Startup decision-making: integrating trial-and-error with the entrepreneur-as-scientist approach

Purpose In recent years, trial-and-error and entrepreneur-as-scientist approaches have gained significant traction in business model development. However, selecting the most suitable one can be challenging. This paper analyses the impact of these approaches on the performance of newly established companies to help entrepreneurs select and tailor the most suitable approach to achieve business success. Design/methodology/approach The sample consisted of 20,631 student-owned businesses from the Global University Entrepreneurship Spirits Students' Survey (GUESSS). Hierarchical regression was performed using SPSS, and AMOS was used to evaluate the goodness-of-fit of the measurement models. To ensure the model's robustness and reliability, a series of pre-tests were conducted before hypothesis testing. Findings The entrepreneur-as-scientist approach significantly enhances the relationship between solution and value proposition with business outcomes, whereas the trial-and-error approach shows limited moderation. Additionally, while solution proposal and value proposition design directly positively impact business performance, problem identification does not. Originality/value By examining the impact of trial-and-error and entrepreneur-as-scientist approaches on the success of companies founded by young university entrepreneurs, this paper adopts the organizational ambidexterity and the Popperian epistemology as a foundational framework. It introduces the ambidextrous tailoring model for experimental-structured approaches, which reconciles two seemingly incompatible entrepreneurial methodologies to serve as a guiding framework for validating nascent business models.