The effects of consumer involvement and training on heuristics and biases *.ABSTRACT To examine the role of involvement and training in reducing biases and heuristics heu·ris·tic adj. 1. Of or relating to a usually speculative formulation serving as a guide in the investigation or solution of a problem: , an experiment was designed and conducted at a large Northern California Northern California, sometimes referred to as NorCal, is the northern portion of the U.S. state of California. The region contains the San Francisco Bay Area, the state capital, Sacramento; as well as the substantial natural beauty of the redwood forests, the northern University, and 319 out of 360 questionnaires were returned and useful. The results showed that the biases and errors caused by representativeness and availability exist in consumer purchase-making process. Increasing involvement does not help consumers avoid these biases and errors. However, training consumers with the necessary statistical skills and knowledge can significantly reduce them. Last, there is no interaction between involvement and training. Implications are discussed as well. Keywords: Heuristics, Consumer Involvement, Training, Biases. 1. INTRODUCTION There are generally two ways for consumers to process information: systematic processing and heuristic A method of problem solving using exploration and trial and error methods. Heuristic program design provides a framework for solving the problem in contrast with a fixed set of rules (algorithmic) that cannot vary. 1. processing (Chaiken, Liberman, and Eagly, 1989). Research has shown that the following factors affect whether consumers choose systematic or heuristic processing: the complexity of decision-making decision-making, n the process of coming to a conclusion or making a judgment. decision-making, evidence-based, n a type of informal decision-making that combines clinical expertise, patient concerns, and evidence gathered from situation (Johnson, Meyer Mey·er , Annie Florance Nathan 1867-1951. American writer and a founder of Barnard College at Columbia University (1889). Her plays include The Dominant Sex (1911) and Black Souls (1932). , and Chose, 1989), time pressure (Johar, Jedidi, and Jacoby Jacoby may refer to: People with the surname Jacoby:
Russo is a surname, a variant of Rossi, and may refer to
The need for cognition, in psychology, is a personality variable reflecting the extent to which people engage in and enjoy effortful cognitive activities. (Mantel and Kardes, 1999), demographics The attributes of people in a particular geographic area. Used for marketing purposes, population, ethnic origins, religion, spoken language, income and age range are examples of demographic data. (Darley Darley may refer to:
n the position of an individual on a socio-economic scale that measures such factors as education, income, type of occupation, place of residence, and in some populations, ethnicity and religion. (Capon capon castrated male fowl, larger than broiler, weighing up to 7 lb; produced either by administration of estrogenic substances or by surgical excision of the testicles. and Burke The name Burke (from Irish Gaelic de Burca, of Norman origin). In English the meaning of the name Burke is "fortified hill." See also Berkley. Places Australia
Heuristics are rules of thumb that consumers use to simplify decision making, which can expedite ex·pe·dite tr.v. ex·pe·dit·ed, ex·pe·dit·ing, ex·pe·dites 1. To speed up the progress of; accelerate. 2. decision-making, but also increase decision-error. It has been shown that a higher level of involvement can reduce heuristic biases and errors during the consumer decision-making process (Na, Marshall, and Son, 1999). However, are all kinds of heuristics sensitive to the level of involvement? If involvement cannot moderate certain heuristic biases, what other factors can possibly reduce such biases? In the present study, the focus is on consumer involvement and its relationship to heuristic information processing information processing: see data processing. information processing Acquisition, recording, organization, retrieval, display, and dissemination of information. Today the term usually refers to computer-based operations. . This study examines two questions: (1) to what degree can consumer biases and heuristics be reduced by increasing consumer involvement; and, (2) what factors can reduce biases and errors when consumer involvement does not. 2. LITERATURE REVIEW Heuristics was first introduced to the management science disciplines. Most previous research have focused on management level decision making, such as accounting, auditing, salesmanship, marketing (Cameron, 2001). Later on, the role of heuristics in consumer decision-making has been increasingly researched. However, the focus of such consumer research has been on how increasing involvement can reduce biases and errors (Na et al, 1999). According to according to prep. 1. As stated or indicated by; on the authority of: according to historians. 2. In keeping with: according to instructions. 