turnover prediction plz read

8/6/2019 Turnover Prediction Plz Read

1/28

Turnover prediction usingattitudes towards benefits, pay,

and pay satisfaction amongemployees and entrepreneurs in

Estonia, Latvia, and LithuaniaShawn M. Carraher

Severson Entrepreneurship Academy, Minot State University,Minot, North Dakota, USA

Abstract

Purpose This paper seeks to examine the efficacy of predicting turnover for employees andentrepreneurs from Estonia, Latvia, and Lithuania using attitudes towards benefits, pay satisfaction,pay, gender, and age across a four-year time frame.

Design/methodology/approach A survey that included information on attitudestowards benefitsand pay satisfaction was used to collect data from 153 Estonian, 157 Latvian, and 146 Lithuanianemployees and 243 Latvian, 103 Estonian, and 109 Lithuanian entrepreneurs. The turnover of theemployees and business owners was then followed over a four-year time period with assessments doneeach year allowing for an examination of temporal variations in the relationships over time. Actualsalary/income data was also obtained from organizational records.

Findings It was found that for the employee samples the classification rates increased slightly ascompared to base rates over time (e.g. did better the longer the time period included), while for theemployers the classification rates and R2 values were relatively flat as compared to base rates. For theemployee samples the R2 values decreased over time. Attitudes towards benefits were generallysignificant predictors of turnover for employees and entrepreneurs over a four-year time period whilesatisfactionwith paywas typicallysignificantfor employeesbut notfor entrepreneurs. It wasalso foundthat for the employees both equity and expectancy considerations were able to explain differences inturnover rates while for entrepreneurs expectancy theory considerations were more powerful thanequity theory explanations.

Research limitations/implications The research is limited both by geography, job types, andthe theoretical construct of turnover. Few studies have examined turnover among both employees andbusiness owners, and few studies have explored the similarities and differences between the two.

Practical implications Pay and benefits are important for employees. Pay seems to be importantfor attracting employees while benefits are important for retaining them.

Originality/value This study examines turnover for both employees and entrepreneurs with afour-year longitudinal design with data from three different countries Estonia, Latvia, andLithuania. Temporal variations in the relationships are also examined on a year by year basis.

As employee retention has been an important factor in the Baltic region over the last two decades it isvital to understand how to retain employees.

Keywords Employee turnover, Entrepreneurs, Pay, Estonia, Latvia, Lithuania

Paper type Research paper

Employee compensation has long been a topic of interest to employers and employeesalike. The concept of an employment relationship implies that employees work inexchange for some reward, and this reward is usually monetary remuneration.

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/1746-5265.htm

Turnoverprediction

25

Received May 2009Revised July 2009

Accepted February 2010

Baltic Journal of ManagementVol. 6 No. 1, 2011

pp. 25-52q Emerald Group Publishing Limited

1746-5265DOI 10.1108/17465261111100905


2/28

Pay, pay satisfaction, and attitudes towards benefits have emerged as popularvariables for use in organizational research (for reviews, see Carraher et al., 2004a, b, c;Gerhart and Rynes, 2003; Scarpello and Carraher, 2008; Williams et al., 2008).They exhibit significant relationships with organizationally important outcomes such

as absenteeism, turnover intentions, perceived organizational attractiveness for jobseekers, organizational citizenship behaviors, and job performance (Carraher et al.,2006a, b; Gaiduk et al., 2009; Labatmediene et al., 2007; Sturman et al., 2003).

Businesses of all sizes are competing in a global marketplace for employees(Labatmediene et al., 2007; Vilma and Egle, 2007; Welsh and Pendleton, 2006). They facethe difficult task of providing competitive compensation and benefit packages toemployees in a cost effective manner (DiFiore, 2000; Simmons, 2001), attracting(and retaining) employees with the needed knowledge, skills, and abilities in order toeffectively perform their jobs (Sturman, 2003), and trying to have the organizationremain profitable. Research with small, medium, and large businesses from around theworld has found that employee benefit and compensation packages can play a strategicrole in enhancing organizational performance and profitability (Joo, 2000; Mangel and

Useem, 2000; Meyer et al., 2001). Employers view compensation as a major cost factor ofproduction, and as a necessary inducement for attracting suitable job applicants inaddition to retaining valued employees, motivating performance, and other desirablebehaviors (Carter and Van Auken, 1990, 2005; Sturman, 2003; Sturman et al., 2003).Within budget constraints, employers attempt to provide fair pay with respect to thefollowing:

. the external labor market;

. the relative value of the job; and

. the added-value individuals produce for the organization.

Within an industry employers tend to experience similar business costs and require the

services of similarly skilled individuals. To maintain competitive positions withinproduct markets, employers typically control their compensation outlays by assessingthe compensation practices of other employers within their industry. Employersmay also attempt to maintain competitiveness with respect to benefit offerings(Carraher et al., 2003a, b). Heneman and Berkley (1999) found that many smallbusinesses were so successful with their compensation and benefit packages that theyhad significantly more applicants per vacancy than larger firms. In 2003, MetLife found

job satisfaction to be higher with small employers than for large employers (54 percentsatisfied vs 37 percent), but found no differences in benefit satisfaction based uponorganizational size. They also found that 25 percent of employees and 27 percent ofemployers believed that employee benefits were an important reason for joining anorganization while 42 percent of employees reported their organizations benefits as animportant reason to stay with the organization (MetLife, 2003). Dale-Olsen (2006) foundthat fringe benefits have a stronger influence on reducing turnover than would beindicated by the direct costs of the benefits.

Employer compensation practices are intended to provide fair compensation(Carraher and Carraher, 2005; Scarpello and Carraher, 2008). The term fair, however, isdefined by the compensation systems ability to balance competitive businessinterests through the cost control of compensation outlays with the compensationgoals of attracting, retaining, motivating, and developing a competent workforce

BJM6,1

26


3/28

(Pohlen and La Londe, 1994). Because employer business costs vary across industriesand countries, fair pay and benefits may be relative terms (Carraher and Welsh, 2009;Gustainiene and Endriulaitiene, 2009; Kakabadse etal., 2004; Kessler et al., 2006; Lunnanand Traavik, 2009; Turk, 2008).

When addressing issues of fair pay and benefits two theories are at the forefront ofmanagerial research: equity theory (Adams, 1963; Jaques, 1961) and expectancy theory(Rotter, 1954; Tolman, 1932; Vroom, 1964), with equity theory being the most commonlyexamined (Scarpello and Carraher, 2008). As their name implies, equity theories concernthemselves with what is equitable or fair. At the most basic level they examine howequity is determined, how individuals respond to unfair situations, and what leadsindividuals to believe/feel that they are being equitably treated and to therefore besatisfied with their current situation (Carraher and Carraher, 2005). Expectation theoriesapproach motivation from a different direction. Expectation theories investigate andexplain why individuals make choices between various courses of action (Steel andKonig, 2006). Expectancies and valence (expected value/attractiveness of an outcome)are used to explain motivations within expectancy theories and two different type ofexpectancies are important: the expectation that one can successfully perform if effort isinvested and the expectation that if one performs they shall receive a particular outcome(Vroom, 1964). Both expectancy theories and equity theories can be useful for explainingindividuals behaviors and how benefits and pay can differentially influence them basedupon variations in backgrounds especially differences in work experiences andcultural diversity (Carraher and Carraher, 2005; Carraher et al., 2008; Konopaske andWerner, 2005; Roolaht, 2006; Scarpello and Carraher, 2008; Sturman and Carraher, 2007).For instance, Krau (1981) has suggested that antecedents of turnover may beorganizational, career, and job specific. Thus, while it is possible that organizational payand benefits may be important factors in reducing turnover, there may be culturalvariations in the relationships observed, differences based upon the industries examined,

and temporal differences (the nature of the relationship may change over time).Lunnan and Traavik (2009) examined whether or not there were cultural variations in

perceptions of fairness of human resource management practices. They found supportfor both national and individual level cultural variations in perceptions of fairness ingeneral human resource management practices. While examining attitudes towardsbenefits Carraher and Buckley (2005) and Carraher (2006) found support for regionalcultural variations in the relationship between attitudes towards benefits and businessturnover. Carraher and Buckley (2005) found that over an 18-month time period attitudestowards benefits were unrelated to business turnover for business owners in Belgium,France, or Luxembourg. Konopaske and Werner (2005) found that tenets fromexpectancy theory in regard to employee benefits could explain managers willingnessto accept expatriate assignments. Carraher (2006), however, found a correlation of 0.1194

between the perceived ease of replacement of benefits and turnover in Eastern Europe(Belarus, Poland, and Ukraine). Thus, previous research has supported the importanceof attitudes towards benefits and business turnover in Eastern Europe but not inWestern Europe, indicating that there may be cultural variations in the relationshipsbetween benefits and turnover. Williams et al. (2006), in their meta-analyses, examinedthe antecedents and consequences of pay level satisfaction and found a r of20.17between voluntary turnover and pay level satisfaction while Griffeth et al. (2000),found rs of 20.09 (when not controlling for turnover base rates) to 20.11

Turnoverprediction

27


4/28

(when controlling for turnover base rates) for actual pay and rs of20.07 (when notcontrolling for base rates of turnover) to 20.08 (when controlling for base rates ofturnover) for pay satisfaction (n 4,425). Thus, both meta analyses support astatistically significant relationship between compensation variables and turnover.

