Post on 20-Jan-2023
Residential Water Use: Predicting and Reducing Consumption
CAhlPBELL K. AITKEN2 AND THOMAS A. MCMAHON Centre for Environmental Applied Hydrology
Deparrmpnr of Civil and Environmental Engineering University of Melbourne
ALEXANDER J. WEARING BRIAN L. FINLAYSON Deparhent of Psychology
University of Melbourne Department of Geography
University of Melbourne
This project had two goals: to explain variation in residential water consumption and to evaluate methods of encouraging residents to reduce their consumption. Survey data for both studies were collected by mail questionnaire in early 1991, and water consumption figures were recorded between June and August of that year. In Study 1 (n = 264) a three-variable regression model (number of residents, clotheswashing machine loads, and property value) accounted for 60% of the variance. Attitudes, habits and values were very poor predictors of water consumption. In Study 2 (n = 226) households were divided into three treatment groups: feedback only, feedback and dissonance, and a control group. Repeated-measures ANOVA revealed that high consumers receiving dissonance and feedback or feedback alone had significantly reduced their water consumption in the treatment period. The implications of these findings are discussed.
Melbourne is the capital of the state of Victoria and the second largest city in Australia, home to more than 3 million people living in over 1 million households. The great majority of Melbourne's residents obtain their water from one statutory authority, the Melbourne Water Corporation. Water consumption in Melbourne is high by world standards; a daily average of 487 liters per head was recorded in 1990-1991 (Melbourne Board of Works, 1991). (By comparison, residents of London use an average 263 lpcd (liters per capita per day), and those of Tucson, Arizona, consume around 500 lpcd.) The residential sector in Melbourne consumes approximately 70% of metered ex-dams water supply, and growth in total city consumption is almost entirely
'Thanks are due to Melbourne Water and the Australian Water Research Advisory Council for providing much of the funding for this project. The contributions of Hugh Duncan of the Division of Water Supply within Melbourne Water were also greatly appreciated.
2Correspondence concerning this article should be addressed to Campbell Aitken. Centre for Environmental Applied Hydrology, Department of Civil and Environmental Engineering, University of Melbourne, Parkville, Victoria 3052, Australia.
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Journal of Applied Social Psychology, 1994, 24, 2. pp. 136-1 58. Copyright 1994 by V. H. Winston & Son, Inc. All rights reserved.
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due to growth in residential use. Currently residential consumption is increas- ing at 2.8% per annum, and total city consumption is increasing at 2.2% per annum (Connelly, Buchanan, Forster, & Gow, 1992). If these rates of annual increase are maintained, consumption will overcome system yield by 2006 (Duncan, 1991). Thus there is a great need to know more about the ways in which Melbournians use water at home so that demand management and water supply measures can be better targeted and planned.
Residential water use in Melbourne was the subject of an earlier study by the authors (see Aitken, Duncan, & McMahon, 1991). Its results provided the motivation for undertaking the studies described here. Data for that initial study consisted of eight quarterly water meter readings collected from 6,788 households between 1984 and 1986, and responses to a water use question- naire completed by 845 of those households (see Duncan, 1987). Economic, physical (water use), social, and demographic variables were regressed against mean annual consumption figures. Two models were eventually derived, the best consisting of only two variables, net annual property value and number of residents per household. This model explained 45% of the variability in the water consumption data. Such results are typical of those obtained in cross-sectional studies of water use worldwide (e.g., Dandy, 1987; Hanke & de Mare, 1982; Morgan, 1973). As yet no one has been able to account for really substantial proportions of variance in cross-sectional water consumption data. It was decided that additional kinds of information were needed if variation in residential water consumption was to be more fully explained.
A notable omission from the categories listed above is any reference to peoples individual attitudes or beliefs. There have been numerous studies of relationships between psychological constructs and resource conservation, although somewhat fewer directly related to water. The connection between electricity consumption in summer and attitudes toward energy use was evaluated by Seligman et al. (1979), and they were able to account for 59% of variance in consumption data. Gordon (1982) investigated a path of prerequisite psychological components to water conservation behavior. Re- sponsibility for the state of water resources was the only factor with a strong direct path to actions. Syme, Thomas, and Salerian (1983) attempted to explain household water consumption in Perth, Western Australia, using attitudinal and behavioral variables. They concluded that household size, gross income, and perceptions of garden value were related to water con- sumption. Kantola, Syme, and Campbell (1982) tested the sufficiency of Fishbein’s attitude model with respect to intentions to conserve water, obtaining inconclusive results. Beliefs were found to be poorly correlated with behavioral intentions. The same authors (1984) applied cognitive dissonance
138 AITKEN ET AL.
and feedback theory (the principles of which are discussed below) to the electricity consumption behavior of 272 households in Perth. Their results suggested that their dissonance hypothesis could be effectively applied to resource conservation.
