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GABRIEL TAN* AND STANLEY MURRELL
R E S P O N D E N T C H A R A C T E R I S T I C S IN C I T I Z E N
E V A L U A T I O N OF M U N I C I P A L S E R V I C E S
(Received 6 April, 1983)
ABSTRACT. Research on citizen surveys tend to focus on how to conduct a survey and how to best utilize the survey data. How respondent characteristics affect responses to a survey has received only cursory treatment in the fiterature. The present study investigated the role of demographics and generalized attitude, two types of respondent characteristics, in citizen evaluations of municipal services. Of particular interest was the pattern of respondent-responses interaction across time. The Automatic Interaction Detector (AID) was used to analyze survey data collected annually from 1974 through 1979 by a University-aff'fliated Urban Studies Center in a mid-size metropolitan area. Results indicated that these respondent characteristics could account for a substantial portion of the variance associated with service evaluation. However, the relationship between respondent characteristics and service evaluations is nonlinear, interactively complex and lacking in consistency across time. This widely varying pattern of respondent-responses interactions across time was explained in terms of the effect of a third exposure-experiential factor. Implications for future research and for using citizen survey data in pubfic policy analysis and program development were discussed.
INTRODUCTION
Citizen survey is increasingly being used by city and county governments to
rink governmental preformance more closely to government's 'customers', the
citizens. Some forms o f ongoing surveys (annual or biannual) are being carried
out in cities like Dallas, Dayton, St. Petersburg and Louisville, among others.
Utilization of the survey data varies but typically includes establishing
performance objectives, comparative ranking of services and making specific
policy decisions.
Stipak (1980) has suggested that usage o f such data is a function o f the
type o f decision makers running the municipal governments. The 'practical'
manager focuses on getting relevant and usable data. In contrast, the
'technological' manager pays careful attention to procedures for instrument design, sampling and statistical analysis. The 'critical' manager looks beyond
the data gathering process and face validity o f the data and focuses, instead, on the careful interpretation and analysis o f the data. Finally, the 'politically
astute' manager's main concern is to incorporate citizen surveys successfully into the political process.
Social Indicators Research 14 (1984) 29-52. 0303-8300/84/0141-0029502.40. �9 1984 by D. Reidel Publishing Company.
3 0 G. T A N A N D S. M U R R E L L
Although the scope and nature of its application and utility depend on the biases and motives of the decision makers, citizen survey has no doubt contributed towards a greater reliance on data in the operation of municipal government. In this age of information oversaturation where government officials and consumers alike are constantly being bombarded with numbers, figures and 'statistics', it is imperative that knowledge on the reliability, validity and appropriate utilization of survey data be continuously updated and refined.
Most research to date tends to focus on how to get survey data and how to use them (e.g., Daneke and Klobus-Edwards, 1979; Clark, 1976). How re- spondent characteristics affect responses to these surveys have received relatively cursory treatment. Furthermore, no study to date has used longitu- dinal data to study the pattern of respondent-responses interaction across time.
One type of respondent characteristic commonly used in surveys is the demographics such as age, race, sex, education and income. The importance of demographics in the understanding and prediction of community behavior and attitude needs no introduction. A recent review of the literature by Tan (1980) indicates that there is some evidence supporting the proposition that demographics are correlated to political orientation, preference and attitude towards community service. However, such evidence seems weak, scattered, and nonaggregatable.
Since citizen survey often deals with attitudinal data, viz, perception of services, rather than the actual service itself, another type of respondent characteristic could be what has been called a general-evaluative orientation towards government. The notion here is that the evaluation of a specific service might be heavily influenced by one's general attitude and perception of government in general. Some support for this thesis has been found by previous research (Stipak, 1977; Murrell and Shulte, 1979).
P U R P O S E
The current study proposes to address these questions: (1) Are respondent characteristics, specifically demographics and general-
lized attitude towards government important in the understanding and interpretation of data from citizen surveys?
