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  market controlling 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.  

Keyword:  Business  opportunity  evaluation,  decision  making  under  uncertainty,  data-driven entrepreneurship