DATA DRIVEN ENTREPRENEUR ANALYSIS FOR BUSINESS OPPORTUNITY EVALUATION

Abstract

High market uncertainty makes it difficult for an entrepreneur to assess the status of
the market for a business opportunity. Data gathering and analysis techniques and technology are
becoming a significant source of uncertainty management for many entrepreneurial endeavours. This
is sometimes referred to as "data-driven entrepreneurship." We examine a datadriven dynamic method
to overcoming market uncertainty in business opportunity appraisals. We focus on the entrepreneur's
investment portfolio, in which each investment generates projected returns as well as knowledge on a
certain market element for a single company opportunity. We create a model that evaluates imperfect
market data (e.g., financial, social, and regulatory) while taking into account the entrepreneur's risk
tolerance and operational resource, routine, reputation, and regulatory constraints. Our numerical
findings indicate that, rather of seeking the best projected returns, an entrepreneur may pick perfect
information, risk hedging, or marketcontrolling investments based on his or her cash level and risk
tolerance. As a result of the availability of data analysis, the entrepreneur may overcome uncertainties
and get superior insights for business opportunity judgments.