One of the most frequent problems organizations in the Baltics have faced has beenemployee retention (Gaiduk et al., 2009). For instance, in Lithuania more than 400,000citizens have emigrated since 1990 and the exiting of qualified workers for higherpaying jobs in Western Europe has resulted in labor costs rising faster than grossdomestic product growth (Gaiduk et al., 2009). Utilizing three samples of employees andthree samples of business owners (one from each of the three Baltic countries ofEstonia, Latvia, and Lithuania), this study adds to the literature by examining attitudestowards benefits to the compensation mix of pay level and pay level satisfaction in theprediction of turnover across four time periods. Hoobler and Johnson (2004) report thatonly 6 percent of articles in leading human resource management journals areconcerned with turnover and 12 percent with all areas of compensation, so this area isripe for study. Even less research has examined issues of motivation, compensation,and retention of entrepreneurs and CEOs within their organizations, occupations, andcareers (Ortqvist et al., 2007; Pundziene and Duobiene, 2006; Sullivan et al., 2007, 2009;Zidonis, 2007). While it has long been known that temporal variations may exist (Heise,1969; Lakis, 2009; McComas, 1922), few studies of turnover have examined possibletemporal variations in relation to turnover (Carraher, 2006) and it appears that nonehave empirically examined these changes in the rapidly changing Baltic region. Basedupon the research discussed here, the following hypothesis is offered: it is hypothesizedthat attitudes towards benefits, pay, pay satisfaction, gender, and age shall be able tosignificantly predict turnover among entrepreneurs and employees in Estonia, Latvia,and Lithuania. It is further hypothesized that both equity and expectancy variablesshall be useful predictors of turnovers for employees and entrepreneurs.

MethodsSamplesData were collected from six samples in three countries in the Baltic region. Threesamples were of employees and three were entrepreneurs (owners of businesses).The first sample consists of 153 Estonian employees in the services sector. Their averageage was 36.59 (SD 12.56) at the beginning of the study, and 61 percent of them weremale. In terms of turnover, 12.4 percent left in the first year, 20.3 percent in the first twoyears, 35.3 percent in the first three years, and 44.4 percent in the full four years. Thesecond sample consists of 157 Latvian employees in the services sector. Their averageage was 35.44 (SD 8.78) at the beginning of the study, and 59 percent were males. Interms of turnover 14.4 percent left in the first year, 12.6 percent in the first two years, 23.3

percent in the first three years, and 34.9 percent in the full four years. The third sampleconsists of 146 Lithuanian employees from the services sector. Their average age was36.85 (SD 11.85) at the beginning of the study, and 59 percent were male. In terms ofturnover, 14.7 percent left in the first year, 27.4 percent in the first two years, 39.9 percentin the first three years, and 53.8 percent by the full four years. The fourth sampleconsists of 243 business owners in Latvia. Their average age was 37.7 (SD 10.89) atthe beginning of the study, and 29.3 percent were male. In terms of turnover 2.5 percentleft in the first year, 5.8 percent in the first two years, 12.8 percent in the first three years,

BJM6,1

28


5/28

and 16.5 percent by the full four years of the study. The fifth sample consists of103 business owners in Estonia. Their average age was 36.1 (SD 10.82) at thebeginning of the study, and 56 percent were males. In terms of turnover 7 percent left inthe first year, 10 percent in the first two years, 18 percent in the first three years, and

23 percent in the full four years of the study. The sixth sample consists of 109 businessowners in Lithuania. Their average age was 35.9 (SD 9.41) at the beginning of thestudy, and 58 percent were males. In terms of turnover 7.1 percent left in the first year,11.1 percent in the first two years, 13.1 percent in the first three years, and 14.1 percent inthe full four years of the study. It is apparent that while the base rates for turnoverbetween the employees and business owners initially do not differ significantly at the0.05 level, they are substantially different by the end of the four years of the study.The entrepreneurial samples came from small businesses in the retail sector while theemployee samples came from service sector organizations.

Procedure

As previously done in other geographic areas the local populations were surveyed in thedata collections which generally results in response rates of over 90 percent (Carraher,2006; Carraher and Buckley, 2005). Reporting response rates for this type of data is notvery straight forward as there are multiple ways of defining the response rates.For example, the three employee samples were recruited through the use of their parentorganizations. The top management teams of the organizations were involved inencouraging the employees to participate so typically all of the employees working onthe days that the data is collected who come in for work fill out the surveys so theresponse rate is nearly 100 percent. However, there are typically between 4 to 12 percentof employees who are absent so it could be between 88 to 96 percent. In terms ofrecruiting organizations only about 1/20 allowed data collection for this study and insome situations it is fewer than 1 in 100. For the entrepreneurial samples the locations

were located by individuals from the regions surveyed and then the owners/managers ofthe mall/market buildings were contacted in order to solicit their permission to surveythe entire sample of businesses operating within their retail areas. The business ownerswere invited to participate in a project designed to increase their profitability and weresurveyed at a presentation done at a central location in the mall/market. The responserates are typically around 95 percent based upon the number of individuals who chooseto attend the presentation. In these sites there were between 92 (Estonia) to 98 percent(Latvia) of the small business owners choosing to participate in the presentations however in Estonia and Lithuania for every site (mall/market building) that participatedthere were 3 that did not choose to participate. In Latvia 2/3 chose to participate which iswhy the sample size is larger. Participants were given unlimited time to complete thequestionnaire. None of their supervisors or any personnel representatives were present

while participants filled out the survey. However, they were encouraged to participateby their managers who were interested in learning how to better retain employees.The surveys were translated by a language translation expert, and then back translatedby another translation expert under the guidance of a third language expert.

MeasuresPay satisfaction. The measure of pay satisfaction was taken from the Satisfaction withPay measure of the Job Descriptive Index (JDI; Smith et al., 1969, revised version,

Turnoverprediction

29


6/28

Bowling Green State University, 1985). Owing to the descriptive nature of the items theonly modification typically needed when using the instrument across countries islanguage translation.

Attitudes towards benefits. This six-item scale purports to measure a variety of

attitudes towards ones benefits (Hart, 1990; Hart and Carraher, 1995; Carraher et al.,2003a, b) and is based on expectancy theory and equity theory (Hart, 1990). The first twoitems are based on equity theory while the other four questions are based on expectancytheory (expectancies for question 3 and valences for questions 4, 5, and 6). Responses toitems 1 through 4 utilize seven-point scales. ATBS1 and ATBS2 are intended to assesslevels of satisfaction with benefits. They include the questions how good are thebenefits you currently receive compared to those received by others in similarorganizations? and how satisfied are you with your current benefits package? ATBS3is concerned with the perceived ease of replacement of benefits, and asks, what are thechances you could obtain a similar job with a better benefits package than you nowreceive? ATBS4 and 5 are intended to measure the importance of benefits to anindividual and ask, how important is your benefits package to you? and would youtrade your benefits package for its equivalent worth in cash? (circle Yes or No). Thefinal item asks, what percentage of your salary would you guess your benefits packageis worth? which is answered on a nine-point scale with 5 percent increments rangingfrom 0 to 45 percent and seeks to assess the perceived worth of ones benefits package(pre-testing in the Latvian samples indicated that it was desirable to use increments of2.5 percent ranging from 0 to 25 percent and so these increments were used). It is used asa diagnostic item concerning the effectiveness of benefit communications related toindividuals levels of satisfaction with their benefits, with satisfaction increasing asperceived worth increases. Carraher et al. (2003a, b) found one-month test-retestreliabilities of 0.90 (importance of benefits) to 0.95 (ease of replacement of benefits) forthe three dimensions of attitudes towards benefits. Owing to the differences in the

benefit programs and the dimensional nature of this instrument within the six samplesin the current study, the items shall be used individually. As the instrument is general innature and does not deal with specific benefits, the only modifications typically neededwhen being used internationally include language translation and possible modificationof the increments for the value of the benefits as a percentage of salary.

Pay. Pay levels were taken from organizational records.Gender. It was self-reported by the respondents. Griffeth et al. (2000) found that

males are typically more likely to leave their place of employment than were females.Age. It was self-reported by the respondents. Griffeth et al. (2000) found that

younger employees are typically more likely to voluntarily leave their employmentthan were older employees.

Turnover. All turnover studied was voluntary turnover and was followed over a four

year period time. Employee turnover data was collected from employee records whilebusiness owner turnover was collected through direct observation. In the case of theentrepreneurs the businesses typically survived but the original entrepreneurs no longerran the businesses.

Analyses and resultsPresented in Table AI (Appendix) are correlations between the studys variables.Presented in Table AII (Appendix) are the results of binary logistic regressions for

BJM6,1

30


7/28

the six samples across the four time periods. All but one of the regression equationsis significant at the 0.001 level. The one regression equation not significant at the 0.001level is the equation for Latvian employees at year 3 which was significant at the 0.005level. Looking at Table AII, it appears that attitudes towards benefits were a meaningful

predictor of turnover of both employees and entrepreneurs. Of the 24 regressionequations attitude towards benefits items were significant in 22 of the cases. The twoinstances in which they were not significant included the first year of the Latvianentrepreneurs and the second year for the Estonian entrepreneurs. Attitudes towardsbenefits also had an average incremental contribution beyond compensation and paysatisfaction of 0.112 Cox & Snell R2 and 0.201 Nagelkerke R2 and had the greatestincremental contribution of any of the variables examined. In six of the 12 samples ofemployees both equity and expectancy items were statistically significant but forthe entrepreneurs in two-thirds of the samples only expectancy items were significant.Interestingly, in only one sample of the entrepreneurs (Estonian entrepreneurs inyear 1) were any of the equity items statistically significant predictors of turnover atthe 0.05 level.

