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Feeling I cannot record all the time I spend on a specific work, project, or job assignment

(N = 236) Variable L abel

No. o f item s Cronbach Alpha Theoretical

range A ctual range M edian M ean

S td

D ev Skewness K u rtosis

Actual Performance

Rating® AP 1 - 1 -5 2 - 5 3.00 3.49 .72 .08 -.25

Effort EFF 1 - 1 - 7 2 - 7 6.00 5.49 .99 -.35 -.09

Equity & Fairness

Perception EFP 4 .80 1 -7 1 - 7 4.40 4.34 1.18 -.38 -.15

Goal Commitment GC 3 .67 1 - 7 2.33 - 7 5.33 5.31 .88 - A l .16

Goal Difficulty GD 1 - 1 - 7 1 - 7 4.00 3.97 1.32 .01 -.46

Interactive Use Of

Control Systems ICS 4 .86 1 - 7 1 - 7 4.50 4.44 1.23 -.44 -.21

Intention To

Turnover IT 1 - 1 - 7 1 - 7 3.00 2.96 1.65 .93 .23

Job Related Tension JRT 4 .69 1 - 5 1.5-5 3.25 3.21 .672 .19 -.12

Job Satisfaction JS 1 - 1 - 7 1 - 7 5.00 4.84 1.44 -.73 .12 Managerial Performance6 MP 1 - 1 - 7 1 - 7 5.00 5.21 1.11 -1.02 1.59 Organisational Commitment OC 4 .78 1 - 7 1.25-7 4.75 4.76 1.19 -.54 .15 Organisational

Hierarchical Level OHL 5 - 1 -5 1 -5 3.00 2.78 1.07 .29 -.73

Quality Threatening

Behaviour QTB 5 .69 1 -5 1 -4.6 2.60 2.56 .67 .24 -.01

Relative Emphasis

On Financial Goals REFG 1 - 0 -1 0 0 0 -1 0 0 50.00 42.02 30.19 .07 -1.15

Relative Emphasis On Quantitative Goals REQG 1 0 -1 0 0 0 -1 0 0 42.50 45.20 25.03 .04 -.77 Supervisory Trust ST 5 .89 1 -7 1 - 7 5.20 5.17 1.19 -.59 .28 Target Focused Style-Full TFl 6 - 1 -7 1.17-5.67 3.42 3.34 .75 .06 .07 Target Focused Style-Short TF2 2 - 1 - 7 1 - 7 2.50 2.86 1.24 1.09 1.00

Target Focused Style Hopwood TFH

Ratio

2:1 - .1 4 - 7 .2 9 -4 .91 0.93 .32 5.08 43.65

Note’. Standard error (SE) o f skewness = .158; SE of kurtosis - .316.

Chapter 6 Data A nalysis & Hypothesis Testing 180

6.4.2 Tests of Hypothesis 1 & 2 - Directs Effects of TF PES

Recall that Hypothesis 1(a) and 1(b) posit a positive association between TF PES and quality

threatening behaviour (QTB), and TF PES and intention to turnover (IT). QTB and IT were

regressed on TFl to test these hypotheses, and results from the regression analysis are

presented in Table 6-12 below. The results show that TFl is a significant predictor o f QTB

(bu =.16, p-value <.01) though with a small variance explained (.R2 = .03). The results using

TF2 and TFH measures are also consistent with that using TFl but with higher R 2, .10 and .05 respectively. Thus Hypothesis 1(a) is supported.

In the second panel o f Table 6-12, the results show that TF PES is positively associated with

IT as expected though the association is not significant using the TFl measure (bu = .06, p

>.10). However, parameter estimates for the TF2 measure (bn = .21) and the TFH measures

(&n = .80) are positive and significant. Thus although Hypothesis 1(b) is not supported using

TFl PES measure, there is indication o f a positive association as supported using the TF2 and TFH PES measures.

