WeIghtIng the factors affectıng logıstıcs outsourcıng

Abstract

Today, growing and changing competitive conditions, products, and services, free movement of labor, and businesses with the information they develop strategies that create value to obtain a competitive advantage. Now, final buyers have the convenience of purchasing the products they demand with the features and conditions they want and at the price they accept. In such an environment, businesses use their supply chain and logistics activities more effectively and efficiently than their competitors. Today, achieving a strategic superiority in a global market where the content and quality of the products are the same is only possible by delivering the desired products to the customer at the desired price, at the desired time, in the desired amount, through the right channel, as quickly as possible and without any damage. In such a situation, the desire to focus on the main activities of the enterprises, the need for effective logistics operations, etc. logistics outsourcing has increased rapidly for reasons. Businesses can carry out logistics activities requiring expertise thanks to third party logistics (3PL) service providers in the field such as transportation, storage, customs clearance, without investing in logistics. For logistics outsourcing to be beneficial, a correct logistics service provider must be selected under the needs of the business. Selecting the right logistics service provider is important in increasing the benefit of outsourcing. In this study neutrosophic AHP was used to prioritize the factors.

Higher education and science popularization: Can they achieve coordinated growth?

“…Two categories of methods, which are objective category and subjective category, are usually used to assess the weight of indices when measuring the coordinated growth relationship between systems. For the objective category, including cluster analysis method, entropy weight analysis method, main component analysis method, Vlse Kriterijumska Optimizacija Kompromisno Resenje method (VIKOR), ranking of alternatives through functional mapping of criterion sub-intervals into a single interval method (RAFSI), criteria importance through inter-criteria correlation method (CRITIC), etc., the methods obtain weights of indices by calculating data objectively, therefore, the weights are much more objective with less bias or errors; however, some problems will be encountered if we use these objective methods; for instance, some important indices will be eliminated if main component analysis method is solely used; the accuracy is doubtful if cluster analysis method is used solely without combing other methods; VIKOR requires the accuracy of weight coefficients of the criterion, which in practice is somehow difficult to obtain; entropy, CRITIC, and RAFSI may not correct and may bias the weights in certain multi-criteria decision-making cases if they are used solely [ 43 – 47 ].…”

Measuring the Return on Investment of Training Modules of Electrical Protection and Uninterruptible Power Supply (UPS) Using the Corrective and AHP Approaches

“…Researchers have introduced some prioritizing methods such as a combination of analytical hierarchy process (AHP) and Ranking of Alternatives through Functional mapping of criterion subintervals into a Single Interval (RAFSI) [12], Fuzzy Measurement Alternatives and Ranking according to Compromise Solution (F-MARCOS) [13], third-party logistics [14], and Data-Envelopment-Analysis-based approach [15]. Moreover, the sensitivity analysis methods are also provided in the literature, including Full Consistency Method (FUCOM) [16], hybrid fuzzy MCDM [17], fuzzy Pivot Pairwise Relative Criteria Importance Assessment and fuzzy Measurement Alternatives and Ranking according to the Compromise Solution [18], Level Based Weight Assessment and fuzzy Multiattributive Border Approximation Area Comparison [19], and Best Worst Method and Multiattributive Ideal-Real Comparative Analysis [20].…”

Research on Application Performance Index System of Pure Electric Buses Based on Extensible Cloud Model

“…Badi et al [19] obtained the most important criteria for location selection based on the FUCOM method, and Alossta et al [20] solved the optimal location selection problem through the AHP method combined with the RAFSI model. In the field of logistics, Karamaşa et al [21] identified priority factors for the impact of logistics outsourcing based on Neutrosophic AHP. Bakır et al [22] and Blagojević et al [23] combined Fuzzy AHP with Fuzzy MARCOS and DEA, respectively, to study the application of MCDM in transportation.…”