Energy Conservation: Overview

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------------------------------------------------- A Study of Factors Influencing Energy Conservation Behavior Richard Semenik, University of Utah Russell Belk, University of Utah John Painter, University of Utah ABSTRACT - Previous research on factors that influence energy conservation behavior have almost without exception been restricted to demographic investigations using bivariate analyses. The present study attempts to go beyond prior research by using a richer set of non-demographic predictors in the context of gasoline conservation.

Multivariate analysis of the predictors suggests that greater understanding of conserver and non-conserver groups can be achieved with a broader set of predictor variables. [ to cite ]: Richard Semenik, Russell Belk, and John Painter (1982) ,"A Study of Factors Influencing Energy Conservation Behavior", in NA - Advances in Consumer Research Volume 09, eds. Andrew Mitchell, Ann Abor, MI : Association for Consumer Research, Pages: 306-312. Advances in Consumer Research Volume 9, 1982 Pages 306-312 A STUDY OF FACTORS INFLUENCING ENERGY CONSERVATION BEHAVIOR Richard Semenik, University of Utah

Russell Belk, University of Utah John Painter, University of Utah ABSTRACT - Previous research on factors that influence energy conservation behavior have almost without exception been restricted to demographic investigations using bivariate analyses. The present study attempts to go beyond prior research by using a richer set of non-demographic predictors in the context of gasoline conservation. Multivariate analysis of the predictors suggests that greater understanding of conserver and non-conserver groups can be achieved with a broader set of predictor variables.

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INTRODUCTION The energy problems first highlighted by the 1973-74 gasoline and fuel oil shortages have spawned a considerable number of research efforts on the topic of energy conservation. Reviews by Anderson and Cullen (1979), Farhar, et al. (1979), Frankena, Buttell, and Morrison (1977), and Joerges (1979) classify over 300 energy consumption studies conducted during the Seventies. A major thrust in many of these studies has been the detection of factors affecting energy conservation.

Such a focus on understanding who conserves and why they do so, is of obvious concern for formulating realistic public policies, effectively encouraging energy conservation, and recognizing problems in operationalizing energy conservation plans. However, despite the fact that a number of studies have been directed at finding correlates of energy conservation attitudes and behavior their findings have generally been weak and often contradictory. The following sections review the findings for the major categories of predictors which have been examined and discusses reasons for the inconsistencies.

FACTORS RELATED TO INDIVIDUAL ENERGY CONSERVATION Income The one factor most studied for its relationship to energy conservation has been income. Income-related influences on conservation or non-conservation of energy seem to be sufficient to have created a confusing set of findings. Based on general indices or questions about energy conservation behavior some studies have found positive associations between energy conservation and income (Grier, 1976; Talarzyk and Omura, 1974) and between energy conservation and social class (Bultena, 1976).

However other studies have found negative associations between energy conservation and income (Cunningham and Lopreato, 1977; Opinion Research Corporation, 1975c) as well as between energy conservation and social class (Gottlieb and Matre, 1975)o Still other studies have found that the middle income classes report the greatest level of energy conservation (Warren and Cliffords 1975; Kilkeary, 1975).

And still other studies report no significant relationship between energy conservation and income (Hogan, 1976; Bartel, 1974). The same inconsistent pattern of findings has emerged when conservation of specific type of energy have been examined separately. For home heating conservation, the largest number of studies have found a positive association between income and conservation behaviors (Morrison and Gladhart, 1976; Murray et al. , 1974; Perlman and Warren, 1975a, 1975b; Reizenstein and Barnaby, 1976).

Nevertheless, there are again exceptions with some studies showing lower income households conserving more heating fuel (Newman and Day, 1975; WaLker and Draper, 1975) and some showing middle income households conserving more (Warkov, 1976), or that some heating conservation actions are more likely in low income households, while other heating conservation actions are more likely in high income households (Opinion Research Corporation, 1974b).

The same inconsistency occurs for studies examining various aspects of gasoline energy conservation, except that in this case the preponderance of evidence shows a negative association between income and conservation (Gallup, 1977a; Opinion Research Corporation, 1976b; Roper, 1977a; Barnaby and Reizenstein, 1977; Newman and Day, 1975). The contradictory evidence either shows a positive association (Roper, 1977b; Murray, et al. 1974; Perlman and Warren, 1975a; Reizenstein and Barnaby 1976), a curvilinear association (Warkov, 1976), or no significant association between income and automobile-related energy conservation (Opinion Research Corporation. 1974c). Education The general expectation here would be that education and conservation would be positively associated. However a major complicating factor may be the positive association between education and income.

