Mergers and acquisitions matching for performance improvement
A DEA-based approach
Bibliographic Data
| ID | 15067803 |
|---|---|
| Authors | Lin Yang (0000-0002-1698-6666, Fujian Normal University, corresponding author), Yang Lin (0009-0001-2700-2781, Fujian Normal University), Ying-Ming Wang (0000-0001-6280-0175, Decision Sciences Institute, Fuzhou University, Fuzhou, China), Ying‐Ming Wang (0009-0001-4500-2734, Fuzhou University), Hai-Liu Shi (0000-0003-1876-6963, School of Electronic Information Science, Fujianjiangxia University, Fuzhou, China) |
| Year | 2020 |
| Volume | 33 |
| Issue | 1 |
| Pages | 3545-3561 |
| Publication date | 2020-01-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Economic Research-Ekonomska Istraživanja (JOURNAL) |
| Journal identifiers | ISSN: 1331-677X • E-ISSN: 1848-9664 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/1331677x.2020.1775673 |
| OpenAlex | W3087637341 |
| Language | EN |
| Citations received | 1 |
| References cited | 56 |
This article proposes a new data envelopment analysis (DEA)-based approach to deal with mergers and acquisitions (M&As) matching. To derive reliable matching degrees between bidder and target firms, we consider both technical efficiency and scale efficiency. Specifically, an inverse DEA model is developed for measuring the technical efficiency, while a conventional DEA model is employed to identify the return of scale of the merged decision-making units (DMUs). Then, an optimization model is formulated to generate matching results to improve DMUs’ performance. An empirical study of M&As matching Turkish energy firms is examined to illustrate the proposed approach. This study shows that both technical efficiency and scale efficiency have impacts on M&As matching practices
Data envelopment analysis · Econometrics · Economics · Geography · Mathematical optimization · Mergers and acquisitions · Microeconomics · Operations research · Optimal matching · Returns to scale · Statistics · Auction Theory and Applications · Computer Science · Efficiency Analysis Using DEA · Electric Power System Optimization · Mathematics · Finance
| Citations per year | 0.33 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |