Effect of Mergers and Acquisitions on Corporate Value in Technology Sectors

Abstract

This research explores how mergers and acquisitions (M&A) affect the value of the firm in the pharmaceutical industry in Bangladesh during the period of 2010 to 2024. The study is based on the Resource-Based View (RBV), and examines the value creation potential of M&As through acquisition of the resources, realization of synergies, and improvement of innovation. The analysis utilizes secondary data on listed pharmaceutical companies and the average and distributional impact of M&A on corporate performance is estimated using pooled OLS, fixed effects, random effects and quantile regression models. The empirical findings show that M&A activities have positive and statistically significant relationships with the corporate value (Tobin's Q), ROA, and ROE. A finding is that both M&A occurrence and deal magnitude (deal size and intensity) are shown to have a positive impact on firm performance, indicating synergy gains from post-merger integration. The results also show heterogeneous effects by firm, with greater effects found for higher performing firms, which is backed up by quantile regression analysis. Firm-specific variables like R&D intensity, firm size and growth opportunities have positive impact on performance, and leverage has a negative impact on performance. The study adds to the literature through the unique combination of long-term empirical data from an emerging pharmaceutical market and an extension of RBV-based explanations of outcomes of M&A. The findings provide valuable insights for managers, investors and policymakers concerning strategic decision making in M&A as well as post-merger integration effectiveness.

Received: 2026-04-15 | Revised: 2026-06-24 | Accepted: 2026-06-26 | Published: 2026-06-30

Declarations

Competing interests: The authors declare no competing interests.

Data availability statement: Data will be made available on reasonable request from the corresponding author.

Funding: This research received no external funding.

Clinical Trial Number: Not Applicable.

Declaration of using generative AI: During the preparation of this work the author(s) used ChatGPT in order to correct the grammatical errors. After using this tool/service, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the published article.

Author Contributions: T.T.: Conceptualization, methodology, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.