopping experience (Huffman and Kahn, 1998;

Jacoby and Morrin, 1998; Mitchell and Papavassiliou, 1999). In addition, consumer confusion has been associated with other consequences of economic relevance to companies, such as negative word of mouth (e.g., Turnbull et al., 2000), cognitive dissonance (Mitchell and Papavassiliou, 1999), decision postponement (Jacoby and Morrin, 1998; Huffman and Kahn, 1998; Walsh et al., 2007), dissatisfaction (Foxman et al., 1990), decreased trust, and decreases in loyalty (Walsh et al., 2007). Word of mouth, trust, and customer satisfaction are among the most important marketing outcomes and most measured by companies. Indeed, Ambler (2003) reports that 68 per cent of firms use customer satisfaction measures and 64 per cent customer loyalty measures. Moreover, customer loyalty and (positive) customer word of mouth communication “are referred to in the marketing literature as key relationship marketing outcomes” (Hennig-Thurau et al., 2002, p. 231) which are inextricably linked with trust.

Despite previous efforts to measure consumer confusion, limited attention has been given to developing a measure of consumer confusion proneness that captures the construct’s various sub-domains. A noticeable exception is a recent study which puts forth a three-dimensional scale of perceived consumer confusion proneness (Walsh et al., 2007). Here, we examine the effects of different types of confusion proneness on consumer general word of mouth, marketplace trust, and macro satisfaction. We begin by discussing the consumer confusion proneness concept before we discuss the construct dimensions and the related hypotheses after which we elaborate how the hypotheses were tested against empirical data. Our paper replicates and extends the work of Walsh et al. (2007) by investigating new outcome variables relevant to marketers and companies. Finally, the results are discussed with reference to marketing as well as consumer policy and education.

The concept of consumer confusion proneness and hypotheses development Some authors argue that consumer confusion is predominantly non-conscious which implies that conscious confusion takes place at least occasionally (e.g., Poiesz and Verhallen, 1989). Walsh et al. (2002) addressed the conscious/unconscious nature of confusion in their conceptual piece. They argue that awareness can be seen as an important aspect because it relates to consumers’ abilities to take measures to reduce it.





Also, Mitchell and Papavassiliou (1999) stress this as an important aspect because it concerns the consumer’s ability to initiate confusion reduction strategies. In the present study, the authors treat consumer confusion as something the consumer is conscious of as a “state” and must deal with.

Drawing on Walsh et al.’s (2007) characterization of consumer confusion as a conscious condition or “state” that individuals may be prone to, we see this as causing them to act differently and/or to affect their decision making ability. For example, when confused, consumers are often in a state of anxiety, frustration, lack of understanding and indecision. Confusion proneness can be seen how easily/often EJM consumers experience this state of confusion or as “consumers” general tolerance for processing similar, too much or ambiguous information, which negatively affects their 44,6 information processing and decision-making abilities’. This approach from Walsh et al.

(2007) contributes to a more sophisticated understanding of the dimensions and outcomes of consumer confusion proneness and builds on previous work which has focused on specific situations of either stimulus similarity or overload.

840 Once confused, there are often general negative consequences. For example, when consumers perceive different brand-related stimuli as similar, overwhelming or unclear and buy the “wrong” brand, the chosen brand might be “inefficient” because it might fail to deliver the desired utility (Kamakura et al., 1988). Or, because the state of confusion is linked with uncertainty, anxiety, a lack of understanding and indecision, the choice process is inefficient and frustrating. Drawing on Walsh and Mitchell (2005a), we argue that confusion can result in mistaken purchases, product misuse, product misunderstanding or misattribution of various product attributes which result in a non-maximization of utility. We now look at each type of confusion in turn to develop our hypotheses.

