scholarly journals Fuzzy AHP, DEA, and Managerial Analysis for Supplier Selection and Development; From the Perspective of Open Innovation

2018 ◽  
Vol 10 (10) ◽  
pp. 3779 ◽  
Author(s):  
Maimouna Diouf ◽  
Choonjong Kwak
Keyword(s):  
Supplier Selection ◽  
Fuzzy Ahp ◽  
Supplier Management ◽  
Decision Makers ◽  
Practical Reasons ◽  
Data Envelopment ◽  
Supplier Development ◽  
Rank And Select ◽  
The Impact ◽  
Hierarchy Process

Supplier management is critical for supply chain management (SCM). The aim of supplier selection is to find an order of preference among potential suppliers. However, the ranking results for supplier selection may not be important, particularly when the performances are conflicting or have minor differences. Different criteria may have different impacts on the ranking results, and different decision makers may place different priorities on multiple criteria. Relatively worse suppliers may still have to be used for many practical reasons. One alternative is supplier development, but it has been focused on categorizing individual suppliers for possible action plans. A new framework is proposed in this research to address supplier selection and supplier development at the same time in the publishing and printing industries. First, the fuzzy analytical hierarchy process (fuzzy AHP) and data envelopment analysis (DEA) are sequentially performed to rank and select the best supplier(s) of a publishing company. In addition to ranking suppliers, a managerial analysis is proposed to assess the impact of important criteria on supplier selection in more detail. Finally, the results of the DEA are provided for direct supplier development without supplier categorization. This research shows that the proposed framework effectively addresses supplier development as well as supplier selection in the publishing and printing industries.

scholarly journals Sustainable Supplier Selection Process in Edible Oil Production by a Hybrid Fuzzy Analytical Hierarchy Process and Green Data Envelopment Analysis for the SMEs Food Processing Industry

Mathematics ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 302 ◽  
Author(s):  
Chia-Nan Wang ◽  
Van Thanh Nguyen ◽  
Hoang Tuyet Nhi Thai ◽  
Ngoc Nguyen Tran ◽  
Thi Lan Anh Tran
Keyword(s):  
Food Processing ◽  
Supplier Selection ◽  
Selection Process ◽  
Oil Production ◽  
Edible Oil ◽  
Decision Makers ◽  
Data Envelopment ◽  
Food Processing Industry ◽  
Processing Industry ◽  
Hierarchy Process

Today, business organizations are facing increasing pressure from a variety of sources to operate using sustainable processes. Thus, most companies need to focus on their supply chains to enhance sustainability to meet customer demands and comply with environmental legislation. To achieve these goals, companies must focus on criteria that include CO2 (carbon footprint) and toxic emissions, energy use and efficiency, wastage generations, and worker health and safety. As in other industries, the food processing industry requires large inputs of resources, which results in several negative environmental effects; thus, decision-makers have to evaluate qualitative and quantitative factors. This work identifies the best supplier for edible oil production in the small and medium enterprise (SME) food processing industry in Vietnam. This study also processes a hybrid multicriteria decision-making (MCDM) model using a fuzzy analytical hierarchy process (FAHP) and green data envelopment analysis (GDEA) model to identify the weight of all criteria of a supplier’s selection process based on opinions from company procurement experts. Subsequently, GDEA is applied to rank all potential supplier lists. The primary objective of this work is to present a novel approach which integrates FAHP and DEA for supplier selection and also consider the green issue in edible oil production in uncertain environments. The aim of this research is also to provide a useful guideline for supplier selection based on qualitative and quantitative factors to improve the efficiency of supplier selection in the food industry and other industries. The results reveal that Decision-Making Unit 1 (DMU 1), DMU 3, DMU 7, and DMU 9 are identified as extremely efficient for five DEA models, which are the optimal suppliers for edible oil production. The contributions of this research include a proposed MCDM model using a hybrid FAHP and GDEA model for supplier selection in the SME food processing industry under a fuzzy environment conditions in Vietnam. This research also is part of an evolution of a new hybrid model that is flexible and practical for decision-makers. In addition, the research also provides a useful guideline in supplier selection in the food processing industry and a guideline for supplier selection in other industries.

