Published online in Wiley InterScience
(www.interscience.wiley.com) DOI: 10.1002/cb.185
Investigating the relationship
between product involvement and consumer decision-making styles
Hans H. Bauer, Nicola E. Sauer*, and Christine Becker
University of Mannheim, Germany
* Recently, a number of studies have investigated consumer decision-making styles (CDMS) and their importance to consumer behaviour research. However, research designs suggested to date are mainly replications of a study by Sproles and Kendall (1986) proposing eight mental characteristics, the so-called Consumer Styles Inventory (CSI). The CSI has been applied across cultures, but without critically examining its validity and reliability. A major concern is the postulated product independence of CSI. The aim of this study is to further develop this approach, to apply it to different product categories and to investigate the relationship between product involvement and CDMS. In doing so, we conducted a survey in Great Britain and Germany, and analysed the data using exploratory and confirmatory factor analysis. Not only did we demonstrate that there is a relationship between products and CDMS, but also that CDMS are governed by consumers’
perceived product involvement. Important implications for marketing practice can be derived.
Copyright # 2006 John Wiley & Sons, Ltd.
Introduction
The investigation of consumer decision-mak- ing has a long tradition in marketing and consumer behaviour research. Recently, con- siderable scientific effort has been devoted to the exploration of consumers’ styles of deci- sion-making and the significance of corre- sponding findings towards a theory of shopping. Some authors suggest classifying research efforts in this field into a three- dimensional pattern: the psychographic/life- style approach, the consumer typology
approach and the consumer characteristics approach (Sproles and Kendall, 1986). The consumer characteristics approach assumes that consumers follow certain decision-making traits to handle their shopping tasks. Traits that have been identified are, for instance, quality consciousness (Darden and Ashton, 1974) or brand and store loyalty (Moschis, 1976).
Sproles and Kendall (1986) combined these and additional traits to develop a consumer decision-making styles (CDMS) list, the so-called consumer styles inventory (CSI), a comprehen- sive instrument that measures eight mental characteristics of consumer decision-making:
perfectionism, brand consciousness, novelty- fashion consciousness, recreational, price- value consciousness impulsiveness, confused by overchoice, andbrand-loyal/habitual. It has
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*Correspondence to: Dr. Nicola E. Sauer, Department of Business Administration and Marketing II, University of Mannheim, L 5, 1, 68131 Mannheim, Germany.
E-mail: [email protected].
been suggested that the CSI could help consumer behaviour researchers to gain a more profound understanding of consumers’
shopping behaviour; additionally, it could assist marketing managers in approaching consumers more efficiently by targeting spe- cific consumer clusters or segments. The CSI has been the most tested instrument currently available to research into decision-making styles in a cross-cultural context. Yet a major concern that arises in this connection has not been addressed in a scholarly context so far: the postulated product independence of CDMS, which have only been tested in product-neutral settings. The major goal of this study is, therefore, to analyse the relationship between CDMS and different kinds of products. If CDMS are dependent on the selected product cate- gories, this link will imply crucial customer insights for marketing practice.
Consumer decision-making styles Literature review
‘A consumer decision-making style is defined as a patterned, mental, cognitive orientation towards shopping and purchasing, which constantly dominates the consumer’s choices.
[. . .] these traits are ever-present, predictable, central driving forces in decision-making. In essence we are speaking of a relatively endur- ing consumer personality, analogous to the more general concept of human personality in psychology’ (Sproles and Kendall, 1985, p. 79).
Detailed knowledge of consumer decision- making is a powerful instrument for marketing researchers and managers alike. Although research results reveal that decision-making styles can vary across cultures (Sproles and Kendall, 1986; Hafstromet al., 1992; Durvasula et al., 1993; Fan and Xiao, 1998), to date not a single accepted CDMS approach exists (Mitch- ell and Bates, 1998).
