relationships between consumer characteristics and do-it-yourself behaviour (do-it-yourself...

J O U ~ of Consumer Studies and Home Economics (1989) 13.3%51.

Relationships between consumer characteristics and do-it-yourself behaviour (do-it-yourself activity )

A N N E S W A R T Z L A N D E R * A N D J E A N S . BOWERS? 'Directions Data, Knoxville, Tennessee and tDepartment of Family Resource Management, Ohio State University, Columbus

As an exploratory venture, this study was developed to identifr variables rehted to the frequency of different types of do-it-yourself maintenance and repair activities, including homes, cars, and major appliances. The findings showed that the extea of do-it-yourself activity was related to gender, age, and education. Other results provide insight for further research.

Introduction

As family economists are aware, household production makes a valuable contri- bution to family and individual well-being. The production by household members of certain household needs, particularly maintenance and repair of housing and durable goods, is often called do-it-yourself activity. Toffler' includes do-it- yourself repair among activities which he labels 'prosumption' and defines as 'all the unpaid work done directly by people for themselves, their families, and their communities'. He maintains that 'unpaid household work', long recognized as household production by family economists, is on !he increase. Ahhough Toffler's contention is questionable in general, surveys have shown that in the past decade consumers have been doing more of their own household and car maintenance and repair than previously.2 The increase in number and sales of home improvement and car parts retail stores supports the survey finding^.^.' The policy of providing free phone numbers for repair advice and understandable do-. it-yourself repair manuals by some manufacturers of major appliances also offers corroboration.' Experts offer several explanations for the increase in do-it-yourself activity.

According to trend analysts, the 'fix-it-yourself trend is a manifestation of a per- vasive self-help movement for individual and family concern^.^" Naisbitt de- scribed the trend as a growing disillusionment with institutional help and an accompanying shift to self-sufficiency and self-help. Stanback' has argued that consumers who are dissatisfied with the quality of services available in the market

Correspondence: Dr Anne Swartrlander, Directions Data, 1640 Clinch Avenue, Knoxville. 37916. U S A .

39

Do-it-yourself activity

will choose to produce their own services when possible. Other sources suggest that economic necessity and the value of creative leisure also motivate do-it- yourself household activities. Comparable longitudinal data are unavailable to provide evidence for the alleged increase in do-it-yourself activity, but speculation about the topic provokes inquiry.

As an exploratory venture, this study was developed to identify variables related to the frequency of different types of do-it-yourself maintenance and repair activities, including homes, cars and major appliances. The findings are primarily intended to provide impetus and insights for further exploration. As with all studies which are conceived with little guidance in the form of previous research, the measurement of the important variables is initially a trial and error process. Thus, results relevant to those providing educational assistance or providing do-it- yourself supplies and tools should be considered tentative. The study has also yielded several suggestions for further research.

Review of literature and hypotheses

To maintain a smooth-running household, a consumer has a choice between purchasing maintenance and repair services for housing and durable goods oi doing maintenance and repair tasks oneself. According to economic theory, a consumer decision is the result of utility maximization subject to a budget constraint derived from prices and income. In an attempt to blend economic and psychological views of consumer behaviour, Redman' argued that 'the budget line reflects "reality" or the limitations the person faces in the situation as perceived by the person'. So the budget could include non-monetary .limitations such as time constraints, lack of information or knowledge, and human energy limitations. The use of time as a cost in household production theory is one example of this approach."' In addition, the amount and quality of information and an individual's information processing abilities can alter the utility maximization decision process by affecting preferences and perceived constraints. ".'* From a household management pcrspe~tive,'~ the inputs in a managerial decision include human resources (knowledge, time, energy, propensities, information) and material resources, such as money. Information, globally defined here as all relevant data and knowledge, including beliefs and attitudes in a consumer's rnemory,l4 is used both in making the decision and as a potential input into implementation of the decision. Is

