Loading...
A decision support model for identification and prioritization of key performance indicators in the logistics industry
Kucukaltan, B. Irani, Zahir Aktas, E.
Kucukaltan, B.
Irani, Zahir
Aktas, E.
Publication Date
2016-12
End of Embargo
Supervisor
Rights
© 2016 Elsevier B.V. Reproduced in accordance with the publisher's
self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
28/08/2016
Institution
Department
Awarded
Embargo end date
Collections
Additional title
Abstract
Performance measurement of logistics companies is based upon various performance indicators. Yet, in the logistics industry, there are several vaguenesses, such as deciding on key indicators and determining interrelationships between performance indicators. In order to resolve these vaguenesses, this paper first presents the stakeholder-informed Balanced Scorecard (BSC) model, by incorporating financial (e.g. cost) and non-financial (e.g. social media) performance indicators, with a comprehensive approach as a response to the major shortcomings of the generic BSC regarding the negligence of different stakeholders. Subsequently, since the indicators are not independent of each other, a robust multi-criteria decision making technique, the Analytic Network Process (ANP) method is implemented to analyze the interrelationships. The integration of these two techniques provides a novel way to evaluate logistics performance indicators from logisticians' perspective. This is a matter that has not been addressed in the logistics industry to date, and as such remains a gap that needs to be investigated. Therefore, the proposed model identifies key performance indicators as well as various stakeholders in the logistics industry, and analyzes the interrelationships among the indicators by using the ANP. Consequently, the results show that educated employee (15.61%) is the most important indicator for the competitiveness of logistics companies.
Version
Accepted manuscript
Citation
Kucukaltan B, Irani Z and Aktas E (2016) A decision support model for identification and
prioritization of key performance indicators in the logistics industry. Computers in Human
Behavior. 65: 346-358.
Link to publisher’s version
Link to published version
Link to Version of Record
Type
Article