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The prospective buyer of consumer durables
85
Book reviews L. de Jonge, W.M. Oppedijk Van Veen The prospective buyer of consumer durables Veldhoven (The Netherlands), 1982 Marketers have often acknowledged the special status of durable goods in the context of consumer behavior, but the literature has provided woefully little analysis of the demand for durable goods. De Jonge and Oppedijk van Veen have made a credible attempt to add to this branch of the literature, presenting an empirical analysis of the demand for television sets and cars. The work is organized into four parts: (1) literature review and presentation of a conceptual model, (2) operationalisation of the model, (3) empirical analysis of consumer behavior, and a concluding section (4) which is partly a summary and partly a proposal for predictively validating the empirical models of part (3). In part 1, the authors argue convincingly that durable goods decisions are different from non-durable goods decisions in a number of ways. Durable goods are not completely divisible and are, consequently, ‘lumpy’ as compared physically to non-durables. Durables tend to be expensive relative to non-durables; thus, because the choice of any single durable good commits a sizeable portion of the consumer’s financial resources to its purchase, consumption decisions about durables tend to be very salient to the consumer. Finally, by definition, durable goods are distinct from non-durables because they depreciate over an extended period of time. The authors develop a conceptual framework in an attempt to integrate some psychological and economic determinants of demand. The variables selected describe the situation and the anticipation of the consumer and Intern. J. of Research North-Holland
0167-8116/84/$3.00
in Marketing
Q 1984,
Elsevier
1 (1984)
Science
85-92
Publishers
are organized in a manner reminiscent of Hughes’ approach to demand analysis (Hughes 1971). Because the authors focus on the process of consumer decision-making, their modeling approach is decidedly more in the spirit of applied psychology than applied economics. The authors’ decision not to apply economic theory is based on the rationality argument, viz. that the consumer cannot be presumed to have either complete and perfect information, or stable preferences. In adopting an economic approach one is saddled on the one hand with some properties of the individual consumer which may not be entirely realistic, but, on the other hand, one may benefit from a powerful and logically consistent method of analysis. It is the latter issue which is not acknowledged by De Jonge and Oppedijk van Veen in choosing their psychology-based modeling approach. In this vein, two specific points addressing the rationale for the modeling approach strike me as important. First, one advantage of an economics-based modeling approach is that there is a well-developed literature in applied economics pertaining to the analysis of demand for durable goods which is consistent with the individual utility-maximization hypothesis. This literature includes the flow, stock, and stock adjustment models (see Huang 1977). Furthermore, as the authors state themselves (p. 27) “. . . there is a general lack of empirical research at the generic product level . . . ” in the psychology-based buyer behavior literature in marketing. The authors consider consumer decisions at the generic level as most appropriate for the analysis of consumer demand for durables. What the authors fail to say is that the economic analysis is applied at the generic product level. To summarize the rationale for the modeling approach selected
B.V. (North-Holland)
86
Book
is more convincing when the researcher can select a modeling approach which is consistent with some specific research objectives rather than the result of eliminating one or more theory foundations from consideration because of their deficiencies. Obviously, each theoretical tradition will be deficient in at least some respects. In the present case, for example, one could say that the authors have selected a discrete choice modeling approach which permits one to estimate a purchase probability but does not permit an analysis of how consumers allocate their scarce resources to the purchase of durables. Part 11 of the book presents a detailed discussion of the authors’ attempts to measure individual household purchase behavior. From the results of a pilot study on 75 households the authors were able to determine that there were no major inconsistencies between the responses of husbands and wives and that a mail survey approach rather than a personal interview approach would be feasible. The pilot study was useful in clarifying other issues regarding the operationalization of key variables and in determining the appropriate sequencing of questions in the questionnaire. The sample which the authors used for their main study was drawn from the Aswood Household Panel in The Netherlands. The sample size was comprised of 2600 housewives, who acted as spokeswomen for their households. Sensitive to the well-known problems of non-response in mail surveys, the authors attempted to minimize response bias by distinguishing between life members and temporary members of the panel. Three measurements were conducted to assess changes in the situation and anticipation variables, and response rates were well over 90% in two of the three measurements and 89.7% in the remaining measurement. The authors devote an entire chapter (Chapter 6) to an explanation of the tests they conducted to detect individual response errors and the procedure they enacted to correct these errors.