3. Gray and Weft-Gray (1999), a study in salesmanship, during salespeople's heuristic process, increasing involvement did not help reduce some biases, such as those related to representativeness and availability. Do these kinds of biases also exist during consumer decision-making process? Kahneman and Tversky (1974) define representativeness as a rule that an individual uses to determine the probability of an outcome based on assessing how much a particular object resembles a class of objects. They describe availability as the tendency for people to assume the probability of "an event by the ease with which instances or occurrences can be brought to mind." Building upon these constructs, the current study postulates the following two hypotheses: H1a(b): The biases and errors caused by representativeness (availability) exist during consumer decision-making process. If these two hypotheses are affirmed af·firm v. af·firmed, af·firm·ing, af·firms v.tr. 1. To declare positively or firmly; maintain to be true. 2. To support or uphold the validity of; confirm. v.intr. , the related question is whether increasing involvement can reduce and eventually eliminate those biases. It has been shown that involvement does play a role during the consumer decision-making process. In a study on college student's purchasing behavior (Celsi and Olson, 1988), the results show that when the students had higher involvement, they spent more time attending to the information, and produced a greater number of thoughts in response to the information, and consequently made decisions with fewer mistakes and biases. However, the question is whether high involvement can help consumers reduce the biases and errors caused by representativeness and availability. According to the management science literature discussed above, a simple increase of involvement cannot help managers and salespeople sales·peo·ple pl.n. Persons who are employed to sell merchandise in a store or in a designated territory. reduce these biases and mistakes (Duchon, Ashmos, and Dunegan, 1991). If we assume a similar situation exists during consumer decision-making process, the following two hypotheses are developed: H2a(b): High-involvement consumers don't show significant difference from low-involvement consumers in terms of the biases and errors caused by representativeness (availability) during their decision-making process. Gray and Wert-Gray (1999) found that the use of a training program could help individual salespeople reduce reliance on certain heuristic strategies, such as representativeness. When training was conducted for experienced students who were asked to be judges to evaluate the quality of different soils, Gaeth and Shanteau (1984) found that the training was successful in reducing the influence of irrelevant information and in increasing the accuracy of the final judgments. In the case of the consumer, even where involvement is high, one may ask if training can minimize errors caused by representativeness and availability. Correspondingly, the following two hypotheses are developed: H3a(b): Training significantly lessens the biases and errors caused by representativeness (availability) during the consumer decision-making process. If training makes a significant difference for consumers to deal with the potential biases and errors caused by representativeness and availability, one may also ask whether the effectiveness of training is moderated by the level of involvement. In other words Adv. 1. in other words - otherwise stated; "in other words, we are broke" put differently , if both consumer A and B had training experiences and had the basic knowledge on representativeness and availability, and if consumer A has higher involvement than consumer B, are they going to show a difference in terms of their biases and errors caused by representativeness and availability? Since the current literature in the management disciplines shows that the biases and errors caused by representativeness and availability are only associated with training, we developed the following hypothesis: H4: There is no interaction between consumer's involvement level and training. 3. METHOD 3.1. Questionnaire Development The questionnaire has three sections. Section-I composed of 16 statements developed by Laurent and Kapferer (1985) to measure consumer involvement with a Liked scale (1=totally disagree and 5=totally agree). The summation summation n. the final argument of an attorney at the close of a trial in which he/she attempts to convince the judge and/or jury of the virtues of the client's case. (See: closing argument) of all the 16 items was used to represent the degree of involvement. The higher the total score, the higher involvement the respondents In the context of marketing research, a representative sample drawn from a larger population of people from whom information is collected and used to develop or confirm marketing strategy. have. Section-II included 8 questions developed to address the biases and errors caused by either representativeness (first 5 questions) or availability (the rest 3 questions). The number of questions answered wrongly by the respondent In Equity practice, the party who answers a bill or other proceeding in equity. The party against whom an appeal or motion, an application for a court order, is instituted and who is required to