The vital-immaterial-mediocre multi-criteria decision-making method

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shervin Zakeri ◽  
Fatih Ecer ◽  
Dimitri Konstantas ◽  
Naoufel Cheikhrouhou
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Validity And Reliability ◽  
Managerial Decision ◽  
Analytic Hierarchy ◽  
Weighting Method ◽  
Content Type ◽  
Complex Process ◽  
Sustainable Supplier Selection ◽  
Managerial Implications

PurposeThis paper proposes a new multi-criteria decision-making method, called the vital-immaterial-mediocre method (VIMM), to determine the weight of multiple conflicting and subjective criteria in a decision-making problem.Design/methodology/approachThe novel method utilizes pairwise comparisons, vector-based procedures and a scoring approach to determine weights of criteria. The VIMM compares alternatives by the three crucial components, namely the vital, immaterial and mediocre criteria. The vital criterion has the largest effect on the final results, followed by the mediocre criterion and then the immaterial criterion, which is the least impactful on the prioritization of alternatives. VIMM is developed in two forms where the first scenario is designed to solve one-goal decision-making problems, while the second scenario embraces multiple goals.FindingsTo validate the method’s performance and applicability, VIMM is applied to a problem of sustainable supplier selection. Comparisons between VIMM, analytic hierarchy process (AHP) and best-worst method (BWM) reveal that VIMM significantly requires fewer comparisons. Moreover, VIMM works well with both fractional and integer numbers in its comparison procedures.Research limitations/implicationsAs an implication for research, we have added the development of the VIMM under fuzzy and grey environments as the direction for optimization of the method.Practical implicationsAs managerial implications, VIMM not only provides less complex process for the evaluation of the criteria in the managerial decision-making process, but it also generates consistent results, which make VIMM a reliable tool to apply to a large number of potential decision-making problems.Originality/valueAs a novel subjective weighting method, there exist five major values that VIMM brings over AHP and BWM methods: VIMM requires fewer comparisons compared with AHP and BWM; it is not sensitive to the number of criteria; as a goal-oriented method, it exclusively takes the decision-making goals into account; it keeps the validity and reliability of the Decision-Makers’ (DMs’) opinions and works well with integer and fractional numbers.

Multi-criteria decision-making toward supplier selection: exploration of PROMETHEE II method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishant Agrawal
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Supply Chain ◽  
Case Studies ◽  
Supplier Selection ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Promethee Ii ◽  
Wide Range ◽  
Managerial Implications

PurposeSupplier Selection (SS) is one of the vital decisions frequently executed by numerous industries. In recent times, the number of suppliers has increased enormously depending on a wide range of criteria. A selection of suppliers is a sensitive process that may impact various supply chain activities. The purpose of this research is to explore an underutilized technique called PROMETHEE II method for SS.Design/methodology/approachVarious tools and techniques are available under multi-criteria decision-making tools, which sometimes creates confusion in researchers' minds regarding reliability. PROMETHEE II was the most prominent method for ranking all available alternatives that ultimately avoid decision-making errors. To execute this equal and unequal weights approach has been used with three case studies.FindingsIn this research, three case studies have been used and soved with the help of the PROMETHEE II approach. The study also provides fundamental insights into the supplier's ranking on different criteria using sensitivity analysis. Further, criteria were divided as per benefits and non-beneficial to get a robust result. The pros and cons of PROMETHEE II approaches are also highlighted compared to other MCDM tools in this study.Originality/valueMost of the SS research uses either AHP or TOPSIS as per existing literature. There are very few attempts highlighted in the literature that use PROMETHEE II for the SS problem with sensitivity analysis. The proposed method is probable to motivate decision-makers to consider using a more sophisticated method like PROMETHEE II in supplier evaluation processes. This study opens a new direction for the ranking of suppliers in the field of the supply chain. The study also bears significant practical as well as managerial implications.

Multi-criteria decision making for supplier selection using fuzzy AHP approach

2015 ◽  
Vol 22 (6) ◽  
pp. 1158-1174 ◽  
Author(s):  
Vinod Yadav ◽  
Milind Kumar Sharma
Keyword(s):  
Decision Making ◽  
Automobile Industry ◽  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Ahp ◽  
Selection Model ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Hierarchy Process

Purpose – 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. Design/methodology/approach – FAHP approach followed by a sensitivity analysis has been used. Findings – 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. Practical implications – 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. Originality/value – 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.