From the literature we identified three concepts that seemed to have theoretical relevance to domestic water consumption: attitudes, habits, and values. The rationale behind the selection of these concepts is discussed in more detail below. We conjectured that variation in the water consumption of urban households that is not accounted for by physical and economic factors is attributable to the different behavioral and psychological characteristics of each household with respect to their use of water. Feedback and cognitive dissonance theory were also investigated, and their potential for influencing householders to reduce water use was readily appreciated (Kantola et al., 1984). It was hypothesized that more frequent meter readings and drawing attention to discrepancies between attitudes to conservation and actual con- sumption (using dissonance and feedback treatments) would encourage more conservative water-use behavior.
Two studies were conducted to test these hypotheses. Study 1 attempted to account for cross-sectional variation in the water use of a sample of Melbourne households by looking for relationships between a range of household characteristics and water consumption. Study 2 examined the water consumption patterns of the same households under different conditions (dissonance and feedback treatments) in the hope of finding effective methods of reducing residential water use.
Study 1
Water is used in many different ways around the home: for drinking, in food preparation, for cleaning people, clothes, and the home itself, and to maintain lawns and gardens. All of these tasks require a certain minimum amount of water; however, some households use more water than others without achieving a better or different result. The use of water for any given domestic task may be determined in part by habits, attitudes, and values.
Attitudes are important because they can be predictors of behavior, although the evidence for this attitude-behavior relationship is varied and often conflicting (Greenwald, 1989; Wicker, 1969). This may be at least partially because so many definitions of the concept exist (see Ajzen, 1987; Eiser, 1987; Greenwald, 1989). For the purposes of this project, we defined attitude as “a relatively stable mental construct held by an individual with respect to a particular entity which facilitates conscious interaction with it. ” In this project the “entity” is water used in the home.
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Habits are formed through repeated action (Ronis, Yates, & Kirscht, 1989), and eventually they may occur without conscious choice. Like atti- tudes, habits reduce the demands on working memory. There are numerous water-using behaviors performed in the home in which the amount of water consumed is likely to be determined by habit. Washing hands and showering are examples of habit-driven behaviors.
The third psychological concept employed in this study is values. Accord- ing to Rokeach (1973), values are the cognitive representations of needs, and are a more central component of the cognitive system than attitudes. A value is “an enduring belief that a specific mode of behavior or endpoint of existence is personally and socially preferable to an opposite or converse goal” (Rokeach, 1973, p. 5). The Rokeach values scale lists 18 instrumental and 18 terminal values; four terminal values are considered to be particularly relevant to residential water use. These are “a world of beauty,” “a comfort- able life,” “pleasure” and “family security.” Support for the selection of this subset comes from Pierce (1979), who evaluated the role of personal values in environmental attitudes. The four values listed earlier may be important because they are achieved to some extent through a range of activities that rely on water consumption.
Method
Study One involved choosing a sample of households from the metropoli- tan area, administering questionnaires, monitoring the water consumption of respondents over a period of weeks, and regressing a mean weekly consump- tion figure against questionnaire responses. Three weeks of consumption data were collected from 321 households. (The same households were used for Study Two, in which recording of water consumption continued for a further 6 weeks.) Demographic, physical, socioeconomic, and behavioral data were collected using a mail questionnaire. The survey design was largely adapted from Dillman’s total design method (Dillman, 1978) and Warwick and Lininger ( 1975).
Questionnaire Design and Development
The three steps outlined below were used in formulating the attitude
1. Approximately 60 strong positive and negative statements about the
2. opinions and contributions were sought from friends and associates;
component of the questionnaire (Warwick & Lininger, 1975).
attitude object-residential water use-were accumulated,
and
140 AITKEN ET AL.
3. a small-scale pilot test was conducted. One hundred and twenty households occupying separate houses were
invited to participate in the pilot test, and after 6 weeks 87 had returned completed questionnaires. Householders were invited to respond to each attitude item using a 7-point bipolar scale ranging from disagree very strongly to agree very strongly. Those items that had produced consistent strongly positive or negative responses were identified, enabling the attitude section of the questionnaire to be reduced from 25 to 17 items. A reliability check conducted with 3 1 fourth-year students (from the university’s School of Engineering) removed a further four items. An example of the items retained for the final questionnaire version is “saving water takes more effort than it is worth.”
