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In recent decades, many managers have conceived the radical role of knowledge in acquiring a competitive advantage and pursuing organizational strategic goals. Therefore, knowledge management is now a competitive requirement in organizations. However, if proper infrastructures and necessary prerequisites are not provided for executing such a process, the result will be nothing except failure and resource waste. Therefore, it is necessary that organizations identify effective factors for their readiness in executing knowledge management. The purpose of this study is identifying and prioritizing of effective constructs in readiness of knowledge management implementation by using fuzzy analytic hierarchy process (AHP).

In the present study, the relevant literature is initially reviewed and then seven factors and 19 affecting indicators on knowledge management readiness are identified by using a questionnaire for knowledge management elites which also constitute the research conceptual model. Finally, the weight of each factor is determined by fuzzy analytical hierarchy process and the readiness priority and preference of each factor are discussed.

The results of fuzzy analytic hierarchy process show that the management factor is recognized as the most effective factor in knowledge management execution readiness.

The model proposed in this study is applicable to the academic culture. Modification of the proposed model may be needed in applying this model to other environments.

As limited studies have been carried out on identifying and prioritizing of effective constructs in readiness of knowledge management implementation by using fuzzy analytic hierarchy process, the findings of this study will be useful in identifying and assessing the main components in readiness of knowledge management implementation in the research and training centers.

The need for the thermal insulation of masonry buildings in Algeria is no longer debated. This paper aims to propose an integrated fuzzy multi-criteria decision aid method for the thermal insulation of masonry buildings to rank the thermal insulation solutions.

The proposed method combines the fuzzy analytical hierarchy process with the fuzzy preference ranking organization method for enrichment evaluation.

A case study using the proposed method is detailed in this paper. The building users’ preferences obtained by the fuzzy analytical hierarchy process had a higher level of consistency and accuracy. The case study demonstrates how in a highly uncertain field such as thermal insulation of masonry buildings, the fuzzy preference ranking organization method for enrichment evaluation can prevent the loss of valuable evaluation data and overcome difficulty in integrating linguistic assessments of the thermal insulation alternatives.

The proposed method extends current knowledge by using the fuzzy analytical hierarchy process to consider uncertainties regarding the building users’ preferences, and the fuzzy preference ranking organization method for enrichment evaluation to get a complete ranking of the thermal insulation solutions taking into account the uncertainties related to the alternatives’ evaluations.

This paper aims to propose a new approach called “analytical hierarchy process weighted fuzzy linear programming model (AHP‐FLP)” for supplier selection.

A hybrid method of supplier selection, AHP‐FLP is applied to a real industry case. The weights of the various criteria, taken as local weights from a given judgment matrix, are calculated using analytical hierarchy process (AHP) that are also considered as the weights of the fuzzy linear programming model. This new model is compared with the classical AHP method.

This study concluded that the AHP‐FLP method outperforms the AHP method for supplier selection with respect to restricted supplier selection criteria. Drawing on a real case, Supplier 1 was identified to be the best supplier through the AHP model under no restrictions, which contradicts the finding that Supplier 2 was selected as the best supplier by the AHP‐FLP model subject to constraints.

More research is definitely called for within the context of studying a more complex supply chain with multiple supply network and nodes. There is also a crucial need for investigating other hybrid methods to find the optimum supplier.

The findings of this study indicate that the weights of supplier selection criteria calculated by the AHP‐FLP model are in line with the actual supplier selection decision of purchasing managers. Since the AHP‐FLP model is relatively more difficult to implement compared with the crisp AHP, its application will be more appropriate for high‐value components where stringent purchasing criteria are required. In contrast, AHP remains an appropriate approach for relatively lower value components (C class).

The novelty of this study lies in the application of a hybrid approach to a real industry case. This study has dealt with one of the most important subjects in supply chain management, providing a better decision for supplier selection using appropriate quantitative techniques.

This paper aims to describe an application of hybrid Multi Criteria Decision Making (MCDM) technique for the selection of wastewater treatment (WWT) technology for treating wastewater.

The proposed approach is based on Analytical Hierarchy Process (AHP) under fuzzy environment, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) and hierarchy Grey Relation Analysis (GRA) techniques. Two models are proposed to evaluate the best WWT. The first model, Fuzzy Analytical Hierarchy Process (FAHP) is integrated with Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) technique. The second model, FAHP is integrated with hierarchy Grey Relation Analysis (GRA) technique. The Fuzzy Analytical Hierarchy Process (FAHP) is used to determine the weights of criteria and then ranking of the WWT technology is determined by PROMETHEE and GRA.

An efficient pair‐wise comparison process and ranking of alternatives can be achieved for WWT technology selection through the integration of FAHP and PROMETHEE, FAHP and GRA.

The paper highlights a new insight into MCDM techniques to select an optimum WWT technology selection for the paper manufacturing industry.

An undergraduate civil engineering programme is assessed for its relevance to the building construction sector. Its contrast from the existing curriculum structure is also highlighted.