Measuring the supply chain competitiveness of e-commerce industry in Indonesia

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ade Febransyah ◽  
Joklan Imelda Camelia Goni
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Future Research ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Content Type ◽  
The Future ◽  
Business To Consumer ◽  
Software And Hardware ◽  
Decision Making Model

Purpose The purpose of this study is to measure the supply chain competitiveness of the e-commerce industry in Indonesia. Design/methodology/approach The study used a multi-criteria decision-making model based on the analytic hierarchy process. Four main criteria are used to measure the supply chain competitiveness, i.e. cost, differentiation, sustainability and infrastructure. Findings The findings of this study show that cost is the most important criterion with a degree of importance of 33.19%, followed by infrastructure of 29.40%, differentiation of 27.96% and sustainability of 9.45%. It shows that the internally controlled strategy contributes about 70% of supply chain competitiveness. The internal infrastructure criterion that consists of software and hardware contributes 65.92% to the whole infrastructure criterion. The internal infrastructure then contributes 19.38% to supply chain competitiveness. Therefore, the internally controlled strategies and internal infrastructure contribute up to 90.08% to the supply chain competitiveness of e-commerce in Indonesia. This result implies that to attain the supply chain competitiveness, the company must carry out strategies focusing on the performance such as cost, differentiation, sustainability as well as on the internal infrastructure such as software and hardware. Research limitations/implications In this paper, the authors limited their study to the business to business (B2B) and business to consumer (B2C) players because these two platforms have been experiencing a very rapid growth. While e-commerce business can take many platforms besides B2B and B2C, the future research should include other platform such as consumer to consumer as well. Because the focus in this study is more the information and material flows, it will be of great interest if the future research covers the platform of mobile payment as well that guarantee the ease of cashflows within supply chains. Also, with the occurrence of the Covid-19 pandemic when this paper was written, in the near future, it is then of great interest to incorporate the pandemic context into the proposed model used in this study. The further study should analyze long-term changes happened as the result of pandemic such as behavioral changes of online shopping from customer side or shift in e-commerce supply chain infrastructure and inventory practice. Practical implications With this study, it is expected that it can be determined which criteria contribute the most to the supply chain competitiveness of the e-commerce industry in Indonesia that will be useful for industry player. Originality/value E-commerce development in Indonesia is still facing serious challenges. The multi-criteria decision making approach used in this research lays a foundation of how supply chain competitiveness is determined based on the judgment of experts coming from major companies within the supply chain.

scholarly journals A Novel Multi-Criteria Decision-Making Model: Interval Rough SAW Method for Sustainable Supplier Selection

Information ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 292 ◽  
Author(s):  
Željko Stević ◽  
Elmina Durmić ◽  
Mladen Gajić ◽  
Dragan Pamučar ◽  
Adis Puška
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Rank Correlation ◽  
Multi Criteria Decision Making ◽  
Weighting Method ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient ◽  
Sustainable Supplier Selection ◽  
Simple Additive Weighting ◽  
The Stability

Sustainability in a supply chain is a demand on the one hand and a challenge on the other. It is necessary to balance between these dimensions in order to fulfill the purpose of the supply chain. Therefore, in the first phase—i.e., in procurement—it is necessary to take into account its sustainability. In this paper, a sustainable supplier was selected respecting all three aspects of sustainability. The evaluation was carried out on the basis of a total of 21 criteria arranged into two levels and three groups. A new Interval Rough SAW (simple additive weighting) method, which represents a contribution to the treatment of problems belonging to the multi-criteria decision-making (MCDM), was developed. The integration of interval rough numbers with the SAW method was completed. In addition, the full consistency method (FUCOM) was applied to determine the weights of the criteria. The integrated FUCOM-Interval Rough SAW model enables treatment of multi-criteria problems while reducing subjectivity to the lowest possible level and eliminating uncertainties and ambiguities. The results obtained were determined throughout a sensitivity analysis consisting of a change in the weight of the criteria and the influence of dynamic matrices on the change in ranks. In addition, Spearman’s rank correlation coefficient (SCC) was calculated to confirm the stability of the previously obtained results.

