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Applied H. R. M. Research, 2013, Volume 13, Number 1, pages 37-50
Response Rates and Incentives in a National Employee
Survey: The Case of the Veterans Administration
Katerine Osatuke, Bridget McNamara, Michelle Pohl, Scott C. Moore
VHA National Center for Organization Development
Mark Meterko, Martin P. Charns,
HSR&D Center for Organization, Leadership and Management Research
Sue R. Dyrenforth
VHA National Center for Organization Development
This study examined the impact of non-monetary incentives used to encourage employee participation in
the voluntary, confidential Veterans Health Administration (VHA) All Employee Survey (AES) in 2007 and
2008. The AES is an annual census survey of employee job satisfaction and workplace perceptions. Its
results inform organizational improvement efforts; addressing AES-based findings through action plans
partly defines VHA managers’ performance measures. This prominent organizational role of the survey
makes high response rate important, therefore many facilities incentivize employee participation. Federal
government systems allow only non-monetary incentives. While cost-efficient, their effects have been
insufficiently examined in prior research. We examine the association of nonmonetary incentives types with
response rates in two years of the AES administration and discuss working strategies of applying
nonmonetary incentives to boost response to voluntary organizational surveys.
This study examined the impact of non-monetary incentives on Veterans Health
Administration (VHA) employee participation in the annual voluntary All Employee
Survey (AES) of job satisfaction and workplace climate. The AES results inform national
and local action plans, and the subsequent implementation of those plans is reflected in
managers’ performance measures. Consequently obtaining a high response rate is
important for VHA facilities. Many facilities have utilized various incentives to
encourage their employees to participate in the survey. Federal government systems
allow only non-monetary incentives. While cost-efficient, their effects have been
insufficiently examined in prior research, a gap that we sought to address in the current
study.
Some mixed evidence notwithstanding (e.g., Nelson, Rubin, Hays & Meterko,
1990; Baruch & Holton, 2008), non-monetary incentives appear less effective than
monetary, but more effective than no incentives (Church, 1993; Dillman, 2000; Teisl,
Roe & Vayda, 2006; Yammarino et al. 1991; Yu & Cooper, 1983). Non-monetary or
quasi-monetary prizes and lotteries are often used as AES incentives. Prizes and raffles
(Bosnjak & Tuten, 2003; Brennan, Benson & Kearns, 2005; Heerweg, 2006), including
specifically quasi-monetary rewards—that is, items that have monetary value but cannot
37
be exchanged for cash (Birnholtz, Horn, Finholt & Bae, 2004; Gitelson, Kerstetter &
Guadagnolo, 1993; Kalantar & Talley, 1999; Cobanoglu & Cobanoglu, 2003) effectively
boosted survey participation in prior studies. Several studies found similar participation
comparing lotteries to no incentives (Mortagy, Howell & Waters, 1985; Porter &
Whitcomb, 2004), possibly because the prize was not perceived as valuable (Porter &
Whitcomb 2004). Insufficiently attractive incentives actually depress participation
(Denton, Tsai & Chevrette, 1988): external rewards can “crowd out” intrinsic motivation,
reducing the incentivized behavior (Frey & Jegen, 2001; Marshall & Harrison, 2005).
Food incentives, ineffective in prior research (Kypri & Gallagher, 2003), are frequently
used in the AES but always within a social interaction context (e.g. food during group
celebrations), thus representing a different incentive than food alone. We are unaware of
prior research that examined or made this distinction.
Incentive timing (before or after participation) also matters (Mangione, 1995) but
its effects may vary by administration mode. Over 90% of AES respondents choose
internet over paper and phone. While results were contradictory for mail surveys
(Church, 1993; Willimack, Shuman, Pennell & Lepkowski, 1995), for internet (Bosnjak
& Tuten, 2003), willingness to participate, response rate, or response quality with prepaid
versus promised incentives were similar. The operant conditioning model (Skinner, 1953)
predicts incentives to be more effective if promised beforehand, but distributed after
survey completion. Promising an award contingent upon a behavior (survey response)
enables individuals to operate on their environment to obtain desired consequences. This
mechanism defines all individual behavior (Skinner, 1953) and effective ways of
influencing others. We are unaware of prior studies that considered survey response
behavior within this theoretical paradigm, but we note operant conditioning as a
potentially relevant explanation for the effects of timing and distribution of incentives on
response rates.
