Selecting Six Sigma projects: MCDM or DEA?

2016 ◽  
Vol 11 (1) ◽  
pp. 309-325 ◽  
Author(s):  
Ali Yousefi ◽  
Abdollah Hadi-Vencheh
Keyword(s):  
Decision Making ◽  
Six Sigma ◽  
Point Of View ◽  
Decision Quality ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Risk Of Failure ◽  
Order Preference ◽  
Hierarchy Process

Purpose – Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks. Design/methodology/approach – In this paper, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, the analytic hierarchy process (AHP) is used to rank the results. Then, a real example is resolved by two important techniques in decision-making process, that is the AHP and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), as well as data envelopment analysis (DEA). The results from the above three methods are compared. Findings – The results of this paper show that by using fewer criteria, the results from AHP and TOPSIS are very similar. Also, the results from these techniques vary from DEA’s ones in many aspects. So regarding the different results and the importance of criteria in selecting the Six Sigma projects, multi-criteria decision-making (MCDM) techniques are more reliable in comparison with DEA, because decision-maker’s point of view is more effective in MCDM techniques. Originality/value – The paper, using a real case study, provides important new tools to enhance decision quality in Six Sigma project selection.

Selecting Six Sigma project: a comparative study of DEA and LDA techniques

2018 ◽  
Vol 9 (4) ◽  
pp. 506-522 ◽  
Author(s):  
A. Hadi-Vencheh ◽  
A. Yousefi
Keyword(s):  
Six Sigma ◽  
Selection Process ◽  
Project Selection ◽  
Decision Quality ◽  
Data Envelopment ◽  
Content Type ◽  
Dea Model ◽  
Risk Of Failure ◽  
Proposed Model

Purpose Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks. Design/methodology/approach First, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model. Findings The results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA. Originality/value The paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.

Evaluation of behavioral biases affecting investment decision making of individual equity investors by fuzzy analytic hierarchy process

2019 ◽  
Vol 12 (3) ◽  
pp. 297-314 ◽  
Author(s):  
Jinesh Jain ◽  
Nidhi Walia ◽  
Sanjay Gupta
Keyword(s):  
Decision Making ◽  
Behavioral Finance ◽  
Investment Decision ◽  
Investment Decisions ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Behavioral Biases ◽  
Investment Decision Making ◽  
Overconfidence Bias ◽  
Hierarchy Process

Purpose Research in the area of behavioral finance has demonstrated that investors exhibit irrational behavior while making investment decisions. Investor behavior usually deviates from logic and reason, and consequently, investors exhibit various behavioral biases which impact their investment decisions. The purpose of this paper is to rank the behavioral biases influencing the investment decision making of individual equity investors from the state of Punjab, India. This research would provide valuable insight into the different behavioral biases to investors and other participants of the capital market and help them in improving investment decisions. Design/methodology/approach The research is conducted on the individual equity investors of Punjab, India. Fuzzy analytic hierarchy process was applied to rank the factors influencing the decision making of individual equity investors of Punjab. The primary factors considered for the study are overconfidence bias, representative bias, anchoring bias, availability bias, regret aversion bias, loss aversion bias, mental accounting bias and herding bias. Findings The three most influential criteria were herding bias, loss aversion bias and overconfidence bias. The five most influential sub-criteria were “I readily sell shares that have increased in value (C61),” “News about the company (Newspapers, TV and magazines) affects my investment decision (C84),” “I invest each element of my investment portfolio separately (C71)” and “I usually hold loosing stock for long time, expecting trend reversal (C52).” Research limitations/implications Although sample survey conducted in the present study was based on a limited sample selected from a particular area that truly represented the total population, it is considered as the limitation of this study. Practical implications The outcome of this research provides investors with a better understanding of behavioral biases that influence their decision making. This study provides them a guideline on different behavioral biases that they should consider while making investment decisions. Originality/value The research model is based on the available literature on behavioral finance and the research results and findings would add value to the existing knowledge base.

