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Article
Publication date: 30 October 2020

Adrija Majumdar and Arnab Adhikari

In the context of sharing economy, the superhost program of Airbnb emerges as a phenomenal success story that has transformed the tourism industry and garnered humongous…

Abstract

Purpose

In the context of sharing economy, the superhost program of Airbnb emerges as a phenomenal success story that has transformed the tourism industry and garnered humongous popularity. Proper performance evaluation and classification of the superhosts are crucial to incentivize superhosts to maintain higher service quality. The main objective of this paper is to design an integrated multicriteria decision-making (MCDM) method-based performance evaluation and classification framework for the superhosts of Airbnb and to study the variation in various contextual factors such as price, number of listings and cancelation policy across the superhosts.

Design/methodology/approach

This work considers three weighting techniques, mean, entropy and CRITIC-based methods to determine the weights of factors. For each of the weighting techniques, an integrated TOPSIS-MOORA-based performance evaluation method and classification framework have been developed. The proposed methodology has been applied for the performance evaluation of the superhosts (7,308) of New York City using real data from Airbnb.

Findings

From the perspective of performance evaluation, the importance of devising an integrated methodology instead of adopting a single approach has been highlighted using a nonparametric Wilcoxon signed-rank test. As per the context-specific findings, it has been observed that the price and the number of listings are the highest for the superhosts in the topmost category.

Practical implications

The proposed methodology facilitates the design of a leaderboard to motivate service providers to perform better. Also, it can be applicable in other accommodation-sharing economy platforms and ride-sharing platforms.

Originality/value

This is the first work that proposes a performance evaluation and classification framework for the service providers of the sharing economy in the context of tourism industry.

Details

Benchmarking: An International Journal, vol. 28 no. 2
Type: Research Article
ISSN: 1463-5771

Keywords

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Article
Publication date: 2 May 2019

Shankar Chakraborty, Prasenjit Chatterjee and Partha Protim Das

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries…

Abstract

Purpose

To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

Design/methodology/approach

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

Findings

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

Practical implications

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

Originality/value

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

Details

Journal of Modelling in Management, vol. 14 no. 2
Type: Research Article
ISSN: 1746-5664

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Article
Publication date: 9 March 2021

Arnab Adhikari, Samadrita Bhattacharyya, Sumanta Basu and Rajesh Bhattacharya

In the context of India, this article proposes an integrated multicriteria decision-making (MCDM) regression-based methodology to evaluate input-level performance of the…

Abstract

Purpose

In the context of India, this article proposes an integrated multicriteria decision-making (MCDM) regression-based methodology to evaluate input-level performance of the schools and investigate the impact of this performance along with contextual factors, i.e. medium of instruction and location of the school, on the school's output level performance, i.e. student pass rate.

Design/methodology/approach

First, Shannon entropy-based approach is applied for the weight assignment to different parameters. Then, integrated VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique for order preference by similarity to an ideal solution (TOPSIS)-based methodology is devised to measure the input-level performance of a school. Finally, multiple linear regression (MLR) analysis is incorporated to study the effect of input-level performance and above-mentioned contextual factors on the school's output-level performance.

Findings

Proposed methodology is applied to assess the input-level performance of 82,930 primary and secondary schools of West Bengal, India. All the factors have a significant impact on boys' pass rate, whereas only input-level performance and location of the school have a significant influence on the girls' pass rate.

Practical implications

The entropy-based approach highlights the importance of scientific weight assignment. Integrated MCDM demonstrates the significance of aggregation due to the variation in scores related to input-level performance across the methods. Regression analysis facilitates the exploration of determinants influencing the output-level performance of the schools.

Originality/value

This work depicts a holistic picture of the performance measurement system of the schools. It encompasses scientific weight assignment to the evaluation criteria, integrated input-level performance assessment of the schools and investigation into the effect of this performance, as well as other contextual factors on the output level performance.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

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Article
Publication date: 24 November 2020

Sakthivel Murugan R. and Vinodh S.

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based…

Abstract

Purpose

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.

Design/methodology/approach

The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.

Findings

The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.

Research limitations/implications

In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.

Practical implications

The study presents the case of an automotive component, which illustrates practical relevance.

Originality/value

In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

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Article
Publication date: 5 February 2020

Yan-Kai Fu, Weilun Huang and Chin-Nung Liao

The purpose of this paper is to evaluate the hotel selection problem of airlines for their hotel and airline alliance (HAA) to develop potential customers of airlines…

Abstract

Purpose

The purpose of this paper is to evaluate the hotel selection problem of airlines for their hotel and airline alliance (HAA) to develop potential customers of airlines. This paper will propose a hybrid mathematics evaluation model to help airline to select an optimal hotel with both qualitative and quantitative criteria.