These theories offer some guidance for exploration of relationships. A consumer decision to self-produce a service rather than purchase it should be affected not only by income, but also by non-monetary 'budget' items. Also, in this study the frequency of do-it-yourself maintenance and repair activity was expected to be a function of an individual's stock of resources, including human and material resources. The resources and accompanying constraints analysed were level of 40

A. Swartzlandcr and J. S. Bowers

education, age, membership in a dual income household with higher time demands, attitudes toward the marketplace and repair, income, and urbadrural residence. Along with examining how consumer resources are related to the self- production decision as non-monetary costs, this approach was used to reinforce the use of socio-demographic data by consumer educators in planning strategies based on measurable and available information about their clientele.

The exploratory hypotheses were based on a review of household production and related consumer behaviour research in addition to a few studies specifically concerning do-it-yourself behaviour. First of all, the frequency of do-it-yourself activity was expected to be higher for men than women. One study16 which peripherally addressed this question showed that there were differences between men’s and women’s responses to repair problem scenarios. For hypothetical mal- function situations men were more likely than women to choose the alternative of fixing a broken piece of household equipment themselves.

Second, the frequency of do-it-yourself activity was expected to be higher for younger consumers. Younger consumers were expected to have more interest in and more energy for doing their own maintenance and repair ovemding the effect of the experience that comes with age. Two studies”*18 support this hypothesis.

contends that if increases in education raise the productivity of time in the labour market, an analogous effect can be expected for non-market production. Other things being equal, household members with more education can produce more with a given amount of time, goods and money. If the effect is universal, i.e. improving efficiency in a general way, households may be able to do their own repairs at a lower relative cost and will engage in do-it-yourself activity more often. However, education may have a greater impact on efficiency in some activities than in others, thereby reducing price per unit for those activities only. Thus, the effect could be expected to vary among different maintenance and repair activities.

Fourth, higher income howholds with higher opportunity costs of time and the ability to afford repair services were expected to engage in less do-it-yourself activity. Game?(‘ found that higher income households were less likely to do their own repairs inside the home. A market segmentation study of do-it-yourselfersz1 suggested that two groups, the reluctant (low income, less education, dispropor- tionately female) and the transitionals (young, wellcducated, in early stages of the family life cycle) were motivated by income considerations. Other studies” have found no relationship. In light of the contradictory evidence, this hypothesis was considered tentative.

Fifth, household labour market decisions could influence the frequency of do-it-yourself activity by affecting the amount of time available to spend on household production. Everything else being equal, members of dual income households were expected to have higher time demands than other households and consequently were expected to engage in do-it-yourself activities less frequently. The indusion of education and income should help rule out confounding

41

Third is the effect of education.


effects of necessity versus choice in the wife's decision to work in these dual income households.

Apart from money, time, and skills, attitudes can also influence household production behaviour so several consumer attitudes were included in the analysis. Game?' found that repair skills are positively related to self-production of home repairs. Thus, consumers who preferred repairing rather than replacing broken goods in general would be more likely to be interested in learning maintenance and repair skills and so were expected to be more frequent do-it-yourselfers. Con- sumers who believed the quality of repair service had deteriorated would also be more frequent do-it-yourselfers. Stanback: has suggested that people will choose to do their own maintenance and repair if they believe the quality of repair service is poor. He argued that they will believe they can get higher quality for the same or a lower price by combining their time and goods and doing it themselves. Since behaviour was expected to be in agreement with beliefs,26 and faith in the marketplace would encourage one to purchase, the belief that manufacturers are willing to repair or replace a defective product and satisfaction with goods available was expected to be negatively related to more frequent do-it-yourself activity.

Finally, two variables, residence location and ownership, were included as con- trols. Residence location was included to account for possible differences in the supply of repair services between urban and rural areas. Also, if ownership were correlated with other independent variables, the exclusion of ownership would result in specification error and bias the estimates of those independent variables.n Rural residence and ownership were expected to be positively related to the frequency of do-it-yourself activity.