(2) If so, what role and impact do they have on the survey responses? (3) How do respondent characteristics interact with responses over time?
CITIZEN EVALUATION OF MUNICIPAL SERVICES 31
DESIGN
The University of Louisville Urban Studies Center has been commissioned by the Jefferson County government in Kentucky to conduct annual citizen sur- veys since 1974. Jefferson County, where the city of Louisville is located, has a population of approximately 800 000 and the typical urban-suburban mix of a mid-size U.S. metropolitan area. Among other objectives, this series of annual surveys requested citizens to evaluate the performance of urban- municipal services by assigning letter grades A through F to each service, much like a report card. Identical questions were repeated throughout these surveys making it possible to compare citizen's perceptions of services across the six-year time span (1974 through 1979). Approximately 350 to 400 re- spondents were selected for each survey using a stratified random sampling procedure which attempted to control for the age, sex, and racial representa- tions in each survey area. More specific information concerning the design and implementation of the surveys can be obtained directly from the Urban Studies Center or its publications.'
For the present study, a post hoc multivariate statistical analysis was per- formed on the survey data collected from 1974 through 1979.
Dependent Variables
The dependent variables for this analysis were grades citizens had assigned to school, police protection, fire protection and mass transit services. These four services were selected out of a list of 20. School and police protection were selected because of the hightest priorities the Jefferson County citizens have consistently accorded these services across the six-year span. Furthermore, recent court-ordered busing had highly accentuated controversy on the delivery of these services in Jefferson County. In contrast, fixe protection and mass transit were relatively more concrete and clearly def'med services, the evaluation of which was probably less subject to emotional bias and distor- tion. At least for the mass transit service, the level of services also appeared to differ widely throughout the county making subsequent analysis of the level of services possible.
Independent Variables
These independent variables were included: race, sex, age, income, education,
32 G. TA N A N D S. M U R R E L L
area of residence, length of residence, whether renting or owning residence and responses to two survey questions asking respondents to rate the state of their community as a whole as compared to five years ago. The first eight
variables are basic demographic characteristics solicited by the survey and the last two variables refer to the general-evaluative orientation previously dis- cussed.
The Automatic Interaction Detector (AID)
The AID is a statistical procedure developed by Sonquist et al. (1973)at the University of Michigan Institute of Social Research. This computer software can be used to analyse systematically a set of independent variables and how they interact to account for the variance of a dependent or criterion variable.
The AID procedure was selected for this study since previous research has pointed towards the interactive nature of the independent variables. Further- more, while other statistical techniques such as stepwise regression and variance analysis demand that interaction effects be measured over the whole sample, the AID procedure measures the effect of each predictor on each sub- group - this is certainly more reflective of the real world. Finally, the AID procedure does not require the assumptions of linearity, additivity, and orthogonality. It was, therefore, believed that this procedure would be most applicable for use with field survey data such as that being investigated in this study.
Data Analysis
The AID program was used systematically to identify and analyse the inter- action patterns among the independent variables as they combined to predict the dependent or criterion variable of service grades. The survey data was first pooled across the six year span to provide a sample of over 2000 cases with a separate AID analysis being executed for each of the four service types. The analyses were then repeated adding 'time' as an independent variable. Com- parison of the program outputs with and without the 'time' variable allowed one to address the issue of stability and/or variation in citizen's perceptions of services across time. Finally, AID analysis was also obtained for each indi- vidual year for each service type.
TA
BL
E I
Mea
n an
d to
tal
vari
ance
exp
lain
ed c
olle
ctiv
ely
by d
emog
raph
ic a
nd g
ener
aliz
ed a
ttit
udin
al v
aria
bles
r Z
t~
<
Pol
ice
serv
ice
Sch
ool
serv
ice
Fir
e se
rvic
e
N
Y
% V
ari-
N
Y
%
Var
i-
N
an
te
an
co
Mas
s tr
ansi
t se
rvic
e C
%
Vad
- N
Y
%
Var
i-
> an
ce
ance
,~
1974
19
75
1976
19
77
1978
19
79
19
74
-19
79
(p
oo~
d)
328
2.51
10
.2
328
2.28
12
.7
328
2.01
8.
