An Individual Analysis to Cross Cultural Research

Chin Tiong Tan, National University of Singapore
Jim McCullough, Washington State University
Jeannie Teoh, National University of Singapore
ABSTRACT - It is suggested that cross cultural research examined using aggregate analysis often results in superficial or meaningless evaluations of cultural differences. A more realistic approach appears to be individual level analysis to examine how one group of individuals differs from another. This paper reports an application of the multi-attribute attitude model at the individual level on Asian consumers, to highlight the richness of individual analysis and advocates its appropriateness for ethnic research on consumer behavior.
[ to cite ]:
Chin Tiong Tan, Jim McCullough, and Jeannie Teoh (1987) ,"An Individual Analysis to Cross Cultural Research", in NA - Advances in Consumer Research Volume 14, eds. Melanie Wallendorf and Paul Anderson, Provo, UT : Association for Consumer Research, Pages: 394-397.

Advances in Consumer Research Volume 14, 1987      Pages 394-397

AN INDIVIDUAL ANALYSIS TO CROSS CULTURAL RESEARCH

Chin Tiong Tan, National University of Singapore

Jim McCullough, Washington State University

Jeannie Teoh, National University of Singapore

ABSTRACT -

It is suggested that cross cultural research examined using aggregate analysis often results in superficial or meaningless evaluations of cultural differences. A more realistic approach appears to be individual level analysis to examine how one group of individuals differs from another. This paper reports an application of the multi-attribute attitude model at the individual level on Asian consumers, to highlight the richness of individual analysis and advocates its appropriateness for ethnic research on consumer behavior.

INTRODUCTION

Studying consumer behavior in cross cultural settings has been made difficult by the failure of researchers to develop effective approaches to study consumer behavior in differing cultures. Many people would argue that we have not developed appropriate methods for the study of consumer behavior in domestic markets (c.f.: Hirschman, 1986), and this is certainly true in cross cultural situations. Whether the cross cultural research approach is humanistic or positivistic it must be designed to study the characteristics of the consumer in a manner unbiased by the culture of the researcher.

Speece (1986), suggests that consumer behavior is a function of some "underlying universal" characteristics and other "culture specific" characteristics. If this is true, as suggested by Hoover et al. (1978) and Peterson and Jolibert (1976), research approaches must be developed to handle both dimensions. Unfortunately, most cross cultural research is conducted by researchers from a foreign culture using methods, and more dangerously, instruments developed in that foreign culture. Nowhere is this more evident in the international market research area.

International cross cultural research is further hampered by the common use of nationality as a surrogate for cultural affiliation. Few consumer behaviorists would be comfortable talking about an "American" culture since we recognize a wide variety of ethnic, social class, and lifestyle subcultures in the American market. Consumer researchers, however, regularly refer to Japanese, French, Chinese, and Singaporean "cultures" as though they were well defined, homogeneous entities. This paper looks at individual analysis as an alternative to aggregation in cross cultural research.

INDIVIDUAL VERSUS AGGREGATE ANALYSIS

In the study of human behavior, social scientists have long appreciated the importance of in-depth analysis of a person's behavior. The knowledge gained from a thorough study on select individuals provides a strong foundation for extension of research into the group domain, and data gathered through individual analysis are often used to design aggregated studies.

Studying human behavior at the individual level is well accepted in-cultural anthropology and clinical psychology. In marketing, however, it is rare to find research at the individual consumer level. A major exception is products in the industrial market where potential customers are relatively few. One reason is the marketer's inherent commercial interest in group or aggregate behavior, since mass marketing involves the actions of segments or groups of consumers rather than the behavior of single individuals. Unfortunately, these approaches make it impossible to see the trees for the forest.

Most marketing research is conducted in the American domestic market where the general characteristics of individual consumers are well known and the researcher often has at least an intuitive feel for the variance in behavior of consumers. When the researcher is a member of the culture in which his study is based, his familiarity and confidence in knowledge about the people studied makes the aggregation of individuals, at least seem, acceptable. The scenario is quite different when the same researcher enters a foreign culture to study consumer behavior. He is likely to bring with him traits and biases that are peculiar to his culture, studying foreign consumers with methods and tools developed in his home culture and rather than for the foreign market.

The problem of bias is particularly serious when the study is aggregated and comparative. In an aggregated study, much information about individual differences is lost due to the need to develop statistics for comparisons of groups. The findings from such studies are easily misinterpreted when the researcher lacks an understanding of the traits and values unique to the members of the culture being studied. When comparisons are then made, spurious results are likely to occur.

