- Email: [email protected]
Consumer habit forming, information acquisition, and buying behavior
Consumer Habit Forming, Information Acquisition, and Buying Behavior Klaus Peter Kaas, University of Frankfurt
Based on rhe three s~uges oj’consumer unul~;es
the itlfluetrces
ittjitrmution, jirsr
child.
oj’cwtrsutner
und buying behavior. their hubit j~trtnutiotr
The duru cwtjirttr ,j&r ttiurketiti~
decisiott muking proposed habit jitrmurion
Using u sutnple
by Ho\curd.
OII inj?trtnution
of' women
stored
having or e.rpecritrg their
!cith regurd to three baby-rehted
tnost oj’the hypotheses derivedfrom
this srud~
ucyuisition.
the theoreticul
products
is us.sessed.
tnodel. Implicuriotts
twe discussrd.
The assertion that man is a habit forming species applies to his role as a consumer as well. George Katona was one of the first to bring this to the attention of economists. He describes habitual behavior very clearly: “What has been done before is done again, long-established patterns of behavior being repeated more or less automatically. Then we are not aware of any problem, and alternative courses of action do not even come to mind. Therefore, there is no deliberation and no choosing” [ 10, p. 1401. If consumers were buying according to this pattern, marketing as a social technology trying to influence behavior would have hardly a chance in “established” product classes. Indeed, in some consumer goods markets it is very difficult nowadays to achieve shifts in market shares or even to position a new brand. On the other hand, there can be no doubt that marketing is done for frequently purchased products, and with success. It seems that the assertion made by Katona has to be put into more precise terms if it is to have any practical value. The present contribution tries to do just this. The aim is to clarify the differences between habitual and nonhabitual buying behavior. What happens to buying behavior, information processing, attitudes, and so forth of a consumer who becomes familiar with a product that at the outset was new to him? A theoretically based and empirically verified answer to this question is important for the marketing of frequently purchased products. It is helpful to solve the following problems: Address correspondence D-6000
FranA-fitrt/M.,
to Klaus Peter Kaas, University
of’Frankfurt,
Mertonstr.
17,
If’est Germany.
10, 3-15 (1982) RESEARCH OFBUSINESS Science Publishing Co., Inc., 1982 52 Vanderbilt Ave., New York, NY 10017
JOURNAL @ Elsevier
3 0148-2963/82/01003-13$2.75
4
Klaus Peter Kaas
1. How has marketing to adapt when new products become old ones, when inexperienced consumers become experienced? 2. How can marketing take advantage of habitual buying behavior? 3. How can habitual buying behavior be broken up by marketing? Following Katona, many authors contrast habitual behavior with problem solving behavior to emphasize the differences [3, 11, 2 I]. Usually the impression is created that problem solving behavior is typical for high-priced specialty goods and services, while the bulk of convenience goods is bought routinely. Thus subjective risk associated with the purchase of a washing machine is supposed to be higher than that associated with buying a package of breakfast cereal. Similar reasoning might apply for the amount of information acquisition before the purchase. However, it is not admissible to use such differences to derive hypotheses about the formation of habits. It is intuitively appealing that for the average consumer the purchase of a washing machine is a small adventure, while the purchase of cereal is a routine matter. However, there are other, product-specific factors that determine the amount of risk and acquired information. A washing machine is more expensive than cereal, it can spoil the laundry while cereal can only spoil the good mood at the breakfast table, a washing machine is much more complex than cereal, maybe the number of brands and types is different, and so on. All this amounts to the following: if changes in buying behavior due to habit formation are to be isolated, first and last purchases of a consumer within the same product class have to be compared (i.e., buying history has to be analyzed).This presupposes a time-related theory of consumer behavior on the theoretical level, and a longitudinal analysis on the methodological level. Our theoretical approach is based on a theory developed by J. A. Howard, while our methodological approach is based on studies on social change. Howard applies Osgood’s theory of concept Theoretical Concept learning to consumer behavior toward a new product [S, 91. He distinguishes three stages of consumer behavior after the introduction of a substantially new product (e.g., instant coffee). See Table 1. In the first stage, concept formation, the consumer has as yet stored no information about the product class (e .g . , instant coffee). He has to gain an image of the new product class (product class comprehension) by learning choice criteria and discriminating among the relevant brands. To do this, the consumer needs product-class-specific, concept forming information. The result is the “awareness set” of brands, which constitutes the product class in the perception of the consumer. In this
Habit, Information,
5
and Buying
Table 1: Stages of Habit Forming”
Learning Amount of information Speed of decision
EPS Extensive Problem Solving
LPS Limited Problem Solving
RRB Routinized Response Behavior
concept formation large
concept attainment medium
concept utilization small
slow
medium
fast
n See Ref. 8, pp. 10-11.
