! 1

Examining the Role of Management in Turnover: A Contingency Approach

Sangyub Ryu Public Management and Policy Analysis Program

Graduate School of International Relations The International University of Japan

777 Kokusai-cho, Minami Uonuma-shi Niigata, 949-7277, Japan

Email: sangyubr@iuj.ac.jp

Young-Joo Lee* School of Economic, Political and Policy Sciences

The University of Texas at Dallas 800 West Campbell Rd. GR 31

Richardson, Texas 75083 Telephone: (972) 883-6477 Email: ylee@utdallas.edu

* All correspondence to Young-joo Lee at ylee@utdallas.edu

Acknowledgement: Authors thank the three anonymous reviewers and Dr. Kaifeng Yang for

their helpful comments.

! 2

Examining the Role of Management in Turnover: a Contingency Approach ABSTRACT

Literature suggests that there is an inverted U-shaped relationship between employee turnover

and organizational performance, and that management should attempt to find and maintain a

turnover-retention equilibrium in order to increase organizational performance. Despite the

observations supporting this argument, little research has investigated how management actually

uses management practices to control turnover in various situations. This study examines how

innovative management within a school district affects teacher turnover by using data from the

2006-07 Superintendent Management Survey and the Academic Excellence Indicator System of

Texas school districts. This study tests the innovation-turnover relationship, contingent on

organizational performance. The results suggest that innovative management increases turnover

in low-performing organizations, while it decreases turnover (increases retention) in high-

performing organizations.

Key words

Innovation, Turnover, Performance, Contingency

! 3

INTRODUCTION

An organization’s current and potential human resources are an integral part of its strategic

business plan (Agarwala, 2003; Huselid, 1995). Therefore, management must find, recruit, and

retain highly productive workers in order to increase organizational performance. In

contemporary management literature, human resources are treated as an organizational asset

rather than as a cost (Barney, 1991), and turnover has become a critical issue in management.

Turnover has two contrasting management implications. On the one hand, employee turnover

incurs costs because an organization needs to spend resources on recruiting and training new

employees. On the other hand, avoiding turnover also incurs various costs, including the creation

of pleasant working conditions, high job autonomy, high wages, and good fringe benefits. Thus,

managing employee turnover involves balancing turnover costs and retention costs, and the

optimal level of turnover is decided at the point where the sum of the direct turnover costs and

the costs associated with retaining employees is minimized (Abelson & Baysinger, 1984). In

other words, turnover-related costs decrease until this optimal level of turnover is attained, and

then increase once the turnover rate exceeds this point. Consequently, a U-shaped relationship

between turnover and turnover-related costs exists. The U-shaped relationship, in turn, suggests

that employee turnover and organizational performance have an inverted U-shaped relationship

(Glebbeek & Bax, 2004). At the low to moderate turnover levels, turnover enhances

organizational performance, but performance declines as turnover increases (Ableson &

Baysinger, 1984; Meier & Hicklin, 2008).

Provided that organizations increase their performance by managing turnover, it is a

critical role of management to find and maintain the turnover-retention equilibrium. Accordingly,

recent studies have treated employee turnover as a dependent variable (e.g., Huselid, 1995; Lee

! 4

& Hong, 2011; Selden & Moynihan, 2000), emphasizing the manageability of turnover. The

question then is: how does an organization manage employee turnover? Given that the level of

performance varies across individuals, organizations may strive to increase the turnover of low-

performing employees and to reduce the turnover of high-performing employees. In other words,

management has to find a way to reach the optimal turnover rate without concrete information on

individual performance. The present study examines how public managers may use innovation as

a strategic tool to control turnover depending on the level of organizational performance.

MANAGING TEACHER TURNOVER

Current research on employees’ turnover in government emphasizes public management as an

important factor (Lee & Hong, 2011; Selden & Moynihan, 2000). For instance, Selden and

Moynihan (2000) argue that human resource management factors such as pay, family-friendly

policies, or training reduce voluntary turnover, and their empirical findings obtained from state

government agencies indicate the significant effects of pay and on-site childcare. Lee and Hong

(2011) investigated the effects of family-friendly policies on turnover rates in federal agencies

and found that childcare subsidies significantly reduce turnover. The research on turnover

intentions also reveals the importance of managerial roles (Lee & Jimenez, 2011; Lee &

Whitford, 2008). Adopting Hirschman’s (1970) theory of exit, voice, and loyalty, Lee and

Whitford (2008) found that managerial efforts to expand and build employees’ perception of

voice and loyalty decrease employees’ intentions to leave. More recently, Lee and Jimenez

(2011) investigated performance-based management practices and their impact on federal

employees’ intentions to leave, and found that managerial factors, including performance-based

rewards, objective performance measures, and performance-supporting supervision, reduce

! 5

employees’ turnover intentions. In summary, empirical research on turnover and turnover

intention supports the view that public management plays a significant role in managing

employees’ turnover.

Managing turnover is particularly critical in educational institutions, including primary

and secondary schools, because of the labor-intensiveness of the industry. For many years,

educational administrators, policy makers, and researchers, as well as the public, have expressed

concerns about the high turnover rates of teachers in America’s schools (Boyd, Hamilton, Loeb,

&Wyckoff, 2005; Guin, 2004; Ingersoll, 2001). Studies report that teacher turnover, rather than

student enrollment or teacher retirement, is the dominant factor hindering school functioning

(Guin, 2004; Ingersoll, 2001). According to Keigher and Cross (2010), of the 3,380,300 public

school teachers who taught during the 2007-08 academic year, 84.5 percent remained at the same

school, 7.6 percent moved to a different school, and 8.0 percent left the profession the following

year. In the same period, the total turnover rate of the U.S. workforce was 3.2 percent (Bureau of

Labor Statistics, 2008). Empirical research also reports a negative relationship between teacher

turnover and school functioning, including difficulties in planning and implementing a coherent

curriculum as well as in sustaining a positive working relationship among teachers (Guin, 2004).