Much the same procedure was employed to construct the habits section. A large number of wasteful and conservative water-using behaviors were listed, criticism and suggestions were sought from friends and colleagues, and a broad selection of these items were tested in the pilot survey. The 33 habit items in the pilot questionnaire were reduced to 20 for the final version, a typical item being “do you leave the tap running while you brush your teeth?” Respondents were asked to indicate the frequency with which they performed the behavior in question on a 5-point scale ranging from never to always.
Values were measured using a modified Rokeach values scale. The Rokeach values scale (Rokeach, 1973) is a standard instrument for the measurement of values. It assesses 18 instrumental and 18 terminal values, which must be ranked separately in order of importance. This is quite a difficult task, and there are a number of objections to ranking procedures in the literature (see Cooper & Clare, 1981; Feather, 1973). However, ranking is attractive because it is a process familiar to most people and provides clear (if arguably artificial) results. A modified ranking method was employed in this study to try to avoid some of the problems inherent in a strict ranking procedure. Respondents were told they could give two or more values the same rank if desired, and that not every value need be ranked. These modifications avoid the ipsative nature of the pure ranking method, and to some extent incorporate the flexibility of ratings.
Demographic and physical water-use items dealt with characteristics such as the number of residents per household, patterns of clotheswashing machine use, and principal garden watering methods. It may be argued that a variable such as “dishwashing machine loads per week” is really a rnea- sure of consumption, and thus part of the dependent variable is being used as a predictor. However, these data are not measured directly and thus are subject to respondent error, and they are imperfectly related to
RESIDENTIAL WATER USE 141
actual volumes consumed (for the dishwashing machine example, type of machine and method of use are variable); thus they can be considered predictive variables like any other. Studies of residential water consumption that employ such variables are abundant (Batchelor, 1975; Dandy, 1987; Darr, Feldman, & Kamen, 1975; Grima, 1972; Power, Volker, & Stark, 1982).
The final questionnaire consisted of four sections, the first concerned with demographics and physical water-using characteristics, then sections for attitudes, habits, and values. It totaled 58 items (not counting the 18 items of the values scale).
Time Frame
It was felt that variation in water use could best be studied by eliminating the most problematic source of variance, which is consumption outside the home. External (principally garden) water use accounts for around 40% of the average Melbourne household’s annual consumption (Duncan, 199 l ) , and is extremely difficult to quantify without direct measurement because it is not typically consumed in discrete “parcels” as indoor water use tends to be. Therefore monitoring of residents’ consumptions was carried out during the winter months, June, July and August, when overall water consumption and external use are at their lowest levels.
Sample Selection
A random sample of census collector districts was chosen from through- out the Melbourne metropolitan area. Next, a street near the center of each district was randomly selected, and 25 properties (separate houses only) were chosen in order along that street and those nearby. Properties were not selected if they exhibited any characteristics that would make meter- reading difficult or otherwise compromise their eligibility for the study. Examples encountered included “for sale” signs, partly built walls or fences, and large dogs. An initial sample of 500 properties in 20 clusters of 25 was chosen.
Procedure
Properties were chosen in March 1991. In April all 500 households were sent an introductory letter and the questionnaire; those not replying within 2 weeks received a second set, and those households which had not responded by the fourth week were sent a third set. This methodology is adapted from
142 AITKEN ET AL.
Dillman (1978). Three hundred and forty-eight of the targeted households (69.6%) had responded positively to the questionnaire after the full 6-week collection period. Three hundred and twenty-one of these 348 households had completed the questionnaire to a standard that justified their inclusion in the project, and their addresses formed the initial meter-reading list.
Collection of Water Consumption Data
Permission to read water meters had been obtained from Melbourne Water in late 1990. Meters were read on the Monday and Tuesday of each week through June, July, and early August 1991. Readings at each property were taken at approximately the same time of the day. Properties at which some problem was experienced (residents absent, meter inaccessible or unreadable, etc.) were deleted from the meter-reading list as their problems became apparent. By the end of the third week (the fourth meter reading) 48 properties had been deleted, leaving 273 sets of records for analysis.
Results
A11 data manipulation and analysis was performed using the Statview (Abacus Concepts, 1986) and SYSTAT (SYSTAT Inc., 1992) statistics pack- ages running on an Apple Macintosh computer. Three important operations were necessary before commencing analysis. Scores on individual attitudes, habits, and values items were recoded so that a high score reflected a nonconservative attribute and summed to give each respondent a single score for each concept (ATT, HAB and VAL).3 The consumption data were edited to remove records displaying extreme variability over the 3-week monitoring period. Record deletion was performed in conjunction with the results of a postexperimental questionnaire, which inquired about events over the moni- toring period that may have caused atypical water use or adversely affected the study in any way (for example, long absences, the installation of a pool, or a change in occupancy). Six records were deleted because of wild variabil- ity over the monitoring period, two due to unreliable meters, and one for having a zero consumption figure. Thus the data set was reduced from 273 to 264 records, Before regression analysis the data were randomly divided into two sets of 132 records, one for the actual analysis and the other for testing
'A weighted scale was initially considered as a way of accounting for differences in frequency of performance and volume of water use for individual habits. But total consumption volume is the real concern, and doubts about the value of weighting (see Dawes & Corrigan, 1974) ruled out its use.
