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Aug 24, 2026·Economics and Public Policy
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Measuring Enterprise Digital Readiness in Manufacturing: Multi-Dimensional Index Construction, Structural Heterogeneity, and Longitudinal Spatiotemporal Evolution

Guilei Tan, Rozaini Rosli

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.

Open access
Digital Transformation in Industry
Big Data and Business Intelligence
Technology Assessment and Management
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