Marketing surveys and promising to share results, although not precisely
incentives, boost participation (Dillman, 1978; Fox, Crask & Kim, 1988). Trust in the
survey agenda and interests that resemble those of survey beneficiaries also enhance
survey participation (Heberlein & Baumgartner, 1978; Schneider & Johnson, 1995).
Specifically, job satisfaction (Rogelberg & Stanton, 2007; Spitzmuller et al., 2006) and
positive organizational experiences (Spitzmuller, Glenn, Barr, Rogelberg & Daniel,
2006) increase employees’ survey participation.
The extensive marketing and public commitment to share AES results within
VHA reflect recommended survey best practices (Rogelberg & Stanton, 2007). Findings
from 1990-1994 IO Psychology journals (Roth & Be Vier, 1998) highlight four
participation enhancers: advance notice, identification numbers, follow-up reminders, and
salience. The AES marketing uses all these four, but targets facilities and workgroups,
not individuals, emphasizing that the survey informs action planning and enables
participants to influence their workplace. Marketing to groups reflects the organizational
practice of using results for workforce-targeted improvements, not for individual-focused
actions. This practice raises a new research question: comparing the effects of incentives
38
that reward individual participation versus incentives that reward high response from
workgroups.
VHA’s commitment to widely market, share and use the AES results disallows
no-feedback control groups for empirically assessing marketing and feedback effects.
Nevertheless, we evaluated the effects of tracking and widely announcing workgroup
response rates during the survey open period, hypothesizing higher response rates with
tracking of responses than without the tracking. Additionally, we assessed the effects of
various non-monetary incentives on participation and response quality, and the effects of
rewarding individual response versus rewarding workgroups for high participation levels.
Higher response was expected with more incentives rather than with less incentives; with
workgroup-oriented rather than with individual-oriented incentives; with incentives
promised beforehand rather than during the survey time; and with incentives distributed
after rather than before the survey completion. We examined the effects of the time off
work in contrast to other non-monetary and quasi-monetary incentives given the lack of
prior research including this type of incentive and also given its popularity within VHA.
We included job satisfaction levels and quality of responses as control variables given
cautions about their potential influence raised in previous literature, although we
hypothesized no influence of these variables on response rates and on quality of
responses, respectively.
Method
We examined the association of nonmonetary incentives with VHA AES
participation in years 2007 and 2008. The staff of the VHA National Center for
Organization Development that administers the AES telephoned local survey
coordinators following each survey and asked them to describe the incentives used at
their medical center. Their responses, recorded verbatim, were categorized and coded by
shared themes (Strauss & Corbin, 1990). Table 1 presents incentive categories and
frequencies for 2007 (155 facilities, 12 incentives used) and 2008 (130 facilities, 9
incentives used).
Organizational complexity is a VHA index for medical centers based on patient
volume, patient risk level, range of clinical specialties, services offered, and amount of
teaching and research. Response rates across five complexity groups were examined in
univariate ANOVAs separately for 2007 and 2008.
The relationship between response rates and the overall number of incentives
within facilities (none; 1; 2 or more) was evaluated through univariate ANOVAs.
Final response rates between facilities that tracked and weekly announced
workgroup response rates in 2007, versus facilities that did not, were compared in a
univariate ANOVA. In subsequent years, the entire VHA used the tracking, precluding
the comparison.
