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The purpose of this paper is to improve the complicated pairwise comparison problem and the consistency of analytic hierarchy process (AHP), the consistent fuzzy preference relation (CFPR) method is applied to select the best fashion design scheme in this study.

The first stage is to review the traditional AHP for fashion design scheme evaluation. The second stage is based on the procedure of CFPR to select the best fashion design scheme. The procedure includes: establishment of the fuzzy preference relation matrix of pairwise comparisons, calculation of criteria weight, and calculation of the evaluation value for ratings of fashion design schemes with respect to criteria. The final stage is to compare the procedures and results between AHP and CFPR for the evaluations of fashion design schemes.

For fashion design scheme selection, there are 76 data for fashion design scheme evaluation in AHP, but only 31 in CFPR. Comparing both AHP and CFPR methods, the rankings of the criteria weight are identical and the priority scores of the fashion design scheme are similar. The CFPR is more efficient than AHP, obviously, to solve the inconsistency of hierarchical decision-making problem.

This paper proposes the CFPR method for the selection of the best fashion design scheme. According to the finding of this study, the CFPR is proposed as a practicable option for solving complicated pairwise comparison problems in fashion design decision.

This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector.

From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure.

The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible.

Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

The purpose of this paper is to develop a novel hybrid multi-criteria decision-making (MCDM) model to help organizations select their knowledge-based strategy effectively. Knowledge management (KM) initiatives are often started with the selection of a strategy, which is a critical decision for a successful KM implementation.

KM initiatives are often started with the selection of a strategy, which is a critical decision for a successful KM implementation. Thus, the aim of this paper is to develop a novel hybrid MCDM model to help organizations select their knowledge-based strategy effectively.

Results illustrate that the proposed model is efficient to consider the complex interactions among criteria and provides a consistent decision with less pair-wise comparisons. Furthermore, a case study indicates that a “codification versus tacitness” strategy is preferred over other strategies considering nine main domain criteria.

The contribution of this paper is threefold: it addresses the gaps in KM literature on the effective and efficient assessment of KM strategy selection; it provides a comprehensive and systematic framework that combines analytic network process (ANP) and consistent fuzzy preference relations (CFPR) to assess KM implementation strategy; and it illustrates a real-world study to exhibit the applicability of the proposed approach and the efficacy of the framework.

The shipper selects a suitable shipping route and plans for a voyage in order to import and export cargo on the basis of published sailing schedules. The reliability of the sailing schedule will influence the shipper’s logistics expense, which means that the logistics costs will depend on the reliability of schedules published by container shipping companies. Therefore, it is important to consider factors which can cause delays would for container ships sailing on sea routes. The reliability of published sailing schedules can be affected by a number of different factors. This study adopts the multi-criteria decision making (MCDM) method to estimate the importance of the delaying factors in a sailing schedule. In addition, the consistent fuzzy preference relations (CFPR) method is applied to identify the subjective importance (weights) of the delaying factors. The entropy weight method combined with the actual performance of the container shipping company are both used when estimating the objective importance (weights) of the delaying factors. According to the analysis results, the criteria can be divided into four quadrants with different management implications, which indicate that instructions for chase strategy, sailing schedule control, fleet allocation, transship operation arrangement and planning for ports in routes are often ignored by container shipping companies. Container shipping companies should consider adjusting their operational strategies, which would greatly improve their operational performance.

The purpose of this paper is to make out a complete solution to logistic outsourcing problem in a medium‐scale organization by using consistent fuzzy preference relation (CFPR) and vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) method.

The initial approach to this research was to develop a comprehensive framework for logistic outsourcing problem and selection of most appropriate third party logistic (3PL) provider.

It has been found that the organization should outsource logistic activities. The alternatives (3PL providers) have also been ranked and the fifth 3PL provider has been termed as best third party logistic provider.

The parameters selected for this study and developed framework are applicable only to a medium‐scale organization manufacturing automobile parts in northern India.

This is probably the first time that an attempt has been made to apply the two‐phase methodology approach, using CFPR and VIKOR, to analyze a multi‐criteria logistic outsourcing problem. A case is provided which demonstrates how to solve logistic outsourcing, a multi‐criteria decision‐making problem.

Resilient route selection for oversized cargoes, one of the general bulk cargoes, has not been adequately optimized in terms of using the Arctic route. This study solves the problem of selecting the optimal shipping routes for oversized cargoes from Busan (South Korea) to Balkhash (Kazakhstan).

The study used the consistent fuzzy preference relation (CFPR) method, which is used to solve multi-criteria decision-making (MCDM) and uncertainty problems, to tackle the route selection. This method involves three procedures: first, the critical factors and alternative routes were obtained by the previous literature and an in-depth interview of experts of oversized cargo-handling with more than 20 years of working experience; second, the weightings for each critical factor were identified using the CFPR calculation process and third, alternative routes were evaluated using weighted critical factors.

The Northern Sea Route (NSR) combined with the inland waterways of Russia and Kazakhstan was first suggested for bulk carriers that handle oversized cargoes. The NSR could be a suitable route from Busan to Cape Kamenny of the Russian transshipment seaport, where oversized cargoes will be transferred to the river barge at Cape Kamenny, covering 4,913 km from the latter to Balkhash of Kazakhstan via the Ob/Irtysh River.

