REVIEWING AND REDEFINING THE CONCEPT OF CONSUMER CONFUSION by V.-W. Mitchell, G. Walsh and M. Yamin

*Contact: Professor V.-W. Mitchell Manchester School of Management UMIST PO Box 88 Manchester M60 1QD UK Tel: +161 200 3475 Fax: +161 200 3167 Email: [email protected]

REVIEWING AND REDEFINING THE CONCEPT OF CONSUMER CONFUSION

ABSTRACT As consumers are provided with ever-increasing amounts of information from more products sold through more channels and promoted in more ways, the notion of confusion is becoming increasingly important. From the extant literature, we propose and define three types of confusion resulting from brand similarity, information load, and misleading or ambiguous information. This latter type should be regarded as an `altered knowledge state' in which a revision of understanding occurs. We argue that the three types of confusion should be conceptualized as attitudes and that existing confusion measures have focused solely on the behavioural and cognitive outcomes of confusion, ignoring the role of affect which is also a part of confusion. The paper is also the first to discuss the consequences of confusion and elaborate on consumer confusion-reducing strategies.

It concludes with some research

implications of the new conceptualization.

INTRODUCTION As consumers are provided with ever-increasing amounts of information from more products sold through more channels and promoted in more ways, the idea of confusion is becoming increasingly important and has been reported as a marketing problem in many markets, e.g., telecommunications (e.g., Turnbull, Leek, and Ying, 2000), life, health and travel insurance (Roberts, 1995), veal products (West et al., 2002), food labeling (Kangun and Polansky, 1995), disclosure statements (Jacoby, Nelson and Hoyer, 1982) and complaint channels in public services (Ashton, 1993). Interest amongst marketing scholars has taken two main perspectives, namely: `brand similarity' as an important `cause' of brand confusion and trademark infringement (e.g., Clancy and Trout, 2002; Brengman et al., 2001; Balabanis and

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Craven, 1997; Kapferer, 1995a; 1995b; Cohen, 1986; Levy and Rook, 1981; Diamond, 1981; Miaoulis and D'Amato, 1978), and the more general issue of information overload (Foxman, Berger and Cole, 1992; Foxman, Meuhling and Berger, 1990; Malhotra, 1984; Malhotra, Jain and Lagakos, 1982; Jacoby, 1974; 1977; Jacoby et al., 1974a; 1974b). Indeed, confusion from overchoice has been identified in consumer decision-making studies in the US, Korea, New Zealand, UK and Germany (Sproles and Kendall, 1986; Hafstrom, Chae and Chung, 1992; Durvasula, Lyonski and Andrews, 1993, Mitchell and Bates, 1998; Walsh, Mitchell, and Hennig-Thurau, 2001). More recently, this conceptual basis for the notion of confusion has been challenging with some authors arguing that to represent consumer confusion more fully, the two concepts of similarity and overload confusion need to be complemented by a third, unclarity confusion (Walsh, Hennig-Thurau, and Mitchell, 2002; Mitchell and Papavassiliou 1999). Here we make further observations regarding the extant literature and research in this area. First, the lack of a generally accepted definition has contributed to very different conceptualizations of consumer confusion. Some definitions restrict confusion to the consumers' sub-conscious, whilst others argue that consumers must be consciously aware of confusion to affect attitudes and behaviour and consumers are to address it (see Table 1). The concept of confusion itself is either often mistaken for similar, but distinctly different, phenomenon such as deception and inadequate brand recognition (Kapferer, 1995a; 1995b), or used as a tool for defining related terms such as information overload (e.g., Assael, 1998, p. 249). Second, the existence and potential significance of an affective dimension of confusion has been neglected in previous confusion studies and definitions. Third, almost all conceptual and empirical work examining consumer confusion has disregarded how consumers cope with confusion and the idea that they employ confusion reduction strategies.

This paper first reviews extant definitions of consumer confusion and relevant literature

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before proposing and defining three types of confusion. We then move on to provide a conceptual model of consumer confusion as well as discussing antecedents, potential moderators and mediators, coping strategies and consequences of consumer confusion.

DEFINING CONSUMER CONFUSION Thus far, confusion has not been treated as a distinct theoretical notion and the literature lacks a generally-accepted definition which can encompass previous divergent perspectives that have often defined it very narrowly. The extant literature offers three somewhat distinct notions of consumer confusion and Table 1 gives an overview over existing definitions which show that consumer confusion can be related to too similar, too many or unclear stimuli. We take these ideas and propose three, more general, definitions of confusion arguing that existing definitions only capture particular aspects of confusion. The definitions view confusion as a conscious state of mind that can occur either in the pre- or the post-purchase situation and have not only a cognitive dimension, but also an affective and behavioral one. We differentiate confusion from ignorance or uncertainty as it is associated with a lack of comprehension or misunderstanding. Similarly, although confused consumers may experience a degree of indecisiveness in making purchases, it is not synonymous with indecision. The critical difference is whether the indecision results from a reduction in confidence or lack of understanding to make an assessment of the purchase decision. We now review and discuss each type of confusion and its antecedents.

INSERT TABLE 1 HERE

Similarity Confusion According to Diamond (1981, p. 52), brand similarity confusion occurs when an imitator,

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“(…) so resembles the mark in appearance, sound, or meaning that a prospective purchaser is likely to be confused or misled”. Similarity in advertisements and commercial messages is also associated with this type of confusion (e.g., Kent and Allen, 1994; Keller, 1991; Poiesz and Verhallen, 1989; Burke and Srull, 1988). The implicit assumption is that consumers rely on visual cues, which can be more easily recalled by consumers (Costley and Brucks, 1992), to locate and distinguish brands and when presented with similar brands, can buy a fake or a retailer own-label brand thinking it is the original (e.g., Simonson, 1994; Loken et al., 1986; Miaoulis and D'Amato, 1978). `Lookalike' brands which have proliferated in recent years (Kapferer, 1995a; 1995b) and `fake' brands such as, `White Horsie' whisky are good examples of products which can invoke brand confusion. Even if a similar brand does not result in a wrong buy (i.e., an imitator instead of the original brand), consumers can make assumptions, e.g., that both are identical in quality or from the same manufacturer, that can result in misunderstandings or misappropriation of brand equity. Once consumers have established a firm preference for a particular brand, they use the trademark to short-circuit the search process (Miaoulis and D'Amato, 1978) which may make them more easily misled by imitations because less time and attention is devoted to the purchase. Brand similarity confusion can be defined as: `A lack of understanding and potential alteration of a consumer's choice or an incorrect brand evaluation caused by the perceived physical similarity of products or services.'

From our perspective, brand similarity does not necessarily cause confusion unless the consumer's are aware of the two brands (e.g., Jonnie Walker and `Johnie Hawker' whiskey). If the consumer makes an unknowing wrong purchase, they are not ‘confused’ but mistaken. Although it seems plausible to assume that conscious and unconscious confusion can occur in all three dimensions and during every phase of the buying process, we refer to confusion here

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as being only that of which the consumer is conscious and aware. Nonetheless, each type of confusion may have a subconscious dimension of which the consumer is unaware (see Table 1 and 2).

Overload Confusion Many markets now contain a bewildering number of products, including many product-line extensions, which often provide only minor differentiations to consumers. The logical basis of the view that brand proliferation causes `confusion' is, implicitly, the `bounded-rationality' of individuals in relation to the volume and diversity of the information generated by a large number of brands (Simon, 1962; Miller, 1956). Thus, when consumers no longer understand their environment because of `information-overload' this can be seen as another type of consumer confusion. Clearly, information overload is not caused only by a proliferation of brands, but also by an increase in the amount of `decision-relevant' information on the product in the environment surrounding the purchase of a given number of goods. Jacoby (1977, p. 570) defined `relevant' information “as the number of alternative brands times the number of information dimensions presented to a subject” and these dimensions can include non-product information from stores, salespeople, advertisements and friends. As consumers tend to compare products on several characteristics before making a choice, and each characteristic comparison involves a comparison effort, and the greater the number of characteristics considered, the more difficult the choice will be (or the more thinking cost incurred) (Shugan, 1980). Some consumers will try to optimise utility and in doing so exceed their information-processing capabilities. Implicit in the notion of `stimulus overload' is the assumption of the possibility of a `perfect' amount of information for consumption decision. We define a `perfect' amount of information as one where all conceivable information relevant to it are appropriately processed into the decision process. However, in reality all

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consumer decisions are inherently imperfect in their decision making as there are always imperfections in the information itself, the amount and how it is processed. We define stimulus overload confusion as: `A lack of understanding caused by the consumer being confronted with an overly information rich environment than cannot be processed in the time available to fully understand, and be confident in, the purchase environment.'