Similarity confusion proneness Similarity confusion proneness is defined as consumers’ “propensity to think that different products in a product category are visually and functionally similar” (Walsh et al., 2007, p. 702). Similarity confusion proneness can be caused by stimuli that are similar to stimuli the consumer learned in the past. Marketing related examples include advertisements (e.g., Poiesz and Verhallen, 1989; Keller, 1991; Kent and Allen, 1994), interpersonal communications, the store environment or products which are very similar (e.g., Loken et al., 1986; Foxman et al., 1992; Kapferer, 1995; Kohli and Thakor, 1997; Jacoby and Morrin, 1998; Brengman et al., 2001). This is because consumers rely on visual cues to locate and distinguish brands and when presented with similar brands or information, can buy a fake or a retailer own-label brand thinking it is the original. Thus, when faced with similar-looking stimuli, consumers prone to similarity confusion will potentially alter their choice because of the perceived physical similarity of products.

Possibly because of the legal context of the research, most stimulus-similarity definitions tend to imply that a prerequisite of confusion is that the consumer buys the wrong brand (e.g., Diamond, 1981; Kohli and Thakor, 1997; Jacoby and Morrin, 1998), which constitutes only one behavioural outcome of confusion and ignores other behaviour-related consequences such as, engaging in word of mouth, and other cognitive consequences such as decreased trust and satisfaction.

Consumers who are prone to similarity confusion are likely to have negative consumption experiences which lead to dissatisfaction. The confusion felt by seeing so many similar products, can result in indecision, frustration, increased mental processing, in addition to possibly buying, not necessarily a “wrong” product but one which might not meet their needs as well as another if they were able to identify the true differences between the different brands. For our word of mouth concept, we draw on the market maven idea since they are key market monitors of such information and deliver it via word of mouth. Mavens are defined as consumers who “initiate discussions with consumers and respond to requests from consumers for market information” (Feick and Price, 1987, p. 85) and we conceptualise word of mouth as The effect of being a general concept of marketplace interpersonal interaction and ‘the degree of product related information which a consumer communicates via speaking to other consumer consumers’. If people are used to giving their opinions of products, these negative confusion occurrences as a result of seeing many products as similar, might naturally lead to consumers wanting to communicate more in order to express their frustration and/or to warn other consumers.

However, similarity confusion prone consumers may not share their frustrating or mistaken shopping purchases with others as this would involve admitting the mistake and could cause them embarrassment. It likely that those who see most brands as similar and are not able to differentiate between brands will not engage in general word of mouth about these brands to others and other consumers are less likely to ask their opinion. It is also possible that when consumers perceive brands in a category as very similar, they perceive them as more like commodities with little differentiation, and thus they exhibit little interest to engage in word of mouth to learn about brand differences in

the marketplace. These counter lines of reasoning lead to our first hypothesis:

H1. Similarity confusion proneness has no significant impact on general marketplace related word of mouth.

Trust has been defined as consumers’ willingness to rely upon their expectations about a firm’s future behaviour (Morgan and Hunt, 1994; Rousseau et al., 1998). Here, we view it on an aggregate level of the marketplace and conceptualise it as the sum of consumers’ willingness to rely on many firms’ future behaviour. In the context of consumer similarity confusion proneness, trust is likely to be undermined because when consumers see all brands as being similar or have mistakenly purchased a copy-cat product, or are confused from similar advertising or messages. This is because they are likely to think that this is either a deliberate attempt by companies to dupe them because they see no reason to have so many similar products on the market when there are few differences. This will raise their suspicions about the companies’ motives and undermine the trust they have in the marketplace. This is also partly because trust can also be understood as firms’ intention to “hold consumers’ interest ahead of their self-interest” (Singh and Sirdeshmukh, 2000, p. 155). Consumers that notice the similarity between products within a product category may be inclined to feel that manufacturers and retailers are putting their own interests ahead of consumers’. This is likely to have a negative impact on consumer trust in the marketplace. The more times a person is confused by similar stimuli coming from numerous brands, the less trust they will have in the marketplace. It can also be argued that similarity confusion prone consumers may not know which products to trust.

Thus, we propose that:

H2. Similarity confusion proneness has a significant negative impact on marketplace trust.



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