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Transcript of Compensation EBSCO
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How Changes in Compensation Plans Affect ' ''•
Employee Performance, Recruitment, and Retention:An Empirical Study of a Car Dealership*
JOANNA L. Y. HO, University of Ca lifornia. In>ine ' • •
LING-CHU LEE, National Pingtung Institute of Commerce
ANNE WU, National Chengchi University
1. Introduction
Economic theory argues that performance-based compensation contracts increase
employees' incentives to exert effort, resulting in improved performance (Baker.
Jensen, and Murphy 1988; Milgrom and Roberts 1992; Prendergast 1999). Previous
empirical and laboratory studies on this topic have covered various compensation
schemes and examined how changes to a more performanc e-sensitive incentive
scheme influence employees' compensation and performance (Waller and Chow1985; Lazear 2000; Banker, Lee, Potter, and Srinivasan 2001). However, compan-
ies may also switch from more to less performance-sensitive incentive schemes.
For example, prior to 1992, Sears adopted a commission-based compensation sys-
tem for auto repair salespersons. This compensation scheme enticed salespersons
to falsely diagnose brake and alignment problems, which cost Sears $15 million in
refunds and other settlement costs. Consequently, Seais discontinued tlie conmiis-
sion system (DriscoU 1994).
Furthermore, during the 1990s, most shoe manufacturers adopted u survivalstrategy by shifting from a piece-rate to an hourly-rate compensation system (Free-
man and Kleiner 1998). In 2001 Fujitsu also changed its compensation system
from performance-based to nonperformance-based (Tanikawa 2001 ) because under
the perform anee-based system , workers tended to set goals as low as possible in
order to receive raises and promotions. Surprisingly, no research has addressed the
impact of changes to less performance-sensitive plans on employee performance.
Our study provides evidence on how a change to a less performance-sensitive
incentive scheme affects individual employee productivity and compensation.' in
* Accepted by Alan Webb. We gratefully ackno wledge the thoughtful and helpful cumnicnts ut twu
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168 Contem porary Accoun ting Research
addition, we examine whether employee ability affects productivity in light of the
plan change and which employee group is affected the most by such a change.
In addition to influencing employees, the compensation plan can affect com-
pany performance by influencing recruitment and retention (Stiglitz 1975; Salop
and Salop 1976; Dem ski and Feltham 1978; M ilgrom and Roberts 1992). For
example, performance-based compensation contracts can attract and retain high
performers and differentiate high from low performers (e.g.. Baron and Kreps
1999; Banker et al. 2001 ). A company benefits when lower-performing emp loyees
leave, but can suffer a setback when higher-performing employees depart. Thus, it
is important to consider who will join or leave a company when the performance
sensitivity of the compensation contract is changed. This study examines the types
of employees who are attracted to the firm, or who leave, when the compensationplan becomes less performance sensitive. In addition, we investigate causes (e.g.,
compensation loss) that may account for employee turnover.
Our study focuses on a car dealership in Taiwan that changed its compensation
scheme from totally com mission-based to a mix of fixed salary and lower comm is-
sion rates. This change was in response to the requirement of the 1998 Taiwanese
Labor Law amendment. Our database includes 4,392 individual-level observations
(e.g., em ploye es' com pensation, sales quantities, performance ratings, and dem o-
graphic information) as well as firm-level data (e.g., turnover rates, new hires, reve-nues, income) for a 56-month period. We find that the change in com pensation plan
lowered individual productivity and compensation, especially for higher-performing
employees. As predicted by theory, we also observe that the less performance-
sensitive plan attracted low performers and retained fewer high-ability performers.
Interestingly, we do not find that the decrease in individual productivity translates
into poor overall company performance. Our interviews with managers and addi-
tional analyses suggest that in light of the decreased individual sales productivity, the
company hired more employees and also changed its sales mix by giving employees
more incentives to sell cars that had higher margins and faced more competition.
Th is study adds to the extant hterature by being the first to examine the impact
of a change to a less performance-sensitive compensation scheme on low-level
employee productivity. We directly measure the impact of a plan change (i.e., from
more to less performance-sensitive) on individual productivity and the adverse
selection effects by using data both prior to and after the plan change. Prior empir-
ical work in this area tends to be experimental in nature and tests for only one of
the two effects (Young and Lewis 1995). However, in this study we are able to
examine both incentive and adverse selection effects simultaneously. Furthermore,Banker et al. (2001) examine how implementing a more performance-sensitive
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Employee Performance, Recruitment, and Retention 169
In our study, the availability of employee-level data before and after the plan
allows more robust conclusions about effects on employee recruiting and turnover.
Furthermore, this study goes beyond related prior studies by investigating how
employee ability affects performance when a company changes to a less performance-
sensitive cotnpensation plan. We measure employee ability by using a factor analysis
of three proxies for ability: employee annual performance rating, nutnber of cars
sold, and tbe reciprocal of time to the first promotion since the etnployee joined the
dealership. Our employee ability measure not only helps us identify specific per-
fortnance groups that are most affected by tbe compensation plan change, but also
provides additional insights into causes of employee turnover after tbe plan
cbange. Tbese findings also have practical implications because they tnay help top
management anticipate tbe effects of a cbange to a less performance-sensitivecompensation plan on incentives and efforts of different etnployee groups as well
as the effects of a change on employee recruitment and turnover.
Tbe remainder of tbis paper is organized as follows. Section 2 describes the
field site and tbe nature of the changes made in the etnployee comp ensation plan.
We develop our hypotheses in section 3. Data and empirical models are discussed
in section 4. Section 5 presents the empirical results, and section 6 summarizes our
results w itb concluding rem arks.
2. Field site
The field site we studied is the largest car dealership in Taiwan, where tbe domestic
autotnobile market has been nearly 400,000 car sales per year.^ In 2001, tbe car
dealership had 1,248 sales representatives and 87 sales outlets located throughout
Taiwan and mainland China.
The details concerning tbe field site reported in this section are based on both
interviews and archival data from the company. Our relationship witb tbe field site
allowed u.s to interview tbe chief executive officer (CEO), senior and branch manag-ers, and salespersons to get information about the compensation scheme, employee
reactions, tbe legal environment, competition, and various management-related
issues. Tn total, we spent roughly 220 hours in site visits, data collection, and con-
ducting more than 20 in-depth interviews, ranging from 50 minutes to two hours.
Eor eacb interview, we sent questions to tbe interviewees at least one week before
the meeting.
The car dealership carries various m odels of sedans and trucks and has a hetero-
geneous g roup of customers. For sedans, annual salary is a major factor in determin-
ing which model (economy versus luxury) a customer buys. However, customers
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170 Contemp orary Accounting Research
alternatives based on those needs. The time spent by an employee to close a deal
ranges from one week to one month, depending on experience, ability, and the type
of car being sold. In general, junior employees spend twice the amount of timeclosing a deal than senior employees, and it takes more time to sell sedans than
trucks. Furthermore, an employee handles each sale entirely by himself or herself
and does not share sales skills or customer information because he or she does not
want to risk having customers "stolen" by colleagues.
In early 1998, the Taiwanese Labor Law amendment required that, by the end
of 1998, companies pay a minimum wage (around U.S.$466 per month) for all
forms of employee-employer relationships.-^ At that time, the CEO of the field site
learned that some competitors would superficially comply with the law's require-
ment by providing a base salary while maintaining the same commission rates.However, they would potentially impose a penalty by taking away the base salary
from employees not meeting the minimum sales requirement. Family competitors
(i.e., those selling the same brand of cars) and two nonfamily competitors (i.e.,
those selling different car brands but competing for the same customer groups) did
not change their compensation contracts after the implementation of the new regu-
lation."^ The CEOs of these companies were concerned about the possible negative
impacts of a switch to a less performance-sensitive scheme on individual produc-
tivity as well as a potential loss of good employees.^ The Taiwanese governmenthas not strictly enforced all of the new regulations, and the penalty associated with
a failure to comply with the regulations is not severe. As such, most companies
would rather risk paying the noncompliance penalty than suffer a short-term loss
due to the change of compensation plan.
