Offering a comprehensive navigation tool for modern businesses, this guide serves as a professional compass for decision-makers and is widely used in top business schools. Its accessible writing makes it suitable for a diverse audience, including junior managers, analysts, and MBA students. The book is designed to enhance understanding of key business concepts and is a valuable resource for anyone interested in the business world, regardless of their current role or experience level.
Study Cases in Finance and Energy Industries
Focusing on human resource management, the book explores BP's challenges through classical and innovative theories, providing actionable recommendations for performance enhancement. It addresses five key HR practices: talent management, health, safety, and environment, diversity management, expatriate management, and project management. For each issue, it offers targeted strategies to optimize HRM processes, making it a practical guide for improving organizational effectiveness within BP.
By Analyzing the Acquirers' Performance Change
The study investigates how a target's ESG score influences an acquirer's return on assets (ROA) and stock price changes following mergers and acquisitions. It finds that the effect on ROA is significant, with low-ESG acquirers experiencing greater declines compared to high-ESG acquirers due to higher integration costs. While most acquirers face ROA drops post-deal, those with higher pre-M&A ESG levels benefit from a more favorable outcome. However, the target's ESG score does not significantly affect the acquirer's stock price changes.
The book offers a comprehensive summary of essential notes for the CFA Level 3 exam, featuring a clear and accessible structure. It serves as a valuable resource for both candidates preparing for the exam and practical portfolio managers. Additionally, it can be utilized as a training guide in corporate and academic settings focused on portfolio and investment management.
Considering Infection Risk during Pandemic Periods
Focusing on urban last-mile delivery, this research introduces a mathematical model to optimize the allocation of autonomous vehicles (AVs) among city logistics centers. It aims to reduce operating costs, environmental impact, and social risks. The model evaluates equipment costs, delivery expenses, and CO2 emissions via social carbon cost (SCC). Additionally, it incorporates a risk assessment for seasonal variations, analyzing four delivery scenarios, including traditional vehicles and mixed methods with optimal AV allocation during pandemics.