The literature suggests that teacher turnover is especially problematic if the most able teachers

are more likely to leave and if high-turnover schools are most likely to serve low-income and

minority group students (Boyd et al., 2005; Guin, 2004; Harris & Adams, 2007).

While teacher turnover may have a negative impact on educational outcomes, recent

studies have provided somewhat different perspectives on teacher turnover in the United States.

First, recent research findings suggest that teacher turnover is not really higher than the turnover

rate in other professions. Henke and Zahn (2001) find that teachers in K-12 schools are least

! 6

likely to leave their profession during their first three years compared to college graduates

working in comparable fields. In their analysis of Current Population Survey data, Harris and

Adams (2007) also report that the average rate of teacher turnover is not significantly higher than

the average turnover rate among comparable occupations, including nurses, social workers and

accountants.

Another, perhaps fresher, view of teacher turnover comes from management literature,

claiming that turnover is not necessarily bad and that it can be both optimal and dysfunctional

(Abelson & Baysinger, 1984; Dalton, Krackhardt, & Porter, 1981; Meier & Hicklin, 2008).

Almost 30 years ago, Abelson and Baysinger (1984) developed the concept of “optimal

organizational turnover” in which every organization has an optimal turnover rate that minimizes

the sum of costs of turnover and the costs of retention. They suggest that situations exist where

increased turnover may result in positive outcomes due to a reduction in organizational costs,

implying a U-shaped relationship between turnover and turnover-related costs. An important

point in their hypothesis is that the optimal rate of turnover varies from one organization to

another – there is no general benchmark (Glebbeek & Bax, 2004). Therefore, each organization

has to find its own optimal turnover rate through trial and error.

The U-shaped relationship between turnover and turnover-related costs suggests that

organizations can also manage their performance by managing turnover. Turnover of poorly

performing employees can benefit the organization and positively influence organizational

performance, while turnover of well performing employees may result in the exact opposite

outcomes (Lee & Jimenez, 2011). Meier and Hicklin’s work (2008) indeed suggests a possible

inverted U-shaped relationship between turnover and organizational performance by finding

evidence that when organizations perform poorly, the higher turnover enhances organizational

! 7

performance up to a certain point (i.e., the optimal point of turnover rate). After a given level,

however, higher turnover decreases organizational performance (Meier & Hicklin, 2008). Their

study implies that if turnover is manageable, then organizations can improve performance by

identifying and working toward their optimal turnover rate.

The turnover-performance relationship and the possible manageability of turnover have

an important implication in an education context. Previous literature suggests that the quality of

teachers is one of the most critical determinants of students’ achievement (Ascher & Fruchter,

2001; Darling-Hammond, 2000; Eide, Goldhaber, & Brewer, 2004; Goldhader, Brewer, &

Anderson, 1999) along with such factors as the social and economic status of their parents (Bali

& Alvarez, 2004; Caldas & Bankston, 1997), environmental conditions of school districts

(Bidwell & Kasarda, 1975; Driscoll, Halcoussis, & Svorny, 2003), or the degree of parental

involvement (Houtenville & Conway, 2008; Jeynes, 2007). Therefore, apart from other relevant

variables, the school districts with more underperforming teachers are likely to perform poorly

and the districts with more able teachers are likely to perform better. The 2012 Colorado

Innovation Schools Act Report points out that teacher turnover has a positive impact on schools’

performance when teachers who are ineffective or unsupportive of the district’s goals leave their

jobs, while turnover of teachers who are effective and supportive of the district’s vision

negatively affects schools’ performance (Chin, 2012). Consequently, if turnover is manageable,

top managers of districts may want to make strategic decisions to increase low quality teachers’

turnover or to decrease high quality teachers’ turnover contingent on the level of performance.

This study employs this perspective on management by top administrators of school districts

(superintendents), and examines how superintendents use innovation to manage teacher turnover

rates in their districts.

! 8

Innovation and Turnover: The Contingency Approach

Every organization, whether it is public or private, finds itself increasingly accountable to its

respective stakeholders. As a result, today’s management is under greater pressure to change

(Mueller, 1996), and organizations try to adopt ideas or behavior new to them in order to meet

these expectations (Daft, 1978; Damanpour, 1996). Innovation generally describes “…an

organization’s emphasis on risk-taking, responsiveness to new opportunities, and being

experimental rather than careful” (Sheridan, 1992, p. 1043). Damanpour (1996) explains that an

organization uses innovation as a means of changing itself, either as a response to changes in its

environment, or as a proactive measure to influence that environment. The implementation of

innovation, including technological innovation, has long been a national, state, and local

educational goal in the United States (Becker, 2000; Glennan & Melmed, 1996). In the state of

Texas, the Texas Education Code encourages school districts to implement innovation within the

classroom and administration by providing more flexibility and by lifting restrictions to meet the

individual needs of students.1 Examples include opening enrollment options, contracting

education services, and implementing the Co-op Alternative Program (CAP), which are being

administered in several school districts in Texas.

The degree of innovation varies across different organizations. It depends on various

factors, including the volatility of the external environment, the industry, an organization’s age

and size, and the leadership’s propensity for innovation. Most of all, top management leadership

is an essential element for organizational innovation (Rivenbark & Kelly, 2003). Using

innovation, management may attempt to increase or decrease turnover, and ultimately, to

maximize organizational performance. The contingency theory claims that the management

! 9

practices of an organization may have different effects on various organizational outcomes

depending on the environment the organization faces and on other aspects of the organization,

including its technology, size, and current performance (Hatch & Cunliff, 2006). Similarly,

research suggests that various management practices may have a distinctive influence on

turnover, contingent on employees’ job performance. The effects of innovative management may

also differ, depending on organizational characteristics including the level of performance

(Sheridan, 1992). In this study, we test two hypotheses on the innovation-turnover relationship,

contingent on an organization’s performance.