CULTURAL DIFFERENCES

Cross cultural research in consumer behavior has obvious marketing applications. Most importantly, the research seeks to identify groups of consumers with similar attitudes and behaviors for segmentation purposes. This type of research is facilitated by individual analysis following by clustering or other forms of systematic aggregation. Again, it is more useful to identify similarities in segmentation patterns across cultures than to identify differences. This is facilitated by an open minded individual approach.

A sensible approach to start cross-cultural research is to first spend time studying individuals within different cultures, then, slowly progressing to comparative work when the researcher has enough familiarity with the group. Understanding these characteristics is the key to sound interpretation of cultural difference.

In cross cultural research, the focus has generally been on identifying differences between cultures rather than on seeking common ground. This has led to an interest in comparing means between groups, particularly means in demographic characteristics. Unfortunately, this misses the essence of cultural difference, the variance in structure and operation the results in a different operating environment. Rather than comparing means of variables chosen because they were found to be important in the domestic market, the researcher should attempt to study variables important to the cultural environment being studied. When identical variables are examined, not only differences in means, but differences in variance and distribution should be examined. Foreign environments may be more or less fragmented than the American market, and examining the nature of the individual in the society may give a clue to these differences which are masked in aggregate analysis.

To have meaningful interpretation of comparative research, the researcher has to be equipped with a sound knowledge of the cultures under investigation. Unfortunately, most marketers' knowledge of foreign cultures is limited and, as a result, cross cultural research has not been effective.

It is a lengthy, difficult and costly task to study consumers at the individual level. Marketers rarely invest in such effort. The approach described below provides a simpler, albeit somewhat compromised method to yield the individual level information. The methodology has popular appeal and has been adopted quite extensively. The objective is to illustrate how a method generally used for cross sectional study can be applied to study individual consumers.

AN ALTERNATIVE COMPROMISING APPROACH

The multi-attribute attitude model is commonly used in attitude research as a tool for studying the behavior patterns of groups of consumers (Fishbein & Ajzen, 1975). The model has characteristics that allow easy adaptation to cross-cultural research. Several issues regarding its usage in marketing have been discussed by Wilkie and Pessemier (1973), including its value as a tool for individual analysis.

A generalized multi-attribute model is as follows:

                    n

BI = Att =          EiIi

                  i=1

Where

Att = Attitude

BI = Behavior Intention

Ei = Evaluation of Attribute i

Ii = Importance of Attribute i

n = Number of salient attributes

In a typical study, several brands of product will be examined. For each brand, the relationship between attitude and behavior intention is examined. The studies usually focus on relationships between groups of subjects.

In most cases, data collected for an aggregated study have little value for individual level analysis. An aggregated study cannot provide answers to many questions that a researcher may ask about individual consumers. For instance, does the relationship found for the group exist for a specific individual? Is the relationship generalizable across products for a person? Is this person a group norm? If not, how does he differ from the group norm? To find answers to above, a researcher often has to investigate beyond the findings of an aggregated study.

In the application of the multi-attribute attitude model, most studies use limited numbers of products and brands, ruling out individual level analysis. If the same data are to be used to investigate attitude/behavioral intention relationships at the individual level, the results will not be meaningful due to limited number of data points in the analysis. The following example on one product with three brands is sufficient to illustrate differences in the data structures for aggregated and individual analyses.

TABLE

Assuming interest is to study relationships between attitudes and behavioral intentions, the researcher will correlate BI with Att across subjects for each brand aggregating across consumers. BI/Att relationships across brands for each subject are examined for individual analysis. It is clear that while the data in most studies are good for the aggregated analysis, they are inadequate for individual level analysis.

METHOD

In this study, individual level analysis was used to cover a wide range of product categories. A total of 132 products were studied, including automobiles, watches, jeans, toothpaste, fast food, shampoo, departmental stores, sports shoes, beer, pens, color televisions, and calculators. For each product, three brands were examined. To simplify the task of filling in the questionnaire, four standardized attributes were used, i.e., price, quality, brand /store image, an d availability/accessibility. A questionnaire was used for the study. The total sample was 129 subjects representing a cross section of the Singaporean population. This research was conducted as part of another larger three-month panel study of Singapore consumers.

