The Relationship between Social Responsibility and Majority Shareholders’ Stock Selling: Considering the Mediation of Investors Tendency

Based on the research object of majority shareholders’ stock selling at the post period of equity division reform, this paper takes 8019 A-share listed companies in Shanghai and Shenzhen stock market from 2007-2013 as sample, empirically analysis the relationship between social responsibility and majority shareholders’ stock selling, and consider mediation effect of the investor tendency. The study found that from the point of internal governance effect, the better of social responsibility, the lower possibility of majority shareholders’ stock selling. At the same time, the lower of market reduction premium, the lower possibility of majority shareholders’ stock selling, after considering the influence of investors’ tendency, the inhibition effect of social responsibility will be magnified, which means securities market identity with the inhibition effect that comes from the social responsibility caused by listed companies’ internal. Further study found that majority shareholders will avoid stock selling during the period of the social responsibility reporting, and market investors will hold different attitudes toward majority shareholders for their first and continuous stock selling, and on their view, continuous stock selling is a “bad” event

Predicting Airline Choices: A Decision Support Perspective and Alternative Approaches

The ability to predict the choices of prospective passengers allows airlines to alleviate the need for overbooking flights and subsequently bumping passengers, potentially leading to improved customer satisfaction. Past studies have typically focused on identifying the important factors that influence choice behaviors and applied discrete choice framework models to model passengers’ airline choices. Typical discrete choice models rely on two major assumptions: the existence of a utility function that represents the preferences over a choice set and the linearity of the utility function with respect to attributes of alternatives and decision makers. These assumptions allow the discrete choice models to be easily interpreted, as each unit change of an input attribute can be directly translated into change in utility that eventually affects the optimal choice. However, these restrictive assumptions might impede the ability of typical discrete choice models to deliver operational accurate prediction and forecasts. In this paper, we focus on developing operational models that are intended for supporting the actual prediction decisions of airlines. We propose two alternative approaches, pairwise preference learning using classification techniques and ranking function learning using evolutionary computation. We have empirically compared these approaches against the standard discrete choice framework models and report some promising results in this paper

Few-shot Image Generation via Masked Discrimination

Few-shot image generation aims to generate images of high quality and great diversity with limited data. However, it is difficult for modern GANs to avoid overfitting when trained on only a few images. The discriminator can easily remember all the training samples and guide the generator to replicate them, leading to severe diversity degradation. Several methods have been proposed to relieve overfitting by adapting GANs pre-trained on large source domains to target domains with limited real samples. In this work, we present a novel approach to realize few-shot GAN adaptation via masked discrimination. Random masks are applied to features extracted by the discriminator from input images. We aim to encourage the discriminator to judge more diverse images which share partially common features with training samples as realistic images. Correspondingly, the generator is guided to generate more diverse images instead of replicating training samples. In addition, we employ cross-domain consistency loss for the discriminator to keep relative distances between samples in its feature space. The discriminator cross-domain consistency loss serves as another optimization target in addition to adversarial loss and guides adapted GANs to preserve more information learned from source domains for higher image quality. The effectiveness of our approach is demonstrated both qualitatively and quantitatively with higher quality and greater diversity on a series of few-shot image generation tasks than prior methods

Exploring Impacts of the Role of Governments on Cross Border M&A of State-owned Enterprises (SOEs) in Emerging Market Based on the Different Industry

We demonstrate the different role of the government has various effects on the state-owned enterprises of emerging market’s internationalization. We further show that the government indeed plays a different role (constraint or encourage) based on the different industry, rather than merely inspecting international behavior as the result of cross border merger and acquisition performance and the role of government separately. Although the role of government has a profound influence on international expansion, these effects depend on three sides: whether the enterprises is the state-owned firms; different types and levels of enterprises with different objectives; different institutional pressures on SOEs. These effects will have impacts on willingness and ability of SOEs to internationalize differently. The role of the government indeed influences the outcome of overseas investment in both developed countries and under-developed countries based on the different type of cross border M&A activities (resource- vs technological-seeking). These effects are from the firms’ own capabilities and the different attitudes from the host countries, suggesting that not all firms could use international government-related advantages appropriately and respond to institutional pressures efficiently. As for research method, we combine the resource-based and institutional theory together, because these two constructs highly dependent on each other, and therefore will enable us to have a deep understanding of why SOEs sometimes succeed but sometimes failed during the period of expanding overseas, and how governments matter