A decision support model for identification and prioritization of key performance indicators in the logistics industry

Show simple item record

dc.contributor.author Kucukaltan, Berk
dc.contributor.author Irani, Zahir
dc.contributor.author Aktas, Emel
dc.date.accessioned 2016-09-19T15:43:15Z
dc.date.available 2016-09-19T15:43:15Z
dc.date.issued 2016-09-03
dc.identifier.citation Berk Kucukaltan, Zahir Irani, Emel Aktas, A decision support model for identification and prioritization of key performance indicators in the logistics industry, Computers in Human Behavior, Volume 65, December 2016, Pages 346-358 en_UK
dc.identifier.issn 0747-5632
dc.identifier.uri http://dx.doi.org/10.1016/j.chb.2016.08.045.
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/10553
dc.description.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. en_UK
dc.language.iso en en_UK
dc.publisher Elsevier en_UK
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Logistics performance indicators en_UK
dc.subject Balanced scorecard en_UK
dc.subject ANP en_UK
dc.subject Multi-criteria decision making en_UK
dc.subject Stakeholders en_UK
dc.subject Social media en_UK
dc.title A decision support model for identification and prioritization of key performance indicators in the logistics industry en_UK
dc.type Article en_UK


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 International Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International

Search CERES


Browse

My Account

Statistics