Date of Award
2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Industrial and Systems Engineering
Committee Chair
Jeffery Williams
Committee Member
Michael Anderson
Committee Member
Nicholas Loyd
Committee Member
L. Dale Thomas
Committee Member
Nicholas Clarke
Research Advisor
Jeffery Williams
Subject(s)
AI Integration, Technology M&A Strategy, Post-merger integration, Executive decision making
Abstract
In the post-COVID-19 era, accelerated engineering advances including Artificial Intelligence (AI) have increased firm’s reliance on technology-driven mergers and acquisitions (M&A) as an expedient strategy to bolster their technological innovation capabilities, retain competitive advantage and ensure sustainability. However, many M&As fail to achieve their strategic goals because of persistent challenges during post-merger integration (PMI). This dissertation adopts and integrates chapter 2 – chapter 4 to identify, theorize, and proactively mitigate the primary recurring PMI challenges that impede successful technology-driven M&A outcomes. Chapter 2 adopts PRISMA guidelines, conducts a systematic literature review, identifies, and synthesizes four persistent PMI risk categories: (1) cultural and strategic misalignment, (2) technological integration issues, (3) financial constraints, and (4) cybersecurity risks. Chapter 3 examines the relationship between pre-merger due diligence and PMI challenges and identifies three pre-merger due diligence risks that exacerbate the PMI phase: (5) lack of early prioritizations of PMI issues, (6) sub-optimal due diligence speed, and (7) cognitive bias. Chapter 4 operationalizes the seven risk categories as failure modes and develops a validated, PMI Actionable Risk Mitigation Strategy (artifact) by employing a Failure Modes and Effects Analysis (FMEA) inspired Design Science Research methodology to analyze the artifact’s utility using 35 completed technology-driven M&As that sought to bolster their technological capabilities by acquiring firms with AI and advanced technologies. Chapter 4 also introduces the new theoretical construct, Escalated Gibberish, which emphasizes information governance controls by deconstructing how poor information quality, interpretive risks, and cognitive distortions impair the pre-merger executive decision-making process and compound PMI challenges. In addition, Chapter 4 also introduces an FMEA-inspired PMI RPN scoring rubric grounded on synthesis of empirical studies, termed PrizRed, which enables proactive assessment of acquiring firms’ PMI risk tolerance in each of the seven failure modes during pre-merger executive decision-making process. This dissertation advances engineering management concepts within the M&A literature by applying systems thinking to accentuate the need to avoid Escalated Gibberish during the pre-merger executive M&A decision-making process and provides practitioners with an actionable playbook to proactively mitigate PMI risks in technology-driven M&A projects and improve the likelihood of attaining M&A strategic goals.
Recommended Citation
Usianeneh, Kingsley Eromosele, "Increase successful outcomes with technology-driven mergers and acquisitions : prioritize post-merger integration risk mitigation" (2025). Dissertations. 475.
https://louis.uah.edu/uah-dissertations/475