Innovation and turnover in low-performing organizations

Whether it is a new set of policies, technologies, or cultural norms, innovation requires an

individual to expend time and effort in order to adopt it. The amount of time and effort involved

in adjustment and adoption, however, varies from one person to another. Because of this

variation, organizational innovation can be used as an effective tool in finding the balance

between turnover and retention rates. When management perceives that the organization is

underperforming because of under-qualified workers, one possible solution is to eliminate low-

caliber performers and to bring in “new blood” (Ingersoll, 2001, p. 504). In this situation, the

cost of retention exceeds the cost of turnover. Therefore, management may want to strategically

implement innovative policies in order to promote turnover as a way of reducing overall costs.

The logic is based on previous research suggesting that resistance to innovation may be stronger

among low-qualified workers than among high-qualified workers (Huselid, 1995). The evidence

is found in Florida, where school districts introduced new accountability systems in 2002. The

purpose of these new accountability systems was to innovate instructional policies and practices

! 10

for improving school productivity (Rouse, Hannaway, Goldhaber & Figlio, 2007). After the

introduction of new accountability systems, Feng, Figlio, and Sass (2010) found high teacher

turnover rates were observed in low-performing school districts as compared to school districts

with a moderate performance. Judging from the theoretical literature and the evidence from the

Florida schools’ case, this study hypothesizes that innovative management to adopt change and

new ideas may result in an increase in employees’ turnover within a low-performing

organization.

Hypothesis 1: When an organization is underperforming, innovative management

increases turnover.

Innovation and turnover in high-performing organizations

The literature suggests that high-performing organizations may be filled with people with

different characteristics when compared with the characteristics of people who work in low-

performing organizations. For instance, after interviewing business executives, Goldsmith (2008)

concluded that high-performing workers see challenges or changes as opportunities, whereas

others see them as threats. Feng, Figlio, and Sass (2010) also argue that high-performing workers

take advantage of challenges and changes rather than avoiding them. Based on an analysis of the

teachers in the Florida school districts, they find that the adoption of new accountability systems

requiring changes of instructional policies and practices increase the retention rates of qualified

teachers. Their findings imply that managerial efforts to innovate may prevent qualified teachers

from leaving their organizations, and once the organizations are filled with high-performing

people, continued innovation can make them take risks and produce greater returns.

! 11

The literature suggests that the success of the innovation depends largely on employees’

acceptance, and that employees’ commitment to innovation, or lack thereof, is determined by the

congruence between innovation values and personal values and between required skills and

current abilities (Choi & Price, 2005). The person-organization fit leads to behavioral

consequences such as organizational citizenship behavior and job satisfaction (O’Reilly,

Chatman, & Caldwell, 1991). On the other hand, a lack of congruence between personal values

and skills and organizational value requirements may lead to negative behaviors such as

absenteeism and turnover.

The top-manager perspective in management theory suggests that top managers are

responsible for adopting key policies that govern an organization (Hambrick & Mason, 1984).

Perhaps more importantly, there is consensus among organization theorists that organizational

leaders have the most influence on organizational culture, as well as the culture of innovation

(Hage & Dewar, 1973; Hatch & Canliff, 2006). Accordingly, top managers’ policy preferences

influence the organization as a whole, and a top manager’s propensity for innovation will affect

an organization’s innovativeness as a whole (Young, Charns, & Shortell, 2001). Research has

shown that top managers’ attitudes and values toward change are a better predictor of innovation

than the structural characteristics of an organization (Morh, 1969).

The literature also points out that the fit between leader and follower is as important as

the person-organization fit (Colbert, 2004). As a result, when leaders have more positive

attitudes toward innovation, individuals with similar values may be attracted and are more likely

to be selected to work in that organization. Therefore, employees with a strong person-

organization fit and leader-follower fit will be more likely to offer a long-term commitment than

employees with a weak person-organization fit (Moynihan & Pandey, 2008). Consequently,

! 12

under the management of leaders with a strong preference for innovation, employees with a

similar preference tend to stay longer in the organization. Superintendents in Texas have the

power and authority to establish district- and school-level policies in their districts as a chief

executive officer (Meier & Hicklin, 2008), and therefore influence the culture within their

district. Hence, superintendents’ innovative management practices decrease employee turnover

in high-performing school districts.

Hypothesis 2: When an organization is high performing, innovative management

decreases turnover.

Data and Method

The unit of analysis in this study is a school district in Texas2 with regard to which a significant

number of public management researchers (e.g., Hicklin, 2004; Fernandez, 2005; Gonzalez–

Juenke, 2005; Hill, 2005; Pitts, 2005; Goerdel, 2006) have developed management concepts and

controls (Meier, O’Toole, & Hicklin, 2010). To clarify a causal relationship between a dependent

variable and explanatory variables in time order, this study uses a dependent variable in

Academic Year (AY) 2007-08 and all explanatory variables in AY 2006-07 except in the 2007-

08 net change of unemployment rates.

This study uses three data sources for the analysis. First, this study utilizes the 2006-07

Superintendent Management Survey (SMS), a part of an ongoing series of Texas school district

surveys by O’Toole and Meier. The 2006-07 SMS survey asked questions about superintendents’

management styles as well as their careers. A total of 757 superintendents from 1,222 school

districts responded to the survey (response rate=62 percent).3 Another data source is the

Academic Excellence Indicator System, available from the Texas Education Agency (TEA)

! 13

website,45 from which information on teachers’ turnover rates and other district resources

including staff, students, and financial situations was obtained. Lastly, the net change of

unemployment rates from 2007 to 2008 was derived from the Bureau of Labor Statistics

website.6

Variables

Dependent variable

The dependent variable of this study is the turnover rate of teachers in AY 2007-08. The TEA

reports the teacher turnover rate by district every year. The turnover rate in 2007-08 is measured

by dividing the total full-time equivalent (FTE) count of teachers from the fall of 2006-07 who

were subsequently not employed in the district in the fall of 2007-08, by the total teacher FTE

count for the fall of 2006-07.7 Figure 1 shows TEA-reported turnover rates for teachers from AY

2003-04 to AY 2007-08. The average turnover rate was slightly higher in AY 2004-05, but the

turnover rates over the AY 2003-08 period have stayed consistently below the 20 percent level.