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the results obtained with the first set. Relevant descriptive statistics for the 132-record subset used for analysis are given in Table 1.
The mean weekly consumption for this sample of 3695 liters (winter) converts to a seasonally adjusted 265 kiloliters per m u m , which compares very well with the average for all Melbourne households (256 kl/yr in 1989: Duncan, 1991).
Modelling Water Consumption
The procedure used to derive the models has been described in Aitken et al. (1991). Variables exhibiting significant collinearity were excluded, reduc- ing the number of variables to be analyzed from 14 to 6. A variable pair was deemed to be highly collinear if the correlation between them was higher than those between each variable and the dependent variable (see Pindyck & Rubinfeld, 1980). In such a case the variable correlating less strongly with the dependent variable was removed. The matrix of correlations is given in Table 2.
As expected, the variable correlating most powerfully with consumption is RE, the number of residents per household. (RE accounted for nearly half of the explanatory power of the model derived in the author s previous study of residential water consumption: Aitken et al., 1991 .) The low correlations of attitudes, habits, and values scores with other variables, and with consump- tion in particular, indicate that they are not important predictors of water use. However, ATT and HAB correlate relatively highly with each other.
Although some similarity of attitudes among members of the same family can be assumed, using questionnaire responses from one member to predict the water consumed by a whole family may weaken or obscure a relationship. The correlation between attitude scores and water consumption for single- member households was computed to see if a stronger relationship between attitudes and consumption was being hidden. A correlation coefficient of -.32 was obtained for 25 single-member households, which is stronger than the coefficient for all households but nonsignificant and negative, and thus offers no greater support for an attitude-behavior relationship.
Variables remaining in the data set after the deletions necessary to minimize multicollinearity were NAV, Press, CW, RE, HAB, and VAL. Variables omitted were DW, TLT, SH, Male, RE14, OWN, GAR, and ATT (see Table 1 for descriptions of all variables). As Table 2 shows, these variables are either correlated strongly with a better predictor (such as RE) or are very weakly correlated with consumption.
Next plots of the dependent variable against predictor variables were examined for suggestions of transformable relationships, but none were
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Table 1
Descriptive Statistics for the Analysis Subset (I 32 records)
Mean SD Min Max
Cons NAV Press cw DW TLT SH RE Male RE14 OWN GAR ATT HAB VAL
3695.25 5010.06
120.14 3 .OO 1.21 1.27
15.81 3.01 1.52 0.63 1.84 1.52
36.38 33.79 51.16
2258.19 2030.13
34.08 2.18 2.13 0.50 9.45 1.30 0.85 0.94 0.37 1.16
10.77 8.27
15.78
414.30 1475 .OO
50.00 0 0 0.75 0 1 0 0 1 0
16 14 4
15083 .OO 14500 .OO
183.00 10 7 3
65 7 4 4 2 4
68 62 76
Cons = NAV = Press = cw = DW = TLT = SH = RE =
Male = RE14 = GAR = OWN = ATT = HAB = VAL =
mean weekly water consumption. net annual property values. static head nearest to property (water pressure proxy). clotheswashing machine loaddweek (adjusted for machine type). dishwashing machine loaddweek (adjusted for machine type). number of toilets (standard + dual-flush x 0.75). number of showers per week. number of people per household. no. of males. number of household members 14 years or less in age. least conservative garden watering method. owningkenting binary variable. attitudes score. habits score. values score.
146 AITKEN ET AL.
identified. An initial stepwise regression was fitted (F-to-enter = 3.84, F-to-remove = 2.71; significance level = 5 % ) , and significant outliers identified in that analysis were deleted from the data set. Further stepwise regressions were fitted until no significant outliers (as judged by the values and patterns in standardized residuals) remained.
Finally, predictor variables identified as important by the last stepwise regression (in terms of their contribution to R2 and standard error) were regressed against the dependent variable to obtain a final model.
After three fittings and the elimination of four records as outliers, a regression model was derived which explains 60% of the variability in residential consumption with three variables see Equation 1.