reviews
In Part 111, the authors’ empirical analysis begins with a surprisingly elementary discussion of alternative estimation procedures available to them. The basic issue is to apply a methodology which permits them to derive empirical weights of the independent variables in their three variable categories, namely, situation, anticipation, and changes in situation or anticipation (between measurements) when relating these variables to a dichotomous purchase behavior variable (dependent variable). Before conducting the estimation, the authors segmented the sample into four groups, on intuitive grounds, and present empirical evidence that the segments differ from each other in terms of levels of the explanatory variables. As there were initially over 200 explanatory variables, these were reduced by means of a correlational analysis for each of the four products studied. The specification of the purchase behavior model for each product was determined empirically by applying step-wise linear regression to the reduced set of explanatory variables. To test the predictive power of the regression specifications, the authors used the same specifications in a two-group discriminant analysis for each product. The authors observe at this point that the empirical results do not strongly confirm their conceptual model, because (1) the regression analyses exhibit low measures of goodness-of-fit and (2) the discriminant analysis predicts only non-buyers well. Faced with such a situation the researcher typically has a stark choice to make. He can either reject his conceptual model, and start the research over; or he can reject something about the empirical aspects of the study (the data, the estimation procedure, etc.) In this case, the authors elected the second. option and proposed a new methodology. Before considering their new methodology, one wonders why they used the methodologies of ordinary least squares and discriminant analysis in the first place. Regressing a binary
Book
dependent on intervally scaled explanatory variables does not permit one to use the normal theory in testing the significance of parameters, and certainly other estimation procedures exist which are more appropriate for binary data (such as logit analysis, cf. McFadden 1973). The disproportionately high representation of non-buyers (from 88% to 94% of the sample, depending on the product) should also make one very reluctant to use discriminant analysis which will naturally classify a high proportion of the small group (buyers) as members of the larger group (non-buyers). (On this point, see the classic article by Morrison 1969.) The new methodology which the authors present is based upon a new measure of classification which they propose, and which they call the Standard Discriminatory Success (SDS). The SDS is obtained from a two-way classification table of actual versus predicted margins which has been standardized by the actual marginal absolute frequencies of each sub-group. An example might help explain the measure. Consider the following 2 x 2 classification table: Predicted Non-buyers
Buyers
Non-buyers Actual Buyers
wj
1::
Now, assume that we have drawn a sample of buyers and non-buyers and have classified them (using discriminant analysis, for example) as follows: Predicted Non-buyers Non-buyers
400
Actual
Buyers k
100
13 15
4 35
0.30
500
0.20
0.80 Buyers
2
50 0.70
reviews
87
Standardizing the cell frequencies by the marginal frequencies of actual buyers and non-buyers yields the proportions in the lower right hand corner of each cell. The authors proceed by constructing a composite estimate, PA, of the proportion of correctly classified observations as the simple average of the proportions in cells 1 and 4. That is, in this case (0.8 + 0.7)+ = 0.75. This, of course, assumes that the buyer category sizes are roughly equal. Obviously, in the illustrative example, reallocation of five observations between cell 2 and cell 1 will have much less effect on PA than a reallocation of five observations between cells 3 and 4. Similarly, the predicted marginals which the authors construct on the standardized table must assume that the category sizes are similar. In the illustration above i(0.8 + 0.3) = 0.55 which is obviously very different from the real marginal (400 + 15)/550 = 0.75 for non-buyers. The authors devote one chapter to the description of their new method of exploratory analysis of discrete observations, the index method. The authors propose the method to help resolve four common empirical problems, namely, population heterogeneity, specification of the functional form of the relationship among the variables, inconsistent scales of measurement on the variables (nominal, ordinal and interval), and missing values on some variables for some observations. The index method consists of three elements: a classification function, a classification procedure and the SDS. The classification procedure essentially is an ad hoc approach to grouping observations on the dependent variable (0 = non-buyer, 1 = buyer) corresponding to subjectively determined discrete intervals on each explanatory variable. The objective in this procedure is to try to detect instances of non-linear relationships. The predictive power of the classification is assessed by the SDS. The authors provide empirical support for the index method as compared to the predict-
88
Book
ions obtained from discriminant analysis, as measured by SDS, over all four product contexts. Unfortunately, the authors do not discuss the relative weights of the so-called explanatory variables, other than to record the contribution of each explanatory variable to the SDS. That is, the reader is given a summary of the empirical work in Part IV which merely argues that the conceptual framework of Chapter 2 is confirmed on grounds of high predictive power. However, there is very little that the reader can take from the empirical analysis as a general substantive result. Thus, one does not know, for example, whether anticipation variables are more important for explaining the demand for black and white TVs or for used cars, or whether situation change variables are more important for describing demand for new cars or for color TVs. In summary, De Jonge and Oppedijk van Veen have succeeded in presenting to the marketing literature a base of reference for future research addressing the special status which durable goods deserve in buyer behavior research. The authors have also communicated to the marketing research audience that research in this area is frought with empirical difficulties. One hopes that future work will attempt to refine the conceptual and empirical bases presented in this book. David A. Gautschi INSEAD Fontainebleau, France References Huang, D. (1977). Consumer purchase of durables. In: R. Ferber (ed.), Selected aspects of consumer behavior. Washington, DC: National Science Foundation. Hughes, G.D. (1973), Demand analysis for marketing decisions. Homewood, III.: R.D. Irwin. McFadden, D. (1973) Conditional logit analysis of qualitative choice behavior. In: P. Zarembka (ed.), Frontiers in econometrics, 105-142. New York: Academic Press. Morrison, D. (1969) On the interpretation of discrirninant analysis. Journal of Marketing Research 6, (May 1969) 156-163.