Pay satisfaction had an average incremental contribution beyond compensation of0.036 Cox & Snell R2 and 0.062 Nagelkerke R2. Pay satisfaction was a significantpredictor in 13 of the 24 equations. Within the sample of entrepreneurs pay satisfactionwas significant for the Estonians in year 2 and for the Lithuanians in all four years.Within the sample of employees pay satisfaction was significant with the Lithuanians inall four years, with the Estonians in year 2, and with the Latvians in years 2, 3, and 4.The Latvian results are especially unusual as the relationship is negative so thatemployees with higher levels of pay satisfaction are more likely to voluntarily leave theiremployment. Post hoc analyses indicate that in the Latvian sample those who left weremore likely than those staying to be looking for promotional opportunities outside oftheir organization (often seeking to move to Western Europe).

Gender was a significant predictor of turnover in 11 of the 24 regression equationsand had an average incremental contribution beyond the compensation variables(compensation level, pay satisfaction, and attitudes towards benefits) of 0.024 Cox &Snell R2 and 0.045 Nagelkerke R2 across all 24 analyses. For the entrepreneurs genderwas related to turnover in the first year for the Latvian sample and in years 2, 3, and 4for the Estonian sample. For the employees, gender was a significant predictor for theEstonians in all four years, with the Latvians in years 1 and 4 and with the Lithuaniansin year 2. Surprisingly, in all of the cases with the exception of the Lithuanian employeesample the relationship is negative so that females were more likely to leave than weremales. As previously mentioned this is exactly the opposite of what prior research hasfound (Griffeth et al., 2000).

Compensation level was a significant predictor of turnover in 7 of the 24 regressions

and the average contribution of compensation level was 0.038 Cox & Snell R2 and0.063 Nagelkerke R2. Within the entrepreneurial samples, salary was a significantpredictor for the Lithuanian samples in years 2, 3, and 4. Within the employee samples,salary was a significant predictor for the Lithuanian sample for all four years. In allseven cases there was a positive relationship so that those with higher salaries weremore likely to voluntarily leave. Age was a significant predictor of turnover in four ofthe twenty-four regression equations and all were in the employee samples. For agethe average incremental contribution beyond that of the compensation variables

Turnoverprediction

31


8/28

(compensation level, pay satisfaction, and attitudes towards benefits) was 0.012 Cox &Snell R2 and 0.019 Nagelkerke R2. Age was a significant predictor of turnover withinthe first year for the Latvian sample, in the second year for the Estonian sample, andfor the third and fourth years of the Lithuanian sample. For the Latvian employees

younger individuals were more likely to voluntarily leave while in the Estonian andLithuanian samples the older employees were more likely to voluntarily leave.

Overall, the R2s decreased over time for both the employee and entrepreneursamples. The classification rates decreased slightly over time for both. However, theefficacy increased over time for the employees. For instance, in year 1 the differencesbetween the base rate and the classification rate varied for the entrepreneurs from0 (Latvian sample) to 5.1 percent (Lithuanian sample) and with employees from4.4 (Latvian sample) to 7.6 percent (Lithuanian sample). For year 4, the differences were0.5 (Latvian sample) to 5 percent (Estonian sample) for the entrepreneurs but hadincreased in the employee samples with the ranges being from 17.1 percent (Lithuaniansample) to 23 percent (Latvian sample). Looking at the intermediate years the resultsremained relatively flat for the employees but showed a large increase from years 3 to 4from an average of 7.6 percent (year 3) to 19.67 (year 4).

Culturally it appears that in Estonia attitudes towards benefits and demographicvariables should be examined when seeking to understand turnover while in Lithuaniaattitudes towards benefits, compensation, and pay satisfaction should be examined.In Latvia it should be most fruitful to examine attitudes towards benefits. It also appearsthat the results for entrepreneurs and employees are often similar within the countries.Forinstance, pay satisfaction was a significant predictor of turnover for both Lithuanianemployees and entrepreneurs for all four years and gender was a significant predictor ofturnover for Estonians for four years for employees and in all but year 1 for theentrepreneurial sample. Gender was also a significant predictor of turnover for bothgroups of Latvians in year 1. Supporting the first hypothesis attitudes towards benefits,

pay, pay satisfaction, gender, and age were found to be useful as predictors of turnoverfor entrepreneurs and employees from Estonia, Latvia, and Lithuania. Their utilitiesvary from year to year, but combined they are significant beyond the 0.05 level everyyear in every sample. Of the predictor variables, attitudes towards benefits were foundto be the most powerful predictor of turnover. As the ATBS is based upon equity andexpectancy (individuals expectations and valences about benefits) theories thissupports the relationship between expectancy theory, equity theory, employee benefits,and turnover. It would appear that with respect to benefits the theoretical results differbetween entrepreneurs and employees with both equity theory and expectancy theoryplaying a part in benefits predicting turnover among employees. Expectancies aboutbenefits are more significant for the entrepreneurs, providing partial support for thesecond hypothesis.

Discussion, future research and conclusionsBenefits represent a yearly expenditure of over $1 trillion by employers in the USA, over$15,000 per full time employee on average (Milkovich and Newman, 2004). The mostrecent figure indicates the cost of benefits average about 28 percent of totalcompensation costs for small to medium sized businesses in the USA, and can accountfor up to 50 percent of total compensation for other employers (Herz et al., 2000).In Western Europe the cost of employee benefits is comparable to the cost of the same

BJM6,1

32


9/28

benefits in the USA (about 30 percent of pay roll costs for small to medium sizedbusinesses), but a higher proportion of the benefits are statutorily required in Europe(Aschkenasy, 1996). On average, in Western Europe required benefits representapproximately 30 percent of base salary (Aschkenasy, 1996). In Eastern Europe and

Asia these costs are lower, but they may still be substantial (Carraher and Buckley,2005). Employer provided health care and other benefits were first popularized inAmerican businesses over 60 years ago during Second World War as a way ofrewarding employees without violating wage and price controls (Morse, 2004). InEurope employee benefits, such as pensions, trace their roots back even further, at leastto the 1800s due to their retentive effects (Taylor, 2000, p. 247). This research is a directoffshoot of this tradition.

There are several directions in which future research could develop based upon theseand prior findings (Carraher, 2006; Carraher and Buckley, 2005; Carraher et al., 2003a, b;Hart and Carraher, 1995). Thousands of studies have examined job satisfaction and itsconsequences with non-managerial and managerial employees in large-, small-, andmedium-sized businesses alike ( Judge etal., 2001). However, little research has examinedthe relationship between turnover and attitudes towards benefits. One area for futureresearch is replicating this research with other samples within these and other culturesandcountries (Bhanugopan and Fish, 2006; Carraher,2003, 2005; Carraher etal.,2003a,b,2004a, b, c; Richardson, 2006) looking both at cultural variations and variations withincultures as economies change and develop (Alas and Vadi, 2006; Carraher et al., 2006a, b;Huettinger, 2008; Pundziene et al., 2006; Welsh et al., 1993). A second area for researchwould focus on the relationship between satisfaction with pay levels and turnover. Thisresearch could seek to explain why employees satisfied with their pay levels might bemore likely to terminate their employment. Previous research has found a negativerelationship between pay satisfaction and turnover (Griffeth et al., 2000; Williams et al.,2006). Perhaps, within these samples those with higher levels of satisfaction with their

pay may have higher levels of self-esteem and are more willing to seek new employment(Pierce and Gardner, 2004; Robinson et al., 1991). This could be similar to research on therelationship between pay and pay levels: different researchers have found differentrelationships. For instance, Rice et al. (1990) found that absolute salary levels couldexplain around 25 percent of the variance in pay satisfaction. Heneman and Judge (2000)found very slight relationships between pay level and pay satisfaction (r 0.15) as didWilliams et al. (2006), who also found mean rs of 0.25 to 0.27 (corrected r 0.29).Carraher and Buckley (1996) found essentially no relationship between salary and paysatisfaction when controlling for organizational level (rs 0.01, 0.00, and 0.01). It couldprove useful to examine whether the relationships between aspects of compensationsystems and turnover have changed over time just as compensation systems themselveshave changed (Carraher, 1991a, b; Hadlock and Lumer, 1997).

A third area for research that may prove fruitful could be examining the antecedentsand consequences of various facets of attitudes towards benefits for business ownersand employees across cultures. This study addresses general attitudes towardsbenefits in a static multi-dimensional fashion. It is possible that attitudes towardbenefits may be both a static and a dynamic concept. The dynamic portions of theattitudes may be related to turnover in a different fashion than the static ones (Fieldset al., 2005). Additional research could also examine the differential impact specificbenefits might have on turnover (Sturman, 2003; Sturman and Short, 2000). For instance,

Turnoverprediction

33


10/28

Taylor(2000) reviewed 200years of the use of employee pensions forincreased employeeretention. A scale developed by Harris (1993) attempts to measure ten dimensions ofgeneral benefits satisfaction. Balkin and Griffeth (1993) have developed an instrumentwhich seeks to measure attitudes towards five specific benefits in a multi-dimensional

fashion. As seen in the current study, it is likely that different aspects of benefits mayhave varying importance for the prediction of turnover. Factors such as intelligence andreading levels, cognitive complexity, social class, and varying compensation systemcharacteristics could influence individuals conceptualization of benefits and theirusefulness for the prediction of employee and business turnover (Carraher and Buckley,1996; Carraher et al., 2000, 2004a, b, c) as could formal organizational socializationprocesses (Allen, 2006; Buckley et al., 1998, 2002; Carr et al., 2006) or labor mobility(Baruch, 2004; de Luis Carnicer et al., 2004). Other compensation related variables couldalso be investigated in terms of their prediction of turnover such as pay equity (Carraherand Carraher, 2005; Fields et al., 2005; Jaques, 1961), organizational justice (McDowalland Fletcher, 2004), fairness (Edgar and Geare, 2005), pay-for-performance perceptions(Chang and Hahn, 2006), pay system changes (Morrell et al., 2004), household or familyincome rather than personal salary (Adamache and Sloan, 1985; Jones, 1993;Turvey et al., 2009), reasons for working (economic vs non-economic; Carraher et al.,2003a, b), economic conditions, number of levels of organizational hierarchy included inthe sample (Jaques, 1961), and organizational financial instability (Arthaud-day et al.,2006). In regards to consequences, benefits might be useful for influencing individualsgeneral performance (Welsh etal., 1993),hospitality andcustomer service (Carraher etal.,1998; McBride et al., 1997; Welsh and Swerdlow, 1992), organizational commitment(Kazlauskaite et al., 2006) leadership (Tuulik and Alas, 2009) or other organizationallyimportant behaviors (Vadi and Turk, 2009) which could retain employees and customers(Carraher, 2006; Carraher and Buckley, 2005; Kuusik and Varblane, 2009)?

