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e10<br />

e9<br />

e8<br />

e7<br />

e6<br />

e5<br />

e4<br />

e3<br />

e2<br />

e1<br />

Figure 4. Effects of external variables on Iranian universities’ Performance<br />

Management and Performance (outcome)<br />

.84<br />

DECENT1<br />

.66 .91<br />

DECENT2 .81<br />

.91 .82<br />

DECENT3.77<br />

.59<br />

DECENT4<br />

DECENT<br />

.47<br />

.30<br />

REWSYS2 .69<br />

.74.86<br />

FREWSYS<br />

.29<br />

REWSYS3<br />

.74<br />

USACPM1<br />

.65<br />

.86<br />

USACPM2 .81<br />

.66 .81<br />

USACPM3.79<br />

.62<br />

USACPM4<br />

.60<br />

DEPPER1<br />

e26<br />

Performance Management Model<br />

.12<br />

.32<br />

e14 e15<br />

USACPM<br />

e23<br />

DEPPER<br />

.20<br />

~ 105 ~<br />

COMPOS<br />

.10<br />

SREWSYS<br />

.78 .70 .82 .65 .81<br />

.48<br />

.67<br />

.42<br />

DEPPER2 DEPPER3 DEPPER4<br />

e27<br />

.12<br />

.27<br />

.16<br />

.49<br />

.14<br />

.04<br />

e28<br />

.04<br />

.32<br />

e25<br />

e29<br />

.14<br />

COMPME<br />

e24<br />

.67<br />

.45<br />

COMPOS1 e11<br />

.66<br />

.81<br />

COMPOS2 e12<br />

.70<br />

.49<br />

COMPOS3 e13<br />

.65<br />

.80 REWSYS5 e16<br />

.82<br />

.91<br />

.37 .63<br />

REWSYS6 e17<br />

.40<br />

REWSYS7 e18<br />

.87<br />

.75<br />

COMPME1<br />

.88<br />

e19<br />

.94 COMPME2<br />

.60<br />

.36<br />

e20<br />

.55COMPME3<br />

.31 e21<br />

COMPME4 e22<br />

.66<br />

DEPPER6<br />

Table 5. Regression coefficients based on Maximum Likelihood (ML) for<br />

Performance Management Model<br />

Variables Estimate S.E. C.R. P<br />

DECENT ->FREWSYS<br />

DECENT ->SREWSYS<br />

DECENT->USACPM<br />

COMPOS ->COMPME<br />

COMPOS->USACPM<br />

FREWSYS -> DEPPER<br />

SREWSYS -> DEPPER<br />

COMPME->DEPPER<br />

USACPM->DEPPER<br />

.145<br />

.330<br />

.278<br />

.621<br />

.201<br />

.033<br />

.023<br />

.202<br />

.199<br />

.085<br />

.073<br />

.067<br />

.130<br />

.105<br />

.052<br />

.059<br />

.045<br />

.053<br />

e30<br />

1.700<br />

4.490<br />

4.145<br />

4.781<br />

1.909<br />

.635<br />

.391<br />

4.538<br />

3.782<br />

Therefore, it can be asserted that based on this model which is fit with the collected<br />

data there is a significant association between “competitive position” and employing a<br />

“comprehensive set of performance measures” (+.81), but not so strong association<br />

with the “usage of accounting information for performance management” (+.14). On<br />

the other side, although the effect of “decentralization” on more “usage of accounting<br />

information in performance management” was explored significant, its effect on better<br />

“reward system” appears to be different for faculty members (+.12) and other staff<br />

(+32). It seems vital to be mentioned here that based on the exploratory and<br />

.089<br />

.000<br />

.000<br />

.000<br />

.056<br />

.526<br />

.696<br />

.000<br />

.000

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