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The hierarchy of consumer participation: knowledge and proficiency in telecommunications decision making.

The Hierarchy of Consumer Participation: Knowledge and Proficiency in Telecommunications Decision Making

Consumer research reveals a differential receptiveness on the part of consumers to the understanding and use of consumer information and education. Receptiveness to consumer education may vary according to (1) cognition, (2) social background characteristics, (3) occupational grouping, (4) participation in community affairs, (5) level of perception of consumer problems, (6) propensity to complain, and (7) information seeking methods (Bourgeois and Barnes 1976; Wackman and Ward 1976; Wilkie 1976; Hempel and McEwen 1976; Bloom 1976; Thorelli and Engledow 1980; Alder and Pittle 1984; Hyman 1986; Maynes 1988). Similar patterns have been identified for complaint behavior and participation (Hill 1982; Warland, Herrmann and Moore 1984; Hyman 1986, 1987; Miewald and Comer 1986; Kroll and Stampfl 1986; Price, Feick, and Higie 1987; Andreasen 1988).

Participation in American society also is not evenly distributed throughout the population. Those who participate in social, economic, and political affairs tend to reflect higher levels of income, education, and age (Verba and Nie 1972). Different patterns of participation have also been identified. Some citizens choose to remain outside, or on the periphery, of decision making. Others become intensely involved. A "hierarchy of political participation" has been identified (Milbrath 1965; Milbrath and Goel 1982). (1)

Previous research has tended to be discipline-based and to address specific aspects of either consumer behavior or political participation. This article takes a step toward synthesis by using the logic of the political participation model, and it examines several aspects of consumer decision making and consumer education in a single study. Four different sets of variables--knowledge about a decision area, independence of decision making, use of information, and propensity to influence others--are used to establish a "hierarchy of participation in consumer decision making," and the relationship to social background characteristics and the propensity to be aware of and take action on related consumer problems are examined. Data from an empirical study of mandated consumer decision making in the wake of the deregulation of telecommunications are used as the basis for a model that posits the existence of conceptually and empirically distinct subgroups based on a combination of variables related to proficiency in consumer decision making.

CONTEXT AND METHODS

Attendant to the deregulation of the telecommunications system in the United States, all consumers were required to make decisions in several areas in the year prior to this study. There was extensive coverage in the media and by consumer groups, regulators, and the telecommunications industry. Informational mailings and decision requests from the utility company went to each household. Thus, it is assumed that consumers had similar opportunities to know about the decision areas (although all consumers would not be expected to avail themselves equally of the opportunities). To the extent possible in a field situation, the time element, information availability, and opportunity to know are held constant. The situation provides a unique opportunity to examine consumer behavior in a quasi-experimental situation where one can make the assumption that everyone had an equivalent opportunity to know and to act, and everyone made a decision in a similar time frame.

Data for the analysis are from a 1985 representative statewide sample of residential telephone customers in Pennsylvania, the state with the fourth largest urban and the largest rural population. A telephone "penetration rate" of 97 percent in Pennsylvania means that for present purposes the full range of consumers had an opportunity to be included in the sample. The sample was selected by random digit dialing procedures using the operating ranges of numbers for each local exchange. This ensures that nonlisted numbers were included. Nonresidential consumers were screened out and are not considered part of the sample frame. Interviewers asked for the "person who makes decisions in your household about telephone decisions." Arrangements for call-backs were made if that person was not home. The response rate is 60 percent. A completed sample of 500 is the basis for the analysis.

The dependent variables consist of data on the respondents' recall of information and decisions related to four areas in which decisions were required: (1) knowledge of the new structure of the telecommunications industry as indicated by understanding the separation of long distance and local service systems, (2) customer premise equipment--the ownership of the phone itself, (3) local calling options--the payment or service plans offered by the local company, and (4) inside wire maintenance--the ownership of telephone wires within the respondent's home. All respondents made decisions in these four areas in the period preceding the study or someone else chose for them. (2)

A three-tiered hierarchy is used to assess the level of knowledge of each respondent. The research protocol calls first for respondents to be asked to explain their options in each decision area without prompting. Those who give incorrect answers are then read their options. The remainder are incorrect or "don't know" responses. The result is a three-level hierarchy of knowledge: recall, the ability to explain the options with no or little prompting (as with an essay exam); recognition, the ability to make a selection from a list (as with a multiple choice exam); and ignorance, incorrect responses on both of the above levels, as well as "don't know" responses (taking a default after being requested repeatedly to make an active decision is, in fact, a decision--or a "nondecision"). Consumers are then asked about the independence of their decisions, sources of information used, and their involvement in influencing others. Composite measures, scores or scales, are constructed by combining responses from several related items. These procedures provide the basis for examining the interaction of these dimensions of decison making.