Selection of Khadi fabrics for optimal comfort properties using multi-criteria decision-making technique

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ashis Mitra
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Sensitivity Analyses ◽  
Multi Criteria Decision Making ◽  
Phase Sensitivity ◽  
Two Phase ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Hierarchy Process ◽  
Selection Of

Purpose Khadi fabrics are known for their unique comfort properties which are attributed to their unique structural and functional properties. For getting optimal comfort from a collection of available Khadi fabrics, further exploration is needed. Ranking the Khadi fabrics from a competitive lot for optimal comfort is a challenging job, which has not been addressed so far by any researcher. The purpose of this study is to present one such selection problem using the multi-criteria decision-making (MCDM) technique, a popular branch of operations research, which can handle almost any decision problem involving a finite number of alternatives and multiple decision criteria. Design/methodology/approach Two widely popular methods/exponents of MCDM, namely, analytic hierarchy process (AHP) and multiplicative analytic hierarchy process (MAHP) have been deployed in this study for ranking a competitive lot of 15 Khadi fabrics and selecting the best alternative for optimal summer comfort based on three comfort attributes, namely, drape coefficient, thermal insulation value and air permeability. Findings Both the approaches yield a similar ranking pattern with Spearman’s rank correlation coefficient of 0.9857, Khadi fabric K1 achieving Rank 1 (best in terms of optimal comfort) and sample K6 acquiring Rank 15 (worst choice). Two-phase sensitivity analyses were performed subsequently to demonstrate the stability of the two approaches: sensitivity analysis by changing weightage levels of the criteria and sensitivity analysis in dynamic decision conditions by changing the elements of the initial decision matrix. During sensitivity analyses, no occurrence of rank reversal is observed for the best and worst alternatives in either of the two approaches. This corroborates the robustness of the two models. Practical implications Khadi fabrics are widely acclaimed for their intrinsic comfort properties for both summer and winter. Although the popularity of Khadi fabrics is increasing day by day, this domain is under-researched, and hence, needs to be explored further. The present approach demonstrates how the MCDM technique can serve as a useful tool for ranking the available Khadi fabrics in terms of optimal comfort in summer. The same approach can be extended to other domains of the textile industry, in general, as well. Originality/value This study is the first-ever theoretical approach/research on the selection of Khadi fabrics for optimal summer comfort using the MCDM tool. Another novelty of the present study is that the efficacy of AHP and MAHP approaches, in this study, has been validated through a two-phase sensitivity analysis. This validation part has been ignored in most of the hitherto published applications of AHP and MAHP in other domains.

scholarly journals Multi-criteria decision-making model for supporting manufacturing settlements location in Africa after COVID-19

2021 ◽  
Vol 13 ◽  
pp. 184797902110233
Author(s):  
Stefania Bait ◽  
Serena Marino Lauria ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Decision Making ◽  
Value Chain ◽  
Multinational Enterprises ◽  
Value Added ◽  
Plant Performance ◽  
Multi Criteria Decision Making ◽  
African Countries ◽  
Analytic Hierarchy ◽  
Location Selection ◽  
Decision Making Model

The COVID-19 emergency is affecting manufacturing industries all over the world. Notably, it has generated several issues in the products’ supply and the global value chain in African countries. Besides this, Africa’s manufacturing value-added rate grew only 1.5 since 2018, and the foreign direct investment (FDI) from multinational enterprises (MNEs) remains very low due to high-risk factors. Most of these factors are linked to a non-optimized location selection that can adversely affect plant performance. For these reasons, supporting decision-makers in selecting the suitable country location in Africa is crucial, both for contributing to countries’ growth and companies’ performance. This research aims at presenting a comprehensive multi-criteria decision-making model (MCDM) to be used by MNEs to evaluate the best countries to develop new manufacturing settlements, highlighting the criteria that COVID-19 has impacted. Thus, it has affected countries’ performance, impacting the plant location selection choices. A combination of the Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods have also been used for comparative analysis. The criteria used in the proposed approach have been validated with a panel of MNEs experts.

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

Jumping to conclusions – an analysis of the NBA Draft Combine athleticism data and its influence on managerial decision-making

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tobias Berger ◽  
Frank Daumann
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Predictive Power ◽  
Principal Component ◽  
Decision Makers ◽  
Decision Quality ◽  
Managerial Behavior ◽  
Managerial Decision ◽  
Content Type ◽  
Selection Behavior

PurposeThe NBA Draft policy pursues the goal to provide the weakest teams with the most talented young players to close the gap to the superior competition. But it hinges on appropriate talent evaluation skills of the respective organizations. Research suggests the policy might be valid but to date unable to produce its intended results due to the “human judgement-factor”. This paper investigates specific managerial selection-behavior-influencing information to examine why decision-makers seem to fail to constantly seize the opportunities the draft presents them with.Design/methodology/approachAthleticism data produced within the NBA Draft Combine setting is strongly considered in the player evaluations and consequently informs the draft decisions of NBA managers. Curiously, research has failed to find much predictive power within the players pre-draft combine results for their post-draft performance. This paper investigates this clear disconnect, by examining the pre- and post-draft data from 2000 to 2019 using principal component and regression analysis.FindingsEvidence for an athletic-induced decision-quality-lowering bias within the NBA Draft process was found. The analysis proves that players with better NBA Draft Combine results tend to get drafted earlier. Controlling for position, age and pre-draft performance there seems to be no proper justification based on post-draft performance for this managerial behavior. This produces systematic errors within the structure of the NBA Draft process and leads to problematic outcomes for the entire league-policy.Originality/valueThe paper delivers first evidence for an athleticism-induced decision-making bias regarding the NBA Draft process. Informing future selection-behavior of managers this research could improve NBA Draft decision-making quality.