Unclarity Confusion Some authors refer to consumer confusion from product complexity (e.g., Cahill, 1995; Boxer and Lloyd, 1994), ambiguous information and advertisements or false product claims (e.g., Chryssochoidis, 2000; Kangun and Polonsky, 1995; Golodner, 1993; Jacoby and Hoyer, 1989; Reece and Ducoffe, 1987), non-transparent pricing (e.g., Berry and Yadav, 1996) and poor product manuals (e.g., Glasse, 1992), all of which directly cause problems of understanding and are related to the concept of cognitive unclarity (see Cox, 1967). According to Cox (1967), consumers perceive unclarity when they feel uncomfortable from information ambiguity and incongruity. Therefore, unclarity confusion can be largely attributed to dubious product claims or conflicting information on the same product from different sources which might occur at any point during the decision making process. Consumers try to comprehend and create meaning out of stimuli, but even when information is clearly and accurately presented, consumers do not always comprehend it. Jacoby and Hoyer (1989, p. 435) define miscomprehension as the situation in which “the receiver of the communication extracts meanings neither contained in nor logically derived from the communication and/or rejects meanings contained in or logically derived from the communication”. Jacoby and Hoyer (1989) go on to distinguish between four forms of miscomprehension: 1) extreme miscomprehension, when a consumer extracts an entirely

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incorrect meaning; 2) partial miscomprehension, describing a situation in which a consumer derives two or more logically independent meanings, of which one portion is correct and another is incorrect; 3) confused miscomprehension, which involves the consumer extracting two or more logically incompatible meanings, then realizing it but still not knowing which of the meanings is correct; 4) derived miscomprehension, which refers to a situation in which the consumer miscomprehension occurs because the consumer combines accurate comprehension of some meanings with the miscomprehension of others. It seems that form three is most closely related to our notion of unclarity confusion.

The important distinction we make is that unclarity confusion is caused by information that is at variance with that already known by the individual, e.g., positively or negatively framed product information (e.g., Maheswaran and Meyers-Levy, 1990; Grewal et al., 1994) that is inconsistent with a consumer's beliefs about that product. The volume of information is not confusing if either, it is ignored because the consumer views the source as biased and/or unreliable, or if it does not contradict the consumer's current judgments or assessments. For example, increasing instances of confusion occur in the health or `slimming' food market not because there may be too many similar varieties or too much information to absorb, but because `credible' sources such as television programs undermine the consumer's confidence in the accuracy of the producers/retailers claims. When the decision environment is highly uncertain and complex and individuals have a finite ability to absorb information effectively, decision-making can only proceed if the individual adopts certain assumptions or premises that reduce the perceived and actual need for information processing. For example, individuals routinely accept seller/retailer claims or pledges as sufficiently credible so that careful evaluation and testing of such claims is usually not perceived as necessary. We argue that unclarity confusion is an impairment of consumers' ability to act or to make

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judgments, because some new, valid or false information has undermined the consumers' confidence in their present understanding of a particular purchase environment. For example, `misleading' information does not necessarily confuse if the consumer can process the information and arrive at a judgment which is more conflicting with existing beliefs. That the decision may turn out to have negative consequences for the purchaser is not relevant to unclarity confusion. Unclarity confusion then is a state of disequilibrium in which current beliefs are undermined whilst new beliefs are not yet fully formulated. When the latter does happen, confusion ceases and the consumer feels able to act decisively in conformity with the new beliefs. We suggest that unclarity confusion should be regarded as a transitional state of knowledge acquisition in which a revision of understanding occurs. We set down conditions for the occurrence of unclarity confusion including: a) there must be `new' information which can be actively or passively acquired, b) the information is believed, c) the information is at variance with the knowledge/understanding currently utilized by the decision maker, and d) the process occurs mainly in a high-involvement context. It is challenging information per se which is the trigger for confusion. Any revision of understanding may take seconds or last for days or months. Thus, unclarity confusion is essentially a transitional state which can be seen as beneficial, even essential.

Unclarity confusion typically occurs because consumers do not treat current beliefs as absolute and rigid, but rather as provisional and in principle subject to alteration. Thus, consumers whose belief structures are very rigid are less likely to experience confusion. From this discussion, we define unclarity confusion as being: `A lack of understanding during which consumers are forced to re-evaluate and revise current beliefs or assumptions about products or purchasing environment.' INSERT TABLE 2 ABOUT HERE

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CONCEPTUAL FRAMEWORK Since confusion concerns a subjective experience (i.e., the unpleasant state of mental discomfiture) relating to an object, that affects the overall evaluation of that object, then in effect, consumer confusion is an attitude. Rosenberg and Hovland's (1960) tri-component attitude model allows us to conceptualize confusion as having cognition, affect and behavior as first-order factors and attitude as a single second order factor. We therefore conceptualize each type of confusion as an attitude with three components, i.e., cognitive, affective or behavioural, which are positively correlated, irrespective of the type of confusion experienced.

The vast majority of previous research has viewed confusion predominantly as either a behavioral or a cognitive state, with no suggestion that confusion includes an affective component. Since “understanding consumers' feelings are as important as understanding their thoughts” (Edell and Burke, 1987, p. 421) and affective judgments remain in the memory longer than the information which caused these judgments (Muncy, 1986), affective confusion could cause more long-term negative consequences (e.g., damage to brand/store loyalty), and may also be more difficult for retailers/manufacturers to reduce. Hunt (1993) argued that it is emotion, not cognition, that drives complaining behaviour. Few researchers have included affect in their definitions of confusion (Jacoby et al., 1974a; Huffman and Kahn, 1998; Walsh, 1999; see Table 1) and most are unclear. For example, it is possible to interpret “feelings of (…) not having obtained the best buy, and feeling that another brand was better” (Jacoby et al., 1974a, p. 66), as translating into feelings of sadness or frustration, but difficult to assess which specific feelings they are actually referring to.

We view

confusion as a negative mental state which is uncomfortable and unpleasant for consumers to

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feel. We propose confused consumers are likely to experience unpleasant emotions which may include; frustration, irritation, anxiety, or even anger. As it is unpleasant and makes consumers feel vulnerable and somewhat inadequate, confusion is an important feeling for consumers to reduce.

It is likely that confusion can occur throughout the decision-making process. Even with defined pre-set search goals, consumers may become confused on coming in contact with the choice environment, in as much as any current belief relating to the worth, quality or suitability of products in the consideration set may be undermined as a result of conflicting messages received from the market place. This highlights the point that confusion can occur at any point before, during and after a purchase. Figure 1 shows the proposed conceptual model, which we will be discussing. In addition to the three types of confusion, antecedents, moderators and mediators, confusion reduction strategies and consequences are depicted (see Figure 1). INSERT FIGURE 1 HERE

Potential Moderators and Mediators of Confusion Research on consumer confusion has mainly focused on identifying causes and effects of confusion paying little attention to its mediators and moderators. Moderator and mediator variables are important because specific factors can reduce or enhance the influence confusion causing antecedents. Mediator variables, such as fatigue, can change while influencing the relationship between an antecedent and confusion (Baron and Kenny, 1986), while moderator variables, such as demographic characteristics, can affect the relationship, but do not change themselves. Confusion Moderator Variables

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Individual characteristics exert an influence because they are often linked to the consumer's ability to rationalize and process stimuli. Age may reduce confusion through an experience framework or may increase confusion as processing competence decreases with the ageing process. Several studies suggest that older, less educated consumers are more likely to miscomprehend information than younger, well-educated consumers and are more prone to experience similarity and overload confusion (e.g., Brengman et al., 2001; Walsh, 1999; Balabanis and Craven, 1997); perhaps because elderly adults exhibit reduced visual and information-processing abilities (John and Cole, 1986).

