Measuring Enterprise Digital Readiness in Manufacturing: Multi-Dimensional Index Construction, Structural Heterogeneity, and Longitudinal Spatiotemporal Evolution

Abstract

Accurately quantifying enterprise digital capability is fundamental to evaluating industrial modernization, yet conventional empirical inquiries predominantly rely on single-dimensional proxy variables or unweighted keyword counts, failing to capture the multidimensional integration of digital assets. Moving beyond causal regression paradigms and reductionist metrics, this inquiry develops a comprehensive, objective Digital Readiness Index (DRI) for physical manufacturing enterprises using an information-theoretic Entropy Weight Method (EWM). Grounded in multi-source text-mining disclosures and corporate balance sheets across 41,756 firm-year observations of Chinese A-share listed manufacturing enterprises spanning 2000 to 2025, the evaluation framework integrates eight discrete operational indicators across three dimensions: Technical Depth (AI, Big Data, Cloud Computing, Blockchain, and Digital Applications), Intangible Capital Endowments, and Governance Oversight. Objective entropy weighting demonstrates that specialized frontier technologies, particularly Blockchain (w=37.81%), Artificial Intelligence (w=15.95%), Big Data Analytics (w=15.93%), and Cloud Computing (w=15.66%)—constitute the primary sources of informational divergence across manufacturing firms. Longitudinal trajectory evaluation reveals a sustained upward trajectory in mean digital readiness, accelerating markedly after the 2015 macroeconomic policy inflection point. Non-parametric Gaussian Kernel Density Estimation uncovers a distinct dynamic polarization pattern, characterized by a shifting rightward distribution and an elongating upper tail. Cross-sectional decomposition establishes substantial structural disparities: high-tech sectors such as Computers and Electronics exhibit the highest mean digital readiness (DRI=16.28), whereas chemical and pharmaceutical sectors display persistent digital inertia (DRI≈4.06). Furthermore, non-state-owned enterprises (Non-SOEs) systematically outperform state-owned enterprises (SOEs) across all asset scale tiers. These findings provide an objective measurement tool and benchmark for corporate technology auditing and industrial policy calibration.