Methodology

The data used in the study were from a national telephone survey, conducted in December 1982 and January 1983, concerning consumers' attitudes about the quality of consumer goods and services. The study was sponsored and designed by a major appliance manufacturer and conducted by a market research firm. The responding households were selected by a random digit dialling system. At least four callbacks were made to each listing except for business, government and dis- connected numbers. The respondent was randomly selected from the household by the Trodahl-Carter-Bryant method.= This procedure yielded 1002 observations, a 63% response rate (after the exclusion of phone numbers which were never answered and households where there was no one 18 years of age or older available or there were language or hearing difficulties). The pre-holiday and post-holiday groups were compared and no differences were found. No attempt was made to determine if the non-response segment differed from the respondents, but the sample was reasonably representative of the American population on several socio-demographic variables.

The frequency of do-it-yourself activity was the dependent variable for separate 42

A. Swartzlander and J. S. Bowers

analyses for do-it-yourself maintenance and repair of home, cars and major appliances. Although the frequency of activity was an imprecise measurement, it was felt that the large sample size and exploratory nature of the study justified its use. Each type of do-it-yourself activity was analysed separately since there were differences in the variance of the dependent variable among the types of activity and because Game? had found that the factors which are related to do-it- yourself activities differ depending on the type of activity. Since M a y e p had shown that men’s and women’s responses to equipment breakdown were quite different and preliminary analysis showed that males were significantly more likely than females to engage in do-it-yourself activity, the sample was divided into male and female subsamples. Multiple regression was used to analyse the relationship between independent variables and the frequency of do-it-yourself activity.

The mean, standard deviation, and frequency distribution of the dependent and independent variables are shown in Table 1. The independent variables were direct or proxy measures of a respondent’s human and material resources - age, education, member of a dual income household, information, household income, residence location, and ownership of housing and durable goods. Consumer information resource variables were: attitude toward the current quality of repair services, satisfaction with goods available, the belief that manufacturers are willing to replace defective products, and a preference for repairing rather than replacing malfunctioning goods. Operational definitions and coding are shown in Table 1.

Tabk 1. Means. standard deviations. and frequencies for variables for male and female subsamples

Variables

Males Females

Mean no 40 Mean n 40

Dependem variables Do-it-yourself home maintenance and repair

never (1)$ once a year or less (2) a few times a year (3) about once per month (4) more than once per month (5)

3.30 (1.21)t

51 10.18 65 12.97

167 33.33 121 24.15 97 19.36 -

2.36 (1-29)

185 3 7 . z 82 16.50

136 27.36 55 11.07 39 7.85 -

501 497 Do-it-yourself car 2.97 2.02 maintenance and repair ( 1.32) ( 1 ~29)

never ( 1 ) 111 22.20 214 55.47 once a year or less (2) 46 9.20 37 7-49

(continued)

43


Table 1. (continued)

Variables

Males Females

Mean n* YO Mean n YO

a few times a year (3) about once a month (4) more than once a month (5 )

Do-it-yourself appliance maintenana and repair

never (1) once a year or less (2) a few times a year (3) about once a month (4) more than once a month ( 5 )

Independent variables Age:

Education:

gradeschool(1) some high school (2) high school graduate (3) some college (4) college graduate (5) postgraduate (6)

Dual income howhold:

Manufacturer willing to repair:

strongly disagree (1) disagree (2) agree (3) strongly agree (4)

Satisfadon with goods:

1.76 (0.97)

38.53 (15.45)

3.92 (1.31)

0.31 (0.46)

2.75 (0-69)

4.12 (0.83)

159 117 67

500

-

262 136 71 23 8

500

-

15 43

160 103 111 71

503

-

154 350

504

-

21 131 290 50

492

-

3140 23.40 13-40

2 2 4 27.20 14.20 4.60 1 *60

2.98 8-55

31-81 20.48 22.07 14.12

30.56 69.44

4.27 26.63 58.94 10.16

110 22.27 45 9.11 28 5.67 -

494 1 *45

(0.81) 345 69.56 97 19.56 39 7-86 10 2.02 5 1.01 -

4%

43.77 (16.86)

