Risk-reward analysis for startup operations

Basu, Preetam (2026) Risk-reward analysis for startup operations. In: Risk-reward analysis for startup operations. Elsevier. (KAR id:115018)

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Official URL: https://doi.org/10.1016/B978-0-443-28993-4.00132-3
Additional URLs: Publisher

Abstract

Startups are essential for promoting innovation and economic progress. However, startups operate in uncertain environments with high failure rates. Key factors influencing the success of a startup include market volatility, technological innovation, and human capital. Disruptive technologies present both opportunities and risks. This chapter examines the extant literature and analyses the risk-reward in startup operations with the aim of providing insights for optimizing decision-making and improving startup success rates. We summarize an algorithm (RiskTrackr) proposed by Basu and Nair (2015) for capturing risk-reward in startup operations. Finally, we provide future research directions in this important business domain.

Item Type:	Book section
Uncontrolled keywords:	Start-ups operations; Risk-Reward; Mean Variance Analysis; Dynamic Environment
Institutional Unit:	Schools > Kent Business School
Former Institutional Unit:	There are no former institutional units.
Funders:	University of Kent (https://ror.org/00xkeyj56)
Depositing User:	Preetam Basu
Date Deposited:	13 May 2026 20:53 UTC
Last Modified:	15 May 2026 23:00 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/115018 (The current URI for this page, for reference purposes)

University of Kent Author Information

Basu, Preetam.

Creator's ORCID:	https://orcid.org/0000-0003-2645-015X
CReDIT Contributor Roles:	Project administration (Lead), Investigation (Lead), Visualisation (Lead), Data curation (Lead), Writing - review and editing (Lead), Conceptualisation (Lead), Formal analysis (Lead), Software (Lead), Writing - original draft (Lead), Validation (Lead), Methodology (Lead), Supervision (Lead), Resources (Lead)

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