However, the situation is different for our field site because it is the largest
dealership in Taiwan, which makes it the most likely target for government investi-
gation to see whether the industry is complying with the law. After considering all
factors (e.g., potential government investigation and penalty, high political costs,etc.), the CEO decided not to follow competitors' actions, but instead chose to
comply with the law's requirement by adding a base salary and reducing commis-
sion rates for all levels of employees. The reason for lowering commission rates
was to keep total compensation expenses at the pre-plan change level.^ In May
1998, the field site announced the new plan, which became effective on July 1,
1998. This plan was implemented throughout the company rather than on a
regional or phased-in basis. As such, we found a unique setting to study employee
recruitment and turnover because the field site and some of its competitors useddifferent compensation plans in response to the government regulation. Further-
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Em ployee Perform ance, Recruitment, and Retention 171
cars every three months instead of three cars each month. This average was insti-
tuted because in Taiwan, the car industry normally performs best in January when
individuals receive their annual bonus and celebrate the Chinese new year holiday.
Conversely, the industry's worst month is August, perhaps because some Taiwanese
believe it is unlucky to conduct any major activities, including making personal
decisions such as getting married, during this period. So, for example, if an
employee sells zero, zero, and nine cars in November, December, and January,
respectively, he or she will not be terminated in February or Marcb because he or
sbe sold nine cars in January. If an employee does not attain the minimum
requirement after three months, he or she receives an initial warning and will be
terminated if bis or her performance does not improve in the following two
months.We chose this field site for three reasons: (a) tbe change in its compensation
scheme from totally commission-based to a less performance-sensitive plan (base
salary plus lower commission rates) was not voluntary, but in response to the 1998
law's requirements;^ (b) it is the largest dealership in tbe Taiwanese automobile
market, with nearly 18 percent of tbe market share over the past five years: and
(c) tbe company agreed to provide us with an extensive arcbival database containing
4.392 sales representatives and 87 branches over a 56-month period. Top manage-
ment also allowed us to review most documents and to interview managers andsales force personnel.
3 . Hypotheses development
The premise of agency theory is that a principal designs a contract to align an
agen t's actions w itb the principa l's best interests (e.g., Holmstrom 1979; Feltham
and Xie 1994; Prendergast 1999; Lambert 2001). Classic agency models bave
focused primarily on the design of performance-based contracts to motivate
employee effort (i.e.. incentive effect) (e.g.. Baker et al. 1988; Baiman 1990; Mil-grom and Roberts 1992). Also, prior studies bave suggested selection effects,
where performance-based compensation contracts can attract and retain bigh per-
formers (e.g., Milgrom and Roberts 1992; Baron and Kreps 1999; Lazear 2000;
Banker et al. 2001). Below, we discuss both tbe incentive and adverse selection
effects and the related bypotbeses to be tested.
Incentive effect
Agency theory identifies the circumstances under wbicb fixed (base salary) and
variable (comm issions and other forms such as bonuses or options) components can
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172 Contemporary Accoun ting Research
y ' = a + b'x, where a is base salary, b' is the new commission rate, and b' < b.
The graphical presentations of the old and new compensation contracts, C and C .
are summarized in Figure 1.
Since the company implemented the Improvement of Low Performance Plan,
an employee must sell al least nine cars every three months (or an average of three
cars each month) to remain on the job. The fixed pay under the new plan is technic-
ally not a guaranteed salary. In essence, the new plan can be thought of as consisting
of two components: "a" is paid when employees sell a minimum of an average of
three cars per month, and "Z?" is paid per unit after the employees achieve the min-
imum requirement and are paid for all the units sold. As pointed out by Demski
and Feltham 1978. the requirement of achieving a minimum number of car sales
imposes some risk on the employees as an inducement to expend some agreedlevel of effort.
Empirical studies have supported the effects of performance-based incentives
on employee behavior (e.g.. Banker. Lee, and Potter 1996; Bailey, Brown, and Coceo
1998; Lazear 2000). Banker et al. (1996) report that implementitig a performance-
based compensation plan increases sales and that the effect persists and grows over
time. Bailey et a l. (1998) find that improvem ent rates in ind ividuals' initial and over-
all performances of an assembly task are higher when an incentive plan is in place.
Similarly, Lazear (2(X)0) examines the impact of piece rates on the performance ofworkers who install auto windshields. He finds that worker output increased after
the company switched its compensation scheme from hourly wages to a piece rate
plan. Conversely, these findings suggest that if a company switches from contract
C (performance-sensitive plan) to contract C (less performance-sensitive plan ), a
lower h' may induce less effort from employees to work hard, resulting in.ï' < jc.
In light of the arguments and empirical findings that performance-based incen-
tives affect employee behavior, our first hypothesis is as follows:
Figure 1 Compensation and sales productivity under the commission-based and base
salary plus lower commission plans
Compensation (y ) Commission-based plan ( Q
Base salary pluscommission plan ( C )
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Em ployee Performance, Recruitment, and Retention 173
HYPOTHESIS 1. Employees ' average sales productivity (cars sold) will decrease
after the company changes its compensation plan to a less performance-
sensitive scheme.
Figure 1 shows the relationship between compensation and cars sold underboth the C and C compensation schemes. Clearly, when sales productivi tyincreases, the differences in compensation {y — y') under the two schemesincrease, which suggests that switching from compensation plan C to C will causehigher-performing employees to lose more compensation (due to lower commis-sion rates) than lower-performing employees. In light of this greater compensationloss, higher-performing employees will reallocate their efforts, expend less elfort,
and enjoy more leisure time than lower-performing employees, which will result incomparatively lower sales productivity, leading to the following hypothesis:
HYPOTHESIS 2 . The decrease in sales productivity (cars sold) of higher-performing
employees after a company chan ges to a less performance-sensitive com-
pensation scheme will be greater than that of lower-performing employees.
Adverse selection effects
Com panies design compensation schemes not only to induce more employee effortbut also to attract and retain high-potential employees (Baker et al. 1988). Adverseselection effects include recruiting and tumover effects. The former relates to tbetype of employees who join the company and the latter to the type of employeeswho leave. For example, contracts with higher piece rates attract high-abilityemployees (Lazear 2000), and adding a performance-based bonus attracts higher-ability employees (Banker et al. 2 001). Prendergast (1999) argues that compensationcontracts are an important means for a company to recruit higher-ability workers.
Employing a perfonTiance-sen.sitÍve contract will benefit high-ability workers morethan low-ability workers, resulting in an increase in the percentage of high-abilityemployees who are attracted to the com pany.
Conversely, when a company changes compensation schemes from C to C , itis likely that the guarantee of a base salary will attract lower-ability employees.Therefore, the recruiting effect suggests that the sales productivity of employeeshired after the change to contract C will be lower than that of employees hiredbefore the plan change. These aiguments lead to the following hypo thesis;
HYPOTHESIS 3. T he average sales productivity (cars sold) of employees hired
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174 Contemporary Accoun ting Research
that poorer performers tended to leave when pay was ba.sed on performance and to
stay wben it was not. The implication of their findings is that performance-based
compensation plans can lead to functional turnover. Lazear (2000) reports that
about one-third of improved performance can be attributed to selection effects (i.e.,
less productive workers leave the company and are replaced by more productive
workers). In Banker et al. 20 01 , results sbow that a performance-based scheme in a
retail firm attracts and retains more productive employees, while the performance
of the less productive sales staff declines before they leave.