Design/methodology/approach

To solve the hotel selection problem of airlines for their HAA, this paper focuses on the implementation of the NGT, Fuzzy TOPSIS and MCGP models in the hotel selection process. Initially, the NGT was used to create HAA decision-making criteria based on the literature review and expert opinions, and it was found that scale and scope possibility, brand value, tourism attraction, operating cost and industrial conditions are the most important criteria. Later, the Fuzzy TOPSIS method was used to obtain the general normalized fuzzy preference and to compute the closeness coefficients of each alternative hotel with respect to each criterion. Third, five tangible constraints were incorporated into the Fuzzy TOPSIS-MCGP model to calculate the optimal hotel with LINGO software.

Findings

Airline managers can use the proposed model to form a clear view of how to choose the most suitable hotel to cooperate with to outperform their competitors. Having access to this information allows airline managers to take steps to perform better and improve the performance of the partnership, helping them to gain more confidence in their decision-making capabilities while reducing investment risks.

Originality/value

This is the first paper that has adopted Fuzzy TOPSIS-MCGP to select hotel for their HAA from the airline’s point of view. The major contributions of this study are as follows: an efficient and simple evaluation framework is proposed for handling vagueness and uncertainty in real-world hotel selection problems; the advancement of treating uncertainty in the MCDM process; the fuzzy TOPSIS-MCGP method is extended for such problems, taking into account tangible and intangible criteria; airline managers can now make decisions in choosing to select the best hotel for their HAA that meets the airline's business goals and passenger demands; hotel operators are flexible in selecting their airline partnership, thus creating greater profit for both parties.

饭店和航空公司之间横向联盟的选择模型:NGT, fuzzy TOPSIS和MCGP方法的综合应用

目的

本文的主要目的是在协助驾驶评估酒店选择的问题, 并通过由酒店与航空公司的合作联盟HAA, 开发整合的潜在客户。评估模型, 以帮助航空公司选择同时满足定性和定量标准的最佳酒店。

设计/方法/方法

这些研究集中在规模和范围的可能性, 品牌价值, 旅游吸引上力, 运营成本和产业条件上。第二个步骤是日期近似近似最佳解排序技术(fuzzy TOPSIS)计算每家替代酒店与理想解决方案的接近度系数。规划方法(MCGP)选择最佳酒店, 同时选择方法同时考虑酒店的定性和定量标准, 并且从未在酒店选择文献中被采用过。

结果

为了帮助评估评估合适的酒店和建立合作联盟, 因此本文提出了NGT-Fuzzy TOPSIS-MCGP模型, 以帮助决策的决策者实现替代的酒店。在此模型中, 决策者通过最后, 在名目人群技术(NGT)确定客观的酒店选择规范, 然后他们可以根据模糊近似最佳解排序技术(TOPSIS)确定标准权重, 并计算模糊的TOPSIS-MCGP模型中, 决策制定者可以使用多选择目标规划(MCGP), 通过设定每个目标的期望水准寻找最佳酒店。

原创/价值

这是第一篇以航空的角度, 同时采用模糊TOPSIS-MCGP方法选择合适的酒店的论文。本文最主要的贡献是: 1. 提出了一种有效而简单的评估框架, 用于处理现实世界中酒店选择问题中的模糊性和不确定性。2. 在处理MCDM过程中不确定性方面的进展;模糊TOPSIS-MCGP方法针对此类问题进行了扩展, 同时考虑了有形和无形的标准。3. 航空公司经理现在可以做出决定, 选择适合其HAA的最佳酒店, 借以满足航空公司的业务目标以及乘客的需要。4. 酒店运营商可以灵活选择航空公司合作伙伴关系, 从而为双方创造更大的利润。

关键词

饭店, 航空公司, 名目人群技术(NGT), 最佳解排序技术(TOPSIS), 多选择目标规划(MCGP), 横向联盟

El modelo de selección Para alianzas horizontales entre hoteles y aerolíneas (Haa): una aplicación integrada de los métodos NGT, fuzzy TOPSIS y MCGP

Objetivo

El objetivo principal de este documento es evaluar el problema de selección de hoteles de las aerolíneas para su HAA (hotel airline alliance) a fin de desarrollar clientes potenciales para las aerolíneas. Este documento propondrá un modelo híbrido de evaluación matemática para ayudar a la aerolínea a seleccionar un hotel óptimo con criterios cualitativos y cuantitativos.