FINDINGS AND RATIONALE FOR A DECISION-BASED HIERARCHY

OF PARTICIPATION IN DECISION MAKING

This section of the study tests the theory that more proficient consumer decision makers are more independent in decision making, they are more informed and educated, they have the appropriate knowledge and experience for consumer decision making, and they exhibit a higher propensity to affect the decisions of other consumers and those in positions of corporate and/or political authority. If these variables are interrelated and cumulative, there is a basis for inferring that a hierarchy exists.

Levels of Knowledge and Independence in Decision Making

The telephone ownership decision was chosen as a basis for exploring this issue for several reasons. All consumers were asked to make a choice in the period immediately before the study. It is a high visibility decision in that consumers are confronted daily in magazines, shopping centers, catalogs, and other media sources with offers of telephones to be purchased. Both industry and consumer groups had extensive information and education programs about this issue. Every consumer received information from his telephone company prior to making a decision. The Pennsylvania PUC and the Consumer Federation of America in Washington, D.C. both had toll-free information lines for consumers. Thus, every residential telecommunications consumer had the opportunity to know and to learn about this issue. Given the offer and the opportunity, those who are less informed are expected to have a lower propensity to perceive and use consumer information materials. The issue of whether they are less proficient in their consumer decision making is examined.

Knowledge of Premise Equipment and Independence of Decision

First, a majority of consumers (73 percent) are knowledgeable about their customer premise equipment. About one in three, however, needs to be prompted to recognize this option (20 percent) or is ignorant of this choice (7 percent). These data form the basis for examining independence and dependence in decision making.

Second, following questions about the level of knowledge for the telephone ownership decision, consumers identified the degree of independence of their decisions. Table 1 shows that about two out of three consumers report making their decisions entirely or mostly by themselves. About one in three reports receiving considerable help in making the decision.

The Information-Getting Propensity

Third, consumers indicated whether they "got information or advice regarding buying or leasing telephones" from any combination among six possible sources (and an "other" catchall). About half of the consumers (51 percent) report using telephone company information in their decision making. About a third use family or friends (39 percent), and a similar proportion use the print media (33 percent). About one-fourth use broadcast media (25 percent). Fewer than one percent report using information from government sources or community groups. Clearly, not all consumers use the same sources, and some consumers use more than one.

Zero to six different types of information sources could be named by each respondent. Totaling the types of sources of information used by each respondent, the "information-getting score" resulting signifies the propensity to use different sources of information in decision making. Table 2, showing the frequencies for the raw scores, indicates the most consumers report using one or two types, and few consumers report using four to six. This is as the theory suggests and provides a basis for the third part of the theory--use of information according to the independence of decision making.

Table 3 shows the relationship between the independence of the phone ownership decision and the information-getting score: the total number of sources of information the respondent reported using to make the decision. There is a clear pattern whereby those reporting greater independence in decision-making are also informed by more sources. Independence in consumer decision making is thus associated with utilizing more sources of consumer information. Conversely, those who allow someone else to decide for them use fewer sources of information, and they appear to be truly unknowledgable and dependent. The third part of the theory is supported.

Information Giving: The Propensity to Influence Others

The fourth and final hypothesis is that those who are more confident in their own decision making are resources for others, and some try to influence community or corporate policies. All respondents reported whether they told others about the phone ownership options, helped others make their decisions, and/or tried to influence policymakers about the issue. On the premise equipment decision, the majority (57 percent) do not give advice to others, complain to officials in the business involved, or express their opinions to political or community leaders. About one in three (36 percent) gives information and advice to acquaintances. About five percent complain to officials in the telephone company. Only a small percentage (less than two percent) contact community leaders, newspapers, magazines, or government leaders about the issue. Thus, most consumers are not involved in the decisions of others, nor are they active in complaining or trying to influence decision makers, but those involved in information giving or influencing exhibit a definite pattern. This being the case, there is a basis for examining whether those who take action to aid or influence others are more confident and proficient consumers.