Fuzzy multi-criteria decision-making: An entropy-based approach to assess tourism sustainability

2019 ◽  
pp. 135481661988520
Author(s):  
Joseph Andria ◽  
Giacomo di Tollo ◽  
Raffaele Pesenti
Keyword(s):  
Decision Making ◽  
Evaluation Criteria ◽  
Multiple Criteria Decision Making ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Entropy Maximization ◽  
Tourist Destinations ◽  
Hierarchy Process ◽  
Direct Applicability

In this article, we propose a method for ranking tourist destinations and evaluating their performances under a sustainability perspective: a fuzzy multiple criteria decision-making method is applied for determining sustainability performance values and ranking destinations accordingly. We select a set of sustainability evaluation criteria and use a fuzzy analytic hierarchy process to weight the selected criteria. We also optimize each evaluator’s membership function support by means of a fuzzy entropy maximization criteria. A case study is illustrated and results are compared with two data envelopment analysis–based models. The simplicity of the proposed approach along with the easy readability of the results allow its direct applicability for all involved stakeholders.

scholarly journals A decision-making methodology integrated in product design for additive manufacturing process selection

2020 ◽  
Vol 26 (5) ◽  
pp. 895-909
Author(s):  
Wei Liu ◽  
Zicheng Zhu ◽  
Songhe Ye
Keyword(s):  
Decision Making ◽  
Additive Manufacturing ◽  
Product Design ◽  
Production Costs ◽  
Process Selection ◽  
Analytic Hierarchy ◽  
Content Type ◽  
The Given ◽  
Hierarchy Process ◽  
Am Processes

Purpose The decision-making for additive manufacturing (AM) process selection is typically applied in the end of the product design stages based upon an already finished design. However, due to unique characteristics of AM processes, the part needs to be designed for the specific AM process. This requires potentially feasible AM techniques to be identified in early design stages. This paper aims to develop such a decision-making methodology that can seamlessly be integrated in the product design stages to facilitate AM process selection and assist product/part design. Design/methodology/approach The decision-making methodology consists of four elements, namely, initial screening, technical evaluation and selection of feasible AM processes, re-evaluation of the feasible process and production machine selection. Prior to the design phase, the methodology determines whether AM production is suitable based on the given design requirements. As the design progresses, a more accurate process selection in terms of technical and economic viability is performed using the analytic hierarchy process technique. Features that would cause potential manufacturability issues and increased production costs will be identified and modified. Finally, a production machine that is best suited for the finished product design is identified. Findings The methodology was found to be able to facilitate the design process by enabling designers to identify appropriate AM technique and production machine, which was demonstrated in the case study. Originality/value This study addresses the gap between the isolated product design and process selection stages by developing the decision-making methodology that can be integrated in product design stages.

Improving risk evaluation in FMEA with a hybrid multiple criteria decision making method

2015 ◽  
Vol 32 (7) ◽  
pp. 763-782 ◽  
Author(s):  
Hu-Chen Liu ◽  
Jian-Xin You ◽  
Xue-Feng Ding ◽  
Qiang Su
Keyword(s):  
Decision Making ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Multiple Criteria ◽  
Analytic Hierarchy ◽  
Effect Analysis ◽  
Maintenance Strategies ◽  
Content Type ◽  
Safety And Reliability ◽  
Hierarchy Process

Purpose – The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes. Design/methodology/approach – A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes. Findings – A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies. Practical implications – The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method. Originality/value – This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

scholarly journals Evaluación comparativa multifuncional de sistemas agrarios mediante AHP: Aplicación al olivar ecológico, integrado y convencional de Andalucía

2011 ◽  
Vol 5 (9) ◽  
pp. 27 ◽  
Author(s):  
Carlos Parra López ◽  
Javier Calatrava Requena ◽  
Tomás De Haro Giménez
Keyword(s):  
Decision Making ◽  
Farming Systems ◽  
Point Of View ◽  
Decision Makers ◽  
Analytic Hierarchy ◽  
Complex Decision Making ◽  
Olive Groves ◽  
Complex Decision ◽  
Hierarchy Process

Even though multifunctionality concept is reflected, implicit or explicitly, in the design of actual agrarian policies, its consideration when analysing and assessing farming systems is relatively limited in the scientific literature. Analytic Hierarchy Process (AHP) is proposed with this aim. AHP is a multicriteria discrete decision support technique that is used in complex decision making. This methodology is stated jointly with a proposed procedure to measure relative agreement among decision makers and uniformity of alternatives’ performances in group decision making. Finally AHP is implemented in the assessment of organic, integrated and conventional olive groves in Andalusia considering criteria of a different nature – economic, technical, sociocultural and environmental –. The final purpose is determining the more interesting growing techniques from a holistic point of view for all the society in the medium/long-term on the basis of knowledge of experts on olive.

