外文翻譯---職業(yè)健康和安全管理體系中可能性影響因素的回歸性分析（英文）

1、Possibilistic regression analysis of influential factors for occupational health and safety management systemsAzizul Azhar Ramli a,?, Junzo Watada a, Witold Pedrycz b,ca Graduate School of Information, Production and Sys

2、tems, Waseda University, 2-7 Hibikino, Wakamatsu-ku, Kitakyushu-shi, Fukuoka-ken 808-0135, Japan b Department of Electrical Sgourou et al., 2010). There are two major groups, which directly involve this important regula

3、tion; that is employees’ personnel and administrative staffs. The overall combination of OHS code ethics and activities has to be clearly defined and their results should be periodically evaluated through some OHS manage

4、ment system (OHSMS). In this situation, the evaluation of factors that influence an OHS provides a useful feedback to employees’ personnel and administrative staff. This process may produce higher safety consciousness as

5、 well as con- tribute to the well-being in a workplace (Gallagher, 2000; Hwang et al., 2009). In addition, the most essential albeit somewhat controversial point concerns a procedure on how to obtain sound knowledge re-

6、lated to the OHS practices while dealing with imprecise or vague data. The inherent complexity of OHS stems from several sources. In particular, we need to stress that a simple computational ap- proach is often inadequat

7、e and traditional data about incidents/ claims have also proved to be quite unreliable (Gallagher et al.,2003; Dul and Neumann, 2009). In light of this, a genuine need emerges to develop an alternative approach, which en

8、ables us to analyze and provide high quality results for the continuous improvement of OHSMS implementation procedures (Gallagher et al., 2001). Currently, supervisors or auditors can use a number of instru- ments or aud

9、it tools in their evaluation of OHSMS influential fac- tors. The factors or criteria that affect OHS practices usually depend on company policy and regulations, where its evaluation process involves a number of approache

10、s or/and parameters, which are often based on imprecise data (Watada et al., 1998). Be- sides that, some companies/organizations still use open-ended and somewhat subjective questions. These types of questions require so

11、me judgment process such as OHS experts’ interpretation to ana- lyze and interpret the results. Without this, it is difficult to arrive at conclusive results or generate useful knowledge (Robson et al., 2005). Moreover,

12、emerging Internet facilities offer advantages to the administration section in companies/organizations when developing a web portal for each level of employees to assess their administrative OHS practice. Using this tech

13、nology in place, related parties such as auditors, companies/organizations administration and employees can envision quite tangible benefits. In order to acquire benefits from the analysis of the results and facilitate t

14、heir comprehensive interpretation related to the OHSMS implementation, an adequate analysis is badly needed. The main objective of this research is to employ possibilistic regression anal- ysis to the OHSMS evaluation. W

15、e anticipate that the possibilistic0925-7535/$ - see front matter ? 2011 Elsevier Ltd. All rights reserved.doi:10.1016/j.ssci.2011.02.014? Corresponding author. Tel.: +81 80 3981 9429.E-mail addresses: azizulazhar@moegi.

16、waseda.jp (A.A. Ramli), junzow@osb.att.ne.jp (J. Watada), pedrycz@ece.ualberta.ca (W. Pedrycz).Safety Science 49 (2011) 1110–1117Contents lists available at ScienceDirectSafety Sciencejournal homepage: www.elsevier.com/l

17、ocate/sscithis critical issue will lead to major problems, especially related to employee’s health and safety (LaMontagne et al., 2004). Much of related research is not directly concerned with OHSMS – it merely implies t

18、hat certain factors or aspects of an OHSMS ex- hibit positive effects on OHSMS action policy and its implementa- tion procedure (Thanet and Hadikusumoa, 2008). Highlighted as the most valuable findings in OHSMS, Gallaghe

19、r (2000) support the conclusion that a particular type of OHSMS called ‘a(chǎn)daptive hazard managers’ distinguished by a ‘safe place’ control strategy and ‘innovative management structure/style’ per- forms better than other

20、types, especially ‘unsafe act minimizes’ with a ‘safe person/traditional management’ approach (Robson et al., 2005). Several related literature studies on OHSMS indicate that a set of six key variables that should be per

21、iodically considered includes the following:i. Development of an OHS policy and program. ii. Method of OHSMS consultation sessions. iii. Setting up a OHSMS training strategy. iv. Setting up hazard identification and work

22、place assessment process. v. Development and implement of OHSMS risk control strategies. vi. Promoting, maintaining and improving of OHSMS strategies.These points have been devised to help companies/organiza- tions imple

