The Effect of Performance Pay on Incentivised
and Non-Incentivised Performance Measures:
Evidence from Personnel Data
Jan Sauermann
October 2011
Abstract
A growing literature has shown that performance-related pay substan-
tially enhances workers’ productivity. In many professions, however,
productivity has several dimensions. This paper makes use of a pol-
icy discontinuity in the call centre of a large firm, which entails the
introduction of a bonus related to output quality (customer satisfac-
tion). Estimation results show that customer satisfaction increases by
15 percent with the introduction of performance pay. In addition to
this incentivised measure of quality, I analyse whether there are exter-
nalities to non-incentivised output dimensions. I find that the bonus
pay, which is based on the qualitative performance, does also affect the
non-incentivised quantity measure by 10 percent. This suggests that
there are externalities from the performance pay also on other, non-
incentivised performance dimensions.
JEL-codes: J33, C93, M52
Keywords: Fixed pay, variable pay, piece rates, natural experiment,
incentives, productivity
Contact: Jan SauermannResearch Centre for Education and the Labour Market (ROA)Maastricht University, School of Business and EconomicsP.O. Box 616, NL – 6200 MD MaastrichtPhone: +31–43–38 [email protected]://sites.google.com/site/jansauermann
1 Introduction
Firms use variable pay aiming to link workers’ wages to their performance to elicit optimal
effort levels. Across different industries and occupational groups in which employers can
monitor workers’ performance, research has shown that the introduction of performance-
related pay can have substantial positive effects on performance (Lazear 2000). Per-
formance pay is usually focused on one performance outcome. If tasks, however, have
multiple dimensions such as quality and quantity of output, incentive schemes can also
affect non-incentivised dimensions of output.
In this paper, I analyse the introduction of performance pay in the call centre of
a multinational mobile telecommunications company located in the Netherlands. The
data contain information on qualitative and quantitative measures of performance before
and after the introduction of the performance-related pay. The performance pay was
only based on the measure of performance quality. In accordance with the related litera-
ture, I find that workers’ performance on the incentivised measure (quality) substantially
increases with the introduction of performance pay. At the same time, however, also
the quantitative performance outcome is found to increase with the introduction. These
results are stable to tests for seasonality and time trends and other robustness tests.
This paper contributes to the literature on how performance pay, as opposed to fixed
hourly wages, affects workers’ performance. Previous research exploiting personnel data
of firms has shown that performance-related pay can have substantial effects on individual
performance. Lazear (2000) showed that the output of windshield installers increases by
44 percent after the introduction of piece-rate pay. Similarly, Shearer (2004) and Shi
1
(2010) found that workers perform about 20 percent better under piece-rate pay in tree-
planting and tree-thinning, respectively. Heywood et al. (2011) found that piece-rate leads
to an increase of 50 percent in peer-reviewed publishing among professors of a university
in China.1
I contribute to this literature by using unique data on call agents with information
on performance measures for the same workers before and after the introduction of piece
rates which allows me to evaluate the effect of a switch to piece rate pay. In recent
years, there have been several studies using quantitative performance information from
personnel records across different sectors (Ichniowski and Shaw 2011). Most of these
studies use quantitative measures of output relative to a given time frame.2 Compared to
these quantitative performance measures, it is more difficult for firms to monitor quality
of workers’ output. In the call centre analysed in this study, however, the management
introduced a monitoring system for quality. Given the availability of an objective quality
performance measure, the firm incentivised this measure to improve overall quality of
calls. Unique to the data used in this study is that it contain precise measurement of
both dimensions of productivity, quality and quantity of calls. In contrast to most other
studies who evaluate the introduction of performance pay, this allows me to estimate
the effect of performance pay on the quality of workers’ output. Furthermore, I evaluate
whether there are externalities on the non-incentivised quantity measures of performance.
1Besides the cited studies analysing the effect of piece rate pay, there is also research on pay based onrelative performance incentives (Bandiera et al. 2005) and the effect of team incentives on productivity(Hamilton et al. 2003; Bandiera et al. 2010; Muralidharan and Sundararaman 2011).