first stage the purchase is a problem for the consumer, because he has only little information. Howard calls this “extensive problem solving” (EPS). At the beginning of the second stage, concept attainment, information about the product class is stored, and brand concepts have to be formed. The choice criteria are applied to the individual brands. Brand attitudes and a distinction between the “evoked set” of accepted brands and the “inept set” of rejected brands are the result [8, 131. Hence information acquisition is concentrated on brand-specific information. The consumer wants to know which values the individual brands have on the choice criteria. This stage, in which the consumer has some, but not sufficient, information is called “limited problem solving” (LPS) by Howard. In the third stage, concept utilization, enough information about the product class is stored. Information processing is concentrated within the evoked set on situational attributes like price, availability, and shelf position of a brand. The purchase has become “routinized response behavior’ ’ (RRB). Howard’s stage model emphasizes the amount and kind of information processed. However, the way in which this information is processed may change from stage to stage as well. Several relevant models are distinguished in the literature (e.g., the linear-compensatory, lexicographic, disjunctive, and conjunctive choice heuristics [3]). Raju and Reilly found that different choice heuristics are used for ‘ ‘familiar” and “unfamiliar” product classes. Heuristics presupposing complex operations (e.g., detailed weighing or at least a rank order of choice criteria) seem to be used mainly with familiar product classes, while less sophisticated heuristics dominate in unfamiliar product classes [ 14, 191. Figure 1 graphically presents information processing in the three stages.
6
Kluus
L______
Peter Kaas
Habit, Information,
and Buying
7
The changes in information processing can be expected to have consequences for buying behavior. In the EPS stage, where perceived risk is still very high, a tendency to buy small quantities and high-priced goods-because price is used as an indicator of quality-is to be expected. The high information need in this stage can be expected to result in a preference for stores having trained sales staff, while discount stores and bargains will be used more frequently in the RRB stage. Research Design To observe the process of habit Methods of Longitudinal Analysis formation empirically, data on buying histories are necessary, especially on their beginnings. Buying histories are triggered by objective innovations in the market or by events in consumers’ lives that confront them with subjectively new products. Such an event may be the founding of a household, which results in needs for certain household appliances, or the birth of the first child resulting in a need for baby products. In the present case the birth of the first child was chosen as the trigger event. For the baby, this event is the beginning of its life history (investigated by sociologists [ 15,221); for the mother, it is the beginning of a buying history concerning products for baby care and baby nutrition (investigated by consumer researchers). The various designs for collecting and evaluating such buving histories are visualized best by means of a schematic representation of longitudinal studies (Figure 2). Figure 2 shows three cohorts of mothers who have given birth to their first child in March, April, and May, respectively. Cohorts are “aggregates of people (within some population) who experienced the same event within the same time interval” [ 15, p. 1361. The vertical lines delineate measurement of the mothers’ information and buying behavior at the respective time points. In comparing any two measurements, three effects have to be distinguished [5,6]: 1. The period effect mirrors the influence of history. In our application this could be influences of price rises or introductions of new products. 2. The aging effect mirrors that women as mothers and buyers of baby products become older. In our application this concerns the influences of habit formation. 3. The cohort effect reflects the influence of the month of birth. In our application, when time spans are short, this effect will certainly not have a major role. It is what in studies on social change is called the generation effect.
Klaus Peter
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Habit, Information,
and Buying
Figure 2 shows that any two measurements
9 pick up at least two effects
PI: Design A (panel analysis): Measurements of the same cohort (e.g., 1 and 2) pick up the period and the aging effect; Design B (cross-sectional analysis): Measurements at the same point in time (e.g., 1,5, and 8) pick up the aging and the cohort effect; Design C: Measurements at the same cohort age (e.g., 2,5, and 7) pick up the period and the cohort effect. In the present case only the aging effect is of interest, since it conforms with the effect of habit formation. Since the cohort effect is most probably nil in our application, design B is most appropriate to isolate the aging effect. Longitudinal Analysis of Cross-sectional Data We are thus dealing with a cross-sectional analysis that gets a temporal dimension because of the inclusion of baby age as an independent variable. Formally, this is the same procedure as the evaluation of an ex post facto experiment [4]. The question remains as to whether baby age should be treated as a categorical or continuous variable. How many cohorts are to be formed, a few big ones or many small ones? Howard’s theory suggests the formation of three cohorts; unfortunately there is no way of knowing a priori how long the respective periods have to be chosen. In the present study baby age was measured in weeks, which results in a rather continuous variable. This seems to be reasonable, since Howard’s three stages are only idealized stages in a basically continuous process. For data collection, personal interviews were conducted with 123 mothers having their first child and 23 women pregnant for the first time. Questions were asked about information and buying behavior in the product classes baby food, diapers, and lotion. According to the theory used, information acquisition (amount, content, sources), stored information (brand awareness, brand attitudes), and buying behavior (brand, price, package size, and the like) were ascertained. The choice heuristic used could not be assessed, because the measurement instrument necessary to do this is too sophisticated for standardized interviews. The results presented in the following section refer to the product class baby food. Results for the other two product classes are almost identical. Hypotheses and Results Amount of Information Acquisition Table 2 shows two hypotheses about the intensity of information acquisition. Subjects were presented a
Klaus Peter
10
Table 2: Hypotheses
With Increasing
Baby Age.
on the Amount
..
