DYNAMIC DECISION-MAKING FRAMEWORK FOR EVALUATING THE MARKET POTENTIAL AND SUCCESS OF INNOVATIVE STARTUPS ON THE BASIS OF A MARKETING RESEARCH APPROACH USING R

Abstract

Currently, the world is highly dependent on technological advancements and innovations (TAI) being the key driver of economic growth, competitiveness, and overall societal progress. And high-tech startups are at the forefront of TAI, developing new products and services that meet the growing needs of consumers. Over the past decades, the quantity and quality of startups have increased significantly, however, they are still known for high risks and low success rates, which often lead to financial losses for investors and startup founders. Therefore, the aim of the study was to develop a dynamic decisionmaking framework for evaluating the market potential and success rates of innovative startups throughout their lifecycle on the basis of a marketing research approach using R programming language to provide a unique solution for startup founders, investors, business incubators, startup accelerators, tech hubs, etc. As a result, a new methodology for evaluating the market potential and success rates of innovative startups was proposed based on T. L. Saaty’s analytic hierarchy process (AHP) methodology. Taking into account the fact that AHP is based on expert opinions, it was proposed to divide experts into five groups – scientific specialists, investors representatives, manufacturers representatives, practicing startup entrepreneurs, business incubators & startup accelerators representatives. Each group of experts determined the degrees of preference between the proposed criteria and sub-criteria of each of the three components of startup attractiveness – market, marketing and investment attractiveness of the startup project. The decision-making framework was created and tested in the RStudio software environment based on the ‘ahp’ package and can be used by startup founders, investors, and other stakeholders on a regular basis as new information about their projects becomes available.

Keywords

• startup marketing
• marketing research
• startup management
• r programming
• analytic hierarchy process
• rstudio
• innovations marketing