Evaluation and analysis of criteria and sub-criteria of a ... - Emerald
Evaluation and analysis of criteria and sub-criteria of a ... - Emerald Evaluation and analysis of criteria and sub-criteria of a ... - Emerald
ECAM15,134assessed in the Questions 2 and 3 of the questionnaire as to their importance indefining their underlying criterion, and their actual effectiveness in the companies ofthe respondents, as can be seen in the Appendix (Figure A1). The sub-criteria of themodel are confirmed in a manner very much similar to that of the model criteria,through assessing their importance and through a factor analysis to ensure the singleconstruct structure.Importance of sub-criteria in defining underlying criterionThe results of the importance of each sub-criterion in defining its criterion in the formof the means, standard deviations and 5 per cent lower confidence limits werecomputed on an Excel spreadsheet, using its built-in functions in a similar manner tothe model criteria. The results show that the mean and lower confidence limits ofsub-criteria were all above average and inclined towards the scale maximum of fivepoints, hence confirming the importance of each sub-criterion in defining its underlyingcriterion. Furthermore, the negative skewness of these items indicate that even if a fewof these distributions are not normal, they are nevertheless peaked and negativelyconcentrated towards the upper end of the scale, as explained with the importance ofthe criteria previously. Thus, the actual confidence limits are expected to be higherthan those reported.Factor analysis of sub-criteria underlying a criterionThe results of the effectiveness assessment of each sub-criterion were used in factoranalysis to determine the single factor structure, which was previously conducted inthe discussion of the content validity and was demonstrated in Table II and Figure 3for the Leadership criterion. The factor analysis in all other criteria showed only onefactor is to be extracted and thus confirms the single factor structure assumed in thecriteria of the model.Calculation of model criterion weightsThe scoring system of the EFQM Excellence Model has been shown to vary acrossindustries and has been criticised as not corresponding to the way companies areworking (Eskildsen et al., 2001). Different methods for assessing the actual weights ofthe model’s criteria have been reported in literature. For example, Eskildsen et al. (2001)used factor regression coefficients. Cheng and Li (2001) used the analytic hierarchyprocess (AHP) to determine the weights of performance measures of a businessprocess. It is difficult to assess which method is more accurate. Nevertheless, any of theempirical approaches mentioned would be preferred to “an arbitrary weight structure,which has never been empirically tested” (Eskildsen et al., 2001, p. 783), as with thecase of EFQM. Furthermore, a method that has been previously applied to excellencemodels would be preferred. The factor regression coefficients method was chosen inthis research because it assesses the actual impact of each criterion on theorganisation’s performance, whereas with AHP requires expert judgement data thatcan be obtained from the importance rating of each criterion, but might affect theaccuracy of outcomes in the paired comparisons process, as well as reflecting theimportance perception rather than actual impact.