of Information
Operationalization of Variables
Acquisition Test, Level of Significance
HII .._ The number of information sources used decreases
Question about the use of 16 information sources before purchase
Pearson
HI2 The frequency of information decreases
Question about the frequency of usage of 16 information sources in past three weeks
Spearman
of usage sources
Kaas
Correlation
r = -0.46 OL< 0.001 Correlation
p = -0.45 lx< 0.001
list of 16 information sources that can be used to acquire information about baby products (e.g., doctors, sales personnel, TV advertising, product tests). They were asked to indicate the frequency of usage of these sources in the past three weeks on a rating scale. With increasing baby age, fewer sources are used (H, ,) and usage is less frequent (H&. As the test values in Table 2 show, this effect is very strong. Mothers of older babies seem to stop their information search activities almost completely. Structure of Information Acquisition Table 3 shows the hypotheses about the structure of information acquisition. Hypothesis Hz, concerns the change in information acquisition from the EPS stage to the LPS stage. The women were asked whether in their information search they paid attention more to general information about baby food or more to information about specific brands. Women who prefer general information had babies that were significantly younger than those of women who acquired information about specific brands. This supports Howard’s suggestion that a product class concept is formed first, followed by the formation of specific brand concepts. Since information about product classes is to be found more easily in neutral sources (e.g., specialized magazines) while brand-specific information is offered mainly by suppliers, it is to be expected that during the process of habit formation, information acquisition shifts from neutral to supplier-controlled sources. This is also supported by the hypothesis that subjective risk decreases over time and with it the preference for credible, competent information sources. The corresponding hypothesis Hz2could not be supported; only when controlling for education did it almost reach significance. This is in accordance with
Habit, Information,
and Buying
Table 3: Hypotheses
With Increasing
Baby Age.
Hz, . . . Information search shifts from concept forming to concept attaining information
HZZ... Information search shifts from neutral to suppliercontrolled sources
Hz3... Product-related criteria become important
choice less
Hz4 Situational choice criteria become more important
11
on the Structure
..
of Information
Acquisition
Operationalization of Variables
Test, Level of Significance
Question if consumer “searches more general product information” or “more information about specific brands”
r-test (Y< 0.05
Sixteen information sources dichotomized into neutral and supplier-controlled
contingency NS
Importance ratings for criteria like digestibility, freshness, vitamin content Importance ratings for criteria like price, availability, special bargains
test,
Correlation (average value) r,r, = -0.29 0 < 0.05 Correlation (average value) ro = 0.22 01 < 0.05
findings indicating that the use of neutral information like product tests correlates with level of education [ 171. Hypotheses Hz3 and Hz4 imply that young mothers, who are not yet familiar with baby products, assign more importance to product-related choice criteria like digestibility, freshness, and vitamin content than do experienced mothers. On the other hand, situational criteria like price, availability, and special bargains are more important for older mothers than for young ones. This does not indicate that women become careless about their baby as time goes on. Rather, they learn the qualities of the various brands, and when the evaluation of quality is no longer a problem, they try to buy as comfortable and as economically as possible. Content and Structure of Stored Information Table 4 lists two hypotheses on content and structure of stored information. According to hypothesis H3,,anextension of the “awareness set” was expected (i.e., the set of brands that the respondents assign to the respective product class, namely, baby food). This hypothesis could be supported for none of the product classes investigated. A probable reason for this is that most women know almost all brands at a very early stage, a result of their high involvement and the modest number of brands (at most six).
Klaus Peter Kaas
12
Table 4: Hypotheses With Increasing
Baby Age
H31 The awareness set becomes larger
Hs2... Brand attitudes drift apart
on the Structure .
of Stored Information
Operationalization of Variables Question known
about
Test, Level of Significance brands
index based on the polarity of ratings on scales measuring perceived instrumentality (aggregated over all ratings and brands of a respondent)
Contingency NS
test,
Correlation r = 0.432 01 < 0.001
Hypothesis H,, concerns the formation of an “evoked set” and an “inept set” [ 131. The concept of “evoked set” plays a major role in Howard’s theory. An important effect of habit formation is that the consumer reduces the number of relevant brand alternatives-in the extreme case of brand loyalty, only one acceptable brand remains. Hence the “awareness set” encompasses two subsets: the “evoked set” of aceptable brands and the “inept set” of rejected brands (sometimes an ‘ ‘inert set’ ’ containing indifferent brands is added [ 131). The evoked set can be measured by directly asking for the acceptable brands [I, 121. Here, however, an indirect method was used, which makes the polarization of brands into “evoked set” on one side and “inept set” on the other side more visible. In order to do this, the perceived instrumentality of the various brands concerning the attributes digestibility, freshness, taste and so on was measured using the procedure proposed by Rosenberg [ 16, 181. Then an index was computed that aggregates the distances between ratings and scale means over all attributes and brands for each respondent. The correlation between the index and baby age is highly significant (i.e., with increasing habit formation brand atitudes drift apart). In the literature, many times habitual buying behavior is associated with brand loyalty [2, 201. The relationship between brand loyalty and habitual buying behavior is asymmetrical. It can be assumed that brand loyalty is a result of habit formation, but habit formation does not always have to result in brand loyalty. Habitual buying can also mean that within the evoked set the consumer always buys the brand that is temporarily cheapest or available in the right package size. Under these conditions it is difficult to establish a hypothesis about the relation between habitual
Habit,
Information,
Table 5: Hypotheses With Increasing
13
and Buying
Baby Age
on Buying Behavior .