Less well-educated and less

intelligent consumers tend to be less analytical and adopt fact-orientated or struggling learning styles which have been found to be positively correlated with overload confusion (Sproles and Kendall, 1990). However, less well-educated consumers are less likely to comprehend information and are more prone to overload and probably unclarity confusion (Hagemann, 1988; Sternthal and Craig, 1982).

Gender differences may also be related to the experience framework, since females tend to have more experience in different product classes than men. Although gender has been found to have no impact on the likelihood of experiencing similarity confusion (Balabanis and Craven, 1997; Foxman et al., 1990), females are reported to perceive more advertisement clutter and miscomprehension (Elliott and Speck, 1998; Reece and Ducoffe, 1987) and Turnbull et al. (2000) found that more females were unclarity confused than males in the mobile phone market, suggesting that product category interrelates with gender. Moreover, from previous research, we can glean that females tend to be more prone to be persuaded by marketing practices (McGuire, 1985), are more field dependent (Marx, 1976), are less likely to make a buying decision after consulting a sales clerk when confronted with an abundance of information (Laroche et al., 2000), are more involved in shopping (Fischer and Arnold,

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1990), and are more likely to engage in compulsive shopping (O'Guinn and Faber, 1989).

Ambiguity has been defined as equal probabilities (Kahn and Sarin, 1988), the absence of information (Hoch and Ha, 1986), or a surplus of information (McQuarrie and Mick, 1992) about products and commercial messages that convey more than one meaning. In the present context, it refers to an individual's reaction to conflicting information and dictates the degree of information variance beyond which the decision-maker is forced to re-assess current choices. Tolerance for ambiguity is also related to uncertainty. In the cognitive psychology literature, tolerance for ambiguity is concerned with the degree to which people can restrain their need for a perfect, clear view of the environment (e.g., Feather, 1969; Goldstein and Blackman, 1977). Consumers with low tolerance for ambiguity prefer definiteness and regularity (Goldstein and Blackman, 1977), which may lead them to perceive the environment as less ambiguous than it actually is. In contrast, consumers with high tolerance for ambiguity feel more comfortable with handling soft and vague data and they are more likely to have a clear view of the ambiguity in the environment. Individuals with low tolerance for ambiguity may prematurely close their information processing activities, and are rigidly impervious to new information. Thus, it is reasonable to expect that consumers with high tolerance for ambiguity are more likely to keep up with increasing product and information choices than consumers with low tolerance for ambiguity. The way tolerance is discussed in the literature suggests that consumers go through a stage of ambiguity if they intend to clarify the choice environment and make a more considered purchase. This is in keeping with the way the notion of unclarity confusion is seen in this paper, where confusion is a possible by-product when decision makers respond to `new' conflicting information. Since all assumptions are partial, because they are based on limited knowledge and understanding, all are subject to a degree of uncertainty and have a given error band.

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Unclarity confusion then occurs when the error band, and uncertainty within the information, exceeds the error and uncertainty tolerance of the consumer.

Reflexive/impulse describes the consumer tendency to pause and consider the alternatives on offer when uncertainty is involved. Reflective individuals spend more time and effort to consider their purchase decision, which might make them more prone to overload, but less prone to unclarity confusion, whereas, impulsive consumers are much quicker and are expected to make more inaccurate purchases. Impulsive shoppers may be more easily deceived because they tend to disregard a large proportion of possibly clarifying product information. Balabanis and Craven (1997) provide empirical support that impulse buying of low-priced goods is likely to induce similarity confusion.

Pinson's (1978) work on cognitive styles distinguished between sharpeners and levellers, which are similar to Cox's (1967) clarifiers and simplifiers. Sharpeners emphasize unique distinguishing details, actively look for cues that might eliminate ambiguity and are receptive to all available information. Levelers, on the other hand, ignore detail, simplify their environment and try to fit new experiences into familiar moulds. Foxman et al. (1992) found sharpeners commit fewer errors than levelers when distinguishing between similar stimuli. Such consumers use more discriminant criteria and are less likely to be deceived when buying an imitator instead of an original brand. In other words, sharpeners are less likely to make errors in product/brand recognition and hence to experience similarity confusion (Lomax et al., 1999). However, as we have noted, inadequate product recognition is different from confusion. In fact, consumers, who use more discriminant criteria may induce or create stimulus overload; particularly in markets where the consumer has little experience. Hence, consumers who are less likely to suffer similarity confusion may be more prone to overload

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confusion. Moreover, in a high involvement purchase environment, we suggest that consumers are more likely to adopt a `sharpener' style even if normally their style is levelling, because of the extra attention and motivation being given to the task.

Field independent individuals impose organization upon visual stimuli, and are able to locate a sought-after component. The ability to better organize stimuli makes field independent consumers less likely to experience overload and unclarity confusion. Conversely, field dependent consumers are less capable of organizing stimuli and are significantly more likely to be similarity confused (Foxman et al., 1990).

Equivalence range refers to the extent which individuals generalize about stimuli presented to them (Gardner, Jackson and Messick, 1960; Foxman et al., 1992). A narrow equivalence range results in a more scrutinized, accurate comparison of the stimuli and stimuli will be perceived as different unless they are very similar. Whereas, an individual with broad equivalence (or low conceptual differentiation) considers stimuli to be the same, even when they are only marginally similar. Thus, broad equivalence consumers are more likely to become similarity confused. Whereas equivalence range might not affect the proneness to overload confusion, it is likely to affect unclarity confusion because when consumers with a narrow equivalence range encounter unclear stimuli, they are more able to accurately evaluate and compare stimuli. We next identify time, shopping environment, social environment, mood, expectation, experiences, task definition and involvement as mediators of the three types of confusion.

Learning styles are defined as, “the way each person absorbs and retains information and/or skills” (Dunn and Arnold, 1986, p. 12). Based on Kolb's (1976) exploratory work, Sproles

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and Kendall (1990) examined the relationship between learning style and decision-making styles and identified three learning styles which could be particularly overload confusion inducing; namely, (1) the passive, accepting learning characteristic, (2) the concrete, factorientated characteristic, and (3) the non-adaptive, struggling learning characteristic. The first and third learning styles suggests that consumers can be overwhelmed by stimuli because they do not make a great effort or are intellectually unable to process a great deal of information. The second learning style could motivate consumers to collect and consider more information than can be processed. The proclivity to become confused is also likely to be influenced by a consumer's decision-making style, which is defined as a, “mental orientation characterizing a consumer's approach to making choices” (Sproles and Kendall, 1986, p. 270). Indeed, in addition to a confused by overchoice factor, Sproles and Kendall (1986) identified several decision-making factors which have links with confusion, namely: Perfectionism,

Brand

Consciousness,

Novelty-Fashion

Consciousness,

Price-Value

Consciousness, Impulsiveness. We now discuss and explain these relationships.

The perfectionistic consumer usually tries to buy products of superior quality (Sproles, 1985), which can involve a great deal of thorough and systematic search for alternatives and comparisons because few products meet their demanding criteria. Overload confusion seems unlikely because, (a) as soon as the perfectionistic shopper realizes that a product does not meet his/her (high) expectations, it will be dismissed from the consideration set and, (b) if consumer motivation is high, which is likely to be the case for the perfectionistic consumer, information processing is likely to be thorough (Davies and Wright, 1994). This thoroughness is also likely to enhance an individual's ability to distinguish between similar stimuli. Hence, we argue that a perfectionistic approach to shopping is an effective shield against similarity and overload confusion. Unclarity confusion might occur if the perfectionistic consumer

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acquires information that he/she fully or partially miscomprehends.