reviews
I. Hagg, J. Johansson (eds.) Fiiretag i niitverk SNS, Stockholm, 1982 K.-O. Hammarkvist, H. Hakansson, Mattsson Marknadsftiring f2ir konkurrenskraft Liber, Malmo, 1982
L.-G.
To everybody having been taught traditional micro-economic theory it is natural to see business firms as independent units competing with each other on markets for homogeneous or slightly differentiated products. They sell their products to independent wellinformed buyers. These buyers are usually many. In a similar way, textbooks on marketing management have made it a habit to see marketing problems as problems of sellers in finding an optimal use of a number of marketing means, i.e. to optimize the marketing mix. Marketing management becomes a matter of choosing some environment (market) and then of trying to adapt to that environment by manipulation of a number of internal decision variables. Interfirm relations are managed by impersonal market mechanisms or sometimes by business managers involved in suspect collusion activities. There are, however, other ways of perceiving the real world of marketing activities. Two Swedish books depart from such a different perspective. The books are: Fiiretag i ntituerk (‘Business firms in networks’), ed. by I. Hagg and J. Johansson and Marknadsfiiring fijr Konkurrenskraft (‘Marketing for competitive strength’) by K.-O. Hammarkvist, H. Hakansson and L.-G. Mattsson. To some extent, the same group of people has been involved in writing both books. The books mainly analyze problems and possibilities of Swedish firms exporting producergoods. It is the choice of perspective in the books that makes them of more general interest. The main characteristics of that perspective are the following.
Book reviews L. de Jonge, W.M. Oppedijk Van Veen The prospective buyer of consumer durables Veldhoven (The Netherlands), 1982 Marketers have often acknowledged the special status of durable goods in the context of consumer behavior, but the literature has provided woefully little analysis of the demand for durable goods. De Jonge and Oppedijk van Veen have made a credible attempt to add to this branch of the literature, presenting an empirical analysis of the demand for television sets and cars. The work is organized into four parts: (1) literature review and presentation of a conceptual model, (2) operationalisation of the model, (3) empirical analysis of consumer behavior, and a concluding section (4) which is partly a summary and partly a proposal for predictively validating the empirical models of part (3). In part 1, the authors argue convincingly that durable goods decisions are different from non-durable goods decisions in a number of ways. Durable goods are not completely divisible and are, consequently, ‘lumpy’ as compared physically to non-durables. Durables tend to be expensive relative to non-durables; thus, because the choice of any single durable good commits a sizeable portion of the consumer’s financial resources to its purchase, consumption decisions about durables tend to be very salient to the consumer. Finally, by definition, durable goods are distinct from non-durables because they depreciate over an extended period of time. The authors develop a conceptual framework in an attempt to integrate some psychological and economic determinants of demand. The variables selected describe the situation and the anticipation of the consumer and Intern. J. of Research North-Holland
0167-8116/84/$3.00
in Marketing
Q 1984,
Elsevier
1 (1984)
Science
85-92
Publishers
are organized in a manner reminiscent of Hughes’ approach to demand analysis (Hughes 1971). Because the authors focus on the process of consumer decision-making, their modeling approach is decidedly more in the spirit of applied psychology than applied economics. The authors’ decision not to apply economic theory is based on the rationality argument, viz. that the consumer cannot be presumed to have either complete and perfect information, or stable preferences. In adopting an economic approach one is saddled on the one hand with some properties of the individual consumer which may not be entirely realistic, but, on the other hand, one may benefit from a powerful and logically consistent method of analysis. It is the latter issue which is not acknowledged by De Jonge and Oppedijk van Veen in choosing their psychology-based modeling approach. In this vein, two specific points addressing the rationale for the modeling approach strike me as important. First, one advantage of an economics-based modeling approach is that there is a well-developed literature in applied economics pertaining to the analysis of demand for durable goods which is consistent with the individual utility-maximization hypothesis. This literature includes the flow, stock, and stock adjustment models (see Huang 1977). Furthermore, as the authors state themselves (p. 27) “. . . there is a general lack of empirical research at the generic product level . . . ” in the psychology-based buyer behavior literature in marketing. The authors consider consumer decisions at the generic level as most appropriate for the analysis of consumer demand for durables. What the authors fail to say is that the economic analysis is applied at the generic product level. To summarize the rationale for the modeling approach selected
B.V. (North-Holland)
86
Book
