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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]

Version 3 (19 February 2004) 1

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


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


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,


“(…) 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


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


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


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


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


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


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


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,


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.


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


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


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, fact-

orientated 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


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 novelty-

fashion 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


Situational variables, such as shopping under time constraints, can lead to rushed decision-

making, 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


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


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


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


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


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


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 high-

involvement 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


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 trade-

offs (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


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


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 self-

confidence, 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.


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 non-

conscious) 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 stimulus-

overloaded 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 product-

related 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.


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


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


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


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 high-

involvement 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


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;


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


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


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/ knowledge

affective/ emotional

conative/ behavioral conscious non-conscious

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

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

+ +

Miaoulis and D'Amato (1978, p. 49)

“We take the position here that “confusion” is in effect stimulus generalization.”

+ +

Diamond (1981, p. 52)

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

+

Lastovicka (1983) The degree of which the commercial is perceived as being misunderstood.

Sproles and Kendall (1986, p. 274)

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

+


information overload.”

Loken, Ross, and Hinkle (1986, p. 196)

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

+

Poiesz and Verhallen (1989, p. 233)

“Brand confusion is a phenomenon that occurs at the individual level (...) and is predominantly non-conscious in nature.”

+ + +

Foxman, Muehling, and Berger (1990, p. 172)

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

+ +

Foxman, Berger, and Cote (1992, p. 125)

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

+ +

Kapferer (1995a, p. 101)

“(…) arises from an incorrect attribution of distinctive markings.”

+

Kohli and Thakor “(...) confusion, + +


(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 + + +


Papavassiliou (1999, p. 327)

mind which affects information processing and decision making. The consumer may therefore be aware or unaware of confusion.”

Walsh, 1999, p. 24

“Confusion is: an uncomfortable state of mind that primarily arises in the pre-purchase phase and which negatively affects consumers' information processing and decision-making abilities and can lead to consumers making sub-optimal decisions.”

+ +

Turnbull, Leek, and Ying (2000, p. 145)

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

+ +


Table 2: Instances of Conscious and Unconscious Confusion Conscious Unconscious

Perceived stimulus similarity

This confusion will occur primarily in the pre-purchase 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 post-purchase 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


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


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

High Involvement

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

Consumers could try to gather as much product-related 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 availableinformation. Confusion can be experienced.

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

Low Involvement

Consumers may be unable to detect differences between products because they have little product experience. 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.


Table 4: Confusion-Reduction Strategies

Similarity Confusion

Overload Confusion

Unclarity 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 information from printed advertisements. +

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. + +


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


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

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

ANTECEDENTS CONFUSION COPING STRATEGIES CONSEQUENCESMODERATORS &MEDIATORS

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

• Too similar information

• Too much information

• Too ambiguous information

Abandon purchase

Confusion Reduction

DecreasedTrust

DecreasedBrandloyalty

Dissonance

NegativeW-O-M

ShoppingFatigue

Dissatis-faction

ProductMisuse

SimilarityConfusion

Cognitive

Beha-vioral

Affective

OverloadConfusion

Cognitive

Beha-vioral

Affective

UnclarityConfusion

Cognitive

Beha-vioral

Affective

• Share or delegate the purchase (SC, OC, UC)

• Do nothing (SC, OC, UC)

• Postpone purchase (SC, OC, UC)

• Seek additional information (SC, UC)

• Clarify buying goals (UC)

• Narrow down the set of alternatives (SC, OC)

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

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

Reduced Self

Confidence

ANTECEDENTS CONFUSION COPING STRATEGIES CONSEQUENCESMODERATORS &MEDIATORS

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

• Too similar information

• Too much information

• Too ambiguous information

Abandon purchase

Confusion Reduction

DecreasedTrust

DecreasedBrandloyalty

Dissonance

NegativeW-O-M

ShoppingFatigue

Dissatis-faction

ProductMisuse

SimilarityConfusion

Cognitive

Beha-vioral

Affective

OverloadConfusion

Cognitive

Beha-vioral

Affective

UnclarityConfusion

Cognitive

Beha-vioral

Affective

SimilarityConfusion

Cognitive

Beha-vioral

AffectiveSimilarityConfusion

Cognitive

Beha-vioral

Affective

Cognitive

Beha-vioral

Affective

OverloadConfusion

Cognitive

Beha-vioral

Affective

UnclarityConfusion

Cognitive

Beha-vioral

Affective

OverloadConfusion

Cognitive

Beha-vioral

AffectiveOverloadConfusion

Cognitive

Beha-vioral

Affective

Cognitive

Beha-vioral

Affective

UnclarityConfusion

Cognitive

Beha-vioral

AffectiveUnclarity

Confusion

Cognitive

Beha-vioral

Affective

Cognitive

Beha-vioral

Affective

• Share or delegate the purchase (SC, OC, UC)

• Do nothing (SC, OC, UC)

• Postpone purchase (SC, OC, UC)

• Seek additional information (SC, UC)

• Clarify buying goals (UC)

• Narrow down the set of alternatives (SC, OC)

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

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

Reduced Self

Confidence


and cope with their inability to come to a judgment regarding the true meaning and significance of claims such as `low fat'. The confusion-causing 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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