answer in order to protect his or her interests. represents the degree to which the respondent is prone to the respective biases. In order to control for consumers' familiarity with the products and brands, we chose one of the most common products, a shampoo shampoo a cleaning agent, usually liquid, for hair; usually consists of a detergent and perfume. Some, usually referred to as medicated shampoos, contain therapeutic substances such as parasiticides, antimicrobials, ketatolytic agents, and antiseborrheic compounds such as selenium , and gave a neutral fictional brand name for the product so as not to introduce differences of perception across genders, age groups, and social classes. Also, by choosing the fictional name of "Shine" for our product, we ensured brand familiarity would not become a confounding variable A confounding variable (also confounding factor, lurking variable, a confound, or confounder) is an extraneous variable in a statistical or research model that should have been experimentally controlled, but was not. among different subjects. One example of a question related to representativeness is as follows: Assuming that a current poll reports that 70% of consumers positively evaluate Shine Shampoo, while 30% negatively evaluate it based on its quality. One of your friends happens to buy one and finds that the quality of Shine Shampoo is not good at all. Will you think that Shine Shampoo is not likely to be of good quality? Yes or No. One example of a question related to availability is as follows: There have been all kinds of consumer reports on Shine during the last several month (both positive and negative). You happened to read one in a local newspaper yesterday, which commented on Shine in a negative way. If you just ran out of shampoo today and need to buy one now, are you going to buy Shine to give it a try instead of buying other brands? Yes or No. In the last section of the questionnaire, demographics were measured: age, gender, ethnic background, major, and current GPA GPA abbr. grade point average Noun 1. GPA - a measure of a student's academic achievement at a college or university; calculated by dividing the total number of grade points received by the total number attempted . 3.2 Data Collection and Sample Data were collected from students taking a general education (GE) class in a large Northern California public university in the spring of 2004. As a general education course, this class did not show any bias or tendency towards any major, gender, or age group. This GE class was offered in three different sections. In order to keep the training process consistent (so that same amount of information is provided in different sections), a 12-min video training tape was recorded in advance. The script in the videotape videotape Magnetic tape used to record visual images and sound, or the recording itself. There are two types of videotape recorders, the transverse (or quad) and the helical. was developed to address different biases related to either representativeness or availability. The concept was introduced first, followed by an example to illustrate the concept, and at the end, the correct answer was provided. The experiment was conducted in two phases. In Phase I, a group of 7 questions were used to test the subjects' basic statistical knowledge. Based on their answers to the 7 questions, each of the classes was equally divided into two groups possessing similar levels of knowledge regarding statistics. For example, if there were 30 subjects in one section got 5 out of 7 questions right, 15 of them were included in Group A and the other 15 were in Group B. In Phase II, Group A subjects were kept in the classroom to watch the training tape (training group), whereas Group B subjects were asked to leave the classroom without watching the tape (non-training group). Group B returned in 15 minutes. This strategy, allowed us to assume that there was no difference between Group A and Group B in terms of their statistical skills before the training. If there was difference between these two groups at the end, then training would be the reason for the difference. 4. DATA ANALYSIS 4.1 Preliminary Results Three hundred and nineteen out of 360 questionnaires were returned and were useful. One hundred and eighty of them were in the non-training group, and 139 were in the training group. The reason of why there were unequal numbers of subjects in the training group and non-training group is because phase two was conducted on a different day of the class from phase one. Some subjects who participated in phase one didn't show up for phase two. The average age of all the subjects was 23 years old, and 43.6% were male and 54.9% were female. The average GPA was 3.76 out of 5. 