Do Geographic Subcultures Vary Culturally?


James W. Gentry, Patriya Tansuhaj, L. Lee Manzer, and Joby John (1988) ,"Do Geographic Subcultures Vary Culturally?", in NA - Advances in Consumer Research Volume 15, eds. Micheal J. Houston, Provo, UT : Association for Consumer Research, Pages: 411-417.

Advances in Consumer Research Volume 15, 1988      Pages 411-417


James W. Gentry, University of Wisconsin-Madison

Patriya Tansuhaj, Washington State University

L. Lee Manzer, Oklahoma State University

Joby John, Bentley College

[The authors would like to thank Tom Gracia for his help in data entry and data analysis. Also, the authors would like to thank the Office of Business and Economic Research at Oklahoma State University for their monetary support of the project.]


One continuing debate characterizing the study of consumer behavior revolves around the notion of regional differences in consumption patterns. Perhaps the strongest argument supporting the regional variation concept is offered by Hawkins, Roupe, and Coney (1980), who hypothesized that geographic subcultures can be an important determinant of both consumption and nonconsumption behaviors. They proposed a model of the geographic subculture influence on consumption (shown in Figure 1) and have reported the results of a study designed to investigate regional variation in the preparation and consumption of coffee. The findings of the research suggest that while the percentage of respondents drinking coffee in various regions (East, Midwest, South, and West) is fairly similar (varying from 63 percent in the East to 55 percent in the West), there are radical differences in how coffee is prepared and consumed. For example, the majority (54%) of the respondents in the East used sweeteners and creaming agents in their coffee while few (24%) of their Western counterparts did likewise. Regional variations were also identified with respect to the use of electric vs. nonelectric percolators in the preparation of coffee, the preference of cups vs. mugs from which to drink the beverage, and the relative preferences for drinking their coffee black. Hawkins, Roupe and Coney (1980) conclude that, while the geographic subcultures are changing over time, the regions do not appear to be losing their distinctive flavor.

Other support for a regional analysis of consumption patterns has been found. Cleaver (1982) found regional differences in grocery purchasing. Dardis et al. (1981) reported significant differences in recreational expenditures by geographical area. Wells and Reynolds (1979) reported significant regional differences in life styles. For example, they supported the common stereotypes of the South being more traditional, the West as being relatively liberal, and the East as being cosmopolitan and innovative.

Perhaps the strongest call for marketers to consider geographic subcultures was Garreau's (1981) book, The Nine Nations of North America. The vivid descriptions of various areas of the United States helped stimulate efforts by firms such as Management Horizon and Ogilvy and Mather (Whalen 1983b, 1983c; Marketing News 1984) to promote geographic segmentation. Apparently, this promotion has been successful as firms such as Campbell's Soup (Business Week 1986) are developing regional advertising approaches for products which have been typically promoted using a single national campaign.

The basis for the subdivision of the United States has been investigated empirically, and Garreau's (1981) model has not been supported (Gentry 1986; Kahle 1986). Further, Lesser and Hughes (1986) have found that segmentation bases are generalizable across various geographical regions in the United States.

The primary questions to be investigated in this study are whether geographic subcultures differ in their consumption patterns (more specifically, in their willingness to try new products and the level of risk associated with different products) and if the regions also differ in terms of their underlying cultural beliefs.


Thirty years ago strong demographic differences existed across different regions of the United States. While differences still exist, the general pattern is toward homogenization. For example, while the South and Southwest regions of the United States have traditionally been younger, poorer, and less educated, both areas are "aging" and increasing in income and education levels at a more rapid rate than the rest of the country (Gentry and Grove 1981). Exceptions to this general homogenization trend relate to the distribution of Hispanics throughout the U.S., religious variation, and (probably related to religious variation) household size.

It would appear that regional differences in consumption, to the extent that they exist and to the extent that they are due to income differences, will gradually disappear unless they are due to other causes. Garreau (1981) based his determination of the boundaries of his nine nations on anecdotal evidence, stating that he was uncertain as to the exact criteria used in the development of his maps. According to his speech to the AMA's Third Research Conference (as reported in Whalen 1983a), he was later able to specify better the type of criteria used in developing his model: economic, social, cultural, political, topographic, and natural resources. These criteria relate closely to the physical landscape and psychological landscape criteria incorporated in the Hawkins, Roupe and Coney (1980) model.