Figure 1 about here

Table 1 presents the means of teacher turnover rates in the estimation sample. The mean turnover

rate for the given period was 18.89 percent. In AY 2004-05, the turnover rate increased to 20

percent, and there has been little change since. This implies that although this study examines

the variation of turnover for teachers in one academic year (AY 2007-08), there is little suspicion

that any particular event such as an unusual economic shock occurred that affected school

districts in that academic year as compared to other academic years. Therefore, findings from

this study may be generalizable.

! 14

Because the error term of the dependent variable is not normally distributed, using the

ordinary least squares (OLS) regression violates homoscedasticity in Gauss-Markov

assumptions.8 This study employs the weighted least squares (WLS) regression, which is known

to be more efficient than OLS in cases of heteroskedasticity (Woodridge, 2006, p. 284).9

Table 1 about here

Independent variable: performance indicator

Organizational performance is operationalized by using the districts’ Texas Assessment of

Knowledge and Skills (TAKS) pass rate in AY 2006-07. The TAKS is a statewide, annual,

standardized examination consisting of reading, writing, English language, art, mathematics,

science and social studies from grades 3 to 11. The TAKS pass rate is an important index of a

school district’s performance because it taps students’ achievement from each grade and because

both communities and educators are concerned about students’ pass rate.

Independent variable: innovative management

The second independent variable is the degree of innovative management as measured by four

survey items from the 2006-07 SMS. The survey asked questions about the extent to which

superintendents agreed/disagreed with the following sentences: “Our district is always among the

first to adopt new ideas and practices,” “We continually search for new opportunities to provide

services to our community,” “Our district continually adjusts our internal activities and structures

in response to stakeholder initiatives and activities,” and “Our district frequently undergoes

change.” Each of these questions measures how likely superintendents are to change and

innovate their organizations.1011 Using a 4-Likert scale, each question was answered from

strongly disagree to strongly agree. In order to capture the innovativeness of top management, a

! 15

principal factor analysis is employed. As shown in Table 2, all four variables were loaded on

one factor with an Eigen value of 1.826. The factor score from this analysis is used as the degree

of innovative management.

Table 2 about here

This study tests the innovation-turnover relationship contingent on organizational performance.

In order to investigate the moderating role of innovative management, an interaction term is

included by multiplying the TAKS pass rate with the factor score of innovative management.

Control variables

The literature finds that individual factors and organizational/environmental factors influence

turnover. In terms of individual-level factors, this study controls the percentage or mean of

teachers’ race, gender, experience, education, and salary in each district in AY 2006-07. It is

expected that high teacher turnover rates exist in school districts with more teachers who are

from racial minorities and/or who are female, have little or a great deal of experience (a U-

shaped relationship), have advanced degree education, have lower salaries, and/or work longer

hours. In terms of organizational/environment-level factors in AY 2006-07, this study controls

for lagged teachers’ turnover rate, instructional funds per pupil, the percentage of educational

aides12, student race, the number of students per teacher, as well as the unemployment rate net

change from 2007 to 2008 by county.13 It is expected that higher turnover is likely to be found in

school districts with a higher lagged turnover rate, lower instructional funds per pupil, higher

percentage of educational aides, and more racial minorities. A higher student-to-teacher ratio

may place a greater burden on teachers. Thus, districts may have higher teacher turnover if they

have a higher student-to-teacher ratio. In addition, a higher unemployment rate may motivate

! 16

teachers to stay in their jobs, but a bad economy may result in the dismissal of personnel,

including teachers. Thus, it is unclear whether a higher unemployment rate will increase or

decrease teacher turnover, but in all likelihood it influences teacher turnover. Lastly, some

superintendents’ demographic information, such as years of service in the district, gender, and

race, are controlled. To correct skewedness, a logarithm is taken on monetary variables

(teacher’s salary and instructional fund per pupil) (Wooldridge, 2006).

FINDINGS

Regression estimates for teacher turnover in Table 3 suggest that superintendents’ innovative

management, TAKS pass rates, and their interaction term (Innovative Management x TAKS pass

rates) have statistically significant impacts on teachers’ turnover; innovative management being

positively associated with turnover rates; TAKS pass rates being negatively associated with

turnover rates; and their interaction term being negatively associated with turnover rates. To

illustrate the effect of innovative management on turnover, the following equation can be drawn,

holding all other variables constant:

(1)

Because we hypothesize that the effect of innovative management on turnover depends

on the level of organizational performance, the model includes an interaction term between the

performance and innovative management to estimate the effect of one independent variable

contingent on the other. The interaction term is indeed statistically significant and negative,

implying that the effect of innovative management on teacher turnover rates depends on the level

of performance.

(Teachers Turnover) = 4.046(Innovative Management) - 0.061(Innovative Management) × (TAKS)

! 17

Figure 2 shows the differences in the marginal effects of innovative management on

teacher turnover between school districts with low performance and school districts with high

performance. Here, low performance refers to the TAKS pass rate that is one standard deviation

below the mean (=52.80), and high performance refers to the TAKS pass rate that is one standard

deviation above the mean (=78.74). This graph shows that when school districts have one

standard deviation lower TAKS pass rate than the average TAKS pass rate, innovative

management increases teacher turnover. By contrast, the impact of innovative management on

teacher turnover is negative when the TAKS pass rate is one standard deviation above the mean

(pass rate = 78.74 percent).