Novelty-fashion seekers may be particularly prone to overload and unclarity confusion because: they tend to obtain more information from the mass media and outside their social system (Midgley and Dowling, 1978); fashion is ever changing and contradictory (Mead, 1993); of the uncertainty surrounding the longevity of such trends and the ambiguity of defining what is fashionable; they cannot be certain whether their products or styles will ever become widely accepted (Winakor et al., 1980). Moreover, their need for `uniqueness' (Snyder and Fromkin, 1980) could translate into a relatively small number of alternatives that can be considered (i.e., the latest). They eliminate out-of-date products/brands from their choice set and replace them with the latest fashions on a regular basis, suggesting that when shopping they are seldom confronted with too many products to choose from, and maybe less prone to overload confusion. However, similarity confusion can be an issue among noveltyfashion seekers in markets that have a great number of counterfeit fashion products.

Economic/price-value conscious consumers want the best value for money, tend to have clear purchasing criteria and their approach to shopping is systematic, thorough and efficient (Stone, 1954; Darden and Reynolds, 1971), which makes them less likely to experience similarity, overload or unclarity confusion. For example, similarity confusion is unlikely for price-value conscious consumers because they will become suspicious and hence more attentive when a national brand is sold at a lower price than usual. On the other hand, they may be overloaded as their desire to find the best offer leads them to engage in intensive information searches.

Confusion Mediator Variables

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Situational variables, such as shopping under time constraints, can lead to rushed decisionmaking, shortened information-processing and inference-making time which is expected to increase similarity confusion (Foxman et al., 1990; Balabanis and Craven, 1997). Time constraints should increase overload confusion because of decreased processing time, but it might also reduce overload confusion in certain circumstances because, knowing the time constraints, consumers might seek to acquire and process less information (Walsh, 1999). However, since overload is derived from the finite limits of human being's ability to assimilate and process information during a given unit of time, the less time the individual has the more likely confusion will occur.

Unclarity confusion can be expected to be

negatively correlated with the amount of available shopping time because it allows time to clarify what the information actually means.

Shopping environment relates to the store layout, variety of products on offer, arrangement of the merchandise, music, colors, lighting, etc. Many retailers now periodically change the positioning of product categories within the store in order to get consumers to encounter, and purchase, products they would not usually pass by; potentially confusing consumers. It can be expected that this constant product moving, combined with poor signage, will increase unclarity confusion especially. Consumers shop faster when fast background music is played (Milliman, 1982) which could make them give less time and be less scrupulous in their information processing and product evaluations, and thus be more susceptible to all three kinds of confusion. Overload confusion is likely to exacerbated when too many products are placed on the shelves. Also, when lookalike brands are placed side-by-side to the original brand, the consumer is more likely to detect that they are different brands and similarity confusion is less likely. The social environment refers to the presence of others and their interactions with the

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consumer. Calder and Burnkant (1977) found that consumers will often accept the opinions of others, especially in instances where they have difficulty in assessing product and brand characteristics by observation, and this may help to reduce all three types of confusion depending on the information received. For example, others’ opinions could add too much information and create overload confusion or could be in conflict with existing beliefs and create unclarity confusion.

Consumers who are in a good mood are more likely to remember positive aspects about a product, to make a positive judgments and quicker buying decisions and to be more open to persuasion (Batra and Stayman, 1990; Gardner, 1985; Aylesworth and Mackenzie, 1998). Quicker buying decisions are likely to increase similarity confusion because consumers fail to detect subtle differences between the imitator and the original brand. With a low-involvement purchase, overload confusion is less likely to occur because less information search and processing takes place. However, Shugan (1980, p. 100) points out that simplifying decisions can “lead to less than optimal alternatives” because utility maximization and quicker decisions are incompatible. Unclarity confusion should be positively correlated with quicker decision making because the consumer is less likely to thoroughly examine ambiguous product information.

Pre-purchase evaluation and expectations toward the purchase outcome are known to influence consumer decision making (e.g., Zeithaml et al., 1993). Consumers expect to receive truthful product information, that products are what they say they are and that information is understandable. If consumers expect that information may be misleading, then they are likely to approach the shopping situation with more thoroughness and a greater degree of involvement. This in turn decreases the likelihood of at least similarity and

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unclarity confusion. However, higher involvement may provoke overload confusion because more information may be acquired than the consumer can process.

Experience can work for or against the consumer with respect to confusion. Although Foxman et al. (1990) claim that “new triers and occasional buyers may be especially vulnerable to confusion” (p. 176), Brengman et al. (2001) found no statistical differences in the proclivity to similarity confusion between light and heavy product category users. Experienced consumers are less likely to thoroughly compare the products they buy regularly and are less likely to be overloaded than inexperienced ones. This is partly because although they consider a greater number of information dimensions, heavy users look at fewer brand alternatives (Jacoby, 1977), and partly because the knowledge that stems from experience facilitates information processing. Also, firmer product beliefs, accrued from experience, make consumers selectively perceptive and reducing consumers' scope of search (Neisser, 1976). As consumers gain brand experience their knowledge base expands, choice alternatives and evaluative attributes become fewer and they should become less susceptible to all three types of confusion.

Foxman et al. (1992) suggest that the task definition can influence the propensity to become confused because it is related to the importance of a purchase. For example, consumers can be scrupulous and attentive when buying a gift and thus, especially similarity confusion is expected to decrease (Balabanis and Craven, 1997). In contrast, a routine low-involvement purchase might increase the risk of buying an imitator brand instead of the intended brand. Foxman et al. (1992) argue that similarity confusion becomes less likely with greater perceived task importance because it is positively correlated with greater consumer efforts in buying evaluations. Important purchases are likely to stimulate more intensive information

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acquisition and processing which could cause consumers to overload themselves unintentionally (Keller and Staelin, 1987), whereas less important buys require less information processing. Making a complex purchase decision (e.g., for life insurance, computer, non-regular medicine) can be potentially confusing because the consumer is confronted with new, difficult and not easily understood information, which incur high costs of thinking.

In Table 3, we describe how different degrees of involvement influence the likelihood of experiencing one of the three confusion types. In high-involvement contexts, the decision maker will put greater effort into making choices by adopting decision styles that involve more deliberation and evaluation and this may help to avoid similarity confusion (Foxman et al., 1992). However, greater effort is only likely to reduce the incidence of confusion if two conditions hold, namely, 1) that the information is available and comprehensible, and 2) that the consumer has the processing ability to analyze the information. If either of these two conditions are not met, consumers could easily become more confused as they increase the purchase evaluation effort. In effect, Foxman et al. (1992) are pointing out that confusion is negatively related to decision makers' information processing ability and purchase motivation. However, in a low-involvement context, the motivation for using, let alone for seeking, new information is lacking and much of the information in the choice environment will `bypass' the decision-maker, hence decreasing the likelihood of overload confusion. Ambiguous and contradictory stimuli are also more likely to lead to unclarity confusion when the consumer does not expend a great effort to understand the stimuli. High-involvement contexts imply that decision-makers expect a high degree of (subjective) utility from the choice (Bonoma and Johnston, 1979) and adopt a decision style that requires more information processing which makes it more likely to induce overload confusion. We now turn to discussing some of

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the consequences of confection.

INSERT TABLE 3 HERE

Consequences of Confusion Before discussing the consequences of confusion, we need to distinguish between two distinct consumer assessments of the buying situation. When confused, an attempt to understand who they will attribute responsibility for the confusion and can either blame themselves or others for the confusion and. Within any exchange process, it is either the stimulus itself, created by the marketer, which is inherently confusing or is it some inability on the consumer's part to process marketing stimuli. We suggest that attribution serves as a moderator of the confusion-outcome link. Attribution theory helps to explain how consumers understand why things happened (Heider 1958; Miller, Brickman, Bolen 1975; Weiner 1980). Typically, confused consumers will make a distinction between internal and external attribution. Internal attribution assigns causality to factors within the person’s control and that the person was directly responsible for the event. With external attribution, where causality is assigned to an outside agent or force, the consumer assumes the perceived confusion is due to information supplied by the company or other agent. The more consumers attribute their confusion to external company sources, the greater will be the effect on company-related consequences.