The curriculum is clustered into 15 groups based on disciplines. A pairwise comparison of groups is conducted by experts from the building construction sector. Expert judgements are analysed using Fuzzy Analytical Hierarchy Process (Fuzzy AHP) to determine the groups' order based on their importance in preparing students for a career in the building construction sector.

Concrete Technology, Structural Design and Analysis, and Building Technology and Town Planning emerged as the three most essential course groups, followed by Construction and Project Management, Surveying, and Geotechnical and Allied. Foundational Science and Math, Hydrology/Water Resource Engineering, and Computing and Programming came last in the order.

Relying on a curriculum from a specific region, generalizability to other geographical areas is limited. The perspective of building construction sector professionals excludes the views of other stakeholder groups within the sector.

The study allows universities in general to enhance students' job prospects in construction by calibrating course group priorities and aligning skills with industry needs, thereby potentially improving employability, and boosting the industry-academia relationship.

Fuzzy AHP has been utilized by building construction industry experts to assess the relevance of an undergraduate civil engineering curriculum. Findings serve as a valuable reference for implementing positive curriculum changes to potentially enhance student employability.

The purpose of this paper is to propose a multi-criteria supplier selection model using fuzzy analytical hierarchy process (FAHP) approach for a leading automobile company in India.

FAHP approach followed by a sensitivity analysis has been used.

In this study, a FAHP-based supplier selection model is proposed to provide useful insights in choosing appropriate suppliers in dynamic situations in order to enhance long-term relationship with them.

This study proposes a supplier selection model for an automobile industry which often faces heterogeneous supply environments. This model may have a high acceptability where a large number of suppliers are available to supply the materials or provide the services. As analytic hierarchy process is the most widely used methodology for supplier selection, however, it becomes less efficient in case of inconsistencies observed in the data. However a FAHP-based approach may overcome this difficulty.

It contributes to supplier selection process and points out the importance of supplier selection problem, especially in the context of multi-criteria decision-making in Indian scenario.

This paper aims to identify and reduce possible process failures occurred in warehouse.

This research used risk analysis method FMEA combined with fuzzy-analytical hierarchy process (AHP). Design FMEA will direct the failure mode or failure of components into levels and will use it to analyze the product before it used in manufacturing processes. Design FMEA has a major point on the failure mode that caused inefficiency in the design while fuzzy-AHP used to reduce subjectivity in the weighting process.

The results show that high inventory is the dominant factor that must be controlled by the company to prevent the risk of failure processes in the warehouse, followed by the number of stocks that do not match with existing records, and misplacement of machines and/or materials.

This research used risk analysis method FMEA combined with fuzzy-AHP to identify and reduce the possible process failures in warehousing.

The purpose of this paper is to provide a good insight into the use of fuzzy Analytical Hierarchy Process (fuzzy AHP) approach that is a multi‐criteria decision‐making methodology in evaluating the benefits of information‐sharing decision problems.

In this study, the integration of AHP with the fuzzy synthetic extent analysis method (fuzzy AHP) is proposed in evaluating the benefits of information‐sharing decision problems as a framework to guide managers.

Findings demonstrate that the customer requirement and operational information alternatives are the preferred key decisions, which all supply chain partners might agree to share with one another. Further, it can also be concluded that the planning and financial information alternatives have almost the same importance.

Fuzzy AHP is a highly complex methodology and requires more numerical calculations in assessing composite priorities than the traditional AHP and hence it increases the effort. In addition, fuzzy methodology could be extended with the other multi‐criteria decision‐making (MCDM) methods such as Analytical Network Process (ANP), TOPSIS, ELECTRE and DEA techniques in solving such a problem.

There is a lack of research in the literature to deal directly with the uncertainty of human judgements in evaluating the benefits of various information‐sharing decisions in a supply chain. Therefore, fuzzy AHP is an appropriate methodology to select the various types of information and has the ability to be used as a decision‐making analysis tool since it handles uncertain and imprecise data. In addition, the paper is especially of interest to managers as they make decisions on which types of information they should share with their supply chain partners.

Airport construction is extremely different than the construction of any other transport infrastructure. It is a vital area affecting both the environment and the economy. Therefore, sustainable selection of building materials represents a very important step. The main objective of this paper was to develop a set of sustainable assessment criteria (SAC) to assist design team members in the selection between two different material alternatives when constructing a new runway in Kuwait international airport. The proposed materials were asphalt or concrete.

A set of 24 sub-criteria were developed, those were emerged from three main criteria: technical, environmental and socio-economic. Fuzzy analytical hierarchy process (FAHP) was employed to assign weights and to measure the relative importance of these criteria for the material alternatives selection. The prioritizing process for criteria was based on a survey of 100 responses.

It had been concluded from the use of FAHP that asphalt material was a better alternative in maintainability, ease of construction, health and safety, initial cost and energy saving. Concrete was better in fire resistance, durability, decay resistance, energy saving and thermal insulation, maintenance cost, aesthetics, minimizing pollution, impact on air quality, low toxicity, environmentally disposal sound system, amount of likely wastage and raw material extraction method.

Develop a set of SAC to assist design team members in deciding between two material alternatives to construct a runway.