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Table 1
Incentives Categories, Number and Percent of Facilities that Used Them in 2007 and
2008
Percent
Incentive type
2007
2008
1. Tracking and widely announcing workgroups response rates
27.0%
100%
2. Providing a theme for the events of AES participation (e.g.
Hawaiian or car racing theme), with corresponding symbols and
visuals widely marketed at facilities.*
2%
0%
3. Enhanced communications about the AES during the survey period
(reminders to participate, appreciation letters, brief workgroup
meetings about the survey)
12%
0%
4. Prizes to members of workgroups with high response rates
28.3%
0%
5. Prizes to individual employees-responders
18.9%
2%
6. Timely completion awards to a pre-specified number of employees
who were the first to participate in the survey *
1.9%
0%
7. Raffles for participating workgroups or individuals:
(a) subcategory: for individual employees-responders,
(b) subcategory: for workgroups with a pre-specified high
response rate
19.5%
12%
6%
22%
17%
12%
8. 59 minutes time off reward for survey completion:
(a) offered to individual employee responders;
(b) offered to workgroups with a pre-specified high response rate
25.2%
8.8%
15.1%
25%
12%
17%
9. A celebratory social event with food (for individuals or
workgroups):
(a) subcategory: on-the-spot popcorn, cookies, small gifts for
individual participants;
(b) subcategory: celebration event with food for workgroups with
pre-specified high response rates
25.8%
23%
13%
8%
11%
19%
10. Fun social event: casual dress days for staff; dress up/dye hair
day*
0%
2%
*Note. These incentives were used at too few facilities to be included in the analyses.
40
In 2007, VHA facilities distributed incentives either before or after survey
participation. In 2008, incentives were all distributed after but announced either before or
during the survey period. We assessed the relationship between response rates and timing
of the incentive distribution (for 2007), or incentives announcement (for 2008), in
univariate ANOVAs.
Effects of incentives on facility participation rates were examined in multiple
regression analyses. Complexity level and overall numbers of incentives within facilities
were control variables. The other predictors included contrasts across particular
incentives: (a) time off (common practice of granting paid time off, in 59-minute
intervals, for achieving pre-specified high participation--granted on a one-time basis, e.g.
not additional paid vacation hours) and any other incentives; (b) incentives conditional on
individual participation decisions, and incentives conditional on workgroups participation
rate; (c) timing: distribution before versus after the survey in 2007; announcement before
versus during the survey in 2008. Regression analyses included five organizational
complexity levels, then were re-run dichotomizing complexity into high (combining
1a,1b,1c) and low (combining 2 and 3), to balance group sizes for statistical power.
Recognizing the potential of incentives to cause multiple survey records (Batagelj
& Vehovar, 1998) or invalid entries (Goritz, 2004; Singer & Kulka, 2002), we computed
facility response rates after deleting duplicate records and responses with inconsistent
demographics (e.g. age 20-29, and 20+ years of VA tenure). We also examined the
association between incentives and record quality (defined as within-facility percentage
of respondents with one third or more ratings missing), using regression models with the
same predictors as above.
We evaluated influence of overall satisfaction on survey participation by
comparing satisfaction ratings measured by the AES, between facilities with high versus
low response rates (VHA mean plus, versus minus, one standard deviation). We
identified facilities in the two groups, selected two random size-balanced samples of
individual respondents from these groups, and compared their overall job satisfaction
ratings through univariate ANOVAs, separately for 2007 and 2008.
Results
The 2007 and 2008 overall VHA AES participation was 71% (individual level).
Facility-level participation ranged from 28% to 100% (mean 77.7%, SD 14.3%) in 2007,
and from 37.5% to 100% (mean 74.5%, SD 13.0%) in 2008. In 2008, 60.2% facilities
used at least one incentive, compared to 62.2% in 2007. In 2008, only 11.7% of facilities
used two or more incentive types, down from 29.4% in 2007. Mean response rates at
facilities that used 0, 1, and 2 or more incentives were, respectively, 71.2% (StD 18.8%),
80.6% (StD 11.6%), and 81.0% (StD 12.5%) in 2007, and 67.6% (StD 12.5%), 78.9%
(StD 12.0%), and 76.6% (StD 8.9%) in 2008.
