An evaluation of alternative business excellence models using AHP
Bibliographic record
Abstract
Purpose The purpose of this paper is to compare some major National Quality Award/Business Excellence Models (NQA/BEM) in terms of the criteria employed and their relative weights. It shows that these models vary both in terms of criteria and their weights. Whereas some of them are changing weights frequently, others are almost static. It employs the analytic hierarchy process (AHP) to allocate scores to 12 criteria identified in the model by Agrawal et al. (1998) to propose a modified quality award model similar to that. The six quality award models used in the USA, Canada, Europe, Australia, Japan and India are compared with the proposed model using AHP and their relative rankings are obtained. Design/methodology/approach First, a literature review is done to identify various quality award models globally, with their features being compared. Furthermore, paired comparison technique is used to rationalize the relative weights of proposed 12 criteria, and then AHP is again used to rank this proposed model with six major award models. Findings This paper shows that the six NQA models vary substantially on parameter weights. They do not include some relevant criteria to evaluate the organizational performance holistically. It also reveals how some models have been revising criteria weights very frequently, whereas others are static. In some models, the results get much higher weightage than enablers, and hence the performance may not be sustainable. The modified Agrawal et al. (1998) model is taken as a base model, with weights rationalized in it using the AHP. The rankings obtained using AHP reveal that proposed model scores over the other six prominent quality award models. The result also reveals that for organizational excellence, the quality of people plays a major role in the successful implementation of quality processes. Hence, it is very important to focus on improving the quality of people before expecting improvement in the quality of products and services. Research limitations/implications The paired comparison results are based on the researchers’ own perception and do not consider interdependence among the criteria, which is a limitation of AHP. Analytic network process can be further explored to overcome the limitation. The proposed model has not been tested in a variety of real-world situations, which can constitute a scope for further work in the direction. Practical implications The proposed model framework and weightages evolved using AHP can provide a universally acceptable quality award model framework. The companies can adopt it with or without modifications to address their contextual adaptation. It can possibly become a standard model framework globally. This model does not capture the measurement of the softer aspects that impact the people quality. As people play an important role in the success of the implementation of any practice, hence measurement of people quality is another important aspect that can be further studied and researched. Originality/value This comparative study & analysis of National Quality Award/Business Excellence Models using AHP is presented for the first time. The authors have not come across any such studies in their literature review. This paper is an original conceptualization of the application of the AHP on the various Quality Award model parameters, and it has been submitted exclusively to JAMR for publishing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".