A fourth area for research could be to examine what other individual level variables

might influence the relationship between compensation/benefits and both employee andorganizational turnover. Some possible variables to examine include demographicdifferences within samples such as racial composition, national culture of the sample,and educational attainment; personality, feedback seeking behaviors, and personalorientation towards being innovative (Banzhaf, 2005; Carraher, 1992; Carraher et al.,2006a, b; Duobiene et al., 2007; Gustainiene and Endriulaitiene, 2009; Harvey et al., 2009;Lilly et al., 2006; Smith, 2009). These have all previously been found to be related toemployee turnover and may also be related to organizational turnover for businessowners. It could be useful to examine the optimal time frames for studying therelationships of these variables and turnover as the current research shows that theimpact of variables on turnover can vary when examining different time periods(Carraher, 2006; Carraher and Buckley, 2005; Kammeyer-Mueller et al., 2005).

A fifth area for research could be examining additional underlying reasonsemployees and business owners separate from their positions (Maertz andGriffeth, 2004). In some cases it might be because of desired flexibility (Carraher andWhitely, 1998; Wooden and Warren, 2004), organizational trust (Dietz and Hartog, 2006;Huang and Dastmalchian, 2006) or because of ones perception of job instability in theregion or country (Bockerman, 2004). Dissatisfaction with per capita income, with thegovernment system in place, or dissatisfaction with previous work experiences(Noorderhaven et al., 2004) have all been shown to be related to self-employment

BJM6,1

34


11/28

in cross-country studies (Bockerman, 2004), and could be reasons for employees to leavetheir current positions and seek to start their own businesses. In samples from Easternand Western Europe, Carraher (2006) and Carraher and Buckley (2005) did post hocfollow-ups as to why business owners sought to leave. They found that the self

employed often would leave in order to start what they saw as a potentially moreprofitable business, to open a similar business at a more desirablelocation, or to work forsomeone else at a higher rate of income (often with their business being purchased bytheir new employer). Fields et al. (2005) found substantial differences in the prediction ofturnover based upon the reasons for turnover, the type of job change, and the location ofthe job change (whether within or outside the employing organization). Additionalresearch could further examine the similarities and differences between turnover forbusiness owners and employees. In the current samples the turnover base rates for thebusiness owners were substantially smaller than for the employees. However, post hocconversations with the business owners revealed a growing trend for them toconsider self-employment to be a temporary employment situation until they could findemployment whether through other self-employment or as an employee that paidthem more (Carraher, 2006; Sullivan et al., 2007). The current results also providesupport for the supposition that turnover among employees and employers may besubstantively different.

A common complaint heard from individuals involved in research on theantecedents of turnover and the consequences of compensation and benefit systemsis that the research tends to be atheoretical (Harris, 1993; Judge et al., 2001). While mostresearch is implicitly based on equity or expectancy theories, these theories are notexamined explicitly. As found in the current study there may be differences betweenemployees and entrepreneurs when it comes to which theories play a part in influencingturnover. New theories of compensation and benefits need to be actively developed, andold theories such as Jaques (1961) equity theory should be more explicitly examined in

this type of research using the proper methods (Ajaev et al., 2007; Klentzman et al., 2006;Sethi and Carraher, 1993; Sturman and Carraher, 2007). In the compensation area, Miceliand Lane (1991) and Williams et al. (2008) have provided excellent examples of the typeof work that should be done in the development of new models of compensation andbenefits, but as always more work is necessary.

There are also managerial implications of the current findings. Attitudes towardsbenefits are important for both employees and entrepreneurs alike. Benefits can help toattract and retain employees. As shown here, which aspects of benefits are importantmay vary from employee to employee, across time, and between countries so it would beuseful for employers to regularly survey employees in order to see which aspects ofbenefits are important to the employees and also communicate the value/cost of thebenefits. When it comes to pay and pay satisfaction their importance was less clear than

were the benefits, and their incremental contribution was far lower which wassurprising. Pay and satisfaction with pay are important for attracting employees.However, their usefulness at retaining employees is unclear as their incremental utilitywas roughly 1/3 of the incremental utility of attitudes towards benefits. As seen herecompetent employees who are paid well and satisfied with their pay may be more likelyto feel comfortable seeking employment elsewhere. Thus, as found by MetLife (2003)andDale-Olsen (2006); while pay maybe importantto attract employees, benefitsseemtoplay a more important role when retaining employees as well as attracting employees.

Turnoverprediction

35


12/28

Employers should pay more attention to employee benefits if desiring to retain qualifiedemployees. Both equity and expectancies of benefits should be considered when seekingto retain employees.

Using six samples of employees and business owners, this study has examined the

influence that attitudes towards benefits, pay, gender, age, and pay satisfaction mayhave on turnover. It was found that for the employee samples the classification ratesincreased slightly as compared to base rates over time (e.g. did better the longer the timeperiod included), while for the entrepreneurs the classification rates were relatively flatas compared to base rates, as were the R2 values. For the employee samples the R2

values decreased over time. Directions for future research and managerial implicationsare also suggested with an emphasis on the need for stronger theoretical and historicalframeworks to guide future research.

References

Adamache, K. and Sloan, F. (1985), Fringe benefits: to tax or not to tax, National Tax Journal,Vol. 38 No. 1, pp. 47-64.

Adams, J.S. (1963), Toward an understanding of inequity, Journal of Abnormal and SocialPsychology, Vol. 67, pp. 422-36.

Ajaev, V., Klentzman, J., Sodtke, C. and Stephan, P. (2007), Mathematical modeling of movingcontact lines in heat transfer applications, Microgravity Science and Technology, Vol. 19Nos 3/4, pp. 23-6.

Alas, R. and Vadi, M. (2006), The employees attitudes and their connections with theorganizational culture in the process of change in the Estonian organizations, Baltic

Journal of Management, Vol. 1 No. 1, pp. 49-66.

Allen, D. (2006), Do organizational socialization tactics influence newcomer embeddedness andturnover?, Journal of Management, Vol. 32 No. 2, pp. 237-56.

Arthaud-day, M., Certo, S., Dalton, C. and Dalton, D. (2006), A changing of the guard: executiveand director turnover following corporate financial restatements, Academy of

Management Journal, Vol. 49 No. 6, pp. 1119-36.

Aschkenasy, J. (1996), Who benefits from Europes benefits?, International Business: Strategies for the Global Marketplace, Vol. 10 No. 1, pp. 10-12.

Balkin, D.B. and Griffeth, R.W. (1993), The determinants of employee benefits satisfaction, Journal of Business and Psychology, Vol. 7, pp. 323-39.

Banzhaf, M. (2005), Structural differences in jobturnoverand wage growth by sexand education,unpublished doctoral dissertation, University of North Carolina, Chapel Hill, NC.

Baruch, Y. (2004), The desert generation: lessons and implications for the new era of peoplemanagement, Personnel Review, Vol. 33 No. 2, pp. 241-56.

Bhanugopan, R. and Fish, A. (2006), An empirical investigation of job burnout amongexpatriates, Personnel Review, Vol. 35 No. 4, pp. 449-68.

Bockerman, P. (2004), Perception of job instability in Europe, Social Indictors Research, Vol. 67No. 3, pp. 283-314.

Bowling Green State University (1985), Job Descriptive Index, Bowling Green State University,Bowling Green, OH.

Buckley, M., Fedor, D., Veres, J., Wiese, D. and Carraher, S.M. (1998), Investigating newcomerexpectations and job-related outcomes, Journal of Applied Psychology, Vol. 83, pp. 452-61.

BJM6,1

36


13/28

Buckley, M., Mobbs, T., Mendoza, J., Novicevic, M., Carraher, S.M. and Beu, D. (2002),Implementing realistic job previews and expectation lowering procedures: a fieldexperiment, Journal of Vocational Behavior, Vol. 61 No. 2, pp. 263-78.

Carr, J., Pearson, A., Vest, M. and Boyar, S. (2006), Prior organizational experience, anticipatory

socialization, and employee retention, Journal of Management, Vol. 32 No. 3, pp. 343-59.Carraher, S.M. (1991a), A validity study of the pay satisfaction questionnaire (PSQ),

Educational and Psychological Measurement, Vol. 51, pp. 491-5.

Carraher, S.M. (1991b), On the dimensionality of the pay satisfaction questionnaire,Psychological Reports, Vol. 69, pp. 887-90.

Carraher, S.M. (1992), The effect of individual differences variables on the perceiveddimensionality of compensation satisfaction, unpublished doctoral dissertation,University of Oklahoma, Norman, OK.

Carraher, S.M. (2003), The father of cross-cultural research: an interview with Geert Hofstede, Journal of Applied Management and Entrepreneurship, Vol. 8 No. 2, pp. 97-106.

Carraher, S.M. (2005), An examination of entrepreneurial orientation: a validation study in68 countries in Africa, Asia, Europe, and North America, International Journal of Family

Business, Vol. 2 No. 1, pp. 95-100.