3.46 (1.15)

26 5-23 45 9-05

218 43.86 115 23.14 68 13.86 25 5.03 -

491 0.27 (0.44)

132 26.56 365 73-44

497

-

2.83 (0.62)

11 2.28 109 22.57 316 65.42 47 9.73 -

483 4.16

(0.76)

44


Table 1. (continued)

Variable

Males Females

Mean n* 'YO Mean n %

very dissatisfied (1) dissatisfied (2) just barely satisfied (3) satisfied (4) very satisfied (5)

Prefer to repair:

never (1) sometima (2) usually (3) always (4)

Quality of home service:

improved (1) stayed the same (2) deteriorated (3)

Quality of car service:


Quality of appliance service:


Residence location:

urban (1) rural (0)

11 2.21 13 2.62 41 8-25

273 54-93 159 31.99

497

-

2.18 (0.87)

11 2.19 118 23.51 144 28.69 229 45.62

502

-

1.98 (0.62)

93 20.44 280 61.54 82 18.01 -

455 2.29 (0.7)

95 19.12 163 32.80 239 48.09

497

-

2.00 (0.65)

95 20.83 264 57.90 97 21.27 -

456 0.78

(0.41) 391 78.20 109 21.80

500 -

3 0.61 15 3.04 47 9.53

263 53-35 165 33.47

493

-

2.10 (0.90)

22 4.47 109 22-15 160 32.52 201 40.85

492

-

2.00 (0.62)

79 18.85 259 61.81 81 19-33 -

419 2.38

(0.70) 56 12.64

164 37.02 223 50.34

443

-

2.06 (0.68)

88 20.00 236 53.64 116 26.36

440

-

0.75 (0.43)

371 75.10 123 24.90

494

-


Taw 1. (conrinued)

Variables Mean n* % Mean n %

Income: 2.54 (1.37)

<t1o,m (1) tlO.OO1 to s2o.OOo (2) $20.001 to 53o.m (3) $30.001 to w,m (4) w.001 to t S 0 , m (5) >S5O,OOo (6)

46 128 136 58 31 56

455

-

10.11 28.13 29-89 12-75 6-81

12.31

106 25-00 132 31.13 107 25-24

23 5.43 23 5.43

33 7.78

- 424

Ownership of home: 0.68 (0.47)

344 159

503

- 68.39 3 1 -69

347 69-96 149 30.04

4%

-

0.88 (0.33)

476 26

502

- 94.82 5.18

437 87.93 60 12.07 -

497 Ownership of appliances: 0.85

(0-35) 0.88

(0.32) 85.29 14-71

429 74

503

- 437 88.11 59 11-90 -

4%

*Number varies due to missing data. tStandard deviations in parentheses. $coding of variables.

The final model developed for each maintenance and repair activity included the variables which were conceptually important and significant for one or more of the separate analyses. In preliminary analysis, several variables including number in household, marital status, and employment status were tested and eliminated due to non-significance. Quadratic forms for age and income were tested to measure possible non-linear effects. Ownership was included as a control. Owner- ship, income, and education were each separately omitted from the equation to examine whether their absence changed the magnitude, direction, or significance of the remaining variables. The four attitude variables were also entered

46


separately and as a group. The independent variables were checked for multi- collinearity ; no problematic correlations were found.

Cases with missing data on any of the variables studied were eliminated from the regression analysis. Per observation, there was very little missing data. Per variable, missing income data represented the highest loss; 122 respondents had not answered this question. Although deleting the observations with missing data for any of the included variables weakens the randomness of the sample, several methods of handling missing data were tested and consistently yielded little differ- ence in direction, relative magnitude, and significance of the coefficients. Elimination was chosen as the least biased approach.