2See for instance Lazear (2000) for windshield installers (windshields per day); Bandiera et al. (2005)for fruit pickers (kilogram per hour); Mas and Moretti (2009) for supermarket cashiers (number of itemsscanned); and Liu and Batt (2007), Breuer et al. (2010), De Grip and Sauermann (2011) for call centres(average handling time).
2
In the following section, I describe the firm whose performance pay is evaluated and
how performance of workers is measured. Furthermore, the section discusses how the
firm set wages before and after the introduction of performance pay.The main estimation
results are shown in Section 3. In Section 4, I show that the results found are robust to
alternative hypotheses (e.g. placebo treatments). Section 5 summarizes and concludes.
2 Context of this study
2.1 The firm and performance measures
I analyse the introduction of a quality-related incentive scheme on workers’ performance
using individual performance information of agents of a call centre. The call centre is part
of a multinational mobile operator and is located in the Netherlands.3 The call centre
is an inhouse centre that deals with inbound calls of current and prospective customers.
In order to focus on a homogenous customer group, I use data of the largest department
only, which deals with customer requests of private customers. Though the department
consists of customer segments for different groups of customers, there is only one task for
all agents: handling inbound customer calls. Apart from talking to the customers, this
task includes making notes in the customer database. Agents are not involved in any
other task such as written customer correspondence. All agents in this department are
assigned to team leaders whose main task is supervising the agents and monitoring their
calls. Team leaders are reporting to managers who are heading the department.
3See De Grip and Sauermann (2011) and De Grip et al. (2011) for studies on the same call centre.
3
Using call centre data is suited to analyse the effects of incentive pay on performance
because different dimensions of performance measures are automatically gathered without
the (potentially subjective) influence of agents or supervisors and are available for a large
number of time periods. Because the tasks of workers are comparable in terms of content
as well as the work environment, these performance measures can be used to compare
performance between agents.
As in most occupations, workers’ performance has both a qualitative and quantitative
dimension. While the quality dimension is important because of customer satisfaction and
enduring customer loyalty, the quantitative dimension is important because it has a direct
effect on the costs (wages) to be made for handling all calls. In general, it is more difficult
to capture the quality a worker brings into the task than the time in which he is able to
finish the task. While several studies use team manager evaluations to measure workers’
performance, this information is potentially biased because of its subjectivity whereas the
reasons for this bias may be unobservable to the researcher (Flabbi and Ichino 2001).4 The
qualitative performance measure on which the bonus is based on is taken from a customer
satisfaction survey. This customer satisfaction index is gathered within one hour after
the call in an automated customer survey. For this automated survey, a random number
of costumers are called back. The index is the answer to a question on whether the
customer would recommend the mobile operator among family and friends which can be
answered on a scale from zero (“very unlikely”) to 10 (“very likely”).5 The bonus-relevant
4To the best of my knowledge, there are only three studies using information on both quality andquantity of workers’ output. Asch (1990) uses information on the number but also on the education ofrecruited soldiers. Kato and Shu (2008) use data on total output as well as information on the defect rateof textile workers in a Chinese weaving company. Shi (2010) uses information on performance quality aswell as performance quantity of workers thinning fruit trees.
5The exact question is “How likely is it on basis of this contact that you recommend [the firm] amongyour family and your friends?”. Besides the customer satisfaction measure that is used for calculating
4
customer satisfaction index is calculated as the percentage point difference between the
share of customers rating the agent as 9 or 10 (high customer satisfaction) and the share
of customer rating the agent as 0 through 6 (low customer satisfaction). It is defined as
ycit = (Nit,9−10 −Nit,0−6)/Nit,0−10, where N is the number of evaluations and the subscript
denotes the grade given by the customer on agent i in week t. For interpretation purposes,
the customer satisfaction index used throughout this study is scaled between zero.6
Both the qualitative and the quantitative measures have the advantage not to be
manipulable by agents or managers. The customer satisfaction survey is mostly gathered
within one hour after the customer called the call centre. Before interacting with an agent,
customers are asked whether they are potentially willing to participate in a customer
satisfaction survey. Furthermore, the agent does neither know if the customer agreed to
participate in the survey or not. Neither agents nor managers have the possibility to affect
the quantitative performance measure yit because these are gathered automatically.
