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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.

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Aircraft’s training is crucial for a flight training organization (FTO). Therefore, an important decision that these organizations should wisely consider the choice of aircraft to be bought among many alternatives. The criteria for evaluating the optimal training aircraft for FTOs are collected based on the survey approach. Single valued neutrosophic sets (SVNS) have the degree of truth, indeterminacy, and falsity membership functions and, as a special case, neutrosophic sets (NS) deal with inconsistent environments. In this regard, this study has extended a single-valued neutrosophic analytic hierarchy process (AHP) based on multi-objective optimization on the basis of ratio analysis plus a full multiplicative form (MULTIMOORA) to rank the training aircraft as the alternatives. Moreover, a sensitivity analysis is performed to demonstrate the stability of the developed method. Finally, a comparison between the results of the developed approach and the existing approaches for validating the developed approach is discussed. This analysis shows that the proposed approach is efficient and with the other methods.

PurposeForests are negatively affected from rapid world population increase and industrialization that create intense pressures on natural resources and the possibility of an achieving circular economy. Forests can be considered as essential resources for providing sustainable society and meeting the requirements of future generations and circular economy. Therefore sustainable production tools as part of circular economy can be handled as one of the basic indicators for achieving circular economy. Accordingly the main purpose of this study is developing a novel rough – fuzzy multi-criteria decision-making model (MCDM) for evaluation sustainable production for forestry firms in Eastern Black Sea Region.Design/methodology/approachFor determining 18 criteria weights a novel Rough PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method is developed. Eight decision-makers (DMs) participated in the research, and to obtain group rough decision matrix, rough Dombi weighted geometric averaging (RNDWGA) operator has been applied. For evaluation forestry firms fuzzy MARCOS (Measurement of alternatives and ranking according to COmpromise solution) method was utilized.FindingsAfter application developed model the fourth alternative was found as the best. Sensitivity analysis and comparison were made to present the applicability of this method.Originality/valueDevelopment of novel integrated Rough PIPRECIA-Fuzzy MARCOS model with emphasis on developing new Rough PIPRECIA method.

PurposeSustainable supply chain management (SSCM) practices and policies are necessary for businesses that seek to take part in international markets and ensure any form of competitiveness. Over time, and especially in the recent past, researchers, governments, and other policymakers have made use of broad and systematic approaches and come to appreciate the value-enhancing activities of sustainability.Design/methodology/approachBusinesses have embraced the integration of sustainable policies and practices within the supply chain as a critical step in ensuring the efficiency of their operations. It is clear in previous studies and operational programs of enterprises that SSCM practices accord businesses certain benefits including improving their environmental, social, and economic performance, and increasing their ecological awareness by way of influencing performance elements within supply networks in enterprises. The study examines the factors influencing performance and theories of SSCM using a neutrosophic method in the textile industry.FindingsSSCM performance is thus of great importance in ensuring business success and competitiveness, realizing customer satisfaction, and leaving the environment in a desirable state for future generations. Performance management, by assisting in the decision-making by managers and ensuring an adequate level of internal interaction, is an integral part of assimilating sustainability management into businesses. SSCM theories also have a strong impact on the determination of the sources of competitive advantage through effective utilization of business capabilities to solve environmental and social challenges that may affect business performance.Originality/valueIn line with the benefits highlighted, this study seeks to evaluate and select the factors affecting SSCM performance and theory in textile enterprises with corporate identity in Ordu and Giresun provinces following a neutrosophic approach. To this end, the elements obtained from the literature review are evaluated using the MULTIMOORA-mGqNN method.

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