CONS = 792.OO(RE) + 239.80(CW) + 0.20(NAV) - 682.57 ( 1 )
R2 = .60 % standard error = 3 1.11
This model has an RZ coefficient of .60 and a standard error of 3 1 %. Variable RE (number of people per household) contributes .50 toward the model’s explanation of variance, the other two variables .05 each. The model was tested by regressing the variables it contained against consumption using the test data set, and comparing the statistics of each. Testing with the second 132-record subset (put aside for this purpose, as described earlier) produced an equation with an R2 coefficient of .54 and a standard error of 38%, which suggests the model accurately represents the data.
Conclusions
Three variables (the number of residents per household, net annual property value, and number of clotheswashing machine loads per week) ex- plain 60% of the variation in the water consumption data. Number of residents per household is by far the strongest predictor. None of the psychological variables-ttitudes, habits or values-are included in the model. Table 2 shows that correlations between ATT, HAB, VAL, and other variables are very low; although ATT and HAB correlate quite highly, neither is a predictor of water consumption. Therefore this study can be added to the body of liter- ature that does not support the relationship of attitudes to behavior (see Ander- son & Lipsey, 1978; Greenwald, 1989; Kantola et al., 1982; Wicker, 1969).
Study 1 did not provide any support for the relationship of attitudes, habits, or values to residential water use, but it did produce a useful result. The model obtained in Study One shows a considerable improvement over
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that derived in the authors previous project in terms of variability explained (.60 against .45: Aitken et al., 1991). Of course, there were substantial differences between the two studies that could account for this improvement, most importantly the fact that this study was confined to the winter period whereas the previous study had to deal with seasonal variation in water use. Winter consumption is lowest in Melbourne largely because of the absence of garden watering.
As part of an attempt to identify the factors that affect residential water use, Study 1 established that attitudes, habits, and values are poor predictors of water consumption. Study 2 makes use of the poor correspondence between householders attitudes, values, and water use by applying cognitive disso- nance and feedback treatments with the aim of inducing reductions in con- sumption.
Study 2
The application of dissonance and feedback in this study derives from Kantola et al. (1984), who examined the effects of these treatments in pro- moting residential electricity conservation. The pivotal assumption of cogni- tive dissonance theory is that when an individual simultaneously holds two attitudes, beliefs or items of knowledge that are conflicting or contradictory, then there exists a tendency to reduce the incompatibility (Kantola et al., 1984). When a freely performed behavior is inconsistent with an attitude, the dissonance is usually resolved by a change in attitude with respect to that behavior. However, if the attitude involved is a central and powerful one, the opposite may occur-the attitude will be reinforced and behavior modified to comply with it. In general, the stronger the dissonance, the stronger the attempts to reduce it (Sherman & Ghorkin, 1980). Feedback is the provision of information to the individual about the results of his or her behavior. The more often feedback is given, the more potent the effect upon the behavior (Oskamp, 1984). Because it has both informational and motivational proper- ties, in that it provides a basis for assessment and action and enables progress toward a goal, feedback can be an effective means of altering human behavior (Becker, 1978; Dennis, Soderstrom, Kocinksi, & Cavanaugh, 1990; Oskamp, 1984).
Study 1 had shown that attitudes, habits, and values were poorly cor- related with water consumption. Thus many households were in a dissonant situation, and the potential existed for a change in attitude or behavior to reduce that dissonance. We intended to exploit that potential by bringing attitude-behavior discrepancies to the attention of householders and providing simple feedback on their consumption.
148 AlTKEN ET AL.
Table 3
Experimental Design for Study 2
June July August
R1 R2 R3 R4 R5 R6 R7 R8 R9 R10
W1 W2 W3 W4 W5 W6 W7 W8 W9
(Baseline) (Treatment) (Recovery) ~
Dissonance group No stimuli Diss. + Feed. No stimuli Feedback group No stimuli Feedback No stimuli Control group No stimuli No stimuli No stimuli
Note. R1 = Reading 1, W1 = Week 1, etc.
Method
The 3 weeks of water consumption data that were regressed against questionnaire responses in Study 1 form the nonintervention or baseline data for Study 2. Meters were read without the knowledge of the residents, although some degree of compliance was implied by the completion and return of the water use questionnaire. The baseline period was followed by a treatment period, in which householders received the combined dissonance and feedback treatment, the feedback-only treatment, or no information at all if assigned to the control group. A third period of time with the treatments withdrawn, a recovery period, concluded the experiment. Table 3 shows the study design, which design allows a two-factor ANOVA with three levels for each factor. However, because one of the factors is repeated measurement of the same attribute over time, it is more properly a repeated-measures two- factor design (Tabachnick & Fidell, 1989).
