1. An Application of Structural Equation Modeling in Evaluating Accident/Injury Occurrences in Underground Coal Mines Dr J Maiti Associate Professor Department of Industrial Engineering and Management IIT Kharagpur

2. Introduction  The purpose of this presentation is to show how Structural Equation Modeling (SEM) can be applied to real life problem solving. 

3. Stages in SEM Stage 1: Developing a Theoretically Based Model Stage 2: Constructing a Path Diagram of Causal Relationships –Elements of a Path Diagram –Examples of Path Diagrams –Basic Terminology –Assumptions of Path Diagrams

4. Stages in SEM Stage 3: Converting the Path Diagram into a Set of Structural Equations and Specifying the Measurement Model –Structural Model –Measurement Model Correspondence to Factor Analysis Specifying the Measurement Model Determining the Number of Indicators Accounting For Construct Reliability –Empirically Estimating Reliabilities –Specifying the Reliabilities »Single-item Measures »Use of Validated Scales or Measures »Two-stage Analysis »Methods of Specifying the Reliability –Correlations Among Constructs and Indicators

5. Stages in SEM Stage 4: Choosing the Input Matrix Type and Estimating the Proposed Model –Inputting Data Assumptions Covariances Versus Correlations Sample Size –Model Estimation Estimation Technique Estimation Processes Computer Programs

6. Stages in SEM Stage 5: Assessing the Identification of the Structural Model Stage 6: Evaluating Goodness-of-Fit Criteria –Offending Estimates –Overall Model Fit –Measurement Model Fit Composite Reliability Variance Extracted –Structural Model Fit –Comparison of Competing or Nested Models

7. Constructs Considered for this Study  Work Injury  Safety Performance Rating  Job Involvement  Job Stress  Safety Environment  Social Support  Work Hazards Depended Constructs Independed Constructs

8. Work Injury injury Safety Performance Rating Rating 1 Rating 2 Rating 3 Job Involvement Safety Environment Safety Training Safety Practice Safety Equipment Availability and Maintenance Manifest Variables Constructs

9. Job Stress Social Support Co-worker Support supervisory Support Management Worker Interaction Work Hazards Physical Hazards Production Pressure Manifest Variables Constructs

10. Manifest variables No. of quest- ions Sample Question Construct Reliability Job involvement Safety training Safety practice Safety equipment availability and maintenance Job stress Co-worker Support Supervisory support Management Worker interaction Physical hazards Production pressure 13 6 19 8 8 5 7 10 12 4 Do you feel uneasy when your work remains incomplete? Do you feel training given to you is effective? Does shortfirer give warning before blasting? Are required amount of helmets, boots and cap lamps available in your mine? Do you think your work is difficult and arduous? Does an extremely friendly atmosphere prevail amongst the workers in this mine? Do supervisors instruct and guide their subordinates? Does management support your decisions concerning safety? Whether loose chunk of coal at the roof and side wall of this mine is seen frequently? Have you ever been pressurized to deliver production targets to the detriment of safety? 0.84 0.66 0.80 0.72 0.67 0.64 0.71 0.84 0.65 0.80 Manifest variables scale items, means, and standard deviations (item format for managerial subjects)

11. Work injury0.500.501.00 Rat 1 52.5420.73-0.35** 1.00 Rat 2 47.8419.74-0.53** 0.60**1.00 Rat 348.2619.68-0.57** 0.63**0.72**1.00 Job involvement 28.966.36-0.16** 0.120.16**0.121.00 Safety training13.223.27-0.19** 0.060.20**0.15**0.25**1.00 Safety practice 39.677.53-0.29** 0.060.18**0.110.50**0.52**1.00 S_Equip_A_M15.733.93-0.24**0.040.12*0.050.52**0.36**0.65**1.00 Job stress16.823.990.14*0.01-0.11-0.06-0.50**-0.54**-0.60**-0.46**1.00 Co_W_Sprt12.862.18-0.030.010.07-0.030.110.29**0.44**0.31**-0.30**1.00 Sup_Sprt14.913.68-0.23**0.050.16**0.15*0.54**0.62**0.70**0.52**-0.64**0.29**1.00 M_W_Int20.365.44-0.23**0.030.15*0.080.57**0.53**0.80**0.67**-0.66**0.39**0.81**1.00 Prod_Pr24.104.360.19**-0.01-0.09-0.07-0.34**-0.17**-0.50**-0.51**0.46**-0.21**-0.42**-0.51**1.00 Phy+Hrz8.782.820.110.04-0.04-0.01-0.38**-0.27**-0.40**-0.38**0.38**-0.10-0.50**-0.45**0.44**1.00 Construct Mean S.D. Correlations Descriptive statistics and interrelationship amongst constructs Legend : S_Equip_A_M= Safety equipment availability and maintenance, Co_W_Sprt= Co- worker support, Sup_Sprt= Supervisory support, M_W_Int= Management worker interaction, Prod_Pr= Production pressure, Phy+Hrz= Physical hazards. * P<0.05 **P<0.01

12. Preliminary path diagram of sociotechnical model Safety Environment Social Support Work Hazards Job Involvement Job Stress Safety Performance Work Injury - + - + - - + + -