is more convincing when the researcher can select a modeling approach which is consistent with some specific research objectives rather than the result of eliminating one or more theory foundations from consideration because of their deficiencies. Obviously, each theoretical tradition will be deficient in at least some respects. In the present case, for example, one could say that the authors have selected a discrete choice modeling approach which permits one to estimate a purchase probability but does not permit an analysis of how consumers allocate their scarce resources to the purchase of durables. Part 11 of the book presents a detailed discussion of the authors’ attempts to measure individual household purchase behavior. From the results of a pilot study on 75 households the authors were able to determine that there were no major inconsistencies between the responses of husbands and wives and that a mail survey approach rather than a personal interview approach would be feasible. The pilot study was useful in clarifying other issues regarding the operationalization of key variables and in determining the appropriate sequencing of questions in the questionnaire. The sample which the authors used for their main study was drawn from the Aswood Household Panel in The Netherlands. The sample size was comprised of 2600 housewives, who acted as spokeswomen for their households. Sensitive to the well-known problems of non-response in mail surveys, the authors attempted to minimize response bias by distinguishing between life members and temporary members of the panel. Three measurements were conducted to assess changes in the situation and anticipation variables, and response rates were well over 90% in two of the three measurements and 89.7% in the remaining measurement. The authors devote an entire chapter (Chapter 6) to an explanation of the tests they conducted to detect individual response errors and the procedure they enacted to correct these errors.
reviews
In Part 111, the authors’ empirical analysis begins with a surprisingly elementary discussion of alternative estimation procedures available to them. The basic issue is to apply a methodology which permits them to derive empirical weights of the independent variables in their three variable categories, namely, situation, anticipation, and changes in situation or anticipation (between measurements) when relating these variables to a dichotomous purchase behavior variable (dependent variable). Before conducting the estimation, the authors segmented the sample into four groups, on intuitive grounds, and present empirical evidence that the segments differ from each other in terms of levels of the explanatory variables. As there were initially over 200 explanatory variables, these were reduced by means of a correlational analysis for each of the four products studied. The specification of the purchase behavior model for each product was determined empirically by applying step-wise linear regression to the reduced set of explanatory variables. To test the predictive power of the regression specifications, the authors used the same specifications in a two-group discriminant analysis for each product. The authors observe at this point that the empirical results do not strongly confirm their conceptual model, because (1) the regression analyses exhibit low measures of goodness-of-fit and (2) the discriminant analysis predicts only non-buyers well. Faced with such a situation the researcher typically has a stark choice to make. He can either reject his conceptual model, and start the research over; or he can reject something about the empirical aspects of the study (the data, the estimation procedure, etc.) In this case, the authors elected the second. option and proposed a new methodology. Before considering their new methodology, one wonders why they used the methodologies of ordinary least squares and discriminant analysis in the first place. Regressing a binary
Book
dependent on intervally scaled explanatory variables does not permit one to use the normal theory in testing the significance of parameters, and certainly other estimation procedures exist which are more appropriate for binary data (such as logit analysis, cf. McFadden 1973). The disproportionately high representation of non-buyers (from 88% to 94% of the sample, depending on the product) should also make one very reluctant to use discriminant analysis which will naturally classify a high proportion of the small group (buyers) as members of the larger group (non-buyers). (On this point, see the classic article by Morrison 1969.) The new methodology which the authors present is based upon a new measure of classification which they propose, and which they call the Standard Discriminatory Success (SDS). The SDS is obtained from a two-way classification table of actual versus predicted margins which has been standardized by the actual marginal absolute frequencies of each sub-group. An example might help explain the measure. Consider the following 2 x 2 classification table: Predicted Non-buyers
Buyers
Non-buyers Actual Buyers
wj
1::
Now, assume that we have drawn a sample of buyers and non-buyers and have classified them (using discriminant analysis, for example) as follows: Predicted Non-buyers Non-buyers
400
Actual
Buyers k
100
13 15
4 35
0.30
500
0.20
0.80 Buyers
2
50 0.70
reviews
87