4.2 Hypotheses Testing Hypotheses 1a and 1b. A simple frequency analysis was used to test H1a and H1b. The results show that only 2.9% of the respondents answered all the five representativeness related questions correctly. More than 82% of them chose the wrong answer for 2 out of 5 questions. Meanwhile, close to 10% of the respondents answered all the three availability-related questions right, whereas close to 50% of them chose the wrong answer for 2 out of 3 questions. Therefore, the results do show that the biases caused by both representativeness and availability exist during the consumer decision-making process. Hypotheses 2a and 2b. A linear regression Linear regression A statistical technique for fitting a straight line to a set of data points. was used to test H2a and H2b. The total score of the representativeness-related questions was the dependent variable in H2a, the total score of the availability-related questions was the dependent variable in H2b, and the total score of involvement was the independent variable in both H2a and H2b. The results show that the level of consumer involvement does not significantly affect the biases caused by representativeness ([[F.bar].sub.(1, 308)] = 2.002, [p.bar] < .158, [R.sub.2] = 0.006), and the level of consumer involvement does not significantly affect the biases and errors caused by availability either ([[F.bar].sub.(1,311)] = 1.232, [p.bar] < .268, [R.sup.2] = 0.004). Therefore, both H2a and H2b are supported. Hypotheses 3a and 3b. A one-way ANOVA anova see analysis of variance. ANOVA Analysis of variance, see there was used to test H3a and H3b. Results revealed that training significantly lessens the biases and errors caused by representativeness ([F.sub.(1, 308)] = 29.465, [p.bar] < .000). Meanwhile, training also significantly lessens the biases and errors caused by availability ([F.sub.(1, 311]) = 18.015, [p.bar] < .000). Obviously, both H3a and H3b are supported. Hypothesis 4. In order to test H4, a linear regression was run separately for training group and non-training group. If in the training group, the level of involvement significantly affect the biases and errors caused by either representativeness or availability, and in the non-training group, the level of involvement significantly affect the biases and errors caused by either representativeness or availability as well, then there is an interaction between involvement and training. The results showed that none of the regression regression, in psychology: see defense mechanism. regression In statistics, a process for determining a line or curve that best represents the general trend of a data set. was significant (see Table 1). Therefore, H4 was supported. 5. CONCLUSION AND IMPLICATIONS In summary, we can draw the following conclusions from this study. The biases and errors caused by representativeness and availability exist in the consumer decision-making process. The level of a consumer's involvement does not affect all heuristic biases and errors. For example, high level of involvement does not reduce the biases and errors caused by representativeness and availability. Training does matter. Specifically, training consumers with the necessary statistical skills and knowledge can significantly reduce the biases and errors caused by representativeness and availability during the consumer decision-making process. There is no interaction between involvement and training. In other words, this study showed that in the training group, there is no significant difference between the high-involvement group and the low-involvement group. Similarly, in the non-training group, there is no significant difference between the high- and low-involvement groups. The results of this study hold potential for consumer research by providing a more complete framework of the consumer decision-making process. This study found that increasing the level of consumer involvement is ineffective in eliminating all heuristic biases; whereas, training does have the potential to affect a change in consumer decision making. Some type of heuristic biases and error, such as representativeness and availability, do not only exist in managerial and sales businesses, but occur during the individual consumer decision-making process. Retailers can improve the quality of their practice, through awareness of the results of this study, by better understanding when and how their target customers employ biases and make errors during decision making, as well as how to help them avoid those biases and errors. Obviously, for those biases and errors caused by representativeness and availability, it won't be a smart strategy for any business to spend substantial money trying to increase consumers' involvement levels. Rather, a more effective and powerful strategy would start from providing different formats of trainings to the target customers. Finally, the results of this study also bring valuable insights to individual consumers by helping consumers not only realize the potential reasons of some heuristic biases and errors, which are not simply caused by low involvement, but providing a clear direction of how to reduce and eliminate those biases and errors. Acknowledgement: This project is funded by 2004 Research and Creative Activity Award from California State University, Sacramento California State University, Sacramento, more commonly referred to as Sacramento State or Sac State, is a public university located in the city of Sacramento, California, USA. It is part of the California State University system. . REFERENCES Bettman, J. R. & Park, C. K (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, 234-248 Cameron, D. (2001). Chefs and occupational culture in a hotel chain: A grid-group analysis. Tourism and Hospitality Research, 3(2), 103-114 Capon, N. & Burke, M. (1980). Individual, product class, and task-related factors in consumer information processing. Journal of Consumer Research, 7(3), 314-26 Celsi, R.L. & Olson, J.C. (1988). 