Probabilistic Interpretation of Entrepreneurial Opportunity Using the Many-Worlds Model

Abstract

This research engages with the uncertainties and unknowable in entrepreneurship with literature on the philosophy of quantum mechanics in an analogical way. Often characterized as a journey into an uncertain future, entrepreneurship stands out as a dynamic and unpredictable domain driven by a compelling and indefinable force. This research’s central argument revolves around the notion that within the entrepreneurial landscape, many latent propensities exist, each carrying its distinct probability of manifesting into various outcomes. Unlike a deterministic process with a single predetermined outcome, entrepreneurship is a complex interplay of potentialities. To capture this multifaceted perspective, we leverage the principles and formalism of quantum mechanics, renowned for its emphasis on potentiality over actuality until subjected to observation and action. This philosophical framework describes the inherent potentialities embedded within entrepreneurial opportunities. This study introduces a groundbreaking Many-Worlds model inspired by the interpretations of quantum mechanics. In this model, the act of observation serves as a catalyst, unraveling a spectrum of potential outcomes, each characterized by its probability. These potentialities materialize based on entrepreneurs’ intentional actions and decisions, reflecting their commitment to shaping the future of their ventures. In summary, our study bridges the gap between entrepreneurship and quantum mechanics by proposing a novel framework that portrays entrepreneurship as an exploration of a quantum-like landscape of possibilities. By emphasizing the significance of intentionality and action, our research sheds new light on entrepreneurship’s dynamic and unpredictable nature, illustrating how entrepreneurs play a pivotal role in transforming potential into reality.

Received: 8 November 2023 | Revised: 26 December 2023 | Accepted: 10 January 2024

Conflicts of Interest 

The author declares that he has no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.