When the company changes from a linear system to a less performance-based
system scheme with a kink — that is, a nonlinear segment in the pay-for-performance
function — it is likely to create turnover am ong employees (Jensen 2003).** Feed-
back on compensation could help employees learn how they are affected by a less
performance-sensitive compensation plan. Higher-performing employees who
continually compare tbeir compensation with past levels and outside opportunities
are likely to be dissatisfied with tbeir compensation. As discussed earlier, some of
tbe field site's competitors did not lower tbeir commission rates. It is likely that
som e unsatisfied higb-perform ing em ployees cbose to join tbese com petitors to
increase their compensation. Tb is is consistent witb Jensen 's 2003 argument tbat if
the commission rate does not sufficiently reward employees for tbeir extra effort,
the company will likely lose high performers to competing firms. Therefore, weexpect the sales productivity of employees wbo were hired under contract C and
left under contract C to be higher than that of employees wbo left before the plan
change. Regarding employees wbo were hired and left under contract C. their
departure may be attributed to either disappointment witb tbe compensation or
being forced out by the Improvement of Low Performance Plan. Because these two
groups' sales productivity may offset each other, we expect no difference in sales
productivity be tween those who were hired and left under contract C and tbose
who left under contract C. Taken together, we expect sales productivity of etnployees
who left after the change in compensation scheme from C to C to be higher than
that of employees who left before the change. We propose the foiiowing hypothesis
concerning turnover effects: i
HYPOTHESIS 4. The average sales productivity (cars sold) of employees who
leave under the ¡ess performance-sensitive compen sation scheme will be
higher than that of employees who leave u nder the performance-sensitive
compensation scheme.
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Em ployee Performance, Recruitment, and Retention 175
diverse distribution (i.e., the true variance is greater than the mean), we develop a
negative binominal (NB) regression model to examine the impact of the com pensa-
tion plan change on employee productivity.
The sampling period covers 97.541 person-months and 5,121 branch-monthsof data from January 1996 to April 2001 (56 months).^ We partition the sample
into two subsamples: (a) before the change to the new plan (a total of 28 months —
from January 1996 to A pril 1998),'** and (b) after the change to the new p ian
(a total of 28 months — from January 1999 to April 2001 ). The models' parameters
are estimated using pooled time-series data over a 56-month period and cross-
sectional data for the 4,392 individuals and 87 branches. Below is the NB regression
model:
-h \^^B_EMPLOY¡, + ^ÎM^,+ s¡, (1),m = I
where / = {1, ... , 4,392}. a subscript to denote employee i, í = { 1 . . . . , 56 }. a sub-
script to denote the time period in which the employee works, and ei¡ is a randomerror term. We measure employee sales productivity iIND_PROD) as the number
of cars sold per person-month. PLAN is equal to 1 if the employee was on the new
plan during the given month. Hypothesis 1 (hypothesized incentive effect on sales
productivity) is tested by examining whether the coefficient of PIAN (aj) is nega-
tive in (1). Also , to rule out the possibility that the effect on sales productivity was
due to employees' being hired at different times, we include EXPER (number of
months em ployed) as a control variable.
In the model, we also include two types of competition control variables (com -
petition type and competition intensity) to capture the general economic condi-tions. There are two types of competitors in our field site: family competitors
{FAM_COMP) and nonfamily competitors {NON_FAM_COMP). Regarding com-
petition intensity, we use CITYJSALE (i.e., total monthly sales of competitors in
the same city) as a proxy. The log forms of monthly car sales for FAM^COMP,NON_FAM_COMP, and CITY_SALE are used. We expect positive coefficients for
both FAM_COMP and NON_FAM_COMP because good economic conditions
help employees sell cars more easily, thereby increasing their productivity. How-
ever, we cannot predict the sign of CITY_SALE because it not only captures thecompetition intensity among car dealers in a specific city, but also reflects the pur-
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176 Contemporary Accoun ting Researcb
four control variables (FAM^COM P, NON_FAM _COM P, CITY^SALE, M„j) are atthe market level. Finally, to control for tbe impact of hiring additional salespeopleon productivity, we include a brancb-level control variable, ^B_EMPLOY (i.e., tbe
log form of number of employees in eacb month). We expect a negative sign for#B_EMPLOY because a bigher number of employees implies more intense compe-tition among tbe employees, resulting in lower individual productivity. A list ofvariable definitions is included in tbe Appendix.
Because ( 1 ) explores how the compensation plan change affects all employees,we do not include employees' ability. To examine whether the bigher-abilityemployees are more likely to be affected by the plan change, we include em ployees'ability (ABILITY) in (2).
= OQ + a^PLANi, + ßyEXPERi, +Yj, X PLAN , + Á^FAM^COMP,
11
+ ^ Í M ^ , + Si, (2).m = 1
We take three steps to measure employee ability. First, we collect differentmeasures that can capture employee ability: the annual performance rating, tbenumber of cars sold prior to tbe month of interest, and tbe reciprocal of time totbe first promotion since they joined the dealership. Gibbs (1995) argues that tbeemployee performance rating is a logical proxy for expected ability and thatexpected ability declines monotonically with tbe number of promotions employeesreceive over time. In tbe dealership, each employee is evaluated by the branchmanager annually on a four-point scale, with "4" being the best performance. Tbe
average number of cars sold reflects changes in an employee's productivity fromthe first month in whicb the em ployee joined the dealership to the preceding monthof interest. Similar to Gibbs 1995, we also use tbe reciprocal of time to the firstpromotion since tbe employees joined the dealership, as the tbird measure.Because of the high turnover rate, we do not use tbe number of promotionsemployees received over time. Second, to preserve a degree of freedom, we usefactor analysis to collapse our three measures into one variable ABILITY, whichdoes not vary between tbe pre- and post-new-plan periods." Finally, we use therank order oí ABILITY to classify employees into the following three groups:HIGH^ABIUTY (in the first quartile), MEDIUM_ABILITY (in tbe second and tbird
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Em ploy ee Perform ance, Recru i tment , and Retent ion 177
OldPlanQuitBefore {D^Q^ = 1 , 0 o the rwise ) : employees who jo ined the dea le r ship
before the change to the new plan and left before July 1, 1998.
OldPlanQuitAfter (D^Q^ = 1 , 0 o th e rw i s e ) : e m p lo y e e s w h o jo in e d th e d e a le r s h ip
before the change to the new plan and left after July 1, 1998 but before the end of
our sample per iod .
NewPlan {D^^^ = 1 . 0 o the rwise ) : employees w ho jo ined the dea le r sh ip af te r the
change to the new plan .
NewPlanQuitAfter {D^Q^ = 1,0 otherwise): employees who joined the dealership
after the change to the new plan and left after July I, 1998. but before the end ofour sample period.
To avoid potentially large variation in individual monthly data, we use the
moving average of sales productivity to capture trend and direction. Figure 2 dis-
plays the three-month moving average of sales productivity for different employee
types from January 1996 to April 2001. As seen in panel A of Figure 2. the average
sales productivity of the old plan is better than that of the new plan, suggesting that
the less performance-sensitive plan attracts more low performers. Furthermore,
panel B of Figure 2 shows that the average sales productivity of OldPlanQuitAfter
is higher than that of OldPlanQuitBefore, implying that more high performers left
the firm after the plan change.