The most widely replicated instrument so far is the CSI by Sproles and Kendall, which has been applied to eight countries: the US, Korea, New Zealand, Greece, India, the United Kingdom, China and Germany (Hafstrom et al., 1992; Durvasulaet al., 1993; Lysonskiet al.,
1996; Mitchell and Bates, 1998; Fan and Xiao, 1998; Walshet al., 2001). Results show that the US eight-factor model is not applicable to all countries under investigation; in some coun- tries fairly similar decision-making styles can be found (e.g., UK, Germany), while in others the extracted styles are totally different (e.g., China). It has to be admitted that the CSI does not cover all relevant styles in a cross-cultural context (Samiee and Jeong, 1994) and, thus, is not an instrument that can be successfully applied across nations. Additionally, there is evidence of problems of non-representative- ness, explained variance, and little external validity. The objective of this study is (1) to test the reliability and validity of the CSI, (2) to propose a revised CDMS model that more adequately represents the measured phenom- enon and to test it with regard to different product categories, as well as (3) to analyse the relationship between CDMS and product involvement.
Reliability and validity of the existing CSI One of the most obvious shortcomings of Sproles and Kendall’s CSI can be found in the formulation of the items and, as a consequence, in the very low to average reliability coeffi- cients. The uppermost problem, however, lies in the conceptualisation of the construct. With regard to its theoretical basis and validity, it has to be remarked that the choice of decision- relevant purchase characteristics appears to be a rather arbitrary selection of relevant concepts mentioned in the marketing literature. The lack of an adequate theoretical framework can for example be demonstrated by taking a closer look at three of the eight sub-constructs of the CSI. Firstly, the CDMS ‘Novelty Fashion Con- sciousness’ seems to represent a style incor- porating two factors: innovativeness and fashion consciousness. Although the first appears to be a sound style, the second cannot be regarded as product neutral since the items show a factual relationship to the subject of fashion and clothing. Moreover, two of the CSI constructs do not seem to frame direct purchase-relevant dimensions as claimed by
the authors: neither is ‘Confusion by Over- choice’ related to principles of product selec- tion, but rather to a state of information overload, nor does ‘Recreational Hedonism’
represent a concrete decision-making style, but instead covers general shopping attitudes of consumers. Furthermore, the concept implies that decision-making styles can be utilised with regard to all kinds of products and product categories. Yet numerous studies provide evidence that purchase-relevant decision-mak- ing traits employed by consumers depend on the product category they intend to purchase and can, therefore, vary considerably. Finally, consumer behaviour in this context is not only strongly connected to the aspect product category, but also to the intensity of product involvement felt by the individual consumer..
Sproles and Kendall are partially aware of the problems inherent in their model (‘Indeed, a consumer may have different consumer styles for each product category.’ Sproles and Kendall, 1986, p. 277) and recommend further research to apply their framework to different cultural contexts and product categories in order to prove its validity. However, none of the subsequent studies have investigated the issue of product dependence.
In a first step, to analyse the current CSI for reliability and validity aspects in greater detail, a German version of the questionnaire was developed. The forty items included by Sproles and Kendall in their final version of the CSI as well as the items of the replicated studies (with exception of the Chinese version) were inves- tigated for stylistic differences and variations in the number of items used. We decided to include 43 items in our study that were translated and checked for consistency in meaning. The questionnaire was administered to German students, who were given class time to fill out the questionnaire. A number of students had major problems responding and complained about the formulation of the items and their missing product relevance. Despite these difficulties, we were able to collect a total of 223 usable questionnaires.
Exploratory and confirmatory factor analyses were performed to test the appropriateness of
the measurement instrument. Exploratory factor analysis resulted in 11 factors with an explained variance of 67 per cent.
When restricting factor extraction to eight, 59 per cent of the variance could be explained.
Coefficient alpha ranged from 0.40 to 0.87 for the eight-factor solution with only two factors staying below 0.70. In general, however, the predicted factor structure could not be con- firmed. This result was reaffirmed by confirma- tory factor analysis using LISREL (Jo¨reskog and So¨rbom, 1993). The items were attributed to the respective factors according to Sproles and Kendall’s CSI. The analysis produced unaccep- table results with unacceptably low global fit criteria, such as the Goodness-of-fit index (GFI¼0.695), Adjusted goodness-of-fit index (AGFI¼0.654), and the Comparative-fit- index (CFI¼ 0.717). Local fit criteria showed the same picture: 22 of the 43 items had indicator reliabilities below.40. These results are in keeping with the findings of another recent CSI replication study in Germany (Walshet al., 2001).