Operationalization of Variables
Test, Level of Sianificance
HaI . . . Quantities per purchase increase
Quantity bought last purchase
Hd2... Consumers change from specialty stores to discounters
Store where last purchase was made
Tendency as expected, n of cases too low for test
Ha3... Number bargains
Bargain used at last purchase
Tendency as expected, n of cases too low for test
of special bought increases
at
Correlation r = 0.25 (Y> 0.05
behavior and brand loyalty. Also, in the present study, brand loyalty could be ascertained only with doubtful validity (by retrospective interviews). This problem is addressed in a panel study currently underway. Here only the hypotheses in Table 5 could be tested, by collecting data about brand, quantity, price, mode of supply, and store of the last purchase of baby food. As was expected, the quantity bought per purchase increases with baby age, owing to the decreased risk. Ha2 and Hd3 were supported by the data as well, but, as a restriction, only a few women buy in specialty shops or buy premium offers. Conclusion Not all hypotheses have survived the test, but in general a rather theoryconforming picture emerges, especially as far as information processing is concerned. Consumers collecting purchase experiences and forming habits reduce their information search and shift from product-specific to brand-specific and situational attributes, they buy larger quantities at a time, and they change from specialty shops to discounters. What does this imply for the answers to the questions posed at the beginning about the opportunities and handicaps of marketing? Doubtlessly, the chances of marketing are highest when consumers are young-not in years, but in product experience. In the case of substantially new products all consumers are young in this sense, in established markets only the cohorts that are added: for automobile
Klaus Peter
14
Kaas
supplies the people buying their first car, for household appliances the people moving into their first apartment, for services those who have just moved and so forth. In young cohorts, it is possible to attain what can be attained in old cohorts only at high cost or not at all: to influence the direction of the process of habit formation. To do this, marketing has to supply the right kind and amount of information at the right time and adapt the supply to the degree of habit formation reached. At the beginning, technical, neutral, general product advice in sales talks or through advertising is important. The high perceived risk has to be overcome by small package sizes, guarantees, free samples, and the like so that a brand has a chance to become a member of the evoked set. When consumers have reached the RRB stage, a different policy is necessary. The emphasis now has to be on the distribution system, sales promotion, store advertising in newspapers, and leaflet advertising. This way the situational influences on consumers’ choice can be taken advantage of [3]. Last but not least, a supplier can try to break up the habitualized behavior to induce consumers to enter a new stage of concept formation. This requires a lot of effort, a lot of noise, and especially innovations that can force consumers to revise their product class concept. New attributes, unknown or unseen to date, or new product uses can be used for this purpose. Thus in the long range a cyclical process emerges, vividly portrayed by Sheth and Raju [ 191, that is kept going not only by marketing but also by other societal forces: people become accustomed to novelities-that is the psychology of simplification. To see known things in a new light-that is the psychology of complication. It could be added: to think and act in this cycle-that is the philosophy of marketing.
References 1.
Belonax, Joseph A., Jr., and Mittelstaedt, Robert A., Evoked Set Size as a Function of Number of Choice Criteria and Information Variability, Advances in Consum. Rex 5 (1978): 48-51.
2.
Berkman, Harold W., and Gilson, Encino and Belmont, CA, 1978.
3.
Bettman, James R., An Information dison-Wesley, Reading, Pa., 1979.
4.
Campbell, Donald mental Designsfor
5.
Glenn, NorvalD.,Cohort Age, Period and Cohort
Christopher
C., Consumer
Behavior.
Processing Theory of Consumer
T., and Stanley, Julian Research. Rand McNally,
C., Experimental Chicago, 1963.
Dickenson, Choice. Ad-
and Quasi-Experi-
Analysists’ Futile Quest: Statistical Attempts to Separate Effects, Am. Socbl. Rev. 41 (1976): 900-904.
Habit.
Infbrrnation.
1.5
and Buying
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Goldstein. Harvey, Age, Period and Cohort Bull. Applied Stat. 6 (1979): 19-24.
7.
Hansen,
8.
Howard, John A., Consumer New York, 1977.
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Kaas, Klaus Peter, bei Konsumgiitern,
Flemming.
George,
Corzsumer
Effects-A
Confounded
Confusion,
Choice Behavior. Free Press, New York, Behavior:
Application
of Theory.
and Dieterich, Michael, Die Entstehung Marketing 1 (1979): 13-22.
The Powerful Consumer. McGraw-Hill,
1972.
McGraw
Hill,
von Kaufgewohnheiten
10.
Katona.
11.
Kroeber-Riel,
12.
May, Frederick, E., and Homans, Richard E., Evoked Set Size and the Level of Information Processing in Product Comprehension and Choice Criteria, Advances in Consum. Res. 4 (1977): 172-175.
13.