Whether due to this association or to a similarity of energy conservation attitudes across education levels, the studies examining this variable again provide mixed results As expected the largest number of studies have obtained a positive association between education and conservation actions (Roper, 1977b; Survey Research Laboratory,1977; Reizenstein and Barnaby, 1976; Thompson and MacTavish, 1976; Gallup, 1977a).

The exceptions consist of findings of a curvilinear relationship between education and energy conservation (Cunningham and Lopreato, 1977), findings of a negative relationship (Opinion Research Corporation, 1974a, 1975a, 1975c), and findings of no significant education/ conservation relationship (Murray, et al. , 1974; Hogan, 1976) e Occupation Occupation has been studied less frequently and one reason may be that there is less of an intuitive basis for hypothesizing a relationship between occupation and energy conservation. The studies which have obtained a ignificant relationship between occupation and energy conservation practices and attitudes have found greater conservation by those with higher status occupations (Thompson and MacTavish, 1976; Opinion Research Corporation, 1975d). Other studies have found no differences in energy conservation by different occupational groups (Lowry and Good, 1977; Gallup 1974, 1977a). Some research has found little difference in overall conservation tendencies between occupational groups, but has found the nature of their conservation efforts to differ.

For example, one study found that those in business and professional occupations reported a greater tendency to turn down home thermostats in cold weather, while clerical, sales and manual labor workers reported a greater tendency to turn off unused lights at home (Gallup, 1977b); Overall however, occupation does not appear to be a good predictor of energy conservation. Age Given the relationship between age and income, it might be expected that the young and old would find the greatest economic incentive for energy conservation, with less of this motivation among middle ages. But given that many energy-conserving behaviors (e. . walking, bicycling, turning down winter thermostats and turning up summer thermostats) may be less feasible for those in poor health, there are greater constraints acting on older consumers who might otherwise be more inclined to conserve through such behaviors. In terms of baseline rates of energy usage, it appears that middle-aged families (especially with children) have the highest levels of energy consumption, and therefore the greatest opportunity to conserve (Morrison and Gladhart, 1976). These mixed expectations are borne out by mixed findings relating energy conservation and age.

For instance, Talarzyk and Omura (1974) report the least resistance to the idea of energy conservation by older consumers, but the greatest number of energy conservation activities by middle age consumers. Cunningham and Lopreato (1977) found the oldest and youngest consumers most likely to conserve, but also found that for some conservation behaviors there was a positive association with age and for others there was a negative age association. While such mixed findings are typical (e. g. Roper, 1977b), other studies report finding no significant relationship between age and energy conservation (Hogan, 1976; KiLkeary, 1975; Bartel, 1974).

Thus age has also failed to act as a consistently good predictor of energy conservation. Family Life Cycle As suggested in the comments concerning the related variable of age, larger families with middle aged parents tend to consume larger amounts of energy (Morrison and Gladhart 1976). While this argument suggests greater opportunities for energy conservation by such households, there are also some countervailing forces. One is that a larger, less fuel efficient automobile may be more of a necessity for larger families.

Similarly, to the extent that energy conservation requires some sacrifice, it may be more difficult in our society to deprive children of some energy-consuming activity than it is to deprive self or self and spouse alone. But another countervailing force in the opposite direction may be that children receive more conservation information in school than their parents did and bring this information and related conservation attitudes home (Opinion Research Corporation, 1976b). Once again we are left with unclear expectations about the relationship of the family life cycle variable and energy conservation.

Even within the area of gasoline conservation, some studies have found conservation more likely among married persons (Burdge, 1975) while others have found conservation more likely among singles (Roper, 1977b). Similarly, some studies have found greater (gasoline) conservation by families with fewer children (Roper, 1977b), while other studies have found greater (general energy) conservation by families with more children (Kilkearny, 1975). Still other studies have found no significant relationship between energy conservation and family composition or size (Hogan, 1976: Morrison 19775.