Although the bonus pay is related only to the quality measure of customer satis-
faction, there may also be an indirect effect on the quantity dimension of agents’ perfor-
mance. On the one hand, quantitative performance measures could be affected by the
performance pay scheme in a negative way. This is reasonable for all tasks where there is
a trade-off between quality and quantity. Although there is no evidence that call agents
provide higher quality at the cost of longer calls (De Grip and Sauermann 2011), one may
argue that agents now have the incentive to make longer calls in order to solve customers’
the bonus pay, the survey contains further information on whether the customer had already approachedthe call centre with the same problem previously, whether the problem which was the reason for the callcould be solved, and how much effort the agent put into the call to solve the problem.
6The lowest possible value is set slightly larger than zero to allow for logarithmic transformation ofthe variable.
5
problems, as solving customers’ problems is likely to affect customer satisfaction and thus
bonuses positively. On the other hand, agents may be inclined to make shorter calls if
customers actually prefer efficient calls. Furthermore, most customers have to pay for
their calls.
To test this hypothesis, I use a second measure of performance that reflects the
quantitative performance dimension of productivity and thus gives information on the
rate in which workers execute their task. This measure is based on the average length of
calls to measure performance. Average handling time ahtit provides a clear and objective
measure of quantitative performance that is available for each agent i and all calendar
weeks t. It measures the average time an agent spends on talking to customers and logging
the information on the call in the customer database. As with the quality measure of
performance, this measure has the advantage that it is automatically generated and not
affected by potentially subjective performance evaluations. The management associates
shorter average handling time with higher performance, because short calls are less costly
to the firm. I therefore define the measure of (quantitative) performance as yit = 100ahtit
.
Shorter calls with a lower average handling time ahtit are thus interpreted as higher
performance yit.
2.2 The introduction of performance pay
Until March 2011, all call agents were paid a fixed hourly wage that increases with tenure.
The only explicit incentive for agents under this payment scheme was an annual wage
increase depending on the performance in the previous year. In the second quarter of
6
each year, an agent’s team leader rates the agent’s performance in the previous year on
a scale from 1 to 5. According to this rating, agents get a salary increase of up to 8
percent.7
Starting in April 2011, the management introduced performance-based pay. In the
mobile telecommunication market, service quality is an important sales argument, besides
cost arguments and network provision. To improve their service quality and thus customer
satisfaction or loyalty, the management decided to introduce performance bonuses. Under
the new payment scheme, agents receive, on top of their gross wage, a bonus in between
zero and 12 percent that is subject to workers’ qualitative performance. While the fixed
pay component remains unchanged and is paid monthly, the bonus payment is calculated
and paid quarterly and is based on a customer satisfaction index. More specifically, there
are j = 1, . . . , 5 bonus levels Bj which correspond to a bonus of 0, 4.8, 8, 10, or 12
percent of the wage earned in this quarter. Prior to each quarter of the year, the general
management sets four thresholds and announces them to all team leaders and agents.
These thresholds are absolute levels of the qualitative performance measure (customer
satisfaction) and valid throughout the quarter. The bonus Bj is paid when the agent
outperforms than yj but not yj+1 on average over the whole quarter. If an agent’s average
performance y does not exceed the lowest threshold y1 (y ≤ y1), he receives no bonus
(B0 = 0). Agents that outperform the highest threshold (yJ−1 ≤ y), receive the highest
bonus, BJ . After the quarter, the management revises the thresholds and announces the
7In the data used in this study, there is no information on the team leaders’ performance ratings. Datafrom previous years, however, show that up to 60 percent of agents received an ‘on-target’ evaluationwhich lead to the overall wage increase negotiated in collective bargaining. Most of the remaining agentsreceived a rating of 2 or 4. Very few agents received a 1 or 5.