Narayana, formance: 1-6.
14.
Raju, Puthankurissi S., and Reilly, Michael D., Product Familiarity and Information Processing Strategies: An Exploratory Investigation, Working Series in Marketing Research, No. 57., The Pennsylvania State University, 1977.
15.
Reuband, Karl-Heinz, Life Histories: Problems and Prospects of Longitudinal Designs, in Historical Social Research. J. M. Clubb and E. K. Scheuch, eds., KlettCotta, Stuttgart, 1980, p. 135-163.
16.
Rosenberg, Milton J., Cognitive Sot. Psy. 53 (1956): 367-372.
17.
Thorelli, Hans B., Becker, Helmut, Ballinger, Cambridge, 1975.
18.
Trommsdorff, Volker, Die Mesung von Produktimages manns, Cologne, 1975.
19.
Sheth, Jagdish N., and Raju, Puthankurissi S., Sequential and Cyclical Nature of Information Processing Models in Repetitive Choice Behavior, Advances in Consum. Res. 1 (1973): 348-358.
20.
Weinberg,
21.
Weinberg, Paderborn,
22.
White Riley, terpretations,
23.
White Riley, Matilda, Johnson, Marilyn, and Foner, Anne, eds., Aging andsociety, Vol. III: A Sociology of Age Stratification, Russel Sage Foundation, New York, 1972.
Werner, Konsumentenverhalten.
Chem L., and An Alternative
Das
1960.
Munich,
1980.
Markin, Rom J., Consumer Behavior and Product PerConceptualization, J. Marketing 39 (October 1975):
Peter, Die Produkttreue Peter, 1981.
New York,
2nd ed. Vahlen,
Structure
and Attitudinal
and Engledow,
Matilda, Aging and Cohort Public Choice Q, 37 (1973):
J. Abnormal
Jack, The Information
der Konsumenten.
Entscheidungsverhalten
Affect,
fur das Marketing.
Gabler,
Wiesbaden,
der Konsumenten.
Succession: 35-49.
Seekers,
Interpretations
Hey-
1977. Schoningh,
and Misin-
Based on rhe three s~uges oj’consumer unul~;es
the itlfluetrces
ittjitrmution, jirsr
child.
oj’cwtrsutner
und buying behavior. their hubit j~trtnutiotr
The duru cwtjirttr ,j&r ttiurketiti~
decisiott muking proposed habit jitrmurion
Using u sutnple
by Ho\curd.
OII inj?trtnution
of' women
stored
having or e.rpecritrg their
!cith regurd to three baby-rehted
tnost oj’the hypotheses derivedfrom
this srud~
ucyuisition.
the theoreticul
products
is us.sessed.
tnodel. Implicuriotts
twe discussrd.
The assertion that man is a habit forming species applies to his role as a consumer as well. George Katona was one of the first to bring this to the attention of economists. He describes habitual behavior very clearly: “What has been done before is done again, long-established patterns of behavior being repeated more or less automatically. Then we are not aware of any problem, and alternative courses of action do not even come to mind. Therefore, there is no deliberation and no choosing” [ 10, p. 1401. If consumers were buying according to this pattern, marketing as a social technology trying to influence behavior would have hardly a chance in “established” product classes. Indeed, in some consumer goods markets it is very difficult nowadays to achieve shifts in market shares or even to position a new brand. On the other hand, there can be no doubt that marketing is done for frequently purchased products, and with success. It seems that the assertion made by Katona has to be put into more precise terms if it is to have any practical value. The present contribution tries to do just this. The aim is to clarify the differences between habitual and nonhabitual buying behavior. What happens to buying behavior, information processing, attitudes, and so forth of a consumer who becomes familiar with a product that at the outset was new to him? A theoretically based and empirically verified answer to this question is important for the marketing of frequently purchased products. It is helpful to solve the following problems: Address correspondence D-6000
FranA-fitrt/M.,
to Klaus Peter Kaas, University
of’Frankfurt,
Mertonstr.
17,
If’est Germany.
