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1 – 10 of over 45000Maria Angela Butturi, Francesco Lolli and Rita Gamberini
This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their…
Abstract
Purpose
This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.
Design/methodology/approach
A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.
Findings
A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.
Originality/value
Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.
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This study aims to apply new modifications by changing the nonlinear logarithmic calculation steps in the method based on the removal effects of criteria (MEREC) method. Geometric…
Abstract
Purpose
This study aims to apply new modifications by changing the nonlinear logarithmic calculation steps in the method based on the removal effects of criteria (MEREC) method. Geometric and harmonic mean from multiplicative functions is used for the modifications made while extracting the effects of the criteria on the overall performance one by one. Instead of the nonlinear logarithmic measure used in the MEREC method, it is desired to obtain results that are closer to the mean and have a lower standard deviation.
Design/methodology/approach
The MEREC method is based on the removal effects of the criteria on the overall performance. The method uses a logarithmic measure with a nonlinear function. MEREC-G using geometric mean and MEREC-H using harmonic mean are introduced in this study. The authors compared the MEREC method, its modifications and some other objective weight determination methods.
Findings
MEREC-G and MEREC-H variants, which are modifications of the MEREC method, are shown to be effective in determining the objective weights of the criteria. Findings of the MEREC-G and MEREC-H variants are more convenient, simpler, more reasonable, closer to the mean and have fewer deviations. It was determined that the MEREC-G variant gave more compatible findings with the entropy method.
Practical implications
Decision-making can occur at any time in any area of life. There are various criteria and alternatives for decision-making. In multi-criteria decision-making (MCDM) models, it is a very important distinction to determine the criteria weights for the selection/ranking of the alternatives. The MEREC method can be used to find more reasonable or average results than other weight determination methods such as entropy. It can be expected that the MEREC method will be more used in daily life problems and various areas.
Originality/value
Objective weight determination methods evaluate the weights of the criteria according to the scores of the determined alternatives. In this study, the MEREC method, which is an objective weight determination method, has been expanded. Although a nonlinear measurement model is used in the literature, the contribution was made in this study by using multiplicative functions. As an important originality, the authors demonstrated the effect of removing criteria in the MEREC method in a sensitivity analysis by actually removing the alternatives one by one from the model.
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Jalil Heidary Dahooie, Ieva Meidute-Kavaliauskiene, Amir Salar Vanaki, Askoldas Podviezko and Elham Beheshti Jazan Abadi
The present study is aimed to develop a firm export performance measurement model. Increased levels of globalization are forcing firms, especially SMEs (i.e. small and…
Abstract
Purpose
The present study is aimed to develop a firm export performance measurement model. Increased levels of globalization are forcing firms, especially SMEs (i.e. small and medium-sized enterprises) and entrepreneurial firms, to enter new markets and increase their exports. Consequently, export performance measurement has become a vital tool for achieving competitive advantages, and this type of measurement is considered an important topic of research in the field of international marketing. However, the literature lacks a comprehensive framework for measuring export performance, even though many criteria for gauging this performance's parameters have been discovered and applied.
Design/methodology/approach
A literature review was conducted, and the most important criteria for export performance measurement was identified using weights obtained by stepwise weight assessment ratio analysis method. Then, the export performance of five firms was evaluated using the additive ratio assessment method with interval-valued triangular fuzzy numbers.
Findings
The 15 most significant criteria were identified and categorized into three dimensions: economic, strategic, and other. The strategic dimension was identified as the most important, while the criteria “strategic goals achievement” and “return on investment” were found to be the most relevant.
Practical implications
A comprehensive framework including a definitive set of the most prominent, useful evaluation criteria was established which enables both scholars and practitioners to assess export performance.
Originality/value
The current study attempts to fill the gaps in the literature by presenting a comprehensive framework for export performance measurement.
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The purpose of the study is the evaluation of choosing the determined logistics centers’ (LCs’) locations via Multi-Criteria Decision-Making (MCDM) methods.
Abstract
Purpose
The purpose of the study is the evaluation of choosing the determined logistics centers’ (LCs’) locations via Multi-Criteria Decision-Making (MCDM) methods.
Design/methodology/approach
Since there is more than one criterion in the evaluation of LC location, MCDM methods are used. The Entropy and CRiteria Importance Through Intercriteria Correlation (CRITIC) methods are used to determine the main criteria and sub-criteria weights. The Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method is used for ranking and evaluating 12 alternatives in Turkey and sensitivity analysis according to the threshold values of criteria and preference functions.
Findings
Possible LC alternatives in Turkey and 12 locations ranked. Changing the criteria weights at a significant level did not affect the ranking results much. In the sensitivity analysis of the criteria for which market data could not be obtained (scored by the experts) it is found that they either made no difference or made little difference in the ranking of the alternatives.
Practical implications
In terms of sustainability, economic factors along with environmental and social dimensions are important criteria for logistics companies and LC. The use of these variables in the LC location selection makes a difference.
Originality/value
This study focuses on LC location selection, via PROMETHEE with evaluated preference functions for criteria, taking into account nine scenarios that use variable criteria weight calculated via different MCDM methods. The results are evaluated by using sensitivity analysis and taking into account the sustainability aspect for LC. Multiple methods have been used effectively together in a way that support each other.
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Ru Liang, Rui Li, Xue Yan, Zhenzhen Xue and Xin Wei
Prefabricated components sustainable supplier (PCSS) selection is critical to the success of prefabricated projects. However, limited studies have addressed the uncertainty and…
Abstract
Purpose
Prefabricated components sustainable supplier (PCSS) selection is critical to the success of prefabricated projects. However, limited studies have addressed the uncertainty and complexities during the selection process, particularly in multi-criterion group decision-making (MCGDM) circumstances. Hence, the research aims to develop a group decision-making model using a modified fuzzy MCGDM approach for PCSS selection under uncertain situation.