Table 6 -12 Sum mary o f regression analysis: TF PES Predicting QTB & IT

<N

II TFl TF2

TFH

E q u a tio n P a ra m ete rs & E x p e c te d sign

P

SE B p SE B

P

S E B Y = QTB Constant 2.01** .196 2.06** .105 2.13** .131 TF (/>„) + .16** .057 .18 .18** .034 .32 .47** .134 .22 R 2 .034 .104 .05 F 8.14** 27.21** 12.35** Y = IT Constant 2.77** .490 2.35** .269 2.22** .327 TF ( b u ) + .06 .143 .03 .21** .086 .16 .80** .334 .16 R2 .001 .025 .024 F .151 5.99** 5.77**

N ote /? is unstandardized beta & B is standardized beta;

A p < . 10; * p < .05; **p < .01. Note: For hypothesis testing purposes a 10% significance level is o f course a test at the 5% level if the hypotheses are directional. However, in this table and subsequent tables o f results the 2- tailed p-values are reported and used in testing the hypotheses. This allows for discussion o f significant results opposite in direction to the hypothesis.

Chapter 6 Data A nalysis & Hypothesis Testing 181

Given that higher TF PES is associated with higher QTB and possibly higher IT, further

analysis was conducted to check if there were differences in QTB and IT between high TF

PES based mainly on financial measures and high TF PES based mainly on non-financial

measures. In order words we investigate to see if the observed positive association is driven

by the nature of the performance measure used in a target focused manner in performance

evaluation. First, data was grouped into high (low) TF PES if the TF PES score was above

(below) the TF PES median. Then the high TF PES groups were subdivided into high TF PES

based mainly on financial or non-financial measures based on if scores on the relative

emphasis on financial goals (REFG) measure were above or below the REFG median. Scores

above the REFG represented TF PES based mainly on financial measures, and scores below

represented TF PES based mainly on non-financial measures. This grouping was represented

by the variable TFl Fin, TF2_Fin, and TFH Fin respectively for the 3 PES measures with a

value o f ‘ 1’ representing high TF PES based mainly on financial measures and ‘O’ otherwise.

Finally, the QTB and IT mean scores for the two sub-groups were compared. The results,

presented in the first panel o f Table 6-13 below, show no significant differences in QTB (for

T F l, t = .69, p = .49) and in IT (for T F l, t = .49, p = .622) between the two sub-groups. The

same results apply using the TF2 and TFH measures. This implies that when quantitative

financial and quantitative non-financial measures are used in the same target focused manner,

they result in similar unintended consequences. Thus Hypothesis 2(a) and 2(b) are supported.

To evaluate this point further data was grouped into two based on whether performance

measures were mainly quantitative or mainly qualitative. Scores above (below) the median on

the relative emphasis on quantitative goals (REQG) measure were identified as use o f more

quantitative (qualitative) performance measures.61 This was represented by a dummy variable

Quant which equalled 1 (0) if performance measures were more quantitative (qualitative).

61 REQG measure asked respondents to indicate the emphasis their superior currently placed on meeting quantitative vs. non-quantitative goals when evaluating their performance. And the REFG measure asked respondents to indicate the amount o f emphasis superiors placed on meeting the financial vs. non-financial measures o f their quantitative measures. See Appendix 3, page 259

Chaptei 6 Data A nalysis & Hypothesis Testing 182

Result o f the analysis, presented in the 2nd panel of Table 6-13, show that those whose

performance measures were mainly quantitative did not report significantly different levels of QTB (t — .66, p =.51) and IT (/ = -.95, p =.34) compared to those with mainly qualitative performance measures.

