Variations in Choice Strategies Across Decision Contexts: an Examination of Contingent Factors

ABSTRACT - Consumer decision strategies were examined across 12 different product categories. Results indicated that choice strategies vary significantly across decision contexts. An attempt was then made to examine how certain contingent factors (e.g., amount of advertising, number of brands available, perceived similarity of brands) were able to account for this variation. Implications of findings are then discussed.


Wayne D. Hoyer (1986) ,"Variations in Choice Strategies Across Decision Contexts: an Examination of Contingent Factors", in NA - Advances in Consumer Research Volume 13, eds. Richard J. Lutz, Provo, UT : Association for Consumer Research, Pages: 32-36.

Advances in Consumer Research Volume 13, 1986      Pages 32-36


Wayne D. Hoyer, The University of Texas at Austin


Consumer decision strategies were examined across 12 different product categories. Results indicated that choice strategies vary significantly across decision contexts. An attempt was then made to examine how certain contingent factors (e.g., amount of advertising, number of brands available, perceived similarity of brands) were able to account for this variation. Implications of findings are then discussed.


Recent work in human information processing has clearly recognized the fact that individuals are highly responsive to the situation or task at hand (Newell and Simon 1972; Belk 1975; Bettman 1979; Simon 1981; Payne 1982). That is, an individual may react quite differently depending on the contingencies surrounding the situation. For example, a consumer may be price-conscious in a product category where major price variations exist, but be brand loyal in another where there are few such differences. Thus, major questions which may be posed are: To what extent and why do consumers employ different decision strategies in different situations? Put another way, in order to develop a more complete theory of consumer decision making, the effects due not only to the individual, but also to the task and the task X individual difference interaction must be considered (Punj and Stewart 1983).

In response to this realization, a number of studies have begun to examine contingent effects upon decision making behavior (Payne 1982; Punj and Stewart 1983). Punj and Stewart (1983) summarized the major findings in this area and attempted to integrate them into a meaningful framework. This framework identifies the key task variables (e g., number of alternatives, number of attributes, time pressure, etc.) and task X individual difference interactions (e.g., the exposure situation, impulse purchases, etc.) which impact on the decision process.

While a review of the studies in each of the areas is beyond the scope of the present paper (for the full review, see Punj and Stewart 1983), an examination of the findings reveals two important generalizations. First, many of the studies have focused on broad level types of processing which occur when a decision is mate. A variety of different dependent variables have been examined including: the amount of information processing (as examples, Jacoby, Chestnut, and Fisher 1978; Bettman and Park 1980), the processing strategy employed (by brand or by attribute-e.g., Bettman and Kakkar 1977; Wright and Barbour 1977), the amount of time taken (e.g., Gardner, Mitchell, and Russo 1978), accuracy of choice (e.g., Jacoby, Szybillo, and Busato-Schach 1977), and intentions (e.g., Belk 1974, 1975). However, a major void concerns the examination of how different task and individual difference factors influence the specific choice rules used to make a decision. Only a handful of studies (e.g., Wright 1975; Wright and Barbour 1977; Park 1978; Crow, Olshavsky, and Summers 1980; Bettman and Park 1980) have focused on this dependent variable and these studies have been concerned with only one task characteristic--the number of alternatives available.

A few other studies have examined cross-product differences (e.g., Cunningham 1956; Massy, Frank, and Lodahl 1968; Wind and Frank 1969) but these studies have limited attention to general buying behaviors such as brand loyalty or private brand proneness. Blattberg, Peacock, and Sen (1976) examined differences in purchasing strategies across product categories, but their major interest was in determining how choice is influenced by general household characteristics such as demographics and they examined differences across only two product categories.

Second, most of the studies have examined contingent effects in discrete situations where at least a moderate degree of information processing takes place (i.e., situations of high to moderate involvement). One must question, however whether the findings of these studies would generalize to situations where processing is relatively continuous or involves repeated decisions over time (Hogarth 1981) and where relatively little information processing occurs (i.e., low involvement situations--Ray, et al. 1973),

In light of these observations, the purpose of the present paper is to examine the very important effect of task variables in low involvement decision situations. The major question to be asked is to what extent do various aspects of the task influence consumers to employ a particular type of choice rule or heuristic. Hypotheses will be developed, followed by an empirical attempt to test these hypotheses.