Organizational complexity. In 2007, response rates did not differ across
complexity. In 2008, more complex facilities had higher participation across the five
41
complexity categories (F (4, 155) = 3.45, p < .010). Response rates were mean 70%, SD
10% for the highest, and mean 80%, SD 13% for the lowest complexity group.
Number of incentives. Response rates increased with larger overall numbers of
incentives within facilities, in 2008 (F (3, 126) = 12.95, p < .001) and 2007 (F (2, 134) =
4.31, p < .006).
Tracking and reporting workgroup response. In 2007, facilities that tracked and
reported workgroup response rates had higher participation (mean 83%, SD 11%) than
facilities that did not (mean 76%, SD 15%; F (1, 135) = 4.68, p < .032).
Timing of incentives. To reiterate a methodological distinction between the two
years, in 2007, incentives were distributed either before or after the survey period. In
2008, incentives were all distributed after, but announced either before or during the
survey. In 2007, facilities that distributed incentives after the survey had higher
participation (mean 82%, SD 13%; F (1, 135) = 12.61, p < .001) than facilities that did
not (mean 73%, SD 15%). In 2008, facilities that announced incentives before the survey
had higher participation (mean 79%, SD 12%) than facilities that did not (mean 69%, SD
12%; F (1, 128) = 23.67, p < .001).
Contrasts between particular incentives. In hierarchical regression analyses
(Tables 2, 3), after accounting for the complexity and overall within-facility number of
incentives, the only significant influence on response rates was that time off related to
higher participation (2007 mean 87%, SD 10%, 2008 mean 81%, SD 10%) than any other
single incentive (2007 mean 76%, SD 10%, 2008 mean 76%, SD 12%). The other
examined contrasts (individual versus workgroup levels of incentives, and the timing of
the incentives) were not significant after accounting for organizational complexity and
overall number of incentives.
Response quality. In hierarchical regression for 2008, no controls or predictors
had significant effects on within-facility percentage of responses with one third or more
missing ratings. In 2007, one control variable, within-facility count of incentives (entered
at the 2nd step of the model, after accounting for the influence of complexity at the 1st
step), resulted in a significant F change (p = .030). Its relationship to response rates,
however, was inverse (negative beta coefficient and bivariate correlation coefficient):
more incentives were associated with smaller, not larger, within-facility percentage of
respondents who had one third or more missing ratings. The incentives count was the
only significant individual predictor (3rd step of the model: β = -.28, p = .024), suggesting
no negative effects of incentives type on within-facility percentage of respondents with
many missing ratings.
Satisfaction levels. In 2007, AES respondents from low versus high response
facilities (total N = 16,742) had similar overall job satisfaction. In 2008 (total N =
16,831), differences in satisfaction were statistically significant (F (1, 16829) = 3.98, p =
.046) but extremely small: effect sizes of .04, corresponding to raw scores difference of
.05 points on a Likert-type scale from 1 (Not At All Satisfied) to 5 (Very Satisfied).
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Table 2
Hierarchical Regression Analyses for Predictors of Response Rates in 2007
Predictor
B
SE
β
Step 1
Complexity level
.575 (2.482)
.960 (2.983)
∆R2
.003
(.007)
.003
(.007)
.059 (.092)
.138***
.134***
(.142***) (.136***)
Step 2
Complexity level
.845 (3.350)
.900 (2.794)
.087 (.110)
Number of
incentives
6.081 (6.115)
1.526 (1.522)
.367***
(.269***)
.214***
(.217***)
Step 3
Complexity level
.423 (2.208)
.895 (2.753)
.043 (.073)
Number of
incentives
4.891 (4.917)
1.819 (1.806)
.295** (.297**)
19.692 (19.466)
6.363 (6.337)
.298** (.295**)
Individual versus
workgroup level
contrast
-2.127 (-2.169)
1.936 (1.929)
-.127 (.-130)
Timing (before,
versus during or
after the survey)
contrast
-.844 (-.876)
2.517 (2.500)
-.033 (-.034)
Time off versus
another incentive
contrast
Adj R2
.076*
(.075*)
*p<.05, **p<.01, ***p<.001.