Gender Expectations for the effect of gender on attitudes toward various conservation practices are difficult to formulate. Farhar et al. , (1979) speculate that home-related energy conservation in heating and appliance use may threaten the traditional role of the woman in providing family comfort. However, several studies show women more favorable toward energy conservation in the home than men (Opinion Research Corporation, 1975b, 1976a; Cunningham and Lopreato, 1977). Other studies find no differences in such attitudes (Bartel, 1974). Within the domain of gasoline-conserving ehaviors, some studies show males to be less favorable (Opinion Research Corporation, 1976a) while others show females to be less favorable (Gallup, 1977a). Again the literature fails to uncover consistent relationships between energy conservation and a potential predictor variable. Other Factors Related to Energy Conservation To a lesser extent, other demographic variables have been examined as predictors of energy conservation behavior Race has been examined with some sort of inconsistencies or no difference in behavior result between blacks and whites (Newman and Day, 1975; Cunningham and Lopreato, 1977).

Political party affiliation has also been examined and in some cases Democrats appear more conserving (Opinion Research Corporation, 1975c) and in other cases Republicans appear more conserving (Gallup, 1977a). Urban versus rural area of residence has been examined with little consistency in results. In some studies, rural residents are more conserving (Blakely, 1976; Morrison, 1977), in others urban residents are more conserving (Opinion Research Corporation, 1975d, 1976a), and in others no difference was found (Hogan, 1976).

Some studies have gone beyond demographic variables in search for predictors of conservation. One study (Reizenstein and Barnaby, 1976) found media exposure and personal sources of information better predictors of conservation attitudes than demographics. Several studies have used activity, interest, and opinion (AIO) variables to predict energy conservation (Morrison, 1977; Barnaby and Reizenstein, 1977; Talarzyk, 1974). Although the results of these studies have found some significant relationships, the substantial differences in AIO items used preclude any generalization of effects of lifestyle on conservation.

REASONS FOR INCONSISTENT FINDINGS Several explanations are possible for the contradictory and inconsistent findings of studies seeking factors related to energy conservation. Two explanations offered by both Farhar et al. , (1979) and Anderson and Cullen (1979), are that there are numerous measures and categorizations of independent variables in these studies and that the dependent variable (energy conservation) has also been operationalized in a number of ways. These do not seem to be adequate to explain all of the anomalies found in the literature.

While different categorizations and measures of independent variables may explain why a variable is a significant predictor of conservation in some studies but not in others, it does not explain why the same relationships are positive in same studies and negative in others. Another explanation which might be suggested is that the samples and time periods of the various studies were different. However, there are also shortcomings to this explanation. The review by Farhar et al. , (1979) finds little in the way of regional differences in energy conservation findings.

Even though all relevant studies have been conducted during the 1970's, there may be enough volatility in attitudes and behavior during this period that studies of several different years could obtain different findings. However, the series of longitudinal studies reviewed by Murray et al. , (1974) would seem to discount this argument since most of the variables remained relativelY stable. The foregoing explanations may go part way toward explaining the differences in findings obtained, but there is another more compelling explanation.

In nearly every instance there are opposing conceptual expectations concerning the nature of the relationship between the predictor variable and conservation of energy. It may well be that the combination of these opposing forces has been sufficient to cause different and even opposite findings in studies with somewhat different samples. Since some of the opposing expectations arise from the correlations between a predictor variable and another variable, a sample which is more homogeneous in such a third variable (e. g. income) than another sample may cause an apparent reversal of the relationship between the predictor variable (e. . education) and energy conservation. With very few exceptions (e. g. Reizenstein and Barnaby, 1976), previous studies have used bivariate rather than multivariate methods in order to examine the relationships of interest. One of the improvements offered in the present paper is to employ a multivariate method in order to go beyond the limitations of the largely bivariate prior studies. In addition, the present paper seeks a richer set of predictor variables than the largely demographic variables employed in prior research.

The primary non-demographic sets of variables added were (1) beliefs about the nature and causes of the energy crisis (often investigated as dependent variables, but not as independent variables), (2) preferences for different energy-related actions, and (3) media exposure variables. No previous study has simultaneously investigated these types of variables. METHODOLOGY In an effort to investigate a wide variety of variables and their effect on gasoline consumption, a sample of 253 heads of households who travel over 150 miles per month was selected using a cluster sampling technique.

The data were collected in Salt Lake City, Utah in the spring and summer of 1979 during a period of pronounced shortages and price increases. A structured questionnaire administered by trained interviewers was used to gather information on a variety of potential predictor variables and demographic information. Questions were carefully worded to avoid potential demand characteristics that could result from "socially acceptable" response options. As discussed above, three primary non-demographic sets of variables were included in the data collection.