Table 4 presents an analysis of the total of all advice and influencing responses. The resulting score is a measure of "propensity to influence others." As found above with propensity to seek information, advice-giving and influencing others are significantly related to higher levels of independence in personal decision making. Those who report higher levels of independence in decision making also report influencing others to a greater degree. (Note that the "influencing scores" are based on the number of different types of attempts to influence others, not the actual number of attempts at influence. An individual may have given advice to several others, which would be reported here as having been involved in one type of influencing.) Conversely, those who are more dependent on others for their decisions usually do not aid or influence others. This pattern is consistent with the previous pattern and supports the creation of a scale combining independence of decision making, use of information sources, and propensity to influence others.

The Consumer Decision-Making Scale (CDS)

To examine all four aspects of the theory together, a Consumer Decision-Making Scale (CDS) is constructed based on the level of knowledge, weighted first by the independence of decision, second by the propensity to use information (the information-getting score), and third by the propensity to influence the decisions of others (the influencing score). Table 5 shows the relationship between independence of decision making and a combined information-getting and influencing score.

The rationale for this relationship is based on the assumption that the variables of knowledge, information, and behavior will be interrelated. First, consumers who are more knowledgeable about a topic may be more or less independent in their decision making. This study finds the former to be the case. Second, greater knowledge will be related to a higher propensity to seek information about the topic. Finally, higher levels of information seeking will be related to giving information and advice to others. Table 5 shows that the relationships observed above with separate variables also hold when the scores are interrelated. (3)

Previous studies found differences among consumers on each of these different variables. This study shows that there is a clear statistically significant pattern across all variables and that high scores on one are related to high scores on the others. Consumers who exhibit greater knowledge and independence in their own decision making have higher than average tendencies both to get information from a variety of sources and to influence others. These data provide support for the construction of a Consumer Decision-Making Scale (CDS) based on combining the scores for knowledge level, independence of decision, information getting, and influencing. (4) The CDS is used below to examine the relationship between proficiency in consumer decision making and other relevant variables. For purposes of analysis, four levels of proficiency are established. (5) Figure 1 shows the distribution of final CDS scores and the four groupings used for analysis. This is not a bell-shaped "normal" distribution but one that is bi- or tri-modal. Low scores on the CDS are associated with low consumer proficiency and vice versa.

Social Background and Consumer Proficiency

The social background of consumers in each of the levels of the consumer decision scale (CDS) is informative regarding the targets and need for action and the approaches required for successful implementation. In particular, data on age, education, and household income provide insights into the dynamics of consumer decision making. (6)

Age

Table 6 shows that proficiency in decision making is related to the age of the consumer. Significantly higher proportions of older consumers rank low on the decision-making scale. While there is a progression across the age groupings, the major differences emerge with those 45 and older. Thus, younger consumers tend to be more proficient in their decision making. They exhibit more independence in making choices, and they report using more types of information sources and attempting to help or influence the decisions of others more.

Education

The education of consumers also shows a statistically significant relationship with proficiency in decision making (Table 7). Consumers with more than a high school education score higher on the CDS than do those with a high school education or less. Twice as many of the groupings with high school education or less score low on the scale, and those with more than a high school education are more than twice as likely to score in the higher levels of proficiency in decision making.

Income

The total household income of respondents is not significantly related to their levels on the CDS, although a pattern is suggested. Table 8 Part A shows the percentages scoring low, moderate, or high on the consumer decision scale for four major income groupings. Very few consumers with incomes less than $10,000 score high on the scale, and the converse is true for those with incomes $20,000 and above; these differences fall short of significance at the 0.05 level.

