Research data

Data Document Description

Research Hypothesis: This study aims to validate a core hypothesis: in the context of energy economic transformation, the key factors influencing enterprises' adoption of Supply Chain Economic Substitutes (SCES) include not only traditional perceptions of usefulness and policy support but are also significantly affected by organizational-level perceptions of ease of use and behavioral economics concepts such as loss aversion. It is hypothesized that barriers related to technological ease of use and enterprises' psychological tendencies towards loss aversion together constitute significant behavioral obstacles.

Data Content and Collection Method: This dataset was generated through a structured computational experiment designed to create a controlled "theoretical laboratory." The data simulates decision-making behaviors from 855 companies across four key industries, including manufacturing and energy, over the period from 2017 to 2024, resulting in a total of 6,840 observations. Core variables include SCES adoption intensity, perceived usefulness (PU), perceived ease of use (PEOU), perceived behavioral control (PBC), estimated enterprise loss aversion coefficient (λ) using Bayesian methods, policy support index, market uncertainty, and technology readiness; all variables are measured on a scale from 0 to 10.

Main Findings and Data Interpretation: The results from data analysis strongly support the research hypothesis.
1. Perceived Ease of Use as a Key Driver: Its overall effect on enterprise attitudes is quantified at 0.486, highlighting the importance of reducing technological application complexity.
2. Loss Aversion Constituting Significant Barriers: The estimated average loss aversion coefficient λ for enterprises is found to be 1.70 with industry heterogeneity observed (highest in manufacturing at λ=2.29). This indicates that fear of potential losses substantially hinders their adoption decisions.
3. Policy Simulation Revealing Effective Pathways: Data suggests that scenarios combining policies with enhancements in ease-of-use can most effectively overcome behavioral barriers; by the end of year eight, this approach could elevate adoption rates to 82.2%.

Data Usage Guidelines: This dataset supports replication studies aimed at reproducing empirical results presented in this paper—including descriptive statistics, correlation analyses, Bayesian structural equation modeling estimates, and foundational policy simulations.