Notes: Numbers in brackets that follow the reported values show results obtained using dichotomized
levels of complexity. Standard error of the estimate and degrees of freedom at step 1: SE=15,292; df1 = 1;
df2 = 103. At step 2: SE=14,295; df1=1; df2=102. At step 3: SE=13,853; df1=3; df2=99.
43
Table 3
Hierarchical Regression Analyses for Predictors of Response Rates in 2008
Predictor
B
SE
β
2.419 (7.584)
.762 (2.316)
.290** (.298**)
.250***
.180***
(.280***) (.191***)
Step 2
Complexity level
2.382 (7.948)
.687 (2.070)
.285*** (.312)
Number of
incentives
8.269 (8.525)
1.603 (1.586)
.424***(.437***)
.287***
(.333*)
Step 3
.696 (2.102)
.226**(.257**)
1.888 (1.879)
.393***(.413***)
8.480 (8.738)
4.172 (4.120)
.173* (.178*)
Individual versus
workgroup level
contrast
-1.517 (-1.494)
1.293 (1.275)
-.097 (-.095)
Timing (before,
versus during or
after the survey)
contrast
-2.672 (-2.327)
1.860 (1.855)
-.137 (-.120)
Complexity level
Number of
incentives
Time off versus
another incentive
contrast
∆R2
.084**
.084**
(.089***) (.089***)
Step 1
Complexity level
R2
1.886 (6.551)
7.655 (8.055)
.056*
(.054*)
*p<.05, **p<.01, ***p<.001.
Notes: Numbers in brackets that follow the reported values show results obtained using dichotomized
levels of complexity. Standard error of the estimate and degrees of freedom at step 1: SE=12,288; df1 = 1;
df2 = 110. At step 2: SE=11,067; df1=1; df2=109. At step 3: SE=10,7893; df1=3; df2=106.
44
Discussion
Non-monetary participation incentives in organizational surveys are relatively
understudied. For example, among 22 studies with incentives as their main topic
presented at the 64th Annual Conference by the American Association for Public Opinion
Research (May 14-17, 2009), 18 predominantly focused on monetized incentives, 4 did
not specify the type of incentive, and only 2 included some non-monetary incentives. The
interest of our study was to address this gap by focusing specifically on non-monetary
and quasi-monetary incentives. Our findings are relevant for organizations which, by
necessity or by choice, do not use monetary incentives.
In our results, a greater variety of incentives was related to higher participation at
facilities, and so was tracking and announcing response rates (the latter could be
examined in 2007 data only). Of all incentive types, authorized time off had the strongest
(positive) association with participation. Incentive use was unrelated to participation
quality as measured by percentages of incomplete records. Response rates were also
unrelated to job satisfaction levels. These findings suggest working strategies to
encourage organizational survey participation using non-monetary incentives.
Both the organizational complexity and overall number of incentives within
facilities positively affected survey response rates. In our sample, organizational
complexity and the overall number of incentives offered appeared to be interrelated,
possibly reflecting different processes of decision-making with respect to incentives that
are used in smaller and simpler versus larger and more complex organizations. While
conceptually interesting, the relationship between these two variables is pragmatically
relevant only for surveys administered across organizations of different complexity (such
as the same All Employee Survey administered to all the small and large healthcare
facilities that belong to the VHA). Unlike the number of offered incentives, complexity
cannot be influenced by survey organizers, Our results demonstrated that overall within
organizations, offering more rather than less different incentives was associated with
higher response rates to the organizational survey.
Combination of several incentives has rarely been examined (Cobanoglu &
Cobanoglu, 2003). Our finding that a greater variety of incentives relates to higher
response can inform surveyors’ decisions regarding how many incentives to use.