The importance of consumer confusion will be ultimately assessed on the basis of these company-related consequences and their economic impact on companies. Behavior-related consequences are particularly important, because these consequences are generally the only ones which can be directly assessed. Although no study has systematically investigated the

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outcomes of consumer confusion, it has been associated with several unfavorable consequences, such as, negative word-of-mouth (Turnbull et al., 2000), dissatisfaction (Foxman et al., 1990; Zaichkowsky, 1995), cognitive dissonance (Mitchell and Papavassiliou, 1999), decision postponement (Jacoby and Morrin, 1998; Huffman and Kahn, 1998; Mitchell and Papavassiliou, 1999), shopping fatigue (Mitchell and Papavassiliou, 1997), reactance (Settle and Alreck, 1988), decreased loyalty and trust and confusing other consumers (Foxman et al., 1990; 1992; Mitchell and Papavassiliou, 1999; Walsh, 1999), all of which can have a negative effect on companies. Furthermore, it can result in possible harmful outcomes (e.g., product misuse that leads to physical harm). Even after confusion has been reduced successfully, consumers can feel negatively about the experience, which itself can have unfavorable consequences such as reduced self confidence. When confused, consumers can experience a reduction in their own confidence (or ability) to make a judgment or evaluation regarding any facet of a product or service. These potential consequences are incorporated in our model (Figure 1). In discussing them, we suggest that there are two temporally-distinct consequence categories. The first relates to the immediate effects of confusion. The second relates to actions aimed to reduce or eliminate confusion.

Immediate Effects of Confusion We propose that the immediate effect of all three types of confusion is indecisiveness and hesitation resulting in the consumer either doing nothing or postponing the purchase decision. Doing nothing is generally an unplanned reaction, which implies that confusion felt is either, below the threshold above which the confusion reduction strategies are used, or so high that it causes purchase-specific decision-making paralysis. Postponing the purchase implies that the confusion is at a higher level than can be dealt with at that time. This deliberate delay of a specific purchase, allows the consumer time to compare alternatives, clarify purchase goals

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and evaluate any information gathered. We suggest that, in many circumstances, abandoning the purchase is not an option for the confused decision-maker as this would suggest that the purchase decision is of low importance. Since confusion is more likely to arise in highinvolvement contexts, where the decision-maker attaches importance to the choice decision, abandonment is a possible, yet unlikely, outcome. Confusion should thus be viewed as being associated with at least temporary indecisiveness and inaction, rather than with the quality of any decision made and consequent action. The ability to postpone the decision is a prerequisite for adopting effective confusion reduction strategies. The situations in which no decision postponement takes place are when a consumer unknowingly acts because of subconscious confusion, e.g., buying an imitator brand believing it is the original.

When choice rather than abandonment is the result of confusion, the same possible negative consequences for all three types of confusion on choice can be: a) a known alteration in brand choice caused by a lack of understanding, b) the same choice, but made with undue amounts of uncertainty, misunderstanding frustration and dissonance, c) the same choice, but poor or non-maximal product utilization caused by inadequate understanding, d) the same choice, but an inability to inform others about the product or misinform them which may create problems for others, e) the same or different choice depending on the outcome of a delay designed to clarify the choice by using confusion reduction strategies. In the following section we offer further specific insights into the potential impact of all three types of confusion on consumers' behaviour.

Stimulus Similarity Confusion and Related Outcomes Stimulus similarity is likely to lead to a delay or abandonment of decision making because when consumers are aware that there is at least a possibility that they are about to buy a brand

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they did not intend to, they are likely to take more time to find out whether the (two or more) alternatives are actually the same (Jacoby and Morrin, 1998). Consumers may also abandon a purchase altogether (`no-choice option') because they want to avoid making difficult tradeoffs (Tversky and Shafir, 1992; Dhar, 1997). For example, consumers often encounter inexpensive retailer own-brands that emulate well-known national brands. In such situations, consumers need to trade off the financial advantages (i.e., lower price) of the copy brand, for the disadvantage of not knowing if both brands are similar in terms of quality and/or origin.

Although interpersonal communication is often instigated when consumers have problems in evaluating complex products and risky purchases (Lutz and Reilly, 1973), since similarity has been reported mainly in relation to low-involvement products (Kapferer, 1995a; 1995b; Miaoulis and D'Amato, 1978), product complexity is not necessarily an issues for stimulus similarity confusion. The relevance of stimulus similarity confusion to social interaction is because consumers sometimes feel ashamed of being unable to differentiate between brands. Consumers who are duped are not always likely to share their negative experience which was their own fault.

When considering similarity confusion, it is possible to distinguish between micro and macro satisfaction. The former relates to a company's goods and services, whereas the latter is concerned with the consumer's evaluation of companies' marketing decisions in general (Renoux, 1974). We expect consumers' inability to differentiate between stimuli (i.e., perceived stimulus similarity confusion) will cause dissatisfaction directed towards one manufacturer that clearly imitates the other. This is partly because of the time and effort needed to assess the authenticity of the alternatives and these opportunity costs yield no utility (Foxman et al., 1990). Worst still for the original manufacturer, is if the consumer does

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not realize that he/she has bought an imitator brand and attributes any dissatisfaction to the original brand.

If the consumer cannot, or does not, want to determine which alternative is the authentic one, and buys a product that turns out to be the wrong one, the consumer is likely to feel dissonance. When consumers buy a lookalike brand and find it is as good as the original, they can feel dissonance because they think they have been paying too much in the past. Even if they buy the original brand, dissonance may arise of the extra effort in assessing both alternatives. Brand loyalty is also likely to be affected by the degree of similarity confusion (Mitchell and Papavassiliou, 1999), because confused consumers who perceive stimulus similarity and have trouble distinguishing products and manufacturers, will find it difficult to reward a manufacturer with their trust. In this context, Zaichkowsky and Simpson (1996) argue that perceived brand similarity can change consumers' attitudes about the uniqueness of the national brand. Consumers might see no reason for developing a relationship with a single brand, when it can be easily substituted by other similar brands.

Familiarity is often viewed as a precondition of trust (Rempel, Holmes and Zanna, 1985; Johnson-George and Swap, 1982), and in a product context, consumers will only trust those brands that they know or with which they have had positive experiences. If consumers trust a product or company without prior experience, then a transfer of trust may be the explanation. For example, consumers who regularly buy and trust a retailer's apparel goods, may extend their trust to the retailer's new food products. In the case of stimulus similarity confusion, consumers' trust is likely to reduce because they will not know which is the `right' alternative and which manufacturer to trust (Lau and Lee, 1999). Similarity-confused consumers are unlikely to misuse products because lookalike brands

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typically belong to the same product category; i.e., if instant-coffee brand A is bought instead of instant-coffee brand B, no physical harm will occur. However, instances of consumers misusing a product and suffering physical harm have been reported (Fletcher and Wald, 1987).

Finally, when consumers repeatedly experience similarity confusion and buy the wrong brand occasionally, it is likely to have a detrimental effect on their shopping-related selfconfidence, at least in instances when consumers blame themselves for the mistake.

Stimulus Overload Confusion and Related Outcomes Overload-confused consumers are likely to interrupt decision making in order to take measures that allow them to deal with the information load by separating important from less important information, narrowing down the choice set or reducing the number of attributes on which the decision is based. Since stimulus overload can be attributed to a lack of (processing) time, delaying the purchase decision can be interpreted as an attempt to gain more processing time. However, expending a greater effort to arrive at a decision without gaining a perceivable utility can lead to consumer dissatisfaction (Turnbull et al., 2000). Perceived overload caused by too many stimuli can cause stress on part of the consumer and dissatisfaction (Wiedmann, Walsh and Polotzek, 2000). Consumers who experience stimulus overload regularly across different products categories are likely to feel dissonance and to become frustrated with, and tired of, going shopping because the information processing associated with purchase decisions is strenuous. Consumers who repeatedly experience overload confusion and buy the wrong brand occasionally, are likely to experience a reduction in their shopping-related self- confidence.

