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The purpose of this paper is to propose a novel weighting algorithm for fuzzy information axiom (IA) and to apply it to the evaluation process of 3D printers.

As a decision-making tool, IA method is presented to evaluate the performance of any design. Then, weighted IA methods are investigated and a new weighting procedure is introduced to the literature. Then, the existing axiomatic design methods and the proposed new method are classified into two groups: weighting based on information content and weighting based on design ranges. The weighting based on information content approach consists of four methods including pessimistic and optimistic approaches. The philosophy of the weighting based on design ranges is to narrow design ranges in order to decrease fuzziness in the model. To prove the robustness and the performance of the proposed weighting method, the results are compared with the existing methods in the literature. Then, the new approach is applied to evaluate 3D printers.

The results of the proposed study show that the proposed weighting algorithm has better performance than the old ones for IA. Therefore, the proposed weighting algorithm should be used for the weighting tool of IA thereafter.

An effective weighting method compatible with the philosophy of IA method has been proposed. Furthermore, the performances of 3D printers are compared by using the proposed method.

The supplier selection problem has gained great attention in business management literature. The first objective of this study is to determine the required variables in selecting the best suppliers and to develop a supplier selection model based on these selected variables. The second objective is to explain how an integrated AHP‐PGP model can be used in supplier selection decisions while minimizing suppliers' defects rate, rate of late order delivery, purchasing costs, and maximizing suppliers' scores and after‐sales service levels.

An integration of an analytic hierarchy process (AHP) and multi‐objective pre‐emptive goal programming (PGP) is used to consider both quantitative and qualitative factors in selecting the best suppliers and allocating the optimum order quantities among them.

The integrated model is presented with a real‐world application using source data provided by the manufacturing firm operating in an automotive industry in Turkey. Findings demonstrate that the integrated AHP‐PGP model can be useful to all firms in their supplier selection decisions.

The integrated model presented in this study could be used to incorporate criteria such as quantity discount, demand satisfaction and budget constraints, etc. Further, the AHP approach could be extended with the genetic algorithm or data envelopment analysis techniques in solving such a problem.

Although there is considerable research in the literature, this study differs from the literature by introducing stages of the AHP model extensively, and adding a service objective function related to the suppliers' after‐sales service levels. In addition, the paper is especially of interest to both practitioners and researchers.

Supplier selection for defence procurement is a crucial function of a Ministry of Defence. The Ministry spends huge amounts of money each year to procure a vast array of equipment, goods and services. The ongoing financial crisis demands less subjective and more cost-saving methods for selecting a supplier. The approach advocated in this article integrates Analytic Hierarchy Process (AHP) with Goal Programming (GP) in order to combine conflicting criteria to select the best suppliers and allocate optimum order quantities among them. This paper presents a model close to real-world situations. Findings demonstrate that cost savings is a feasible result along with a viable combination of conflicting criteria in the suppliers' selection area.

Unlike previous literature, this study offers a novel integrated fuzzy approach to the field of outsourcing decisions. The purpose of this paper is to use design ranges of evaluation criteria that satisfy the functional requirements (FRs) of decision makers to solve the outsourcing provider selection problem.

In this study, considering the expected significance of outsourcing evaluation criteria, and the FRs of decision makers expressed in linguistic terms, a robust multi-criteria decision-making (MCDM) tool based on the integrated use of fuzzy Step-wise Weight Assessment Ratio Analysis and weighted fuzzy axiomatic design methods is proposed for use in decision process.

The proposed method is applied to a Turkish chemical company. A sensitivity analysis is performed and the outcomes of the proposed integrated framework are compared with those of other MCDM methods such as fuzzy-based Technique for Order Preference by Similarity to Ideal Solution, fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje and fuzzy Multi-Objective Optimization on the basis of Ratio Analysis. This validates the usefulness and practicality of the proposed methodology.

The main contribution of this study is that it defines specific requirements that will assist company managers in eliminating alternatives that do not satisfy the needs and expectations of their company.

This paper compares the present study with other studies in the field of manufacturing. Additionally, it provides a well-documented case study, which makes the paper of value to researchers interested in the practical applications of MCDM methods.

This study aims to develop a push–pull factors theory of women entrepreneurship, to identify and prioritize the factors influencing Emirati women entrepreneurs, and also aims to implement the proposed theory in two cases: Emirati women entrepreneurs with business family and non-business family backgrounds.

