发布时间 : 星期三 文章建筑安全管理外文翻译文献更新完毕开始阅读1a7c32e8112de2bd960590c69ec3d5bbfd0ada1c
建筑安全管理外文翻译文献
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 compare each element or sub-factor against one another based on a 9-point scale using pairwise comparison 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 ‘absolute importance’. Each element or sub-factor was pitted against one another in order to establish the importance weightage. For example, in the elements section where policy factor was compared against the process factor, a two-way 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, public-sector 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 face-to-face 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 sub-factors as the survey progressed in order to understand what they were comparing. The respondents were further reminded that during the comparison 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 2000 software. The programme makes use of the respondents’ data to crosscompare 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 ‘‘acceptable’’ 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
建筑安全管理外文翻译文献
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 computed 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.
4.2.2. 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 5-point 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 5-point scale where 1 ? not important, 3 ? neutral, 4 ? important and 5 ? very important (critical). To determine the importance of lower level attributes, 17 experts were randomly selected from the following types of organisations: clients (public and private); building contractors (local and foreign); safety auditing and consulting firms; and the
建筑安全管理外文翻译文献
MOM which is the safety regulatory body.
Among the 17 respondents contacted, 12 expressed interest to take part in the questionnaire survey. They comprised four clients, two safety auditing and consulting firms, five large building contractors and MOM. Data were collected using the structured questionnaire, through face-to-face interviews. All interviewees were senior management and had many years of experience in the construction industry. From the ratings of the 12 interviewees, mean importance weight for each lower level attribute was calculated. These importance weights were also normalised. For the same reasons as given above, the individual importance weights are not provided in this paper.
4.3. Rating the construction site for each attribute (step 11)
The next element of the MAVT model is the rating method that auditors are required to use to rate the different attributes. The rating method was first designed, and then verified with five of the industry experts who participated in the AHP described earlier. The principles adopted in designing the rating method were ease of rating and objectivity during assessment.
The ideal rating method is one that allows safety auditors to allocate points to the attributes in an objective and straight forward manner. This is to minimise the probability of having two auditors getting vastly different results when evaluating the same construction worksite at the same time.
Before the actual design of the rating methods, the five experts were interviewed on what appropriate rating methods could be adopted. Based on their feedback, the research team designed a set of rating methods, which were then shown to them. The five experts agreed with the rating methods, which are now described. Four possible rating options were designed: ? 0/1 which means 0 or 1,
? 0–1 which means fraction between ‘‘0’’ and ‘‘1’’, ? 0/1/NA which means 0 or 1 or not applicable,
? 0–1/NA which means fraction between 0 and 1 or not applicable. 4.3.1. 0/1 rating option
In the 0/1 rating option, 0 means ‘No’ or ‘does not comply’, and 1 means ‘Yes’ or ‘compliance’. The 0/1 option is straightforward and objective, thus it is the most commonly used rating option. One example is attribute 01.01—‘‘Is there a list of relevant legislation, standards and codes of practice that is monitored and updated periodically?’’ under Policy Factor. If the list is found, then the rating would be 1.
建筑安全管理外文翻译文献
Otherwise, the site is rated 0 for this attribute. 4.3.2. 0– 1 rating option
The 0–1 rating option is normally applicable to an attribute that is assessed based on a set of samples. The rating is obtained by dividing the number of samples that complied with a specified standard or condition (NC ? number complied) by the total number of
samples that were evaluated (NE ? number evaluated), i.e. NC/NE.
For example, attribute 05.01(F)(iii)—‘Are the following idling plant/machinery positioned properly to prevent collapse and obstruction’ under Process Factor. The NC would be the number of idling plant/machinery that are positioned properly and NE would be the number of idling plant/machinery that had been observed on site. If NC is 5 and NE is 10, then the rating would be 0.5. 4.3.3. NA rating option
The NA option is to be used only when the attribute is not relevant in the context of that particular construction project. For example, attributes related to a specific type of work (e.g. demolition) will not be applicable to a site that does not have that particular type of work (new works).
4.4. Aggregation rule to calculate the CSI score
After rating an attribute, its score is calculated using Eq. (1) below:
Score eS1T ? Weight ew1T _ Rate er1T (1)
Where S1 is the score for Attribute 1, w1 is the relative importance of Attribute 1, r1 is the auditor’s assessment on Attribute 1 of a specific construction site. The additive method of aggregation was adopted to calculate the CSI score. In this method, the total construction safety score of each site is computed by multiplying the rating of an alternative for an attribute by the importance weight assigned to the attribute and then up summing the products over all the attributes. The value function is given in Eq. (2) below. where CSI is the total score for ith site, j is the attribute reference, and there are n number of attributes, wj is the weight assigned to jth attribute, rij is the rating given to the ith site on the jth attribute, andPmeans to sum the weighted scores over all the attributes from the 1st to the nth attribute.
The assumption of the additive model is that the attributes are independent. This means that the contribution of an individual attribute to the total score is independent of other attribute values. The rating of one attribute should not be influenced in any way by the values of the other attributes. To ensure independence, there is a need to minimise the degree of overlap or correlation among the attributes by combining or