ANALYSIS

The individual level analysis was performed to accomplish the following objectives:

1. to examine individual attitude patterns for the population.

2. to categorize individuals based on individual attitude patterns using attribute saliency as the categorizing variable.

3. to describe market segments based on attitude Patterns.

For each subject in the sample, analysis was performed regressing attitudes with 81. The four attitude categories in the model were not summed, but were treated as independent variables in the analysis. This analysis was conducted for each of the subjects (n=129) in the sample population. In each analysis, there were 36 data points (12 products x 3 brands). The stepwise option of multiple regression analysis was adopted.

Looking at results of individual regressions, greater insights of individual consumers can be gained. Much of the information that he is able to extract from individual analysis is not available from aggregated analysis. For example, using the psychographic and demographic profiles developed in McCullough and Tan (1986) the following individual descriptions can be developed:

1. The extent one's attitude is related to BI. Among the 129 subjects, R ranged from .11 to individual subjects are presented for illustration:

Subject A: R2 of .47. Price, availability and image entered the equation in that order. Based on his psychographic and demographic profiles, he is above average on education and income. He holds more western values than the average Singaporean.

Subject B: R2 of .57. Availability was the only variable in his equation. He is convenience oriented with strong western values. His age is younger than the average.

Subject C: R2 of .12. Price was the only important factor. With strong Asian and family values he is inclined to be influenced by external factors in purchasing with a low effect of his own attitude structure.

2. The number of attributes are consistently used in buying. From the above, it is obvious that some subjects are like A, who use several attributes in buying, while there are others like B and C, who consistently rely on a single attribute.

Using psychographic and demographic variables a discriminant analysis was performed to classify the subjects into segments based on their attribute saliency. The function developed correctly categorized 66 percent of the subjects into the four groups as shown below:

TABLE

3. Saliency of attributes for a person across product types. From above, one notices that availability is consistently important to B while price is important to C.

Individual level analysis can be easily extended to cross-sectional analysis, if necessary. Aggregate data can be generated by grouping individuals. The following are generated from 129 subject regressions:

The average R2 for the sample was .36

A large majority (55 percent) of subjects used only one attribute, and 30 percent relied on two attributes.

Saliency of attributes tended to differ among subjects. The breakdown of subjects' most salient attributes were:

price--34 percent

quality--28 percent

image--13 percent

availability--25 percent

For researchers interested in aggregated analysis, the above aggregated data can be analyzed with other demographic and psychological variables. Readers can refer to Tan and McCullough (1986} for detail.

CONCLUSION

In performing cross-cultural research, the researcher should possess a sound knowledge of the consumer environment in which he is working. This requires a thorough understanding of the consumer at the individual level. Unfortunately, obtaining richness of understanding through individual analysis or humanistic inquiry is expensive. This paper has presented an initial look at methodology to provide this information within the context of conventionally accepted marketing research.

As marketing becomes more international and cross cultural business activity becomes more sophisticated, understanding the foreign environment will become increasingly important. In depth understanding of the foreign consumer and his environment appears to be the only feasible approach to success.

REFERENCES

Fishbein, M., and I. Ajzen (1975), Belief, Attitude; Intention and Behavior: An Introduction to Theory and Research, Reading, Massachusetts: Addison-Wesley.

Hirschman, E.C. (1986), "Humanistic Inquiry in Marketing Research: Philosophy, Method, and Criteria", Journal of Marketing Research, 23 (August), 237-49.

Hoover, R.J., R.T. Green, and J. Saegert (1978), "A Cross National Study of Perceived Risk, Journal of Marketing 42, 103-138.

McCullough, J.M., and C.T. Tan, (1986,, "Are the Chinese really Chinese?", Advances in Consumer Research, 13.

Peterson, R.A., and A.J.P. Jolibert (1976), "A Cross-National Investigation of Price and Brand as Determinants of Perceived Product Quality", Journal of Applied Psychology 61, 533-536.

Speece, M. (1986), "The Role of Culture in Patterns of Store Choice", working paper, University of Washington.

Tan, C.T., J. Tech, and J. McCullough (1986), "Ethnic Research in Consumer Behavior: An Individual Bevel Analysis Approach", Proceedings: Academy for International Business Southeast Asian Regional Conference. (in Press)

Wilkie, W.L., and E. Pessemier (1973), "Issues in Marketing Use of Multi-Attribute Models", Journal of Marketing Research, (November), 428-441.

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