Figure 2 about here

The lines in Figure 2 imply that the effects of innovative management on turnover change

as the level of performance changes. School districts with a low TAKS pass rate experience more

teacher turnover as their superintendents exercise innovative management. In contrast,

innovative management decreases teacher turnover when school districts have achieved a higher

TAKS pass rate. The figure provides evidence supporting our hypotheses that innovative

management decreases turnover when an organization is high performing, and it increases

turnover when an organization is low performing.

In order to locate the point where the impact of innovative management turns from

positive to negative, we take the first derivative of teacher turnover with respect to innovative

management from Equation 1, and find the following equation:

(2)

∂(Teachers Turnover)∂(Innovative Management)

= 4.046 - 0.061(TAKS)

! 18

From the equation above, the analysis finds that 66.33 percent (=4.046/0.061) of the

TAKS pass rate is the turning point in this sample. When school districts have lower pass rates

than 66.33 percent, superintendents’ innovative management increases teacher turnover rates, but

the innovation-turnover relationship turns negative as TAKS pass rates exceed the turning point

of 66.33 percent. As shown in Table 4, the median of students’ pass rate for TAKS is 67 percent

and the mean is 65.77 percent. The turning point of 66.33 percent is between the mean and the

median pass rates.

Defining good or poor performers is perceptual and subjective. However, in the

estimation sample (n=460), about 47 percent of them (n=216) are found to have lower pass rates

than 66.33 percent. For these districts, superintendents may attempt to increase turnover by

practicing innovative management, and they may have capacity to hire new, more able teachers.

For the rest of the districts (53 percent) with a TAKS pass rate higher than 66.33 percent,

superintendents might perceive the teachers in those districts as being good performers, and

would keep the turnover rate as low as possible through innovative management.

Table 4 about here

The effects of the remaining control variables mostly meet the expectation previous research

suggests. As for individual factors, districts with more female teachers have lower turnover rates.

Previous literature finds that an employee’s experience and turnover have a U-shaped

relationship (Ingersoll, 2001) and the finding provides evidence of such a relationship. That is,

districts with inexperienced and very experienced teachers have higher teacher turnover rates,

while districts with middle-experienced teachers have lower teacher turnover rates.

! 19

As for organization/environment-related factors, school districts have higher turnover

rates if they had a higher turnover rate in the previous year. This implies that teachers’ turnover

is inertial and/or systematic. Such characteristics of districts’ turnover make this study more

meaningful because innovative management can handle inertial or systematic teacher turnover of

school districts. Districts with a higher percentage of white students have lower turnover rates.

Generally, communities with more white students and their families have better living and

working environments. Unlike the expectation, other control variables such as a net change in

the unemployment rate, class size, the number of educational aides and so on are not found to be

statistically influencing.

CONCLUSION AND DISCUSSION

The findings of this study suggest that managers may use innovation to manage turnover rates,

and the relationship between innovative management and turnover is contingent on the

organization’s performance. In other words, management adjusts innovative strategies

depending on the organization’s current level of performance in an effort to improve future

performance by finding an optimal level of turnover. The results demonstrate that, in poorly

performing school districts, superintendents’ innovative management increases teacher turnover,

while it decreases turnover in high-performing districts. This finding may provide an explanation

for why innovation capability is a determining factor of firm performance (Mone, McKinley, &

Barker, 1998). In summary, the results imply that innovative management on the part of top

managers promotes turnover in low-performance situations and retention in high-performance

situations.

! 20

How might managers practice innovative management? Literature on creativity

management provides potential answers to this question. Creativity management, according to

Berman and Kim (2010) is “management processes whose goals are to increase, evaluate, and

prepare new ideas for subsequent implementation in organizations” (p. 621). Creativity

management involves developing new strategies, solutions, services, and processes for

organizational success (Rangarajan, 2008). Although relatively little scholarly attention has been

paid to creativity management in public sector, Rangarajan (2008) finds that state and local

governments outperform in creativity management compared to the federal government. Berman

and Kim’s investigation (2010) of creativity management in Seoul Metropolitan Government

also shows that the government of the world’s eighth largest city practiced creativity

management by a) evaluating and rewarding for subordinates who suggest new ideas; b)

encouraging new ideas through training, education, and discussion; c) auditing and managing

performance that stimulates program innovation; and d) adopting constituents’ ideas for

improving public organization services – consistent with the idea of innovation. As a result of the

creative management initiative, Seoul Metropolitan Government adopted 13 percent of 62,666

ideas (Berman & Kim, 2010). The ideas and practices of creativity management imply that

public managers can innovate their organizations through adopting these ideas, and findings of

this study suggest that innovation can help public managers control employee turnover in that

process.

Existing research has examined the effects of employee turnover by investigating the

nonlinear link between turnover (at time T) and organizational performance (at time T+1).

However, little is known about the ways in which management may control turnover under

different circumstances. This study contributes to the literature by examining the link between

! 21

innovative management and turnover and the contingency between an organization’s

performance and innovative management. The findings of this study imply that turnover rates (at

time T) are manageable through innovative policies (at time T-1) for both well-performing

organizations and badly-performing organizations (at Time T-1). Management can therefore use

innovation to increase organizational performance. Future research may simultaneously

investigate management’s role in terms of a recurring performance (at time T-1) - turnover (at

time T) – performance (at time T+1) link.

While this study makes a unique contribution by finding the performance-contingent

innovation-turnover relationship, the results should be applied with caution because of a few

limitations with regard to the data and analysis. First, this study uses data on school districts, and

they may not be representative of all types of public organizations. However, these school

districts are a highly diverse set of organizations in terms of size, economic conditions, and racial

and ethnic composition. In addition, as Kettl and Fesler (2007) point out, school districts account

for a significant part of America’s public administration, as more than half of state and local

budgets are spent on education. The data have also been used to examine public management

questions in numerous studies (see Meier & Hicklin, 2008; Meier & O’Toole, 2003; Pitts, 2005).