Results

The regression coefficients for the male and female subsamples for home, car, and major appliance do-it-yourself maintenance and repair are shown in Table 2. The F-tests were significant (P < 0.01) for all six equations. The R-squares ranged from 0.222 to 0.074.

Younger consumers generally engaged in do-it-yourself maintenance and repair more frequently, suggesting that interest and energy, not experience, influences behaviour. Age squared was not significant. The relationship between education and do-it-yourself activity differed among activities and by gender. Women with more education engaged in home and appliance repair more frequently than women with less education, consistent with the hypothesis that education raises efficiency and productivity in household production. For men, lower levels of education were associated with more frequent car repair. Perhaps their employment skills were relevant to the mechanical knowledge needed. A member of a dual income household was expected to have high time demands and, consequently, to engage in do-it-yourself projects less frequently. This hypothesis was supported for men in home and car projects, but not for women. This result could be due to varying degrees of need for maintenance and repair or the effect of other responsibilities. Men who had a preference for repairing rather than replacing malfunctioning goods, which could indicate they had repair interest and skills, were more frequent do-it-yourselfers.

Dissatisfaction with the quality of goods and services in the market was linked to self-production as opposed to purchase. Men who believed that the quality of appliance senice had deteriorated in recent years were more likely to do more appliance repair. A woman who was dissatisfied with the goods she could purchase in her area was more likely to engage in home or appliance repair. However, the belief that manufacturers were willing to repair or replace defective goods, which could imply trust in the market, was not associated with any do-it- yourself activity. These inconclusive findings are probably due to imprecise measurement.

Economic necessity did not appear to be a motivator for do-it-yourself activity

47


Tab& 2. Regression coefficients for male and female do-it-yourself activity

Home car Appliances

Variables Males Females Males Females Males Females

Education

Dual income household Manufacturer will repair Satisfaction with goods Refer to repair

Oualityof scrvicc I m m e

Residence location OIVaCrshiP

Intercept

n

F R2

-0.01' (-2.70)$

+O-06 (+1*2S) -0.43'

(-3.25)

(-1.86) -0.16

+0.06 (+0.78) +O-lSt

(+2*27) +047

(+O.R) +0*55'

(+2-75) -0-08*

(-2.81) -0-03

(-0.22) +0*31t

(+2*16) +2*35*

(+4.29) 398

3.76' 0.097

-0.02'

+0*16t (+2.47) +048 (+Om) -0.22

(-1.88) -0.24'

(-2.69) + O W

(+0.91) +045

(+0-42) -0.40

(- 1.89) +046

(+1-78) -0.26

(-1.59) +0*58'

(+3.43) +4*23'

(+5.86) 335

(-3.30)

4-00' 0.120

-0.03' (-7.01) -0.llt

(-2.33) -0.35'

(-2.75) -0.05

(-0.63) -0.03

+0.21' (+3*13)

+O&?

+0-53' (+2.78) -0.08'

(-3-06) -0-29t

(-2.07) + 1.28'

(+4*81) +2.67'

(+4*65) 430

(-0.36)

(+0*21)

10-81' 0.222

-0.03' (+7.23) +0-08

(+ 1.31) +0.09

(+0*62) -0.05

(-0.47) +0.004

(+0*05) +048

(+1.07) +0.10

(+144) +0-15 (+o.n) -0.03

(- 1.02) -0.23

(- 1.51) +0-76'

(+3*08) +2.10*

(+2*97) 360

7.64' 0.194

-0.01t (-2.01) -0.08

(- 1.94) -0.21 (1.96) -0.10

(-1.46) -0.04

(-0.58) +0*14t

(+2.55) +O. l a r

(+2*50) -0.06 (-0.38) +0-01

(+0*32) +0*13

(+1.12)

(+3-93) +0*61'

+ 1.64' (+ 3-69) 395

3-63. 0-095

-0.01t (+2.18)

+ O W t (+2.06) +042

(+0-16) +0.10

(+0*19) -0.20'