10, 3-15 (1982) RESEARCH OFBUSINESS Science Publishing Co., Inc., 1982 52 Vanderbilt Ave., New York, NY 10017
JOURNAL @ Elsevier
3 0148-2963/82/01003-13$2.75
4
Klaus Peter Kaas
1. How has marketing to adapt when new products become old ones, when inexperienced consumers become experienced? 2. How can marketing take advantage of habitual buying behavior? 3. How can habitual buying behavior be broken up by marketing? Following Katona, many authors contrast habitual behavior with problem solving behavior to emphasize the differences [3, 11, 2 I]. Usually the impression is created that problem solving behavior is typical for high-priced specialty goods and services, while the bulk of convenience goods is bought routinely. Thus subjective risk associated with the purchase of a washing machine is supposed to be higher than that associated with buying a package of breakfast cereal. Similar reasoning might apply for the amount of information acquisition before the purchase. However, it is not admissible to use such differences to derive hypotheses about the formation of habits. It is intuitively appealing that for the average consumer the purchase of a washing machine is a small adventure, while the purchase of cereal is a routine matter. However, there are other, product-specific factors that determine the amount of risk and acquired information. A washing machine is more expensive than cereal, it can spoil the laundry while cereal can only spoil the good mood at the breakfast table, a washing machine is much more complex than cereal, maybe the number of brands and types is different, and so on. All this amounts to the following: if changes in buying behavior due to habit formation are to be isolated, first and last purchases of a consumer within the same product class have to be compared (i.e., buying history has to be analyzed).This presupposes a time-related theory of consumer behavior on the theoretical level, and a longitudinal analysis on the methodological level. Our theoretical approach is based on a theory developed by J. A. Howard, while our methodological approach is based on studies on social change. Howard applies Osgood’s theory of concept Theoretical Concept learning to consumer behavior toward a new product [S, 91. He distinguishes three stages of consumer behavior after the introduction of a substantially new product (e.g., instant coffee). See Table 1. In the first stage, concept formation, the consumer has as yet stored no information about the product class (e .g . , instant coffee). He has to gain an image of the new product class (product class comprehension) by learning choice criteria and discriminating among the relevant brands. To do this, the consumer needs product-class-specific, concept forming information. The result is the “awareness set” of brands, which constitutes the product class in the perception of the consumer. In this
Habit, Information,
5
and Buying
Table 1: Stages of Habit Forming”
Learning Amount of information Speed of decision
EPS Extensive Problem Solving
LPS Limited Problem Solving
RRB Routinized Response Behavior
concept formation large
concept attainment medium
concept utilization small
slow
medium
fast
n See Ref. 8, pp. 10-11.
first stage the purchase is a problem for the consumer, because he has only little information. Howard calls this “extensive problem solving” (EPS). At the beginning of the second stage, concept attainment, information about the product class is stored, and brand concepts have to be formed. The choice criteria are applied to the individual brands. Brand attitudes and a distinction between the “evoked set” of accepted brands and the “inept set” of rejected brands are the result [8, 131. Hence information acquisition is concentrated on brand-specific information. The consumer wants to know which values the individual brands have on the choice criteria. This stage, in which the consumer has some, but not sufficient, information is called “limited problem solving” (LPS) by Howard. In the third stage, concept utilization, enough information about the product class is stored. Information processing is concentrated within the evoked set on situational attributes like price, availability, and shelf position of a brand. The purchase has become “routinized response behavior’ ’ (RRB). Howard’s stage model emphasizes the amount and kind of information processed. However, the way in which this information is processed may change from stage to stage as well. Several relevant models are distinguished in the literature (e.g., the linear-compensatory, lexicographic, disjunctive, and conjunctive choice heuristics [3]). Raju and Reilly found that different choice heuristics are used for ‘ ‘familiar” and “unfamiliar” product classes. Heuristics presupposing complex operations (e.g., detailed weighing or at least a rank order of choice criteria) seem to be used mainly with familiar product classes, while less sophisticated heuristics dominate in unfamiliar product classes [ 14, 191. Figure 1 graphically presents information processing in the three stages.
6
Kluus
L______
Peter Kaas
Habit, Information,
and Buying
7
The changes in information processing can be expected to have consequences for buying behavior. In the EPS stage, where perceived risk is still very high, a tendency to buy small quantities and high-priced goods-because price is used as an indicator of quality-is to be expected. The high information need in this stage can be expected to result in a preference for stores having trained sales staff, while discount stores and bargains will be used more frequently in the RRB stage. Research Design To observe the process of habit Methods of Longitudinal Analysis formation empirically, data on buying histories are necessary, especially on their beginnings. Buying histories are triggered by objective innovations in the market or by events in consumers’ lives that confront them with subjectively new products. Such an event may be the founding of a household, which results in needs for certain household appliances, or the birth of the first child resulting in a need for baby products. In the present case the birth of the first child was chosen as the trigger event. For the baby, this event is the beginning of its life history (investigated by sociologists [ 15,221); for the mother, it is the beginning of a buying history concerning products for baby care and baby nutrition (investigated by consumer researchers). The various designs for collecting and evaluating such buving histories are visualized best by means of a schematic representation of longitudinal studies (Figure 2). Figure 2 shows three cohorts of mothers who have given birth to their first child in March, April, and May, respectively. Cohorts are “aggregates of people (within some population) who experienced the same event within the same time interval” [ 15, p. 1361. The vertical lines delineate measurement of the mothers’ information and buying behavior at the respective time points. In comparing any two measurements, three effects have to be distinguished [5,6]: 1. The period effect mirrors the influence of history. In our application this could be influences of price rises or introductions of new products. 2. The aging effect mirrors that women as mothers and buyers of baby products become older. In our application this concerns the influences of habit formation. 3. The cohort effect reflects the influence of the month of birth. In our application, when time spans are short, this effect will certainly not have a major role. It is what in studies on social change is called the generation effect.
