K-Means Clustering for Analyzing Productivity in Light of R&D Spillover

International Journal of Information Technology, Modeling and Computing (IJITMC) Vol. 4, No.2, May 2016

10 Pages Posted: 27 Jan 2020

See all articles by R. S. Kamath

R. S. Kamath

Chhatrapati Shahu Institute of Business Education

R. K. Kamat

Shivaji University

Date Written: 2019

Abstract

The differences between countries go far beyond the physical and territorial aspects. Hence, for analytical purposes, it is essential to classify countries in groups based on some of their attributes. Investment in Research and Development (R&D) influences innovations which in turn stimulates growth of a country. In this context the productivity of the R&D expenditure is analysed pragmatically. Present study aims to discover impact of R&D expenditure on its productivity in terms of number of journal articles published, patent applications filed and trademark applications registered. A more significant analysis by means of designing prominent clusters of countries by applying unsupervised learning has been presented. In this division, percentage of Gross Domestic Product (GDP) spending on R&D and its productivity are considered.

Keywords: R&D Productivity; Data Mining; Clustering; Unsupervised Learning

Suggested Citation

Kamath, R. S. and Kamat, R. K., K-Means Clustering for Analyzing Productivity in Light of R&D Spillover (2019). International Journal of Information Technology, Modeling and Computing (IJITMC) Vol. 4, No.2, May 2016. Available at SSRN: https://ssrn.com/abstract=3509618

R. S. Kamath (Contact Author)

Chhatrapati Shahu Institute of Business Education

Kolhapur
India

R. K. Kamat

Shivaji University

Kolhapur
416004
India

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
16
Abstract Views
84
PlumX Metrics