{"title":"Funding Breakthrough Innovation: The Theory of Value Translation","authors":"Elisa Alvarez-Garrido","doi":"10.5465/amproc.2023.15059abstract","DOIUrl":null,"url":null,"abstract":"Breakthrough (high-impact) innovation often happens at startups, which need to attract funding in the early stages of these high-risk/high-reward projects. Extant research argues that investors lack appetite for the high risk; I argue that assessing the high reward is also challenging, since the invention could develop into innovation along multiple technological trajectories of different value. I develop the theory of value translation, a theoretical framework to analyze how the knowledge of investor and startup and the characteristics of the innovation affect the decision to fund the project. The investor and startup need to map and evaluate all possible trajectories to understand which has maximum value—loosely defined as financial, strategic, scientific, or societal. Mapping the technological trajectories, however, requires that one organization possess both knowledge about the science and technology, in order to understand which trajectories are feasible, and knowledge about the commercialization, in order to understand which trajectories are valuable. Startups tend to have more scientific/technological knowledge, and investors more commercialization knowledge. With incomplete knowledge, there is a dual bounded rationality problem: fewer trajectories are mapped, leading to a gap in valuation. This gap, or the value translation problem, is exacerbated for novel or complex innovations, which have greater knowledge requirements. Breakthrough innovation may indeed be underfunded and the theory points to a potential solution: organizations armed with knowledge of business and science can bridge the gap. This theory is inspired by fifteen interviews with life sciences investors and startups.","PeriodicalId":471028,"journal":{"name":"Proceedings - Academy of Management","volume":"212 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings - Academy of Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5465/amproc.2023.15059abstract","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Breakthrough (high-impact) innovation often happens at startups, which need to attract funding in the early stages of these high-risk/high-reward projects. Extant research argues that investors lack appetite for the high risk; I argue that assessing the high reward is also challenging, since the invention could develop into innovation along multiple technological trajectories of different value. I develop the theory of value translation, a theoretical framework to analyze how the knowledge of investor and startup and the characteristics of the innovation affect the decision to fund the project. The investor and startup need to map and evaluate all possible trajectories to understand which has maximum value—loosely defined as financial, strategic, scientific, or societal. Mapping the technological trajectories, however, requires that one organization possess both knowledge about the science and technology, in order to understand which trajectories are feasible, and knowledge about the commercialization, in order to understand which trajectories are valuable. Startups tend to have more scientific/technological knowledge, and investors more commercialization knowledge. With incomplete knowledge, there is a dual bounded rationality problem: fewer trajectories are mapped, leading to a gap in valuation. This gap, or the value translation problem, is exacerbated for novel or complex innovations, which have greater knowledge requirements. Breakthrough innovation may indeed be underfunded and the theory points to a potential solution: organizations armed with knowledge of business and science can bridge the gap. This theory is inspired by fifteen interviews with life sciences investors and startups.