scholarly journals AN INTEGRATED FUZZY AHP/DEA APPROACH FOR PERFORMANCE EVALUATION OF TERRITORIAL UNITS IN TURKEY

2018 ◽  
Vol 24 (4) ◽  
pp. 1280-1302 ◽  
Author(s):  
Ahmet Çalik ◽  
Nimet Yapici Pehlivan ◽  
Cengiz Kahraman
Keyword(s):  
Social Life ◽  
Fuzzy Ahp ◽  
Decision Makers ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Second Stage ◽  
Dea Method ◽  
Two Stages ◽  
Hierarchy Process

Due to the differences between regions and sub-regions in the countries, some problems come out especially in economic and social life. The issue of differences of regions has been widely implemented to evaluate the economic performance of Turkey in many disciplines. The objective of this paper is to evaluate the efficiency of 26 sub-regions of NUTS-2 classification using integration Fuzzy Analytic Hierarchy Process (FAHP) with Data Envelopment Analysis (DEA). The integrated FAHP/DEA method comprises two stages. In the first stage, linguistic terms are used to determine the decision makers’ opinion and are converted to quantitative forms by using FAHP methods. Subsequently, in the second stage, DEA method is applied to obtain relative efficiency of sub-regions in Turkey. The integrated FAHP/DEA method is illustrated with a real case study.

scholarly journals Selection of In-Flight Duty-Free Product Suppliers Using a Combination Fuzzy AHP, Fuzzy ARAS, and MSGP Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yan-Kai Fu ◽  
Chung-Jen Wu ◽  
Chin-Nung Liao
Keyword(s):  
Free Product ◽  
Airline Industry ◽  
Supplier Selection ◽  
Fuzzy Ahp ◽  
Decision Makers ◽  
Fuzzy Analytical Hierarchy Process ◽  
Qualitative And Quantitative ◽  
Hierarchy Process ◽  
Selection Of ◽  
Airline Company

Over a billion people travel by air all over the world every year, and there are many in-flight retailing opportunities for the airline industry. This paper proposes a novel integration fuzzy analytical hierarchy process (FAHP), fuzzy additive ratio assessment (FARAS), and multisegment goal programming (MSGP) methods to select the best supplier for in-flight duty-free product in airline industry. The advantage of this proposed method is that it allows decision makers (DMs) to set multisegment aspiration vague levels considering both the qualitative and quantitative criteria for supplier selection simultaneously. To the best of our knowledge, a simultaneous consideration of qualitative and quantitative criteria for supplier selection of in-flight duty-free product has never been applied under the airline retail industry context. This research will fill into the gaps of supplier selection in in-fight duty-free product for airline industry. The integrated model is illustrated by an example in an airline company in Taiwan.

scholarly journals Facility location selection for the furniture industry of Bangladesh: Comparative AHP and FAHP analysis

2021 ◽  
Vol 13 ◽  
pp. 184797902110308
Author(s):  
Md Nazmul Hasan Suman ◽  
Nagib MD Sarfaraj ◽  
Fuad Ahmed Chyon ◽  
Md Rafiul Islsm Fahim
Keyword(s):  
Facility Location ◽  
Raw Materials ◽  
Fuzzy Ahp ◽  
Facility Location Problem ◽  
Decision Makers ◽  
Energy Availability ◽  
Furniture Industry ◽  
Data Set ◽  
Location Selection ◽  
Hierarchy Process

The furniture industry is growing to a great extent in Bangladesh. Many market researchers believe that the industry has enormous potentiality. However, the expansion of this industry may face complexities within a few years. Due to the wrong selection of facilities, many organizations failed to earn profit as expected. It also needs a large investment. Selecting a suitable place for a new facility is going to be the biggest question of upcoming years. This study aimed to analyze Bangladesh’s furniture industry, address the facility location problem, and provide a constructive solution to the decision-makers. In this study, seven criteria were considered: availability of raw materials, transportations, skilled labor, proximity to customers, energy availability, economic zone facility, and environmental impact, and five ideal locations or alternatives: Khulna, Chattogram, Bogura, Gazipur, and Manikganj. Thirty-four experts took part in the survey to analyze the significant criteria for selecting a furniture industry’s facility location and alternatives or potential locations for the facility. The Analytical Hierarchy Process (AHP) and Fuzzy AHP methods (FAHP), two MCDM techniques, were used to analyze the data set. A sensitivity analysis was done to determine the model’s robustness for any critical changes in the real world. The result showed that ‘energy availability is the most significant criterion to select a facility location for the furniture industry, where it got 35.1% criteria weight in AHP and 33.9% in FAHP. ‘Chattogram’ was selected as the most suitable place containing 33.74% normalized weight in AHP and 33.81% normalized weight in FAHP.