More recently, Kahle (1986) pointed out that the basis for geographic segmentation is, in part, the assumption that there are geographic differences in values. He investigated differences in values such as self-respect, self- fulfillment, security, fun and enjoyment, warm relationships, sense of accomplishment, and sense of belonging. Regional differences in values were found, though Garreau's breakdown of areas was not found to coincide with many of the differences.

We will look at other cultural variables and see if geographic differences exist. Specifically, we will investigate the individual's fate orientation, his or her religious commitment, and the ties to their traditional cultural values. Fatalism or fate-orientation may be defined as the belief that all events are predetermined by fate and therefore unalterable by man. The concept is similar to Henry's (1976) value orientation with respect to man's relation to nature, classified as subjugated by, in harmony with, or mastery over nature. People with a relatively high degree of fatalism would be similar to those who believe that man must simply take events as they come, instead of being able to plan, avoid, or master the environment. Varying levels of fate orientation would seem to be explained in large part by differences in religious background. Hirschman (1983b) cites literature indicating that Catholics are relatively fatalistic (Callahan 1963; Gleason 1969), that Protestants are lower in fatalism (Anderson 1970; Greeley 1977), and that Jews are high in terms of internal locus of control (Patai 1977). [Locus of control scales have been used frequently to measure "fatalism" (Aldrich, Lipman, and Goldman 1975; Surlin 1976).] Hoover, Green, and Saegert (1978) proposed that fatalism may explain cross-cultural differences found in levels of perceived risk.



Just as fate orientation may vary across the United States due to the distribution of various religious groups, the level of religious commitment may also vary. Recent studies by Hirschman (1981a, 1981b, 1982a, 1982b, 1982c, 1982d, 1983a, 1983b; 1985) have found religious beliefs to play an important role in the formation of the consumer's values, attitudes and behavior.

In addition, we considered one's adherence to traditional cultural values. Such adherence can be expected to relate directly with perceived risk associated with new products and inversely with their willingness to try those products.


The study will investigate:

1. whether differences exist in cultural values (fate orientation, religious commitment, and adherence to culture) across geographical regions;

2. whether differences exist in related consumer behavior variables(perceived risk and willingness to try new products); and

3. whether differences in cultural values help explain differences in the consumer uncertainty variables.

Specifically, to the extent that differences in cultural values exist, we hypothesize that those areas higher in fate orientation, in religiosity, and in adherence to cultural values will show higher levels of perceived risk associated with new products and less willingness to try those products.


A questionnaire was distributed to college students in four areas: West (Washington), North Central (Wisconsin), Southwest (Oklahoma), and Northeast (Massachusetts). The respective sample sizes were 67, 98, 189, and 135. The convenience sample of college students was intended to make the overall sample relative homogeneous in terms of socio-economic characteristics.


Fate Orientation. While many studies have used Rotter's (1977) Locus of Control instrument to measure the fatalism construct (Aldrich, Lipman, and Goldman 1975; Surlin 1976), some researchers (Aldrich, Lipman, and Goldman 1975; Chamberlain 1976; Farris and Glenn 1976) developed their own measures. We used three measures: a four-item fatalism scale developed by Farris and Glenn (1976), a six-item Locus of Control scale that Lumpkin (1985) reduced from Rotter's (1966) 29-item scale, and a two-item product-specific scale which we developed. The scales are shown in Figure 2.



Religious Commitment. The respondents were also asked a series of questions as to the role that religion had played in their lives. Hirschman (1981a) measured commitment using a five-point "Very Strong" to "Very Weak" scale. We used the four-item scale developed by Putney and Middleton (1961) to measure the current influence of their religion on their lives. In addition, we added one item which deals with the role that religion had in their upbringing.

Cultural Adherence. We created a five-item scale to determine the respondents' adherence to his/her culture (like to conform to traditional value; culture is worth preserving; young people should adopt new values; want loved ones to behave consistently with tradition; people should not mix other cultural values with their own).


