【導(dǎo)讀】在,安全標(biāo)準(zhǔn)的提高并不顯著。為了回應(yīng)需要改進(jìn)的有效性和安全管理體系審計(jì)。研究方法采用了15個(gè)步進(jìn)行調(diào)查，安全專家被邀請(qǐng)通過面試或工作。表達(dá)自己的意見。層次分析法及因子分析是用來協(xié)助識(shí)別影響最為關(guān)鍵的因素。到驗(yàn)證審核,利用模型中施工安全指數(shù)可以計(jì)算出來。結(jié)果表明,該模型可以作。為一個(gè)客觀CSI衡量不同管理和評(píng)估。樣可以使不足之處得以更正。該研究工作是在協(xié)作與職業(yè)安全部門監(jiān)督下進(jìn)行的,人。這與影響船舶的修建行業(yè)一樣,經(jīng)歷了一個(gè)穩(wěn)定提高安全性能的階。在新加坡,沒有規(guī)定管理SMS的方式和政策，缺少的部分由建筑公司。以往的研究發(fā)現(xiàn)成功的安全關(guān)系體系在建筑工地有助于防止事故的發(fā)生。系統(tǒng)守則基于在新加坡的廣泛使用的規(guī)程實(shí)施。這個(gè)調(diào)查的目的是制定一項(xiàng)審計(jì)協(xié)議來有效的評(píng)價(jià)解釋網(wǎng)站的安全管理體系。安全性能也是至關(guān)重要的。因此,及時(shí)的安全檢查將幫助確定強(qiáng)項(xiàng)和。BOWEC法規(guī)要求所有的施工工作城市及合同價(jià)值$1000. ·緊急事件處置；

　　

【正文】 ts, that is, to make weights sum to 1 at each level of the tree. This study adopted two methods to obtain the importance weights, using: ? Saaty’s [19] AHP for higher level attributes (levels 1 and 2). ? Likert Scale for lower level attributes (level 3 onwards). . Importance weights for higher level attributes using AHP (step 9) The questionnaire to obtain the first and second level weights using AHP. The weights of the four factors (Policy, Process, Personnel and Incentives) make up the first level weights. The second level weights are the 17 subfactors of the 3P + I model (see Fig. 2). The questionnaire consists of five sections. They are (1) factors relating to site safety through policy, process, personnel and incentive aspects (level one weights)。 (2) factors relating to site safety through policy aspect (level two weights)。 (3) factors relating to site safety through process aspect (level two weights)。 (4) factors relating to personnel aspect (level two weights)。 and (5) factors relating to site safety through incentive aspect (level two weights). Using Saaty’s [19] AHP technique, respondents were asked to pare each element or subfactor against one another based on a 9point scale using pairwise parison method to indicate their relative importance. The measure of intensity of importance is determined by a scale of 1 as ‘equal importance’ to 9 as ‘a(chǎn)bsolute importance’. Each element or subfactor was pitted against one another in order to establish the importance weightage. For example, in the elements section where policy factor was pared against the process factor, a twoway scale of 1–9 in each direction indicates the relative importance over either the policy factor or the process factor. The selection of a number is done in accordance with the respondent’s experienced opinion and judgment for all construction projects s/he had been involved in. This is to minimise the possibility of a bias decision based on a particular project. To determine the weights using AHP, 30 experts with extensive experience in site safety were identified. They represent various stake holders in the construction value chain such as contractors, publicsector client, government safety department and safety auditing consultancy firm. All respondents have more than 5 years of working experience in the construction industry. They are considered subject matter experts because they have the necessary knowledge and working experience in handling construction projects. Data were collected through facetoface interviews using the structured questionnaire. Each interview lasted for approximately 2 h. Respondents were instructed to refer to Fig. 3 showing the four factors (level 1) and the 17 subfactors as the survey progressed in order to understand what they were paring. The respondents were further reminded that during the parison of the variables, they had to relate them to the enhancement of SMS on construction worksites. The points were given as genuinely and honestly as possible based on respondents’experience and no influence over any variables were induced. The relative importance ratings from the 30 respondents were input into Expert Choice 2021 software. The programme makes use of the respondents’ data to crosspare all variables to determine the weights and inconsistency ratios. Inconsistency ratio is a measure of the percentage of time decision makers are inconsistent in making judgement. The considered ‘‘a(chǎn)cceptable’’ inconsistency ratio is approximately 10% or less but‘‘particular circumstance’’ may warrant the acceptance of a higher value [19]. An inconsistency ratio of 100% is however unacceptable because the ratings are as good as random judgements. 14 of the 30 experts had inconsistency ratios above 15%. This was too high and their responses were discarded. Of the remaining 16, 14 Experts had low inconsistency ratios eo5%T and two had ratios between 10% and 15%. These two respondents (Experts 4 and 5) were given another chance to relook at their ratings and determine if they would like to change their decisions. Caution was taken to ensure that respondents do not change their previous decisions just to fulfil the inconsistency ratio target. Eventually, one respondent did not change his rating (Expert 5) while another (Expert 4) made some adjustments on his own free will. The inconsistency ratio for Expert 5 on the section of policy aspect was 38%. This is considered very high and Expert 5 had chosen to keep this score. Nevertheless, Expert 5’s data were included in the analysis of weightage because the higher than usual inconsistency ratio was due to his extreme judgement rather than a clerical error. Thus, Expert 5’s ratings were accepted even though the inconsistency ratio was greater than 10%. According to Saaty [19], an accurate judgement is more important than consistently inaccurate judgement. The first and second level weights were puted by averaging the weights for the 16 remaining respondents. As the 3P+I Model may be licensed, the actual weights are not shown in this paper. Nevertheless, the relative importances of the factors, in ascending order are: ? Personnel Factor, ? Incentive Factor, ? Process Factor, ? Policy Factor. . Importance weights for lower level attributes using Likert scale (step 10) Due to the large number of third and lower level attributes, it was not practical to use AHP to determine the weights. As such, the 5point Likert Scale was used to elicit the importance weights. A questionnaire showing all the lower level attributes was designed. Respondents were asked to rate the extent to which each attribute contributed to the effectiveness of SMS on construction sites on a 5point scale where 1 ? not important, 3 ? neutral, 4 ? important and 5 ? very important (critical). To determine the importance of lower level attrib