PMID- 36374384
OWN - NLM
STAT- MEDLINE
DCOM- 20230824
LR  - 20230824
IS  - 1614-7499 (Electronic)
IS  - 0944-1344 (Print)
IS  - 0944-1344 (Linking)
VI  - 30
IP  - 39
DP  - 2023 Aug
TI  - A hybrid Bayesian BWM and Pythagorean fuzzy WASPAS-based decision-making 
      framework for parcel locker location selection problem.
PG  - 90006-90023
LID - 10.1007/s11356-022-23965-y [doi]
AB  - One of the main causes of the significant commercial vehicle traffic in the city 
      region is last-mile deliveries. Parcel lockers, which are one of the easiest and 
      most environmentally friendly solutions for last-mile delivery, are one of the 
      most studied subjects recently. The parcel locker ensures consumer privacy while 
      being quick and efficient. Its full-time service can effectively address the 
      issue of student and office worker pickup. In this paper, the location of a 
      parcel locker intended to be established in the most convenient location in 
      Besiktas district of Istanbul, Turkey has been determined. This problem can be 
      solved using a multi-criteria decision-making (MCDM) structure due to the 
      availability of numerous aspects that must be considered while choosing the 
      optimum location. Additionally, the benefit of fuzzy logic is employed to 
      translate expert opinions into mathematical expressions and incorporate them into 
      decision-making processes. To choose the ideal location for the parcel locker, a 
      novel model integrating the Bayesian Best Worst Method (B-BWM) and Pythagorean 
      fuzzy Weighted Aggregated Sum Product Assessment (PF-WASPAS) approaches is 
      proposed for the first time in the literature. Additionally, a sensitivity 
      analysis is conducted to evaluate the model's robustness. As a consequence, the 
      suggested model effectively identifies the best location for a parcel locker in 
      Istanbul.
CI  - (c) 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, 
      part of Springer Nature.
FAU - Yalcin Kavus, Bahar
AU  - Yalcin Kavus B
AUID- ORCID: 0000-0001-5295-1631
AD  - Department of Industrial Engineering, Nisantasi University, 34398, Istanbul, 
      Turkey.
FAU - Ayyildiz, Ertugrul
AU  - Ayyildiz E
AUID- ORCID: 0000-0002-6358-7860
AD  - Department of Industrial Engineering, Karadeniz Technical University, 61080, 
      Trabzon, Turkey. ertugrulayyildiz@ktu.edu.tr.
FAU - Gulum Tas, Pelin
AU  - Gulum Tas P
AUID- ORCID: 0000-0003-1644-256X
AD  - Department of Engineering Systems and Services, Delft University of Technology, 
      2628 BX, Delft, Netherlands.
FAU - Taskin, Alev
AU  - Taskin A
AUID- ORCID: 0000-0003-1803-9408
AD  - Department of Industrial Engineering, Yildiz Technical University, 34349, 
      Istanbul, Turkey.
LA  - eng
PT  - Journal Article
DEP - 20221114
PL  - Germany
TA  - Environ Sci Pollut Res Int
JT  - Environmental science and pollution research international
JID - 9441769
SB  - IM
MH  - Humans
MH  - *Decision Making
MH  - Bayes Theorem
MH  - *Fuzzy Logic
MH  - Cities
MH  - Turkey
PMC - PMC9660107
OTO - NOTNLM
OT  - Bayesian best worst method
OT  - Location selection
OT  - Parcel locker
OT  - Pythagorean fuzzy numbers
OT  - WASPAS
COIS- The authors declare no competing interests.
EDAT- 2022/11/15 06:00
MHDA- 2023/08/24 06:42
PMCR- 2022/11/14
CRDT- 2022/11/14 11:31
PHST- 2022/08/08 00:00 [received]
PHST- 2022/10/29 00:00 [accepted]
PHST- 2023/08/24 06:42 [medline]
PHST- 2022/11/15 06:00 [pubmed]
PHST- 2022/11/14 11:31 [entrez]
PHST- 2022/11/14 00:00 [pmc-release]
AID - 10.1007/s11356-022-23965-y [pii]
AID - 23965 [pii]
AID - 10.1007/s11356-022-23965-y [doi]
PST - ppublish
SO  - Environ Sci Pollut Res Int. 2023 Aug;30(39):90006-90023. doi: 
      10.1007/s11356-022-23965-y. Epub 2022 Nov 14.