Carraher, S.M. (2006), Attitude towards benefits among SME owners in Eastern Europe:a 30-month study, Global Business and Finance Review, Vol. 11 No. 1, pp. 41-8.

Carraher, S.M. and Buckley, M. (1996), The effect of cognitive complexity on the perceiveddimensionality of the PSQ, Journal of Applied Psychology, Vol. 81, pp. 102-9.

Carraher, S.M. and Buckley, M. (2005), Attitudes towards benefits among SME owners inWestern Europe: an 18-month study, Journal of Applied Management and

Entrepreneurship, Vol. 10 No. 4, pp. 45-57.

Carraher, S.M. and Carraher, S.C. (2005), Felt fair pay of small to medium, sized enterprise (SME)owners in Finland and Latvia: an examination of Jaques equity construct, Journal ofSmall Business Strategy, Vol. 16 No. 1, pp. 1-8.

Carraher, S.M. and Welsh, D.H.B. (2009), Global Entrepreneurship, Kendall Hunt Publishing,Dubuque, IA.

Carraher, S.M. and Whitely, W. (1998), Motivations for work and their influence on pay acrosssix countries, Global Business & Finance Review, Vol. 3, pp. 49-56.

Carraher, S.M., Buckley, M. and Cote, J. (2000), Strategic entrepreneurialism in analysis: globalproblems in research, Global Business & Finance Review, Vol. 5 No. 2, pp. 77-86.

Carraher, S.M., Carraher, S.C. and Whitely, W. (2003a), Global entrepreneurship, income, andwork norms: a seven country study, Academy of Entrepreneurship Journal, Vol. 9 No. 1,pp. 31-42.

Carraher, S.M., Gibson, J. and Buckley, M. (2006a), Compensation satisfaction in the Baltics andthe USA, Baltic Journal of Management, Vol. 1 No. 1, pp. 7-23.

Carraher, S.M., Hart, D. and Carraher, C. (2003b), Attitudes towards benefits amongentrepreneurial employees, Personnel Review, Vol. 32 No. 6, pp. 683-93.

Carraher, S.M., Scott, C. and Carraher, S.C. (2004a), A comparison of polychronicity levelsamong small business owners and non business owners in the US, China, Ukraine, Poland,Hungary, Bulgaria, and Mexico, International Journal of Family Business, Vol. 1 No. 1,pp. 97-101.

Carraher, S.M., Sullivan, S. and Carraher, C. (2004b), Validation of a measure of internationalstress: findings from multinational health service organization professionals, Journal of

Applied Management and Entrepreneurship, Vol. 9 No. 3, pp. 3-21.

Turnoverprediction

37


14/28

Carraher, S.M., Sullivan, S.E. and Crocitto, M. (2008), Mentoring across global boundaries:an empirical examination of home- and host-country mentors on expatriate careeroutcomes, Journal of International Business Studies, Vol. 39 No. 8, pp. 1310-26.

Carraher, S.M., Mulvey, P., Scarpello, V. and Ash, R. (2004c), Pay satisfaction, cognitive

complexity, and global solutions: is a single structure appropriate for everyone?, Journalof Applied Management and Entrepreneurship, Vol. 9 No. 2, pp. 18-33.

Carraher, S.M., Mendoza, J., Buckley, M.R., Schoenfeldt, L. and Carraher, C. (1998), Validation ofan instrument to measure service-orientation, Journal of Quality Management, Vol. 3No. 2, pp. 211-24.

Carraher, S.M., Parnell, J., Carraher, S.C., Carraher, C. and Sullivan, S. (2006b), Customer service,entrepreneurial orientation, and performance: a study in health care organizations inHong Kong, Italy, New Zealand, the United Kingdom, and the USA, Journal of Applied

Management & Entrepreneurship, Vol. 11 No. 4, pp. 33-48.

Carter, R. and Van Auken, H. (1990), A comparison of small business and large corporations:interrelationships among position statement accounts, Journal of Small Business and

Entrepreneurship, Vol. 2, pp. 73-80.

Carter, R. and Van Auken, H. (2005), Bootstrap financing and owners perception of theirbusiness constraints and opportunities, Entrepreneurship & Regional Development,Vol. 17 No. 2, pp. 129-44.

Chang, E. and Hahn, J. (2006), Does pay-for-performance enhance perceived distributive justicefor collectivistic employees?, Personnel Review, Vol. 35 No. 4, pp. 397-412.

Dale-Olsen, H. (2006), Wages, fringe benefits and worker turnover, Labour Economics, Vol. 13No. 1, pp. 87-105.

de Luis Carnicer, M.P., Sanchez, A.M., Perez, M.P. and Jimenez, M.J.V. (2004), Work-familyconflict in a southern European country: the influence of job-related and non-relatedfactors, Journal of Managerial Psychology, Vol. 19 No. 5, pp. 466-89.

Dietz, G. and Hartog, D. (2006), Measuring trust inside organizations, Personnel Review, Vol. 35

No. 5, pp. 557-88.

DiFiore, B. (2000), Small business no longer has to mean small benefits, Employee BenefitsJournal, Vol. 25 No. 3, pp. 9-13.

Duobiene, J., Gavenas, J., Anskaitis, A. and Pundziene, A. (2007), Applying indicators oforientation to innovations, potential of growth and strategic objectives to explaincorporate entrepreneurship: case study of the three Finnish companies, Problems and

Perspectives in Management, Vol. 5 No. 3, pp. 31-43.

Edgar, F. and Geare, A. (2005), HRM practice and employee attitudes: different measures different results, Personnel Review, Vol. 34 No. 5, pp. 534-49.

Fields, D., Dingman, M., Roman, P. and Blum, T. (2005), Exploring predictors of alternative jobchanges, Journal of Occupational & Organizational Psychology, Vol. 78, pp. 63-82.

Gaiduk, R., Gaiduk, J. and Fields, D. (2009), Limiting the brain drain: determinants of employeeorganizational attachment in Lithuania, Baltic Journal of Management, Vol. 4 No. 2,pp. 149-68.

Gerhart, B. and Rynes, S. (2003), Compensation: Theory, Evidence, and Strategic Implications,Sage, Thousand Oaks, CA.

Griffeth, R., Hom, P. and Gaertner, S. (2000), A meta-analysis of antecedents and correlates ofemployee turnover: update, moderator tests, and research implications for the nextmillennium, Journal of Management, Vol. 26 No. 3, pp. 463-88.

BJM6,1

38


15/28

Gustainiene, L. and Endriulaitiene, A. (2009), Job satisfaction and subjective health among salesmanagers, Baltic Journal of Management, Vol. 4 No. 1, pp. 51-65.

Hadlock, C. and Lumer, G. (1997), Compensation, turnover, and top management incentives:historical evidence, Journal of Business, Vol. 70 No. 2, pp. 153-87.

Harris, M. (1993), Reactions to employee benefits: development and refinement of a measure, IRRA 45th Proceedings of the Industrial Relations Association, pp. 91-8.

Hart, D. (1990), The effects of perceived reward contingencies, recognition, and benefit equity onturnover functionality, unpublished PhD dissertation,Texas A&MUniversity, Austin, TX.

Hart, D. and Carraher, S.M. (1995), The development of an instrument to measure attitudestowards benefits, Educational and Psychological Measurement, Vol. 55, pp. 498-502.

Harvey, M., McIntyre, N., Thompson, J. and Moeller, M. (2009), Mentoring global femalemanagers in the global marketplace: traditional, reverse, and reciprocal mentoring,

International Journal of Human Resource Management, Vol. 20 No. 6, pp. 1344-61.

Heise, D. (1969), Some methodological issues in semantic differential research, PsychologicalBulletin, Vol. 72 No. 6, pp. 406-22.

Heneman, H. and Judge, T. (2000), Compensation attitudes: a review and recommendations forfuture research, in Rynes, S.L. and Gerhart, B. (Eds), Compensation in Organizations:

Progress and Prospects, Jossey-Bass, San Francisco, CA, pp. 61-103.

Heneman, H.G. III and Berkley, R. (1999), Applicant attraction practices and outcomes amongsmall businesses, Journal of Small Business Management, Vol. 37, pp. 53-74.

Herz, D., Meisenheimer, J. and Weinstein, H. (2000), Health and retirement benefits: data fromtwo BLS surveys, Monthly Labor Review, Vol. 123 No. 3, pp. 3-20.

Hoobler, J. and Johnson, N. (2004), An analysis of current human resource managementpublications, Personnel Review, Vol. 33 No. 6, pp. 665-76.

Huang, H.J. and Dastmalchian, A. (2006), Implications of trust and distrust for organizations: roleof customer orientation in a four-nation study, Personnel Review, Vol. 35 No. 4, pp. 361-77.

Huettinger, M. (2008), Cultural dimensions in business life: Hofstedes indices for Latvia andLithuania, Baltic Journal of Management, Vol. 3 No. 3, pp. 359-76.

Jaques, E. (1961), Equitable Payment, Wiley, New York, NY.

Jones, C.B. (1993), A human capital approach to modelling registered nurses wages andturnover/retention behaviors, unpublished doctoral dissertation, University ofSouth Carolina, Columbia, SC.

Joo, S. (2000), Improving employee productivity: the role of financial counseling and education, Journal of Employment Counseling, Vol. 37, pp. 2-15.

Judge, T., Thoresen, C., Bono, J. and Patton, G. (2001), The job satisfaction-job performancerelationship: a qualitative and quantitative review, Psychological Bulletin, Vol. 127 No. 3,pp. 376-407.