To test hypothesized adverse selection effects, we specify the following NB
regressions (3) and (4):
IND_PROD¡, = «0
11
^ ^M^, + e,, (3),
m = 1
IND_PRODi, = 00 + ßiEXPERj, + r2D^Q'^ + r^D^QA -\- \yFAM_COMP,
It
^iM^^+Bi, (4).
m = 1
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178 Con tem pora ry Accoun t ing Resea rch
Figure 2 Sales productivity by timing of employee employm ent and tumover
Panel A: Employees by different time of employment
• SaoS
u
•S
6 -
5 -
4 -
9 _
M
OldPlan
NewPlan
~T 1 r 1 1 1 1 r 1 1 1 1 1 1 r-
-30-26-22-18-14-10 -6 -2 3 7 11 15 t9 23 27 31
Month before (-30 t o - 1 )/a fte r PLANPanel B: Em ployees by different time of tumover
7 - 1
6 -
5
2 -
1 -
- OldPlanQuitBefore
- OldPlanQuitAfter
" NewPlanQuitAfler
|Vv'\
n [ I I I I 1 1 1 1 1 \ \ 1 1 r
-30-26-22-18-14-10 -6-2 3 7 II 15 19 23 27 31
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Em ployee Performance, Recruitment, and Retention 179
no difference in sales productivity between NewPlanQuitAfter and OldPlanQuit-
Before. Thus, we expect that the coefficient of r^ will be greater than zero and r2
will be equal to zero. In botb (3) and (4), we do not include ABILITY, PLAN, or
tbeir interaction variable, because in these models we test only for the differencesbetween the groups (i.e.. new plan versus old plan. D^Q^ versus D^Q^, and D^^^
versus D^Q^). Because employees may have different times of employment and
departure, we also include EXPER as a control variable.
5. Results
Descriptive statistics
Table 1 summarizes the descriptive statistics of tbe key variables. Means (standard
deviations) for tbe entire period and the two subperiods are presented in panel A ofTable 1. The average num ber of cars sold per month per employee {IND_PROD) is
3.30, wbicb is slightly higher than 3. the minimum requirement under the Improve-ment of Low Performance Plan. The turnover rate per month (MTHJTURNOVER)
is 2.31 percent (or 27.45 percent per year), which is the lowest rate in the car sales
industry.'2 This high turnover rate suggests that we are able to examine adverse
selection effects. Further analysis shows that the turnover rate for employees with-
out dismissal threat is only 0.34 percent, which is similar to other industries. On
the other band, the turnover rate for employees with dismissal threat is 1.97 per-cent. Furthermore, the turnover rate increases slightly for both employee subgroups
after tbe plan change; however, the difference is statistically insignificant. Also, the
average age of employees hired under the new plan (32.88) is older than tbat under
tbe old plan (31.46).
As seen in panel A of Table 1, the average of IND_PROD under tbe new plan
(3.15) is significantly (p < 0.0001) lower tban that under the old plan (3.49), sug-
gesting tbat the change to a less performance-sensitive compensation plan decreased
individual sales productivity. Under the new plan, the fixed pay is $466 and tbeaverage commission rate is $225 (s.d. = $250). which is significantly lower than
tbat under tbe old plan (mean = $495; s.d. = $287;p < O.OOOl).'^ This shows tbat
the plan change causes a significant decline in the average monthly compensation
from $1,612 to $1,255 ($357; p < 0.0001), which can bave a significant impact on
employees' living standards.''* Furthermore, these results suggest tbat the Improve-
ment of Low Performance Plan was effective. Eor example, as seen in panel A of
Table 1, the standard deviation of IND_PROD significantly decreased (from 4.09
to 3.45; p < 0.0001) after the change in compensation plans. Also, additional data
sbow that, in general, the average sales productivity of NewPlanQ ititAfter is belowtbree cars over the 34-month period. Eurtbermore, tbe monthly employee turnover
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180 Con temporary Accoun ting Research
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Em ployee Performance, R ecruitment, and R etention 181
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182 Contem porary Accoun ting Research
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Employee Performance, Recruitment, and Retention 183
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184 Contemporary Accounting Research
7.50 to 7.39) and also for nonfamily competitors (NON_FAM_COMP; from 10.01
to 9.96). Panel B of Table 1 presents tbe distribution of individual sales productiv-
ity for both the old-plan and new-plan periods. These are the actual numbers of
cars sold by the employees, including those wbo sell more than 10 cars. As shown
in panel B of Table 1. the change to a less performance-sensitive plan caused a
decrease in sales productivity. Eor example, there are more employee-montbs with
no cars sold under the new plan (24.8 percent) than under the old plan (20.1 per-
cent). However, there is a slightly higher percentage of employee-months where
three cars were sold under tbe new plan than under the old plan ( 15.7 percent versus
13.7 percent). This suggests that lower-ability employees exerted greater effort to
meet tbe minimum sales burdle to avoid job loss. Regarding the high performers,
after the plan change there was a decrease (from 20.6 percent to 17.3 percent) inthe percentage of employee-months wbere six or more cars were sold and also a
slight decrease in the employee-months where 10 or more cars were sold (from 4.5
percent to 3.4 percent). It is possible tbat lower commission rates discouraged top
employees from exerting effort.
To examine tbe impact of the plan cbange on different groups, we present
means (standard deviations) of cars sold and compensation by ability group in
panel C of Table 1. These results sbow that the new plan has a negative impact on
sales productivity for the HIGH_ABILTTY group (from 6.2 to 5.9; p = 0.051). anda positive impact on the MEDIUM_ABILnYemployees (from 3.3 to 3.4;;; < 0.00! ).
MEDIUM_ABILITY emp\oyeea may have worked harder to compensate for tbeir
loss in income due to lower commission rates. Although the average sales produc-
tivity for the LOW_ABILITY group is still less tban tbe minimum requirement of
three cars after the plan change, ii increases from 1.3 to 1.7 (/? < O.OOOI), None-
theless, all three groups have significant decreases In compensation ($518 for
HIGH_ABILITY; $303 for MEDIUM _ABIUTY; $92 for LOW_ABILITY).
Tests of incentive effects (Hypothesis i and Hypothesis 2)
Hy pothesis 1 predicts tbat em plo yee s' average sales productivity w ill decrease
after the plan cbange. Panels A and B of Table 2 show NB regression results with
individual sales productivity (¡ND_PROD) as the dependent variable. As discussed
above, we expect a negative coefficient of PLAN ( a ,) . Panel A of Table 2 (column 1)
shows that aj is negative and significant (-0.153;/) < O.OOOI).'-'^
Recall that the dealership also introduced an Improvement of Low Perfor-
mance Plan. Therefore, the overall impact of contract C on sales productivity maynot necessarily be negative because the Improvement of Low Performance Plan
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Employee Performance, Recruitment, and Retention 185
but it is not significantly less than zero (p = 0.0923). This suggests that the threat
of dismissal under the Improvement of Low Performance Plan does not improve
the productivity of employees with poor performance. One explanation is that indi-
vidual productivity is jointly determined by effort and skills (Demski and Feltham
1978; Gibbs 1995), and incentives do not aiways work when the tasks require skills
TABLE 2
Negative binomial regression results of hypotheses testing
(dependent variable: ¡ND^PROD')
Panel A: Test of incentive effects {Hypothesis 1 ) — The plan change decreases average
sales productivityModel 1
n
Intercept
PLANEXPER
EAMJCOMP
NON_FAM_COMP
CITY_SALE
m_EMPLOY
Goodness-of-fit (LR statistic)
p-value
Full sample
(1)
76.850
-5 .290f
-0.153+0.062t
0.023t
0.524+
0.046+
- 0 . 0 0 5
47,135
0.0001
Subsamplewithout
dismissal threat
(2)
40,082
-5.149+
- 0 . 1 3 2 t0.017+
0.02+
0.568+
0.057+
- 0 .0 3 3 *
21,961
0.0001
Subsample withdismissal threat
(3)
36,768
-4.615+
- 0 . 0 2 70.008*
0.032+
0.446+
-0.035+
0.061*
10,177
0.0001
Panel B : Test of incentive effects (Hypothesis 1) — Short-term versus long-term effects of
the plan change
Model I
Sample
n
Intercept
PLAN
EXPER
Adjustment period(from - 2 to 16 months)
62.988
- 7 . 3951 +-0.0794+
0.0701+0.025 It
Status quo period
(from 17 to 34 months)
60,915
-5.2658+
-0.1514+
0.0614+
0.0242+
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186 Contemporary Accounting Research
TABLE 2 (Continued)
Panel C: Test of incentive effects Hypothesis 2 (model 2 for the effects of the plan change
on employee groups with different levels of ability)Model 2
n
InterceptPLAN
ABILITY
ABIUTY*PLAN
EXPER
FAM_COMP
NON_FAMjCOMP
CITY^SALE
m_EMPLOY
Goodness-of-fit (LR statistic)/?-value
73,239
- 5 . 7 4 9 t0.225t
1.987t
- 0 . 4 2 7 t
- 0 . 0 1 3 t
O.O35t
0.495t
0.05 It
- 0 . 0 2 8 Í
26,0000.0001
Panel D: Tests of Hypothesis 3 (model 3 for recruiting effect) and Hypothesis 4 {model 4
for turnover effects)Model 3 Model 4
Sample
n
Intercept[)NEW
QNQA
OOQA
EXPER
EAMJOOMP
NON_FAM_COMP
CITY_SALE
#B_EMPLOY
Goodness-of-fit
Fullsample
(1 )
76,850- 6 . 0 8 6 t- 0 . 2 2 6 t
0.053t0.018t0.6 i Ot0.046t
-o .o i o
T\imover
samp le
(2)
3 7 , 6 7 0- I 2 . 3 6 0 t
0 .013
0.484t
0.045t
- O . O I 8 t
1.225^
0.0135
- 0 . 0 3 0 5
Turnoversamp lewi thout
re t i rementpossibi l i ty
(3 )
3 7 , 5 6 8- 1 2 . 2 9 9 t
0 .014
0.484t
0.046t
- 0 . 0 1 8 t
1.2I9Í
0.0138-0 .033§
Turnoversamplewithout
dismissalthreat
(4 )
9.534-1 0 . 0 7 8 t
0.0640.231 +
-O.O34t
-0 .00111.108t
0.014- 0 . 1 1 4 t
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Em ployee Performance, Recruitmen t, and Retention 187
TABLE 2 (Continued)
Notes:
* Variables are as defined in the Appendix.