Fuzzy analytic hierarchy process model for multi-criteria analysis of internet of things

Kybernetes ◽  
2019 ◽  
Vol 49 (10) ◽  
pp. 2509-2520
Author(s):  
Ibrahim Mashal ◽  
Osama Alsaryrah
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Process Model ◽  
Fuzzy Model ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Iot Applications ◽  
Effective Decision Making ◽  
Application Developers ◽  
Hierarchy Process

Purpose Nowadays, there are various internet of things (IoT) applications covering many aspects of daily life. Many people own numerous smart objects that use these IoT applications. The purpose of this study is determining suitable IoT applications for each user which is a relevant challenge because it is amulti-criteria decision-making. Design/methodology/approach To solve this challenge, the authors propose fuzzy analytical hierarchy process model. Based on the opinions of IoT experts, the model and the hierarchy were designed to assess and compare three crucial IoT criteria, namely, object, application and providers. Findings The results indicated that the application criterion is far more relevant for users other than the two criteria. The findings of this study offer insights into more effective decision-making for IoT application developers and providers. Originality/value This study contributes to the IoT through proposing a fuzzy model to classify IoT applications. The findings provide meaningful implications for IoT application providers.

Supporting decision-making in service supplier selection using a hybrid fuzzy extended AHP approach

2017 ◽  
Vol 23 (1) ◽  
pp. 196-222 ◽  
Author(s):  
Giustina Secundo ◽  
Donato Magarielli ◽  
Emilio Esposito ◽  
Giuseppina Passiante
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Hybrid Approach ◽  
High Tech ◽  
Manufacturing Companies ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Hierarchy Process

Purpose Service supplier selection is a multi-criteria decision-making (MCDM) problem assuming a strategic role for the competitiveness of high-tech manufacturing companies. Nevertheless, especially for service quality evaluation, there is little empirical evidence of the practical usefulness of MCDM methodologies. Aiming to cover this gap between theoretical approaches and empirical applications, the purpose of this paper is to propose a fuzzy extended analytic hierarchy process (FEAHP) approach for service supplier evaluation. Design/methodology/approach A hybrid approach which combines some of the strengths of the analytic hierarchy process (AHP) and of the fuzzy set theory is presented, as organized into five steps. A case study is used to evaluate the applicability in a real company context. Findings The usability of the approach is demonstrated in an aerospace company for solving the supplier selection problem of a business software whose applications are still in infancy: a Test Data Management System (TDMS). The illustrative application contains both “general” criteria to be used for other service supplier selection contexts as well as service-specific criteria related to software selection. Research limitations/implications Even if the application regards the selection of a software supplier, the methodology can be generically extended to other services’ selection in complex manufacturing industries through the personalization of some criteria. Practical implications Implications can be derived both for business managers involved into the decision-making process and for suppliers identifying the most promising features of software quality. Originality/value The originality consists in the combination into a hybrid approach of the strong points of the AHP with the fuzzy set; the inclusion of multiple perspectives of decision criteria for service supplier selection, basically the “software product” and “supplier” ones; a real empirical application to test and demonstrate the efficacy and the practical utility of the proposed approach.

Use of AHP in decision-making for machine tool configurations

2016 ◽  
Vol 27 (6) ◽  
pp. 874-888 ◽  
Author(s):  
Uday Hameed Farhan ◽  
Majid Tolouei-Rad ◽  
Adam Osseiran
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Pairwise Comparison ◽  
Assessment Process ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Four Levels ◽  
Time Required ◽  
Hierarchy Process ◽  
Selection Of

Purpose The purpose of this paper is to develop a model of analytic hierarchy process (AHP), a multiple criteria decision-making method, to assist selecting suitable machine configurations for special purpose machines (SPMs) from available alternatives. Design/methodology/approach The necessary criteria and sub-criteria were identified and used in the developed model. The assessment process was carried out by constructing the hierarchy of four levels. Then, pairwise comparison matrices were created for each level to compute the weights for the alternatives. The model was programmed and implemented by software for practical use. Findings Different scenarios were obtained from the assessment process of the developed AHP model showing the influence of changing the relevant importance of the elements in the hierarchy on the selection of SPMs configurations. Selection of the suitable scenario was also affected by some factors of manufacturing preferences and industry recommendations such as cost and production rate. Originality/value This is a new application of AHP method which assists decision makers to select suitable configurations for SPMs, and reduce the time required for designing SPMs.

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