Improved Model of Global Quality Infrastructure Index (GQII) for Inclusive National Growth

The Quality Infrastructure (QI) of a country relies on 4 major pillars i.e. metrology, standardization, accreditation, and certification. These pillars are closely associated and build a system of national and international organizations for barrier-free trade following relevant, standards, guides, rules and regulations, policies, protocols, etc. The recently developed Aswal model for the effective and robust QI system clearly explains the mechanisms wherein metrology as a core pillar and an invisible force, in association with documentary standards, accreditation, and conformity assessment facilitates the strong interactions among the Government agencies; Universities and Academic Institutions; Science and Technology Institutions; Citizens, Media and industry, for the comprehensive development and inclusive growth of the country for improved quality of life. Ulrich and Matteo proposed a Global Quality Infrastructure Index (GQII) as an indicator to measure the growth and the performance of QI of an economy. In the present paper, improved model is proposed for the GQII. A case study is presented using the improved GQII and utilizing the data available in the public domain i.e. BIPM website related to member states countries (62 countries). Further, the Global Competitiveness Index (GCI) which is used to measure the institutions, policies, and the effective use of available resources for sustainable prosperity and level of prosperity of their citizen is studied and compared with GQII for some of the leading economies. The study also depicts the export status of the leading economics with the GQII. The study clearly indicates the correlation of GQII with various influencing components i.e. calibration and measurement capabilities (CMCs), key and supplementary comparisons (K&SCs), gross domestic product (GDP) per Capita, and % expenditure of GDP incurred on education. GQII value is normally higher with higher participation in key comparisons and having a higher number of CMCs. Similarly, the same trend is obtained between GQII and GDP per capita as well as the % expenditure of GDP incurred on education. The Indian data related to these parameters is also presented and discussed. Admittedly, though utmost care is taken to accommodate the most relevant and latest information and earlier published work, some of the unnoticed discrepancies are not ruled out, which may be unintentional. The study would be very helpful for the government agencies, industry, academia, and enterprises for future decisions and policymaking related to strong and robust QI