7
new thresholds for the next quarter. The bonus is paid with the monthly wage in the
second month after the end of the quarter.
In accordance with the bonus payments, the performance thresholds that the bonus
are based are not equally distributed. The distance between the lowest threshold (thresh-
old 1) and the second lowest threshold on the customer satisfaction index (threshold 2)
is .05 units of customer satisfaction which is defined on a scale from 0 to 1. The distance
between threshold 2 and threshold 3 as well as between thresholds 3 and 4 is only .025.
The identification strategy to estimate the effect of performance pay on performance
assumes that there are no other changes that affect the performance measures and occur
at the same time as the change from fixed to variable pay or that the timing of the
introduction is endogenously chosen. At the time of the introduction of performance pay,
there was no organisational change, no introduction of a new product, nor other events
that may have affected the quality or quantity dimension of agents’ performance. Agents
were first informed about the fact that bonuses will be used in the future in January 2011
without a specific information about the date of the introduction. In the second half of
March 2011, agents were informed that there will be a bonus on top of their wage paid
from April 2011. Figure 1 shows that the qualitative performance measure was roughly
stable over time before the introduction of performance pay.
8
3 Results
3.1 Descriptive evidence
The data used in this study provides detailed information on different dimensions of
performance of the same workers before and after the introduction of the performance
pay. This allows estimating the effect of incentive pay on performance as well as whether
workers substitute quality and quantity. In my case, I can analyse how incentivised
(quality) and non-incentivised (quantity) are affected by the introduction of the new
payment scheme.
The call centre is faced by a continuous inflow and outflow of agents, as well as
internal mobility to other departments. For this reason, I only consider agents that were
employed for at least one week in either the first or the second quarter of 2011 in between
which the new payment scheme was introduced and that were eligible to participate in
the bonus scheme.8 Besides the month of the introduction (April 2011), this period also
includes the month of the first announcement of the new scheme (January 2011).
The overall number of agents in the estimation sample is 328 with an overall number
of observations of 2985. The agents are observed on a weekly basis from week 27/2010
(start of quarter 3/2010) until week 26/2011 (end of quarter 2/2011). The sample thus
consists of weekly data over three quarters before the introduction and one quarter after
8The department can be differentiated in three subgroups. The first group consists of agents thatparticipate in the performance-based pay scheme (‘Core group’; N = 328). The second group, which areeither agents with tenure less than six months or temporary help agency workers, is not eligible for theperformance pay (‘Starters group’; N = 208). The reason that this group is not included is that theseagents have very steep learning curves which may affect their performance (De Grip, Sauermann, andSieben 2011). The third group are workers that worked in the quarter before the introduction of theperformance pay but not under performance pay (‘Leavers’; N = 87). These agents are also excludedfrom the estimation sample. Table 1 gives an overview over the descriptive statistics for all three groups.
9
pay. In the estimation sample, 37 percent are men; agents have an average tenure of 5.4
years (Column (1), Table 1).
Table 2 shows descriptive statistics of the estimation sample before and after the in-
troduction of performance pay. Agents included in this sample worked in both the quarter
before and the quarter after the introduction of performance-related pay in April 2011.
The table shows that the gender and tenure composition of the agents do not significantly
differ between the period before and the period after the introduction of performance pay.
After the introduction, however, agents worked on average 1.5 hours less. As first, descrip-
tive, evidence on the effect of the introduction of performance pay the table shows that
the customer satisfaction index ycit is significantly higher after the introduction, compared
to the period before the introduction. Unconditional on other covariates, the customer
satisfaction increases by 7.2 percent. Though the mean of the quantitative performance
measure yit is slightly higher after the introduction of performance pay, the difference is
not significantly different from zero.
Figure 1 shows the development of the two performance measures over time. Both
lines show substantial variation over time that does not seem to follow seasonal patterns.
