The Compatibility of National Culture in International Mergers and Acquisitions

This paper examines the relationship between national culture differences and five-day cumulative abnormal returns of acquirers around cross-border merger announcements. The sample consists of 1,200 cross-border deals by frequent acquirers from emerging countries for the period of January 1, 1985 to June 30, 2008. The main objective is to analyze the relation between the difference in Hofstede (1984)’s four cultural dimensions --- power distance, individualism, masculinity, and uncertainty avoidance and the merger performance. The results imply the compatibility of some cultural dimensions, individualism in particular, that result in gains in merger. The results also show that the cultural effects vary with the firm size. In addition, the evidence provides support for the hubris hypothesis by Roll (1986)

The Compatibility of National Culture in International Mergers and Acquisitions

This paper examines the relationship between national culture differences and five-day cumulative abnormal returns of acquirers around cross-border merger announcements. The sample consists of 1,200 cross-border deals by frequent acquirers from emerging countries for the period of January 1, 1985 to June 30, 2008. The main objective is to analyze the relation between the difference in Hofstede (1984)’s four cultural dimensions --- power distance, individualism, masculinity, and uncertainty avoidance and the merger performance. The results imply the compatibility of some cultural dimensions, individualism in particular, that result in gains in merger. The results also show that the cultural effects vary with the firm size. In addition, the evidence provides support for the hubris hypothesis by Roll (1986)

Neurocognitive Evidence for Different Problem-Solving Processes between Engineering and Liberal Arts Students

Differences exist between engineering and liberal arts students because of their educational backgrounds. Therefore, they solve problems differently. This study examined the brain activation of these two groups of students when they responded to 12 questions of verbal, numerical, or spatial intelligence. A total of 25 engineering and 25 liberal arts students in Taiwan participated in the experiment. The results were as follows. (i) During verbal intelligence tasks, differences between the two groups were observed in the information flows of verbal message comprehension and contextual familiarity detection in the problem-identifying phase, whereas no significant differences were found in the resolution-reaching phase. (ii) During numerical intelligence tasks, differences between the two groups were observed in the information flows of mental calculation and message comprehensionin the problem-identifying phase and those of verbal perception and analogical reasoning in the resolution-reaching phase. (iii) During spatial intelligence tasks, differences between the two groups were observed in the information flows of spatial relation integration and spatial context memory retrieval in the problem-identifying phase and those ofspatial attentionand contextual relation integration in the resolution-reaching phase

The Mediating Roles of Generative Cognition and Organizational Culture between Personality Traits and Student Imagination

Using science majors as an example, we analyzed how generative cognition, organizational culture, and personality traits affect student imagination, and examined the mediating effects of generative cognition and organizational culture. A total of 473 undergraduates enrolled in physical, chemical, mathematical, and biological science programs participated in this empirical study. The traits of openness, agreeableness, conscientiousness, extraversion, and neuroticism had various effects on student imagination. Openness proved to be the most influential factor on initiating, conceiving, and transforming imagination. Extraversion was the second best predictor of initiating imagination, and conscientiousness was the second best predictor of conceiving and transforming imagination

Revisiting the Antecedents of Social Entrepreneurial Intentions in Hong Kong

This study examined how empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and prior experience with social problems are associated with social entrepreneurial intentions. Through a survey, a sample of 252 Hong Kong students was used for analyses. Factor analyses supported that the antecedents of social entrepreneurial intentions could be divided into dimensions of empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and prior experience with social problems. Multiple regression analysis results indicated that perceived social support was the most prominent antecedent of social entrepreneurial intentions, followed by moral obligation, empathy, and prior experience with social problems. Notably, moral obligation was revealed to be negatively associated with social entrepreneurial intentions.

A New Runway for Journalists: On the Intentions of Journalists to Start Social Enterprises

Journalists have been facing a variety of challenges and are even being laid off in the face of changing media ecosystems in the age of digital convergence. Sharing similar characteristics with entrepreneurs, numerous journalists have worked together to develop social enterprises, attaining social change through business approaches. The present study explores the intentions of former and current journalists to establish social enterprises, using questionnaires focused on personality traits, creativity, and social capital. Results reveal that creativity was found to have a significant influence on the social entrepreneurial intentions of journalists, as does having higher bridging-type social capital

A Novel Compact Quadruple-Band Indoor Base Station Antenna for 2G/3G/4G/5G Systems

This paper presents a quadruple-band indoor base station antenna for 2G/3G/4G/5G mobile communications, which covers multiple frequency bands of 0.8 - 0.96 GHz, 1.7 - 2.7 GHz, 3.3 - 3.8 GHz and 4.8 - 5.8 GHz and has a compact size with its overall dimensions of 204 × 175 × 39 mm 3 . The lower frequency bands over 0.8 - 0.96 GHz and 1.7 - 2.7 GHz are achieved through the combination of an asymmetrical dipole antenna and parasitic patches. A stepped-impedance feeding structure is used to improve the impedance matching of the dipole antenna over these two frequency bands. Meanwhile, the feeding structure also introduces an extra resonant frequency band of 3.3 - 3.8 GHz. By adding an additional small T-shaped patch, the higher resonant frequency band at 5 GHz is obtained. The parallel surrogate model-assisted hybrid differential evolution for antenna optimization (PSADEA) is employed to optimize the overall quadruple-band performance. We have fabricated and tested the final optimized antenna whose average gain is about 5.4 dBi at 0.8 - 0.96 GHz, 8.1 dBi at 1.7 - 2.7 GHz, 8.5 dBi at 3.3 - 3.8 GHz and 8.1 dBi at 4.8 - 5.0 GHz respectively. The proposed antenna has high efficiency and is of low cost and low profile, which makes it an excellent candidate for 2G/3G/4G/5G base station antenna systems

ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection

Anomaly detection in multivariate time series data is of paramount importance for ensuring the efficient operation of large-scale systems across diverse domains. However, accurately detecting anomalies in such data poses significant challenges. Existing approaches, including forecasting and reconstruction-based methods, struggle to address these challenges effectively. To overcome these limitations, we propose a novel anomaly detection framework named ImDiffusion, which combines time series imputation and diffusion models to achieve accurate and robust anomaly detection. The imputation-based approach employed by ImDiffusion leverages the information from neighboring values in the time series, enabling precise modeling of temporal and inter-correlated dependencies, reducing uncertainty in the data, thereby enhancing the robustness of the anomaly detection process. ImDiffusion further leverages diffusion models as time series imputers to accurately capturing complex dependencies. We leverage the step-by-step denoised outputs generated during the inference process to serve as valuable signals for anomaly prediction, resulting in improved accuracy and robustness of the detection process. We evaluate the performance of ImDiffusion via extensive experiments on benchmark datasets. The results demonstrate that our proposed framework significantly outperforms state-of-the-art approaches in terms of detection accuracy and timeliness. ImDiffusion is further integrated into the real production system in Microsoft and observe a remarkable 11.4% increase in detection F1 score compared to the legacy approach. To the best of our knowledge, ImDiffusion represents a pioneering approach that combines imputation-based techniques with time series anomaly detection, while introducing the novel use of diffusion models to the field.Comment: To appear in VLDB 2024.Code: https://github.com/17000cyh/IMDiffusion.gi