Standardizing the cell frequencies by the marginal frequencies of actual buyers and non-buyers yields the proportions in the lower right hand corner of each cell. The authors proceed by constructing a composite estimate, PA, of the proportion of correctly classified observations as the simple average of the proportions in cells 1 and 4. That is, in this case (0.8 + 0.7)+ = 0.75. This, of course, assumes that the buyer category sizes are roughly equal. Obviously, in the illustrative example, reallocation of five observations between cell 2 and cell 1 will have much less effect on PA than a reallocation of five observations between cells 3 and 4. Similarly, the predicted marginals which the authors construct on the standardized table must assume that the category sizes are similar. In the illustration above i(0.8 + 0.3) = 0.55 which is obviously very different from the real marginal (400 + 15)/550 = 0.75 for non-buyers. The authors devote one chapter to the description of their new method of exploratory analysis of discrete observations, the index method. The authors propose the method to help resolve four common empirical problems, namely, population heterogeneity, specification of the functional form of the relationship among the variables, inconsistent scales of measurement on the variables (nominal, ordinal and interval), and missing values on some variables for some observations. The index method consists of three elements: a classification function, a classification procedure and the SDS. The classification procedure essentially is an ad hoc approach to grouping observations on the dependent variable (0 = non-buyer, 1 = buyer) corresponding to subjectively determined discrete intervals on each explanatory variable. The objective in this procedure is to try to detect instances of non-linear relationships. The predictive power of the classification is assessed by the SDS. The authors provide empirical support for the index method as compared to the predict-
88
Book
ions obtained from discriminant analysis, as measured by SDS, over all four product contexts. Unfortunately, the authors do not discuss the relative weights of the so-called explanatory variables, other than to record the contribution of each explanatory variable to the SDS. That is, the reader is given a summary of the empirical work in Part IV which merely argues that the conceptual framework of Chapter 2 is confirmed on grounds of high predictive power. However, there is very little that the reader can take from the empirical analysis as a general substantive result. Thus, one does not know, for example, whether anticipation variables are more important for explaining the demand for black and white TVs or for used cars, or whether situation change variables are more important for describing demand for new cars or for color TVs. In summary, De Jonge and Oppedijk van Veen have succeeded in presenting to the marketing literature a base of reference for future research addressing the special status which durable goods deserve in buyer behavior research. The authors have also communicated to the marketing research audience that research in this area is frought with empirical difficulties. One hopes that future work will attempt to refine the conceptual and empirical bases presented in this book. David A. Gautschi INSEAD Fontainebleau, France References Huang, D. (1977). Consumer purchase of durables. In: R. Ferber (ed.), Selected aspects of consumer behavior. Washington, DC: National Science Foundation. Hughes, G.D. (1973), Demand analysis for marketing decisions. Homewood, III.: R.D. Irwin. McFadden, D. (1973) Conditional logit analysis of qualitative choice behavior. In: P. Zarembka (ed.), Frontiers in econometrics, 105-142. New York: Academic Press. Morrison, D. (1969) On the interpretation of discrirninant analysis. Journal of Marketing Research 6, (May 1969) 156-163.
reviews
I. Hagg, J. Johansson (eds.) Fiiretag i niitverk SNS, Stockholm, 1982 K.-O. Hammarkvist, H. Hakansson, Mattsson Marknadsftiring f2ir konkurrenskraft Liber, Malmo, 1982
L.-G.
To everybody having been taught traditional micro-economic theory it is natural to see business firms as independent units competing with each other on markets for homogeneous or slightly differentiated products. They sell their products to independent wellinformed buyers. These buyers are usually many. In a similar way, textbooks on marketing management have made it a habit to see marketing problems as problems of sellers in finding an optimal use of a number of marketing means, i.e. to optimize the marketing mix. Marketing management becomes a matter of choosing some environment (market) and then of trying to adapt to that environment by manipulation of a number of internal decision variables. Interfirm relations are managed by impersonal market mechanisms or sometimes by business managers involved in suspect collusion activities. There are, however, other ways of perceiving the real world of marketing activities. Two Swedish books depart from such a different perspective. The books are: Fiiretag i ntituerk (‘Business firms in networks’), ed. by I. Hagg and J. Johansson and Marknadsfiiring fijr Konkurrenskraft (‘Marketing for competitive strength’) by K.-O. Hammarkvist, H. Hakansson and L.-G. Mattsson. To some extent, the same group of people has been involved in writing both books. The books mainly analyze problems and possibilities of Swedish firms exporting producergoods. It is the choice of perspective in the books that makes them of more general interest. The main characteristics of that perspective are the following.