The Nature of Low-Involvement,Repeat Purchase Decision Making

A recent article by Hoyer (1984) provides a view and empirical examination of consumer decision making for product categories which are purchased frequently over time and which are low in involvement or importance. The basic notion underlying this view is that consumers employ very simple choice heuristics when making low involvement purchases. These rules are referred to as "choice tactics" and they permit consumers to make a quick and effortless decision. These tactics are acquired as a result of a learning or "trial and error" process over time. In other words, depending upon the nature of the post-purchase brand evaluation (e.g., positive, negative, or neutral), consumers can "adjust" their decision heuristic on the next purchase occasion in order to provide a more satisfactory choice. Thus, low involvement repeat purchase decision making is viewed as a continuous as opposed to discrete processing situation and observed decision making at one point in time would appear to be very limited.

Some preliminary support for this notion has been provided in a study by Hoyer (1984). In examining the in-store purchase of laundry detergent, it was fount that the median amount of time devoted to a purchase was about four seconds. Thus, on an observational level, there appears to be an extremely low level of in-store information processing. Further, when asked why they purchased the brand they tit, 92% of the respondents supplied one simple reason (i.e., a choice tactic). These tactics tended to be of six major types: (1) price oriented tactics (e.g., "buy the cheapest," "buy the brand on sale," "buy the brand for which I have a coupon," etc.), (2) performance tactics (e.g., "buy the brand which works the best," etc.), (3) affect-related tactics (e.g., "buy the most familiar brand," "buy the brand I like," etc.), (4) normative tactics (e.g., "buy what my parents bought," "buy what my friend advises," etc.), (5) in-store factor tactics (e.g., "buy the first brand I see," "buy the brand most prominently displayed," etc.), and (6) hybrid tactics (see Hoyer 1984). When viewed in conjunction with other studies (e.g., Olshavsky and Granbois 1980), there appears to be support for the notion that consumers employ simple choice rules in one type of low involvement situation.

In light of this fact, a major question which remains yet to be answered concerns the reasons why a particular tactic is employed. In particular, it is unlikely that the same tactic would be used in every product category. On the other hand. there will be certain individual difference characteristics which will lead to the usage of a particular tactic. It is a major assumption of the present paper, however, that aspects of the situation (e.g., task variables) will also account for a significant portion of the potential within-subjects variance. Specifically, it is suggested that contingent factors will interact with individual difference factors to produce the usage of a particular choice tactic. Therefore, in order to more fully understand the nature of common, repeat purchase decision making, an attempt must be made to empirically examine the effects of these task variables upon the decision process.

In summary, a major purpose of the present research is to more formally examine the consistency of consumer decision strategies across a number of product categories. A major question concerns the extent to which consumers employ the same tactic or strategy across product categories or whether different strategies are used for different decisions. Specifically, consumers' choice tactics were assessed for 12 different product categories in order to examine both within-subject and across product consistencies.

In addition, the present research attempts to empirically assess the importance of a number of contingent or task factors: the amount of advertising for the product class, price variations within the product category, the number of brands available, and the perceived similarity of brands in the product category. In examining these factors, it is important to remember that interest is in examining factors which influence the specific reason why the brand was chosen as opposed to variables such as the amount of processing and the type of strategy employed (e.g., within-brand vs. within dimension). These hypotheses are not meant to be exhaustive; rather their intent is to provide initial evidence of the importance of contingent factors in determining the specific type of decision strategy employed. With this in mind, the following hypotheses are offered:

Hypothesis 1: The greater the amount of product class advertising, the more likely consumers will employ tactics based on affect or familiarity and less likely to base a decision on price tactics.

Given that familiarity which results from repeated exposures to advertisements is critical to the development of product-related affect (Ray, et al. 1973; Zajonc and Markus 1982), it is hypothesized that affect related tactics are more likely to be employed in product categories where there tends to be a heavy amount of advertising.

Hypothesis 2: The greater the range in prices for a particular product category, the more likely consumers will employ a price related tactic and less likely they will employ an affective, normative, or performance tactic.

If no appreciable variations in price exist, consumers must rely on some other form of criterion to make a decision. Put another way, little variance on the attribute would not permit it to be determinant (Alpert 1980). If, on the other hand, there are major price differences between brands, it is much more likely that this factor will come into play as a key decision criterion. This would be consistent with the finding that consumers are less brand loyal when prices are active (Farley 1964).

Hypothesis 3: The greater the number of brands, the more likely consumers will employ a price tactic and less likely to employ a performance tactic.