Evaluating Supplier Involvement Using DEA and Piecewise Triangular Fuzzy AHP

2007 ◽  
Author(s):  
Shouhua Yuan ◽  
Yiliu Tu ◽  
Deyi Xue
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Comparison Method ◽  
Data Envelopment ◽  
Novel Method ◽  
Overall Performance ◽  
Dea Method ◽  
The Individual ◽  
Hierarchy Process

Data Envelopment Analysis (DEA) has been widely applied in evaluating multi-criteria decision making problems which have multi-inputs and multi-outputs. However, the traditional DEA method does neither take the decision maker’s subjective preferences to the individual criteria into consideration, nor rank the selected options or decision making units (DMUs). On the other hand, Satty’s Analytical Hierarchy Process (AHP) was established to rank options or DMUs under multi-inputs and multi-outputs through pairwise comparisons. But in most cases, the AHP pairwise comparison method is not perfectly consistent, which may give rise to confusions in determining the appropriate priorities of each criterion to be considered. The inconsistency implicates the fuzziness in generating the relative important weight for each criterion. In this paper, a novel method which employs both DEA and AHP methods is proposed to evaluate the overall performance of suppliers’ involvement in the production of a manufacturing company. This method has been developed through modifying the DEA method into a weighting constrained DEA method by using a piecewise triangular weighting fuzzy set which is generated from the inconsistent AHP comparisons. A bias tolerance ratio (BTR) is introduced to represent the varying but restrained weighting values of each criterion. Accordingly, the BTR provides the decision maker a controllable parameter by tightening or loosening the range of the weighting values in evaluating the overall performance of available suppliers, which in hence, overcomes the two weaknesses of the traditional DEA method.

scholarly journals A NOVEL HESITANT INTUITIONISTIC FUZZY LINGUISTIC AHP METHOD AND ITS APPLICATION TO PRIORITIZATION OF INVESTMENT ALTERNATIVES

2019 ◽  
Vol 11 (1) ◽  
pp. 127-142 ◽  
Author(s):  
Ali Karasan
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Ahp ◽  
Decision Makers ◽  
Membership Degree ◽  
Intuitionistic Fuzzy Number ◽  
Ahp Method ◽  
Intuitionistic Fuzzy ◽  
The Stability ◽  
Fuzzy Linguistic ◽  
Hierarchy Process

Intuitionistic fuzzy extensions are the most used type of fuzzy extensions in the literature since they better represent decision makers strength of commitment on the considered subject in an effective way including membership and non-membership functions. On the other hand, decision makers may assign more than one intuitionistic fuzzy number in order to capture their hesitancies when they are hesitant in assigning a membership degree and a non-membership degree. Hesitant fuzzy sets, another extension of ordinary fuzzy sets, help decision makers to assign different values on the same element aiming at reflexing decision makers’ hesitation. Utilizing these two types of fuzzy sets capture both uncertainty and ambiguity of the considered problem and helps to eliminate the weaknesses of each fuzzy extension. In this study,hesitant intuitionistic fuzzy linguistic sets (HIFLSs) are used to extend the Analytical Hierarchy Process (AHP). The developed method is applied to investment prioritization problem, based on relevant risk factors. Comparative analyses with intuitionistic fuzzy AHP and hesitant fuzzy AHP methods are realized in order to validate the proposed method. A sensitivity analysis is also conducted for the stability of the results of the hesitant intuitionistic fuzzy linguistic AHP method.

scholarly journals Resource depletion: where is an intervention most effective?

