Culture Bound Assumptions in Behavior Intention Models

ABSTRACT - Many models of consumer behavior include fundamental assumptions which are rarely questioned. Behavior intention models, for example, assume people have: a linear time orientation (the future has meaning), an internal locus of control, and the ability to think in probabilistic terms. While this may be true in western, industrialized countries, it may not be true in developing countries. An empirical test, using data from Jordan, Thailand and the United States, partially supports the hypothesis that time orientation, locus of control, and probabilistic thinking ability influence a consumer's ability to form accurate intentions.


Joseph A. Cote and Patriya S. Tansuhaj (1989) ,"Culture Bound Assumptions in Behavior Intention Models", in NA - Advances in Consumer Research Volume 16, eds. Thomas K. Srull, Provo, UT : Association for Consumer Research, Pages: 105-109.

Advances in Consumer Research Volume 16, 1989      Pages 105-109


Joseph A. Cote, Washington State University

Patriya S. Tansuhaj, Washington State University

[This study was funded in part under USAID contract AID/DSAN-X11-G-0187. Culture Bound Assumptions in Behavior Intention Models.]


Many models of consumer behavior include fundamental assumptions which are rarely questioned. Behavior intention models, for example, assume people have: a linear time orientation (the future has meaning), an internal locus of control, and the ability to think in probabilistic terms. While this may be true in western, industrialized countries, it may not be true in developing countries. An empirical test, using data from Jordan, Thailand and the United States, partially supports the hypothesis that time orientation, locus of control, and probabilistic thinking ability influence a consumer's ability to form accurate intentions.

It is well know that values can affect how consumers behave in the marketplace both within and across cultures (Tse, Wong and Tan 1988). However, very little research has examined the effect of basic values (called primary culture by Hall, 1983) on consumer behavior. Primary culture can differ drastically across cultures, and is so fundamental it molds peoples' perceptions of the world. Even when differences in primary culture are recognized, it may be very difficult for a person to truly understand alternative perspectives (Hall, 1983). More importantly, primary culture (predominantly the western cultural perspective) is incorporated in most consumer behavior models as basic assumptions and as such, the models may be culturally bound. For example, Lee (1988) suggests current conceptualizations of the Fishbein model are inappropriate for South Koreans who emphasize group conformity and face saving, and proposes a modification of the subjective norm construct for the Korean culture.

Cunningham and Green (1984) suggest that marketing theory needs to be broadened in scope to become culture-free with universal applicability (also see Hampton and Gent 1984). Following their suggestion, this study investigates whether basic cultural values affect the ability to form accurate behavioral intentions. The research focuses on three concepts likely to influence the relationship between intention and behavior: time orientation, probabilistic thinking, and locus of control.


Behavior intention models posit that at some specific time period, consumers formulate some expectation about their behavior in some future time period. There are three key components to the model. Foremost, the model focuses on the future. This underlies the basic purpose of the model, to predict how the consumer will act. Understanding the formation of intentions is unimportant if they can't be used to predict future behaviors. Second the model posits that consumers plan to take some course of action which will lead to some behavior.- For example, they may pursue an education to improve their chances of getting a good job. A course of action (education) leads to some outcome (good job). Lastly, the model measures expectations or likelihoods of certain actions and outcomes occurring. Each of these components contain basic assumptions about the abilities and values of the respondent. In particular, they assume a linear time orientation, an internal locus of control, and the ability to think in probabilistic (likelihood) terms.

If we ask someone about their future behavior, the respondent must have some conception of "future" for their answer to be meaningful. Westerners have relatively little difficulty conceiving the "future." This is not true of all cultures (Meade 1971). Different cultures often have different perceptions about time (McGrath and Rotchford 1983). Graham (1981) identifies three general orientations toward time, linear-separable, circular-traditional, and procedural-traditional. Linear time is most similar to western perceptions of a past, present and future stretching to infinity. Time is also seen as being separable into discrete units along this line. People with a circular time orientation perceive time relative to repeated patterns such as cycles of the sun, moon and seasons. They have no perception of time stretching into the future and therefore, expect the future to be like the past. instead they focus on the present. People with a procedural time orientation view time as being irrelevant. Behavior is activity driven rather than time driven.

Behavior intentions models assume a linear time orientation. As noted above, the formation of intentions requires some conception of "future". The future is a less clearly defined concept for both circular and procedural time orientations. In addition, the formation of intentions often assumes behavior will occur in a specific time period. Again, the conception of discrete time periods is foreign to people with a procedural or circular time orientation. Given that the formation of intentions requires a time orientation with discrete future components, our first hypothesis is that subjects with a stronger linear time orientation will be able to form more accurate behavior intentions. Specifically:

H1: The discrepancy between intentions and behavior will be smaller if the subject has a strong linear time orientation.