In addition, current gasoline consumption behaviors and demographic variables were also identified. The five total categories of variables and the dimensions for data gathered in each category are displayed in Table 1. The rationale for choosing to investigate variables in these categories stem from several influences. First, the previous research, discussed at the outset of this paper, tented to narrowly define the potential influences on consumption behavior. The categories used in this study attempt to broaden the base of investigation of potential influences.

Second, the types of variables examined in earlier works provided a foundation for the categories of variables used here. Earlier studies were relied on for choosing variables to examine within categories. Finally, since there is an issue related to using demographics versus other types of variables to predict energy-related behaviors, demographics were also included in the investigation. RESULTS The main purpose of data analysis was to identify factors that influence gasoline conservation behavior. The initial step in this procedure was to classify respondents as either conservers or non-conservers of gasoline by virtue of various behaviors.

The behaviors used to classify respondents were: 1. estimated mpg of the auto being driven 2. consuming less gasoline than six months ago 3. consuming less gasoline than five years ago 4. currently riding in a car pool 5. moving to a residence closer to work to help conserve gas 6. increase in bus usage TABLE 1 NEANS AND UNIVARIATE F SCORES FOR VARIABLES CONSIDERED AS PREDICTORS If a respondent was engaging in two or more conservation behaviors with regard to the above set of variables, the decision rule was to classify this respondent as a conserver.

Respondents engaging in less than two conservation behaviors or behaving in a fashion that indicated increased consumption of gasoline were categorized as non-conservers. On the basis of reported behavior, 83 respondents were classified as conservers and 75 as non-conservers. The remaining 95 respondents were unclassified by virtue of demonstrating contradictory conservation and non-conservation behaviors. In an effort to verify this grouping procedure and thereby establish that legitimately different groups were formed by the process 9 a discriminant analysis was performed on the newly formed conserver and non-conserver groups.

The discriminant analysis indicated that each of the variables discussed earlier which were used in the group forming process produced significant (p;. 01) differences between conservers and non-conservers. The most important variables in distinguishing the two groups were consumers' use of a more fuel efficient auto and consuming less gasoline than five years ago. Further verification of the grouping was provided by the classification matrix in this analysis in which a 90. 5% correct prediction was achieved in classifying respondents as conservers or non-conservers versus maximum chance percentage of 52. %. The establishment of groups which were legitimately different in energy related behaviors provided a foundation for investigating a broad set of potential predictor variables. Table 1 shows the means and univariate F-Scores for the complete set of variables considered. The variables in Table 1 were then analyzed using discriminant analysis for their value in predicting the conserver and non-conserver groups. From the original set of 32 variables viewed as potentially useful predictors, Table 2 shows the results of those that were significant in forming the discriminant function.

On a univariate basis, many of the variables distinguish between the conserver and non-conserver groups. Additionally, on a multivariate basis this group of variables provided a highly significant (p< . 001) discriminant function. Further evidence of the overall power of the variable set is provided in Table 3 by the classification matrix. Predicted group membership had a 76. 58% accuracy based on the discriminant function formed from the group of predictor variables (again versus a 52. 5% level by the maximum chance criterion, (Morrison, 1969). TABLE 2 SIGNIFICANT VARIABLES IN DISCRIMINANT ANALYSIS OF CONSERVER GROUPS

TABLE 3 CLASSIFICATION MATRIX FOP CONSERVER GROUPS In light of the variables' power in distinguishing between conservers and non-conservers, a discussion of the contribution made by each variable set is worthwhile Beliefs About the Gasoline Shortage This set of predictors indicated consistently different views between conservers and non-conservers. Non-conservers were more prone to believe that no real gasoline shortage existed, that there was less of a need for the country to decrease its consumption of gasoline, and that the gasoline availability problem was due to government bungling of the situation.

The conserver group tended toward opposite beliefs in each of these areas. The government issue is one of the strongest contributors to the multivariate prediction of group membership. Evaluation of Potential Solutions Univariate comparisons of the two groups on this set of variables indicate that significant differences exist between the groups on two of six dimensions (closing gas stations on certain days as an acceptable solution and higher prices as a best solution).