Kakabadse, N., Kakabadse, A. and Kouzmin, A. (2004), Directors remuneration: the need for a

geo-political perspective, Personnel Review, Vol. 33 No. 5, pp. 561-82.Kammeyer-Mueller, J., Wanberg, C., Glomb, T. and Ahlburg, D. (2005), The role of temporal

shifts in turnover processes: its about time, Journal of Applied Psychology, Vol. 90 No. 4,pp. 644-58.

Kazlauskaite, R., Buciuniene, I. and Turauskas, L. (2006), Building employee commitment in thehospitality industry, Baltic Journal of Management, Vol. 1 No. 3, pp. 300-14.

Kessler, I., Heron, P. and Gagnon, S. (2006), The fragmentation of pay determination in theBritish civil service: a union member perspective,Personnel Review, Vol. 35 No. 1,pp. 6-28.

Turnoverprediction

39


16/28

Klentzman, J., Markos, M. and Ajaev, V. (2006), The effect of evaporation on fingeringinstabilities, paper presented at the American Physical Society 59th Annual Meeting,November 19-21.

Konopaske, R. and Werner, S. (2005), US managers willingness to accept a global assignment:

do expatriate benefits and assignment length make a difference?, International Journal ofHuman Resource Management, Vol. 16 No. 7, pp. 1159-75.

Krau, E. (1981), Turnover analysis and prediction from a career developmental point of view,Personnel Psychology, Vol. 34 No. 4, pp. 771-90.

Kuusik, A. and Varblane, U. (2009), How to avoid customers leaving: the case of the Estoniantelecommunications industry, Baltic Journal of Management, Vol. 4 No. 1, pp. 66-79.

Labatmediene, L., Endriulaitiene, A. and Gustainiene, L. (2007), Individual correlates oforganizational commitment and intention to leave the organization, Baltic Journal of

Management, Vol. 2 No. 2, pp. 196-212.

Lakis, J. (2009), Social conflicts and the culture of cooperation in transitional society, Baltic Journal of Management, Vol. 4 No. 2, pp. 206-20.

Lilly, J., Duffy, J.A. and Virick, M. (2006), A gender-sensitive study of McClellands needs, stress,and turnover intent with work-family conflict, Women in Management Review, Vol. 21No. 8, pp. 662-80.

Lunnan, R. and Traavik, L. (2009), Is the standardization of human resource practices perceivedas fair across national cultures? The cases of China, Lithuania, and Norway,Baltic Journalof Management, Vol. 4 No. 2, pp. 127-48.

McBride, A., Mendoza, J. and Carraher, S.M. (1997), Development of a biodata index to measureservice-orientation, Psychological Reports, Vol. 81, pp. 1395-407.

McComas, H. (1922), A measure of the attention, Journal of Experimental Psychology, Vol. 5No. 1, pp. 1-18.

McDowall, A. and Fletcher, C. (2004), Employee development: an organizational justiceperspective, Personnel Review, Vol. 33 No. 1, pp. 8-29.

Maertz, C. and Griffeth, R. (2004), Eight motivational forces and voluntary turnover: a theoreticalsynthesis with implications for research,Journal of Management, Vol. 30 No. 5, pp. 667-83.

Mangel, R. and Useem, M. (2000), The strategic role of gainsharing, Journal of Labor Research,Vol. 21, pp. 327-43.

MetLife (2003), The MetLife Study of Employee Benefits Trends, MetLife, New York, NY.

Meyer, C., Mukerjee, S. and Sestero, A. (2001), Work-family benefits: which ones maximizeprofits?, Journal of Managerial Issues, Vol. 13, pp. 28-44.

Miceli, M.P. and Lane, M.C. (1991), Antecedents of pay satisfaction: a review and extension, inFerris, G.R. and Rowland, K.M. (Eds), Research in Personnel and Human Resources

Management, Vol. 9, JAI Press, Greenwich, CT, pp. 235-309.

Milkovich, G. and Newman, J. (2004), Compensation, 8th ed., McGraw-Hill Irwin, Homewood, IL.

Morrell, K., Loan-Clarke, J. and Wilkinson, A. (2004), Organizational change and employeeturnover, Personnel Review, Vol. 33 No. 2, pp. 161-73.

Morse, D. (2004), Rethinking employeebenefits: Part I,Benefits Law Journal,Vol.17No.2,pp.1-4.

Noorderhaven, N., Thurik, R., Wennekers, S. and Stel, A. (2004), The role of dissatisfaction andper capita income in explaining self-employment across 15 European countries,

Entrepreneurship Theory & Practice, Vol. 29, pp. 447-66.

Ortqvist, D., Drnovsek, M. and Wincent, J. (2007), Entrepreneurs coping with challenging roleexpectations, Baltic Journal of Management, Vol. 2 No. 3, pp. 288-304.

BJM6,1

40


17/28

Pierce, J. and Gardner, D. (2004), Self-esteem within the work and organizational context:a review of the organization-based self-esteem literature, Journal of Management, Vol. 30No. 5, pp. 591-622.

Pohlen, T. and La Londe, B. (1994), Implementing activity based costing (ABC) in logistics,

Journal of Business Logistics, Vol. 15 No. 2, pp. 1-23.Pundziene, A. and Duobiene, J. (2006), CEOs entrepreneurship in relation to reaction to

organizational change, Engineering Economics, Vol. 47 No. 2, pp. 91-8.

Pundziene, A., Kundrotas, V. and Lydeka, Z. (2006), Management challenges in rapidly growingLithuanian enterprises, Baltic Journal of Management, Vol. 1 No. 1, pp. 34-48.

Rice, R.W., Phillips, S.M. and McFarlin, D.B. (1990), Multiple discrepancies and paysatisfaction, Journal of Applied Psychology, Vol. 75, pp. 386-93.

Richardson, J. (2006), Self-directed expatriation: family matters,Personnel Review, Vol.35 No. 4,pp. 469-86.

Robinson, P., Stimpson, D., Huefner, J. and Hunt, H. (1991), An attitude approach to the predictionof entrepreneurship, Entrepreneurship Theory & Practice, Vol. 15 No. 4, pp. 13-31.

Roolaht, T. (2006), The companys involvement in international networks as an entrepreneurialdecision, Baltic Journal of Management, Vol. 1 No. 1, pp. 102-15.

Rotter, J.B. (1954), Social Learning and Clinical Psychology, Prentice-hall, New York, NY.

Scarpello, V. and Carraher, S.M. (2008), Are pay satisfaction and pay fairness the sameconstruct? A cross-country examination among the self-employed in Latvia, Germany, theUK, and the USA, Baltic Journal of Management, Vol. 3 No. 1, pp. 23-39.

Sethi, V. and Carraher, S.M. (1993), Developing measures for assessing the organizationalimpact of information technology: a comment on Mahmood and Soons paper, DecisionSciences, Vol. 24, pp. 867-77.

Simmons, J. (2001), Flexible benefits for small employers, Journal of Accountancy, Vol. 191,pp. 37-41.

Smith, C. (2009), Moral judgment: a comparison of Latvian and US business persons, Baltic Journal of Management, Vol. 4 No. 2, pp. 188-205.

Smith, P., Kendall, L. and Hulin, C. (1969), The Measurement of Satisfaction in Work andRetirement: A Strategy for the Study of Attitudes, Rand McNally, Chicago, IL.

Steel, P. and Konig, C. (2006), Integrating theories of motivation, Academy of ManagementReview, Vol. 31 No. 4, pp. 889-913.

Sturman, M. (2003), Searching for the inverted U-shaped relationship between time andperformance: meta-analyses of the experience/performance, tenure/performance, andage/performance relationships, Journal of Management, Vol. 29 No. 5, pp. 609-40.

Sturman, M. and Short, J. (2000), Lump-sum bonus satisfaction: testing the construct validity ofa new pay satisfaction dimension, Personnel Psychology, Vol. 53, pp. 673-700.

Sturman, M., Trevor, C., Boudreau, J. and Gerhart, B. (2003), Is it worth it to win the talent war?Evaluating the utility of performance-based pay, Personnel Psychology, Vol. 56,pp. 997-1035.

Sturman, M.C. and Carraher, S. (2007), Using a random-effects model to test differingconceptualizations of multidimensional constructs, Organizational Research Methods,Vol. 10 No. 1, pp. 108-35.

Sullivan, S.E., Forret, M.L., Carraher, S.M. and Mainiero, L.A. (2009), Using the Kaleidoscopecareer model to examine generational differences in work attitudes, Career Development

International, Vol. 14 No. 3, pp. 284-302.

Turnoverprediction

41


18/28

Sullivan, S.E., Forret, M.L., Mainiero, L.A. and Terjesen, S. (2007), What motivates entrepreneurs?An exploratory study of the Kaleidoscope career model and entrepreneurship, Journal of

Applied Management and Entrepreneurship, Vol. 12 No. 4, pp. 4-19.

Taylor, S. (2000), Occupational pensions and employee retention: debate and evidence,

Employee Relations, Vol. 22 No. 3, pp. 246-59.Tolman, E. (1932), Purposive Behavior in Animals and Men, Appleton-Century-Crofts,

New York, NY.

Turk, K. (2008), Performance appraisal and the compensation of academic staff in theUniversity of Tartu, Baltic Journal of Management, Vol. 3 No. 1, pp. 40-54.

Turvey, A., Knight, J. and Wosnitza, B. (2009), Regional economic indicators: a focus onhousehold indicators, Economics & Labour Market Review, Vol. 3 No. 5, pp. 55-68.

Tuulik, K. and Alas, R. (2009), Leadership in transformational Estonia, Baltic Journal ofManagement, Vol. 4 No. 2, pp. 169-87.

Vadi, M. and Turk, K. (2009), Behavior patterns in Estonian enterprises from the perspective ofthe value chain, Baltic Journal of Management, Vol. 4 No. 1, pp. 34-50.