Klaus Peter
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Habit, Information,
and Buying
Figure 2 shows that any two measurements
9 pick up at least two effects
PI: Design A (panel analysis): Measurements of the same cohort (e.g., 1 and 2) pick up the period and the aging effect; Design B (cross-sectional analysis): Measurements at the same point in time (e.g., 1,5, and 8) pick up the aging and the cohort effect; Design C: Measurements at the same cohort age (e.g., 2,5, and 7) pick up the period and the cohort effect. In the present case only the aging effect is of interest, since it conforms with the effect of habit formation. Since the cohort effect is most probably nil in our application, design B is most appropriate to isolate the aging effect. Longitudinal Analysis of Cross-sectional Data We are thus dealing with a cross-sectional analysis that gets a temporal dimension because of the inclusion of baby age as an independent variable. Formally, this is the same procedure as the evaluation of an ex post facto experiment [4]. The question remains as to whether baby age should be treated as a categorical or continuous variable. How many cohorts are to be formed, a few big ones or many small ones? Howard’s theory suggests the formation of three cohorts; unfortunately there is no way of knowing a priori how long the respective periods have to be chosen. In the present study baby age was measured in weeks, which results in a rather continuous variable. This seems to be reasonable, since Howard’s three stages are only idealized stages in a basically continuous process. For data collection, personal interviews were conducted with 123 mothers having their first child and 23 women pregnant for the first time. Questions were asked about information and buying behavior in the product classes baby food, diapers, and lotion. According to the theory used, information acquisition (amount, content, sources), stored information (brand awareness, brand attitudes), and buying behavior (brand, price, package size, and the like) were ascertained. The choice heuristic used could not be assessed, because the measurement instrument necessary to do this is too sophisticated for standardized interviews. The results presented in the following section refer to the product class baby food. Results for the other two product classes are almost identical. Hypotheses and Results Amount of Information Acquisition Table 2 shows two hypotheses about the intensity of information acquisition. Subjects were presented a
Klaus Peter
10
Table 2: Hypotheses
With Increasing
Baby Age.
on the Amount
..
of Information
Operationalization of Variables
Acquisition Test, Level of Significance
HII .._ The number of information sources used decreases
Question about the use of 16 information sources before purchase
Pearson
HI2 The frequency of information decreases
Question about the frequency of usage of 16 information sources in past three weeks
Spearman
of usage sources
Kaas
Correlation
r = -0.46 OL< 0.001 Correlation
p = -0.45 lx< 0.001
list of 16 information sources that can be used to acquire information about baby products (e.g., doctors, sales personnel, TV advertising, product tests). They were asked to indicate the frequency of usage of these sources in the past three weeks on a rating scale. With increasing baby age, fewer sources are used (H, ,) and usage is less frequent (H&. As the test values in Table 2 show, this effect is very strong. Mothers of older babies seem to stop their information search activities almost completely. Structure of Information Acquisition Table 3 shows the hypotheses about the structure of information acquisition. Hypothesis Hz, concerns the change in information acquisition from the EPS stage to the LPS stage. The women were asked whether in their information search they paid attention more to general information about baby food or more to information about specific brands. Women who prefer general information had babies that were significantly younger than those of women who acquired information about specific brands. This supports Howard’s suggestion that a product class concept is formed first, followed by the formation of specific brand concepts. Since information about product classes is to be found more easily in neutral sources (e.g., specialized magazines) while brand-specific information is offered mainly by suppliers, it is to be expected that during the process of habit formation, information acquisition shifts from neutral to supplier-controlled sources. This is also supported by the hypothesis that subjective risk decreases over time and with it the preference for credible, competent information sources. The corresponding hypothesis Hz2could not be supported; only when controlling for education did it almost reach significance. This is in accordance with
Habit, Information,
and Buying
Table 3: Hypotheses
With Increasing
Baby Age.
Hz, . . . Information search shifts from concept forming to concept attaining information
HZZ... Information search shifts from neutral to suppliercontrolled sources
Hz3... Product-related criteria become important
choice less
Hz4 Situational choice criteria become more important
11
on the Structure
..
of Information
Acquisition
Operationalization of Variables
Test, Level of Significance
Question if consumer “searches more general product information” or “more information about specific brands”
r-test (Y< 0.05
Sixteen information sources dichotomized into neutral and supplier-controlled
contingency NS
Importance ratings for criteria like digestibility, freshness, vitamin content Importance ratings for criteria like price, availability, special bargains
test,
Correlation (average value) r,r, = -0.29 0 < 0.05 Correlation (average value) ro = 0.22 01 < 0.05
findings indicating that the use of neutral information like product tests correlates with level of education [ 171. Hypotheses Hz3 and Hz4 imply that young mothers, who are not yet familiar with baby products, assign more importance to product-related choice criteria like digestibility, freshness, and vitamin content than do experienced mothers. On the other hand, situational criteria like price, availability, and special bargains are more important for older mothers than for young ones. This does not indicate that women become careless about their baby as time goes on. Rather, they learn the qualities of the various brands, and when the evaluation of quality is no longer a problem, they try to buy as comfortable and as economically as possible. Content and Structure of Stored Information Table 4 lists two hypotheses on content and structure of stored information. According to hypothesis H3,,anextension of the “awareness set” was expected (i.e., the set of brands that the respondents assign to the respective product class, namely, baby food). This hypothesis could be supported for none of the product classes investigated. A probable reason for this is that most women know almost all brands at a very early stage, a result of their high involvement and the modest number of brands (at most six).
