MODELING AND ANALYSIS OF GLOBALIZING MANUFACTURING SME S IN DEVELOPING ECONOMIES

Abstract

The work undertaken in the dissertation is of pioneering nature integrating world databases to accrue knowledge about economies and enterprises around the globe. It is an endeavor to demonstrate the adequacy of applying data mining techniques in global databases concealing heaps of knowledge about enterprises engaged in manufacturing and exporting in the global context. A cohesive and coherent exploration of databases from repositories of World Bank, GEM, WEF and IFC’s Enterprise Survey elucidates the patterns of internationalization of enterprises through manufacturing exports in developed and developing economies. We have followed inductive reasoning methodology using symbiosis of statistical modeling and data mining coupled with extensive data visualizations. The exploratory research has asserted the fitness of manufacturing exports as the core engine for economic health of a country. Both Kruskal-Wallis and Chi-square tests affirm that manufacturing export share level is not independent of economy type and, developed economy block shares 77% of world manufacturing exports matching to their share in world GDP. Manufacturing exports per capita for world five economies ranks them exactly analogous to their income-group ranks. The predictive MLR modeling reveals a positive relationship between GDP and manufacturing exports for LMC and UMC economies. LMC economy countries have the prospects of 14% increase in GDP share by unit increase in manufacturing export share. The findings from the global databases regarding economies and enterprises in these economies are in unison. The enterprises of the developing economies (LIC, LMC and UMC) have more inclination towards manufacturing than economies and enterprises of developed (NOC, OEC) block. However, the enterprises of developed economy block lead by a significant margin in terms of exporting and manufacturing exports. The enterprises of LIC economy block portrays an exorbitant despondency in all spheres of activities ranging from manufacturing to exporting with pathetic state of entrepreneurial climate culminating in extreme level of poverty. Enterprises in Pakistan portray a posture identical to other countries of LMC economy. K-means and HCA clustering identify LFE (Large, Foreign and Exporter) enterprises in Pakistan to form one group and align their practices benefiting from information and communication technologies (ICT) to boost and spearhead the internationalization through exports. Both statistical and data mining methodologies work in unison to identify characteristics of a Pakistani SME to be exportable. Registration with original equipment manufacturer (OEM) is a significant key determinant for an enterprise to acquire the exporting status.