Sahney, S. (2019), "A response to “A research note on the article of ‘Quality framework in education through application of interpretive structural modeling’”", The TQM Journal, Vol. 31 No. 1, pp. 11-11. https://doi.org/10.1108/TQM-12-2018-00002Download as .RIS
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With the assumption that the satisfaction of the external customer would have to be preceded by the satisfaction of the internal customer, our paper “Quality framework in education through application of interpretive structural modeling: an administrative staff perspective in the Indian context” presented the results of an empirical study conducted on the administrative staff of educational institutions, so as to obtain the internal customer’s perspective on quality through the application of interpretive structural modeling (ISM). Based on the literature review and an earlier study based on the quality function deployment technique, certain elements, indicators and strategic issues in quality assessment were identified. The ISM was applied to prioritize these elements qualitatively, and thereby propose a hierarchical structure based on sequencing, and categorization.
This study was conducted with the objectives of:
identifying the design characteristics of a system that would meet the requirements of the administrative staff as an internal customer of the educational system; and
sequencing, categorizing and prioritizing these design characteristics and then structuring these into a comprehensive systemic model which when adopted would lead to quality from an internal customers’ perspective.
Our response to the critique:
We used the binary-based structural model, where there are very less chances of transient linkages as is evident in our study.
The objective of the paper was not to lay focus on the “cause and effect” analysis amongst different design elements used in the study. The paper did not deal with the driver power and dependence power amongst two elements like relay or linkage variables and autonomous or exogenous variables. The objective of my study was to identify driver, enabler/facilitator and dependent relationships between the design characteristics and arrange them structurally (MICMAC is essentially done to determine the driver power and dependence power through clusters). Because, the identification of linkage and autonomous variables, and the assessment of the driver and dependence power amongst enablers lay beyond the scope of my study, MICMAC was not used.
Further, the final structural hierarchical model was made using ISM itself, and the MICMAC analysis seemed unnecessary.
The paper was double blind reviewed by your esteemed publishing house, and our findings were found to be satisfactory for the context and period under study.