Modification of the CSI
Both the previously mentioned problems of the CSI and our own negative experience suggest developing an instrument that more appro- priately measures CDMS: after the conceptua- lisation and operationalisation of a new set of styles, these will be tested in Great Britain and Germany. The procedure of developing and evaluating a measurement model for our hypothetical construct hereby follows propo- sals by Churchill (1979), Malhotra (1981) and Nunally and Bernstein (1994). The first phase includes the generation of indicators capturing the theme of the hypothetical construct. This task is performed with the help of literature reviews and content analysis of text docu- ments. The standard scheme classifying con- sumer decision-making tasks into extended, limited, habitual, and impulsive purchase decisions dependent on product involvement hereby serves as a theoretical framework (e.g., Howard and Sheth, 1969).
In extensive purchase decisions, consu- mers act closest to the paradigm of rational
decision-making, behaving with intense cogni- tive involvement and carefully selecting a product alternative. Extensive decision-making mostly occurs within product categories that are important to the consumer, such as specialty goods. We classify Sproles and Kendall’s consumer decision-making styleper- fectionismas a representative style within this category. A second central behavioural pattern in this context is innovativeness. Here, our interest is focused on the basic characteristics of innovative consumers: active information search and active communication behaviour along with characteristics usually associated with opinion leaders (King and Summers, 1970).
Limited purchase decision-making charac- terises a process of restricted problem-solving effort and reduced cognitive power (e.g., Hoyer and MacInnis, 2004). Information search and judgment are mostly limited to a few, subjectively important information pieces called information chunks, such as brand and price information. Relevant CDMS are brand consciousnessandprice-value consciousness.
Regarding the first decision-making style, high prices and widely known brands are associated with high quality. Likewise, in the second, consumers search for the lowest price of products of the same or similar quality.
Habitual decisions usually appear when the consumer is familiar with the relevant product category and makes a routine decision based on positive experience. The degree of cognitive involvement is fairly small. The corresponding CDMS are brand/store loyalty and variety- seeking. The classification of the first is clear since brand and store loyalty are well-under- stood research topics with a long tradition (Brown, 1952; Cunningham, 1956). The sec- ond aspect of variety-seeking refers to the phenomenon of a consumer switching brands in a repeat-purchase situation not because of changed preferences or dissatisfaction (instru- mental brand switching), but because of his desire for change (exploratory brand switch- ing), deriving benefit from the change itself (van Trijpet al.1996; Raju, 1984; Faison, 1977).
The decision-making style with the lowest cognitive effort and a strong presence of
reactive elements, as well as an intensive, suddenly arising affective action is called impulsive decision-making. Research on unplanned, impulsive decision-making goes back to Stern (1962), Kollat and Willet (1967). Typically, although by no means exclusively, this behaviour is exhibited in situations of purchasing low-priced, low-invol- vement products of periodical need. A pur- chase is triggered at the point of sale. In our research study, we include spontaneity to complete the number of relevant CDMS (see Figure 1). In sum, we postulate a seven-factor inventory of CDMS that is dependent on the product under investigation (i.e., the consu- mer’s product and purchase experience).
The improved instrument shares five factors in slightly modified forms with the original CSI:
perfectionism, brand consciousness, price- value consciousness, brand/store loyalty, and spontaneity. In compliance with our previous explanations, we supplemented the instru- ment by two additional factors, innovativeness and variety-seeking, and eliminated three factors, confusion by overchoice, recrea- tional/hedonistic shopping, and novelty-fash- ion consciousness. Each of the seven factors consists of four to six items. The whole measurement inventory includes 32 variables.
Since we believe the CDMS to be product- dependent, we asked the test persons to answer the items with respect to certain products.
Empirical study
Before the modified instrument to measure CDMS is administered, two pretests were conducted. The first is aimed at the identifica- tion of the objects under investigation, namely the products. The standard scheme classifying products into convenience, shopping, and specialty goods serves as the theoretical frame- work. Our goal is to include one product that is commonly regarded as highly involving by consumers and one for which the opposite holds true. Keeping the target group—
students aged 18 to 28 in Great Britain and Germany— in mind, we performed an
extensive literature analysis to pre-select six product categories: stereo system, jeans and wristwatchas products linked to high involve- ment, while toothpaste, chocolate bar and yoghurt were chosen as low involvement products. Fifteen test persons were asked to respond to three questionnaires consisting of two product categories each. Results of the analysis (mean value comparisons and explora- tory factor analysis) unveiled a clear picture.
