Date of Award

2018

Document Type

Dissertation - Open Access

Degree Type

Dissertation

Degree Name

Doctor of Business Administration (DBA)

Advisor(s)

Halil Kiymaz

Second Advisor

Misty L. Loughry

Keywords

M&A performance, M&A capability, Serial acquisitions, Dynamic capabilities, Knowledge-based view, Natural language processing

Abstract

The Merger and Acquisitions (M&A) market is a sophisticated option for firms to complement their organic growth strategy. Firms that adopt an M&A strategy develop a superior management capability (M&A capability). The M&A capability is built on the management of the M&A process phases and the M&A learning process through experience accumulation and deliberate learning mechanisms. The management of the M&A process can critically influence the acquisitions outcomes and the firm's long-term performance. This research investigates the influence of the M&A capability on the firm's long-term performance. This mixed-method study uses a text mining methodology to quantify unstructured qualitative data from 564 annual reports and 2,602 M&A synopses between January 01, 2013, and December 31, 2016. The research contributes to the literature in three significant ways. First, the empirical research findings evidence a positive and meaningful relationship between the M&A capability construct with two performance dimensions, profitability (Return on Equity) and market value (Price-to-Book). Second, the M&A capability was effectively measured, and its significant predictors defined, i.e., number of acquisitions, size of the firm, and M&A motives. Third, the novel mixed-method approach provided an alternative to M&A and strategic management research with the emerging use of automated, natural language processing techniques to analyze unstructured data in intricate settings. Practitioners can use the study to understand the antecedents of firm performance in serial acquirers and the M&A capability formation. In addition, academics can benefit from the interdisciplinary M&A construct findings and the mixed-method methodology in future studies.

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