Start-ups are increasingly seen as drivers of sustainable transformation by developing, adapting and applying new technologies and new disruptive business models. However, entrepreneurs that strive to promote a sustainability transition face a complex task to address sustainability, on top of creating a venture that survives and grows. In reality the rational of receiving public or private financial funding is biased towards creating economic value and hence rational acting entrepreneurs might have the tendency of prioritizing economic goals rather than social, societal or ecological goals, particularly throughout stages of their development. In addition, capturing the sustainable impact of start-ups most often remains vague and anecdotal. Identifying business models with high sustainable impact is time-consuming, cost-intensive and often inaccurate. Given complexity and time constraints, experts judgements may suffer (e.g., repetitive, exhaustion, analytical limitations) relying on potentially biased assumptions or simple "gut feelings" that function as shortcuts. The literature distinguishes between the following three categories of accounting frameworks. First, scorecards in which startups gather KPIs to track their performance. Second, process-based approaches that collect data structured along an input-output-outcome-impact logic. Third, synthetic indicators that allow comparison of impacts between different organizations by providing a global measure of a venture's performance. The most prominent of the latter category is the SROI (social return on investment) indicator that uses self and expert assessment in a longitudinal approach to evaluate different types of impacts of the social program. A drawback of all these approaches to measure sustainable impact is that they are based on isolated subjective assessments or costly manual work from experts.

This Special Issue addresses exactly this issue by looking for papers that present, test and validate measurement instruments that capture the sustainable impact of early-stage business models. The measurement instruments should overcome the deficiencies of current applications (a) by measuring sustainable impact of early-stage start-ups valid and reliable; (b) by being cost and time efficient; and (c) by presenting triangulated assessments rather than isolated judgements. The methodology of the investigated measurement instruments is open from more qualitative approaches based on interviews, external judgements and observations via more quantitative analytics based on documents and surveys to AI guided information gathering, data crunching and measuring. Also, meta-analysis and systematic literature analysis and instrument/tool collections are appreciated.

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