One possible reason greater differences were not discovered in univariate analysis of these factors is that non-conservers were not convinced a shortage of gasoline really existed. In this context, non-conservers may have found it difficult to evaluate potential solutions to a hypothetical problem. Again, on a multivariate basis, each of the variables in this set contributed significantly to the distinction between the groups. Gasoline Consumption Behaviors This set of variables identifies differences in the way conservers and non-conservers use their personal automobiles.

Non-conservers tented to drive a greater number of miles in a year and had a significantly higher percentage of work related use of the automobile. Given the influence of using the automobile for work related purposes, perhaps non-conservers hold a view that there is an element of inflexibility in their ability to conserve gas. This proposition, however, must be evaluated in the context of the non-conservers' stronger belief that a shortage of petroleum doesn't really exist anyway. Media Habits

The only media habit that was different between the groups was ratio listening behavior and this is only significant in the context of the multivariate analysis. Data were gathered on television viewing behavior and amount of time spent reading the newspaper. As the data in Table 2 indicates, non-conservers spent more time listening to the radio (perhaps as part of work related travel). Demographics The demographic analysis in this current study provides a basis for comparison with previous energy conservation research.

The results in Table 2 indicate that conservers are younger, and have higher education and income status than non-conservers. The age relationship is more straightforward than suggested by prior research. The significance of the education variable contributes to the body of evidence which suggests a positive association between conservation and education level (Roper, 1976b; Survey Research Laboratory; Reizenstein and Barnaby, 1976; Thompson and MacTavish, 1976; Gallup, 1977a). Conservers were also found to have a higher income than non-conservers.

While the difference between groups is not significant on a univariate basis, this is another variable that contributes to the overall differences between the groups on a multivariate basis. In general, the positive association of income to conserver status joins a relatively few previous efforts discovering the same result (Roper 1977b. , Murray et al. ; 1974; Perlman and Warren, 1975a; and Reizenstein and Barnaby, 1976). DISCUSSION First, it may be noted some of the belief, attitudinal, and behavioral predictors are stronger predictors of conserver status than any of the demographic variables.

It therefore appears that the inclusion of this enriched set of predictors paid off and that prior studies have been limited by restricting themselves to demographic variables. From a public policy standpoint, the current results indicate that non-conservers simply are not convinced that an energy problem exists. They are clearly more prone to believe that the government is responsible for shortages in petroleum and that decreasing consumption of gasoline will not eliminate the source of the problem.

This mentality on the part of non-conservers manifests itself in several ways. The non-conserver group drives less fuel efficient cars and uses car pooling and public transportation far less than conservers. Further, the non-conserving group has shown little effort over the past six months or five years to consume less gas. The lack of belief in the reality of a gasoline shortage also results in lack of enthusiasm by non-conservers for any potential solutions.

Admittedly, the conservers were not overly favorable toward most solutions, but non-conservers did not rate a single potential solution positively as a group. Since not one of 75 respondents classified as non-conservers cited higher gas prices as the best solution to the problem, perhaps this tactic would have the greatest impact on the group. Aside from any attempt to speculate regarding specific policy strategies though, the main conclusion is that this group needs to be convinced of the existence of any energy problem.

It can also be recognized that non-conservers drive more miles and drive more for work related reasons than conservers. The implication here could be that non-conservers consider the consumption of gasoline a necessity and therefore do not feel they have the flexibility to engage in conservation behaviors. Demographically conservers are younger, more highly educated and higher in income than non-conservers. Perhaps, these demographic factors have contributed to their ability to obtain and comprehend information about the energy situation, hereby influencing their beliefs about its existence. This in turn may have influenced conservers to car pool, use public transportation, drive more fuel efficient cars, and generally reduce consumption of gasoline. At least this cognitive-behavioral chain of events is the one we would expect for a high involvement choice like gasoline conservation. The distinctions between conservers and non-conservers Just discussed were, to a large degree, discovered through the use of a multivariate approach to the predictor variables.

Many factors that were not significant on a bivariate basis, nonetheless, were significant in the context of a multivariate analysis of the two groups. To the extent that factors are operating in conjunction with one another to influence conservation behavior such a simultaneous investigation appears to have promise in untangling the contradictory findings produced by previous bivariate analyses The task of future research investigating energy conservation behavior is to further enhance and enrich the set of predictor variables by taking into account longitudinal changes in the beliefs and attitudes found to be important in this study.

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