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As brand loyalty reflects habitual purchasing and requires less decision making, information seeking and brand evaluation, the prospect of having to do less information processing and comparison is likely to be appreciated by those consumers who are prone to stimulus overload confusion. Therefore, loyalty can be viewed as a strategic (conscious or nonconscious) reaction to overload.

Irrespective of cognitive abilities, consumers tend to feel better prepared for purchase decisions with a greater amount of information (Jacoby et al., 1974a; Jacoby et al., 1974b). Consumers also tend to perceive it positively when manufacturers and retailers provide them with extensive product-related information. In contrast, consumers can be become skeptical when they feel they are not provided with sufficient information. Information can strengthen consumers' trust in manufacturers and retailers because consumers think they have nothing to hide and are transparent about their products. Since consumers tend to prefer larger stores, with a greater assortment, to smaller stores with a small assortment (Hoyer and MacInnis, 1997), the over-abundance of products and information which today's consumers encounter is unlikely to decrease trust per se. This is despite the fact that some consumers have problems coping with the many products, offers and information. One outcome of this is that stimulusoverloaded consumers can ask other, more competent, people to assist them in their buying decisions (Walsh and Mitchell, 2001), as competent consumers can help to determine which decision-relevant information are relevant and which can be omitted. Misusing a product because of a cluttered purchasing environment or too much productrelated information appears unlikely. However, it is conceivable that overload confused consumers use perceptual blocking to avoid acquiring more information and this may lead them to neglect information that is crucial for an optimal product use.

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Unclarity Confusion and Related Outcomes Consumers who are confused by unclear stimuli, or who suffer from partial miscomprehension (i.e., who extract more than one logically independent meaning), are likely to try to find information that will help them clarify their choice environment, e.g., by trying to establish which information is more credible.

This will inevitably involve

suspending the decision-making process. When consumers compare two or more complex products and experience unclarity confusion, it could lead to choice deferral because the consumer tries to cope with what is seen as a non-comparable alternative (Dhar 1997). Indeed, Dhar (1997) showed that consumers who expressed more thoughts or made more comparisons (and found the choice more difficult) were more likely to postpone a decision.

Unclear information can lead to product misuse, for example, when a consumer buys a drug and miscomprehends the instruction leaflet.

Unclear product information also prevents

consumers from fully evaluating product attributes and information that are difficult to gauge, such as `healthy' or `nutritious', which can lead to unclarity confusion and dissatisfaction (Golodner, 1993). This is not so true for the deliberate use of emotional subjective wording (e.g., the “compact and powerful” Nokia 8800), with which no concrete product characteristics are associated that consumers can assess. In this context, studies show that a product's user friendliness is an important quality dimension (Brucks, Zeithaml and Naylor, 2000).

If they are not able to arrive at a buying decision, and be satisfied with the decision and product, unclarity-confused consumers are likely to talk about their negative experience. However, unclarity confused consumers are unlikely to engage in negative word-of-mouth if they tend attribute their inability to fully use and understand a product to themselves and not

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the product (Hansen and Hennig, 1996).

Similar to stimulus overload, unclarity is likely to cause consumers to seek ways to make satisfactory decisions on a more permanent basis and becoming brand loyal equates to making fewer comparisons, which means consumers are confronted with less ambiguous or unclear stimuli. Trust can help to reduce the perceived complexity in the environment (Hillmann, 1994) because products that have once been positively evaluated do not need to be assessed again. Interestingly, unclarity confused consumers may feel that product complexity can be positively correlated to quality, as consumers often appreciate and trust complex products (i.e., with numerous attributes) even though they are unable to use the product to the full extent (Hansen and Hennig, 1996). From an attribution viewpoint, it is also conceivable that consumers do not blame manufacturers and retailers for their perceived unclarity, but blame themselves, which is unlikely to entail a withdrawal of trust. Depending on who consumers blame for the confusion, unclarity confusion can have a negative impact on their shopping-related self- confidence if they blame themselves.

Confusion Reduction Strategies Some of the outcomes of confusion can be mitigated by using techniques to reduce the confusion. When confusion is experienced by consumers, the same contexts may (or will) cause different degrees of confusion depending on the individual's prior skill or competence in information processing and with respect to `strategies' adopted to cope. The confused consumer will respond to the cognitive strain by developing strategies to reduce it once the level of confusion exceeds an acceptable level or duration. An important prerequisite for the use of confusion reduction strategies (CRS) is that the consumer is aware of the confusion involved in the decision. The more intolerant of confusion a consumer is, the more likely

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he/she will be to use CRS. Some strategies may reduce confusion effectively, e.g., asking a salesperson to explain the differences between products can reduce unclarity confusion. Others can have little effect, e.g., a 14-day money-back guarantee can minimize the financial risk, but may not help consumers to clear up their confusion or to decide between different options. Confusion reduction has not been studied before and this section identifies some strategies which consumers might use.

In our view, CRS are, in the main, concerned with clarifying a choice, reducing unclarity and increasing understanding relating to a purchase decision. We propose that the confused consumer develops strategies which can be categorized into four generic approaches, namely; (1) clarify the buying goals, (2) seek additional information, (3) narrow down the set of alternatives, (4) share/delegate the purchase decision. These represent CRS categories rather than individual strategies in an attempt to provide some clearer basis for conceptualizing the confusion reduction process. The categories can co-exist in the same purchasing occasion and can be inter-related, e.g., seeking information and narrowing down the choice set. However, we argue that CRS are mainly aimed at cognitive and affective confusion; behavioral confusion reactions usually happen immediately in some way, which leaves consumers little time to apply CRS (see Table 4).

INSERT TABLE 4 HERE

The `seeking additional information' category mostly consists of strategies which clarify the choice environment, but can also involve simplifying strategies. For example, the consumer might seek information to clarify which is the best brand on the market, or if two similar brands are produced by the same manufacturer. Once obtained, the consumer is likely to use

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the information as a simplifying cue to reduce the scope of the search and confusion. The reduction of similarity and unclarity confusion critically depends on the content of the information received, since additional information which is conflicting will not reduce similarity confusion and can exacerbate unclarity confusion. We propose that for highinvolvement products, there is likely to be a negative relationship between information acquired and the level of overload and unclarity confusion. Up to a certain point, the accumulation of information will help to reduce overload and unclarity confusion, if the information is clear and non-conflicting. With regard to in-store price knowledge, Dickson and Sawyer (1990) found that many consumers are aware of price information, but this knowledge drops immediately after a decision has been made and the shopper moves on to make the next buying decision. However, at any point, overload and unclarity confusion can increase if too much information is acquired or if the new information is itself unclear or misleading. One implication of this proposition is that it suggests an optimum range of purchase-relevant information acquisition within which purchasing decisions are most comfortably and effectively made.

Consumers having problems assessing complex information tend to seek help through interpersonal communication (Wilkie, 1986). Confused consumers can often involve other people (i.e., spouse, family member, friend) in the purchasing decision by asking a person to accompany them whilst shopping to help them comprehend the choice environment. Alternative, they may delegate the task completely. However, shopping partners can give opinions which contrast with the buyer's opinion or they convey inaccurate or unclear information about a product and/or store and thus can sometimes confuse the purchaser and inhibit the decision-making process. Furthermore, consumers may feel guilty about wasting their companion's time and feel pressured into either making a purchase quickly or seeking to

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abandon the search/purchase. A useful distinction can be drawn between optional and compulsory companionship. Compulsory companionship, e.g., mother and young child, may make consumers more stressed and confused by reducing their purchase information processing capacity and motivation through annoying distractions.