7 36
6 2.
50
10.6
36
6 2.
52
13.5
36
6 2.
14
12.9
37
8 2.
59
11.9
37
8 3.
17
18.4
37
8 2.
05
5.8
409
2.60
11
.4
409
3.08
17
.6
408
2.11
6.
6 42
9 2.
65
8.5
429
3.00
15
.7
428
2.15
8.
3 44
1 2.
89
7.0
441
3.50
13
.1
441
2.47
11
.8
2351
2.
63
3.0
2351
2.
96
6.5
2349
2.
17
2.8
328
2.70
13
.5
Z
366
2.45
13
.8
0 37
8 2.
24
12.9
"~
40
9 2.
19
13.1
42
9 2.
39
9.7
C
:Z
441
2.84
13
.6
> 23
51
2.47
1.
1 t'-
'
Im
.<
r
34 G. TAN AND S. MURRELL
While the AID program's capacity is enormous, its utilization in this proposed research was intended primarily to provide the following informa- tion:
(1) The total % variance that could be explained by the independent variables as they interacted to predict the dependent or criterion variable.
(2) The pattern of interactions among the independent variables as revealed by the 'tree analysis'.
(3) Which independent variables were important and which ones were not with respect to reducing the error variance.
RESULTS
Variance Explained by Predictor Variables
The results of this study indicated that demographic and generalized attitu-
dinal variables account for a substantial portion of the variance when used
collectively to predict citizen evaluations of community services. The variances
explained by these predictor variables are shown in Table I. 2 For all four
service types tested, the respective multiple correlation coefficients ( R ) o r
other appropriate statistics for the pooled six year samples were significant at
the 0.01 level. (See Table II.) When each of the independent variables was
cross-tabulated against evaluation scores for each of the four service types
TABLE II
Statistical test of significance for 1974-1979 pooled sample
Variable Beta Pearson r Police School Fire Mass transit
Age Generalized attitude
towards county (G) G • Age xG Age x area
N df Multiple R R ~
0~09E-06 0.206
2383 2379 0.193 a 0.037
0.176 0.665E-06 0.095 a
0.258 0.187 0.274
2394 2376 2391 2373 0.269 a 0.158 a 0~72 0.025
2308
a p < 0 . 0 1 .
TA
BL
E I
II
Ser
vice
ev
alu
atio
ns
by
dem
og
iap
hic
s an
d g
ener
aliz
ed a
ttit
ud
es N
= 2
45
7 (
19
74
-19
79
po
ole
d s
amp
le)
rn
Z
Police
Sch
oo
l F
ire
Mas
s T
~an
sit
t~
Var
iabl
e X
~
Tau
C
X*
Tau
C
X ~
T
au C
X
= T
au C
Survey are
a 148.65 c
191.52 c
143.21 c
92.22 c
Sex
6.52
0.007
8.60
0.007
8.07
-0.044 a
21.66 c
-0.010
Age
56.05 c
-0.055 c
127.09 c
-0.108 c
67.79 c
-0.104 c
80.75 c
-0.029
Race
86.68 c
0.095 c
51.92 c
-0.080 c
18.82 b
0.017
20.56 c
-0.015
Tim
e liv
ed i
n Je
ffer
son
County
50.43 c
0.007
44.39 b
0.001
67.32 c
-0.011
20.10
0.005
Education
46.03 b
0.003
74.63 c
-0.130 c
36.30
-0.049 b
56.96 c
-0.089 c
Rent/Own
26.68 b
0.025 a
23.35 a
-0.018
36.37 c
-0.059 c
17.68
0.003
Income
61.85 c
-0.004
146.83 c
-0.088 c
76.23 c
-0.020
81.44 c
-0.028 a
Gen
eral
ized
att
itu
de
tow
ard
s n
eig
hb
orh
oo
d
136.