If there are a large number of brands available, it is likely that there are a number of alternatives which will satisfy consumers' needs. Therefore, consumers could select an inexpensive brand from this set. Further, research has indicated that consumers tent to be less loyal toward products with many available brands (Farley 1964).

Hypothesis 4: When the perceived similarity of brands is high. consumers will be less likely to base their decision on a performance tactic and more likely to employ a price tactic. {394

In other words, if the brands in a particular product class are perceived to be of roughly equal quality, some other form of tactic other than a performance-related one is likely to be employed. If there is a strong discrimination in terms of quality, however, a performance tactic will have a higher probability of being chosen.


Subjects. The subject population consisted of 175 consumers in a Southwestern city who were intercepted as they engaged in grocery shopping. Shoppers were interviewed in eight different grocery stores (representing the three major local chains) throughout the entire city. Interviewing times were divided equally between the morning, afternoon, and evening hours. However, due to varying traffic patterns, 22 (12.5%) of the shoppers were interviewed in the morning, 117 (67%) in the afternoon, and 36 (20.6%) in the evening. One hundred twenty four of the subjects (70.9%) were women and 51 (29.1%) were men. When compared to city demographics, subjects approximately corresponded to the city population in terms of education, age, and income.

Product Categories (Independent Variables). Twelve different product categories were selected for study. These products were chosen to ensure variance along the major independent variables (i.e., the external factors): advertising expenditures, the number of brands available and the price range among brands. The remaining variable: (i.e., the internal factor of perceived similarity of brands) varies from individual to individual and, thus, was measured by means of a questionnaire item.

In order to select the product categories, information was collected along the previously mentioned dimensions for 24 common low involvement products, In each of the eight test stores, interviewers recorded the number of brands available, the number of shelf tags present, the price range (lowest to highest brands), and the face dominance (one, two, three, or no brand dominates). The values for each individual store were then combined to calculate an overall mean for each product for each variable. The product categories resulted by selecting products which were high, medium, and low in terms of the means for each external factor. The twelve products chosen adequately fulfilled this requirement. These products were: breakfast cereal, canned peas, canned soup, coffee, butter, shampoo, headache remedies, bar soap, toothpaste, aerosol bathroom cleaner, toilet paper, and tuna.


Choice Tactic. The major variable of interest was the choice tactic(s) employed by consumers when making a purchase. Due to the fact that consumers were volunteering their time in the middle of a shopping trip to indicate their choice strategies for 12 different product categories, a verbal protocol was abandoned in favor of a more streamlined procedure.

On the basis of a number of previous studies (Deshpande, Hoyer, and Jeffries 1982; Cobb 1983; Hoyer 1984), six major types of choice tactics were identified. A list of these is provided in Table 2. A seventh category (I never buy this product) was added to account for subjects who did not purchase the product. Subjects were presented with these statements by means of an index cart and were asked to read aloud the number of the statement(s) which best represented the way they usually bought the product. The response was then recorded on a special answer sheet by the interviewer.

Similarity of Brands. A similar procedure was employed to measure the perceived similarity of brands in the product category. Subjects were presented with an index card which contained categories ranging from 1=very similar to 5=very dissimilar. Subjects were asked to indicate how similar in quality the brands in the product category were. Again, responses were recorded by the interviewer.


Variations in Tactic Usage Within Subjects

Table 1 presents a summary of the number of choice tactics employed by each subject. It can be seen from the Table that tactic usage varied fairly substantially among the decision makers. Only 7% (n=12) of the subjects employed the same tactic across all 12 product categories, while 49% of the sample (n=85) used 4 or more. Thus, it can be concluded that a substantial number of consumers do use different choice strategies across different product categories. This finding serves as the justification regarding further investigation as to the origins of this variation.



Choice Tactic Usage Across Product Categories

A second area of interest was to determine the specific types of tactics used across product categories. It can be seen from Table 2 that significant variations in tactic usage did exist. First, price-related tactics were most likely to be employed for decisions regarding toilet paper (42.3%), tuna (27.4%), and butter (24.6%), while price was of least concern for breakfast cereal (5.7%) and toothpaste (11.4%) decisions.

Performance-related tactics were most evident for decisions regarding shampoo (40.0%), breakfast cereal (36.6%), and toothpaste(30.9%), while least employed for canned peas (16.6%) and aerosol bathroom cleaner (16.9%).