Analysis of position on the CDS by poverty status approaches significance but remains below the generally accepted level. Poverty level is measured by classifying consumers according to whether they are below 150 percent of the Federal poverty level for the state. It adjusts household income for family size. Table 8 Part B shows that differences exist, but they are not significant at the 0.05 level of significance. (Education is a confounding variable because of its relationship to income, thus further supporting the idea that income alone is not significant.)

THE CONSUMER DECISION SCALE AND ASSOCIATED DECISIONS

If a relationship exists between the consumer decision scale (CDS) and other telecommunications decisions, one can begin to make inferences to more general areas and provide support for a theoretical consumer decision-making hierarchy. The CDS is based on a single decision area; it may represent a unique phenomenon. If, however, higher scores on the hierarchy are associated with higher levels of consumer knowledge in other areas, there is an empirical basis for inferring that a general pattern exists. This section examines this relationship.

Table 9 shows the levels of consumer knowledge on three telecommunications decisions and knowledge of the body responsible for regulating utilities in Pennsylvania (this last variable is introduced to test the relationship of the CDS to an even more general area). Based on the tripartite distinction on level of knowledge--recall, recognition, ignorance--the table shows different levels of knowledge among consumers for different decision areas.

The table lists the decisions with the higher aggregate levels of recall first, followed by lower levels. The consuming public is most informed about the phone ownership decision, with three out of four respondents being able to explain their options without prompting. There are lower levels of recall for the inside wire maintenance choice and understanding of the regulatory system. The level of recall is lowest for local phone service options, with fewer than one out of five consumers being able to name two or more of the three options that were available to them (and from which they had made a choice, including defaults, in the year preceding the study).

Table 10 shows the relationship between consumers' levels on the CDS and their knowledge levels on the two other telecommunications decisions. There is a significant relationship between the CDS and knowledge in both areas. Thus, a pattern across decisions is inferred.

The general nature of the pattern gains additional support through examination of the relationship of a combined "telecommunications decision index" to the CDS. (7) Table 11 shows that a statistically significant relationship exists between a telecommunications decision index and the consumer decision scale (CDS). Consumers who score low on the CDS tend to have lower levels of telecommunications knowledge across all decisions and vice versa.

Further support for the generalizability of the CDS is provided in Table 12, which depicts the relationship between the consumer decision scale and awareness of a more general actor in the telecommunications regulatory system--knowledge of the utility regulatory body. Again, those consumers with higher decision scale scores also have higher levels of knowledge about the regulatory system. A logical inference is that people who score higher on the CDS have a comparative advantage both in the marketplace and in the regulatory arena. They are expected to be more proficient in making wise choices and exercising their consumer rights and responsibilities.

IMPLICATIONS FOR THE FIELD: A HIERARCHY

OF PARTICIPATION IN CONSUMER DECISION MAKING

Consumers are not equally independent in their decision making; they are not equally well informed; they do not use the same sources of information, nor do they equally attempt to influence others. Most importantly, level of knowledge, decision independence, propensity to use information sources, and propensity to influence others are significantly interrelated. The findings of this study, in conjunction with previous studies, provide a basis for a "hierarchy of consumer participation" with levels comparable to the hierarchy of political participation developed by Milbrath (1965, 1982). Four ideal types of consumers are identified: consumer influentials, active consumers, dependent consumers, and nondecision makers. (8)

Figure 2 is a graphic depiction of the hierarchy of consumer participation. The different levels represent points on a continuum. Consumer proficiency increases as one moves up the hierarchy. Participation is considered cumulative, in that consumers who engage in the topmost behaviors are likely to have done or considered those in lower levels. Conversely, those who engage in the lower-level behaviors would be expected to confine their activities to those ranking low on the hierarchy.

The hierarchy includes most common consumer activities related to making and influencing decisions. The hierarchy does not include consumer complaining, which has been shown to reflect a similar hierarchical pattern (Warland, Herrmann, and Moore 1984). As is also the case with Milbrath's hierarchy, behaviors higher in the hierarchy tend to require greater expenditures of energy and commitment. Fewer people are expected to be involved in the higher levels than those lower on the hierarchy. Finally, there also seems to be a logical progression from doing little or nothing to affect one's situation, to being involved with personal consequences, and to attempt to influence the way things are done.

