Leveraging Probabilistic Optimization for Digital Transformation Maturity Evaluation of Construction Enterprises
针对建筑企业数字化转型评估不足，提出一个包含成熟度模型和公平感知集体意见生成范式的框架，通过贝叶斯最优最劣法和双目标优化模型提高评估准确性，并以中建三局为例验证可行性。
The construction industry's digital transformation is lagging despite accelerated digital technology development necessitating business adaptation. While individual digital technologies have received some focus, comprehensive evaluations and recommendations concerning digital transformation remain scarce. Maturity assessment models comprehensively evaluate an organization's state, but construction enterprises have lacked emphasis on assessing digital transformation maturity. This study aims to develop a framework evaluating construction enterprises' digital transformation maturity degree. The framework comprises a digital transformation maturity assessment model facilitating expert individual assessments and an assessment method based on the optimized fairness-aware collective opinion generation paradigm generating collective assessments. The model explores digital transformation's influencing factors to construct a hierarchical model with dimensions, indicators, and levels. The paradigm reduces expert subjectivity and fairness concern's influence, improving collective assessment accuracy. Under this paradigm, Bayesian best-worst method determines indicator weights and a bi-objective optimization model aggregates expert opinions. We apply the framework to China State Construction Engineering Corporation's 3rd Bureau, verifying feasibility and validity, analyzing results and providing suggestions.