Research Interests
Geospatial Analytics
LBS & POI data for retail site selection
Machine Learning
Predictive modeling & deep learning
Big Data Platform
CDP, Spark, Hadoop ecosystems
Retail Analytics
Consumer behavior & O2O strategies
AI Research
AI applications & intelligent systems
Decision Research
Data-driven decision making
Working Research
中国多元商圈类型研究 —— 基于改革开放以来商业地产发展历程的视角
Working Research | Jinan University | Expected: May 2029
本研究旨在系统梳理中国改革开放以来商业地产发展的多元商圈类型，通过历史演变分析与五维分类框架（业态组合、目标客群、空间规模、运营模式、地域特征），探讨中国商圈的演化规律与发展趋势。研究将结合定量数据分析与定性案例研究，为商业地产规划与零售业选址提供理论指导。
Working Papers
Spatial Analysis of Retail Business Districts in Urban China: A Multi-Dimensional Classification Framework
Working Paper
This paper proposes a five-dimensional classification framework for analyzing retail business districts in post-reform China: format mix, target customers, spatial scale, operation mode, and geographic characteristics. Through case studies of Beijing CBD, Shanghai Nanjing Road, and Suzhou Industrial Park Neighborhood Centers, we identify distinct district typologies and their evolution patterns.
Research Reports
中国多元商圈类型研究报告
March 2026
综合性研究报告，系统梳理中国商圈的历史演变（从地摊经济到新零售）、五维分类框架、以及四种主要类型（办公型商圈、纯商业型商圈、社区型商圈、多元综合型商圈）的特征分析。报告包含北京CBD、上海南京路、苏州工业园区邻里中心等典型案例。