Second, the data sets used in this study were collected at the organizational (district) level.

Consequently, this study is limited in terms of directly testing whether innovative management

has distinctive effects on individual workers, depending on their performance level and their fit

with organizational values. Lastly, one should keep in mind that innovation is a multifaceted

concept which includes many different aspects such as technology, process, and culture. While

this study focuses on the innovativeness of an organization as a whole as perceived by top

! 22

managers, future research might investigate the link between different aspects of innovation and

turnover.

! 23

Table 1: Turnover Ratio over Time

Academic Year Turnover Ratio

2003-2004 17.84

2004-2005 20.20

2005-2006 18.25

2006-2007 19.31

2007-2008 18.85

Average 18.89

! 24

Table 2: Factor Loadings for Innovative Management

Factor Loadings

Our district is always among the first to adopt new ideas and practices

0.738

We continually search for new opportunities to provide services to our community

0.638

Our district continually adjusts our internal activities and structures in response to stakeholder initiatives and activities

0.624

Our district frequently undergoes change 0.696

Eigen Value 1.826

! 25

Table 3. Impact of Performance on Turnover and Moderating Effects of Innovative Management Dependent Variable = Teacher Turnover Rates in 2007-8 Slope Standardized Coefficient

Innovative Management 4.046* 0.380

(1.607)

TAKS Pass Rate -0.110*** -0.120

(0.034)

Innovative Management x TAKS Pass Rate -0.061** -0.395

(0.023)

% White Teachers 0.039 0.065

(0.030)

% Female Teachers -0.085 -0.056

(0.047)

Teachers’ Experience (years) -2.856*** -1.039

(0.019)

Teachers’ Experience Squared (years) 0.093*** 0.657

(0.027)

% Teachers with PhD Degree 0.274 0.102

(0.206)

Average Teacher's Base Salary (logged) -5.906 -0.075

(5.659)

Lagged Turnover (2006-7) 0.326*** 0.355

(0.039)

Instructional Funds per Pupil (logged) 2.261 0.050

(3.473)

% White Students -0.033 -0.074

(0.019)

Unemployment Rate Net Change (07-08) 1.278 0.039

(0.811)

Students per Teacher -0.351 -0.097

(0.290)

Superintendent’s Tenure in the District (years) -0.035 -0.016

(0.059)

Educational Aides -0.090 -0.036

(0.069)

Female Superintendent (dummy) 0.224 0.006

(0.859)

White Superintendent (dummy) -0.368 -0.008

(1.522)

Constant 93.684* (49.384) Observations 460

Adjusted R-squared 0.764 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

! 26

Table 4: Distribution of the TAKS Pass Rates in 2007 Percentile Pass Rate (%)

25th Percentile 59 50th Percentile 67 75th Percentile 74

Average 65.77

! 27

Figure 1: Box-whisker Plot for Teacher Turnover from AY 2003-04 to AY 2007-08

! 28

Figure 2: Differences in the Marginal Effects of Innovative Management on Teacher Turnover between Low-performing and High-performing School Districts

Low Performance

High Performance

! 29

Appendix 1: Correlation Matrix and Descriptive statistics

(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19)

(1) Turnover (2007-08) 1.000

(2) Innovative Management 0.188 1.000

(3) TAKS Pass Rate -0.362 -0.136 1.000

(4) Innovative Management x TAKS Pass Rate 0.159 0.979 -0.096 1.000

(5) % White Teachers -0.212 -0.219 0.436 -0.197 1.000

(6) % Female Teachers -0.095 -0.058 0.388 -0.027 0.156 1.000

(7) Teachers’ Experience (years) -0.416 -0.235 0.268 -0.217 0.298 -0.022 1.000

(8) Teachers’ Experience Squared (years) -0.359 -0.240 0.229 -0.223 0.261 -0.016 0.969 1.000

(9) % Teachers with PhD Degree 0.184 0.106 -0.147 0.093 -0.081 -0.109 -0.079 -0.052 1.000

(10) Average Teacher's Base Salary (logged) -0.350 -0.051 0.175 -0.035 -0.059 -0.101 0.460 0.408 -0.128 1.000

(11) Lagged Turnover (2006-07) 0.551 0.193 -0.369 0.170 -0.203 -0.120 -0.461 -0.389 0.231 -0.421 1.000

(12) Instructional Funds per Pupil (logged) -0.023 -0.118 0.012 -0.100 0.135 -0.165 0.318 0.311 -0.034 0.208 -0.116 1.000

(13) % White Students -0.292 -0.252 0.495 -0.231 0.782 0.139 0.268 0.231 -0.107 -0.056 -0.263 0.025 1.000

(14) Unemployment Rate Net Change (2007-08) 0.062 0.006 0.061 0.014 0.052 0.131 -0.151 -0.137 0.091 -0.054 0.001 -0.121 0.114 1.000

(15) Students per Teacher 0.055 0.229 -0.150 0.196 -0.352 0.069 -0.349 -0.329 0.095 0.038 0.164 -0.808 -0.280 0.102 1.000

(16) Superintendent's Tenure in the District (years) -0.091 0.032 0.082 0.034 0.036 0.033 -0.037 -0.033 0.013 -0.052 -0.072 0.058 0.077 0.016 -0.043 1.000

(17) Educational Aides (% of paraprofessional staff) -0.148 -0.136 -0.027 -0.119 0.148 0.031 0.086 0.060 -0.096 -0.046 -0.167 0.067 0.028 -0.079 -0.021 0.000 1.000

(18) Female Superintendent (dummy) 0.090 0.033 0.077 0.045 -0.077 0.056 -0.110 -0.096 0.069 -0.035 0.088 -0.033 -0.078 0.018 0.079 -0.047 -0.101 1.000

(19) White Superintendent (dummy) -0.130 -0.130 0.247 -0.124 0.700 0.117 0.155 0.141 -0.082 -0.027 -0.110 0.135 0.545 -0.001 -0.304 0.048 0.048 -0.009 1.000