The analytic hierarchy process (AHP) model was developed with 6 criteria and 19 sub-criteria, based upon the findings of previous studies. Data were collected using a questionnaire survey given to 20 Emirati women entrepreneurs in the United Arab Emirates (UAE). The respondents were selected on the basis of their family backgrounds. The data collected were interpreted and a priority vector was assigned to the criteria and sub-criteria.

A well-researched methodology was used for the synthesis of priorities and the measurement of consistencies. The findings show that education, skills and training are the three main criteria considered to be the most important factors that influence the growth and success of Emirati women entrepreneurs.

The model can be used by authors for future academic and entrepreneurial studies. The findings interpreted can help policymakers and related associations develop various policies based on the specific factors found to empower Emirati women entrepreneurs in an effective manner. This process will increase the participation of Emirati women in the entrepreneurial field. The research model had limited dimensions and the findings cannot be generalized. Hence, it would be valuable to conduct future study in other countries to generalize the findings. The model can be enhanced by including other factors, and alternatives could be based on types of sectors.

This study is the first of its kind to present an AHP model that contains most dimensions influencing the success and growth of Emirati women entrepreneurs and prioritizes the dimensions based on their importance.

This study aims to determine the ranking of the 81 provinces at the NUTS-3 level in Turkey with respect to the personal satisfaction and public services satisfaction by applying Fuzzy Multi-Criteria Decision-Making methods to the Life Satisfaction Survey Results.

Fuzzy TOPSIS, Fuzzy MULTIMOORA and Fuzzy ARAS are implemented to assess life satisfaction of the individuals who lived in provinces, based on Life Satisfaction Survey 2013 for Turkey’s national comparison. In the solution process, 14 indicators for personal satisfaction and 38 indicators for public services satisfaction were considered.

The results showed that personal health satisfaction, earnings from work satisfaction and monthly income satisfaction are the most important criteria in terms of personal satisfaction. Also, healthcare services satisfaction, judicial services satisfaction and education services satisfaction have the highest importance in terms of public services satisfaction. The final ranking of the 81 provinces is obtained by considered methods. According to the ranking results, there is no significant difference between the east and the west part of Turkey in terms of personal satisfaction, whereas there is a distinct difference between them in terms of satisfaction with public services.

This study is the first research for evaluating the ranking of the provinces at the NUTS-3 level in Turkey according to the Life Satisfaction Survey 2013 results considering 14 indicators for personal satisfaction and 38 indicators for public services satisfaction by using FMCDM approaches that have not been applied before.

Due to the current pandemic, the importance of logistics functions and decisions is well understood both at the level of companies and users. Logistics systems and related decisions are of vital importance in making supply chains effective, efficient and without disruption. Logistic pressure factors may emerge at different points along the logistics process, and given the role of logistics decisions as one of the important indicators of competitiveness, the determination of the logistics pressures that are likely to increase the costs of business, and their causative factors are a vital aspect of the logistics decision-making process. The study aims to provide assistance in the selection of the most ideal logistics decision by ranking the pressure factors affecting the logistics system, especially during the pandemic period for logistics enterprises operating in Ordu and Giresun provinces and which have a corporate identity.

In this study, it is aimed to make the most ideal logistics decision selection by ranking the pressure factors affecting the logistics system, especially during the pandemic period for the logistics enterprises operating in Ordu and Giresun provinces and having a corporate identity. For that purpose interval-valued Pythagorean fuzzy (IVPF)–analytic hierarchy process (AHP) based combinative distance-based assessment (CODAS) methodology was used. Additionally sensitivity and comparison analysis were discussed.

Competitive pressure was found as the most important pressure factor affecting the logistics system during the pandemic period. Change in regulatory rules was the pressure factor found to have the least effect on the logistics system. Using the weights of logistics pressure factors, “Operational Decisions” was found to be the most ideal logistics decision selection.

The findings provide support for the evaluation of logistical pressures and decision options by presenting a decision model capable of processing ambiguous information. During a pandemic or similar period, the study assists decision makers in determining a new route. The findings will also call business managers' attention to logistical pressure factors and lead them toward more realistic and feasible practices in the logistics decision-making process.

This study provided an effective and applicable solution to a decision-making problem in the logistics sector including logistics pressure factors and the selection of logistics decisions. In this context, a methodology was presented that will allow businesses to self-evaluate their own logistics pressure factors and the selection of optimal solutions.

Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.

To achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.

The feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.

The proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.

A new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.