Consumer influentials are both active and proactive--they make their own decisions using a variety of sources of information, and they are also involved in influencing the decisions of others. At lower levels, influentials give information and advice to family, friends, and acquaintances. At higher levels, they seek to influence seller practices, community action, and/or public policy. Consumer influentials exhibit the characteristics of leaders, whether this leadership is in relation to a close circle of significant others or to broader corporate and public policy circles. Consumer influentials are open to, and most likely seek, information about options, and they are sought out by others for information and advice. These individuals are not only targets for consumer information and education, but also they provide a reservoir of talent, motivation, and leadership for informing others and influencing policies and programs.

Active consumers are informed consumers to varying degrees--they make their own decisions based on information from one or more sources. At lower levels on the hierarchy, these consumers may get help from others or decide conjointly with others. At higher levels, their decisions will be generally independent of others, based on information from one or more sources. Active consumers tend to make their own decisions, and they make them based on various degrees of knowledge of options open to them. They tend to be reasonably knowledgeable about their options, and their concerns are more for their own decisions than for others.

Dependent consumers let others decide for them--they uncritically do what significant others do or tell them to do. Their decisions tend to be made without direct personal consideration of information or evaluation of options. To the extent that the decision leaders to whom they defer understand their situation and have their interests foremost (as with a parent, close friend, or community helper), the final outcomes will most likely be positive. To the extent that the decision leaders have their own (or their business') interest foremost, as with sellers or advertisers, or at least are unconcerned about the interest of the dependent consumer, the final outcomes will be negative or, at best, benign.

Nondecision makers are proxy decision makers--they do not take an active part in their decisions and, typically by default, someone else decides for them. At the "lowest" level, they are uninformed about the decision area, apparently do not care, and when offered a choice, take no action. By default, they frequently give the seller a proxy to decide for them, or they go without the product or service if no default exists. These people are, perhaps, the most problematic from both personal and social perspectives. Their health and safety may be threatened by the consequences of nondecisions. Some are capable decision makers who choose not to decide. Many are not. They may be unable to afford the goods or services provided by default. Such nondecision makers may command resources that they cannot use or that will be used indiscriminately. When such situations occur, individual harm leads to pain and suffering and increased requirements for other resources such as hospital, public health, police, fire, income assistance, and other protective services. Companies may need to expend significantly higher resources in collections, complaint handling, monitoring, restitution, and protective services. The public finds itself in the dilemma of either allowing social and personal costs to accrue or covering the cost of protecting these people from negative consequences of their inaction.

Program and Policy Implications of the Hierarchy

The hierarchy of ideal types of consumers provides a framework for synthesis of research findings and a guide to further inquiry and action. The levels of consumer participation, based on proficiency and initiative in decision making, are expected to be highly salient in defining targets for consumer action--whether it be research, education, protection, or policy. Nondecision makers require either consumer protection by official bodies or fundamental, in-depth education about how and why they need to make wise decisions, as well as information about options for specific decisions. In general, these consumers need protection if they are to be spared the vicissitudes of the marketplace. Dependent consumers must have knowledgeable, interested, and trusted consumer influentials who are readily available when decisions are to be made. They, too, might benefit from fundamental, in-depth, consumer education. Otherwise, either private corporate or regulatory practices must ensure that the defaults and dominant choices available will have either positive or benign outcomes. Active consumers are the primary target for consumer information and education. Their varying degrees of openness to information, different levels of proficiency, and use of different distribution media must all be considered in designing and implementing programs and policies. Consumer influentials generally seek out information on their own and are open to a variety of sophisticated approaches. They are potential targets for detailed information as they will become the sources used by others in making decisions. In addition, these consumer leader types provide a reservoir of interest and talent for developing and revising policies and programs. They may become involved in changing policies or directions of agencies, corporations, or organizations.

