1. Safety management systems: Performance differences between adopters and non-adopters Safety Science 47 (2009) 155–162 Eleonora Bottani, Luigi Monica, Giuseppe Vignali Speaker: Jenny 2008/12/10

2. Outline Purpose Introduction Hypotheses development Survey phase Results and Discussion Conclusions

3. Purpose whether the performance of safety management systems (SMSs) adopting and non-adopting companies statistically differ

4. Introduction Human factor plays a important role in an organization’s safety performance. (Attwood et al., 2006; Hughes and Kornowa-Weichel, 2004) Unsafe behavior resulted from latent failures in the organization and management systems. (Hughes and Kornowa-Weichel; Kawka and Kirchsteiger, 1999) SMS: a set a policies and practices aimed at positively impacting on the employees’ attitudes and behaviors with regards to risk. (Fernandez-Muniz et al., 2007)

5. Introduction Benefits of SMS: Achieve and maintain high level safety (Mitchison and Papadakis, 1999) improve safety standards Enhance communication, morale, and productivity (Cox and Vassie, 1998) Decrease financial impact of safety (Cox and Vassie, 1998)

6. Hypotheses attitude differs between SMSs adopters & non-adopters H1: define safety and security goals and communicate them to employees H2: update risk data H3: assess risks and define corrective actions H4: implement employees training programs

7. Survey Phase Sample and data collection Questionnaire contents Methodology

8. Survey Phase Sample and data collection Choose the companies randomly on www.kompass.com www.kompass.com Pre-test: e-mail (100) Rewritten the questionnaire, and add explanations Data collection: March to May 2007 Send by email: 400 companies Response: 23.2% (116/500) a = 0.838 (recommended value 0.6)

9. Survey Phase Questionnaire contents 4 sections 4-points Likert scale SPSS

10. Survey Phase Methodology (Minand Galle, 2001) Confirmatory factor analysis (CFA) Verify the questions and double check Reduce the factors to a limited number Factors reliability: Cronbach’s a or Pearson correlation cofeeicient Hypotheses testing independent-samples T test Multiple comparisons

11. Results Respondents Safety managers Quality managers Finance managers 36%16% ManufacturingAgricultureBuildingcommercial 55%14.7%11.3%6%

12. Results Adopt SMS (more  less) Industries: Building (66.67%)  Agriculture  Manufacturing  Commercial Company size: Big (58.33%)  Medium (56.82%)  Micro  Small No difference in product quality and competitive position Current market share: adopters are higher Adopters 65.52% v.s Non-adopters 39.66% More accidents happened to Non-adopters (15.05) Manufacturing (13.97) & Building(14.75)

13. Results Confirmatory factor analysis Engenvectors >1 Variance maximizing procedure is used to extract factors

14. Results Hypotheses Testing

15. Results

16.  update risk data  evidence for causal relationships between SMS implementation and improvements  SMS is used to systematically codify incidents, so facilitating the use of updating risk data (Rowlinson, 2004)

17. Results  access risks and define corrective reactions  adopting SMS improves risk monitoring  SMS codify incidents and related causes, which helps companies to get useful information for improving the design and planning of safety measures, and for monitoring the result performance

18. Results  implement employees training strongly supported by the results Human resource: employees training and awareness

19. Conclusions The difference between two groups is the key points—implementing SMS can get benefits, i.e. 4 factors Companies adopting SMSs exhibit higher performance. This study doesn’t provide a direction of causality of the results obtained. Future research: investigate only one industry, causal relationship between SMS implementation and improvement, difference between IMS(Integrated) and SMS