Familiarity-related tactics were employed little across all product categories. This tactic was most evident for bar soap (10.3%) and canned soup (9.7%). One possible reason for this low reporting however may be the social undesirability of admitting this type of behavior. Normative tactics were also employed infrequently, but were most likely to appear in breakfast cereal decisions. This likely reflects the influence of children in the decision.

Finally, significant variations existed in the tendency to purchase habitually (i.e., always buy). This type of decision making was most likely to appear for toothpaste (40.0%), butter (32.0%), canned soup (29.1%), and bar soap (291> . This tactic was employed in choices regarding aerosol bathroom cleaner (9.1%) and canned peas (12.0%).

In summary, wide variations in tactic usage do appear to exist across product categories. Different types of tactics tend to be employed in different product categories. Merely documenting this fact however, does not provide provocative information to those interested in consumer decision making. What is needed is an attempt to explain the nature of the variations in tactic usage or why different tactics are employed across product categories. Attention is now turned to an initial investigation of several potential factors.


Four exploratory hypotheses were presented to provide a preliminary explanation of strategy variation across product categories. Specifically, four major situational variables were investigated: amount of product class advertising, price variations within the product category, the number of brands available, and perceived similarity among brands.

In order to test the hypotheses related to each of these variables, previously collected information regarding each of the independent variables was converted to ranks. For example, each of the product categories was ranked from 1 (=low) to 12 in terms of the amount of advertising, number of brands available, etc. These rankings were then correlated with a ranking for the presence of a tactic for the product category using a rank-order correlation statistic. Table 3 presents a summary of this analysis.

Hypothesis 1 stated that the greater amount of product class advertising, the more likely consumers will employ familiarity based tactics and less likely to base the decision on price factors. It can be seen from the Table that support for the hypothesis was mixed. Consumers were less likely to employ price tactics (r=-.78, p<.01) when product class advertising was high, but were not more likely to use a familiarity tactic (r=.28). It is important to note, however, that consumers did not indicate heavy usage of familiarity as a tactic across all product categories. It was interesting to find, however, that the usage of performance-related tactics increased with higher levels of advertising (r=.66, pc 05) One possible explanation for this finding is that advertising may create stronger performance perceptions in consumers' mints.

Hypothesis 2 states that greater price variations in a product category will lead consumers to use a price-related tactic and result in less usage of affective, normative, or performance tactics. From Table 3, it can be seen that support for this hypothesis was not in evidence. When price variations were higher, consumers were no more likely to employ a price tactic (r=.06); rather, the incidence of performance (r=.43) and habitual tactics (r=.50, p<.05) were more in evidence. One possible explanation is that a price-quality relationship may be higher when price variations are greater.

Hypothesis 3 indicates that consumers will be more likely to employ a price tactic and less likely to employ a performance tactic when there are a greater number of brands available. In this case, findings were in the opposite direction from the hypothesis. As the number of brands increased, consumers were less likely to employ a price tactic (r=-.50, p<.05) and more likely to use a performance tactic (r=.59, p<.05). Perhaps with many brands available, consumers are more likely to rely on a favored brand in order to make the decision task more manageable.

Finally, Hypothesis 4 states that consumers will be less likely to use a performance tactic when the perceived similarity of the brands in the product category is high. As shown in Table 3 strong support for this hypothesis is in evidence. When perceived similarity was high, consumers were more likely to use a price tactic (r=.49) and much less likely to base their decision on performance (r=-.79, p<.01) and habit (r=-.40).


The results of the present study indicate that significant variations in choice strategies do exist across product categories. First, a fairly substantial proportion of consumers employed 4 or more tactics across the 12 product categories. If individual difference factors were the major determinant of decision strategy, one would expect strategies to be fairly consistent across product categories. The findings of the present study suggest, however, that certain aspects of the task of decision situation intervene to cause subjects to employ different strategies across choice situations. As further evidence of this fact, a second finding was that the different types of choices were employed in different proportions across the product categories. For some products, price related tactics were dominant. while for other performance related, habitual. or other tactics tended to be employed. Again, it is suggested that certain aspects of the task cause these tactics to be applied in different proportions across the product categories.



The present study attempted to provide initial evidence regarding the influence of several contingent factors or tactic usage. Results of this attempt was mixed. Both the amount of product class advertising and the perceived similarity of brands in the product class appeared to have a strong impact on the type of tactic employed. When advertising levels are high, consumers are more likely to employ performance related tactics and less likely to use price related tactics. The perceived similarity of brands in the product category had the opposite effect (i.e., greater use of price tactics and less use of performance and habitual tactics). In addition, the degree of price variations increased the level of performance tactic usage and the number of brands led to a decreased use of price tactics and more frequent use of performance tactics.

