2 research outputs found
Cross-Border Mergers & Acquisitions and Business Growth in Healthcare: An absorptive capacity perspective: - Confab 360 Degree Annual Conference in Dubai, 2025
No full textObjective: This study explores the impact of cross-border mergers and acquisitions (M&As) on the business growth of pharmaceutical companies. Based on evidence from the 2015 acquisition of Novartis's vaccine division by GlaxoSmithKline (GSK) as a paradigmatic case study, we also explore how this M&A led to business growth during the COVID-19 pandemic.
Design: We employ qualitative analysis of 10 years of executive reports, annual reports, market research, and peer-reviewed journal articles from Business Source Premier. Then, we developed a thematic analysis of this secondary data based on five critical dimensions of post-merger success, including strategic rationale, after-acquisition growth, operational synergies, cultural integration, and competitive positioning.
Results: Our findings suggest that the acquisition’s success was fundamentally driven by its tight strategic alignment with GSK's long-term objectives of specialising in vaccines and innovative healthcare. Operational efficiencies were achieved through phased integration, while proactive leadership and open communication were found to be crucial in reducing cultural challenges.
Conclusions: We conclude that in the intricate healthcare ecosystem, carefully planned and executed M&As that prioritise cultural alignment in addition to financial and operational objectives can result in substantial, long-term value. For executives, academics, and policymakers navigating international M&A strategy in the healthcare industry, the paper offers insightful theoretical analysis and useful recommendations
A Meta-Analysis of Evolution of Deep Learning Research in Medical Image Analysis
No full textWith a text mining and bibliometrics approach, we review the literature on the evolution of deep learning in medical image literature from 2012 – 2020 in order to understand the current state of the research and to identify the major research themes in image analysis to answer our research questions: RQ1: What are the learning modes that are evident in the literature? RQ2: What are the emerging learning modes in the literature? RQ3: What are the major themes in medical imaging literature? The analysis of 8704 resulting from a data collection process from peer-reviewed databases, our analysis discovered the six major themes of image segmentation studies, studies with image classification, evaluation procedures such as sensitivity and specificity, optical coherence tomography studies, MRI imaging studies, and Chest imaging studies. Additionally, we assessed the number of articles published each year, the frequent keywords, the author networks, the trending topics, and connections to other topics. We discovered that segmenting and classifying the images are the most common tasks. Transfer learning is the most researched area and cancer is the highly targeted disease and Covid-19 is the most recent research tren