Novelty Seeking. We used the approach taken by Hirschman (1983a), in which she asked respondents how willing they are to try something new. The responses were recorded on a four-point scale anchored by "Very Willing" and "Not at All Willing." We used most of the 15 consumption areas which she used: dance styles, places to shop, fashion clothes, books, magazines, food, restaurants, and hair styles. Due to confusion found earlier in a cross- cultural study using a similar instrument (John, Tansuhaj, Manzer, and Gentry 1986), we dropped home furnishings, movies, political ideas, religious ideas, transportation, and sports. Several respondents gave written and oral feedback that those stimuli elicited a variety of images. Also, the variance in the ratings of those stimuli was greater. In their place, we added toothpaste, cameras, watches, motorcycles, and computers.

Perceived Risk. We used a perceived risk measure similar to the one used by Hoover, Green,- and Saegert (1978). This measure asked how much risk (a great deal, some, little, no) is associated with the use of a product. The risk questions were asked for the same products listed above.


The analysis took three stages: (1) an investigation of the measures themselves; (2) an investigation of regional differences in the perception of uncertainty in the marketplace and in fate-orientation, religious commitment, and cultural adherence; and (3) an investigation of the relationship between the cultural values and uncertainty in the marketplace.


At points it will be more efficient to use unidimensional rather than multidimensional measures in the analysis. Consequently, Cronbach alphas were calculated for the following constructs: Willingness to buy (across the 13 products) .71; risk associated with the products (across the products) .78; Farris and Glenn's (1976) four-item fatalism scale .56; the six-item Lumpkin (1985) locus of control measure .12; the five-item religious commitment measure .92, and the five-item cultural adherence measure .36. The bias toward larger scales is evident in these reliabilities. The cultural adherence measure shows only marginal reliability, while the locus of control measures shows none at all. Lumpkin (1985) found an alpha of .68, but our findings show much less support.



When factor analyses were conducted on the constructs, the fatalism scale and the religious commitment scale were single dimensions as indicated by a scree analysis. The cultural adherence and locus of control measures yielded two factors. Thus, our experience would indicate that those seeking a short locus of control scale for use in survey research should probably not use the Lumpkin (1985) measure. Factor analyses of the willingness to try new products measure and the risk measures each found four groupings of products: fashion- related or symbolic products (fashion clothes, hair styles, dance styles); reading material (books and magazines); entertainment (food and entertainment places); and technological products (cameras, watches, motorcycles, and computers). Factor scores for the four factors were used in further analyses.


Table 1 presents a summary of the marketing and cultural variables across the four areas. The respondents were fairly comparable across regions on most demographics measured except for religion and (unfortunately) age. Graduate students constituted the Wisconsin respondents, while the respondents in the other areas were primarily undergraduates. Some differences across regions can be explained also by age differences, so an analysis using both age and region will be presented later.

The religious distribution varied across the regions with Massachusetts being predominantly Catholic (69%) and Oklahoma predominantly Protestant (57%). Wisconsin had the largest percentage of other (35%), while the Washington distribution was the most balanced across the religious options.

Respondents across the four areas did vary according to cultural adherence, religious commitment, and fate-orientation. Since Oklahoma is located in the conservative Bible Belt, it is not unexpected that respondents from that area expressed the highest level of adherence to traditional cultural values as well as the greatest religious commitment. Areas with the highest percentage of Catholics (Washington and especially Massachusetts) expressed the most fatalistic views; this is consistent with the findings cited by Hirschman (1983b). No differences were found for product-specific fatalism nor for locus of control across the four regions.

Some differences were found across regions for the willingness to try new reading material (books and magazines) and for the risk associated with fashion innovations and new reading materials. Wisconsin and Washington students were more likely to try new books and magazines. Washington respondents perceived a greater level of risk to be associated with symbolic innovations, while Massachusetts respondents perceived the lowest amount of risk associated with new reading materials. That Massachusetts students see the least amount of risk but still are the least likely to try new books and magazines is a somewhat contradictory finding. It had been expected that willingness to try new products would be inversely related to the amount of risk perceived.

