Pre-evaluating efficiency gains from potential mergers and acquisitions based on the resampling DEA approach: Evidence from China's railway sector

This study combines resampling DEA and the potential merger gains model to pre-evaluate the efficiency gains of three representative M&A schemes (i.e. regional M&A, megamerger, and a coalition between ‘strong’ and ‘weak’ railway bureaus) for China's railway sector over the period 2011–2015. The results reveal that geographically meaningful M&As are better than the other two types in creating efficiency gains due to the special characteristic of the railway sector – network economics. The timing of M&As and the roles and endowments of the railway bureaus must also be considered before any merger. A proper M&A can produce a so-called ‘stimulant’ effect in the short run, but as the ‘stimulant's efficacy’ becomes exhausted over time, the M&A's effect will gradually turn weak. At this time, it is particularly important for policy-makers to introduce a series of desirable institutions. Finally, the authors' empirical findings also support the view that an M&A between two (efficient or not) DMUs does not ensure positive efficiency gains.

• Record URL:
  https://doi.org/10.1016/j.tranpol.2019.01.012
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0967070X18305365
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/29485010
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Bai, Xue-jie
  • Zeng, Jin
  • 0000-0003-1297-3734
  • Chiu, Yung-Ho
• Publication Date: 2019-4

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 46-56
• Serial:
  • Transport Policy
  • Volume: 76
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0967-070X
  • Serial URL: http://www.elsevier.com/locate/issn/096707X

Subject/Index Terms

• TRT Terms: Economic efficiency; Evaluation; Mergers and acquisitions; Railroads; Sampling
• Uncontrolled Terms: Data envelopment analysis
• Geographic Terms: China
• Subject Areas: Administration and Management; Finance; Planning and Forecasting; Railroads;

Filing Info

• Accession Number: 01699673
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 25 2019 9:57AM