Some Key Research Issues

Important unanswered questions deal with the generalizability of the phenomena observed. Other research leads to questions related to other consumer areas (Maynes 1988), adoption of new ideas (Rogers and Shoemaker 1971), and sociopolitical participation (Verba and Nie 1972; Milbrath 1982). First, the study calls for research into whether consumers, especially the dependent consumers and nondecision makers, behave similarly across other product and service decisions. If nondecision makers are informationally disadvantaged across all product categories, there are important implications in an "information age" market-based system that assumes considerable sophistication on the part of consumers. Is this a general phenomenon, or is it unique to telecommunications? Second, the extent to which consumer actives and influentials are generalists or specialists remains to be examined. Are they also higher-level participants in other sectors? Third, the relationship between consumer decision making and other areas of consumer behavior such as problem perception and complaining behavior needs to be explored. Finally, research on the relationship between the patterns identified herein and general sociopolitical behavior requires examination and documentation. These are crucial questions, for they address patterns of choice and bias, and if research shows that the pattern generalizes to other areas, issues of comparative advantage and ultimately status and power are involved.

CONCLUSIONS

The preceding analyses identify a cumulative character to consumer capabilities and levels of participation in decision making. Social background, achievement in education, consumer knowledge and competence, and decisions in the marketplace are highly interrelated. The comparative advantage enjoyed by some is counterbalanced by the relative disadvantage of others. The existence of an "underclass" may be more pervasive and deeply rooted than otherwise presumed.

A persistent and pervasive relationship exists between micro-level consumer decision making in specific areas, behavior in seeking and using information, and influencing corporate and public policy and practice. This study suggests that patterns of participation, knowledge seeking, and decision making are deeply rooted in the sociopolitical personalities of consumers. This phenomenon, in turn, is expected to create differential patterns of bias in the American political and economic culture.

Empirical data support the creation of a "hierarchy of consumer participation" in one area, with a high probability that it represents a more general phenomenon. Significant relationships are demonstrated between consumer decision making, propensity to use information for decisions, propensity to influence others, and social background characteristics. Thus a synthesis of knowledge from several fields including political science, sociology, consumer economics, and education, as well as among concepts of participation, political culture, socialization, information seeking, and decision making, is approached. The results should be useful methodologically, theoretically, and practically for research, program design, and public policy analysis.

One reviewer points out the parallels of this research to studies of the diffusion of innovations. The literature on the use of communications in decision making during the adoption of innovations also finds hierarchically patterned variations. For example, Rogers and Shoemaker (1971) find that early adopters of innovations have greater knowledge, seek information more, have more change agent, and have more mass media contact than late adopters and laggards. Since this literature did not underlie the present study, it is not discussed herein. However, the readers, especially those considering followup research, are referred to this body of knowledge.

(2) Since this is a statewide study, there was no control for the company variable. About three-fourths of Pennsylvania consumers are customers of one company, with the remainder divided among several smaller companies. Separate analysis of the primary versus smaller companies shows no statistically significant (chi-square at the 0.05 level or better) differences in the sample for age, education, and income. Some differences are found on knowledge questions.

Observed differences on satisfaction, sources of information, adequacy of information, and believability are not statistically significant at the 0.05 level. Appropriate adjustments are made on knowledge questions to account for different company policies on the local options and wire maintenance variables.

(3) These data were examined using several methods of scale construction. Each revealed similar relationships to those described herein. Analysis of the relationship of information-getting scores to influencing scores shows that those with higher getting scores tend to have higher influencing scores--the pattern is pervasive. The final scores reported are thus based on the product of the total information-getting score and the total influencing score for each respondent. This approach ensures that influencing is not equated to getting, as with a simple sum.

(4) The CDS scale is the product of: level of knowledge (K) weighted by (1) the level of decision independence (6 = all by self . . . to 1 = default) and (2) the information-getting score (1 + the sum of the information sources used in the decision) multiplied by (3) the influencing score (1 + the sum of the influencing responses). CDS = {[(K * 1) * 2] * (3)}.

(5) The pattern presented in Table 5 is maintained, as well as the need for relatively equivalent proportions for statistical analysis. The final scores range from 1 to 144. Examination of the frequencies for raw scores in relation to the pattern presented in Table 5 suggests that four categories are adequate. There are breaks (no observations) between 11-12, 21-24, and 41-45. The groupings used herein are as follows: Low = 1-10 CDS score (n = 166); Moderate 1 = 11-20 CDS score (N = 159); Moderate 2 = 21-40 CDS score (N = 166); High = 41-144 CDS score (N = 46).