Mean 19.484 0.007 65.772 -1.228 83.629 75.335 11.762 148.528 0.285 10.602 20.463 8.546 56.729 0.078 12.051 4.556 12.116 0.198 0.874

Standard Deviation 11.311 0.975 12.969 65.396 23.289 8.446 3.196 66.941 0.961 0.087 11.837 0.239 28.480 0.382 2.797 4.261 5.322 0.399 0.332

Minimum 0.000 -1.971 15.000 -161.641 0 43.244 0.060 0.004 0.000 10.250 0.000 7.055 0.000 -2.000 4.200 0.167 0.000 0.000 0.000

Maximum 81.818 2.694 96.000 226.261 100 100 20.100 404.010 10.114 10.948 90.578 9.674 98.900 1.800 27.621 29.000 36.177 1.000 1.000

Observation: 460

! 30

Appendix 2: Response Results for Innovative Management-related Survey Items

Survey Item Strongly Agree Tend to Agree Tend to Disagree

Strongly Disagree

Our district is always among the first to adopt new ideas and practices

5

(.91 %)

226

(41.02 %)

272

(49.36 %)

48

(8.71 %)

We continually search for new opportunities to provide services to our community

2

(.36 %)

59

(10.71 %)

366

(66.42 %)

124

(22.50 %)

Our district continually adjusts our internal activities and structures in response to stakeholder initiatives and activities

6

(1.09 %)

101

(18.33 %)

365

(66.24 %)

79

(14.34 %)

Our district frequently undergoes change

17

(3.09 %)

225

(40.83 %)

255

(46.28 %)

54

(9.80 %)

Reference Abelson, M. A., & Baysinger, B. D. (1984). Optimal and dysfunctional turnover: Toward an organizational level

model. The Academy of Management Review, 9(2), 331-341.

Agarwala, T. (2003). Innovative human resource practices and organizational commitment: an empirical investigation. The International Journal of Human Resource Management, 14(2), 175-197.

Ascher, C., & Fruchter, N. (2001). Teacher quality and student performance in new york city's low-performing schools. Journal of Education for Students Placed at Risk (JESPAR), 6(3), 199-214.

Bali, V. A., & Alvarez, R. M. (2004). The race gap in student achievement scores: Longitudinal evidence from a racially diverse school district. Policy Studies Journal, 32(3), 393-415.

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.

Becker, H. J. (2000). Findings from the teaching, learning, and computing survey: Is larry cuban right? Education Policy Analysis Archives, 8. Retrieved from http://epaa.asu.edu/ojs/article/view/442/565

Berman, E. M., & Kim, C.-G. (2010). Creativity management in public organizations jump-starting innovation. Public Performance and Management Review, 33(4), 619-652.

Bidwell, C. E., & Kasarda, J. D. (1975). School district organization and student achievement. American Sociological Review, 40(1), 55-70.

Boyd, D., Hamilton, L., Loeb, S., & Wyckoff, J. (2005). Explaining the short careers of high-achieving teachers in schools with low-performing students. The American Economic Review, 95(2), 166-171.

Bureau of Labor, S. (2008). Job openings and labor turnover. Retrieved from http://www.bls.gov/news.release/archives/jolts_06102008.pdf.

Caldas, S. J., & Carl, B., III. (1997). Effect of school population socioeconomic status on individual academic achievement. The Journal of Educational Research, 90(5), 269-277.

Chin, C. (2012). Colorado innovation schools act annual report. Retrieved from http://www.cde.state.co.us/choice/download/SB130/AnnualReportInnovation2012.pdf.

Choi, J. N., & Price, R. H. (2005). The effects of person–innovation fit on individual responses to innovation. Journal of Occupational and Organizational Psychology, 78(1), 83-96.

Colbert, B. A. (2004). The complex resource-based view: Implications for theory and practice in strategic human resource management. The Academy of Management Review, 29(3), 341-358.

Daft, R. L. (1978). A dual-core model of organizational innovation. The Academy of Management Journal, 21(2), 193-210.

Dalton, D. R., Krackhardt, D. M., & Porter, L. W. (1981). Functional turnover: An empirical assessment. Journal of Applied Psychology, 66(6), 716-721.

Damanpour, F. (1996). Organizational complexity and innovation: Developing and testing multiple contingency models. Management Science, 42(5), 693-716.

Darling-Hammond, L. (2000). Teacher quality and student achievement: A review of state policy evidence. Education Policy Analysis Archives, 8(1), Retrieved from http://epaa.asu.edu/epaa/v2018n2011/.

Driscoll, D., Halcoussis, D., & Svorny, S. (2003). School district size and student performance. Economics of Education Review, 22(2), 193-201.

Eide, E., Goldhaber, D., & Brewer, D. (2004). The teacher labour market and teacher quality. Oxford Review of Economic Policy, 20(2), 230-244.

Feng, L., Figlio, D. N., & Sass, T. (2010). School accountability and teacher mobility. Working Paper 47.

Calder Urban Institute

Fernandez, S. (2005). Developing and testing an integrative framework of public sector leadership: Evidence from the public education arena. Journal of Public Administration Research and Theory, 15(2), 197-217.

Glebbeek, A. C., & Bax, E. H. (2004). Is high employee turnover really harmful? An empirical test using company records. The Academy of Management Journal, 47(2), 277-286.

Glennan, T. K., & Melmed, A. (1996). Fostering the use of educational technology: Elements of a national strategy. Santa Monica,CA: RAND.

Goerdel, H. T. (2006). Taking initiative: Proactive management and organizational performance in networked environments. Journal of Public Administration Research and Theory, 16(3), 351-367.

Goldhader, D. D., Brewer, D. J., & Anderson, D. J. (1999). A three-way error components analysis of educational productivity. Education Economics, 7(3), 199-208.