Design/methodology/approach
The proposed study develops a framework for sorting decisions in PCSS selection by using the hesitant fuzzy technique for order preference by similarity to ideal solution (HF-TOPSIS) method. The maximum consistency (MC) model is used to calculate the weights of decision makers (DMs) based on the cardinality and sequence of decision data.
Findings
The proposed framework has been successfully applied and illustrated in the case example of CB01 contract section in Hong Kong-Zhuhai-Macao Bridge (HZMB) megaproject. The results show various complicated decision-making scenarios can be addressed through the proposed approach. The MC model is able to calculate the weights of DMs based on the cardinality and sequence of decision data.
Originality/value
The research contributes to improving accuracy and reliability decision-making processes for PCSS selection, especially under hesitant and fuzzy situations in prefabricated megaprojects.
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Madjid Tavana, Amir Karbassi Yazdi, Mehran Shiri and Jack Rappaport
This paper aims to propose a new benchmarking framework that uses a series of existing intuitive and analytical methods to systematically capture both objective data and…
Abstract
Purpose
This paper aims to propose a new benchmarking framework that uses a series of existing intuitive and analytical methods to systematically capture both objective data and subjective beliefs and preferences from a group of decision makers (DMs).
Design/methodology/approach
The proposed framework combines the excellence model developed by the European Foundation for Quality Management with the Rembrandt method, the entropy concept, the weighted‐sum approach, and the theory of the displaced ideal. Hard data and personal judgments are synthesized to evaluate a set of business units (BUs) with two overall performance scores plotted in a four quadrant model.
Findings
The two performance scores are used to benchmark the performance of the BUs in accordance with their Euclidean distance from the “ideal” BU. Quadrants are used to classify the BUs as efficacious, productive ineffectual, proficient unproductive, and inefficacious. The efficacious BUs, referred to as “excellent”, fall in the competency zone and have the shortest Euclidean distance from the ideal BU relative to their peers.
Originality/value
The benchmarking framework presented in this study has some obvious attractive features. First, the generic nature of the framework allows for the subjective and objective evaluation of a finite number of BUs by a group of DMs. Second, the information requirements of the framework are stratified hierarchically allowing DMs to focus on a small area of the large problem. Third, the framework does not dispel subjectivity; it calibrates the subjective weights with the objective weights determined through the entropy concept.
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Juha-Matti Lehtonen and Kai Virtanen
The purpose of this paper is to propose and test a multi-criteria decision analysis (MCDA) approach based on an additive value function (AVF) to select the most economically…
Abstract
Purpose
The purpose of this paper is to propose and test a multi-criteria decision analysis (MCDA) approach based on an additive value function (AVF) to select the most economically advantageous tender under European Union public procurement regulations.
Design/methodology/approach
A case study in which the AVF tender evaluation model is constructed by the procurement personnel and the results of the original, real-life public procurement evaluation model are compared to those discovered by the MCDA approach.
Findings
The AVF model captures the preferences of the procurement authority in a more reliable and transparent manner than commonly used evaluation models based on scoring formulas.
Practical implications
While commonly used in public procurement, relative scoring formulas can neither present the preferences of a procurement unit accurately nor do they enable bidders to draft bids according to these preferences. The proposed MCDA approach can achieve both.
Originality/value
The contribution of this paper is threefold. First, the successful construction of the AVF model with procurement personnel is introduced. Second, the model is used in an actual, real-life case. Third, a thoughtful comparison of features, structures and results of the AVF model and the evaluation model using scoring formulas is presented.
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Fatma Pakdil, Pelin Toktaş and Gülin Feryal Can
The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM…
Abstract
Purpose
The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry.
Design/methodology/approach
This study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework’s applicability and validity for future decision-makers who will take place in Six Sigma project selection processes.
Findings
The study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank.
Practical implications
The methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches.
Originality/value
This is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts’ rankings related to criteria and the performance values of alternates for criteria.
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Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou and Dimitrios Zevgolis
Evaluation of energy and climate policy interactions is a complex issue, whereas stakeholders' preferences incorporation has not been addressed systematically. The purpose of this…
Abstract
Purpose
Evaluation of energy and climate policy interactions is a complex issue, whereas stakeholders' preferences incorporation has not been addressed systematically. The purpose of this paper is to present an integrated weighting methodology that has been developed in order to incorporate weighting preferences into an ex ante evaluation of climate and energy policy interactions.
Design/methodology/approach
A multi‐criteria analysis (MCA) weighting methodology which combines pair‐wise comparisons and ratio importance weighting methods has been elaborated. It initially introduces the users to the evaluation process through a warming up holistic approach for an initial rank of the criteria and then facilitates them to express their ratio relative importance in pair‐wise comparisons of criteria by providing them an interactive mean with verbal, numerical and visual representation of their preferences. Moreover, it provides a ranking consistency test where users can see the degree of (in)consistency of their preferences.
Findings
Stakeholders and experts in the energy policy field who tested the methodology stated their approval and satisfaction for the combination of both ranking and pair‐wise comparison techniques, since it allows the gradual approach to the evaluation problem. In addition, main difficulties in MCA weights elicitation processes were overcome.
Research limitations/implications
The methodology is tested by a small sample of stakeholders, whereas a larger sample, a broader range of stakeholders and applications on different climate policy evaluation cases merit further research.
Originality/value
The novel aspect of the developed methodology consists of the combination of ranking and pair‐wise comparison techniques for the elicitation of stakeholders' preferences.
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