2019 ◽  
Vol 8 (4) ◽  
pp. 307-321 ◽  
Author(s):  
Patrick de Laat
Keyword(s):  
Resource Depletion ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Content Type ◽  
New Ways Of Working ◽  
Rules Of Thumb ◽  
Structured Analysis ◽  
Operation Phase ◽  
The Impact ◽  
Hierarchy Process

Purpose Where does one need to intervene in to be most effective? The purpose of this study is to rank areas of the resource system, according to how much of a change can be expected from interventions in an area, in relation to the problem of depleting resources. Design/methodology/approach Principles of structured analysis are used to model how society uses resources. From this model, nine intervention areas are defined. These intervention areas are ranked in terms of effectiveness, through the use of the analytic hierarchy process. Findings To be most effective, one must prioritize intervention areas as follows: material inputs to the operation phase; process inputs to the operation phase; products’ longevity; process inputs to the manufacturing phase; and material inputs to the manufacturing phase. Practical implications Most decisions are not made on the basis of rigorous analysis but by using heuristics (rules of thumb). The results of this study are expressed as rules of thumb. They can help decision makers prioritize what is most important, but without imposing new ways of working. Originality/value In the construction domain, heuristics that generalize the impact of actions (content), instead of intervention areas (context), currently seem to prevail. The heuristics of this study generalize the impact of intervention areas. Therefore, they provide an extra perspective for many decision makers. This extra perspective can help reduce mistakes that are typically made by oversimplifying matters.

Using Data Envelopment Analysis for Green Supplier Selection in Manufacturing under Vague Environment

2012 ◽  
Vol 622-623 ◽  
pp. 1682-1685 ◽  
Author(s):  
Atefeh Amindoust ◽  
Ahmed Shamsuddin ◽  
Ali Saghafinia
Keyword(s):  
Data Envelopment Analysis ◽  
Supplier Selection ◽  
Decision Makers ◽  
Central Component ◽  
Data Envelopment ◽  
Linguistic Terms ◽  
Green Supplier Selection ◽  
Growth Of Knowledge ◽  
Using Data

In these days, considering the growth of knowledge about environmental protection and green issues in manufacturing, green supplier selection would be the central component in the management of supply chain. This paper intends to apply data envelopment analysis for supplier selection considering environmental merits. The suppliers’ performances with respect to criteria are not pure numbers and considered in linguistic terms according to decision makers’ opinion. To handle the subjectivity of decision makers’ assessments, fuzzy logic has been applied. A case study is done to present the application of the method.

scholarly journals Analysing Stakeholder Consensus for a Sustainable Transport Development Decision by the Fuzzy AHP and Interval AHP

2019 ◽  
Vol 11 (12) ◽  
pp. 3271 ◽  
Author(s):  
Sarbast Moslem ◽  
Omid Ghorbanzadeh ◽  
Thomas Blaschke ◽  
Szabolcs Duleba
Keyword(s):  
Fuzzy Ahp ◽  
Urban Transport ◽  
Decision Makers ◽  
Service Development ◽  
Environmental Damage ◽  
Combined Application ◽  
Computation Process ◽  
Stakeholder Consensus ◽  
The Impact

In any public service development decision, it is essential to reach the stakeholders’ agreement to gain a sustainable result, which is accepted by all involved groups. In case this criterion is violated, the impact of the development will be less than expected due to the resistance of one group or another. Concerning public urban transport decisions, the lack of consensus might cause lower utilisation of public vehicles, thus more severe environmental damage, traffic problems and negative economic impacts. This paper aims to introduce a decision support procedure (applying the current MCDM techniques; Fuzzy and Interval AHP) which is capable of analysing and creating consensus among different stakeholder participants in a transport development problem. The combined application of FAHP and IAHP ensures that the consensus creation is not only based on an automated computation process (just as in IAHP) but also on the consideration of specific group interests. Thus, the decision makers have the liberty to express their preferences in urban planning, along with the consideration of numerical results. The procedure has been tested in a real public transport improvement decision as a follow-up project, in an emerging city, Mersin, Turkey. Results show that by the application of the proposed techniques, decision-makers can be more aware of the conflicts of interests among the involved groups, and they can pay more attention to possible violations.

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