t Statistically significant at or less than the 0.0001 level (two-tailed).
t Statistically significant at the 0.01 level (two-tailed).
§ Statistically significant at the 0.05 level (two-tailed).
or experience (Ashton 1990; M erchant, Van der Stede, and Zheng 200 3). Skills are
normally developed over time and cannot be changed in the short run. As such,
while the new plan may encourage employees with a threat of dismissal to exertmore effort, the increased effort may not always translate into an increase in sales
productivity if the required skills are not possessed. Furthermore, one branch man-
ager made a comment that the new compensation contract is more risky for junior
employees than for senior employees. This is especially the case for employees
who recently joined the car sales industry. Therefore, the minimum requirement for
car sales may impose more risk for poorly performing employees but it did not
improve productivity. Collectively, our results suggest that the new plan had a nega-
tive effect on employees and therefore the results support Hypothesis 1.Some studies in the organizational behavior literature indicate initial reactions
to changes in compensation plans that tend to stabilize over time (Lazear 2000).
Therefore, we also analyze the short-term (or adjustment period) versus long-term
(status quo period) effects of the change in compensation plan on individual
productivity. Specifically, we separate the sample period into two stages: initial
adjustment period ( - 2 through 16 m onths) and status quo period (17 to 34
months). As shown in panel B of Table 2, in both subperiods we observe significant
negative coefficients of PLAN (-0.0794 in the ini t ial adjustment period and
-0.1514in the status quo period).'^ These results suggest that the negative effects
of the plan change are stronger in the status quo period, which is consistent with
Banker et al. 1996, who report that the compensation plan change effect grew over
time.
Hypothesis 2 predicts that the magnitude of the negative impact of the com-
pensation plan change on sales productivity is greater for higher-performing
employees than it is for lower-performing employees. Therefore, we expect the
coefficient of ABILITY X PLAN, ßj, to be negative. As d iscussed earlier, ABILITY
is derived through a factor analysis and is a continuous variable. Panel C of Table 2shows that the coefficient oí ABILITY X PLAN has a significant (p < 0.0001 ) neg-
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188 Contem porary Accounting Research
than that of employees hired under the old plan.'8 in (3), we include onlyavoid potential multicollinearity problems. The average sales productivityis «o , and the average sales productivity of D^^^ is «Q -I- y ,. Th us, H ypothesis 3 is
tested by examining the following inequality: (a ^ + Ti) - «o = Ti < 0. As seen incolumn 1 of Table 2, panel D, yi is -0.226, which is significantly less than zero (atthe 0.0001 level), which suggests that sales productivity was higher for employ-ees hired under the old plan than for those hired under the new plan, thereby sup-porting Hypothesis 3.
To test turnover effects (Hypothesis 4) , we first compare the differences in thesales productivity of those who left before the change in compensation plans (Old-
PlanQuitBefore, D^QB ) with those of employees who were hired under the old plan
and left after the change {OldPlanQuitAfter, D^Q^). We expect that the coefficientof average sales productivity oíD<^Q^ («Q) will be less than that of 0^0-4 (^Q -I - ^3).In other words, jy will be greater than zero. As shown in column 2 of Table 2,panel D, 73 is 0.484 (significantly greater than 0 at the 0.0001 level).'^ Recall thatthe higher 73, the higher the chance that the dealership will lose higher-performingemployees by implementing the new plan. We then compare the sales productivityof DOQB with that of NewPlanQuitAfter (D^Q^ ) (i.e., those who were hired underthe new plan). Recall that we expect the coefficient of average sales productivities
of D^Ö^ (öQ + 72) will not be different from that of D^Öß (OQ) (i.e., 73 wü ' not bedifferent from zero). As shown in column 2 of panel D, 73 (0.013) is not signifi-cantly greater than zero.
Employee tumover may not be caused by disappointment with the compensa-tion plan change, but instead by retirement or threat of dismissal. While dismissalis related to poor performance, retirement is not. Furthermore, after working for 25years employees can decide when they want to retire, but dismissed employees areforced to leave immediately after they receive the dismissal notice. Thus, to rule
out the possibility that our tumover results may be confounded by employee retire-ment and threat of dismissal, we conduct two additional analyses to measure thesepotential effects on tumover. O ur interviews with m anagers indicate that employ-ees can receive all retirement benefits if they serve tbe company for 25 years. Tbeycan receive partial retirement benefits if they serve the company at least 10 years.Because the company was established in 1975, fewer than five employees were eli-gible to receive full retirement benefits in 2001. Therefore, we use employee tenureof more than 10 years as a proxy for possible retirement to further separate tbesample. As seen in column 3 of panel D , the results for the tumover sam ple w ithout
retirement possibility are similar to those of the entire tumover sample. Specifically,73 is positive and significant (0 .484;/^ < O .O O O i) and 72 (0.014) is not significantly
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Employee Performance, Recruitment, and Retention 189
Also, the new compensation plan may force lower-performing employees to leave
due to tbeir lack of ability and experience. To examine the effects of compensation
loss (COMP_LOSS) and an em ployee's experience (EXPER) and ability (ABILITY)
on employee departures, with and witbout the threat of dismissal, we ran logitregression models separately for tbese two employee groups. COMP_LOSS is the
difference between the average new com pensation minus the average old com pen-
sation, divided by the average old compensation. Therefore, we only include
employees who joined the dealership in the old plan and separate them into two
groups : employees wi tb and wi thout d i smissa l th rea t . Also , we inc lude
0B_EMPLOY, a brancb-level variable, because a higher number of employees
enhances the intensity of competition among the employees, which may increase
tbe l ikel ihood of employee turnover. As such, we expect a posi t ive sign ofm_EMPLOY.
Table 3 summarizes tbe logit regression results. Model A shows that wben
employees face a threat of dismissal, their departure decisions are not influenced by
compensation loss but their level of experience does matter (-0.392; p < 0.0001).
Conversely, as seen in model B, departure decisions by em ployees who are not facing
the threat of dismissal are affected by botb compensation loss (-2.329; p < 0.0(X)1 )
and experience (-0.252; p < 0.0001).