(-3.65) +046

(+ 1-30) +0-03

(+0-49) -0.15

(- 1.12) +0*02

(+ 1.03) -0.01

+0.17 ( + 1.18) +2.09'

(+4.80) 355

(-0.09)

2.49' 0.074

'P<O-Ol. tP<0-05. st-ratios in parentheses.

in this study. Household income was not associated with any type of women's do- it-yourself behawour. The non-linear relationship between men's household income and their home and car maintenance and repair showed that middle income men engaged in do-it-yourself activities more often than either lower or higher income men. This finding suggests that other factors, including inclination and skills, may be more influential than the cost of repairs or insufficient income. However, future research would benefit from a continuous income measure. 48


Rural male respondents were more likely than city dwellers to work on their cars themselves, perhaps implying a sparse, inconvenient, or inaccessible supply of car repair shops. Rural residents also might have more space in which to do repairs. As would be expected, home owners were more likely to be do-it- yourselfers.

Implications

The results of this study can provide guidance for further research. Factors which were related to do-it-yourself activity were not uniform across different types of activity or between males and females supporting previous research finding^.^' Future researchers should design studies of do-it-yourself behaviour accordingly. In addition, the respondent, selected by a random method, reported only their own behaviour. Since differences were found between men and women, if household do-it-yourself behaviour is of primary interest, studies need to be designed so that data from all household members are collected. As Maye?2 stated, surveys that randomly select the adult household members to be interviewed may not be accurate reflections of other members' or the household's behaviour. However, collecting and analysing multiple response data from households is complex and

The low explained variance in do-it-yourself activity, a limitation of the study, showed that other factors are likely to influence do-it-yourself behaviour besides those examined. Further research in this area would benefit from data on specific repair skills and knowledge, attitudes toward do-it-yourself activity such as: interest in maintenance and repair and satisfaction from do-it-yourself activity, age of housing and length of housing tenure, possession and age of specific appliances and automobiles, and possession of appropriate tools and equipment. The lack of variance in the frequency of do-it-yourself activity, especially for appliance repair shows that more quantitative data on the amount and scope of do-it-yourself activity, its specific nature, and maintenance and repair requirements and standards would also aid the explanation of influences.

Several findings can be of some value to consumer educators and providers of do-it-yourself products and information. The consistent effect of age suggests that promoters and designers of home improvement programmes directed toward older homeowners, e.g. energy conservation enhancement projects, need to explore the reasons for less frequent do-it-yourself activity by older consumers. The effects of gender and education suggest that informative brochures and dis- plays, instructional programmes, do-it-yourself manuals should be designed with sex and various education levels in mind. Also, since do-it-yourself activity is less frequent for older consumers and less educated women, researchers, educators and marketers need to examine their repair service needs and information requirements. The indication of a possible link between consumer dissatisfaction with the quality of goods and services and more frequent do-it-yourself activity

49

costly.


suggests that consumer advisers and repair service providers should examine this aspect further, In all cases, however, the findings should be considered tentative.

Although often suggested as a reason for the increase in do-it-yourself activity, lower household income was not related to more frequent household production of maintenance and repair in this study. Economic necessity does not appear to dictate doing it oneself rather than purchasing. This implies that high cost of repair services may not be the primary motivation for do-it-yourself and that price is not likely to be the principal consideration in the purchase of do-it-yourself products. This viewpoint agrees with Browning and Zabr i~kie’s~~ recent study of do- it-yourselfers. Their study also supports the notion that do-it-yourself activity is related more to pursuit of satisfying leisure than economic need.

This study of do-it-yourself household maintenance and repair activity explored an area of consumerhousehold behaviour that has received little attention. It is clear that gender is an important variable for research in this area, as would be expected, but is often overlooked. Study of do-it-yourself activity would also benefit from precise measures of the nature and extent of projects.

Acknowledgment

The authors wish to thank the firms who supplied the data and provided technical assistance.

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A. SwarWander and J. S. Bowers

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relationships between consumer characteristics and do-it-yourself behaviour (do-it-yourself...

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