Mergers and Acquisitions (M&A) - Crossref Bibliographic Metadata

This dataset provides detailed bibliographic metadata records for scholarly publications related to 'Mergers and Acquisitions' (M&A), as retrieved from Crossref.org. This metadata corpus facilitates in-depth exploration of the academic discourse surrounding these significant corporate strategic actions. Contextual Overview of Mergers and Acquisitions (M&A): 1. Definition and Context: Mergers and Acquisitions (M&A) refer to the consolidation of companies or assets through various types of financial transactions, including mergers, acquisitions, consolidations, tender offers, purchase of assets, and management acquisitions. A key instrument for corporate growth, market entry, and capability enhancement, M&A activity often occurs in waves, influenced by economic cycles, technological disruptions, and regulatory environments. It is a central theme in corporate finance and strategic management. 2. Strengths and Weaknesses: M&A can offer benefits such as achieving scale economies, market power, diversification, access to new technologies or talent, and shareholder value creation. However, M&A deals are notoriously complex and have high failure rates in achieving their intended synergies. Challenges include overpaying (winner's curse), difficulties in post-merger integration (cultural clashes, system incompatibilities), loss of key talent, and misjudgment of market or target company dynamics. 3. Relevance and Research Potential: M&A remains a critical area of study due to its profound impact on firm performance, industry structure, and economic development. It is a core topic in corporate strategy, finance, and organizational behavior. Research opportunities include understanding success factors in different M&A types (e.g., cross-border, high-tech), the role of due diligence and integration processes, human capital aspects in M&A, long-term value creation versus destruction, and the impact of regulatory changes and digital transformation on M&A strategies. Dataset Structure and Content: The dataset consists of one or more archives. Each archive contains a series of approximately 850 monthly folders (e.g., spanning from January 1950 to January 2025), reflecting a granular month-by-month process of metadata retrieval and curation for M&A. Within each monthly folder, users will find several JSON files documenting the search and filtering process for that specific month: term_results/: A subfolder containing JSON files for results of initial broad keyword searches related to M&A. merged_results.json: Aggregated results from these individual term searches before advanced filtering. filtered_results.json: Results after applying a more specific, complex Boolean query (e.g., ("mergers and acquisitions" OR "M&A") AND ("strategy" OR ...)) and exact phrase matching to refine relevance. The exact query used is detailed within this file. final_results.json: This is the primary file of interest for most users. It contains the curated, deduplicated (by DOI) list of unique publication metadata records deemed most relevant to 'Mergers and Acquisitions' for that specific month. Includes fields like Title, Authors, DOI, Publication Date, Source Title, Abstract (if available from Crossref). statistics_results.json: Summary statistics of the search and filtering process for the month. This granular monthly structure allows researchers to trace the evolution of academic discourse on M&A and identify relevant publications with high temporal precision. For an overview of the general retrieval methodology, refer to the parent Dataverse description (Management Tool Bibliographic Metadata (Crossref)). Users interested in aggregated publication counts or trend analysis for M&A should consult the corresponding datasets in the Raw Extracts Dataverse and the Comparative Indices Dataverse.