31 c
0
.09
7 c
89
.45
c 0
.06
4 c
9
7.8
2 c
0.
051
c 9
1.3
4 c
0
.06
0 c
G
ener
aliz
ed a
ttit
ud
e towards county
284.53 c
0.121 c
285.22 c
0.163 c
159.97 c
0.073 c
185.31 c
0.064 c
Z O Z ~3
t~
a p
< 0.
05.
b p
< 0.
005.
c
p <
0.00
1.
M U3
t~
36 G. TAN AND S. M U R R E L L
TABLE IV
Effects of "time' on total variance explained by demographic and generalized attitudinal variables
Variance explained
Without "time' With "time'
Increment (With "time'/Without 'time')
Police 3.0% 3.0% 0 School 6.5% 14.3% 220% Fire 2.8% 5.5% 196% Mass transit 1.1% 6.0% 545%
tested, the resulting X 2 and/or Kendall's tan C a indicated statistical signif- icance at the 0.05 level or better, for all except a few of the correlations. (See Table III.)
Patterns of Interaction A cross Service Types and Across Time
The AID tree analysis for each of the four service types was illustrated by Figures 1 through 4. When the time variable (survey year) was added to the analysis, the resulting 'trees' are shown in Figures 5 through 8. In comparing Figures 1 through 4, one notes some resemblance in the pattern between fire service (Figure 3) and school service (Figure 2). However, this resemblacne diminishes when the time variable is added to the analysis. Furthermore, when each of the service types is examined by each individual year from 1974 through 1979, any resemblance between service types becomes almost impos- sible to detect.
When service evaluations are compared across time (Figures 1 through 4 versus Figures 5 through 8), a considerable increase in the total variance explained is noted when time element is introduced for three of the four service types. Table IV shows the precentage increase for each service type which ranges from 0% for police to 545% for mass transit services.
Service Level Confounding
Finally, an attempt was made in this study to rule out possible confounding between service level and service evaluations. Table V shows that the correla- tion between a service level measure and mass transit evaluation for 1979 was
CITIZEN EVALUATION OF MUNICIPAL SERVICES
TABLE V
Frequency matrix for service level index by mass transit grade a
Mass transit grade
Service level index 1 2 3 4 5
2 1 19 29 6 1 4 3 13 15 5 3 8 6 18 18 8 2 9 1 12 35 11 2
12 6 25 11 8 2 17 6 25 16 1 0 20 1 17 31 8 1 27 3 32 30 8 0
N = 439 Pearson r = -0.08645 b
a Data for 1979 only. b p < 0.05.
37
statistically significant at the 0.05 level. However, when its power or capacity
to explain variance of the dependent variable was tested against that of the
demographic and generalized attitudinal variables in a subsequent AID
analysis, the role of service level appeared ne~li~ble. Specifically, introduc-
tion of the service level measure to the AID analysis did not alter the out-
comes of the analysis. Figures 9 and 10 show that the AID 'trees' for mass
transit service evaluations for the year 1979 without and with 'service level'
added to the analysis are identical.
DISCUSSION
This research has set out to determine the role of respondent characteristics such as demographics and generalized attitudes in citizen evaluations of com-
munity-urban services. The results indicated that a selected number of these
characteristics can explain a substantial portion of the variance attributed to the evaluation grades for all four service types tested. This relationship, how- ever, is not linear but interactively complex and multifaceted. Specifically, the following observations can be made.
(1) The interactions between the respondent characteristics are consistent- ly more powerful predictors than the individual variables themselves.
LO
Oo
Total
Sample
N =
2351
Y
ffi 2.
63
Positive
N
= 11
20
u - 2.48
Generallzed A
tt
lt
ud
e~
Towards County
1.9%
Neut
ral,
Negative
Race
N
=
12
31
1
.1%
ffi
2.7
7
Whites
N =
10
86
u =
2.72
Blacks
N =
145
u =
3.18
> Z > Z ~e
~n
t"
t"
Fig
. 1.