(6) These findings reflect the patterns identified by Thorelli and Engledow (1980).

(7) The telecommunications decision index reflects a combined score for each respondent of the levels of knowledge for four areas: local options, wire maintenance, premise equipment, and ability to identify correctly both local and long distance companies. Levels are coded as: recall = 3, recognition = 2, and ignorance = 1.

(8) Ideal types are conceptualizations based on observations of reality, in this case the empirical analysis, in order to facilitate comparisons. They are constructed by logically abstracting characteristics of the phenomenon under consideration. The main levels of the hierarchy are inferred and considered conceptually parallel to Milbrath's (1965) levels of political involvement (apathetics, spectator activities, transitional activities, and gladiatorial activities).

REFERENCES

Alder, Robert S. and R. David Pittle (1984), "Cajolery or Command: Are Education Campaigns an Adequate Substitute for Regulation?" Yale Journal on Regulation, 1:159-193.

Andreasen, Alan R. (1988), "Consumer Complaints and Redress: What We Know and What We Don't Know," in The Frontier of Research in the Consumer Interest, E. Scott Maynes (ed.), Columbia, MO: American Council on Consumer Interests:675-722.

Bloom, Paul N. (1976), "How Will Consumer Education Affect Consumer Behavior?" Advances in Consumer Research, Urbana, IL: Association for Consumer Research:202-218.

Bourgeois, Jacques C. and James G. Barnes (1976), "Consumer Activists: What Makes Them Different?" Advances in Consumer Research, Urbana, IL: Association for Consumer Research:73-80.

Hempel, Donald and William McEwen (1976), "The Impact of Mobility and Social Integration on Information Seeking," Advances in Consumer Research, Urbana, IL: Association for Consumer Research:341-347.

Hill, Larry (1982), "Bureaucratic Monitoring Mechanisms," The Public Encounter, Charles Goodsell (ed.), Bloomington, IN: Indiana University Press:160-186.

Hyman, Drew (1986), "Prosuming, Participation, Consumer Education and the Deregulation of Telecommunications," The Journal of Voluntary Action Research, 15(3) (July-September):7-23.

Hyman, Drew (1987), "Citizen Complaints as Social Indicators: The Negative Feedback Model of Accountability," The Ombudsman Journal:47-65.

Kroll, Robert J. and Ronald W. Stampfl (1986), "Orientations Toward Consumerism," The Journal of Consumer Affairs 20(2) (Winter):214-230.

Maynes E. Scott (ed.) (1988), The Frontier of Research in the Consumer Interest, Columbia, MO: American Council on Consumer Interests.

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Milbrath, Lester W. and M.L. Goel (1982), Political Participation, 2nd edition, New York, NY: University Press.

Price, Linda L., Lawrence F. Feick, and Robin A. Higie (1987), "Information Sensitive Consumers and Market Information," The Journal of Consumer Affairs, 21(2) (Winter):328-341.

Rogers, Everett M., with F. Floyd Shoemaker (1971), Communication of Innovations, New York, NY: The Free Press.

Thorelli, Hans B. and Jack L. Engledow (1980), "Information Seekers and Information Systems: A Policy Perspective," Journal of Marketing, 44(2) (Spring):9-27.

Verba, Sidney, and Norman H. Nie (1972), Participation in America, New York, NY: Harper and Row.

Wackman, Daniel B., Scott Ward, and Marketing Science Institute (1976), "The Development of Consumer Information-Processing Skills," Advances in Consumer Research, Urbana, IL: Association for Consumer Research:531-535.

Warland, Rex H., Robert O. Herrmann, and D.E. Moore (1984), "Consumer Complaining and Community Involvement," The Journal of Consumer Affairs 18(1): 64-78.

Wilkie, William L. (1976), "Consumer Information Acquisition: Public Policy Perspectives," Advances in Consumer Research, Urbana, IL: Association for Consumer Research: 334-340.

Drew Hyman is a Professor of Public Policy and Community Systems in the Department of Agricultural Economics and Rural Sociology, The Pennsylvania State University, University Park, PA.
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