Sustainable circular supplier selection and evaluation in the manufacturing sector using Pythagorean fuzzy EDAS approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chang Liu ◽  
Pratibha Rani ◽  
Khushboo Pachori
Keyword(s):  
Decision Making ◽  
Human Behavior ◽  
Circular Economy ◽  
Supplier Selection ◽  
Manufacturing Sector ◽  
Uncertain Information ◽  
Manufacturing Companies ◽  
Content Type ◽  
Sustainable Supplier Selection ◽  
Selection Of

PurposeDue to stern management policies and increased community attentiveness, sustainable supply chain management (SSCM) performs a vast component in endeavor operation and production management. Sustainable circular supplier selection (SCSS) and evaluation presented the environmental and social concerns in the fields of circular economy and sustainable supplier selection. Choosing the optimal SCSS is vital for organizations to persuade SSCM, as specified in various researches. Based on the subjectivity of human behavior, the selection of ideal SCSS often involves uncertain information, and the Pythagorean fuzzy sets (PFSs) have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the multi-criteria decision-making (MCDM) procedure. Here, a framework is developed to assess and establish suitable suppliers in the SSCM and the circular economy.Design/methodology/approachThis paper introduced an extended framework using the evaluation based on distance from average solution (EDAS) with PFSs and implemented it to solve the SCSS in the manufacturing sector. Firstly, the PFSs to handle the uncertain information of decision experts (DEs) is employed. Secondly, a novel divergence measure and parametric score function for calculating the criteria weights are proposed. Thirdly, an extended decision-making approach, known as PF-EDAS, is introduced.FindingsThe outcomes and comparative discussion show that the developed method is efficient and capable of facilitating the DEs to choose desirable SCSS. Therefore, the proposed framework can be used by organizations to assess and establish suitable suppliers in the SCSS process in the circular economy.Originality/valueSelecting the optimal sustainable circular supplier (SCS) in the manufacturing sector is important for organizations to persuade SSCM, as specified in various research. However, corresponding to the subjectivity of human behavior, the selection of the best SCS often involves uncertain information, and the PFSs have a huge capability to tackle strong vagueness, uncertainty and inaccuracy in the MCDM procedure. Hence, manufacturing companies' administrators can implement the developed method to assess and establish suitable suppliers in the SCSS process in the circular economy.

The effects of brand equity and failure severity on remedy choice after a product recall

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sascha Raithel ◽  
Alexander Mafael ◽  
Stefan J. Hock
Keyword(s):  
Decision Making ◽  
Brand Equity ◽  
Probit Model ◽  
Future Research ◽  
Product Recalls ◽  
Product Recall ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Failure Severity

Purpose There is limited insight concerning a firm’s remedy choice after a product recall. This study aims to propose that failure severity and brand equity are key antecedents of remedy choice and provides empirical evidence for a non-linear relationship between pre-recall brand equity and the firm’s remedy offer that is moderated by severity. Design/methodology/approach This study uses field data for 159 product recalls from 60 brands between January 2008 to February 2020 to estimate a probit model of the effects of failure severity, pre-recall brand equity and remedy choice. Findings Firms with higher and lower pre-recall brand equity are less likely to offer full (vs partial) remedy compared to medium level pre-recall brand equity firms. Failure severity moderates this relationship positively, i.e. firms with low and high brand equity are more sensitive to failure severity and then select full instead of partial remedy. Research limitations/implications This research reconciles contradictory arguments and research results about failure severity as an antecedent of remedy choice by introducing brand equity as another key variable. Future research could examine the psychological process of managerial decision-making through experiments. Practical implications This study increases the awareness of the importance of remedy choice during product-harm crises and can help firms and regulators to better understand managerial decision-making mechanisms (and fallacies) during a product-harm crisis. Originality/value This study theoretically and empirically advances the limited literature on managerial decision-making in response to product recalls.

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