CONCLUSION AND IMPLICATIONS The preceding discussion can be brought together and a descriptive model which attempts to present an integrated approach to understanding confusion creation and reduction. It considers the inputs, e.g., what causes confusion, and outputs how people react to confusion (see Figure 1). Consumers evaluate the confusion they feel against their level of confusion tolerance. If confusion exceeds this level, the consumer will be motivated to develop and use CRS. In some cases, the consumer will be unaware and hence will be less likely to develop strategies for handling it. If confusion goes above the tolerable level and consumers are unable to reduce it, they might either attempt to ignore the confusion and buy impulsively, or may be paralyzed into complete indecision. Although this implies that confusion exerts its effects at a cognitive level, we have suggested that confusion also occurs at a behavioral and affective level.

This paper stimulates a number of research questions driven by the proposed model. For example, how is confusion affected by the decision context, e.g., by the degree of involvement and how it is affected by purchaser characteristics such as; age, gender and cognitive style. The role of atmospherics and the overall physical store environment and its relationship with consumer confusion requires would appear complicated and requires further exploration. Indeed, basis research parameters of confusion need to be established such as to; identify and measure antecedents of confusion; identify and measure moderators of confusion;

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and identify and measure outcomes of confusion. Outcomes which require further research might include shopping fatigue; as consumers who experience stimulus similarity regularly across different products categories are likely to become more frustrated with, and tired of, shopping. To the extent that much of the information processing and assessment of error and uncertainty are done without our conscious awareness, we can agree somewhat with Foxman et al.'s (1992) assertion that unclarity confusion is concerned with errors of which the consumer is unaware (at least partially), because sub-conscious processing of information is a basic condition driven by our mental limitations vis-à-vis a complex environment. This presents a major challenge for the measurement process. One interesting research question is whether confusion is significantly associated with brand switching. For example, when purchasing a fake or look alike product and gaining a positive experience, consumers may alter their beliefs about both the `fake' brand and maybe the more expensive brand. If the fake brand experience was good, the initial beliefs about the `real' brand will be undetermined. Our conceptual approach to unclarity confusion as an `altered state' strongly implies such a possibility and marketers could use confusion to encourage re-evaluation of brand choice decisions by deliberately undermining beliefs about a competitor's product performance. This line of research may be of particular relevance to marketers as it suggests the deliberate generation of unclarity confusion as a competitive strategy. It must be noted though, that the marketer's ability to generate `targeted' confusion may be limited since confusion generation is not always a controllable or easily manipulable process. There is therefore a need for further theoretical effort to clarify whether, and to what extent, marketers can purposefully, and competitively, utilize consumer confusion.

There is a tendency in the literature to regard confusion as akin to (a reverse) `hygiene' factor in the consumer decision-making; its presence causes dissatisfaction, but its absence does not

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motivate consumers to purchase and does not necessarily lead to satisfaction. This is likely because the experience of confusion can be rather unpleasant, the eventual outcome or consequences flowing from it can be negative. The `hygiene' analogy gives a negative view of confusion, which we contend for the most part to be correct.

In order to examine some of these ideas, we need to measure each type of consumer confusion which depends significantly on the development of a comprehensive confusion scale (e.g., Foxman et al, 1992). Thus far, no comprehensive scale exists, although some existing scales may capture elements of the overload confusion concept e.g., Reiling's (1982) `Role Overload of the Wife', Childers, Houston and Heckler's (1985) `Style of Processing Scale' and Sproles and Kendall's (1986) confusion factor in their `Consumer Styles Inventory'. There is therefore a need to devise a completely new scale to measure the degree of similarity and unclarity confusion. In pursuing this goal, convergent and discriminant validity might be examined using a confirmatory factor analysis.

In terms of practitioner implications, the economic consequences of confusion need to be assessed if a compelling argument is going to be made to business to address confusion. For example, how much business is lost because consumers are confused and how much does a company suffer because of the reductions in good will and brand trust caused by consumers being confused? Moreover, consumers themselves suffer economic consequences such as buying the wrong thing, not fully utilizing products and the danger of misunderstanding or misusing products which might result in physical harm. Related to the issue of consumerism is that of how we identify the vulnerable consumers. In particular, confusion can seriously undermine the four pillars of consumers rights, namely the rights to be informed (understand the information), to choose (and not be overloaded with choice), to safety (and not be

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confused by complicated manuals and instruction), and to be heard (and not be unable to work out how to complain). In addressing these concerns, consumer-policy makers and marketing researchers not only need to become more aware of consumer confusion and to identify sources of consumer confusion, but also should focus on the issue of identifying confusion-prone consumer segments because from a consumer-protection and marketing perspective, it is not sufficient to know that some consumers are confused, we need to know of whom this group consists.

One final problem for further research derives from the goods orientation of all previous research. This is particularly problematic when we wish to examine confusion in services and business-to-business marketing where personal relationships are important and where intangibility and subjectivity of services can conspire to increase confusion. A much broader understanding of confusion is therefore required if we are to find a general use for the concept across multiple-purchase situations.

The primary aim of this paper has been to begin to clarify the concept of confusion. The paper has offered working definitions of three types of confusion and considered their antecedents, mediators, moderators and outcomes. A main advantage of our proposed definitions which take a broader, more generalizable view of confusion, is that they might be used in different exchange situations including service encounters and relationship marketing. Our main contribution to theory lies in developing a model of consumer confusion. The paper suggests some interesting future research, which should involve the development of a robust measurement instrument covering the three confusion types and subsequent testing of the conceptual model and hypothesized relationships.

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Table 1: Definitions of Consumer Confusion and their Classification Author(s)

Definition

Quasi-Definition

cognitive/ affective/ conative/ conscious knowledge emotional behavioral

“(...) feelings of confusion, of not having obtained the best buy, and feeling that another brand was better.”

Jacoby, Speller and Kohn (1974a, p. 66)

+

Miaoulis and “We take the position here D'Amato (1978, p. that “confusion” is in effect 49) stimulus generalization.”

+

“(...) so resembles the mark in appearance, sound, or Diamond (1981, p. meaning that a prospective 52) purchaser is likely to be confused or misled.”

+

Lastovicka (1983)

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+

+

The degree of which the commercial is perceived as being misunderstood.

Sproles and Kendall (1986, p. 274)

non-conscious

“[consumers] perceive many brands and stores from which to choose and have + difficulty making choices. Furthermore, they experience

44

information overload.”

Loken, Hinkle 196)

Ross, and (1986, p.

“(...) physical similarities between products may result in the misattribution + of source of origin or identity by the consumer.”

“Brand confusion is a Poiesz and phenomenon that occurs at Verhallen (1989, p. the individual level (...) and 233) is predominantly nonconscious in nature.” Foxman, Muehling, and Berger (1990, p. 172)

+

+

+

“(…) consumers who are misled clearly are + confused.”

+

“(...) consists of one or more errors in inferential processing that lead a consumer to unknowingly Foxman, Berger, and form inaccurate beliefs about Cote (1992, p. 125) the attributes or performance of a less-known brand based on a more familiar brand's attributes or performance.”

+

+

“(…) arises from an incorrect Kapferer (1995a, p. attribution of distinctive 101) markings.”

+

Kohli and Thakor

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“(...)

confusion,

+

45

+

(1997, p. 213)

when respondents may pick confusingly similar names, instead of the target names.”

Huffman and Kahn (1998, p. 492; 493)

“the huge number of potential options (…) may be confusing” and “The confusion a consumer experiences with a wide assortment of + options, however, is due to the perceived complexity, not necessarily to the actual complexity or variety.”

Jacoby and Morrin (1998, p. 97)

“If someone other than the owner were to use a trademark, there would be the possibility that such use (by the second or + junior user) could cause consumers to be confused regarding who actually makes the product.”