Allocation to Treatment Groups
The water-use questionnaire administered earlier in the year consisted of four sections: demographics and physical items, attitudes, habits and values. The attitude section of the questionnaire contained the statement “It is my duty as a responsible citizen to conserve water” (adapted from
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Kantola et al., 1984). Dissonance group membership was allocated to a randomly-chosen subset of the residents agreeing strongly or very strongly with that statement. Of the 321 households on the initial meter-reading list, there were 208 that gave either of those positive responses to that item. Accordingly these households were all potential members of the dissonance group, and 107 of them were randomly allocated to it. The 214 remaining households were randomly allocated to either the feedback or control group. (The practice of assigning only households that had expressed a pro- conservation attitude to the dissonance group theoretically introduces baseline nonequivalence to the experiment. This was unfortunate but un- avoidable: cognitive dissonance relies upon an attitude-behavior discrep- ancy for its effect, and the result desired was to induce a reduction in consumption, so dissonance could only be given to pro-conservation house- holds. )
Treatments
Hand-delivered postcards were used to impart cognitive dissonance and feedback treatments to householders. These contained very simple, neutrally worded information that respondents could interpret as they pleased. The dissonance card carried an introductory sentence that reminded the recipient of hisher completion of the water-use questionnaire. It then pointed out the recipient’s agreement with the conservation responsibility statement mentioned above. Lastly, it gave the consumption at that property for the past week along with the average consumption for a household of the same size as the recipient’s (in winter, in Melbourne). Averages were calculated from data collected between 1984 and 1986 (see Aitken et al., 1991), and were made artificially low by about 10% to create a larger number of residents with the potential to be influenced by the treatments. The feedback card gave the household’s consumption for that week, plus the expected weekly figure for that household’s size. Both included the date of delivery on the obverse, and carried the study’s title, the names of the researchers, and their departmental address on the reverse. Thus the disso- nance card contained the information of the feedback card plus the dissonance trigger.
Procedure
Each treatment card had the necessary consumption information written on it and was hand-delivered immediately after the recipient’s water meter was read. Treatments commenced at the end of the baseline period (third
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week, fourth reading-see Table 3), and the recovery period covered the seventh to the final reading (weeks seven to nine). At the conclusion of the 9-week monitoring period households remaining on the meter-reading list numbered 261. Editing the data to remove households with highly variable consumption records over the monitoring period was performed with refer- ence to the postexperimental questionnaire (see Study 1). Some problems with inaccurate meters and zero consumption figures were also detected. Thirty-five households were eventually removed in this way, and thus analysis commenced with a data set containing consumption records from 226 house- holds.
Results
At the conclusion of the 9 weeks of monitoring, each household still in the data set was represented by 9 consumption figures taken over nine consecutive weeks (three values for each of the three periods). To facilitate analysis these were averaged to give a single consumption figure for each of the baseline, treatment and recovery periods, giving three data points per household.
The main analytical tool was repeated measures ANOVA, also known as randomized block factorial, split plot, or between-within-subjects ANOVA (Tabachnick & Fidell, 1989). Analysis proceeded in four ways. First all 226 households were included in a 3 x 3 x 2 ANOVA, Treatment Group x Period x High/Low Consumption Group (“high” meaning the top 113 households as measured by the difference between baseline consumption and that expected on the basis of household size). Next the data for high-consuming households were analyzed in isolation, and, thirdly, the behavior of low-consuming households was investigated. The final analysis examined the data from proconservation households, defined as those households that gave a strongly positive response to the attitude item used to select the dissonance group.
When all records were used in the 3 x 3 x 2 analysis significant differences between the high and low groups, F(1, 220) = 182.82, p < .01, and across the repeated measures, F(2, 220) = 4.19, p < .02, were exposed, and the interaction between these factors was also significant, F(2, 440) = 4.19, p € .02. A significant difference can be expected when households are artificially divided into high and low groups; analysis proceeds using that basic division. The significance of the repeated measures or time factor suggests that the treatments were effective in altering consumption behavior. Means for this ANOVA are shown in Table 4 below.
On the basis of the results of the 3 x 3 x 2 analysis, further ANOVAs were performed within the high- and low-consumption households separately. Analysis of the consumption behavior of high-consuming households-the top
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1 13 consumers-yielded the most important results. Again, significant differ- ences were found to exist within the repeated measures, F(2, 110) = 8.97, p < .01, between the baseline and both treatment and recovery periods. The same pattern was discovered when dissonance group households were analysed in isolation, F(2,74) = 7.32,~ < .01, the average reduction among dissonance group consumers in the treatment period was 4.3 % . Neither the feedback or control groups displayed significant differences. Means for the high-consuming households are shown in Table 4.