Klaus Peter Kaas
12
Table 4: Hypotheses With Increasing
Baby Age
H31 The awareness set becomes larger
Hs2... Brand attitudes drift apart
on the Structure .
of Stored Information
Operationalization of Variables Question known
about
Test, Level of Significance brands
index based on the polarity of ratings on scales measuring perceived instrumentality (aggregated over all ratings and brands of a respondent)
Contingency NS
test,
Correlation r = 0.432 01 < 0.001
Hypothesis H,, concerns the formation of an “evoked set” and an “inept set” [ 131. The concept of “evoked set” plays a major role in Howard’s theory. An important effect of habit formation is that the consumer reduces the number of relevant brand alternatives-in the extreme case of brand loyalty, only one acceptable brand remains. Hence the “awareness set” encompasses two subsets: the “evoked set” of aceptable brands and the “inept set” of rejected brands (sometimes an ‘ ‘inert set’ ’ containing indifferent brands is added [ 131). The evoked set can be measured by directly asking for the acceptable brands [I, 121. Here, however, an indirect method was used, which makes the polarization of brands into “evoked set” on one side and “inept set” on the other side more visible. In order to do this, the perceived instrumentality of the various brands concerning the attributes digestibility, freshness, taste and so on was measured using the procedure proposed by Rosenberg [ 16, 181. Then an index was computed that aggregates the distances between ratings and scale means over all attributes and brands for each respondent. The correlation between the index and baby age is highly significant (i.e., with increasing habit formation brand atitudes drift apart). In the literature, many times habitual buying behavior is associated with brand loyalty [2, 201. The relationship between brand loyalty and habitual buying behavior is asymmetrical. It can be assumed that brand loyalty is a result of habit formation, but habit formation does not always have to result in brand loyalty. Habitual buying can also mean that within the evoked set the consumer always buys the brand that is temporarily cheapest or available in the right package size. Under these conditions it is difficult to establish a hypothesis about the relation between habitual
Habit,
Information,
Table 5: Hypotheses With Increasing
13
and Buying
Baby Age
on Buying Behavior .
Operationalization of Variables
Test, Level of Sianificance
HaI . . . Quantities per purchase increase
Quantity bought last purchase
Hd2... Consumers change from specialty stores to discounters
Store where last purchase was made
Tendency as expected, n of cases too low for test
Ha3... Number bargains
Bargain used at last purchase
Tendency as expected, n of cases too low for test
of special bought increases
at
Correlation r = 0.25 (Y> 0.05
behavior and brand loyalty. Also, in the present study, brand loyalty could be ascertained only with doubtful validity (by retrospective interviews). This problem is addressed in a panel study currently underway. Here only the hypotheses in Table 5 could be tested, by collecting data about brand, quantity, price, mode of supply, and store of the last purchase of baby food. As was expected, the quantity bought per purchase increases with baby age, owing to the decreased risk. Ha2 and Hd3 were supported by the data as well, but, as a restriction, only a few women buy in specialty shops or buy premium offers. Conclusion Not all hypotheses have survived the test, but in general a rather theoryconforming picture emerges, especially as far as information processing is concerned. Consumers collecting purchase experiences and forming habits reduce their information search and shift from product-specific to brand-specific and situational attributes, they buy larger quantities at a time, and they change from specialty shops to discounters. What does this imply for the answers to the questions posed at the beginning about the opportunities and handicaps of marketing? Doubtlessly, the chances of marketing are highest when consumers are young-not in years, but in product experience. In the case of substantially new products all consumers are young in this sense, in established markets only the cohorts that are added: for automobile
Klaus Peter
14
Kaas
supplies the people buying their first car, for household appliances the people moving into their first apartment, for services those who have just moved and so forth. In young cohorts, it is possible to attain what can be attained in old cohorts only at high cost or not at all: to influence the direction of the process of habit formation. To do this, marketing has to supply the right kind and amount of information at the right time and adapt the supply to the degree of habit formation reached. At the beginning, technical, neutral, general product advice in sales talks or through advertising is important. The high perceived risk has to be overcome by small package sizes, guarantees, free samples, and the like so that a brand has a chance to become a member of the evoked set. When consumers have reached the RRB stage, a different policy is necessary. The emphasis now has to be on the distribution system, sales promotion, store advertising in newspapers, and leaflet advertising. This way the situational influences on consumers’ choice can be taken advantage of [3]. Last but not least, a supplier can try to break up the habitualized behavior to induce consumers to enter a new stage of concept formation. This requires a lot of effort, a lot of noise, and especially innovations that can force consumers to revise their product class concept. New attributes, unknown or unseen to date, or new product uses can be used for this purpose. Thus in the long range a cyclical process emerges, vividly portrayed by Sheth and Raju [ 191, that is kept going not only by marketing but also by other societal forces: people become accustomed to novelities-that is the psychology of simplification. To see known things in a new light-that is the psychology of complication. It could be added: to think and act in this cycle-that is the philosophy of marketing.
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