While jeans and chocolate bars assume a middle position between high and low involve- ment and stereo system and tooth-paste are rated on the extreme points of the five-point Likert scale, the product categories wristwatch and yoghurt clearly follow the hypothesised factor structure of the developed involvement construct (as described in a later section of this paper) and are viewed as high and as low- involvement products on the average, respec- tively. We, therefore, decided to include the productswristwatchandyoghurtin our study.
The second pretest with a small German (n¼10) and British (n¼10) sample lead to the reformulation of some items and the adjustment of both questionnaires. The final
questionnaire has a straightforward structure, using Likert-scaled items on scales of one to five with ratings of ‘strongly disagree’ and ‘strongly agree’ as end points. It consists of two central parts of questions including (1) product involvement and (2) CDMS (items within these categories were randomly ordered), and is completed by a section of (3) socio-demo- graphic information. Questionnaires were administered during classroom sessions at two British and one German university. The usable data basis consists of a total of 241–120 British and 121 German—questionnaires.
Principal component and confirmatory factor analysis of the modified CSI Principal component and confirmatory factor analyses are performed to test our hypothe- sised factor structure. Our research design is a two-by-two design (two products, two coun- tries). Due to the small national sample sizes, we first only performed principal component analysis. At a later point, we included con- firmatory factor analysis. We first analysed the wristwatch data for both countries. Using the
Figure 1. Summary of CDMS inventory.
Kaiser-criterion (eigenwert>1), we were able to retrieve a total of seven components explaining 69.9 per cent of variance for the British sample. Contrary to our hypothesis, however, a majority of items could not be clearly assigned to the factors we assumed they would belong to (the termsfactorandcompo- nentare used interchangeably throughout the paper), which resulted in some interpretation difficulties. Following Clark and Watson (1995), we eliminated those items that did not clearly meet our standards. Measure of sampling adequacy values (MSA) and factor loadings have to exceed 0.50, Item-to-total correlations (ITTC) have to surpass 0.40, and items loading on more than one factor are eliminated (e.g., Bagozzi and Baumgartner, 1994). Employing these threshold values, we reduced the instrument to 20 items. Principal component analysis resulted in four factors explaining 64.8 per cent of variance. All items show very high factor loadings between 0.68 and 0.93. Factor 1 comprises a total of nine items with ITTC and factor loadings ranging from 0.66 to 0.75 and 0.72 to 0.79 respectively.
Factor 1 has an alpha value of 0.92 and could be labelled brand/store loyalty. Factor 2 contains five items with ITTC between 0.52 and 0.63 and factor loadings between 0.64 and 0.77.
This dimension has an alpha value of 0.79 and could be designated spontaneity. Factor 3 comprises three items with satisfactory ITTC values (between 0.69 and 0.83) and factor loadings (between 0.83 and 0.93). The factor has an alpha value of 0.88 and could be termed price-value consciousness. Factor 4 includes three items with ITTC and factor loadings ranging from 0.37 to 0.56 and 0.68 to 0.81 respectively. It has an alpha value of 0.65 and could be labelled variety-seeking. Since the factor only comprises three items, the low Alpha value should not be viewed too nega- tively (e.g., Cortina, 1993).
A similar picture is drawn for the German sample in the wristwatch case. Principal com- ponent analysis produces eight factors that are hard to interpret. When reducing the instrument to ensure that all fit criteria are met, there are 17 items left that load on four factors explaining
65.0 per cent of variance. Factor labels are consistent with those in the British sample.
When analysing the product category yoghurt, different results emerged. EFA pro- duced six factors for the British sample, which could not be interpreted logically. A majority of items had to be deleted because of unaccep- table fit criteria. The reduced measurement instrument comprised only 12 variables load- ing on three factors that were still difficult to explain. Reliability and validity for these factors were not bad and 70.5 per cent of variance was explained. Alpha coefficients ranged from 0.47 (for a factor with two items) to 0.90, factor loadings from 0.66 to 0.87. The problem, however, was great difficulty in interpreting the factors. Analysis of the German sample extracted seven factors including a number of items not meeting the fit criteria. After elim- inating these items the final instrument con- tained 19 variables loading on four factors with two to seven items. Again fit criteria were acceptable, but the factors could not be interpreted in a reasonable way.
