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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.

The use of Analytical Hierarchy Process (AHP) is an effective way to deal with qualitative decision areas of operations management. Four published applications of AHP are briefly reviewed in forecasting, supplier selection, facility location, and choice of technology. Furthermore, four more potential applications are suggested in other areas of operations management, including product design, plant layout, maintenance frequency selection, and choice of logistic carrier. In addition, suggestions for other areas of research are discussed.

Refractory materials are now used in all major industries that demand high-temperature resistance, including petrochemicals, steel, cement and aviation. Businesses must decrease operating costs, enhance product technology, sell well and manage corporate risks in decision-making, notably supplier selection, to be more competitive. The study aims to determine the key criteria and factors of supplier selection and to evaluate the importance of the key factor of the supplier selection criteria for the refractory materials manufacturers in Taiwan.

Analytical hierarchy process (AHP) is used to rank these factors for the decision maker. The AHP method is suitable for verifying refractory supplier selection criteria and providing references. The weighted loss scores for each supplier are then determined using the relative importance as the weights. Supplier selection criteria are ranked using their aggregate weighted loss scores. The provider with the lowest loss score should be chosen.

Product quality is the most significant of the five criteria: product quality, production technology, logistics capacity, service capability and supplier background. Professionalism is the most significant aspect of product quality, whereas equipment and capacity are vital in manufacturing techniques. The studies also show that the delivery rate is essential for logistics and service capabilities.

This research has important implications for refractory suppliers in promptly fine-tuning the production and service to enhance customer satisfaction, which is key to business sustainability.

The application of an AHP technique to a real-world industrial issue is what makes this research unique. This research addressed one of the most critical topics in supply chain operations by offering better judgement for supplier selection via the use of suitable quantitative methodologies.

Selection of the design concepts is one of the significant activities in product development process. Most of the products are usually failed due to inappropriate decision during the selection of the design concepts at the early stage of product development process. The determination of the greatest selection of design concepts at the conceptual design stage is a crucial decision due to a poor design concept which can never be compensated for by a good detailed design and it will implicate great expense of redesign cost. Analytical Hierarchy Process (AHP) is one available method in forming a systematic approach for a single decision maker or a group decision maker, is employed to solve such problem. In this paper, 7 design concepts of wheelchair designs were considered as a case study. The AHP through utilizing Expert Choice software was implemented to determine the most suitable design concept of wheelchair design at the conceptual design stage. The sensitivity analysis was performed to test the stability of the priority ranking and to increase the confidence in the selection of design concepts.

The purpose of this paper is to present a detailed literature review of the recent applications of the analytic hierarchy process (AHP) and analytic network process (ANP) group decision‐making methodologies.

Among more than 600 related papers published in the period 2005‐2009, a total of 232 application articles published in highly reputed international academic journals were selected and referenced in this paper. Papers were categorized according to application areas, subject titles, publication date, country of origin, academic journals, and integrated methodologies, and are summarized herein by various tables and charts.

The findings show that during the years 2005‐2009, use of the AHP technique has continued to increase exponentially. Moreover, it is expected that ANP will gain more popularity in the future, as the benefits of ANP become better understood. Applications of AHP have been dominant in manufacturing, followed by the environmental management and agriculture field, power and energy industry, transportation industry, construction industry, and healthcare. Other remarkable application fields include education, logistics, e‐business, IT, R&D, telecommunication industry, finance and banking, urban management, defense industry and military, government, marketing, tourism and leisure, archaeology, auditing, and the mining industry.

The study does not consider theoretical based AHP or ANP articles. Also the search excluded conference proceedings, masters' theses, and doctoral dissertations.

It is hoped that this study will guide practitioners in future work towards advancement of these techniques and will help the managers to select better decisions by making use of these methodologies.

The paper presents a comprehensive literature review of recent applications of AHP, and also ANP decision tools over the period 2005‐2009. Furthermore, the paper covers fuzzy AHP and fuzzy ANP extensions that are becoming popular methods in some application areas of traditional AHP and ANP.

The purpose of this paper is to present a new warranty model to improve warranty management. As a case study, the developed model has been applied on an industrial vehicle manufacturing company. The model is composed of quality function deployment (QFD) and interval-based analytical hierarchy process (i-AHP). The i-AHP is an extension of the concept of analytical hierarchy process (AHP) that takes the benefits of interval computations in order to mitigate the shortcomings of AHP and fuzzy AHP.

Using a combination of i-AHP and QFD, the authors analyzed the several options and alternatives available, weighting each one by means of an interval pair-wise comparison. Using collected data, the authors have shown how to map the capability of each option against each alternative and thereby build a relationship matrix under the QFD approach based on interval computations.

The use of i-AHP&QFD integrated methodology helps to identify the best options to solve several decision problems in diverse fields and could be applied successfully in warranty management. This methodology is especially useful when dealing with several options and equal numbers of alternatives for each warranty option.

The case study includes competitiveness analysis at the first house of quality (HOQ), but not at the subsequent HOQ, due to a lack of information from the relevant competitors. However, the paper demonstrates the kind of competitiveness analysis at the first HOQ which can be extended to all subsequent HOQs.