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It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the Canadian province of : The Guilford Press Darley, W.K. & Smith, R.E. (1995). Gender differences in information-processing strategies: an empirical test of the selectivity selectivity /se·lec·tiv·i·ty/ (se-lek-tiv´i-te) in pharmacology, the degree to which a dose of a drug produces the desired effect in relation to adverse effects. selectivity 1. model in advertising response. Journal of Advertising, 24(1), 41-56 Duchon, D., Ashmos, D., & Dunegan, K.J. (1991) Avoid decision making disaster by considering psychological bias. Review of Business, 13 (1), 13-18 Gaeth, G. J. & Shanteau, J. (1984). Reducing the influence of irrelevant information on experienced decision makers. Organizational Behavior and Human Performance, 33(Summer), 263-82. Gray, G. T., & Wert-Gray, S. (1999). Research note: Decision-making processes Presented below is a list of topics on decision-making and decision-making processes: | width="" align="left" valign="top" |
| width="" align="left" valign="top" | Importance of sales management is critical for any commercial organization. Expanding business in not possible without increasing sales volumes, and effective sales management goal is to organize sales team work in such a manner that ensures a , 19(3), 53-61 Johar, G.V., Jedidi, K. & Jacoby, J. (1997). A varying-parameter averaging model of online brand evaluations. Journal of Consumer Research, 24(2), 232-47 Johnson, E.J., Meyer, R.J. & Ghose, S. (1989). When choice models fall: Compensatory models in negatively correlated cor·re·late v. cor·re·lat·ed, cor·re·lat·ing, cor·re·lates v.tr. 1. To put or bring into causal, complementary, parallel, or reciprocal relation. 2. environments. Journal of Marketing Research, 26, 255-70 Johnson, E.J. & Russo, J.E. (1984). Product familiarity and learning new information, Journal of Consumer Research, 11, 542-50 Kahneman, D. & Tversky, A. (1974). Subjective probability: A judgment of representativeness. Cognitive Psychology cognitive psychology, school of psychology that examines internal mental processes such as problem solving, memory, and language. It had its foundations in the Gestalt psychology of Max Wertheimer, Wolfgang Köhler, and Kurt Koffka, and in the work of Jean , 3(July), 43054 Inman, J. J., McAlister, L., & Hoyer, W.D. (1990). Promotion signal: Proxy for a price cut? Journal of Consumer Research, 17(June), 74-81 Laurent, G. & Kapferer, J (1985). Measuring consumer involvement profiles. Journal of Marketing Research, 22, 41-53 Mantel, S.P. & Kardes, F.R. (1999). The role of direction of comparison, attribute-based processing, and attitude-based processing in consumer preference. Journal of Consumer Research, 25(3), 335-52 Na, W., Marshall, R., & Son, Y. (1999). An assessment of advertising agency service quality. Journal of Advertising Research, 39(3), 33-41 Dong Shen Shen, in the Bible, place, perhaps close to Bethel, near which Samuel set up the stone Ebenezer. , California State University, Sacramento, California California (kăl'ĭfôr`nyə), most populous state in the United States, located in the Far West; bordered by Oregon (N), Nevada and, across the Colorado River, Arizona (E), Mexico (S), and the Pacific Ocean (W). , USA Joseph Richards Joseph Richards was an Australian cricket Test match umpire. He umpired one Test match in 1931 between Australia and the West Indies at the Melbourne on 13 February to 14 January 1931, Australia taking just two days to win by an innings, with Don Bradman scoring 152 and Bert , California State University, Sacramento, California, USA Ernest Olson, California State University, Sacramento, California, USA Dr. Dong Shen earned her Ph.D. at the Ohio State University Ohio State University, main campus at Columbus; land-grant and state supported; coeducational; chartered 1870, opened 1873 as Ohio Agricultural and Mechanical College, renamed 1878. There are also campuses at Lima, Mansfield, Marion, and Newark. in 1999. Currently, she is an assistant professor at California State University, Sacramento. Dr. Joseph Richards earned his Ph.D. from Syracuse University Syracuse University, main campus at Syracuse, N.Y.; coeducational; chartered 1870, opened 1871. Syracuse is noted for its research programs in government and industry; facilities include the Center for Science and Technology, the Newhouse Communications Center, and , New York in 2001. Currently, he is an assistant professor at California State University, Sacramento. Dr. Ernest Olson earned his Ph.D. at the University of Illinois University of Illinois may refer to:
TABLE 1. ANOVA REPORT FOR HYPOTHESIS 4
Heuristics Group df F Sig.
Representativeness Non-training (1,170) .202 .653
Training (1,136) .647 .423
Availability Non-training (1,172) .968 .627
Training (1,137) .012 .913
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