Abstract

Exploring and conceptualizing different aspect of entrepreneurship is top priority of policymakers at present days. Importance of entrepreneurial research is increasing day by day in the present complex and changing business environment. In this regard, it has become absolutely pertinent to re-examine the mechanism of interaction between environment and personality in entrepreneurial ecosystem to understand its impact on entrepreneurial development on MSME perspectives. Perfect interaction of personality characteristics with institutional variables can lead towards sustainable development. Significant personality characteristics or optimum business environment can’t alone make any difference. It is the magnitude of proper interaction between them which can increase the resultant vector in many folds. An attempt has been made in this paper to identify the significant interaction variables that can create impact during different entrepreneurial growth stage. The research is of a dynamic and multiregional structure and was conducted on the target sample based on the longitudinal study of GEDI (Global Entrepreneurship Development Institute report) report 2012-2016. The study confirms that interaction within ecosystem is complex as well as different in nature for different stage of business. The present study also explores the intricate situation and developed a suitable model for each stage of business development. The most notable part of this study is considering the heteroscedasticity and autocorrelation of the data. Panel Corrected Standard Error (PCSE) model has been used in our paper. The analysis of the present study indicates the positive and negative interaction variables for each stage of business development that can be used for policy making considering the present situation of the country. Notation Used: In equation [1], [2], [3], i indicates individual Country, t indicates year, indicate Nascent Entrepreneurship Rate, Established Business Ownership Rate and Sustainability. α and β are coefficients and € indicate error term. In equation [4] X represents the explanatory variables, whereas Ω is the covariance matrix for all error terms.

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