The analysis showed that it was not possible to confirm the hypothesised factor structure for the low-involvement product. Even worse, the factors that were extracted could not be interpreted logically. In the high-involvement product case, the hypothesised CDMS was partly confirmed. Four out of seven factors were verified. In addition to the goodness-of-fit indices of the final measurement instrument, the solution is almost identical for both countries. Therefore, sufficient evidence of high reliability and validity of the CDMS model for modest to high-involvement products is provided. The models to measure CDMS for low and high-involvement products show major differences in their principal compo- nents. In addition, a test of measurement invariance between the two products con- firmed our hypothesis of product-dependence of CDMS (H1). Using LISREL and applying the testing procedure suggested by Steenkamp and Baumgartner (1998), the two measures were found not to be invariant. The configural invariance model without equality constraints produced a Chi-square (2) of 748.15 with 135
degrees of freedom (df). The hypothesis of full metric invariance was tested by constraining the matrix of factor loadings to be invariant across products, resulting in a 2 of 937.15 with 153 df. A significant increase between the model of configural and the model of full metric invariance (2(18)¼189,p<0.000) proved that the two measures are not invariant and thus seems to support our assumption of the dependence of CDMS on products and con- sumer’s product and purchase experience.
To reduce complexity, avoid repetitions, and to reach a sample size that allows us to perform confirmatory factor analysis and causal model- ling, we joined the two national samples into one sample. Again, tests of measurement invariance had to be performed, which, at this point, validated the existence of measurement invariance. No significant difference (2 (14)¼8.16,p0.85) between the model with no equality constraints (configural invariance model,2(139)¼759.78) and the model of full metric invariance (2(153)¼767.94) had to be reported, and the fit did not decrease much in terms of the alternative fit indices. Keeping the problems that can arise with cross-national samples (e.g., Nash et al., 1991; Hui and Triandis, 1985) in mind, the British and German samples were joined. Results of the principal components analysis (EFA) and Confirmatory factor analysis (CFA) are shown inTable 1.It is evident that EFA and reliability results are good.
Results of CFA are average to good. Especially local fit criteria could be improved. Global fit indices like GFI (0.92) and AGFI (0.89) as well as CFI (0.91) are good, and thus much better than in the unmodified CSI, where they were unacceptably low.
Consumer decision-making styles and product involvement
Conceptualisation and operationalisation of product involvement
After having shown that CDMS are not product- independent, we want to go one step further and postulate that CDMS are not only product- dependent but also influenced by the involve-
ment a consumer attributes to a particular product. Research on consequences of invol- vement goes back to the eighties when Mitchell (1981) and Costeley (1988) claimed a causal model of involvement and information behaviour, stating that involvement influences information search, -processing and -saving.
Since CDMS are closely related to information handling, we believe involvement to govern CDMS.
To conceptualise and operationalise product involvement, we have extensively reviewed the existing involvement literature. According to Zaichkowsky (1985), involvement can be understood as: ‘. . . a person’s perceived relevance of the object based on inherent needs, values, and interests’ (p. 342). Although a number of instruments to measure invol- vement have been proposed so far (e.g., Zaichkowsky, 1985; Laurent and Kapferer, 1985; Mittal and Lee, 1988; Jain and Srinivasan, 1990; McQuarrie and Munson, 1992), not a single good measurement model exists. The personal involvement inventory (PII) of Zaich- kowsky (1985) and the consumer involvement profile (CIP) of Laurent and Kapferer (1985) are the most widely used measurement instru- ments. Nevertheless, both incorporate some drawbacks. The PII, for instance, is considered a model of high reliability; however, its validity has long been questioned because research indicates a dual factor structure in contra- diction to the one factor structure claimed by the author. The CIP, on the other hand, was hypothesised to have a five-factor structure that could not be confirmed. The CIP was then assumed to contain four factors: imporisk (importance and risk), interest,pleasure, and sign value.
