Nonparametric decision tree: The impact of ISO 9000 on certified and non certified companies

José António Figueiredo Almaça, Joaquín Texeira Quirós, Maria do Rosário Fernandes Justino

Abstract


Purpose: This empirical study analyzes a questionnaire answered by a sample of ISO 9000 certified companies and a control sample of companies which have not been certified, using a multivariate predictive model. With this approach, we assess which quality practices are associated to the likelihood of the firm being certified.

Design/methodology/approach: We implemented nonparametric decision trees, in order to see which variables influence more the fact that the company be certified or not, i.e., the motivations that lead companies to make sure.

Findings: The results show that only four questionnaire items are sufficient to predict if a firm is certified or not. It is shown that companies in which the respondent manifests greater concern with respect to customers relations; motivations of the employees and strategic planning have higher likelihood of being certified.

Research implications: the reader should note that this study is based on data from a single country and, of course, these results capture many idiosyncrasies if its economic and corporate environment. It would be of interest to understand if this type of analysis reveals some regularities across different countries.

Practical implications: companies should look for a set of practices congruent with total quality management and ISO 9000 certified.

Originality/value: This study contributes to the literature on the internal motivation of companies to achieve certification under the ISO 9000 standard, by performing a comparative analysis of questionnaires answered by a sample of certified companies and a control sample of companies which have not been certified. In particular, we assess how the manager’s perception on the intensity in which quality practices are deployed in their firms is associated to the likelihood of the firm being certified.


Keywords


Quality; ISO9000; Decision Trees, Performance

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DOI: https://doi.org/10.3926/ic.303


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Intangible Capital, 2004-2024

Online ISSN: 1697-9818; Print ISSN: 2014-3214; DL: B-33375-2004

Publisher: OmniaScience