This study equips stakeholders in route selection for cargoes with strategies and methods to improve transportation efficiently and enhance shipping routes between Asia and the Commonwealth of Independent States (CIS). In addition to oversized cargoes, coal and timber from Russia can be transported to Asia using inland waterways and the NSR, which can also be used to transport plant equipment for petroleum refineries among Asian countries.

This is the first study to evaluate the suitability of the Artic route for oversized cargoes from South Korea to Kazakhstan. It provides a comprehensive evaluation framework of multimodal shipping routes and offers references for decision-makers when dealing with similar problems.

The purpose of this paper is to test the 5GP concept with measurement of the performance of Busan, Hong Kong, Singapore and Shanghai ports, employing a hybrid method of consistent fuzzy preference relation (CFPR), VIsekriterijumska Optimizacija i KOmpromisno Resenje (VIKOR) and PROMETHEE.

The authors developed the concept of the fifth generation ports (5GPs), and apply CFPR, VIKOR and preference ranking organization method for enrichment evaluations (PROMETHEE) to evaluate the 5GPs.

The performance of the ports of Hong Kong and Singapore is close to meet the definition of 5GP criteria. On the contrary, ports of Busan and Shanghai are still behind the 5GP stage in light of the majority of the evaluation criteria’s performance.

This paper studies four ports. More empirical tests are needed to verify the applicability of the 5GP concept toward other ports.

The findings provided port managers with the insight of how to improve their port to meet the criteria of 5GP.

New criteria and higher expectations of existing requirements present challenges to port managers for a need to raise the bar of service standards and develop new competencies.

The authors developed the concept of the 5GPs. Newly developed 5GP contributes to expanding the concepts of first to fourth generation ports developed by UNCTAD.

The purpose of this paper is to develop a qualitative framework for the selection of the most appropriate optimization algorithm for the multi-objective trade-off problem (MOTP) in construction projects based on the predefined performance parameters.

A total of 6 optimization algorithms and 13 performance parameters were identified through literature review. The experts were asked to indicate their preferences between each pair of optimization algorithms and performance parameters. A multi-criteria decision-making tool, namely, consistent fuzzy preference relation was applied to analyze the responses of the experts. The results from the analysis were applied to evaluate their relative weights which were used to provide a ranking to the algorithms.

This study provided a qualitative framework which can be used to identify the most appropriate optimization algorithm for the MOTP beforehand. The outcome suggested that non-dominated sorting genetic algorithm (NSGA) was the most appropriate algorithm whereas linear programming was found to be the least appropriate for MOTPs.

The devised framework may provide a useful insight for the construction practitioners to choose an effective optimization algorithm tool for preparing an efficient project schedule aiming toward the desired optimal improvement in achieving the various objectives. Identification of the absolute best optimization algorithm is very difficult to attain due to various problems such as the inherent complexities and intricacies of the algorithm and different class of problems. However, the devised framework offers a primary insight into the selection of the most appropriate alternative among the available algorithms.

The purpose of this paper is to develop comprehensive criteria for evaluating fashion design schemes and used an integrated model which considers the interrelation between the clusters of evaluation and the influence between criteria for evaluating alternative fashion design schemes.

The integrated approach uses the advantages of all three methods: the Decision-Making Trial and Evaluation Laboratory (DEMATEL) can be used to analyse the interrelations between the major clusters of fashion design evaluation. The analytical network process can calculate the criterion weight that is adjusted based on the influence between different elements in the decision framework. The Visekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) determines the best fashion design by ranking a set of designs by using ten conflicting criteria.

Style is the decisive dimension because it is highly affected by other clusters. The comfort of the style is the most crucial criterion. “Veracious” is the best and most preferred design scheme.

The study develops the decisive cluster and criteria in designing a fashion design scheme. The proposed approach can be used as a decision analysis tool in fashion design and other fields and has various advantages (e.g. considering interrelations between clusters and influences between criteria, and ranking a set of alternatives), and therefore, is appropriate for practical circumstances.

Globalisation and liberalization of today's markets economy has posed new challenges to all manufacturing organizations, irrespective of their size and sector, for effective utilization of advanced manufacturing technologies (AMTs) for sustaining their competitiveness. The purpose of this paper is to provide a new insight into the use of hybrid methodology using analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach, which is a multi‐criteria decision‐making methodology for measuring the effective utilization of advanced manufacturing technologies.

A hybrid methodology using analytical hierarchy process and technique for order preference by similarity to ideal solution approach has been applied in this study. In this research work, seven factors such as top management support, resistance of employees, pay scale, training to employees, industry‐institute‐interaction, proper planning and team structure have been selected to determine the priority weights of attributes by using AHP. TOPSIS method is then employed to achieve the final ranking results. To benchmark the success possibility of AMTs utilization, AHP has been applied.

Top management support, resistance of employees and pay scale have been ranked as first, second and third important sub‐objectives for effective utilization of AMTs. While industry‐institute‐interaction, proper planning, training to employees and team structure have been placed at fourth, fifth, sixth and seventh positions for effective utilization of AMTs. It has been further noted that by using AHP, the successful utilization of AMTs can be found out.

The parameters selected for this study are applicable to the northern India manufacturing industry.

An attempt has been made to apply hybrid methodology approach using AHP and TOPSIS for effective utilization of AMTs. This is probably the first time that an attempt has been made to apply the hybrid methodology using AHP‐TOPSIS‐AHP for benchmarking the success possibility of utilization of AMTs in the northern Indian manufacturing industry.