Decision-making under uncertainty in early-stage venture capital : a qualitative study of investor heuristics
Suomi, Emil (2026)
Pro gradu -tutkielma
2026
School of Business and Management, Kauppatieteet
Kaikki oikeudet pidätetään.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2026052958046
https://urn.fi/URN:NBN:fi-fe2026052958046
Tiivistelmä
The purpose of this study is to investigate how early-stage investors approach funding decisions in highly uncertain circumstances. The research will specifically examine how adaptive heuristics shape funding decisions for early-stage investments.
Early-stage investments are typically characterized by a lack of reliable information, ambiguity about the quality of potential investment opportunities, and the unpredictability of results. As such, traditional analytical decision-making methods are often inadequate for addressing these issues.
A qualitative research design was used as the method of investigation. Semi-structured interviews were conducted with seven early-stage investors with backgrounds in venture capital and angel investing. Thematic analysis (Gioia) was applied to the interview data to identify first-order concepts, second-order themes, and aggregated dimensions.
The research identified six major themes in how investors approached decision-making during periods of uncertainty: decision-making under uncertainty; screening/filtering heuristics; founder-based evaluation; signal-based evaluation; intuition; and experience-based pattern recognition. Investors do not rely solely on formal models to make their investment decisions. Instead, they combine rapid screening, selective interpretation of specific signals, interaction-based assessments of founders, and intuitive judgments based on prior experience. These heuristics operate sequentially and/or interactively, forming an adaptive decision-making system that is consistent with the constraints of early-stage investment environments.
This study contributes to the current body of knowledge on entrepreneurial finance by developing a process-oriented model of heuristic use in early-stage investment decision-making. In addition, it builds on prior research by showing that heuristics are not isolated cognitive "shortcuts" but integral components of a multi-stage evaluation process. Finally, the findings offer theoretical and practical implications for investors and entrepreneurs by explaining how funding decisions are made and identifying the factors that have the greatest impact on early-stage funding evaluations.
Early-stage investments are typically characterized by a lack of reliable information, ambiguity about the quality of potential investment opportunities, and the unpredictability of results. As such, traditional analytical decision-making methods are often inadequate for addressing these issues.
A qualitative research design was used as the method of investigation. Semi-structured interviews were conducted with seven early-stage investors with backgrounds in venture capital and angel investing. Thematic analysis (Gioia) was applied to the interview data to identify first-order concepts, second-order themes, and aggregated dimensions.
The research identified six major themes in how investors approached decision-making during periods of uncertainty: decision-making under uncertainty; screening/filtering heuristics; founder-based evaluation; signal-based evaluation; intuition; and experience-based pattern recognition. Investors do not rely solely on formal models to make their investment decisions. Instead, they combine rapid screening, selective interpretation of specific signals, interaction-based assessments of founders, and intuitive judgments based on prior experience. These heuristics operate sequentially and/or interactively, forming an adaptive decision-making system that is consistent with the constraints of early-stage investment environments.
This study contributes to the current body of knowledge on entrepreneurial finance by developing a process-oriented model of heuristic use in early-stage investment decision-making. In addition, it builds on prior research by showing that heuristics are not isolated cognitive "shortcuts" but integral components of a multi-stage evaluation process. Finally, the findings offer theoretical and practical implications for investors and entrepreneurs by explaining how funding decisions are made and identifying the factors that have the greatest impact on early-stage funding evaluations.