A Novel Integrated Fuzzy-Rough MCDM Model for Assessment of Barriers Related to Smart Logistics Applications and Demand Forecasting Method in the COVID-19 Period

Željko Stević, Selçuk Korucuk (), Çağlar Karamaşa (), Ezgi Demir () and Edmundas Kazimieras Zavadskas ()
Additional contact information
Željko Stević: Faculty of Transport and Traffic Engineering, University of East Sarajevo, Doboj, Republic of Srpska Bosnia and Herzegovina
Selçuk Korucuk: Department of International Trade and Logistics, Bulancak Kadir Karabaş Vocational School, Giresun University, Giresun, Turkey
Çağlar Karamaşa: Department of Business Administration, Faculty of Business, Anadolu University, Eskişehir, Turkey
Ezgi Demir: Department of Management Information Systems, Gebze Technical University, Kocaeli, Turkey
Edmundas Kazimieras Zavadskas: Institute of Sustainable Construction, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania

International Journal of Information Technology & Decision Making (IJITDM), 2022, vol. 21, issue 05, 1647-1678

Abstract: During the pandemic period, smart logistics applications have rapidly changed the way organizations do business in order to provide competitive products and services while still remaining flexible. Smart logistics applications and demand forecasting, which have an important place in ensuring customer satisfaction and increasing competitive advantage, came to the fore even more in this period. However, smart logistics applications are often bogged down by several barriers, and then there is the need to choose the most ideal demand forecasting method despite these barriers. The main purpose of this study is to assess the barriers to the smart logistics applications in companies that receive and provide logistics services with corporate identity in Ordu Province, and to choose the most ideal demand forecasting method during the COVID-19 period. This study has the characteristic of a roadmap that helps the construction of smart logistics transformation applications by detecting barriers related to smart logistics applications and determining the most ideal demand forecasting alternative in logistics sector. Fuzzy FUCOM (FUll COnsistency Method)-based interval rough EDAS (Evaluation based on Distance from Average Solution) methodology was used to weight the barriers and to rank and choose the most ideal demand forecasting method during COVID-19 period, respectively.

Keywords: COVID-19; smart logistics implementation; demand forecasting methods; fuzzy FUCOM; interval rough EDAS (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622022500274
Access to full text is restricted to subscribers

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:wsi:ijitdm:v:21:y:2022:i:05:n:s0219622022500274

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622022500274

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().