Purpose

This paper investigates the puzzle of mergers and acquisitions’ (M&A) long-term performance through the strategic management perspective. The authors measure the M&A capability construct and test its relationship with the long-term performance of the firms.

Design/methodology/approach

The study employs a natural language processing (NLP) methodology to quantify unstructured data from 564 annual reports and 2,602 M&A synopses from January 01, 2013 to December 31, 2016. The authors combine qualitative document analysis with a quantitative method using a multiple regression analysis model.

Findings

Among serial acquirers, M&A capability positively relates to long-term firm performance measured by both return on equity and price-to-book value. The authors also find that the size of the company and the number of acquisitions influence the M&A capability, confirming previous results in the literature.

Research limitations/implications

Detailed M&A management plans are usually confidential and not fully reported. Future studies could employ enhanced artificial intelligence tools to measure the M&A capability construct beyond filing reports, encompassing interviews, social media posts, press releases and other unstructured data sources.

Practical implications

Firms can improve their M&A capability by understanding the underlying foundation of the construct provided in the research. Additionally, researchers can build on the methodology employed using advanced NLP tools to measure M&A capability.

Social implications

Improving their M&A capability would allow firms to better choose their targets and conduct a superior integration process, which could prevent distressing mergers, unnecessary negative social impacts and culture disruption. As a result, the ensuing organization would be stronger, and the long-term performance would improve.

Originality/value

This study addresses gaps in the literature on M&A performance and provides a new empirical method to measure the M&A capability.

中文翻译：

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并购能力与企业长期绩效：战略管理视角

目的

本文从战略管理的角度探讨了并购（M&A）长期绩效的难题。作者衡量并购能力结构并检验其与公司长期绩效的关系。

设计/方法/途径

该研究采用自然语言处理 (NLP) 方法从 2013 年 1 月 1 日至 2016 年 12 月 31 日期间的 564 份年度报告和 2,602 份并购概要中量化非结构化数据。作者将定性文件分析与使用多元回归分析模型的定量方法相结合.

发现

在连续收购方中，并购能力与通过股本回报率和市账率衡量的长期公司业绩呈正相关。作者还发现公司规模和收购数量影响并购能力，证实了文献中先前的结果。

研究局限性/影响

详细的并购管理计划通常是保密的，不会完全报告。未来的研究可以使用增强的人工智能工具来衡量并购能力构建，超越提交报告，包括采访、社交媒体帖子、新闻稿和其他非结构化数据源。

实际影响

公司可以通过了解研究中提供的结构的基础来提高他们的并购能力。此外，研究人员可以使用先进的 NLP 工具来衡量并购能力所采用的方法。

社会影响

提高并购能力将使公司能够更好地选择目标并进行更出色的整合过程，从而防止令人痛苦的合并、不必要的负面社会影响和文化破坏。结果，随之而来的组织会更强大，长期绩效也会提高。

原创性/价值

本研究解决了并购绩效文献中的空白，并提供了一种新的实证方法来衡量并购能力。