A
ID '
tree
ana
lysi
s' f
or p
olic
e se
rvic
e. (
Surv
ey y
ear
excl
uded
fro
m a
naly
sis.
) T
otal
var
ianc
e ex
plai
ned
ffi 3
.0%
.
Total Sample
N = 2351
Y ffi 2.96
60
and
Old
er
N - 346
Y ~ 2.35
~ Central and South
I L
ou
isv
ille
, S
ou
thw
est
and
Eas
t Je
ffer
son
C
ou
nty
[
- 14
7 [
Y ffi
1.9
3 [
I Su
rvey
Area
l.Og
-~
[West and East
I L
ou
Isv
Ille
, [
Sou
th
and
So
uth
east
[J
eff
ers
on
County
[ ~
- 19
9 Y
ffi 2
.66
I 15
-
59
I Year O
ld
I Generalized Attitude
~ 20
05
Tow
ard County
Y -
3
.07
2.
1%
Positive,
Ne
utr
al
N =
13
99
Y -
2.9
2
Neg
ativ
e - 606
Y =
3
.40
Fig
. 2.
A
ID '
tree
ana
lysi
s' f
or s
choo
l se
rvic
e. (
Surv
ey y
ear
excl
ud
ed f
rom
ana
lysi
s.)
Tot
al v
aria
nce
expl
aine
d =
6.5%
.
f~
Z
< > > z 0 c z < R
o~
CD
Total Sample
N = 2349
Y = 2.17
60 and Over
N
ffi
34
4
Y
=
1.8
6
.
15 - 59
Year Old
N = 2005
Y = 2.22
Positive
=
95
9
Y
ffi
2.1
0
Generalized Attitude Toward County
1.1%
Neutrsl or
Negative
= 1046
Y = 2.32
Z
Z
t~
Fig.
3.
AID
'tr
ee a
naly
sis'
for
fir
e se
rvic
e. (
Sur
vey
year
exc
lude
d fr
om a
naly
sis.
) T
otal
var
ianc
e ex
plai
ned
= 2.
8%.
CITIZEN E V A L U A T I O N OF MUNICIPAL SERVICES 41
l i I I
/
il
.j
.<
b~
Total
Sample
N =
2351
Y =
2.63
~~
Positive
--
erallzed Attitude
ards County
1.9% Negative
Race
N_ = 1231
l.l%
Y =
2.77
Whites
N =
1086
Y =
2.72
Bla
ck
s
N =
145
Y
ffi
3.1
8
> Z
> Z
U~ ~v
~v
t"
Fig.
5.
AID
'tr
ee a
naly
sis'
for
pol
ice
serv
ice.
(Su
rvey
yea
r in
clud
ed i
n an
alys
is.)
Tot
al v
aria
nce
expl
aine
d ffi
3.0
%.
Total
Sam
ple
R
-
2351
Y
- 2.96
//•
19
74
, /
[19
75
6.
1
s ...
. ~Y
ear
/ 1
97
6-
[ 19
79
[ N
- 1657
u - 3.19
I
I I
1.2%
15
-59
Y
ear
Old
N
=
57
0
Y =
2.54
W, C,
S
Lou
N -
55
6
Survey Area
1.9%
60 and
Over
N ffi 12
4 Y
ffi
1.8
2 Survey
Year
I. 6%
1976-1978
N =
396
Y =
2.65
1979
-
160
Y -
3
.44
60 and
Older
N - 13
3 Y
ffi 2
.80
o
l:l C
ou
nty
Balance
N -
If01
.
�9
15 -
59
ffi 3
.35
Yea
r O
ld
N -
968
Y-
3.43
I SW
, E
County
- 46
Y -
2
.07
Su
rvey
A
rea
0.8%
Po
siti
ve
, I
Neutral
General
Attitude
N -
639
[ T
ow
ard
~
ffi
3.2
8
County
~ Negative
N -
329
= 3.73
E L
ou,
S, SE County
N ffi
87
Y f
fi 3
.18
(n
Z <
> c >
.q
O
-a
c Z > < ra
4~
F
ig,
6,
AID
'tr
ee a
naly
sis'
for
sch
ool
serv
ice.