In line with the descriptive evidence shown in Table 2, the figure shows that the customer
satisfaction index increases substantially with the introduction of piece rate pay. Quanti-
tative performance seems to be increase slightly as well, but to a much lower extent than
customer satisfaction.
Furthermore, Panel (a) of Figure 2 shows the distribution of the customer satis-
faction index ycit when comparing the last quarter before and the first quarter after the
10
introduction of performance-based pay. Panel (b) is the equivalent for performance yit.
Though the distribution before and after the introduction of performance based pay is
similar, the distribution seems to be slightly shifted to the right with the introduction of
performance pay.
3.2 Regression results
The results in the previous subsection have shown descriptive evidence that the introduc-
tion of performance pay leads to an increase in customer satisfaction but no effect on the
quantitative performance measure. In the next step, I regress the performance measures
on a performance-pay dummy and observable characteristics of the agents. This allows
to additionally control for covariates that may have changed with the introduction of
performance pay and thus increases the efficiency of the estimates. The regression model
takes the following form:
log(ycit) =αi + τpit + β1tt + β2Xit + uit (1)
where αi are individual fixed effects to account for individual heterogeneity, pit is a dummy
variable capturing the effect of the introduction of piece-rate payments which is defined
as one in all weeks after the introduction of performance based-pay; the variable tt is a
linear time trend that controls for trends in aggregate performance affecting all agents.
Xit are covariates that are assumed to be independent from the treatment status pit, such
11
as working hours in week t and agents’ tenure, and uit is an idiosyncratic error term.
Throughout all regressions, standard errors are clustered at the agent level.9
Using information on performance on the individual level before and after the intro-
duction of piece rate pay, Table 3 shows the results when estimating Equation (1) with
log-qualitative performance as an outcome variable. Column (1) shows that when esti-
mating Equation (1) without covariates and individual fixed-effects, the introduction of
variable pay leads to an increase of 12.2 percent in the customer satisfaction index. When
including a linear time trend, this effect decreases to 10.1 percent, but is still significantly
different from zero (Column (2)). This decrease is most probably because the time trend
is partially picking up the treatment effect of the introduction of performance pay. Con-
trolling for individual fixed effects (Column (3)) and additionally controls for an agent’s
tenure and the number of working hours (Column (4)), the preferred specification, shows
an effect of the introduction of performance pay on the qualitative performance measure
of 15.0 percent. This result shows that workers do react to the incentives set by the
management by generating higher satisfaction among customers compared to the period
before the introduction of performance based pay.10
Though the bonus is based on the qualitative performance outcome of the customer
satisfaction index only, one may expect an effect on the non-incentivised performance
outcomes as well. While one may argue on the one hand that calls of higher quality
should take more time, it could also be that customers are eager to have short and efficient
9The regressions using ycit as the measure of outcome is furthermore weighted by the number ofevaluated calls in week t. I introduce this weighting because the number of evaluated calls varies; agent-weeks with lower number of evaluated calls are more likely to be responsive to each single evaluation.
10The number of observations is smaller in regressions where I use the customer satisfaction as themeasure of outcome. This is because this measure is based on the aggregate of customer satisfactionevaluations of agent i in week t.
12
calls if they have to pay for their call to customer services. In order to test whether the
introduction had an externality effect on the quantitative performance measure, I estimate
Equation (1) with the logarithm of yit as the dependent variable. Table 4 shows that
independent of the specification, the introduction of performance pay has a significant
effect on the quantitative performance measure of agents. Column (4) of Table 4 shows
that agents make 10.1 percent faster calls under performance pay, as opposed to fixed
pay.
These results strongly suggest that the introduction of performance pay does not only
affect the intended performance measure (quality), but also has positive externalities on
other, non-incentivised performance measures. There are two hypotheses that can explain
this behaviour. First, in the ask, answering customers’ phone calls, there is no substitutive
relationship between the qualitative and the quantitative performance measure but rather
a complimentary relationship. Second, agents may be inclined by customers to make
shorter calls because customers partly have to pay for their calls. Furthermore, customers
may simply value short calls as opposed to long calls.11
11An alternative explanation for the effects found is that not the incentive itself, but the informationabout one own’s performance may actually lead to an increase in performance, e.g. due to agents com-paring their own performance with their peers. Given, however, that agents could easily monitor theirown performance also before the introduction of performance pay, I argue that this is not likely to drivethe effects found.
