and AMOS software, the correlation and regression method and path analysis are used for analysis. I. Hafeez et al. Impact of workplace environment on employee performance: mediating role... a a Research Model: This research work has focused on the relationship between the work- ing environment and employee performance. The Study based on the relationship among the working environment and the performance of employee. We took two main factors of working environment; the 1° factor that we considered is physical location in which (office lights, surroundings of office building, sitting arrangements of employee in office) and the 2"¢ factor behavioral (tea time environment, over time bonuses etc) In this study we calculated the effect of these factors on the developers life by gathering data from different software houses of Pakistan. Correlation: In the current study, Pearson’s correlation has been applied as data was in terval scale data. Pearson's correlation is defined as the covariance of two variables dividec by the product of their standard deviations. Correlation values are given in Table 3. Value o coefficient of Pearson's correlation between Behavioural factors (BF) and Physical Environ mental Factors (PEF) is 0.130, and this value is significant at p = 0.05. Between Employe: Health (EH) and Behavioural Factors (BF), it is 0.382, and it is significant at p = 0.000. Pear sor’s correlation value for Employee Performance (EP) and Behavioural Factors (BF) is 0.331 and the results are significant at p = 0.000. Correlation value between Physical Environmen Factors (PEF) and Employee Health (EH) is 0.404 and is significant at p = 0.000. Correlatior between Physical Environmental Factors (PEF) and Employee Performance (EP) is 0.342, anc it is significant at p = 0.000 level of significance and correlation between Employee Healtl (EH), and Employee Performance (EP) is 0.815, and it is significant at p = 0.000. Table 2. Reliability statistics I. Hafeez et al. Impact of workplace environment on employee performance: mediating role... Path Analysis: As discussed earlier SPSS has been used for fundamental analysis and mod: has been tested using AMOS-22 and path analysis (SEM) has been applied. Path analysis is technique used for multivariate analysis for testing the relationship among variables. It is als considered as a part of regression analysis and a part of structural equation modelling. Figure explains the relationship of variables via Path Analysis. In the current model value of chi-squar is 10.721 and DF is 6 while probability is 0.097. Value of Chi-square is crucial in the model, an the small value indicates that the proposed model/ theory arecorrect. The acceptable ratio of f between chi-square and the degree of freedom is 3:1. In the current model, the minimum valu of Chi-square is 4.511 with probability = 0.211 and with degrees of freedom = 3. Model Fit Summary. Summary of model fit is given in Table 4. Values of Degree of Freedom 3 and p = 0.211 exhibit that results current mode goodness of fit. The current study is a Structural Equation Modeling technique wit ate data analysis, in this kind of studies if the value of p is insignificant, it is considered good fit, unlike other multivariate techniques. The acceptable range for the value o f CMI proved the h multivari- as a /DF is 1 to 3. Results show that the value of CMIN/DF is 1.504, and it lies in an acceptable range and signifies the goodness of fit and CMIN corresponds to chi-square value, whic h is 4.5 1. Table 4. Model Fit summary Table 5. Baseline comparisons Table 6. Parsimony-adjusted measures For checking the goodness of fit, we applied Normed Fit Index (NFI ), RFI, Incrementa Fit Index (IFI) Tucker-Lewis Fit Index (TLI) and Comparative Fit Index (CFI). It can b Oo ( bserved from Table 5 that the value of Normed fit index (NFI) 0.987 w 980) cut off criteria for IFI index is 0.95. Tucker Lewis Fit (TLI) Ind value is 0.991 according to criteria its value should be closer to 1 for a hich is greater thar the recommended value of 0.9, RFI value is 0.973, and its recommended value is 0.9 (Bentle & Bonett, 1980). Incremental Fit Index (IFI) value is 0.995. According to Bentler and Bonet ex results show it better-fitted mode (1 fucker & Lewis, 1973). All the above results are falling in an acceptab e range, and it cai be concluded that the goodness of fit shows that the proposed model is a good fit. PNFI anc PCFI are Proximity Adjusted Measures there is 0.493 and 0.498, and its recommended valu is 0.5, actual and recommended values are very close again. Details are given in Table 6. Table 7. Regression weights able 7 shows that value of the coefficient of regression for Physical Environmental rac- tors (PEF) and Employee Health (EH) is 0.347 at p = 0.00, and it is considered as significant while Standardized estimate is 0.367. The values show that there is a positive and signifi- cant relationship between Physical Environmental Factors (PEF) and Employee Health (EH) Hence, H, is accepted. Regression coefficient value between Behavioural Factors (BF) and Employee Health (EH) is 0.328, p = 0.000, and it is significant. The standardised estimate is 0.341. It means that a positive and significant relationship exists between Physical Environ- mental Factors (PEF) and Employee Health (EH) and H, is accepted. Regression coefficient between Employee Health (EH) and Employee Productivity (EP) is 0.796 at p = 0.00 while the standardised estimate is 0.810 which is also significant and indicates that there is a positive and significant relationship between Employee Health (EH) and Employee Productivity (EP) and H; is also accepted. The goodness of fit of has exhibited that Employee Health (EH) play mediating role between Physical Environmental Factors (PEF) and Employees Performance Table 8. Intercepts: (Default model) Table 9. Total, direct and indirect effects Discussion Results Path analysis results indicated that one unit change in Physical Environmental Factors (PE generates 35% change in Employee Health. There is a significant positive relationship betweer PEF and EH, so H, is accepted. Path diagram also explains that Behavioural Factors (BF has a positive influence on Employee Health (EH) and one unit change in BF creates 33% change in EH. There is a positive and significant relationship between BF and EH, and H, i accepted. 80% change in Employee Productivity (EP) is caused by a unit change in Employe Health (EH), and we can conclude that employee health is a strong predictor of employee productivity and there a strong and positive relationship between them, H; is also accepted have also revealed that there is a mediating role of Employee Health (EH) betwee1 PEF and nr... 4. EP as wal as between BF and EP. ac. 1 co eee OO B.S LL re 2 oe be, . i , . a a oo ee oe