In sum, our additional analyses provide deeper insights into H ypothesis 4. Thehigher average sales productivity of employees who leave under tbe new plan ver-
sus the old plan is attributable more to the departure of high-ability employees
because of greater compensation loss than to the departure of employees witb less
experience and lower ability.
TABLE 3
Results of logit regression of employee turnover (dependent variable: LEFT)
Model A Model B
w ith dismissal withou t dismissal
threat threat
Intercept
COMF_LOSS*EXPER
291 (LEFT =
80 (LEFT =
1.232
- 0 . 1 5 9- 0 . 392*
1)
0)
1 4 9 ( L £ / T =
472 (LEFT =
- 1 . 0 8 2
- 2 . 3 2 9 '- 0 . 2 5 2 "
1)
0)
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190 Contem porary Accou nting Research
Additional analysis of the impact of the change in compensation plan oncompany overall performance
An optimal compensation contract needs to balance the benefits of increased firm
performance resulting from additional employee efforts and the compensation costsincurred (Abowd 1990, 55). As discussed earlier, the change to a less performance-
sensitive compensation plan hurts individual sales productivity. Nonetheless, the
decreased individual sales productivity may not result in lower overall company
performance. This change occurs because the new compensation plan may bring
cost savings, and management may take actions to mitigate the negative impact of
decreased individual sales productivity (e.g., hiring more workers). Due to the lack
of data, prior research has focused on individual effort and pay perfonnance (e.g.,
Banker et al. 2001) and also assumed a positive relationship between individualproductivity and company performance (e.g., Lazear 2000). Because we were able
to gain access to data at both individual and division levels, we also investigated
the relationship between individua! productivity and overall company performance.
To study that relationship, w e collected additional company-level performance
(PERFORM) data as follows: revenues (REVENUE), gross profits (GS_PROFIT),income before headquarter expenses allocation (INCOME), and number of cars
sold (CAR_SOLD). To control for possible infiation over the sample period, all
financial performance variables are deflated by the monthly consumer price indexin Taiwan. Also, we include two comp etition-type control variables (FAMjCOMPand NON_FAM_COMP), the number of emp loyees at the field site (i^F_EMPLOY),and sales mix of sedans versus trucks (SALES_MIX) to capture the general eco-
nomic condition. Our model is:
PERFORM, = «0 + (XiPLAN, + \^FAM^COMP, +
II
+ ÁiSALES_MIX, + X^#F_EMPLOY, + V ^A i^ , + e, (5).
HI = I
Table 4 summarizes the regression results. None of the coefficients for PLANis significantly less than zero (except for CAR_SOLD), suggesting that the change
in compensation plan does not negatively affect overall company performance. To
shed light on why the negative effects of the plan change on individual productivity
did not translate into poor company performance, we interviewed two branch man-
agers. One manager attributed the lack of negative impact on the company's overall
performance to hiring more employees and lower compensation costs. His explan-ation is consistent with our finding that on average there is a 7.81 percent increase
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Em ployee Performance, Recruitment, and Retention 191
Other possible explanations for the lack of negative impact on company per-formance include change in sales mix, more effort by etnployees leading to highercustomer satisfaction ratings, and more repeated sales. Branch managers suggested
that sales mix can be measured either by type of car (i.e.. high-margin sedans versuslow-margin trucks) or by exclusive versus nonexclusive cars. Exclusive cars arethose that can be sold only by the field site and nonexclusive cars are those that canbe sold by both the field site and family competitors. In general, compared withexclusive cars, nonexclusive cars have higher profit margins and more intense com-petition. The managers we interviewed mentioned that in response to different levelsof competition, the field site has significantly lowered the commission rates forexclusive cars but not for nonexclusive cars. However, the company only had sales
data on exclusive and nonexclusive cars from September 1997 to April 2001.Results (not tabulated) based on these limited data show that the plan change causeda significant increase in sales of nonexclusive cars (from 40.71 percent to 50.24percent; p < 0.001). This increase suggests that employees allocated more effort toselling higher-margin and m ore competitive nonexclusive cars under the new plan,which mitigates the loss resulting from selling fewer cars. Regarding the sales mixof sedans and trucks, our additional analyses (not tabulated) show that the percent-age of sedans did not change significantly (from 73.43 percent under the old planto 72.55 percent under the new plan;/? = 0.2547) during this sample period.
TABLE 4Regression results at the company level (n— 64)*
Dependent variablet
InterceptPLAN
FA M COMP
NON FAM COMP
SALES MIX
F EMPLOY
Adjtisted R~
CAR SOLD
(1 )
-30 ,084*- 4 6 5 Í Í
153,5lli
-7 . 7 0 13*
0.902
REVENUE
(2)
- 57 . 395*2.956
2.568*56,182*
-49 ,60758*
0.877
GS PROFiT
0)
-37.0485- 4 3 6
215"3,1741,481
5§
0.665
INCOME
(4J
-5 . 6 1 1-3.52
44385
- 2 , 2 7 02
0.354
Notes :
We carry out the Diirbin-Watson fDW) test for AR 1 — that is, first-order serial
correlation. Our results show that DW is close to 2, and there is no serious first-order serial correlation. Also, we find that all variance inflation factors at^ less
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192 Contemporary Accoun ting Research
6. Concluding remarks
Because of a lack of access to objective, individual-level performance data, prior
empirical studies of compensation schemes have been limited in their ability to fur-
ther our knowledge of how an incentive plan affects employees' selection of
employment and effort level (Banker et al. 2001). In this study, we have used data
at both the individual and company levels to empirically test how a company's
change to a less performance-sensitive compensation plan affected employee per-
formance, recruitment, and retention. Our empirical results support predictions based
on econom ic theory that a change to a less performance-sensitive com pensation
scheme reduces individual sales productivity but not overall company performance.
Consistent with Banker et al. 1996, we also observe that the negative impact of the
plan change on individual productivity was higher in the status quo period than inthe adjustment period. Furthermore, our findings suggest that while lower com mis-
sion rates reduce the incentive for employees to work hard after meeting the mini-
mum requirement, the hurdle rate motivates some employees to exert more effort to
avoid losing their job s. In addition, we found that lower-performing em ploye es
were attracted to the company while fewer high performers were retained.
This study also extends prior research by investigating the employee groups
most affected by the change to a less performance-sensitive plan. As predicted, we
find that higher-performing employees were affected more than lower-performingemployees. These findings suggest that managers should anticipate the impact of
alternative compensation plans on the efforts of different employee groups (e.g..
ones with different levels of ability). As such , top management may need to refine
the compensation contracts or take various actions to mitigate potential dysfunc-
tional impacts.
Furthermore, our results support the recruiting effect; that is, the average sales
productivity was higher for those hired under the old plan than for those hired
under the new pian. Our results also support the turnover effect. We find thatemployees who were hired under the old plan and quit after the plan change had
higher average sales productivity than those who left before the plan change. How-
ever, we find no significant difference in sales productivity between those who
were hired and left under the less performance-sensitive plan and those who were
hired and left before the change. Results from additional analyses show that turn-
over occurs either when employees experience higher compensation loss or have
less experience and poor performance, causing them to fail to meet the minimum
requirement of productivity. These results may help management anticipate that
employees with certain characteristics will be more likely to leave if the compensa-
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Em ployee Performance, Recruitment, and Retention 193
to sell higher-margin, more competitive nonexclusive cars. However, why the
increased sales mix of higher margin cars did not increase the company's overall
revenue is an open question. Although we find an increase in the proportion of
high-margin cars being sold, the total num ber of cars sold decreases significantlyafter the change to the new plan. As such, the increase in revenues due to a favor-
able sales mix change may have been offset by the decrease in the number of cars
sold, resulting in no change to the com pany 's overall revenue.