13
4 Robustness analyses and additional tests
4.1 Robustness of the treatment effect
In this setting, variable pay was introduced for all workers at the same time. Compared
to settings where the researcher decides over the timing of the treatment or observes
randomised treatment and control groups at the same time (see Bandiera et al. 2007;
Shi 2010; De Grip and Sauermann 2011), the bonus pay was introduced for all agents at
the same time. The effects are thus identified by observing the same workers over time,
before and after the introduction of variable pay. In this case, the estimated treatment
effect is overestimated if there are seasonal or other effects that lead to an increase in
performance.
To provide evidence against this hypothesis, I use data for the same type of call
agents of the previous year. This sample comprises data from the week 5/2010 to week
26/2010. To test for seasonal effects that occur annually , a placebo treatment dummy
that is introduced after April 1, 2010, i.e. one year before the actual introduction of
performance-based pay. Table 5 shows the results of estimating Equation (1) using this
sample with the placebo treatment dummy.12 The results show no significant difference
in qualitative as well as quantitative performance outcomes before and after the placebo
introduction of variable pay. This result suggests that there are no recurring seasonal
effects that may explain the treatment effect of performance-based pay.
12Individual tenure is not included in this and the following regressions because of insufficient variationacross time.
14
Furthermore, one may be concerned about the effect of general time trends on worker
productivity. Throughout the analysis, I control for changes in aggregate performance by
including a linear time trend in the regressions. I provide additional evidence against the
hypothesis that time trends may explain the estimated treatment effect, by narrowing
down the estimation period. If the results show to be stable also across shorter periods,
it is less likely that the treatment effect is due to time trends instead of the introduction
of variable pay. Table 6 shows the estimation results when restricting the sample to four
weeks before and four weeks after the introduction of performance pay. Both estimated
treatment effects become smaller, but remain significantly positive. For this shorter time
frame, the introduction of performance pay affects customer satisfaction by 10.8 percent.
Also the effect on the quantitative performance measure yit decreases, to 3.1 percent,
compared to the results shown in Table 4. This suggests that in the main regressions,
the treatment effect partly reflects time trends in overall performance. Nonetheless, these
estimates serve as a lower bound of the effect of variable pay on performance.
4.2 Entitlement to bonus pay
Though the bonus pay scheme was intended for all call agents in the call centre with
sufficient experience (see Section 3.1), there is one restriction for agents that work less
hours than planned for this quarter. Agents are only entitled for the full bonus if they
worked 9 weeks or more in the quarter. If agents work less, they are only entitled to
receive a share the bonus they could achieve, depending on the number of weeks worked.
15
To test whether agents provide less effort if the potential returns are lower, I estimate
Equation (1) separately for agents that worked 8 weeks or less and for agents that worked
9 weeks or more. Columns (1) and (3) of Table 7 shows that when agents are only
partially entitled to receive bonus pay, they do not perform significantly better after the
introduction of performance pay. This holds for both the qualitative and the quantitative
performance measure. Agents that are entitled to receive the full bonus, however, do
perform better. Though the number of observations for partial bonus pay are rather low,
this result suggests that agents do provide less effort because the incentive is lower.
5 Conclusion
This study analyses the effect of the introduction of piece rate pay on workers performance
using unique data of agents working in a call centre in the telecommunications industry.