Goldsmith, M. (2008). Helping successful leaders get even better. Business Strategy Series, 9(3), 95-103.

Gonzalez-Juenke, E. (2005). Management tenure and network time: How experience affects bureaucratic dynamics. Journal of Public Administration Research and Theory, 15(1), 113-131.

Guin, K. (2004). Chronic teacher turnover in urban elementary schools. Education Policy Analysis Archives, 12(42).

Hage, J., & Dewar, R. (1973). Elite values versus organizational structure in predicting innovation. Administrative Science Quarterly, 18(3), 279-290.

Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. The Academy of Management Review, 9(2), 193-206.

Harris, D. N., & Adams, S. J. (2007). Understanding the level and causes of teacher turnover: A comparison with other professions. Economics of Education Review, 26(3), 325-337.

Hatch, M. J., & Cunliffe, A. L. (2006). Organization theory : modern, symbolic, and postmodern perspectives (2nd ed.). New York, NY: Oxford University Press.

Henke, R. R., & Zahn, L. (2001). Attrition of new teachers among recent college graduates comparing occupational stability among 1992-93 graduates who taught and those who worked in other occupations. Washington, D.C.: National Center for Education Statistics.

Hicklin, A. (2004). Network stability: Opportunity or obstacles? Public Organization Review, 4(2), 121-133.

Hill, G. C. (2005). The effects of managerial succession on organizational performance. Journal of Public Administration Research and Theory, 15(4), 585-597.

Hirschman, A. O. (1970). Exit,voice and loyalty:responses to decline in firms, organizations and states. Cambridge, MA: Harvard University Press.

Houtenville, A. J., & Conway, K. S. (2008). Parental effort, school resources, and student achievement. Journal of Human Resources, 43(2), 437-453.

Huselid, M. A. (1995). The impact of human resource management practices on turnover, productivity, and corporate financial performance. The Academy of Management Journal, 38(3), 635-672.

Ingersoll, R. M. (2001). Teacher turnover and teacher shortages: An organizational analysis. American Educational Research Journal, 38(3), 499-534.

Jeynes, W. H. (2007). The relationship between parental involvement and urban secondary school student academic achievement. Urban Education, 42(1), 82-110.

Keigher, A., & Cross, F. (2010). Teacher attrition and mobility results from the 2008-09 teacher follow-up survey. Washington, D.C.: National Center for Education Statistics.

Kettl, D. F., & Fesler, J. W. (2007). The politics of the administrative process. Washington, D.C.: CQ Press.

Lee, G., & Jimenez, B. S. (2011). Does performance management affect job turnover intention in the federal government? The American Review of Public Administration, 41(2), 168-184.

Lee, S.-Y., & Hong, J. H. (2011). Does family-friendly policy matter? Testing its impact on turnover and performance. Public Administration Review, 71(6), 870-879.

Lee, S.-Y., & Whitford, A. B. (2008). Exit, voice, loyalty, and pay: Evidence from the public workforce. Journal of Public Administration Research and Theory, 18(4), 647-671.

Meier, K. J., & Hicklin, A. (2008). Employee turnover and organizational performance: Testing a hypothesis from classical public administration. Journal of Public Administration Research and Theory, 18(4), 573-590.

Meier, K. J., & O'Toole, L. J. (2003). Public management and educational performance: The impact of managerial networking. Public Administration Review, 63(6), 689-699.

Meier, K. J., O'Toole, L. J., & Hicklin, A. (2010). I’ve seen fire and i’ve seen rain: Public management and performance after a natural disaster. Administration and Society, 41(8), 979-1003.

Mohr, L. B. (1969). Determinants of innovation in organizations. The American Political Science Review, 63(1), 111-126.

Mone, M. A., McKinley, W., & Barker, V. L., III. (1998). Organizational decline and innovation: A contingency framework. The Academy of Management Review, 23(1), 115-132.

Moynihan, D. P., & Pandey, S. K. (2008). The ties that bind: Social networks, person-organization value fit, and turnover intention. Journal of Public Administration Research and Theory, 18(2), 205-227.

Mueller, F. (1996). Human resources as strategic assets: An evolutionary resource-based theory. Journal of Management Studies, 33(6), 757-785.

Nicholson-Crotty, S., & Meier, K. J. (2002). Size doesn't matter: In defense of single-state studies. State Politics & Policy Quarterly, 2(4), 411-422.

O'Reilly, C. A., Chatman, J., & Caldwell, D. F. (1991). People and organizational culture: A profile comparison approach to assessing person-organization fit. Academy of Management Journal, 34(3), 487-516.

Pitts, D. W. (2005). Diversity, representation, and performance: Evidence about race and ethnicity in public organizations. Journal of Public Administration Research and Theory, 15(4), 615-631.

Rangarajan, N. (2008). Evidence of different types of creativity in government: A multimethod assessment. Public Performance and Management Review, 32(1), 132-163.

Rivenbark, W. C., & Kelly, J. M. (2003). Management innovation in smaller municipal government. State and Local Government Review, 35(3), 196-205.

Rouse, C. E., Hannaway, J., Goldhaber, D., & Figlio, D. (2007). Feeling the Florida heat? How low-performing schools respond to voucher and accountability pressure. Cambridge, MA: National Bureau of Econmic Research.

Selden, S. C., & Moynihan, D. P. (2000). A model of voluntary turnover in state government. Review of Public Personnel Administration, 20(2), 63-74.

Sheridan, J. E. (1992). Organizational culture and employee retention. The Academy of Management Journal, 35(5), 1036-1056.

Wooldridge, J. M. (2006). Introductory econometrics : A modern approach (3rd ed.). Mason, OH: Thomson/South-Western.

Young, G. J., Charns, M. P., & Shortell, S. M. (2001). Top manager and network effects on the adoption of innovative management practices: A study of TQM in a public hospital system. Strategic Management Journal, 22(10), 935-951.