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ORIGINAL PAPER
The role of risk analysis in capital budgeting decisions: A comparative study of high vs. low-risk industries
1
National Institute of Legislative and Democratic Studies (NILDS), Nigeria
2
Elizade University, Ilara-Mokin, Nigeria
3
Northeastern University, Boston, USA
A - Research concept and design; B - Collection and/or assembly of data; C - Data analysis and interpretation; D - Writing the article; E - Critical revision of the article; F - Final approval of article
Submission date: 2026-01-26
Final revision date: 2026-02-03
Acceptance date: 2026-02-13
Online publication date: 2026-06-30
Publication date: 2026-06-30
NSZ 2026;21(2):83-97
KEYWORDS
ABSTRACT
Research objectives and hypothesis/research questions:
The study aims to examine the role of risk analysis in capital budgeting decisions, compare the use of risk analysis techniques between high-risk and low-risk industries, identify barriers to effective risk integration, and assess the influence of organizational risk culture on investment decisions. It is hypothesized that advanced risk analysis techniques significantly influence capital budgeting decisions and are more prevalent in high-risk industries than in low-risk industries.
Research methods:
The study employs a comparative cross-sectional survey design with an analysis of risk analytics implementation during capital budgeting within high-risk industries, including oil and gas, pharmaceuticals, and ICT sectors, as well as low-risk industries, including utilities, consumer goods, and real estate. The designed framework enables direct time-based analysis between risk assessment methods without changing any test variables.
Main results:
Findings indicate that high-risk industries such as oil and gas and technology employ sophisticated risk analysis methods, including sensitivity analysis, scenario planning, and Monte Carlo simulations, which strongly influence project approval decisions. In contrast, low-risk industries, including education and utilities, rely mainly on NPV and IRR due to conservative risk cultures and limited technical expertise. Major barriers identified include inadequate data, a shortage of skilled personnel, and insufficient training.
Implications for theory and practice:
The study contributes to financial decision-making theory by emphasizing industry-specific risk alignment in capital budgeting. Practically, it recommends investment in advanced risk assessment systems, workforce training, and strong data infrastructure to improve strategic investment outcomes.
The study aims to examine the role of risk analysis in capital budgeting decisions, compare the use of risk analysis techniques between high-risk and low-risk industries, identify barriers to effective risk integration, and assess the influence of organizational risk culture on investment decisions. It is hypothesized that advanced risk analysis techniques significantly influence capital budgeting decisions and are more prevalent in high-risk industries than in low-risk industries.
Research methods:
The study employs a comparative cross-sectional survey design with an analysis of risk analytics implementation during capital budgeting within high-risk industries, including oil and gas, pharmaceuticals, and ICT sectors, as well as low-risk industries, including utilities, consumer goods, and real estate. The designed framework enables direct time-based analysis between risk assessment methods without changing any test variables.
Main results:
Findings indicate that high-risk industries such as oil and gas and technology employ sophisticated risk analysis methods, including sensitivity analysis, scenario planning, and Monte Carlo simulations, which strongly influence project approval decisions. In contrast, low-risk industries, including education and utilities, rely mainly on NPV and IRR due to conservative risk cultures and limited technical expertise. Major barriers identified include inadequate data, a shortage of skilled personnel, and insufficient training.
Implications for theory and practice:
The study contributes to financial decision-making theory by emphasizing industry-specific risk alignment in capital budgeting. Practically, it recommends investment in advanced risk assessment systems, workforce training, and strong data infrastructure to improve strategic investment outcomes.
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| eISSN: | 2719-860X |
| ISSN: | 1896-9380 |
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