Diseño/metodología/enfoque

Para resolver el problema de selección de hoteles de las aerolíneas para su HAA, este documento se centra en la implementación de los modelos NGT, Fuzzy TOPSIS y MCGP en el proceso de selección de hoteles. Inicialmente, el NGT se utilizó para crear criterios de toma de decisiones de HAA basados en la revisión de la literatura y las opiniones de expertos, y se descubrió que la escala y la posibilidad de elección, el valor de la marca, la atracción turística, los costes operativos y las condiciones industriales son los criterios más importantes. Posteriormente, se utilizó el método Fuzzy TOPSIS para obtener la preferencia fuzzy general y normalizada y calcular los coeficientes de cercanía de cada hotel alternativo con respecto a cada criterio. En tercer lugar, se incorporaron cinco restricciones tangibles al modelo Fuzzy TOPSIS-MCGP para calcular el hotel óptimo con el software LINGO.

Resultados

Los gerentes de aerolíneas pueden usar el modelo propuesto para tener una visión clara de cómo elegir el hotel más adecuado para colaborar con el fin de superar a sus competidores. Tener acceso a esta información permite a los gerentes de las aerolíneas tomar medidas para gestionar mejor y mejorar el resultado de la alianza, lo que les ayuda a ganar más confianza en su capacidad de toma de decisiones y al mismo tiempo reducir los riesgos de inversión.

Originalidad/valor

Este es el primer documento que adopta el modelo Fuzzy TOPSIS-MCGP para seleccionar un hotel para su HAA desde el punto de vista de la aerolínea. Las principales contribuciones de este estudio son las siguientes: 1. Se propone un marco de evaluación eficiente y simple para manejar la imprecisión y la incertidumbre en los problemas de selección de hoteles del mundo real. 2. El avance del tratamiento de la incertidumbre en el proceso MCDM; extiende el método fuzzy TOPSIS-MCGP a tales problemas, teniendo en cuenta criterios tangibles e intangibles. 3. Los gerentes de aerolíneas ahora pueden tomar decisiones al elegir el mejor hotel para su HAA que cumpla con los objetivos comerciales de la aerolínea y las demandas de los pasajeros. 4. Los operadores de hoteles son flexibles en la selección de su asociación de aerolíneas, creando así mayores ganancias para ambas partes.

Palabras clave:

Hotel, Aerolínea, Técnica de grupo nominal (NGT), Técnica Para el orden de preferencia por similitud a solución real (TOPSIS), Programación de objetivos de opción múltiple (MCGP), Alianza horizontal

Tipo de papel

Trabajo de investigación

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Article
Publication date: 1 February 2016

Shouzhen Zeng and Yao Xiao

The purpose of this paper is to present a hybrid intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method, called intuitionistic…

Abstract

Purpose

The purpose of this paper is to present a hybrid intuitionistic fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method, called intuitionistic fuzzy ordered weighted averaging weighted averaging (OWAWA) distance TOPSIS (IFOWAWAD-TOPSIS) method for intuitionistic fuzzy multiple-criteria decision making (MCDM) problems.

Design/methodology/approach

Based on the OWAWA operator, the authors develop the intuitionistic fuzzy OWAWA distance measure, then the IFOWAWAD-TOPSIS method is obtained by using the IFOWAWAD and traditional TOPSIS.

Findings

The developed IFOWAWAD-TOPSIS method can overcome the drawback of traditional TOPSIS method that cannot consider both the subjective information of attributes and the attitudinal character of decision maker.

Research limitations/implications

Clearly, this paper is devoted to the OWA operator, MCDM and intuitionistic fuzzy theory.

Practical implications

The developed method is applicable in a wide range of situations such as decision-making, statistics, engineering and economics. A numerical example concerning investment selection is given to illustrate the practicability and usefulness of the proposed approach.

Originality/value

This paper fulfils an identified need to study how to make a decision considering both the subjective information of attribute and the attitudinal character of decision maker in intuitionistic fuzzy environment.

Details

Kybernetes, vol. 45 no. 2
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 28 August 2009

Selçuk Perçin

Third‐party logistics (3PL) provider selection has gained great attention in logistics management literature. The purpose of this paper is to provide a good insight into…

Abstract

Purpose

Third‐party logistics (3PL) provider selection has gained great attention in logistics management literature. The purpose of this paper is to provide a good insight into the use of a‐two‐phase analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach that is a multi‐criteria decision‐making methodology in the evaluation of 3PL providers.

Design/methodology/approach

In this paper, after the selection criteria of 3PL providers are determined by modified Delphi method, the weights of criteria have been calculated by applying the AHP method. The TOPSIS method is then employed to achieve the final ranking results. And an actual case example is presented to clarify the methodology. Sensitivity analysis is also given to demonstrate how sensitive the proposed model is to changes in the weights of different main criteria.

Findings

This model provides decision makers with a simple, flexible, and easy‐to‐use approach to evaluate potential 3PL providers efficiently. Findings demonstrate that the proposed benchmarking framework, with minor modifications, can be useful to all firms in their 3PL provider selection decisions.