The data contain information on qualitative as well as quantitative performance informa-
tion on performance before as well as after the introduction of piece rates. The bonus pay,
however, was based only on the qualitative performance measure, customer satisfaction,
while the second performance indicator which is based on the average handling time of
agents was not incentivised. I find that agents increase their qualitative performance by
15 percent. At the same time, the rate in which agents handle their calls increases by
10 percent. These results serve as upper bounds of the treatment effects because the
treatment effect reduces when using a narrower time frame to rule out aggregate trends
in performance. I furthermore show that agents response to incentives is lower when the
potential bonus payment is reduced. These results suggest that not only incentivised per-
16
formance outcomes, but also other dimensions of productivity that are not incentivised
are affected by the introduction of performance pay.
17
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A Figures
Figure 1: Qualitative and quantitative performance measures over time
.1.2
.3.4
.5A
vera
ge p
erfo
rman
ce
.3.3
5.4
.45
.5A
vera
ge c
usto
mer
sat
isfa
ctio
n
2010w26 2010w40 2011w1 2011w13 2011w26week
Note: This figure shows the qualitative performance measure (customer satisfaction) ycit (left axis; black line) and averagequantitative performance (right axis; grey line). The sample is restricted to the estimation sample (N = 328).
Figure 2: Distribution of qualitative performance ycit (a) and quantitative performancemeasures yit (b) by payment scheme
(a) ycit
01
23
Ker
nel d
ensi
ty
0 .2 .4 .6 .8 1Customer satisfaction
(b) yit
01
23
4K
erne
l den
sity
0 .5 1 1.5 2Performance
Note: This figure shows distribution of ycit (Panel (a)) and yit (Panel (b)) in the last quarter under fixed pay (solid line)and the first quarter under variable pay (dashed line).
21
B Tables
Table 1: Descriptive statistics of call agents
(1) (2) (3)Agents: Core group Starters group LeaversGender .3662 .4541 .4643(share of male agents) (.4825) (.4991) (.5017)Tenure 5.4418 .2849 1.6221(in years) (4.5153) (.5588) (3.1116)Average working hours 11.0570 11.8828 14.5023
(11.0558) (10.6725) (10.6476)Qualitative performance measure (ycit) .3981 .3834 .2935
(.1517) (.1387) (.1690)Quantitative performance measure (yit) .4254 .2835 .3706
(.2072) (.1394) (.2137)Number of agents 328 208 87
Standard deviation in parentheses. Descriptive statistics are calculated in their first working week in 2011.
Table 2: Unconditional differences in descriptive statistics before and after the introduc-tion of variable pay
(1) (2) (3)Agents: Fixed pay Variable pay Difference (2)-(1)Gender .3616 .3662 .0045(share of male agents) (.0270) (.0268) (.0380)Tenure 5.4633 5.8191 .3558(in years) (.2596) (.2596) (.3672)Average working hours 11.4871 9.9593 -1.5278**
(.5344) (.4907) (.7249)Qualitative performance measure (ycit) .3987 .4241 .0253**
(.0080) (.0069) (.0106)Quantitative performance measure (yit) .4685 .4820 .0134
(.0117) (.0131) (.0175)Number of agents 321 328
Difference significant at * p < 0.10, ** p < 0.05, *** p < 0.01. Standard errors in parentheses. Descriptive statistics areaveraged for each period. The sample consists of agents of the core group only (N=310).
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Table 3: The effect of variable compensation on qualitative performance
(1) (2) (3) (4)Piece rate dummy .1219*** .1009** .1520*** .1503***
(.0294) (.0487) (.0533) (.0567)Time trend .0008 -.0001 -.0011
(.0018) (.0017) (.0021)Tenure .0558
(.0503)Working hours -.0001
(.0037)Constant -1.0693*** -1.1038*** -1.0790*** -1.2361***
(.0305) (.0812) (.0786) (.1680)Individual fixed effects No No Yes YesObservations 2985 2985 2985 2974Number of agents 176 176 176 173R2 .0044 .0044 .1329 .1329
* p < 0.10, ** p < 0.05, *** p < 0.01. Standard errors in parentheses. Dependent variable: log(ycit). All regressions areweighted by the number of evaluated calls in week t for agent i. All standard errors are clustered at the agent level.