The research would be useful to academics and practitioners in developing integrated versions of the QFD and i-AHP methodologies to improve warranties.

This study contributes to the diffusion of a new form of integrated warranty model, through the presentation of practical examples of industrial vehicle warranty management. Also, the model presents the i-AHP in order to quantify and compare variables via the use of geometrical averages and to synthesize a subsequent solution.

The purpose of this paper is to provide an integrated approach that prioritizes organizational key performance indicators (KPIs) in terms of the criteria of SMART (Specific, Measurable, Attainable, Realistic, Time‐sensitive) goal setting.

The research was carried out using the analytical hierarchy process (AHP) technique as the basis for pairwise comparisons of SMART criteria, considering each KPI.

A new approach is outlined, encompassing step‐by‐step guidelines for decision makers to conduct the prioritization process of SMART KPIs. The results of the case study highlight the applicability of the proposed approach and the calculation process for prioritizing KPIs.

The rating scales used in the AHP analysis are conceptual; although it identifies which dimensions require improvement, the proposed approach does not provide guidance on an appropriate action plan to address deficiencies; another limitation is that the framework adopted only the SERVQUAL service dimensions.

This paper gives a novel approach for prioritization of KPIs. The proposed approach has a holistic mechanism; it could empower decision‐making teams; it is capable of enhancing advanced quality engineering approaches; and provides great opportunities for future research.

The purpose of this paper is to show that there is a wealth of academic literature that qualitatively examines the outsourcing and offshoring from a go/no go perspective. The paper examines the complex “where to outsource” question by applying a quantitative approach called Analytic Hierarchy Process (AHP).

The authors examine a Fortune 500 company's real‐world decision about where to outsource and summarize the current selection process employed by the company. We then apply our AHP model to the company's decision and compare the results.

There are four major findings: the location selection decision is a component of the outsource supplier selection decision; the AHP model effectively manages the complexity of the decision making process, incorporating all decision criteria harmoniously; a method such as AHP, which is able to incorporate both qualitative and quantitative criteria into evaluations, would streamline the decision‐making process; and the AHP process allows firms to look at a portfolio of choices and determine which firms are basically equal in qualifications.

The research implies that: (AHP may be more applicable in these areas by providing a rigorous framework for assessment of qualitative and quantitative factors together; and AHP offers substantial flexibility to accommodate the variety and quantity of decision criteria set forth by the firm.

As firms are more active in pursuing opportunities in global markets, identifying the right offshoring location is critical. The selection process is complex, involving a set of qualitative and quantitative factors and requiring rigorous and careful analysis. Therefore, a scientific method that not only offers flexibility and simplicity, but also simultaneously accommodates a wide variety of decision criteria is invaluable. The research demonstrates that AHP provides these benefits and is an effective technique for analyzing the where‐to‐outsource decision.

The extensive literature review suggests that the majority of the existing works focus on analyzing the go/no‐go decision using a qualitative approach. This paper applies the AHP method to the “where to outsource” question to demonstrate one quantitative approach to this complex decision. Additionally, the paper provides a detailed description of how the AHP method is implemented in analyzing the decision by using a Fortune 500 company's data and information as an example.

Property investment requires accurate market forecasts. The use of judgemental forecasting to predict property market performance is well established and widely practised. However, the need to deal with a large number of variables and to assess the impact of structural, exogenous and policy changes makes forecasting an inextricably difficult task, given the limitations of holistic forecasting. Proposes the incorporation of the analytical hierarchy process (AHP) to translate expert judgement into accurate and meaningful market forecasts. Such an approach facilitates communication of expert judgement and at the same time provides feedback for the expert. Provides a 12‐month forecast of the Singapore residential property market to illustrate the expert judgemental‐AHP approach.

The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections.

The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the weights for the criteria. The validity of the approach is confirmed by comparing the outputs of school inspection and the outputs of the model in a sample of schools.

The framework proposed enables school management to address several issues pertaining to its competitive advantage with other schools, the two most important being establishing its performance ranking in the marketplace and identifying the service elements that most require improvement. This study develops a cohesive approach to identify which quality attributes or dimensions require attention.

For school inspections, the data collection and computational problems would increase with the increase in the number of criteria and sub-criteria, as well as the number of schools considered in the selection. Although the range of reported AHP applications is extensive in many disciplines, examples in school quality and inspection remain still rare; as a result, this study could not compare its results with other AHP applications in school inspection or assessment.

The AHP method has the distinct advantage that it decomposes a decision problem into its constituent parts and builds hierarchies of criteria. AHP enables assessors to capture both subjective and objective evaluation measures of school quality. By providing a useful mechanism for assessing the consistency of the evaluation measures and alternatives, the AHP reduces bias in decision making.

The AHP model also provides a more systematic evaluation of a given school’s qualitative performance criteria. The proposed AHP model is attractive to assessors and decision makers because its pairwise comparison procedure enables them to offer a relative (rather than absolute) individual criterion assessment on those qualitative factors.

The AHP model could become a sustainable component of overall school system quality improvement by maturing over time. The AHP annual scores could be used as realistic and measureable gauges for measuring school improvement.