It is important to note a number of limitations of the present research. First, the present study, due to its exploratory nature, examined the effects of contingent factors in a global level. However, a complete understanding of the selection of a choice tactic involves individual level measurement that pertains to the purchase of a particular brand in a particular store and in a particular store environment. Further research is needed to examine the raised issues in this more individual level context. Second, in some cases, one may question whether the classification schemes for choice tactics are mutually exclusive. For example, knowledge of price or performance factors may be the bases for which consumers claim familiarity with or positive effect towards a brand. Future research of this nature might employ probes to determine the underlying nature of tactic usage. Also, further research is needed to evaluate the adequacy of the tactic measurement approach employed. The possibility exists that retrospective questioning may not be the most effective method for determining choice strategies.

These findings are taken as evidence of how meaningful hypotheses regarding the impact of contingent factors on the use of choice strategies can be developed. Future research is now needed to explore the effects of other contingent factors on the decision process. A number of potentially interesting variables can be identified. These would include both external factors which involve basic aspects of the task which are generally consistent across all individuals, and internal factors which are individual centered perceptions which the consumer brings to the situation. In addition to the number of brands, amount of product class advertising, and price variations, external factors would include product packaging, amount of shelf space, brand placement on the shelf, the presence of coupons, the presence o displays, and price fluctuations. Also, the type of advertising may have a strong impact on the type of choice tactic used. For example, if the product class advertising was price-based or stressed particular performance attributes, these factors should logically influence the choice. Internal factors would consist of the nature of post-purchase evaluations, the perceived similarity of brands, product class experience, time pressure, and individual difference variables (e.g., frugality, dogmatism, self-confidence, etc.). It is hypothesized that both these internal and external factors will interact to determine the type of choice strategy chosen. Finally, studies which more specifically examine the task-individual interaction are needed.

In summary, the results of the present study indicate that we cannot assume a consistent decision process across all choice contexts. Individuals are reactive to their environment and a complete theory of consumer choice must specify how key contingent factors impact on the decision process. This study is viewed as an initial step in this direction. Future research is needed to develop richer hypotheses regarding these concepts and to test these hypotheses empirically.



Alpert, Mark I. (1980), "Unresolved Issues in Identification of Determinant Attributes," in J. C. Olson (ed.), Advances in Consumer Research, Vol. 7, Ann Arbor Association for Consumer Research, 83-88.

Belk, Russell W. (1974), "Application and Analysis of the Behavioral Differential Theory for Assessing Situational Effects in Buyer Behavior," in S. Ward and P. Wright (eds.), Advances in Consumer Research, Vol. 1, Ann Arbor: Association for Consumer Research, 158-61.

Belk, Russell W. (1975), "Situational Variables and Consumer Behavior," Journal of Consumer Research, 2 (December), 157-66

Bettman, James R. (1979), An Information Processing Theory of Consumer Choice, Reading, MA: Addison-Wesley.

Bettman, James R. and Pradeep Kakkar (1979), "Effects of Information Presentation Format on Consumer Information Acquisition Strategies," Journal of Consumer Research, 3 (March), 233-40.

Bettman, James R. and C. W. Park (1980), "Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis," Journal of Consumer Research, 7 (December), 234-48.

Blattberg, Robert C., Peter Peacock, and Subrata K. Sen (1976), "Purchasing Strategies Across Product Categories," Journal of Consumer Research, 3 (December), 143-54.

Crow, Lowell E., Richard W. Olshavsky, and John O. Summers (1980), "Industrial Buyers' Choice Strategies: A Protocol Analysis," Journal of Marketing Research, 17 (February), 34-44.

Cunningham, Ross M. (1956), "Brand Loyalty - What, Where, How Much," Harvard Business Review, 34 (January, February), 116-28.

Deshpande, Rohit, Wayne D. Hoyer, and Scot Jeffries (1982), "Low Involvement Decision Processes: The Importance of Choice Tactics," in R. F. Bush and S. D. Hunt (eds.), Marketing Theory: Philosophy of Science Perspectives, Chicago: American Marketing Association, 155-8.

Farley, John V. (1964), "Why Does Brand Loyalty Vary Over Products?" Journal of Marketing Research, 1 (November), 9-14.