Religion (Catholic, Protestant, and other) [International students were deleted from the sample, so that "other" primarily reflects no religious preference. The number of Jews, Moslems, etc., included was too small to treat as a separate category.] and age were also used separately as independent variables in the attempt to explain differences in the cultural and market uncertainty variables (shown in Table 2). Differences in cultural adherence, fate-orientation, and religious commitment were found across religions; however, in most cases, the effect was due almost entirely to the "other" group and not to differences between Catholics and Protestants. "Other" respondents were less likely to adhere to cultural traditions, to have less religious commitment, and to be less likely to blame product failure on fate. However, Protestants were found to be significantly less fatalistic than either Catholics or others. Older (over 22) student respondents showed less adherence to tradition, less religious commitment, and less tendency to blame product failure on chance rather than the manufacturer; however, there were no differences between the two age groups in terms of fate-orientation.



Since religious variation is a major component of geographic subcultures, no further analysis of religious differences was made. However, our intent was to avoid age differences by taking a relatively homogeneous student sample. Since age differences across regions were found and since they are associated with differences in the cultural variables, we investigated the relative effects of both geographic area and age. Due to the fact that the Massachusetts sample had virtually no respondents over the age of 22, we did include an interaction variable. When both age and region are used as independent variables in the ANOVA models, age is not significant while region is for cultural adherence (age: F(1,454) = .4, p = .53; region: F(3,454) = 42.5, p = .00), fate-orientation (age: F(1,463) = 1.15, p = .28; region: F(3,463 = 5.6, p = .00), and religious commitment (age: F(1,463) = 3.6, p = .06; region: F(3,463) = 12.8, p = .00). Thus, the geographic variation associates more with varying cultural values than does age. Similarly, when differences are found for the willingness to try new products and for the risk associated with new products, region is much more significant than age in those cases where one (or both) main effects is (are) significant.

Relating Cultural Variables to the Marketing Uncertainty Variables

The various cultural variables (cultural adherence, religious commitment, fate- orientation, product-specific fatalism, and locus of control) were related to the willingness to try new products and the risk associated with new products using canonical correlations. The results are summarized in Table 3. The set of cultural variables is related to both the willingness to innovate and the risk factors; however, the small redundancy values indicate that the cultural values do not explain a great deal of variance in either set of dependent variables.

For the willingness to try new products variables, the first canonical correlation is significant (Rc = .31, p = .00). Cultural adherence and (to some degree) fate-orientation variables are inversely related to the willingness to try non-technical products (reading materials, fashion, and entertainment). As expected, the stronger the ties to current cultural values and the more fatalistic the respondent is, the less willing one is to try new non-technical products. The willingness to try technical products is not related directly nor inversely to the cultural variables.

Greater risk is associated with non-technical products by those who have higher levels of religious commitment and by those who are more fatalistic. Again, the risk associated with technical products is not related (inversely nor directly) to the cultural variables.


Geographic regions do vary in terms of innovativeness and the levels of perceived risk. Further, differences exist across regions in terms of cultural adherence, religious commitment, and fate-orientation. Finally, the results indicate that the varying cultural values can explain differences in the marketing variables. Residents in those areas with more adherence to traditional values are less likely to try new products. Residents in areas with higher levels of religious commitment and fate-orientation may perceive higher levels of risk associated with new products.



Inadvertently, our study varied age as well as geographic region and we found that the cultural values held by older students differ from those held by younger students. However, geographic area was a much better explanatory variable for both cultural differences and differences in innovativeness and perceived risk.

One implication of these differences in students across regions is that the results challenge the common assumptions that all students are similar. Student subjects have been shown to differ from adult subjects for many types of behavior (Enis, Cox, and Stafford 1972; Hawkins, Albaum, and Best 1977; Park and Lessig 1977; Permut, Michel, and Joseph 1976; Shuptrine 1975). This study points out that student samples may well vary across the United States in terms of their cultural composition.

Thus, the study provides support for the existence of geographic subcultures and for the proposition that cultural differences across areas of the United States result in varying consumption patterns.


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James W. Gentry, University of Wisconsin-Madison
Patriya Tansuhaj, Washington State University
L. Lee Manzer, Oklahoma State University
Joby John, Bentley College


NA - Advances in Consumer Research Volume 15 | 1988

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