Next consumption data from households in the highest quartile of consum- ers (57) were analyzed. Results diverge from those obtained for the set of 113 high consumers in that only the baseline-treatment comparison is significant for the dissonance group in this analysis, F(2, 34) = 3.79, p < .05, whereas both the baseline-treatment and baseline-recovery differences are significant for the feedback group, F(2, 36) = 8.23, p < .01.
Table 4
Table of Means for the j-Factor, Repeated Measures ANOVA, All Households
Repeated measures
AvBASE AvTRT AvREC Means
Means (113) (113)
5 169.37 2 169.29 5795.30 2306.35 5186.65 2297.3 1
5358.59 2259.64
4778.18 2 108.63 5564.49 2472.68 5018.11 2406.51
5096.99 2334.45
4853.67 2 167.76 5551.34 246 1.05 4928.72 2414.42
5085.3 1 2351.93
4933.74 2148.56 5637.04 2413.36 5044.50 2372.75
5 180.30 2315.34
~ _____ ~ ~~~
Note. Means for the low half of consumers are shown in italics. D = Dissonance, F = Feedback, C = Control. AvBASE = average weekly consumption in the baseline period. AvTRT = average weekly consumption in the treatment period. AvREC = average weekly consumption in the recovery period.
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Table 5
Table of Means for the 2-Factor, Repeated Measures ANOVA, Lowest Quartile of Consumers
Repeated measures
AvBASE AvTRT AvREC H’holds/Means
D 18 1510.56
1669.83
1765.13
Treatment groups F 21
C 18
Households 57 Means 1649.63
18 1420.64
21 1768.33
18 173 1.30
57 1646.84
18 1433.51
21 1866.29
18 1777.46
57 1701.57
18 1454.90
21 1768.15
18 1757.96
57 1666.01
Note. See Table 4 for explanation of symbols.
Although the behavior of high consumers under dissonance and feedback treatments is more important to the aims of this study, low-consuming households are also of interest. We expected that low-volume consumers would exhibit more stable consumption patterns and be less affected by the treatments than high consumers. After all, the effectiveness of the treatments relies on the recipient resolving to lower consumption relative to what they are told is average for their household size. If water use is already relatively low, then the incentive to reduce is negligible.
Results tended to confirm this expectation of small or no reductions in water use by low-consuming households, with one interesting exception. No divergences were detected in the initial 3 x 3 ANOVA or subsequent analyses performed on particular groups. However, when households in the lowest quartile of consumers were examined, a significant difference was discovered between consumptions in the baseline and recovery periods for feedback group households, F(2, 40) = 6.19, p < .01, a percentage increase (adjusted for the corresponding control group increase) of nearly 12% (see Table 5).
This increase in consumption among feedback treatment recipients may be construed as being due to a relaxing of the previously conservative behavior of feedback group households when told they were in fact lower-than-average
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Table 6
Table of Means for the 2-Factor, Repeated Measures ANOVA, Using the High Half of Pro-Conservation Water Consumers
Repeated measures
AvBASE AvTRT AvREC H’holddMeans
D 43 43 43 43 4941.5 4613.33 4618.31 4724.38
6233.08 6077.51 6222.28 6177.63
4791.91 4758.57 4644.47 4731.65
Treatment groups F 12 12 12 12
C 21 21 21 21
Households 76 76 76 76 Means 5104.10 4884.65 4878.80 4955.85
Note. See Table 4 for explanation of symbols.
consumers. Households receiving dissonance cards may have interpreted their relatively low consumption figure, combined with the reminder of their expressed positive attitude to water conservation, as a reward for conservative behavior and thus did not “relax” as did households receiving feedback.
Examination of data from pro-conservation households completes the analysis. The interaction effect was significant in an initial two-factor, repeated measures ANOVAAreatment groups by periods-sing all 15 1 records, F(4, 296) = 2.671, p < .05. Subsequent to this result a significant difference was found between average baseline and treatment consumptions for dissonance group households alone. Analyses run on data for the high half of consumers gave more definite results. For these 76 households, average consumption in the baseline period was significantly different from that in both treatment and recovery periods, F(2, 150) = 5.14, p < .01. Further analysis showed that this was entirely due to reductions made by dissonance group households, who reduced their consumption over the treatment period by an average 6%. ANOVAs run on the highest quartile of the consumption data (38 households) revealed the same pattern at stronger levels of signifi- cance. No significant differences were detected in analyses run on the low
154 AITKEN ET AL.
half of the data. Table 6 shows the consumption means for the 76 households in the high-consuming half of the pro-conservation data set.
Results from the analysis of pro-conservation households confirm that feedback and dissonance together are the more potent treatment in terms of their effect on consumption behavior.