Vilma, Z. and Egle, K. (2007), Improving motivation among health care workers in privatehealth care organizations: a perspective of nursing personnel, Baltic Journal ofManagement, Vol. 2 No. 2, pp. 213-24.

Vroom, V.H. (1964), Work and Motivation, Wiley, New York, NY.

Welsh, D.H.B. and Pendleton, Y. (2006), Direct selling worldwide: the Mary Kay Cosmeticsstory, International Journal of Family Business, Vol. 3, pp. 67-74.

Welsh, D.H.B. and Swerdlow, S. (1992), Hospitality Russian style: nine communicationchallenges, Cornell Hotel & Restaurant Administration Quarterly, Vol. 33 No. 6, pp. 64-72.

Welsh, D.H.B., Sommer, S. and Birch, N. (1993), Changing performance among Russian retailworkers: effectively transferring American management techniques, Journal ofOrganizational Change Management, Vol. 6 No. 2, pp. 34-50.

Williams, M., McDaniel, M. and Nguyen, N. (2006), A meta-analysis of the antecedents and

consequences of pay level satisfaction, Journal of Applied Psychology, Vol. 91 No. 2,pp. 392-413.

Williams, M.L., Brower, H.H., Ford, L.R., Williams, L.J. and Carraher, S.M. (2008),A comprehensive model and measure of compensation satisfaction, Journal ofOccupational & Organizational Psychology, Vol. 81 No. 4, pp. 639-68.

Wooden, M. and Warren, D. (2004), Non-standard employment and job satisfaction: evidencefrom the HILDA survey, Journal of Industrial Relations, Vol. 46 No. 3, pp. 275-97.

Zidonis, Z. (2007), Entrepreneurial internationalization: a case study of Libra company, Baltic Journal of Management, Vol. 2 No. 3, pp. 273-87.

Corresponding author

Shawn M. Carraher can be contacted at: [email protected]

To purchase reprints of this article please e-mail: [email protected] visit our web site for further details: www.emeraldinsight.com/reprints

BJM6,1

42


19/28

Appendix

Country

Year1

turnover

Year2

turnover

Year3

turnover

Year4

turnover

ATBS1

ATBS2

ATBS3

ATBS4

AT

BS5

ATBS6

Pay

satisfaction

Salary

Age

Sex

Estonia

Year1

turnover

Pearson

correlation

1

0.3

02

0.1

80

0.5

04

2

0.1

99

0.1

00

0.1

56

2

0.2

24

20

.003

0.0

22

0.0

32

2

0.1

46

2

0.06

4

2

0.2

41

Sig.

(two-ta

iled)

0.0

02

0.0

68

0.0

00

0.0

46

0.3

14

0.1

15

0.0

23

0

.974

0.8

26

0.7

50

0.1

41

0.51

9

0.0

15

Year2

turnover

Pearson

correlation

0.2

05

1

0.7

13

0.6

12

0.1

93

0.2

05

2

0.0

32

0.1

19

20

.066

2

0.0

77

0.3

21

0.0

44

0.07

8

2

0.0

94

Sig.

(two-ta

iled)

0.0

11

0.0

00

0.0

00

0.0

54

0.0

38

0.7

48

0.2

33

0

.509

0.4

42

0.0

01

0.6

61

0.43

3

0.3

49

Year3

turnover

Pearson

correlation

0.0

54

0.6

83

1

0.8

58

0.0

97

0.0

91

0.1

97

0.1

02

20

.014

2

0.0

34

0.1

41

2

0.0

17

2

0.06

8

2

0.1

52

Sig.

(two-ta

iled)

0.5

10

0.0

00

0.0

00

0.3

33

0.3

58

0.0

46

0.3

06

0

.891

0.7

34

0.1

54

0.8

66

0.49

8

0.1

26

Year4

turnover

Pearson

correlation

0.4

21

0.5

64

0.8

26

1

2

0.0

26

0.0

91

0.3

06

2

0.0

53

0

.015

0.0

41

0.0

65

2

0.0

80

2

0.09

1

2

0.2

43

Sig.

(two-ta

iled)

0.0

00

0.0

00

0.0

00

0.7

93

0.3

58

0.0

02

0.5

95

0

.877

0.6

84

0.5

13

0.4

20

0.36

0

0.0

14

ATBS1

Pearson

correlation

2

0.2

74

0.3

19

0.1

89

0.0

04

1

0.5

19

2

0.1

43

0.3

44

20

.060

0.1

29

0.1

17

0.1

11

2

0.00

3

2

0.0

24

Sig.

(two-ta

iled)

0.0

01

0.0

00

0.0

19

0.9

60

0.0

00

0.1

53

0.0

00

0

.552

0.1

97

0.2

42

0.2

68

0.97

9

0.8

15

ATBS2

Pearson

correlation

0.1

11

0.2

90

0.1

19

0.1

25

0.4

99

1

2

0.2

05

0.1

97

20

.312

0.2

98

0.1

82

0.0

74

0.11

2

2

0.0

18

Sig.

(two-ta

iled)

0.1

71

0.0

00

0.1

44

0.1

24

0.0

00

0.0

38

0.0

47

0

.001

0.0

02

0.0

65

0.4

56

0.26

1

0.8

60

ATBS3

Pearson

correlation

0.1

92

2

0.1

51

0.1

73

0.3

38

2

0.2

49

2

0.2

86

1

2

0.1

33

0

.216

0.0

26

2

0.1

61

2

0.0

48

2

0.20

1

2

0.1

87

Sig.

(two-ta

iled)

0.0

17

0.0

62

0.0

32

0.0

00

0.0

02

0.0

00

0.1

79

0

.029

0.7

92

0.1

03

0.6

32

0.04

2

0.0

60

ATBS4

Pearson

correlation

2

0.3

05

0.1

87

0.1

97

2

0.0

24

0.4

61

0.1

70

2

0.1

62

1

20

.068

0.1

01

2

0.0

81

0.0

60

2

0.05

6

0.1

39

Sig.

(two-ta

iled)

0.0

00

0.0

21

0.0

14

0.7

73

0.0

00

0.0

35

0.0

46

0

.495

0.3

12

0.4

16

0.5

47

0.57

4

0.1

64

ATBS5

Pearson

correlation

2

0.0

54

2

0.1

28

2

0.0

25

0.0

10

2

0.0

57

2

0.4

05

0.2

39

0.0

34

1

2

0.0

95

0.0

15

0.0

50

0.12

3

2

0.3

41

Sig.

(two-ta

iled)

0.5

07

0.1

15

0.7

57

0.9

04

0.4

84

0.0

00

0.0

03

0.6

81

0.3

38

0.8

83

0.6

15

0.21

6

0.0

00

(continued)

Table AI.Intercorrelations

Turnoverprediction

43


20/28

Country

Year1

turnover

Year2

turnover

Year3

turnover

Year4

tur

nover

ATBS1

ATBS2

ATBS3

ATBS4

ATBS5

ATBS6

Pay

satisfaction

Salary

Age

Sex

ATBS6

Pearson

co

rrelation

0.0

00

2

0.0

55

2

0.0

20

0.0

64

0.1

55

0.2

88

2

0.0

10

2

0.0

06

2

0.1

40

1

2

0.0

36

0.0

09

0.0

48

0.0

56

Si

g.

(two-tailed)

0.9

99

0.5

00

0.8

02

0.4

31

0.0

56

0.0

00

0.8

98

0.9

38

0.0

83

0.7

21

0.9

27

0.6

28

0.5

74

Pay

satisfaction

Pearson

co

rrelation

2

0.0

12

0.3

67

0.1

27

0.0

20

0.2

31

0.2

57

2

0.3

02

0.0

41

2

0.0

35

2

0.0

95

1

0.2

91

0.1

31

2

0.0

14

Si

g.

(two-tailed)

0.8

79

0.0

00

0.1

18

0.8

03

0.0

04

0.0

01

0.0

00

0.6

11

0.6

68

0.2

43

0.0

03

0.1

87

0.8

93

Salary

Pearson

co

rrelation

2

0.2

21

0.1

46

0.0

35

2

0.0

71

0.2

39

0.2

09

2

0.2

57

0.0

53

2

0.0

43

0.1

84

0.2

65

1

0.5

19

0.1

06

Si

g.

(two-tailed)

0.0

06

0.0

72

0.6

69

0.3

81

0.0

03

0.0

10

0.0

01

0.5

13

0.5

97

0.0

23

0.0

01

0.0

00

0.2

88

Age

Pearson

co

rrelation

2

0.1

24

0.1

79

2

0.0

29

2

0.0

71

0.0

76

0.1

49

2

0.3

65

2

0.0

79

0.0

62

0.1

84

0.1

71

0.6

45

1

0.2

38

Si

g.

(two-tailed)

0.1

27

0.0

27

0.7

26

0.3

84

0.3

53

0.0

66

0.0

00

0.3

30

0.4

46

0.0

22

0.0

35

0.0

00

0.0

16

Sex

Pearson

co

rrelation

2

0.2

98

2

0.0

99

2

0.1

64

2

0.3

03

0.0

00

2

0.0

42

2

0.2

72

0.0

88

2

0.2

77

0.0

76

0.0

69

0.2

56

0.3

51

1

Si

g.

(two-tailed)

0.0

00

0.2

25

0.0

43

0.0

00

0.9

98

0.6

04

0.0

01

0.2

81

0.0

01

0.3

50

0.3

94

0.0

01

0.0

00

LithuaniaYear1

turnover

Pearson

co

rrelation

1

0.6

58

0.5

26

0.6

09

0.2

10

0.1

30

0.0

24

0.0

89

0.0

17

2

0.1

84

0.2

18

2

0.1

202

0.1

42

2

0.1

48

Si

g.