Rewarding individual respondents did not demonstrate stronger effects than
rewarding workgroups for pre-specified high response rates. Distributing individual level
incentives requires identifying the participants, e.g. by having them drop their name off
into a separate box after turning in their paper survey or after completing the survey
online. Such requirements can raise respondents’ confidentiality concerns. Assuaging
these concerns, although unfounded, demands additional time and resources and carries
the liability of potentially dampening the facility response rate. This makes workgroup
level incentives a preferred option compared to individual level. These findings should be
considered in the context of employee surveying within the Veterans Admninistration,
where the AES results serve to inform workforce improvement efforts. Individual
45
incentives may be more applicable within organizations that put employee survey data
towards more individual-oriented uses.
With some exceptions (e.g. Hagget & Vincent-Wayne, 1994; Cobanoglu &
Cobanoglu, 2003), survey research oftentimes overlooks the cost of incentives. One AES
incentive, tracking and announcing response rates, involved almost no operational costs
and was associated with significantly higher response rates in 2007. Largely in response
to this finding, the VHA encouraged consistent use of this strategy in subsequent years
and the resulting lack of variation in this practice precluded empirical testing of the
effects of announcing response rates in survey years following 2007.
Researchers are cautioned about possible effects of job satisfaction on
organizational survey participation and potential influences of incentives on response
quality (i.e. percent of missing values) (Rogelberg & Stanton, 2007). We assessed these
influences, which is rare when studying incentives (Rogelberg & Stanton, 2007), and
found response rates to be unrelated to satisfaction levels across facilities. The number or
type of incentives and use of each particular incentive was unrelated to response quality,
with one exception. In 2007 only, as the total number of incentives at a facility increased,
the percentage of responses with a third or more missing ratings declined–results that do
not caution against using incentives.
In both years examined, the relationship between participation and incentive
timing supports the motivating effect of incentives within the Skinnerian paradigm of the
operant conditioning model. Incentives offered or announced before the survey had
significant relationships to response rates whereas incentives offered after or announced
during the survey did not. These findings are consistent with the key postulate of the
Skinnerian model: promising an award contingent upon a future behavior (survey
response) will increase the frequency of the behavior (response rates). Our results provide
initial support for the relevance of the operant conditioning model to explaining how the
timing of incentives influences survey participation behaviors. The operant conditioning
model has an implication important for annual surveys: rewarding participation in a given
year is expected to reinforce the chances of participation in subsequent years. This
hypothesis can be tested in future research.
Incentives of non-significant impact had low prevalence, suggesting low analytic
power as a possible explanation. Importantly, no examined incentives were associated
with significant participation decreases, suggesting they did not appear aversive to
respondents.
Limitations
This study did not use experimental design; we did not prescribe particular
incentives to facilities or analyze incentive effects nested within facilities. Experimental
designs typically remain unavailable for studies in real-world settings, a limitation that
we addressed by statistically controlling for major potential confounding factors (facility
46
complexity, job satisfaction) and replicating the findings across two years to verify their
stability.
Relationships between incentives and response rates differed across
organizational complexity levels. Given the small subsamples within complexity
categories, we did not systematically examine these differences. For survey
administrators, organizational complexity represents a given (can be identified but not
changed), suggesting less relevance of “why” than of “what” the impact of incentives is
for given complexity levels.
We examined incentives with an impact broad enough to observe at the facility
level. Using workgroup level data could clarify the effects of workgroup types (e.g.,
clinical versus administrative, hourly versus salaried employees). Longitudinal approach
could clarify the timing effects. For example, assessing participation immediately before,
then after, announcing specific incentives could distinguish incentives that enhance
already high response rates, from incentives that improve low but not high participation.
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Author Note
Address for correspondence:
Katerine Osatuke, PhD
Health Scientist / Research Director
VHA National Center for Organization Development
11500 Northlake Drive, Suite 230
Cincinnati OH 45249
Email: [email protected]
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