Conclusions
The results given here demonstrate that statistically significant reductions in residential water consumption can be achieved by the application of simple cognitive dissonance and feedback information, at least in the short term. In particular, high-consuming households can be expected to reduce their con- sumption. Households receiving both dissonance and feedback treatments exhibited the greatest reductions, followed by households receiving feedback alone. These results suggest that although feedback is useful, the added effect of placing the subject in a dissonant situation is more effective in encouraging a reduction in water consumption.
General Discussion
In Study 1 it was demonstrated that a very low and insignificant corre- lation exists between the expressed attitudes of householders to residential water use and their actual consumption. The correlation between the habits variable employed in Study 1 and household water consumption is similarly poor, as is that between values and consumption. Thus the hypothesis that these variables are partial predictors of residential water consumption is unsupported by our results. Poor correlations with consumption, considered in the light of the relatively high correlation between the attitude and habits variables, suggest that not only are residents’ expressed attitudes at variance with their behavior but their perception of their habits is also faulty. There are a number of possible interpretations of the noncorrespondence of ex- pressed attitudes and habits and actual water-use behavior found to exist in this project. The definition of attitude used here associates attitudes with reasoned decisions, whereas many of the water-use behaviors are habitual (and probably unthinking). Consequently the poor correlation between water consumption and the attitude variable can be viewed as a logical result. However, the low correlation between the habits variable and consumption cannot be explained in this manner. Many water use behaviors are repeated, and so the habits variable was expected to predict consumption to a greater degree than actually occurred. (It should be pointed out that the correlation between the habits variable and consumption of 0.17, although very low, is
RESIDENTIAL WATER USE 155
in fact significant and higher than that between attitude and consumption.) Study 2 made use of this discrepancy between attitudes and actual water-
use behavior by bringing it to the attention of the householder in simple terms. The resulting dissonant situation produced a textbook reaction from the subjects, supporting the initial hypothesis that cognitive dissonance and feedback are effective methods of inducing significant water-use behavior change. Residents significantly altered their behavior to bring it more into line with a belief they had strongly endorsed'hat water conservation is important and the duty of every citizen. This result is the most important practical outcome of the project. It shows that careful presentation of simple infor- mation can induce significant behavioral changes in the recipients. (However, it must be acknowledged that differences between the groups which are attributed to the dissonance treatment may have been obscured to some degree by differential response to feedback by respondents holding varying degrees of support for the water conservation e t h i ~ . ~ )
The reductions in consumption induced by our dissonance and feedback treatments are small in terms of percentages of total weekly water use. However, most household consumption measured in this project is not amenable to really large reduction. The study did not include the largest single component of residential water use, outdoor consumption, which peaks over the summer months. Changes attributed to our treatments are considerably more impressive if seen as percentages of the typical yearly volume of water use. A conservative figure for the contribution of outdoor water use to total household consumption in Melbourne is 30%, so this study's average reduc- tion of 1.9% can be immediately scaled up to 2.7%, still conservative because potential for reductions in garden and other outdoor uses is considerable (Duncan, 1991). A similar study running over the summer months should find that much greater reductions in water use are possible.
An interesting paradox exists between the results of the two studies described here. In Study 1 attitudes are not good predictors of consumption, which implies they are not important with regard to residential water use. However, in Study 2 householders made significant behavioral changes to align their water use with their expressed attitudes, suggesting the reverse- that attitudes are an important consideration. The explanation may be that attitudes to water conservation and consumption are valuable to the people expressing them, but in ordinary circumstances those attitudes are not
4This point was made by a reviewer. While acknowledging its theoretical validity, the authors point to the reduction in average consumption in the dissonance group and the effect of dissonance in the analysis involving only pro-conservation households as evidence for its efficacy.
156 AITKEN ET AL.
challenged or examined and can become distanced from reality. Thus attitudes to water use are poorly related to actual consumption and not good predictors of it, but because they are valued by the holder they can still be harnessed to alter behavior.
The results of this project have important implications for the management of residential water consumption. In recent years Melbourne Water has made extensive use of public education as part of its demand management strategy, including television, radio, and newspaper campaigns. These have aimed to change householders’ attitudes to their use of water. However, the results presented here show that attitudes to water use do not correspond to people s actual behavior, which suggests that public education aimed at attitude change, although certainly not harmful, may not be very effective as a demand management tool. Behavior change requires stronger inducements and better targeted information, as demonstrated by the minor success of the dissonance and feedback treatments employed in this project. However, it must be recognized that the reductions in water consumption described here were achieved using weekly treatments, a considerably higher frequency of stimu- lus than could be used in practical, large-scale applications of the technique. Thus there is a need for further research on this topic over a longer time scale. Nevertheless, this project suggests that potential exists for more frequent distribution of specialized information to effect useful reductions in residen- tial water consumption.
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