大数据驱动的三类典型工商市场主体风险识别决策研究

项目名称： 大数据驱动的三类典型工商市场主体风险识别决策研究

项目编号： No.91546121

项目类型： 重大研究计划

立项/批准年度： 2016

项目学科： 管理科学

项目作者： 齐佳音

作者单位： 上海对外经贸大学

项目金额： 43万元

中文摘要： 当前我国经济发展既处于战略机遇期，又处于高风险防控期。僵尸企业、非法集资和企业的不诚信经营这三类风险是目前国家工商行政管理部门重点监控的三类市场风险。在传统的工商行政管理中，通常很难或无法高效地对这三类风险进行识别发现。大数据为改变这一局面带来了机遇。为此，本项目重点研究：1）基于大数据的企业画像建模；2）基于大数据的僵尸企业识别；3）基于大数据的非法集资行为预判4）基于大数据的企业不诚信线索发现；5）基于元学习的技术实现架构及验证平台搭建。本项目的五个主要研究任务不仅本身具有突出的学术价值，而且可以在抽象层面对大数据价值的产生机理和转换规律做出公共管理领域的探索性回答。本项目以三类典型市场主体风险的发现作为研究目标，在“宽进严管”的新型市场监管体系改革背景下，符合国家重大需求，具有重要实践应用价值。

中文关键词： 大数据；市场主体风险；僵尸企业；非法集资；不诚信线索

英文摘要： The current economic development in our country is both in the period of strategic opportunities, but also in a high risk prevention and control period. Zombie firms, illegal fund raising and bad faith operation are the three typical risks of market players. Using traditional methods, it is often very hard to identify these risks efficiently. Big data changes this situation and creates possibilities. Therefore, in the era of big data, this project focuses on enterprise profile modeling, zombie companies recognition, illegal fund-raising behavior predicting and firms’ bad faith operation clues finding. Also, we will build a meta learning implementation architecture based on Hadoop framework to verify the methods and algorithms of this research. Not only the five main research tasks themselves have prominent academic value, but also in the generalization level, this research can provide answers to the value creation and value transformation mechanism of big data from the perspective of public administration areas. Taking the three typical market players’ risks as research targets, this research has significant value for the widely practice of the big data driven decision making in the whole supervision of the State Administration for Industry and Commerce in the future.

英文关键词： big data;market player risk;zombie firms;illegal fund raising;bad faith operation clues