To compute the regression coefficients of the criteria relevant to one another, theyneed to be loaded on a single factor. Hence, the CFA Model of Figure 6, was used toreflect such a single factor structure. In this model, each of the criteria is loaded on alatent variable termed “excellence”. The regression coefficients are computed for eachcriterion in predicting the latent variable “excellence”. The computations were carriedout on SPSS, and the results are illustrated in Table III. Moreover, the coefficients intheir crude format might not be suitable for excellence scoring calculations and need tobe presented in a more workable format. Therefore, weights for each criterion werecalculated on an Excel spreadsheet such that the total weight of all criteria is 1,000.This was achieved by dividing the coefficient of each criterion by the total of allcoefficients and multiplying the result by 1,000.A constructionexcellence model35Benefits and limitationsThe main benefit of the Construction Excellence Model is that it provides an excellencemodel developed for and evaluated by construction companies. It has a morecomprehensive and wider coverage of performance criteria than other excellencemodels. Its underlying logic is also easier to understand and more user friendly. Thelimitation of the suggested model is that, as in all other models, it is only as good aswhoever uses it. Thus, the model is merely a tool that clarifies what needs to bemeasured/improved, but in no way can guarantee success of the organisation. Forexample, if management pursues an inappropriate strategy or the economy takes adownturn, the organisation’s performance would most certainly be affected, no matterhow efficient the business models it uses. However, the use of the suggested model isexpected to raise the chances of success and increase organisational performance inrelation to competitors. Furthermore, the use of the Construction Excellence Model, byits nature, is targeted towards project-based industries, specifically construction, andScore coefficientsCriterion weightsLeadership 0.0967 71Customer focus 0.0928 68Other stakeholder focus 0.0738 54Information and analysis 0.0877 65Strategic management 0.0939 69Intellectual capital management 0.0914 67People management 0.0903 67Partnership and supplier management 0.0952 70Resource management 0.0779 57Risk management 0.0890 66Process management 0.0712 53Work culture 0.0610 45Project performance 0.0833 61Organisational performance 0.0833 61Internal stakeholder performance 0.0778 57External stakeholder performance 0.0931 69Total 1.3584 1,000Table III.Component scorecoefficients andcriterion weights
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To compute the regression coefficients <strong>of</strong> the <strong>criteria</strong> relevant to one another, theyneed to be loaded on a single factor. Hence, the CFA Model <strong>of</strong> Figure 6, was used toreflect such a single factor structure. In this model, each <strong>of</strong> the <strong>criteria</strong> is loaded on alatent variable termed “excellence”. The regression coefficients are computed for eachcriterion in predicting the latent variable “excellence”. The computations were carriedout on SPSS, <strong>and</strong> the results are illustrated in Table III. Moreover, the coefficients intheir crude format might not be suitable for excellence scoring calculations <strong>and</strong> need tobe presented in a more workable format. Therefore, weights for each criterion werecalculated on an Excel spreadsheet such that the total weight <strong>of</strong> all <strong>criteria</strong> is 1,000.This was achieved by dividing the coefficient <strong>of</strong> each criterion by the total <strong>of</strong> allcoefficients <strong>and</strong> multiplying the result by 1,000.A constructionexcellence model35Benefits <strong>and</strong> limitationsThe main benefit <strong>of</strong> the Construction Excellence Model is that it provides an excellencemodel developed for <strong>and</strong> evaluated by construction companies. It has a morecomprehensive <strong>and</strong> wider coverage <strong>of</strong> performance <strong>criteria</strong> than other excellencemodels. Its underlying logic is also easier to underst<strong>and</strong> <strong>and</strong> more user friendly. Thelimitation <strong>of</strong> the suggested model is that, as in all other models, it is only as good aswhoever uses it. Thus, the model is merely a tool that clarifies what needs to bemeasured/improved, but in no way can guarantee success <strong>of</strong> the organisation. Forexample, if management pursues an inappropriate strategy or the economy takes adownturn, the organisation’s performance would most certainly be affected, no matterhow efficient the business models it uses. However, the use <strong>of</strong> the suggested model isexpected to raise the chances <strong>of</strong> success <strong>and</strong> increase organisational performance inrelation to competitors. Furthermore, the use <strong>of</strong> the Construction Excellence Model, byits nature, is targeted towards project-based industries, specifically construction, <strong>and</strong>Score coefficientsCriterion weightsLeadership 0.0967 71Customer focus 0.0928 68Other stakeholder focus 0.0738 54Information <strong>and</strong> <strong>analysis</strong> 0.0877 65Strategic management 0.0939 69Intellectual capital management 0.0914 67People management 0.0903 67Partnership <strong>and</strong> supplier management 0.0952 70Resource management 0.0779 57Risk management 0.0890 66Process management 0.0712 53Work culture 0.0610 45Project performance 0.0833 61Organisational performance 0.0833 61Internal stakeholder performance 0.0778 57External stakeholder performance 0.0931 69Total 1.3584 1,000Table III.Component scorecoefficients <strong>and</strong>criterion weights
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