In operationalising product involvement for the purpose of our study we were guided by existing research efforts. We formulated 13 items measuring product involvement and believe them to be attributed to three factors:
(1) importance, (2) pleasure, and (3) sign value. Our decision for not including risk into our involvement construct is in line with recent research efforts. Researchers are cur- rently propagating the conceptual separation
Table 1. Measurement model for consumer decision-making styles
Item Item-to-total Factor Factor Indicator
correlation loading (EFA) loading (CFA) reliability (CFA) (ITTC0.40) (a0.60) (a0.50) (px0.40) Factor 1: brand/store loyalty (Alpha¼ 0.91) Construct reliability (pc0.60) 0.85
I usually choose the more expensive brands. 0.78 0.81 nc nc
I prefer buying well-known brands. 0.72 0.78 nc nc
In order to buy this product, I always go to 0.77 0.76 nc nc
the same shop(s).
I have certain favourite brands, which 0.71 0.76 0.46 0.21
I buy every time.
I usually make a special effort to choose 0.70 0.75 0.79 0.63
the best quality product available.
Once I have made a choice regarding the 0.75 0.74 nc nc
shop(s) from which to buy this product, I prefer shopping there without trying other shops.
Once I have found a brand I like, 0.68 0.74 0.65 0.42
I buy it regularly.
My standards and expectations 0.68 0.71 0.50 0.25
regarding the product I intend to buy are very high.
I usually buy the very latest products. 0.57 0.62 0.69 0.48
I do my shopping quickly, buying 0.52 0.56 0.75 0.57
the first product I find that seems good enough.a
I do not think the different brands in 0.51 0.54 0.80 0.64
this product category differ much in terms of overall quality.
Factor 2: spontaneity (Alpha¼0.73) 0.78
I often make careless purchase decisions, 0.52 0.79 0.70 0.49
which I later regret.
I should plan my shopping more carefully. 0.62 0.76 0.73 0.53
I should spend more time deciding in 0.53 0.68 0.67 0.45
favour of a certain product.
I often make spontaneous purchase 0.44 0.60 0.64 0.41
decisions.
Factor 3: Price-Value Consciousness 0.45
(Alpha¼0.88)
I often look for sale specials. 0.83 0.91 0.57 0.45
I look very carefully to find the best 0.71 0.85 0.50 0.29
value for money.
I usually save quite a lot of money 0.77 0.84 nc nc
by shopping around for bargains.
Factor 4: Variety-Seeking (Alpha¼ 0.67) nc
I really enjoy trying different products 0.53 0.80 nc nc
or brands.
For variation’s sake, I shop in different 0.48 0.72 nc nc
or new stores and choose different brands.
I am very cautious about trying out new 0.45 0.68 nc nc
products or brands.a
Global fit criteria: GFI¼0.92 AGFI¼0.88 CFI¼0.90 2¼631b df¼62
Note: EFA¼ Exploratory factor analysis; CFA, Confirmatory factor analysis; nc, not considered in the analysis
aItem is reverse scored.
bIt has to be kept in mind that2has to be interpreted very carefully when using the Unweighted least squares method (ULS) and should not be regarded as key criteria in this context.
of involvement and risk constructs, which represent related, but by no means identical constructs (Andrews et al., 1990; Bloch and Richins, 1983). Rajaniemi und Laaksonen (1986) further emphasise that the risk con- struct is a manifestation of the individual state approach, while all other components of the CIP represent cognitive states. We consider involvement to be a complex mental and enduring intervening construct (consisting of three factors) that stands between the con- sumer and his behaviour, and therefore influences his purchase decision process.
Thus, the hypothesis we formulate is the following:
H1: Consumer decision-making styles are dependent on product involvement.
EFA and CFA confirmed our hypothesised factor structure. We believe that the results produced by the following analysis of the whole sample in the wristwatch case provide a sound basis for a transfer of findings to
products within the same product category (as classified by the traditional consumer decision- process continuum scheme) and with a similar level of consumers’ product involvement. As demonstrated in Table 2, the analysis of our proposed involvement model shows excellent results. The hypothesised three-factor struc- ture was identified by EFA with the three factors explaining 67.4 per cent of variance.