Not only must people be able to conceive of the future, they must also believe they can control their actions in the future. Ajzen and Madden (1985) found perceptions of volitional control affect the intention-behavior relationship. While their study examines temporary changes in perceptions of control, it is also likely that persistent perceptions of control (fatalism) can affect the intention-behavior relationship. Cultural beliefs very widely about man's control over his destiny. Fatalists believe, ". . . that all events are predetermined by fate and therefore unalterable by man" (Gentry et al. 1988). Fatalism is related to locus of control (Mirels 1970; Schneider and Parsons 1970). People with an external locus of control believe that factors beyond the control of the individual determine future behaviors. They simply take events as they come, instead of being able to plan, avoid, or master the environment. People with an internal locus of control believe they are masters of their destiny. Hoover, Green, and Saegert (1978) have suggested that the degree of fatalism varies across national groups. John et al. (1986) found that American students are less fatalistic than Indians, and Indians are less fatalistic t} an Thais, and Wilson (1970) found that Asian culture is more fatalistic than British culture.

Respondents with an external locus of control should be less able to form accurate intentions. Since they believe they have less control over their behavior, they would feel less able to predict their behavior. For example, Muslim cultures feel Allah determines future events. Trying to predict the future is considered either stupid or irreligious. When asked if they intend to do something in the future, they reply "Insha' Allah", or "As God wills." This inability or reluctance speculate about the future leads lo our second hypothesis:

H2: The discrepancy between intentions and behavior will be smaller for people with an internal locus of control

Measures of intentions include a likelihood component (Justner 1966). Responding to the likelihood component requires the person to use probabilistic thinking. Probabilistic thinking may be defined as, " . . . the tendency to view the world in terms of uncertainty, ascribing different degrees of uncertainty to events and the ability to express this uncertainty meaningfully either verbally or as a numerical probability" (Wright and Phillips 1979, p. 295). Probabilistic thinking varies across cultures (Wright 1984; Wright and Phillips 1979). Wright et al. (1978) found a large difference between Asian (Indonesian, Malaysian, and Hong Kong Chinese) and the British. The British have a much more finely differentiated view of uncertainty than the Asians in response to uncertain situations. Wright's work has at least two implications: 1) decision analysis based on probability would be inapplicable in cultures where people can not think in probabilistic terms; 2) Nonprobabilistic thinking may result in a lack of long-term future planning. Events in the future may be seen as "uncertain" rather than "probable" or improbable." These suggest that behavioral intention models and other decision models which assume probabilistic assessments may not be valid for predicting consumer behavior in some cultures. This leads to our third hypothesis.

H3: The discrepancy between intentions ar.d behavior will be smaller if the person is able to think in probabilistic terms.


A survey was conducted to assess the intentions and actual behavior of students in Jordan, Thailand and the United States. Three general categories of behavior were examined across the three cultures; soft drink consumption, food consumption and class related activities. The actual behaviors examined in each country was modified to be consistent with cultural norms. For example, the American students were asked about pizza consumption while the Thai students reported on noodle consumption. In addition to assessing intentions and behavior, data were collected on the student's time orientation, locus of control and probabilistic thinking ability. The sample consisted of 33 students in Jordan, 41 in Thailand, and 173 in the United States.


Respondents reported the amount of products or activity they intended to consume within a specific time. In addition, the degree of certainty associated with the intentions was also measured. At the end of the time period, a follow-up was conducted to measure actual consumption. The time period between the measure of intentions and the measure of behavior varied among the countries from 1 to 7 days depending on our access to the students. Since the products and activities examined varied slightly from country to country, scores were converted into discrepancy values using equation (1). The discrepancy value ranged from 0 to 1 where 1 indicates either the subject's intended consumption was 0 while actual consumption was greater than 0 or intended consumption was greater than 0 but actual consumption was 0. A value of 0 indicates there was no discrepancy. The absolute value was examined since the size of the discrepancy was the variable of interest, not the direction of the discrepancy.

(1) D = ¦(B-(BI*PBI)/(B+(BI*PBI)¦


D = Discrepancy between intentions and behavior

B = Behavior

BI = Behavior intention (quantity)

PBI = Behavior intention (probability)

Fatalism/locus of control was measured using a five point Likert scale modified from Farris and Glenn's (1976) fatalism scale and Lumpkin's (1985) locus of control scale. Example items include: What happens to me is my own doing; God determines what I will do in the future; Many of the things that happen in life are due to luck.

Measures of linear time orientation were constructed using Graham's (1981) descriptors of different time orientations. Respondents were asked to agree or disagree with a time description statements on a five-point Likert scale. For example, Time is like money, it can be spent or saved; Time can be measured and allocated to specific tasks; Time is like a road that stretches from the past into the future and people travel along this road.