Although our study has advanced the understanding of tbe effects of perfomiance-
based incentive schemes, it is important to recognize some limitations. First, due to
the lack of nonfinancial measures (e.g., customer surveys) at the field site, we can-
not measure other goals for employees to achieve and therefore bave to limit our
analyses to sales productivity and compensation. Second, like prior studies onchanges of incentive schemes (e.g.. Banker et al. 1996; Lazear 20(X); Banker et al.
2001; Brickley and Zimmerman 2001), our analysis was restricted to a large data
set from one organization. Therefore, our results may have low generalizability to
otber organizations and contexts. Finally, although we have included both com petitor
performance and local competition intensity in our m odels, we do not have informa-
tion about the competitors' strategy, which may have also affected the performance
of our field site.
To shed more light on the change to a less performance-sensitive plan, futurestudies could examine optimal contracts for employees with different levels of
ability. Our results show that the change to a less performance-sensitive compensa-
tion scheme has a greater negative impact on tbe productivity of high-ability
employees and that tbe threat of dismissal does not improve the productivity of the
poorest performers. Future studies could examine tbe best incentive schemes when
companies are under different competitive circum.stances. For example, what are
the benefits and costs associated with different types of contracts (e .g., higher fixed
salary associated with a higher hurdle; same fixed salary with higher commission
rates)? Finally, worker heterogeneity (i.e., workers with different skill levels) com-monly exists, and companies may use team-based compensation plans to motivate
employees to share their knowledge (Hamilton, Nickerson, and Owan 2003). As
such, future studies could investigate bow team-based compensation plans can reap
the benefits of worker heterogeneity by motivating higher-ability workers to teach
lower-ability workers how to deal with customers more effectively, thereby
improving their performance.
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194 Contem porary Accounting Research
APPENDIX
Variable definitions
Variables Definition
ABIUTY
AGE
CARJSOLD
C¡TY_SALE
COMMISSIONJiATE
COMPENSATION
COMP_L0SS
zyVEW (NewPlan)
D^Q^ (NewPlanQuitAfter)
DOLD (OldPlan)
DOQA {OldFlanQuitAfter) =
DOQB (OldPlanQuitBefore) -
EXPER
FAM COMP
FIXED_PAY
GS_PROFIT
HIGHJiBIUTY
= employee's ability
= average age of employee
= number of cars sold per month
= log of monthly market sales of local com petitors. The
hranch and its local comp etitors are located in the same
city
= the dollar comm ission per car
= compen sation per person-month
= (the average compensation after the new plan - the
average compensation before the new pian)/the average
compensation before the new plan
= an employee w ho joined the dealership after the new plan
= anemployee who joined the dealership after the new plan
and who left the dealership after July 1, 1998 and beforethe end ofotir sample period
= an employee who had joined the dealership before the
change to the new plan (July 1. 1998)
= an employee w ho joined the dealership before the change
to the new plan and who left the dealership after July 1,
1998 and before the end of our sample period i
^ an employee who had joined the dealership before the
change to the new plan and left before July I. 1998
= number of years given employee had been employed
= log of monthly m arket sales of family com petitors that sell
the same brand of cars
= fixed salary per person-month
= gross profit per month
= a dummy set equal to 1 if em ployees' ability is in tbe first
quartile
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Em ployee Perform ance, Recru itment, and Retention 195
APPENDIX (Continued)
Variables Definition
LOW_ABIUTY
MARKET_SHARE
MEDWMJiBlLlTY
MTH_TURNOVER
NON_FAM_COMP
PERFORM
PLAN
REVENUE
SALES_MIX
m_EMPLOY
#F EMPLOY
- a dummy set equal to 1 if employ ees' ability is in the
fourth quartile
= market share in Taiwan car market
= a dumm y set equal to 1 if employees' ability is in the
second and third quartiles
^ turnover rate per month
= log of monthly market sales of nonfamily com petitors that
sell different car brands but comp ete for the same cu stomergroups
= company-level performance
= a dumm y set equal to 1 if the emp loyee is on the new plan
during given month
= revenue per month
= sales mix of sedans versus trucks
= log of monthly head count of employees in a branch, notincluding the administrative staff
= log of monthly head count of employees in the company
Endnotes1. We use the term "less performance-sensitive plan" because the comm ission under the
new plan is lower for each car sold, which is generally the case for employees whose
productivity is far greater than the required m inimum num ber of cars sold each m onthand who have a low risk of falling below the minimum threshold.
2. Quantities of sale are 361,615, 374,955 , 394,160, 357,63 4. and 350,461 from 1996 to
2000, respectively (source: Taiwanese D irectorate General of H ighwa ys).
3. For presentation purposes, throughout the paper we have converted Taiwanese do llars
to U.S . dollars with an exchange rate of 34 to 1.
4. According to the CEO , family co mpetitors m ake up the major com petition. In Taiwan,
the top five car brands (i.e., Toyota, Mitsubishi, Nissan, Ford /M azda , and Honda) have
more than 80 percent of the market share, and each car manufacturer has at least twodealerships.
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196 Con temporary Accoun ting Research
learning about new cars and recruiting new customers and also incur an opportunity
cost of lo.sing existing custom ers w ho are loyal to the car brand of the field site. The
third employment alternative is to work for noncar industries such as real estate and
life/product insurance. Although employees can use their general sales skills, they need
to invest a tremendous amount of time learning about new products and new industries.
6. At that time (before the implem entation of the new compensation plan), fewer than
three cars were sold in 45.2 percent of the em ployee-m onths (i.e., no cars were sold in
20.1 percent of the employ ee-months; one car in II .3 percent of employee-months;
and two cars in 13.8 percent of emp loyee-m onths). Because fewer than three cars were
sold in almost half of the employee-months, the total compensation costs will increase
dramatically if the company were to pay a base salary on top of the old (higher)
commission rates. Therefore, to control total compensation costs, the CEO decided tolower the commission rates.
7. The field site was forced to include fixed pay by governm ental regulation. As a result,
this plan was implemented throughout the company rather than on a regional or
phased-in basis, which can avoid po tential selection bias of employee s with specific
risk preferences choosing to work for different regions or branches. In addition , as
discussed earlier, som e of the field site's competitors did not lower their com mission
rates, which also allows us to examine how the change in compensation plan affects the
retention or turnover of em ployees with different ability levels.8. As shown in Figure 1, there is a kink at the minimum requirement in the new con tract
( C ) . Specifically, employees receive a base salary before they reach the minimum
requirement but are paid additional commission after the minimum requirement is met.
9. The company did not have a com plete data set available until January 1996. To make the
monthly data covered in the two subsam ples equal, we only include data up to April 2001 .
10. We exclude eight months (May to December) in 1998 from our sample for two
reasons. First, we want to avoid a possible man ipulation of the sales timing . There w ere
two months between the announcement date of the new plan (MayI )
and the effectivedate (July 1 ). During these two months, in light of the future decrease in commission
rates, it is likely that some employees boosted sales to earn higher compensation.
Second, we controlled for possible seasonal-month-sales effects.
11. The eigenvalues of these three factors are 1.77, 0.85, and 0.38 . Following Ka iser's
1960 rule (i,e., eigenvalue greater than un ity), we use factor 1 as the ability proxy. The
factor loadings for the number of cars sold, employee annual performance rating, and
reciprocal of time to the first promotion since he or she joined the dealership are 0.8719.
0.8416, and 0.5516. Including the number of cars sold prior to the month of interest may
confound our measu re of ability because the new plan results in lower productivity.
Therefore, we ran a robustness check excluding the number of cars sold prior to the
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Em ployee Performance, Recruitmen t, and Retention 197
— that is. b> b' + alx for x > 3 cars. Recall that b {b') is the average com mission
rate under the old (new) plan, x is the number of cars sold, and a is fixed salary. As seen
in Table 1, 6 is $495 , b' is $225, and a is $466. Therefore, an employee w ho sells three
cars receives an average compensation rate of $495 under the old plan, but reeeives alower compensation of $380 ($225 + $46 6/3 ) under the new plan. Similarly, an
employee who sells 10 cars receives an average compensation of $495 per car under
the old plan, but receives only $271.6 ($225 -\- $466/10) under the new plan. As such,
our assumption that all employees receive lower compensation rates under the new
plan is supported.
