Valuing Industrial Data Products as Decision Systems: A Parameter-Governed Cost–Premium Framework for Oil and Gas Data Assets
Year: 2026
Type: article
Abstract: Industrial data products create economic value through embodied technical resources, current decision use, and future deployment rights. This article develops a Cost–Premium Valuation System (CPVS) that measures these channels as a quality-adjusted cost anchor, a data-attributable utility premium, and an activation-adjusted real-option premium. A recoverability coefficient connects the cost term to current technical, legal, and commercial usability, and an integration weight combines recoverable cost evidence with the business-based value indication. The application concerns a geological simulation and prediction model for oil and gas reservoirs. Enterprise records and two structured five-expert procedures produce a quality coefficient of 0.854 and a data-factor contribution rate of 47.6%. The cost anchor is CNY 166.957 million, the utility premium is CNY 143.544 million, and the option premium is CNY 87.078 million, giving an integrated value of CNY 205.156 million at an integration weight of 0.60. A fourteen-parameter analysis and 10,000 triangular draws yield a 5th–95th percentile range of CNY 181.368–214.347 million. Black–Scholes, a five-step CRR lattice, and a three-tranche rollout tree produce activation-adjusted option values within 1.04% of one another. The Reliability-Weighted Parameter Exposure index equals 0.4227 and ranks the inputs by combined value influence and evidence priority. CPVS thereby connects technical condition, cash flow, deployment readiness, and evidence quality with data maintenance, investment review, reuse preparation, and transaction design.
Source: Systems
Authors: Lujia Yang, Hongbao Yu, Zhiming He
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G1822511033
OpenAlex ID: W7202396842