The Effects of M&A on Corporate Performance in Japan:DID Analysis in the Era of Corporate Governance Reform

This study analyzes how mergers and acquisitions (M&A) affect the performance of acquired companies in Japan. The sample period includes the era in which the government of Japan promoted a series of corporate governance reforms. A difference-in-differences analysis is implemented to eliminate the endogenous effects of a corporate acquisition. Choosing a control group by propensity score matching, we find that acquisitions have significantly negative effects on employment but no significant effects on labor productivity. For acquisitions by Japanese companies, we also find no significant improvement in ROA but significant improvement in Tobin’s q. The results are consistent with the zombie company theory, which indicates that an M&A prolongs the life of an insolvent company. Acquisitions by Japanese companies are in contrast with those by foreign companies, which have positive effects on ROA.     

Third-party certification and post-IPO acquisitions

ABSTRACT

We explore the link between third-party certification (venture capital backing, analyst following and having a top underwriter), and post-IPO acquisition activity through the reduction in valuation uncertainty channel. In a sample of 2,424 U.S. IPOs, we find that third-party certification facilitates post-IPO acquisitions. The certified firms are both more likely and conduct acquisitions sooner after the IPO. Our results support the notion that third-party certification reduces post-IPO valuation uncertainty and thereby facilitates a more efficient acquisition strategy.     

基于广义资源观的企业并购整合的价值创造

并购是重新配置资源有效机制,而并购后的整合是提高社会资源配置的有效手段。并购后整合是否能实现价值的创造是决定企业是否进行并购的重要决定因素。基于广义资源观,探讨了并购后整合的价值创造机理,认为在企业并购中资源、能力和知识的转移是可以实现的,但因要素特性不同和转移过程中遇到的影响因素不同使得其转移的过程和难度有所不同。在企业并购中,经过长期学习积累起来的、以知识为主要形态的无形资源、隐性知识和核心能力的转移难度就很大。无形资源、隐性知识和核心能力的转移难度与这些要素的特征有直接关系。     

A genetic algorithm based approach to transactional and QoS-aware service selection

As there are various risks of failure when Web services are deployed in unreliable environment, the execution of a composite Web service (CWS) requires the transaction mechanism to guarantee its reliable execution. However, the existing service selection approaches consider QoS and transaction separately and have not considered that transactional properties may affect the QoS such as the execution time of a CWS. This work addresses the importance of considering transactional properties and how the transactional properties affect the QoS simultaneously in the process of service selection by a QoS-aware and transactional-aware selection approach. First, a performance evaluation method is proposed to calculate the execution time of a transactional CWS. Then, a genetic algorithm based approach, which takes into account the execution time, price, transactional property and successful execution rate of CWS, is presented to achieve global optimisation service selection. Finally, experimental results show the efficiency and effectiveness of the approach.     

Structured deplaning via simulation and optimization

Deplaning naturally occurs row by row down the length of an aircraft. Using simulation and optimization, we design deplaning strategies (e.g., deplane by group and/or column) that significantly reduce the overall unstructured deplaning time. The evaluations derived from a combination of optimization and simulation were tested across several equipment types using data gathered through field observations for calibration.     

Design and development of inventory knowledge discovery system

Inventory management (IM) performance is affected by the forecasting accuracy of both demand and supply. In this paper, an inventory knowledge discovery system (IKDS) is designed and developed to forecast and acquire knowledge among variables for demand forecasting. In IKDS, the TREes PArroting Networks (TREPAN) algorithm is used to extract knowledge from trained networks in the form of decision trees which can be used to understand previously unknown relationships between the input variables so as to improve the forecasting performance for IM. The experimental results show that the forecasting accuracy using TREPAN is superior to traditional methods like moving average and autoregressive integrated moving average. In addition, the knowledge extracted from IKDS is represented in a comprehensible way and can be used to facilitate human decision-making.     

Migration,Friendship Ties,and Cultural Assimilation

We study immigrant assimilation by analyzing whether friendship with natives is a measure of cultural assimilation, and by investigating the formation of social ties. Using the German Socio‐Economic Panel, we find that immigrants with a German friend are more similar to natives than those without German friends, along several important dimensions, including concerns about the economy, an interest in politics, and a host of policy issues. Turning to friendship acquisition, we find that becoming employed, time spent in the host country, the birth of a child, residential mobility, and additional education acquired in the host country are significant drivers of social network variation.     

Reconceptualizing cultural distance: The role of cultural experience reserve in cross-border acquisitions

Cultural distance is one of the most widely used distance construct in international business. However, scholars have long questioned the notion that cultural distance has a homogenous impact on organizational actions and performance. We redress this by examining how the relationship between cultural differences and deal abandonment in cross-border acquisitions is contingent on firm-level cultural experience reserve and industry affiliation. Drawing on the organizational learning theory and cultural friction perspective, we first propose that the cultural experience reserve of a focal firm mitigates the positive impact of cultural differences on cross-border deal abandonment. We then hypothesize that the firm's industry context affects the uncertainties associated with cultural differences. Our findings based on a sample of 197 Indian services sector firms support our theoretical predictions.     

Estimation of interregional input–output table using hybrid algorithm of the RAS method and real-coded genetic algorithm

In this paper, we propose a method for improving the accuracy of the estimation of interregional input–output tables, by combining the RAS method and the real-coded Genetic Algorithm (GA); these are simple representative methods for the estimation of an interregional input–output table. By comparing the performance evaluation results obtained using the proposed method, the RAS method, and Simulated Annealing, we verified that the combination of the genetic algorithm and the RAS method can enhance the estimation accuracy of an interregional input–output table. In addition, performance is further enhanced by adjusting GA parameters.     

A Brief Survey of Modern Optimization for Statisticians

Modern computational statistics is turning more and more to high‐dimensional optimization to handle the deluge of big data. Once a model is formulated, its parameters can be estimated by optimization. Because model parsimony is important, models routinely include non‐differentiable penalty terms such as the lasso. This sober reality complicates minimization and maximization. Our broad survey stresses a few important principles in algorithm design. Rather than view these principles in isolation, it is more productive to mix and match them. A few well‐chosen examples illustrate this point. Algorithm derivation is also emphasized, and theory is downplayed, particularly the abstractions of the convex calculus. Thus, our survey should be useful and accessible to a broad audience.