(Su
rvey
yea
r inc
lude
d in
ana
lysi
s.)
Tot
al v
aria
nce
expl
aine
d =
14.3
%.
Total Sample
N = 2349
Y = 2.17
1974
-
1978
~S
urve
y Y
ear
2.3%
I
Y = 2.47
1.0%
J Survey Area
2.1%
I 60 and
Over
N
= 34
4 Y
=
1.86
15 - 59
Year Old
N
ffi 1
564
Y ffi 2.15
All Other
Areas
N = 333
Y
ffi 2
.30
SW, E
County
N =
I15
Y = 3.02
Fig
. 7.
A
ID '
tree
ana
lysi
s' f
or f
ire
serv
ice.
(Su
rvey
yea
r in
clud
ed i
n an
alys
is.)
Tot
al v
aria
nce
expl
aine
d =
5.5%
.
4~
> Z >
Z
Total
Sample
N ffi 2351
Y = 2.47
1974
-1978
=
19
1o
Y ~
2.38
/ I
Surv
ey Ye
ar
2.2Z
I 19
79
= 441
Y = 2.84
Less Than
Hi School
Graduate
N =
759
u
2.19
/
Education
1.2Z
Ill School
Grad and
Above
= 11
51
Y =
2.5
1
All Other
Areas
N =
378
/ - Y
= 27
3
Surv
ey
Are
a
SW County
N ffi 63
V = 3.49
[ 19
76-7
8 N
ffi
742
Y=
2.
35
I Su
rvey
Yea
r 1.
6% 19
74, 1975
I = 409
Y =
2.80
Z < z o Z
{-
Ca
< Cn
Fig
. 8.
A
ID ~
ree
anal
ysis
' for
mas
s tr
ansi
t se
rvic
e. (
Sur
vey
year
inc
lude
d in
ana
lysi
s.)
To
tal
vari
ance
exp
lain
ed =
6.0
%.
4~
L~
Tot
al
Sam
ple
= 441
Y =
2.8
4
All
Os
Areas
N =
378
= 2:73
S yArea
....
4.7%
7i!7
Tech
Sc
hool
and
Lo
wer
=
272
Y =
2.6
1 du
cati
on
1.8%
Above Tech
Scho
ol
- 1o
6 Y
ffi 3
.02
~n
H
i Sc
hool
G
rad
and
Abo
ve
N =
37
u -
3.08
Below
Hi School
Grad
N
ffi
26,
u =
4.08
Posi
tive
ffi
90
u =
2.29
I G
euer
al
Neu
tral
, A
ttit
ude
Neg
ativ
e To
war
d N
= 1
82
Nei
ghbo
rhoo
d Y
ffi 2
.77
2.1%
lurv
~ey
E Lo
u N
=
33
lAre
a I
V "
2.
67
l o.gz
I
W,
C,
S Lo
u S,
SE
, E
Cou
nty
= 73
Y =
3.18
C,
S Lo
u S,
SE
Cou
nty
N_ ~
122
Y
= 2
,59
Surv
ey A
rea
I .g
Z
I W
, E
Lou
N=
60
Y=
3.15
Fig
. 9.
A
ID '
tree
ana
lysi
s' f
or m
ass
tran
sit
serv
ice
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E Lou
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W, C, S Lou
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County
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. 10
. A
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al v
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nce
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48 G. TAN AND S. M U R R E L L
(2) The interaction patterns differ considerably from year to year for all four services types tested.
(3) The interaction patterns basically differ among service types even though some similarity is also noted.
(4) The introduction of 'time' into the analysis consistently dilutes and lessens the strength of the relationship.
