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 83801j.sauermann@maastrichtuniversity.nlhttp://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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