A meta-frontier network data envelopment analysis approach for the measurement of technological bias with network production structure
Ming-Miin Yu () and
Li-Hsueh Chen ()
Additional contact information
Ming-Miin Yu: National Taiwan Ocean University
Li-Hsueh Chen: Fo Guang University
Annals of Operations Research, 2020, vol. 287, issue 1, No 20, 495-514
Abstract:
Abstract Typically, the meta-frontier network data envelopment analysis model can be used to evaluate the technological gaps in individual stages simultaneously. However, the technological gap in each stage could also have a biased effect, i.e. one which improves the productivity of a subset of input or output factors. Since decision-making units may face different operational technologies, and have two-stage network structures, this study develops a new approach to investigate the favored direction of technology shift. The novelty of this approach is to identify that the technological gaps could affect the overall production function, both with the input technological bias in the first stage and with the output technological bias in the second stage. By comparing the difference between meta-technology and group technology, the favored direction of technology shift for individual decision-making units can be judged. The proposed approach is illustrated using data from 109 Taiwanese tourist hotels in 2015.
Keywords: Technological bias; Efficiency; Network data envelopment analysis; Meta-frontier approach (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://link.springer.com/10.1007/s10479-019-03436-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:287:y:2020:i:1:d:10.1007_s10479-019-03436-3
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1007/s10479-019-03436-3
Access Statistics for this article
Annals of Operations Research is currently edited by Endre Boros
More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().