The implications here are quite clear. First, it is not meaningful for decision makers to ask simply if a specific respondent characteristic such as race is an important determinant of service evaluation. Instead, one should look at a specific service type and ask how do different respondent subgroups differ in their perceptions of that service. For instance, this research indicated that race is important only for police service evaluation, and only among the subgroup who had a negative generalized attitude towards the community. For other subgroups (as defined by various combinations of respondent characteristics) and other service types, race plays a minor and insignificant role in the prediction of evaluation outcome.
Second, and perhaps more important, the role of respondent characteristics varies considerably from year to year presumably mediated and/or confound- ed by an exposure-experiential factor. Among this may be included the emotional climate related to the nature and extent of media coverage at the time of the survey. For instance, when analysed across time, perception of school service reveals a definite split between 1974-75 and 1976-79 which coincided roughly with the occurrence of a controversial community event in Jefferson County, viz, court-ordered busing for desegregation. During the pre- busing years, those 60 and older rated school services more favorably as com- pared to the younger residents of the county. The post-busing years, however, showed a more complex interactive pattern between survey areas, survey years, age, and generalized attitude towards community.
Another interesting finding is that some respondent characteristics such as area of residence and education appear to have a less stable relationship to service evaluations across time than other respondent characteristics such as age. If one were to pick any one year for the purpose of analysis, the proba- bility would be very high that area of residence and education would explain the larger portion of the variance attributable to respondent characteristics. Yet, with samples pooled across several years, the role of these two variables would all but disappear from the effective predictor list. While the reason behind this phenomenon is not entirely clear, a plausible explanation lies with
CITIZEN E V A L U A T I O N OF M U N I C I P A L SERVICES 49
the observed lack of a consistent pattern between these variables and service evaluations. For instance, high education may be associated with poor evalua- tion one year but good evaluation the next year. Similarly, those living in cer- tain geographical areas may fluctuate from year to year in their ratings of a certain service. At least in the case of area of residence, the apparent multi- dimensionality of this variable would be expected to contribute towards its sensitivity to change. Unlike age, for instance, area of residence could represent a variety of geographical as well as socioeconomic affinity characteristics.
At a somewhat different level, one could raise the question of what role service quality plays, if any, in confounding the relationships between the respondent characteristics and service evaluations. Previous f'mdings by Stipak (1976) among others, of no relationship between objective indices of service performance and service evalutions has been partially supported by the cur- rent research finding that evaluations of Mass Transit service for 1979 were not affected by the introduction of a service level measure. These findings, however, do not fully address the issue of service quality since credence was not given to the factor of service utilization outcome. Objective indices are statistical 'averaging' measures which do not discriminate between those who have had personal contact with a particular service and hence might be in a better position to judge the quality of the service than those not personally exposed. Future research will need to control for this personal exposure- experience dimension.
Suggestions for Future Research
On the whole, the current research findings appear to support Stipak's (1'976) contention that adoption from reference groups and generalization from other attitudes do play a substantial role in determining citizens' evaluations of community-urban services. In order to further explore and clarify this conceptualization, the following steps for future research are suggested. These steps are based on a proposed model which stipulates 'exposure' as a mediating variable between respondent characteristics and service evaluations. 'Exposure' can be either via personal experience or via mass media publicity.
(1) Develop a measure for 'exposure' which might include frequency and outcome of previous contact with services, and degree of mass media publicity designated as positive, neutral, or negative.
5 0 G. T A N A N D S. M U R R E L L
(2) Investigate how these exposure measures interact with respondent characteristics in the process of shaping citizens' perception of services.
(3) The origin and nature of generalized attitude needs to be further darified. Is attitude generalization the outcome of geographical (neighbor- hood) or SES affinity? What is the relationship between demographics and generalized attitude?
(4) Specification of respondent characteristics into meaningful subclasses and inclusion of other respondent characteristics might help to further delineate the role of these variables to service evaluations.
(5) Develop a scheme for grouping services under certain dimensions such as high versus low priority, essential versus less essential, high versus low probability of direct citizen contact, etc. This might help to get at the basis for attitude fromation.