Only one item needed to be eliminated because of a low factor loading of 0.46, all other factor loadings exceed 0.50. Results from CFA are good as well. Only two of 12 items do not meet local fit criteria. Global fit indices are satisfac- tory. Table 2 also includes a column showing mean item values. On the five-point Likert- scale, items for wristwatch involvement show values between 2.7 and 4.5. Mean item values for involvement with the product category yoghurt are considerably lower; they range from 1.42 to 2.92. Two tailored t-tests reveal that the differences in mean item values between the two product categories are highly
Table 2. Measurement model for product involvement
Item Item-to-total Factor Factor Indicator Mean
correlation loading (EFA) loading (CFA) reliability item
(ITTC0.40) (a0.60) (a0.50) (CFA) value
(px0.40)
Factor 1: sign value (Alpha¼0.89) Construct reliability (pc0.60) 0.66
*This product tells other people 0.80 0.86 0.44 0.19 3.29
sth. about me.
*It helps me express my personality. 0.83 0.84 0.77 0.59 3.22
*It does not reflect my personality.a 0.72 0.81 0.61 0.38 3.49
*It is part of my self-image. 0.67 0.73 0.46 0.21 3.04
Factor 2: importance (Alpha¼0.83) 0.79
*It is not relevant to me.a 0.74 0.80 0.64 0.41 4.28
*It does not matter to me.a 0.62 0.80 0.73 0.53 4.34
*It is of no concern to me.a 0.68 0.78 0.76 0.58 4.18
*It is important to me. 0.60 0.75 0.66 0.44 4.53
Factor 3: pleasure (Alpha¼0.86) 0.76
*This product is fun. 0.66 0.84 0.72 0.52 3.10
*I find it fascinating. 0.74 0.78 0.66 0.44 2.92
*I find it exciting. 0.70 0.77 0.62 0.38 2.72
*I am interested in it. 0.64 0.61 0.59 0.35 3.51
Global fit criteria: GFI¼0.92 AGFI¼0.88 CFI¼0.90 2¼415b df¼51 Note: EFA, exploratory factor analysis; CFA, confirmatory factor analysis; nc, not considered in the analysis.
aItem is reverse scored.
bIt has to be kept in mind that2has to be interpreted very carefully when usingULSand should not be regarded as key criteria in this context.
significant in all cases. This result confirms our pretest results.
Causal modelling
In the previous sections we created models to measure CDMS as well as product involvement.
Now, the relationship between these two constructs shall be analysed. We believe that consumers highly involved in a product cate- gory are more loyal, less spontaneous and less price-value conscious. Because CFA did not result in usable values of the CDMS Variety Seeking we are not able to test its relationship with product involvement. We assume the stated causalities, and thus, formulate the following hypotheses:
H2:Between product involvement and the CDMS Brand/Store Loyalty, a positive relationship exists.
H3:Between product involvement and the CDMS Spontaneity, a negative relationship exists.
H4:Between product involvement and the CDMS Price-Value Consciousness, a nega- tive relationship exists.
The postulated relationships are analysed with the help of a structural equation model (SEM). In contrast to measurement models that can be estimated even if the construct is not directly determined by indicators, but by factors (a so called second-order factor model, for this please refer to Byrne (1998)), LISREL restricts structural equation modelling to con- structs directly measured by indicators. Since this is not the case for our involvement construct, we have to estimate the causalities between the three involvement factors sign value, importance, and pleasure. Results of the SEM are good for all cases. The causalities between the three involvement factors and the CDMS brand/store loyalty are all positive, those between involvement and Spontaneity and price-value consciousness are all negative.
The CDMSbrand/store loyaltyis determined by the involvement factor sign value, with a
significant effect of 0.55, by Importance with 0.64, and by pleasure with 0.07 (not signifi- cant). The significant path coefficients of the three involvement factors onspontaneityand price-value consciousness are the following:
0.52 and0.73,0.72 and0.65,0.17 and 0.38, respectively. Global goodness-of-fit indices are all satisfactory. GFI for all three models exceeds 0.90; AGFI is at least 0.87, and CFI at least 0.88. Thus, hypothesesH2,H3and H4are confirmed.