(two-tailed)

0.0

00

0.0

00

0.0

00

0.0

29

0.1

78

0.8

05

0.3

58

0.8

58

0.0

60

0.0

23

0.2

15

0.1

47

0.1

24

Year2

turnover

Pearson

co

rrelation

0.6

18

1

0.8

08

0.7

79

0.0

89

0.1

08

2

0.0

44

0.0

34

0.1

52

2

0.1

51

0.2

77

2

0.2

092

0.0

97

2

0.0

40

Si

g.

(two-tailed)

0.0

00

0.0

00

0.0

00

0.3

60

0.2

63

0.6

51

0.7

29

0.1

16

0.1

24

0.0

04

0.0

29

0.3

23

0.6

83

Year3

turnover

Pearson

co

rrelation

0.4

61

0.7

72

1

0.9

65

0.1

52

0.0

68

2

0.0

38

0.1

07

0.0

53

2

0.0

81

0.1

37

2

0.2

642

0.1

06

2

0.0

39

Si

g.

(two-tailed)

0.0

00

0.0

00

0.0

00

0.1

15

0.4

80

0.6

94

0.2

70

0.5

86

0.4

12

0.1

59

0.0

06

0.2

80

0.6

84

Year4

turnover

Pearson

co

rrelation

0.5

59

0.7

38

0.9

55

1

0.1

51

0.0

71

2

0.0

20

0.0

88

0.0

37

2

0.1

14

0.1

07

2

0.2

442

0.0

90

2

0.0

60

Si

g.

(two-tailed)

0.0

00

0.0

00

0.0

00

0.1

19

0.4

64

0.8

37

0.3

62

0.7

05

0.2

46

0.2

72

0.0

10

0.3

64

0.5

35

(continued)

Table AI.

BJM6,1

44


21/28

Country

Year1

turnover

Year2

turnover

Year3

turnover

Y

ear4

turnover

ATBS1

ATBS2

ATBS3

ATBS4

ATBS5

ATBS6

Pay

satisfaction

Salary

Age

Sex

ATBS1

Pearson

co

rrelation

0.2

93

0.1

01

0.2

00

0.1

98

1

0.6

36

2

0.0

92

0.4

75

2

0.2

15

0.2

38

0.1

79

2

0.0

71

0.0

09

0.1

41

Sig.

(two-tailed)

0.0

00

0.2

27

0.0

15

0.0

16

0.0

00

0.3

42

0.0

00

0.0

25

0.0

15

0.0

65

0.4

66

0.9

28

0.1

46

ATBS2

Pearson

co

rrelation

0.1

91

0.1

55

0.0

86

0.0

90

0.6

14

1

2

0.1

70

0.4

98

2

0.2

44

0.0

85

0.1

37

2

0.0

92

0.0

34

0.0

76

Sig.

(two-tailed)

0.0

21

0.0

62

0.3

02

0.2

80

0.0

00

0.0

77

0.0

00

0.0

11

0.3

87

0.1

59

0.3

40

0.7

30

0.4

30

ATBS3

Pearson

co

rrelation

0.0

39

2

0.0

60

2

0.0

52

2

0.0

24

2

0.0

87

2

0.1

72

1

0.0

27

0.0

11

2

0.0

98

2

0.3

40

0.0

292

0.1

16

2

0.1

96

Sig.

(two-tailed)

0.6

42

0.4

73

0.5

31

0.7

73

0.2

98

0.0

38

0.7

82

0.9

12

0.3

22

0.0

00

0.7

61

0.2

37

0.0

41

ATBS4

Pearson

co

rrelation

0.1

21

0.0

25

0.1

47

0.1

14

0.5

29

0.5

16

0.0

11

1

2

0.2

99

0.0

72

2

0.0

95

0.0

26

0.0

56

0.1

50

Sig.

(two-tailed)

0.1

46

0.7

65

0.0

78

0.1

71

0.0

00

0.0

00

0.8

92

0.0

00

0.3

85

0.2

53

0.7

56

0.5

02

0.1

20

ATBS5

Pearson

co

rrelation

0.0

17

0.2

29

0.0

72

0.0

45

2

0.2

41

2

0.2

04

0.1

59

2

0.2

99

1

2

0.0

60

2

0.0

55

2

0.1

052

0.0

99

2

0.3

32

Sig.

(two-tailed)

0.8

37

0.0

05

0.3

89

0.5

92

0.0

03

0.0

14

0.0

55

0.0

00

0.4

74

0.5

11

0.2

09

0.2

33

0.0

00

ATBS6

Pearson

co

rrelation

2

0.2

93

2

0.2

53

0.0

01

2

0.0

55

0.2

35

0.0

26

2

0.0

95

0.0

72

2

0.0

60

1

2

0.1

19

2

0.0

682

0.0

36

0.1

89

Sig.

(two-tailed)

0.0

00

0.0

02

0.9

86

0.5

09

0.0

04

0.7

52

0.2

55

0.3

85

0.4

74

0.1

53

0.4

12

0.6

70

0.0

22

Pay

satisfaction

Pearson

co

rrelation

0.3

10

0.4

06

0.1

85

0.1

35

0.2

03

0.1

63

2

0.3

40

2

0.0

95

2

0.0

55

2

0.1

19

1

0.0

90

0.0

41

0.1

59

Sig.

(two-tailed)

0.0

00

0.0

00

0.0

26

0.1

04

0.0

14

0.0

50

0.0

00

0.2

53

0.5

11

0.1

53

0.2

80

0.6

26

0.0

55

Salary

Pearson

co

rrelation

2

0.1

47

2

0.2

86

2

0.3

77

2

0.3

42

2

0.0

67

2

0.1

05

2

0.0

35

0.0

26

2

0.1

05

2

0.0

68

0.0

90

1

0.6

41

0.2

36

Sig.

(two-tailed)

0.0

76

0.0

00

0.0

00

0.0

00

0.4

19

0.2

09

0.6

73

0.7

56

0.2

09

0.4

12

0.2

80

0.0

00

0.0

04

Age

Pearson

co

rrelation

2

0.2

15

2

0.1

39

2

0.1

55

2

0.1

25

2

0.0

58

0.0

13

2

0.1

30

0.0

56

2

0.0

99

2

0.0

36

0.0

41

0.6

41

1

0.2

84

Sig.

(two-tailed)

0.0

09

0.0

93

0.0

62

0.1

32

0.4

84

0.8

74

0.1

18

0.5

02

0.2

33

0.6

70

0.6

26

0.0

00

0.0

01

(continued)

Table AI.

Turnoverprediction

45


22/28

Country

Year1

turnover

Year2

turnover

Year3

turnover

Year4

tur

nover

ATBS1

ATBS2

ATBS3

ATBS4

ATBS5

ATBS6

Pay

satisfaction

Salary

Age

Sex

Sex

Pearson

co

rrelation

2

0.2

23

2

0.0

52

2

0.0

51

2

0.0

86

0.1

10

0.0

69

2

0.2

08

0.1

02

2

0.2

84

0.1

89

0.1

59

0.2

36

0.2

84

1

Sig.

(two-tailed)

0.0

07

0.5

33

0.5

40

0.3

00

0.1

85

0.4

05

0.0

12

0.2

23

0.0

01

0.0

22

0.0

55

0.0

04

0.0

01

Latvia

Year1

turnover

Pearson

co

rrelation

1

0.3

01

0.2

29

0.5

57

2

0.0

03

0.0

13

0.0

10

2

0.0

52

2

0.0

08

2

0.0

33

0.0

68

2

0.1

122

0.3

06

2

0.2

34

Sig.

(two-tailed)

0.0

00

0.0

00

0.0

00

0.9

66

0.8

44

0.8

81

0.4

23

0.9

02

0.6

11

0.2

96

0.0

93

0.0

00

0.0

00

Year2

turnover

Pearson

co

rrelation

0.1

02

1

0.8

20

0.6

93

0.0

13

0.0

88

0.0

47

2

0.0

84

0.1

18

2

0.0

59

0.0

70

0.0

72

0.0

50

2

0.0

28

Sig.

(two-tailed)

0.2

02

0.0

00

0.0

00

0.8

37

0.1

73

0.4

61

0.1

95

0.0

66

0.3

60

0.2

86

0.2

83

0.5

36

0.6

73

Year3

turnover

Pearson

co

rrelation

2

0.0

03

0.7

72

1

0.8

45

2

0.0

09

0.1

07

0.0

50

2

0.0

35

0.1

36

2

0.0

02

0.0

20

0.0

81

0.0

59

2

0.0

06

Sig.

(two-tailed)

0.9

70

0.0

00

0.0

00

0.8

86

0.0

96

0.4

34

0.5

84

0.0

34

0.9

75

0.7

59

0.2

23

0.4

66

0.9

30

Year4

turnover

Pearson

co

rrelation

0.3

81

0.5

74

0.7

44

1

2

0.0

45

0.0

54

0.0

86

2

0.0

66

0.1

21

2

0.0

29

2

0.0

37

0.0

13

0.0

45

2

0.1

16

Sig.

(two-tailed)

0.0

00

0.0

00

0.0

00

0.4

89

0.4

02

0.1

79

0.3

06

0.0

60

0.6

60

0.5

72

0.8

51

0.5

77

0.0

79

ATBS1

Pearson

co

rrelation

2

0.0

37

0.1

44

0.0

95

0.0

19

1

0.5

33

2

0.1

40

0.2

51

2

0.2

09

0.2

71

0.2

06

0.0

572

0.0

58

0.0

74

Sig.

(two-tailed)

0.6

42

0.0

72

0.2

38

0.8

11

0.0

turnover prediction plz read

Documents