Respondents' probabilistic thinking ability was measured by asking them to assess a probable occurrence of 4 situations:

- If I flip a coin, what is a chance that a head will appear?

- A bag contains one red ball and three white balls. If you select one ball, what chance is there that it will be white?

- How likely is it that the sun will rise tomorrow?

- How likely is it that there will be a drought next summer?

The scale ranges from 0% chance to 100% chance or don't know. For the first two questions, respondents received a score of I for the correct answers of 50% and 75% respectively. For the third question the respondents received a 1 if the respondent reported a high probability of the sun rising (greater than 90%). A score of 1 was assigned for the final question if the respondent provided any guess about the probability rather than simply responding "don't know". The value for the probabilistic think scale was determined by summing the four values.


The first step in the analysis was to construct a single index score for linear time orientation and locus of control measurement scales. Separate factor analyses were conducted for each country separately. A single factor model was fit to each scale and factor scores were computed. These factor scores were then used to construct single index score for each of the variables.

Before testing the hypotheses, nonparametric ANOVA was conducted to test for differences between countries on each of the variables. To test the hypotheses, three regressions were conducted. The data for each of the countries were combined in one analysis for each of the general behaviors studied. For example, one regression examined soft drink consumption across the three countries. Fatalism/ locus of control, linear time-orientation, and probabilistic thinking ability were used as predictor of the discrepancy between intentions and behavior.


ANOVA indicated that there were significant differences between the cultures on the independent variables. As expected, The American students had the highest agreement with the linear time orientation statements, followed by the Jordanians, then the Thais (See Table 1). The American students also scored the highest on internal locus of control, while the Jordanians had the lowest scores on internal locus of control. Finally, the American students had the highest probabilistic thinking scores. There was no significant difference between the Jordanians and the Thais. These results are consistent with past studies that found Western cultures have a stronger linear time orientation, higher perceived internal locus of control and higher probabilistic thinking ability.

The analysis of academic related behavior provided strong support for the hypotheses. Linear time orientation, locus of control, and probabilistic thinking predicted 27.2% of the variation in the discrepancy between intentions and behavior (P<0.001). All relationships were also in the direction hypothesized. A stronger linear time orientation, an internal locus of control, and better probabilistic thinking ability lead to smaller discrepancies between intentions and behavior.

The analyses of soft drink and food consumption were less compelling. The analysis of soft drink consumption indicated linear time orientation explained 5.6% of the variation in the discrepancy (P<0.05). The relationship was again in the hypothesized direction. Finally, none of the discrepancy for food consumption could be explained by the independent variables It may be that certain behavior are more routinized, the formation of intentions is closely related to past behaviors, and therefore the role of time orientation, locus of control and probabilistic thinking is diminished.


Cunningham and Green (1984) have noted the need to broaden consumer behavior theory across cultures. One way to broaden our theories is to reexamine the basic assumptions inherent in any given theory. In the case of behavior intention models, the hypothesized link between behavior and intentions assumes that people have some conception of the future, believe they have some control over their lives, and can think in probabilistic terms. The results of this study provide limited support for the contention that our models of consumer behavior are inherently cultural bound due to underlying assumptions.

The effect of inherent assumptions has far reaching implications for the development of consumer behavior theory. It must be recognized that incorrect assumptions about respondents can exist within societies as well as across societies. Researchers often lament that consumer behavior models do not explain much behavior (Peterson, Albaum, and Beltramini 1985). While some of this may be caused by poor theory or measurement problems (Cote and Buckley 1988), it may also reflect the failure to include basic model assumptions. Not only would modeling basic assumptions improve the predictive accuracy of a model, it should also provide insights into measurement issues and problems.

Further study is needed to investigate the basic assumptions underlying consumer behavior models. Additional underlying assumptions of behavior intention models can be identified. For example, Lee (1988) has shown differing approaches to compliance with group norms (i.e., the collectivism-individualism dimension) affects relationships in behavior intention models. Other areas of consumer behavior have models with similar assumptions based on basic Western values. In studies of family decisions making, it is often assumed the family has a nuclear structure, shared power between husband and wife,and monogamy. These assumptions are not valid in many cultures. Models of consumer innovativeness assume consumers are more internally controlled and that product benefits are perceived similarly by consumers. This may not be true in many less developed societies. Consumer behaviorists should examine the assumptions underlying the models or theories in their area of research as an important step toward greater generalization of consumer behavior theories.




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Joseph A. Cote, Washington State University
Patriya S. Tansuhaj, Washington State University


NA - Advances in Consumer Research Volume 16 | 1989

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