Table 6-13 T-test o f D ifferences in QTB & IT Means

Groups based on Nature o f Performance Measures - Financial vs. Quantitative N on-finan cial Measures; Quantitative vs. N on-quantitative_________ _______ _________________ Group T F l Fin* T F l F i n T F H F i r f N Mean t (Std. (2-tailed Dev) Sig.) N Mean (Std. Dev) t (2-tailed Sig.) N Mean (Std. D ev) (2-tailed Sig.) QTB 1 50 2.70 .69 46 2.85 1.21 43 2.74 1.30 (0.59) (.490) (0.60) (0.23) (0.68) (0.20) 0 44 2.61 40 2.68 55 2.55 (0.75) (0.73) (0.75) IT 1 50 3.00 .49 46 3.13 -0.43 43 2.88 -0.65 (1.93) (.622) (1-96) (0.67) (1.62) (0.52) 0 44 2.82 40 3.30 55 3,11 (1.59) (1.62) (1.75) Q uanT Fin1 Mean t Mean /

Group N (Std. Dev) (2-tailed Sig..) N (Std. D ev) (2-tailed Sig.)

QTB 1 2.59 0.66 2.67 1.73 118 (0.67) (0.51) 80 (0.67) (0.08) 0 2.53 2.49 118 (0.68) 114 (0.68) IT 1 2.86 -0.95 2.93 -0.09 118 (1.67) (0.34) 80 (1.78) (0.93) 0 3.06 2.95 118 (1.63) 114 (1.6 6)

T F l F in = 1 for high TFl PES based mainly on financial measures and O' for high TFl PES based mainly on non-financial measures; same for TF2_Fin,and TFH_Fin.

b Q u a n t = 1 (0) when mainly quantitative (non-quantitative) performance measures are emphasized; Fin = 1 (0) when mainly financial (non-financial) performance measures are used.

In addition, comparisons were also made between those whose performance measures were

mainly quantitative financial and those with more quantitative non-financial measures. This

was measured byf the dummy'- variable Fin which equalled 1 (0) for scores above (below) the REFG median. Again no significant differences were found between the two groups, although

Chapter 6 Data A nalysis & Hypothesis Testing 183

those with more financial measures reported marginally more QTB (t = 1.73, p =.08). This

marginal difference provide some support to the findings o f Hopwood (1972) and others, i.e.

that emphasis on the short-term meeting of budget targets, which are quantitative and

financial, are associated with dysfunctional behaviours. However, it is also shown here to be

o f less importance with the more general quantitative vs. qualitative measures thus extending

the findings o f earlier studies. Furthermore, combining this and the finding o f similar QTB

levels between the high TF PES financial and non-financial groups indicate that using

quantitative non-financial measures in the same target focused manner as quantitative

financial measures produces similar unintended consequences. Thus this study further extends

earlier studies in showing that emphasis on achieving targets in general, budget or non budget

related, has similar unintended consequences.

6.4.3 Tests o f Hypothesis 3 -D irect (Curvilinear) Effects o f TF PES

Recall that Hypothesis 3 posits a convex, i.e. inverted U-shaped, curvilinear relationship

between TF PES and effort (EFF), and TF PES and performance. Recall also that performance

is measured in terms o f the actual performance ratings respondents received in their last

performance review (AP) and by managers self rated measure of performance, i.e. managerial

performance (MP). A hierarchical regression analysis was employed to evaluate the

hypothesized curvilinear relationship. EFF was regressed on the gender control variable in the

first step, then the linear TF PES term w as added in the second step, and the cu n ilinear term

(i.e. squared TF PES) was entered in the last step. Similarly, the criterion variables (AP and

MP) were regressed on the linear TF PES term in the first step, and the curvilinear TF PES

term was added in the second step. If the relationship between TF PES and the criterion

variables are best represented by linearity, then a significant amount o f the variation in these

variables should be explained by the TF PES term alone. If on the other hand the inclusion of

the squared TF PES term explains a significant amount o f variation beyond that explained by

Chapter 6 Data Analysis & Hypothesis Testing 184

form best represents the relationship between TF PES and the criterion variable. Results are presented in Table 6-14 below.

Table 6 -1 4 Summary o f hierarchical regressions: Linear & curvilinear TF PES predicting Effort

N = 2 3 6