23、ment efficient and effective OHSMS, which facilitated the prevention of accidents, incidents, injuries and work-related ill-health (Parker et al., 2006; Paul and Maiti, 2008). Moreover, these dangerous situations are not

24、 avoidable and some of them may be repetitive because of the differences among workplaces (Leclercq et al., 2007; Grassi et al., 2009). Therefore, an efficient approach becomes our major concern in order to rank OHSMS in

25、fluential factors. Currently, the general the- ory of OHS and OHSMS is used in most of the companies/organiza- tions all around the world to successfully implement this policy. As mentioned in the previous section, the r

26、equirements of an IDA tool are faced with a large size of OHSMS samples and therefore a way of dealing with imprecise data presentation becomes necessary (Moriyama and Ohtania, 2009).2.2. The importance of occupational h

27、ealth and safety policy assessment procedureIn general, the International Labour Organization (ILO) has stressed that when practical ergonomics approaches are built in the workplaces environment and participatory trainin

28、g methods are engaged, the approaches have been proven useful for facilitat- ing concrete workplace improvements under the existing condi- tions present in developing countries (Kawakami and Kogi, 2005; Niu, 2010). In ad

29、dition to this broad set of OHS significant needs, Zink in 2005 highlighted the assessment of OHSMS influential factors be- comes a preliminary phase because of the following reasons:i. Prevention and systematic approach

30、es. ii. Continuous improvement. iii. Integration in normal operations and planning. iv. Comprehensive deployment. v. Strong relationship to policy and strategy and respective goals. vi. Orientation toward the best in cla

31、ss (benchmarking).Moreover, applying ergonomic principles such as OHS policy is beneficial to the workers as well as employers. Both parties areequally significant (Niu, 2010). In addition, healthy employees can be nearl

32、y three times more productive than those being of poor health. Niu has also composed the potential effects of ignoring OHS procedure by both workers and employers, refer to Table 1. Consequently, on the basis of above-li

33、sted reasons, we can real- ize here that good quality and highly accurate results are required in order to clearly determine appropriate OHSMS influential fac- tors, which were acknowledged as a major component of OHS po

34、l- icy. Moreover, a suitable timeline becomes an important issue because it is interrelated with the frequency of analysis being made. Therefore, a real-time data analysis looks more appropriate to efficiently deal with

35、this critical problem; likewise, an adequate IDA tool is also necessitated. Overall, considering future trends of the OHSMS data analysis, one should emphasize that here we are faced with large scale data, which come fro

36、m various sources and of different formats. There- fore, the needs of robust IDA become of priority given that such analysis is capable of producing optimized results within some gi- ven time constraints.3. Fundamental i

37、deas of models of possibilistic regressionIn statistical regression, deviations between observed and esti- mated values are assumed to be due to random errors. Although conventional regression has been applied to various

38、 areas, the re- lated problems include the vague relationship existing between in- put and output variables that cannot be clearly justified (Ciarapica and Giacchetta, 2009). Therefore, this becomes a major reason be- hi

39、nd its unsuccessful usage in the meaningful interpretation of the model. Regression analysis is one of commonly encountered ap- proaches in describing relationships among the analyzed data. The regression models explain

40、dependencies between independent and dependent variables. The variables, which are used to explain the other variable(s) are called explanatory ones (Watada and Ped- rycz, 2008). A ‘‘standard’’ numeric linear regression

41、model comes in the following formy ¼ a0 þ a1x1 þ ? ? ? þ aKxK: ð1ÞAs an interesting and useful extension, Tanaka et al. (1982)introduced an enhancement of the regression model by accommo- da

42、ting fuzzy sets thus giving rise to possibilistic regression. The models of this category reflect upon the fuzzy set based nature of relationships between the dependent and independent variables.Table 1Potential effects

43、of ignoring OHS policy procedure (Niu, 2010).Workers EmployersPain and suffering due to injuries andoccupational diseasesIncreased absenteeism and lostworking timeMedical care cost Adverse effects on labor relationsLost

44、work time Higher insurance and compensationcostsLost future earning and fringebenefitsIncreased probability of accidentsand errorsReduced job security and careeradvancementRestriction, job transfer and higherturnover of

45、workersLost home production and child care Scrap and decreased productionHome care costs provided by familymembersLawsuitsAdverse effects on family relations Low-quality workLost sense of self-worth and identity Less spa

46、re capacity to deal withemergenciesAdverse effects on social andcommunity relationshipsHigh administrative and personnelcostsAdverse effects on recreationalactivities1112 A.A. Ramli et al. / Safety Science 49 (2011) 1110