【正文】 了 現(xiàn)場安全研究。 通過 四個因素 (一級 )調查比較 來 解他們 ， 受訪者 請求 比較變量 ,他們 必須為他們提高 安全管理體系的城市 建設 給出 分數(shù) ,其真實可靠性是 基于受訪者的經(jīng)驗和不影響任何變量 而 歸納 的 。 刺激因素， 一個全面的名單已確定了 590 個屬性，可用于評估施工安全。在該評級方法的基礎上，五位專家采訪和定稿的評價方法是四種可能的評價選項： 0/1， 01，0/1/NA01/ NA。 通過框架計算滬深開發(fā)和測試在這項研究是非常重要，因為它可以作為衡量一個項目安全管理體系考核成效的參考。無效的安全管理體系可以通過低滬深分數(shù)確定。顯然，在這項研究中開發(fā)的模型不可能解決所有項目上的安全問題。 [2] Hinze 2020 129（ 2） :15964。4（ 1） :2944。1996 年。 [8] Petersen 。紐約： 麥格勞 希爾公司， 1987。23:32941。 Developing a model to measure the effectiveness of safety management systems of construction sites Evelyn Ai Lin Teoa,_, Florence Yean Yng Linga aDepartment of Building, School of Design and Environment, National University of Singapore, 4 Architecture Drive, Singapore 117566, Singapore Received 16 February 2020。 Safety audit。 ? importance weights of attributes。 personnel and incentive (see Fig. 2,Level 1). Second level attributes were the significant attributes derived from the survey questionnaire, ttest and factor analysis. Each second level attribute was further opertionalised to lower level attributes until a measurable lowest level attribute was obtained. The finalised list contained 590 attributes and these make up the CSI checklist. . Importance weights of attributes There is a need to make a distinction between what are essential and what are desirable attributes in the 3P+ I hierarchical framework which as mentioned earlier, contained 590 detailed attributes. This is because different attributes are of different importance with respect to site safety. It is therefore necessary to find out the degree of importance of each attribute by assigning them weights. The weight is important to decision makers because it expresses the importance of each attribute relative to the others. For those attributes being evaluated, a weight indicates what the decision makers are most concerned about in a quantitative way. There are several conventions to follow in assigning weights to attributes [17]. One convention is that the final weight for each twig on the hierarchy tree is obtained by ‘multiplying through the tree’. The next convention is to normalise the weights, 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)。 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 2020 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