基于前景理论和数据包络分析的企业并购资源匹配理论与方法研究

Mergers and Acquisitions (M&A) matching decision is a key link of M&A activities. Reasonable M&A matching can realize the integration of enterprise resources and make enterprises bigger and stronger; on the contrary, unreasonable M&A fit can reduce management performance, and can not achieve the ideal desired results. With respect to risk of M&A matching decision, We should consider not only the rational behavior of decision makers, but also the non-rational behavior. Therefore, this project aims to make a deep study of the problems of M&A matching decision based on prospect theory: jointly using logistic regression analysis and prospect theory for the Mergers and Acquisitions (M&A) matching decision is a key link of M&A activities. Reasonable M&A matching can realize the integration of enterprise resources and make enterprises bigger and stronger; on the contrary, unreasonable M&A matching can reduce management performance, and can’t achieve the ideal desired results. There are researches on two aspects needs to be further improved: With respect to risk of M&A matching decision, we should consider not only the rational behaviors of decision makers, but also their non-rational behaviors; In view of the acquisition of resource index weights, the existing researches are usually based on the subjective judgment of the decision-maker, which ignored the objectivity of resource evaluation. Therefore, the Prospect Theory is used to solve the problem of "bounded rationality" of decision makers facing risks, and DEA method is used to solve the subjective problem of resource evaluation in this project. Logistic Regression Analysis and Prospect Theory are jointly used to determine the acquirer and the target of M&A matching; DEA method and Prospect Theory are used to determine the feasible M&A matching that can realize the resource optimization configuration; The M&A matching optimization models are constructed taking prospect values of various resource as the matching satisfaction, based on rationality of dynamic and interval reference points. The research outcomes have important theoretical and practical significance to the development and perfection of prospect theory and DEA method, and can provide theoretical and practical guidance for M&A matching decision in our country.

并购匹配决策是并购活动的关键环节，合理的并购匹配，既可以实现企业资源整合，又可以使企业做大做强；相反，不合理的并购匹配，既降低管理绩效，又不能取得理想的预期效果。已有研究有待进一步完善之处：针对并购匹配决策风险，不仅要考虑决策者的理性行为，而且要考虑其有限理性行为；针对并购资源指标权重获取，已有研究多基于决策者主观判断，有失评价的客观性。本项目利用前景理论解决决策者面对风险的“有限理性”问题，利用DEA方法解决资源评价的主观性问题。联合运用前景理论和logistic回归分析确定并购匹配的收购方和目标方；联合运用DEA方法和前景理论，确定以实现资源优化配置为标准的可行并购匹配的筛选途径与方法；研究动态和区间参照点的合理性，构建以各类资源前景值为匹配满意度的并购匹配优化模型。研究成果对发展和完善前景理论、DEA方法和并购决策有重要的理论意义，对指导我国企业并购匹配决策有较好的实际意义。

随着国内“产业升级”、国际国内“双循环”、区域经济一体化等政策和战略出台，我国并购活动频繁。《2020年中国企业并购市场回顾与2021年展望》报告显示，2020年中国并购交易金额增长了30%，高达到7338亿美元，是自2016年以来最高水平，预计并购活动在未来五年仍然持续活跃。然而现实中并购失败率居高不下，为了降低并购失败的概率，一个关键的环节是为并购双方选择合理的匹配对象，即企业并购匹配。传统的并购匹配方案，很少考虑决策者“有限理性”问题，实质上，面对是否参与并购和并购对象选择问题时，决策者更多地受有限理性因素影响。为此，我们研究了绩效评价标准多样性和基于评价标准为参照点的绩效评价方法，评价标准的多样性体现在评价标准可以是最优决策单元（IDMU）、最差决策单元（ADMU）或者绩效水平，决策单元投入产出可以是精确数，也可以是区间数，进一步研究基于不同评价标准下的并购匹配。由于并购资源匹配的理想状态是并购资源的互补与协同，由于某些资源指标权重，难以用确定数据描述，传统研究多采用基于决策者主观判断的定性评价，评价结果容易受到与判断过程相联系多种因素的影响。为此，我们进一步研究了考虑非理性行为的并购资源匹配研究。利用前景理论量化并购决策者对并购目标的非理性价值评估和运用数据包络分析（DEA）对并购双方资源的协同性和互补性进行量化研究，资源指标权重不必事先确定，根据各类资源的投入和产出量确定。针对并购匹配双方的理性和非理性心理，提出有针对性的理论模型与策略，为并购双方的合作提供科学的双赢方案，从而形成稳定的并购匹配策略。项目研究整体进展顺利，取得了一系列新颖的研究进展与成果。