The micro-foundations of strategic ambidexterity: Chinese cross-border M&As,Mid-View thinking and integration management

Chinese cross-border mergers and acquisitions (M&As) display several unique properties in relation to the ways in which their international business operations are organised and managed. Their seemingly puzzling ‘light-touch’ integration approach can be significantly understood from a strategic ambidexterity perspective: on the one hand, the ‘light-touch’ enables the exploitation of the targets’ existing knowledge bases; on the other hand, elements of the ‘light-touch’ facilitate the exploration of the new knowledge arising from the collaboration between targets and acquirers. However, an important theoretical gap remains: why do Chinese companies deploy such a strategic ambidexterity approach in their post-acquisition integrations? This paper aims to fill this gap by proposing Mid-View thinking as a micro-foundation of strategic ambidexterity in integration management from a cultural and philosophical perspective. To illuminate our conceptualization and argument, we conducted qualitative in-depth interviews with CEOs/high-level managers of acquired German companies. Communication approach and organizational control—as two critical aspects in integration management—reveal how Mid-View thinking can serve as a micro-foundation of strategic ambidexterity. We conclude this paper by presenting its theoretical contributions, managerial implications, and future research directions.     

浅谈泵送产品的公告试验检测

论文针对泵送产品公告试验检测的现状,详述了公告试验检测方案中的关键控制点,并就目前检测过程中存在的问题提出了建议。     

海洋物探技术在近岸海底礁石探测中的应用

论文介绍了海底礁石地质特征,同时通过重点分析几种常用的海底礁石探测技术方法特点,说明了海洋物探是目前海底礁石探测最值得推荐使用的技术方法,其效率高、成本低、适应性强、适用范围广的特点能够很好地满足海底礁石探测的各项要求,并在相关工程项目得到了有效应用。实践证明,海洋物探法可精确还原疏浚区海底礁石分布状态,为项目提供可靠的数据支持。     

社会互动与家庭金融资产配置

运用中国家庭金融调查(CHFS)数据,研究社会互动与家庭金融资产配置之间的关系。研究发现,适当增强社会互动会促进家庭更多地参与风险金融市场,增加投资风险资产的比例,提高金融资产的分散化程度,优化资产的配置效率。但当社会互动达到一定程度后,过度的社会互动则会抑制家庭参与风险市场,减少风险资产的投资比重,降低金融资产的分散化程度以及资产配置的有效性。因此,家庭需要建立适度而高质量的社会互动,这有助于家庭获得更多的外部资源,缓解信息不对称,降低交易成本,从而优化家庭金融资产配置。     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

Object detection based on visual memory: a feature learning and feature imagination process

ABSTRACT

Visual memory plays an important role for the human’s visual system to detect objects. The features of an object stored in the visual memory have much lower dimensions than the features contained within an image. We simulate the visual memory as a feature learning and feature imagination (FLFI) process to build an object detection algorithm. The method is constructed by a bottom-up feature learning and a top-down feature imagination. The proposed object detection method is tested using publicly available benchmark data sets, and the result indicates that it is fast and more robust.     

The impact of (un)conventional expansionary monetary policy on income inequality – lessons from Japan

ABSTRACT

This paper analyzes the impact of conventional and unconventional monetary policy on income inequality in Japan, using hitherto unexplored data from the Japan Household Panel Survey. Empirical evidence shows that expansionary monetary policy in Japan has contributed to diminishing the gender pay gap through an increase in working time of women relative to men, but also to increasing the education pay gap. These effects may have materialized via the aggregate demand channel and the labour productivity channel. In contrast, expansionary monetary policy has had no significant impact on the development of the age pay gap.     

Managing Technological,Sociopolitical, and Institutional Change in the New Normal

A New Normal environment for business has emerged in the years after the 2008 financial crisis based on numerous changes in the world's economic, technological, demographic, and sociopolitical factors. This combination of changes has created a New Normal environment for firms with major implications for managers, strategists, and entrepreneurs alike. It has resulted in an environment with new challenges and opportunities that are considerably different from what firms had to contend with in the years previous. In this paper, we present the main changes that characterize the current New Normal business environment and highlight some key implications for strategy and management. Then, we present the nine articles in this special issue dealing with different dimensions of this new environment for firms. Subsequently, we outline some future research questions that could help to advance our knowledge of the New Normal environment and its implications for firms and management theories. In examining the New Normal, it is important to be reminded that the world is indeed round and even small actions on one side of the globe can have a major impact on organizations on the other side of the globe.     

Contracting and Reporting Conservatism around a Change in Fiduciary Duties*

We exploit an influential 1991 Delaware court ruling to examine simultaneously two types of conservatism that play important roles in resolving creditor–owner agency conflicts: contracting conservatism and reporting conservatism. The ruling expanded managerial fiduciary duties in favor of creditors for Delaware-incorporated firms in the vicinity of insolvency. In those firms, following the ruling, debt contracts are less likely to include conservative adjustments to accounting numbers used for covenant compliance (i.e., contracting conservatism decreases), while public financial reporting becomes more conservative (i.e., reporting conservatism increases). The decrease in contracting conservatism is concentrated in firms that exhibit a greater increase in reporting conservatism, suggesting that reporting conservatism is more cost-effective in resolving agency conflicts. In addition, the substitution effect is more pronounced in firms facing greater business uncertainty and firms with greater board independence.     

Bankruptcy prediction for small- and medium-sized companies using severely imbalanced datasets

Bankruptcy prediction is still important topic receiving notable attention. Information about an imminent bankruptcy threat is a crucial aspect of the decision-making process of managers, financial institutions, and government agencies. In this paper, we utilize a newly acquired dataset comprising financial parameters derived from the annual reports of small- and medium-sized companies. The data, which reveal the true ratio between bankrupt and non-bankrupt companies, are severely imbalanced and only contain a small fraction of bankrupt companies. Our solution to overcome this challenging scenario of imbalanced learning was to adopt three one-class classification methods: a least-squares approach to anomaly detection, an isolation forest, and one-class support vector machines for comparison with conventional support vector machines. We provide a comprehensive analysis of the financial attributes and identify those that are most relevant to bankruptcy prediction. The highest prediction performance in terms of the geometric mean score is 91%. The results are validated on two datasets from the manufacturing and construction industries.