13. Safety Performance Rating Job Involvement Safety Environment Job Stress Social Support Work Hazards Injury (1) Rating 1 (2) Rating 2 (3) Rating 3 (4) Job Involvement (5) Safety Training (6) Safety Practice (7) Safety Equipment Avail. and Maintenance (8) Job Stress (9) Co-worker Support (10) supervisory Support (11) Management Worker Interaction (12) Physical Hazards (13) Production Pressure (14) Baseline measurement model

14. Chi-square with 55 degree of freedom = 219.52 Goodness of Fit Index (GFI = 0.90 Adjusted Goodness of Fit Index (AGFI) = 0.82 Root Mean Square Residual (RMR) = 0.049 Normed Fit Index (NFI) = 0.90 Relative Fit Index (RFI) = 0.84 Goodness of fit Indices for the Measurement Model

15. Parameter 1 1 2 2 3 2 4 2 5 3 6 4 7 4 8 4 9 5 10 6 11 6 12 6 13 7 14 7 Estimates 1.00 0.70 -0.82 0.89 1.00 0.60 0.87 0.72 1.00 0.41 0.85 0.94 0.70 0.63 t-value -------- 16.81* 24.63* 24.28* -------- 19.68* 23.14* 22.85* -------- 14.16* 24.96* 25.33* 13.45* 13.78* * indicates 0.01 probability level of significance Parameters Estimates with their t-values, for the Measurement Model

16. Safety Environment Social Support Work Hazards Job Involvement Job Stress Safety Performance Work Injury -0.23 0.23 -0.53 -0.58 0.45 -0.15 0.15 Final path diagram of sociotechnical model

17. Chi-square with 11 degree of freedom = 48.71 Goodness of Fit Index (GFI) = 0.96 Adjusted Goodness of Fit Index (AGFI) = 0.89 Root Mean Square Residual (RMR) = 0.03 Normed Fit Index (NFI) = 0.97 Relative Fit Index (RFI) = 0.95 Expected Cross Validation Index (ECVI) = 0.28 Square multiple Correlations for Structural Equations Safety performance= 0.02 Work injury= 0.42 Job involvement= 0.33 Job stress = 0.53 Goodness of fit Indices for the Structural Model

18. Parameter Estimatest-value  1 1-0.23-5.28**  3 1 0.45 6.79**  4 2-0.53-8.50**  4 3 0.23 3.65**  1 2-0.58-13.26**  2 3 0.15 2.61*  3 4-0.15-2.29*  1 10.5612.17**  2 20.9812.17**  3 30.6712.17**  4 40.4712.17** Parameters Estimates with their t-values, for the final Structural Model * indicates 0.05 probability level of significance ** indicates 0.01 probability level of significance

19. Findings from the Study  The case study results showed that there is a sequential interaction amongst the sociotechnical factors leading to accidents/injuries in mines.  Work hazards induce more job stress to the workers while social support mitigates the same.  Job stress and safety environment predict the workers’ job involvement.  A worker who is more job-involved exhibits better safety performance, which in turn reduces work injury.  Safety environment is shown to have direct mitigating effect on work related injury. Safety Environment Social Support Work Hazards Job Involvement Job Stress Safety Performance Work Injury -0.23 0.23 -0.53 -0.58 0.45 -0.15 0.15

20.  The case study result supported the hypothesis that social support predicts employees job stress, which in turn dictates their job involvement.  This finding indicates that increase in social support will result in decrease in job stress perceived by the workers. The construct social support is measured upon co-worker support, supervisory support, and management worker interaction. Hence workers perceiving poor supports form the surroundings of his workplace i.e. from supervisors, and co-workers, and also from mine management feel more job stress.  So care must be taken to identify these workers and appropriate training should be given to overcome this situation. Face to face counseling, encouragement for more intensive participation of these workers into the safety matters will definitely help in this regard. Recommendation Safety Environment Social Support Work Hazards Job Involvement Job Stress Safety Performance Work Injury -0.23 0.23 -0.53 -0.58 0.45 -0.15 0.15

21. Recommendation (Contd.)  As expected, job stress reduces workers’ job involvement. The model shows that job involvement is the only direct predictor of safety performance and better safety performance yields less injury. So, the root cause lies in less job involvement, which is again predicted by job stress and safety environment.  Safety environment also directly effects work injury. Therefore, safety environment and job stress are the two key variables of work injury for the mines studied. Safety Environment Social Support Work Hazards Job Involvement Job Stress Safety Performance Work Injury -0.23 0.23 -0.53 -0.58 0.45 -0.15 0.15

22. Safety Environment Social Support Work Hazards Job Involvement Job Stress Safety Performance Work Injury -0.23 0.23 -0.53 -0.58 0.45 -0.15 0.15  Identification of these highly job stressed individuals, understanding their existing problems, and rectifying through the class room teaching is required for the case study mines so that they can overcome the existing unhealthy conditions by developing good relationship with co-workers, supervisors, and mine management.  Upkeeping good safety environment through proper checking of the working conditions with technical persons, providing adequate training both psychological counseling and on the job task training and allocating jobs properly (right person to right jobs) must improve the existing safety status of the mines. Recommendation (Contd.)