(6) Extension of analysis to include other services besides the four tested especially if done in conjunction with the other suggested steps would help to determine the generalizability of current findings to all community-ruban services.
(7) In every case, it is recommended that future investigations utilize data across several years rather than a single year and that the AID procedure be included whenever applicable.
Utilization of Survey Data
Finally, the issue of utility of citizen survey both as an evaluation tool and as a data source must be critically examined. The results of this and other previous studies have left no doubt that citizen survey can provide useful information for decision making and policy analysis, however, the issue of what information is gathered for what purpose must be more ready addressed by future research. Survey questions which ask citizens to grade or rate a service produce subjective and attitudinal data which should not be confused as feedback on actual service performance. Attitudinal data, especially when further explored by the proposed future research, can be used to identify 'high risk' groups and clustering of volatile emotion which often stand in the way of effective operation of government services. When thus identified, intervention earl be developed and tailored towards these specific groups. The fact that one is dealing with attitude formation and attitude change would suggest that knowledge and previous research in this
CITIZEN E V A L U A T I O N O F MUNICIPAL SERVICES 5 l
area can be applied to the advantage of the decision maker or decision making
group. For instance, the potential of harnessing mass media for shaping positive as well as negative attitudes twoard public community services is relatively untapped as compared to the private counterparts in consumer research and product advertising. Satisfaction depends not only on quality of a product or service but also on the image and attitude associated with the product or service. It would, therefore, seem legitimate, if not essential, for policy makers to view the successful operation of services as having both objective quality and subjective attitudinal dimensions. At least in this sense, citizen survey can be used as a 'dip stick' to sample community attitude among various subgroups.
Citizen surveys can also be used to provide more objective, performance- based feedback when the survey questions get begond the general global
rating level. For instance, those having had personal contact or having utilized a service can be identified and specific performance questions asked. The answers to these questions can then be compared to service objective and local or national norms. Specific, qualitative feedback on the nature of past contacts and other questions pertaining to improving future delivery of services can also be included to expand the utility of citizen survey. In this sense, citizen survey, when routinely conducted, can be a useful program evaluation and development tool.
NOTES
i Community Priorities and Evaluations, Report 1 through Report 16, 1974 through 1979. The University of Louisville Urban Studies Center. 2 For all tables and figures presented in this report, P stands for the mean evaluation grade; the lower the value, the better the rating and conversely, higher value indicates less favorable grade. (l =A, 2=B, 3=C, 4=D, 5=F). 3 The X 2 statistic can be used for both the nominal and ordinal variables reported; however, Kendall's tau C is more conservative and appropriate for ordinal level variables.
B I B L I O G R A P H Y
Clark, T.N.: 1976, Citizen Preferences and Urban Policy (Sage Publications, Beverly Hills).
Daneke, G. A. and P. Klobus-Edwards: 1979, 'Survey research for public administrators', Public Administration Review (September/Oct. issue), pp. 421-426 .
Murrell, S.A. and P. Sehulte: 1979, 'Measuring citizen evaluations of services amidst community change', mimeographed paper (University of Louisville, Department of Psychology).
52 G. TAN AND S. MURRELL
Sonqnist, J. A., E. L. Baker, and J. N. Morgan: 1973, Searching for Structure (Institute for Social Research, University of Michigan).
Stipak, B.I.: 1976, 'Citizen evaluations of urban services as performance indicators in local policy analysis', Ph.D. dissertation (University of California, Los Angeles).
Stipak, B. I.: 1977, 'Addendum to attitudes and belief systems concerning urban services', The Public Opinion Quarterly 41, pp. 41-55.
Stipak, B.I.: 1980, ' local government's use of citizen surveys', Public Administration Review (Sept./Oct. issue), pp. 521-525.
Tan, G.K.: 1980, 'The role of demographics and generalized attitudes in citizen evaluations of community service', Ph. D. Dissertation (University of Louisville, Louisville).
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