14. According to the D irectorate G eneral of Budget, Accounting and Statistics of
Executive Yuan in Taiwan, the average national income per capita in Taiwan from 1996
to 2001 is $12,292. The national income per capita from 1996 to 2001 is $12,418,$12,707, $11,522, $12,324, $13,090, and SI 1,692, respectively. The decline in the
average annual incom e per capita at our field site during this period is 35 percent
($357*12/$12,292).
15. Because of repeated observations on the same set of cross-section units (Johnston and
Dinardo 1997, 388), Hypothesis 1 can also be tested by examining w hether a , is
negative in panel data with the employee fixed effects model. We observe qualitatively
similar results by using panel data with tixed effects.
16. We cannot directly compare the coeffieients for PLAN betvi-een the adjustment and the
status quo periods because they are estimated in two different regressions. Therefore,
we include the two proxies (PLAN_Adjustment and PLAN_ StatusQuo) in one
regression and then use an F-test to compare the two coefficients. Our results show that
the coefficient on the status quo period (-0.1237,;? < 0.0001) significantly (p =
0.0036) differs from that on the initial adjustment period (-0.0736./) < 0.0001).
17. To test the robustness of (2), we also use dummy variables for ability (i.e., classifying
employees into HIGHjKBlUTY, MEDIUM_ABILITY, or LOW_ARIUTY group).
Compared with the LOW_ABlLny group, the plan change had a significantly higher
negative impact on the MEDlUM_ABILnY group (the coefficient of
MEDWM_ABIUTY X PLAN is - 0 . 5 4 3 ; / ; < 0.0001) and on the HIGH_ABILITY
group (the coefficieni of HIGH_ABILITY X PL\N is -0.736;/) < 0.0001).
18. The fixed-effects model using panel data is not feasible for testing adverse selection
effects because there was a high em ployee turnover rate, with som e employe es leaving
the dealership and new entrants joining the tirm at the same time.
19. We also include the coefficient of variation of sales to control for a possible effect of
unstable sales over time on employee turnover. We find similar results tbat y^ is 0.486
(significantly greater than Oat the 0.0001 level) and 72 is 0.012 (not significant atconventional levels).
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198 Con temporary Accoun ting Research
Bailey C , L. Brown, atid A. Coceo. 1998. The effects of monetary incentives on worker
learning and performance in an assembly task. Journal of M anagement Accounting
Research 10: 119-31 .
Baiman, S. 1990. Agency theory in managerial accounting: A second look. Accounting,
Organizations and Society 15 (4): 3 4 1 - 7 1 .
Baker, G. P., M . C. Jensen, and K. J. M urphy. 1988. Com pensation and incentives: Practice
vs. theory. The Journal of Finance 43 (3) : 593 -616 .
Banker, R. D., S. Lee, and G . Potter. 1996. A field study of the impact of a performance-
based incentive plan. Journal of Accounting and Economics 21 (2): 195-226.
Banker, R. D., S. Lee, G. Potter, and D . Srinivasan. 2001. An empirical analysis of
continuing improvements following the implementation of a performance-based
compensation plan. Journal of Accounting and Econom ics 30 (3) : 31 5-5 0.Baron , J. N., and D. M. Kreps. 1999. Strategic human resources — Frameworks for general
managers. New York: John Wiley & Sons.
Brickley, J. A., and J. L. Zimmerman. 2001. Changing incentives in a multitask
environment: Evidence from a top-tier business school. Journal of Corporate Finance
1 (4) : 367 -96 .
Cam eron. A. C . and P. K. Trivedi. 1998. Regression analysis of count data. New York:
Cambridge University Press.
Demski, J., and G. Feltham. 1978. Economic incentives in budgetary control systems. TheAccounting Review 53 (2): 33 6-5 9.
Driscoll, P. A. 1994. Sears to link incentives for auto service sales to customer satisfaction.
Marketing News 28 (8): 8.
Feltham, G., and J. Xie. 1994. Performance measure congruity and diversity in multi-task
principal/agent relations. The Accounting Review 69 (3) : 42 9- 53 .
Freeman, R. B., and M . M. Kleiner. 1998. The last American shoe manufacturers: Changing
the method of pay to survive foreign competition. Working paper. National Bureau of
Economic Research.
Gibbs, M. 1995. Incentive compensation in a corporate hierarchy. Journal of Accounting
and Economics 19 (2-3 ) : 247 -77 .
Greene, W. H. 200 0. Econometric analysis. Upper Saddle River, NJ: Prentice Hall.
Hair, J., R. Anderson, R. Tatham, and W. Black. 1998. Multivariate data analysis, 6th ed.
Upper Saddle River, NJ: Prentice Hall.
Hamilton, B. H., J. A. Nickerson. and H. Owan. 2003. Team incentives and worker
heterogeneity: An empirical analysis of the impact of teams on productivity and
participation. Journal of Political Economy 111 (3): 46 5- 97 .
Hoilenbeck, J. R., and C R. W illiams. 1986. Tum over functionality versus tumover
frequency: A note on w ork attitudes and organizational effectiveness. Journal of
8/3/2019 Compensation EBSCO
http://slidepdf.com/reader/full/compensation-ebsco 33/34
Em ployee Performance, Recruitmen t, and Retention 199
Kaiser. H. F. 1960. The application of electronic com puters to factor analysis. Educational
and P sychological Measure 20 (1): 1 41 - 51 .
Lambert, R. A. 200 1. C ontracting theory and accounting. Joumal of Accounting and
Economics 32 (1-3 ) : 3 -8 7 .
Lazear, E. P. 2000 . Performance and productivity. American Economic Review 90 (5):
1346-61.
Long, J. S, 1997. Regression models for categorical and limited dependent variables.
Advanced quantitative techniques in the social sciences. Thousand Oaks, CA: Sage.
Maddala, G. S. 1992. Introductions to econometrics. Englewood Cliffs, NJ: Prentice Hall
Intemational.
M erchant. K. A .. W. A. Van der S tede. and L. Zheng . 2003. Disciplinary constraints on the
advancement of knowledge: The case of organizational incentive systems. Accounting.Organizations and Society 28 (2-3 ) : 251 -86 .
Milgrom, R, and J. Roberts. 1992. Economics, organization and management. Englewood
Cliffs, NJ: Prentice Hall.
Rrendergast, C. 1999. The prov ision of incentives in firms. Joumal of Economic Literature
37( 1 ): 7 - 63 .
Salop, J., and S. Salop. 1976. Self-selection and turnover in tbe labor market. Quarterly
Journal of Economics 90 (4): 619- 27 .
Stiglitz, J. 1975. Incentives, risk, and inform ation: N otes toward a theory of hierarchy. Bell
Joumal of Economics 6 (2): 552 -79 .
Tanikawa, M. 2001. Fujitsu decides to backtrack on performance-based pay. New York
Times, late ed., East coast, Marcb 22, W.I.
Waller, W. S., and C. W. Chow. 1985. The self-selection and effort effects of standard-based
employment contracts: A framework and some empirical evidence. The Accounting
Review 60 (3): 45 8- 76 .
W illiams. C. R., and L. P. Livingstone. 1994. Another look at the relationship between
[jerformance and voluntary turnover. Academy of Management Journal 37 (2): 26 9-9 8.
Young, S. M .. and B . Lew is. 1995. Experim ental incentive-con tracting research in
management accounting. In Judgment and Decision-Making Research in Accounting
and Auditing, eds. R. H. Ashton and A. H, Ashton, 5 5 - 7 5 . New York: Cambridge
University P ress.
8/3/2019 Compensation EBSCO
http://slidepdf.com/reader/full/compensation-ebsco 34/34