Mitchell

and “Confusion (...) is a state of

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+

+

46

+

Papavassiliou (1999, mind which affects p. 327) information processing and decision making. The consumer may therefore be aware or unaware of confusion.” “Confusion is: an uncomfortable state of mind that primarily arises in the pre-purchase phase and which negatively affects consumers' information processing and decisionmaking abilities and can lead to consumers making suboptimal decisions.”

+

“(...) consumer confusion is defined as consumer failure to develop a correct Turnbull, Leek, and interpretation of various Ying (2000, p. 145) facets of a product/service, during the information processing procedure.”

+

Walsh, 1999, p. 24

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+

+

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Table 2: Instances of Conscious and Unconscious Confusion Conscious

Unconscious

Perceived stimulus similarity

This confusion will occur primarily in the prepurchase phase from similarity of alternatives or some attributes are considered similar. For example, Sainsbury introduced its own brand of `Classic Cola' in 1994 which many consumers confused with Coke's visual identity and caused them to feel uncertain about whether the two brands were the same in all product characteristics (e.g., quality, source of origin).

This confusion will occur primarily in the pre-purchase phase. The consumer perceives different alternatives (e.g., Ravini vs. Martini in Germany, Asda's Puffin (biscuit) brand vs. McVities' Penguin brand in the UK, Seiko vs. Seycos in the US) as identical and possibly buys the wrong one without knowing.

Perceived stimulus overload

This confusion can occur throughout the process but will occur primarily in the pre-purchase phase. The consumer is aware of being confused and of having difficulties assessing alternatives because of the amount of information and the number of sources; e.g., when trying to work out the best buy for a mobile phone or an electronic equipment or choosing an expensive Chinese menu. Because processing ability depends upon the time available, overload can be exacerbated under time pressure.

This confusion will occur primarily in the pre-purchase phase. Consumers overload and confuse themselves by exceeding their own information-processing capacity, e.g., when processing a lot of information, but where erroneous processing occurs without knowing. For example many recreational and veteran shoppers enjoy hunting for information just for the fun of it and may engage in information search without intending to make a purchase, which increases the likelihood of becoming confused through overload.

Perceived stimulus unclarity

This confusion will occur in both the pre- and postpurchase phase and during usage. Consumers are aware of being confused because of contradictory and ambiguous stimuli which make it difficult to assess alternatives; e.g., competing products claim that different types of fat being healthy or not, or when consumers do not understand the technical data for competing computers.

This confusion will occur in the pre-purchase phase and during usage. Consumers will not notice that contradictory and ambiguous stimuli are the cause for their miscomprehension and will not be aware of the erroneous inferences made as a result of it; e.g., buying a mobile phone you think has low radiation emissions, but it does not. Unconscious confusion can also be caused by marketable claims such as `healthy” and `nutritious” which convey a

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positive message about a food product but which may have a different meaning than consumers' associate with these claims.

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Table 3: Consumer Confusion's Relationship to Involvement Stimulus Similarity

Consumer is more likely to detect differences in High appearances and less Involvement likely to experience confusion.

Consumers may be unable to detect differences between products because they Low little product Involvement have experience. There is a moderate likelihood of confusion.

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Stimulus Overload

Stimulus Unclarity

Consumers could try to gather as much productrelated information as possible and thereby overload themselves. It is also conceivable that the highly involved consumer is time pressed and hence unable to process the available information. Confusion can be experienced.

Consumers will identify ambiguous and contradictory information, unless there is too little time. There is a moderate likelihood of confusion.

Less involved consumers typically do not attempt to process a great amount of information that can overload and confuse them. Confusion is unlikely to occur.

Although consumer only have a small proclivity to acquire and process information, cognition does take place. If this cognition involves processing ambiguous and contradictory information, unclarity confusion can be the result.

50

Table 4: Confusion-Reduction Strategies Similarity Overload Unclarity Confusion Confusion Confusion Do Nothing I do nothing/I ignore the difficulty and act as if it does not exist. Postpone/abandon I postpone the purchase.

+

I abandon the purchase.

+ +

Clarify goals I clarify my purchasing goals/what I need.

+

+

When buying a present, I ask the recipient.

+

+

Seek information I devote more time to information gathering. I obtain additional advertisements.

information

from

+

+

printed

+

I obtain more information from advertisements on TV.

+

I look for information in order to make a purchase that offers the best value for money. I focus on information that will help me to make a + reasonably good purchase without wasting my time.

+

I stay in the shop as long as I need to make the + decision.

+ +

I visit as many shops as I can searching for the bargain. I read carefully the product information.

+

+

I ask the salesperson for information.

+

+

Narrow down the choice-set I buy the item which is on sale.

+

I buy the first item I see and like.

+

I buy something quickly to get it over with.

+

In complex cases, I buy the most simple item. I do not buy a new product if it has not been tested by others.

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+ +

+

51

I buy the newest or most modern product.

+

I buy the cheapest of the items that I like.

+

I buy the most well-known brand.

+

I buy the most unusual brand.

+

I buy the most expensive brand.

+

+ +

+

I buy from shops in my area or that are convenient to me.

+

I buy something that I like the moment I see it, regardless of the shop.

+

I buy only from shops that I have selected over time.

+

I buy from shops with the best reputation.

+

Share-delegate I follow the advice of my friends, family, and spouse.

+

+

I follow the advice of the salesperson.

+

+

I take a joint decision with another person.

+

+

I delegate the responsibility to somebody else.

+

+

+ indicates which CRS applies to or is appropriate for which type of confusion

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Figure 1: Conceptual Model for Antecedents Moderation and Consequences of Confusion

ANTECEDENTS

• Too similar information

MODERATORS & MEDIATORS Individual Characteristics • Age • Education / Intelligence • Gender • Tolerance for ambiguity • Cognitive style • Learning style • Decision-Making Style • Field (in)dependence • Equivalence range

CONFUSION

COPING STRATEGIES

Negative W -O-M Cognitive

Similarity Confusion

Abandon purchase Dissatisfaction

Affective

Behavioral

Confusion Reduction • Clarify buying goals (UC)

• Too much information

• Too ambiguous information

Cognitive

Overload Confusion Situational Variables • Time • Shopping Environment • Social Environment • Mood • Expectation • Experience • Task Definition • Involvement

CONSEQUENCES

• Seek additional information (SC, UC)

Shopping Fatigue

Affective

Behavioral

• Narrow down the set of alternatives (SC, OC) • Share or delegate the purchase (SC, OC, UC) • Do nothing (SC, OC, UC)

Cognitive

Unclarity Confusion

Dissonance

• Postpone purchase (SC, OC, UC)

Decreased

Brand loyalty

Decreased Trust

Affective

Product Misuse

Behavioral

Note: Abbreviations in parentheses indicate for which type of confusion a reduction strategy is relevant. SC = Similarity Confusion; OC = Overload Confusion; UC = Unclarity Confusion

Reduced Self Confidence

In the above example, seller credibility is a substitute for consumer knowledge. Once the credibility is undermined, consumers have to confront

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and cope with their inability to come to a judgment regarding the true meaning and significance of claims such as `low fat'. The confusioncausing factor is therefore not adequate understanding per se, but the consumer's deprivation of sellers credibility for signaling healthy, organic foods and free from animal testing products. For example, in the late 1990s the Center for Science in the Public Interest (CSPI) warned consumers about the consumption of Procter & Gamble's snack foods containing Olean (a fat free oil substitute) because it was thought to be associated with gastro-intestinal problems. At the same time, P&G heavily advertised Olean. However, the clarification process alone does not guarantee that the consumer will achieve cognitive clarity. In fact, consumers may end up in a worse state of cognitive imbalance after an attempt at clarification. Relating this to Cox's (1967) notions of clarifiers and simplifiers, it could be argued that clarifiers could be more confused than simplifiers in certain circumstances. In many cases, simplification strategies lead to a reduction of choice alternatives, e.g., being brand loyal. However, in this sense, simplification could be a result of previous clarification activity. We have therefore to be careful how we interpret simplifying behavior. 38

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