Discussion
The findings of our study are threefold. Firstly, in line with previous research, Sproles and Kendall’s consumer styles inventory (CSI) was found to entail some shortcomings with regard to reliability and validity aspects. For this reason, we proposed a new, more compact, but product category-dependent model of consumer decision-making styles (CDMS). In developing the new CDMS model, we relied on the traditional consumer decision-process con- tinuum scheme. Extensive analyses revealed the special importance of four factors for products with moderate involvement and medium financial investment: brand/store loy- alty, spontaneity, price-value consciousness, and variety-seeking. Interestingly, the exten- sive purchase decisions styles (i.e., perfection- ism and innovativeness) did not form a separate dimension but intermingled with the indica- tors of brand and store loyalty. This result, however, is consistent with the product category under investigation: watches. It underlines the importance of developing adequate CDMS for different product cate- gories (e.g., different overall product involve- ment). Yet, we believe that the model proposed for such moderate involvement and financial investment products is of good ease of administration and utility and thus represents a first step into the necessary research direction.
However, future research has to verify the model’s appropriateness, reliability, and valid- ity. Most importantly it has to be noted that we succeeded in showing that CDMS are not product-independent and that they—on top
of their product-dependence —are governed by consumers’ product involvement. The latter finding is even more precious if one takes the common use of CDMS into consideration: up to now, CDMS have only been investigated in product-independent settings.
The findings we produced are certainly disappointing for those who believed in the existence of a consumer decision-making styles inventory that is applicable across products, population groups, and cultures. The approach needs some rethinking and further research has to be facilitated into decision-making styles within product categories. However, such style-knowledge bears some major advantages over that of apparently ‘general’ (i.e., product- independent) CDMS. It is more precise and, thus, more realistic than the universal approach. Just think about your own shopping behaviour when buying toothpaste or butter, for instance, in comparison to deciding on a new pair of sneakers or jeans. Does your decision-making process and finally your beha- viour follow the same pattern? A precise styles inventory is a valuable tool for a number of interest groups: It helps consumer behaviour researchers to better understand consumers’
shopping behaviour. In addition, findings in this field will enable marketing managers to more efficiently target consumers exhibiting the same CDMS. Consequently, consumers will be provided with offers that are more ade- quately tailored to their needs, which will result in greater consumer satisfaction. Further- more, consumer affairs specialists will develop a better understanding of how to help and educate consumers with low shopping or consumer sophistication, turning them into
‘better’ consumers. Since customer satisfac- tion is not only a goal of consumers, but is also in the interest of consumer affairs specialists and companies, all groups can take advantage of more clear-cut CDMS.
In order to achieve this goal, consumer behaviour researchers are encouraged to further investigate the discovered relationship, namely that products and product involvement appear to have an important influence on the style consumers exhibit in decision-making.
Biographical Notes
Prof. Hans H. Baueris a full tenured professor and chairman of the Department of Business Administration and Marketing II at the Uni- versity of Mannheim in Germany. Furthermore, he is the scientific director of the Institute for Market-Oriented Management (IMU) at the University of Mannheim. Before joining the Mannheim faculty in 1993, he was professor of marketing at the Otto Beisheim Graduate School of Management Koblenz (WHU), where he also held the office of president from 1991 to 1993. He published five books and more than 200 journal and book articles. His major research areas are customer management, consumer behaviour analysis, brand manage- ment and strategic marketing.
Nicola E. Sauer is an assistant marketing professor at the Department of Business Administration and Marketing II at the Uni- versity of Mannheim in Germany. She obtained a doctorate in business administration at the same school, specialising in consumer beha- viour construct development. She currently teaches consumer behaviour in the graduate program of the school. Her research interests are related to consumer decision-making, cross-cultural issues of consumer behaviour, lifestyle analysis, as well as customer satisfac- tion and loyalty research.
Christine Beckerrecently graduated from the University of Mannheim, where she studied English and Business Administration with a major area of concentration in marketing. She wrote her diploma thesis in the field of consumer decision-making behaviour. Her primary research interests focus on consumer behaviour and market research, with a special emphasis on cross-cultural issues. She is now working as a marketing manager at a reputable, globally operating company in the automotive supplier industry.
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