Net Present Value As a Decision Tool During Investment: Evaluating the Effectiveness of Net Present Value (NPV) Against Traditional Investment Appraisal Techniques in Predicting the Financial Success of Technology Startups

Jiayi Lin; Junhao Dong; Yihan Zheng

doi:10.54254/2754-1169/2024.26903

Advances in Economics, Management and Political SciencesOpen access

Net Present Value As a Decision Tool During Investment: Evaluating the Effectiveness of Net Present Value (NPV) Against Traditional Investment Appraisal Techniques in Predicting the Financial Success of Technology Startups

Research Article

Open Access

Net Present Value As a Decision Tool During Investment: Evaluating the Effectiveness of Net Present Value (NPV) Against Traditional Investment Appraisal Techniques in Predicting the Financial Success of Technology Startups

Jiayi Lin ¹, Junhao Dong ², Yihan Zheng ^3*

¹ University of Syndey

² Tulane University

³ Southland School

^*Corresponding author: duegn@icloud.com

Published on 16 September 2025

AEMPS Vol.217

ISSN (Print): 2754-1177

ISSN (Online): 2754-1169

ISBN (Print): 978-1-80590-363-5

ISBN (Online): 978-1-80590-364-2

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Abstract

This work studies whether the net present value (NPV) is a more effective investment appraisal tool than other traditional methods like internal rate of return (IRR) and payback period in forecasting the financial success of tech startups. The major task for financial forecasting is due to volatility, fast growth of tech startups, varying consumer preferences. Our study assesses these valuation methods not only by statistical regression analysis but also by examining various companies like Airbnb and Booking.com as a case study. The findings indicate that although NPV can be very informative about financial performance in the long run, the analysis is enriched when IRR and period of return are also included. Using this holistic method in technology investment valuation should minimize risk and improve decision-making, especially in the high-risk field of rapidly growing technology firms.

Keywords:

Net Present Value, Technology Start Up, Payback Period, Regression Model, PCF Model

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References

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References

[1]. Braun, R. (2009). Risk of private equity fund-of fund investments—A detailed cash flow-based approach, SSRN Electronic Journal.

[2]. Charsios, G., Moutafidis, K., & Foroglou, G. (2016). Valuation model for Internet-of-Things (IoT) startups (Conference Paper).

[4]. Visconti, R. M. (2020). The valuation of technological startups. In Springer eBooks (pp. 155–192). https://doi.org/10.1007/978-3-030-36918-7_6

[5]. Myers, S. C., & Majluf, N. S. (1984). Corporate financing and investment deci-sions when firms have information that investors do not have. Journal of Financial Economics, 13, 187–221.

[7]. Nwogugu, M. C. I. (2016). Anomalies in net present value, returns and polynomials, and regret theory in decision-making. Palgrave Macmillan.

[9]. Smith, C. W., & Warner, J. (1979). On financial contracting: An analysis of bond covenants. Journal of Financial Economics, 7 (2), 117–161.

[10]. Venture Valuation. (2019). Valuation methods. Available at https://www.venturevaluation.com/en/ methodology/valuation-methods.

Cite this article

Lin,J.;Dong,J.;Zheng,Y. (2025). Net Present Value As a Decision Tool During Investment: Evaluating the Effectiveness of Net Present Value (NPV) Against Traditional Investment Appraisal Techniques in Predicting the Financial Success of Technology Startups. Advances in Economics, Management and Political Sciences,217,41-60.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of the 4th International Conference on Financial Technology and Business Analysis

ISBN: 978-1-80590-363-5(Print) / 978-1-80590-364-2(Online)

Editor: Lukáš Vartiak

Conference website: https://2025.icftba.org/

Conference date: 12 December 2025

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.217

ISSN: 2754-1169(Print) / 2754-1177(Online)

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