Table 4: The effect of variable compensation on quantitative performance
(1) (2) (3) (4)Piece rate dummy .0698*** .1116*** .1082*** .1010***
(.0138) (.0135) (.0106) (.0109)Time trend -.0017** -.0029*** -.0026***
(.0007) (.0005) (.0007)Tenure -.0223
(.0280)Working hours -.0112***
(.0008)Constant -.8989*** -.8257*** -.7664*** -.5175***
(.0204) (.0328) (.0229) (.1308)Individual fixed effects No No Yes YesObservations 11688 11688 11688 11268Number of agents 322 322 322 306R2 .0055 .0071 .7329 .7545
* p < 0.10, ** p < 0.05, *** p < 0.01. Standard errors in parentheses. Dependent variable: log(yit). All standard errorsare clustered at the agent level.
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Table 5: The effect of variable compensation under a placebo piece rates in 2010
Outcome log(ycit) log(yit)(1) (2)
Piece rate dummy (previous year) -.1217 .0144(.2456) (.0122)
Time trend .0249 .0013(.0170) (.0011)
Working hours -.0037 -.0054***(.0196) (.0014)
Constant -1.3282** -.8022***(.5339) (.0195)
Individual fixed effects Yes YesObservations 535 4663Number of agents 98 280R2 .2050 .8086
* p < 0.10, ** p < 0.05, *** p < 0.01. Standard errors in parentheses. Dependent variable: log-qualitative performance(log(ycit); Column (1)); log-quantitative performance (log(ycit); Column (2)). Individual tenure is not included because ofinsufficient variation across the sample. The sample considers all call agents working in the same department as used inthe main analysis between week 5/2010 and week 26/2010. The placebo piece rate dummy is defined as 1 after April 1,2010. All standard errors are clustered at the agent level. The regression shown in Column (1) is weighted by the numberof evaluated calls in week t for agent i.
Table 6: The effect of variable compensation in a restricted time window
Outcome log(ycit) log(yit)(1) (2)
Piece rate dummy .1082* .0310**(.0639) (.0136)
Time trend -.0106 -.0099***(.0158) (.0033)
Working hours .0050 -.0025**(.0048) (.0010)
Constant -.4420 -.2159(.9973) (.1979)
Individual fixed effects Yes YesObservations 633 2004Number of agents 130 277R2 .7429 .8996
* p < 0.10, ** p < 0.05, *** p < 0.01. Standard errors in parentheses. Dependent variable: log-qualitative performance(log(ycit); Column (1)); log-quantitative performance (log(ycit); Column (2)). Individual tenure is not included because ofinsufficient variation across the sample. The sample considers information from the four weeks before the introduction ofperformance pay until four weeks after the introduction. The regression shown in Column (1) is weighted by the numberof evaluated calls in week t for agent i.
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Table 7: The effect of variable compensation on customer satisfaction and performanceand bonus entitlement
Outcome log(ycit) log(yit)(1) (2) (3) (4)
Piece rate dummy .0957 .1559*** .0173 .1033***(.1412) (.0586) (.0573) (.0108)
Time trend .0036 -.0003 -.0028* -.0030***(.0045) (.0018) (.0015) (.0005)
Working hours -.0137 .0003 -.0143*** -.0112***(.0149) (.0038) (.0022) (.0008)
Constant -1.0450** -1.0760*** -.6319*** -.6046***(.4145) (.1053) (.0797) (.0241)
Individual fixed effects Yes Yes Yes YesEntitled bonus share Partial Full Partial FullObservations 162 2823 1091 10597Number of agents 22 154 52 270R2 .1187 .1330 .7290 .7589
* p < 0.10, ** p < 0.05, *** p < 0.01. Standard errors in parentheses. Dependent variable: qualitative performance(log(ycit); Columns (1) and (2)); log-quantitative performance (log(yit); Columns (3) and (4)). Tenure is not included inthe regressions because of low variation in Column (1). All standard errors are clustered at the agent level. The regressionshown in Column (1) is weighted by the number of evaluated calls in week t for agent i.
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