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Title Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS
ID_Doc 36990
Authors Büyüközkan, G; Göçer, F
Title Prioritizing the Strategies to Enhance Smart City Logistics by Intuitionistic Fuzzy CODAS
Year 2019
Published
DOI
Abstract Accurate, well-timed, and efficient delivery operations is a must for supply chains and logistics providers' survival in a digitally enhanced business environment. Sustainability, mobility and livability related objectives of Smart City Logistics (SCL) address the reduction of trucks, congestion and pollution. In order to accomplish this objective, all stakeholders must work together. In addition to strong collaboration among cities, supply chains, and logistics providers, digital enablers can resolve traditional challenges in last-mile logistics for sustainable, mobile and livable cities. While the approaches to enhance SCL are in abundance, prioritizing suitable SCL strategies is a non-trivial task. In order to improve the SCL and evaluate the required strategies, this paper develops a decision-making model based on the Combinative Distance Based Assessment (CODAS) under Intuitionistic Fuzzy (IF) setting and carries out a pioneering study to determine and prioritize the required SCL strategies. It proposes a new approach to support the claim, and analyzes the SCL for the evaluation system. Then, selection criteria are established to define SCL strategies and to develop a method based on IF CODAS and the prospect theory. Finally, the advantages, disadvantages, as well as the limitations of the proposed method are discussed. This study is one of the pioneering research with empirical contributions to the existing vastly conceptual discussion.
Author Keywords Intuitionistic Fuzzy; Intuitionistic Fuzzy CODAS; Decision-Making; Smart City Logistics; Strategy Listing
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Conference Proceedings Citation Index - Science (CPCI-S)
EID WOS:000558710000110
WoS Category Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; Mathematics, Applied
Research Area Computer Science; Mathematics
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