No abstract

Apart from the loss of time and money, disputes between public authority and private partner in China’s public-private partnership (PPP) projects are destroying the government’s image of PPP support and the private partner’s investment confidence. This article aims to explore the main causes for PPP disputes, present the results of disputes, and then predict the litigation outcomes. Based on 171 PPP litigation cases from China Judgements Online within 2013–2018, the research identified 17 legal factors and explained how these factors influence the litigation outcomes, which are named as “prediction approach” in this study. Nine machine learning (ML) models were trained and validated using the data from 171 cases. The ensemble model of gradient boosting decision tree (GBDT), k-nearest neighbor (KNN) and multi-layer perceptron neural network (MLP) performed best compared with other nine individual ML models, and obtained a prediction accuracy of 96.42%. This study adds meaningful insights to PPP dispute avoidance, such as high compensation of expected revenues could prevent the government from terminating the contract unilaterally. To some extent, if parties consider the case litigation outcome, they are more likely prefer a rational settlement out of court to avoid further aggravation of the dispute, and would also alleviate the pressure of litigation in China.

This paper aims to investigate the role that institutional shareholders play in acquisition decision using micro data in the Chinese stock market during [2003][2004][2005][2006][2007][2008]. Acquisition decision is the selection and coordination process of shareholders as strategic alliances, which is determined by corporate acquisition ability, composition of institutional shareholders and concentration of tradable share (TS) in China. We use Heckman selection model to surmount the selection biases in acquisition decision. We find that institutional shareholders including qualified foreign institutional investors (QFII), social security funds (SSF), security firms (SF) and security investment funds (SIF), as well as TS concentration affect acquisition probability rather than annual acquisition scale. SSF, SIF and TS concentration can increase acquisition probability while QFII decreases it. Our paper contributes to the published literature in three ways. First, we offer a model to understand the selection and coordination process of acquisition decision. Second, we investigate whether institutional shareholders could effectively monitor annual acquisition scale. Third, we identify Heckman selection problem that institutional shareholders could affect PLCs' acquisition decision on whether to acquire rather than how much to acquire.

No abstract