Gardner, Meryl P., Andrew A. Mitchell, and J. Edward Russo (1978), "Chronometric Analysis: An Introduction and Application to Low Involvement Perception of Advertisements," in H. K. Hunt (eds.), Advances in Consumer Research, Vol. 5, Chicago, IL: Association for Consumer Research, 379-84.

Hogarth, Robin M. (1981), "Beyond Discrete Biases: Functional and Dysfunctional Aspects of Judgmental Heuristics," Psychological Bulletin, 90 (2), 197-217.

Hoyer, Wayne D. (1984), "An Examination of Consumer Decision Making for a Common Repeat Purchase Product," Journal of Consumer Research, 11 (December), 822-9.

Jacoby, Jacob, Robert W. Chestnut, and William A. Fisher (1978), "A Behavioral Process Approach to Information Acquisition in Non-durable Purchasing," Journal of Marketing Research, 15 (November), 532-44.

Jacoby, Jacob, George J. Szybillo, and Jacqueline Busato-Schach (1977), Information Acquisition Behavior in Brand Choice Situations," Journal of Consumer Research, 3 (March), 209-16.

'Making Better Use of Space" (1978), Chain Store Age Executive, June, 44-45.

Massy, William F., Ronald E. Frank, and Thomas Lodahl (1968), Purchasing Behavior and Personal Attributes, Philadelphia: University of Pennsylvania Press, 1968.

Newell, Alan and Herbert A. Simon (1972), Human Problem Solving, Englewood Cliffs, NJ: Prentice-Hall.

Olshavsky, Richard W. and Donald H. Granbois (1979), "Consumer Decision Making: Fact or Fiction?" Journal of Consumer Research, 6 (September), 93-100.

Park, C. U. (1978), "A Seven-Point Scale and a Decision Maker's Simplifying Choice Strategy: An Operationalized Satisfying-Plus Model," Organizational Performance and Human Performance, 21 (April), 252-71.

Payne, John W. (1982), "Contingent Decision Behavior," Psychological Bulletin, 92 (September), 382-402.

Punj, Girish N. and David W. Stewart (1983), "An Interaction Framework of Consumer Decision Making," Journal of Consumer Research, 10 (September), 181-96.

Ray, Michael L., Alan G. Sawyer, Michael L. Rothschild, R. M. Heeler, E. C. Strong, and J. B. Reed (1973), "Marketing Communication and the Hierarchy of Effects," in P. Clarke (ed.), New Models for Mass Communication Research, Vol. II, Beverly Hills: Sage.

Simon, Herbert A. (1981), The Sciences of the Artificial, Cambridge, MA: MIT Press.

"The Brand Power Study: 13 Reasons for Welcoming Salesmen" (1976), Progressive Grocer, November, 54.

Wind, Yoram and Ronald E. Frank (1969), "Interproduct Household Loyalty to Brands," Journal of Marketing Research, 6 (November), 434-5.

Wright, Peter L. (1975), "Consumer Choice Strategies: Simplifying vs. Optimizing," Journal of Marketing Research, 11 (February), 60-67.

Wright, Peter L. and Frederic Barbour (1977), "Phased Decision Strategies: Sequels to an Initial Screening," in North Holland TIMS Studies in the Management Sciences: Multiple Criteria Decision Making, Vol. 6, Amsterdam: North Holland. 91-109.

Zajonc, Robert B. and Hazel Markus (1972), "Affective and Cognitive Factors in Preferences," Journal of Consumer Research, 9 (2), 123-31.



Wayne D. Hoyer, The University of Texas at Austin


NA - Advances in Consumer Research Volume 13 | 1986

Share Proceeding

Featured papers

See More


The Effects of Being Time Poor and Time Rich on Happiness

Marissa Sharif, University of Pennsylvania, USA
Cassie Mogilner, University of California Los Angeles, USA
Hal Hershfield, University of California Los Angeles, USA

Read More


Ineffective Altruism: Giving Less When Donations Do More

Joshua Lewis, University of Pennsylvania, USA
Deborah Small, University of Pennsylvania, USA

Read More


Growing Up Rich and Insecure Makes Objects Seem Human: Childhood Material and Social Environments Predict Anthropomorphism

Jodie Whelan, York University, Canada
Sean T. Hingston, York University, Canada
Matthew Thomson, Western University, Canada
Allison R. Johnson, Western University, Canada

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.