Research limitations/implications

A two‐phase AHP and TOPSIS methodology is very flexible and suitable for various decision situations. However, selection of the appropriate 3PL provider requires consideration of multiple alternative solutions and evaluation criteria because of complex methodology, and hence it increases the effort.

Originality/value

This is probably the first time that an attempt has been made to apply the modified Delphi method, AHP and TOPSIS methodology in the decision of 3PL provider selection in a Turkish automotive supplier company. This is the most powerful motivation to consider this problem. In addition, the paper is especially of interest to managers as they make decisions on which criteria should be considered in the evaluation process and how a decision model should be structured by using a two‐phase AHP and TOPSIS methodology.

Details

Benchmarking: An International Journal, vol. 16 no. 5
Type: Research Article
ISSN: 1463-5771

Keywords

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Article
Publication date: 6 May 2014

Ki-Yoon Kim and Kwan-Sik Na

The extended TOPSIS approach including the analytical hierarchy process method is used to solve business recovery priority decision problem mixed with interval data and…

Abstract

Purpose

The extended TOPSIS approach including the analytical hierarchy process method is used to solve business recovery priority decision problem mixed with interval data and exact data of an insurance company. The paper aims to discuss these issues.

Design/methodology/approach

According to the concept of TOPSIS, the authors construct the normalized decision matrix and the weighted normalized decision matrix. Using the vertex method, the authors calculate the distance of each alternative from the positive or negative ideal solution.

Findings

The proposed TOPSIS algorithms on interval data provide a useful framework for systematic risk assessment that an incident or disaster manager can use to prioritize recovery during business discontinuity.

Research limitations/implications

As a managerial implication, the proposed method can be applied to any case for providing information for risk management decision-making in industrial and service organizations. As for a future direction, other decision-making methods can be included in the methodology to ensure more integrated and/or comparative study.

Practical implications

The ratings and weights of the criteria in the decision problem are assessed by means of interval data. The use of the interval data in decision problem is highly beneficial when performance values cannot be expressed by means of numerical values. The authors extended the TOPSIS approach for solving MCDM problem with interval data as well as exact data.

Social implications

The authors have shown how TOPSIS method on interval data can be used to provide priority decision for business recovery of an insurance company. The proposed method provides the authors a useful way to deal with a business recovery problem, where the values of evaluating items are represented by generalized exact numbers or interval-valued numbers.

Originality/value

The proposed approach has the potential to resolve incident and disaster management and can be applied to the implementation of business recovery plan for business continuity.

Details

Journal of Systems and Information Technology, vol. 16 no. 2
Type: Research Article
ISSN: 1328-7265

Keywords

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Article
Publication date: 2 March 2020

Liz Hassad de Andrade, Jorge Junio Moreira Antunes and Peter Wanke

The aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.

Abstract

Purpose

The aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.

Design/methodology/approach

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Ng-model, Grey relational analysis (GRA), and principal component analysis (PCA) were applied to evaluate the programs, using audience, share, and duration as the performance criteria.

Findings

By comparing TOPSIS to the Ng-model, PCA, and GRA, we verified that SVD and bootstrap SVD TOPSIS provide a good balance between equal-weights TOPSIS and the other models. This is because SVD and bootstrap SVD TOPSIS break down the data to a higher degree, but are less impacted by outliers compared to the long tail models.

Practical implications

To determine which TV programs should be replaced or modified is a complex decision that has not been addressed in the literature. The advantage of using a multi-criteria decision-making (MCDM) approach is that analysts can choose as many criteria as they want to rank TV programs, rather than relying on a single criterion (e.g., audience, share, target rating point).

Originality/value

This work represents the first time that robust MCDM methodology is applied to an audience data set to analyze the performance of TV programs and to identify what can be done to improve them. This study shows the application of a detailed methodology that is useful for the improvement of TV programs and other entertainment industry content.

Details

Benchmarking: An International Journal, vol. 27 no. 3
Type: Research Article
ISSN: 1463-5771

Keywords

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Article
Publication date: 4 June 2018

Henry Lau, Dilupa Nakandala and Paul Kwok Shum

Frequent food safety incidents caused widespread consumer concerns. Even though food safety is one of the weakest links in the fresh food supply chain and influences…

Abstract

Purpose

Frequent food safety incidents caused widespread consumer concerns. Even though food safety is one of the weakest links in the fresh food supply chain and influences consumer food choice in ways different from the quality dimension, this factor is hardly proposed as one of the key traditional supplier selection criteria (e.g. quality, delivery, and price) in the literature. The purpose of this paper is to develop a business process decision model to assess the non-compensating food safety sub-criteria in order to disqualify fresh food suppliers that cannot reach the minimum threshold for low probable food safety failure. The preferred fresh food suppliers can minimize the risk of food safety failure and the associated huge food safety failure costs spanning from private consumer anguish to social distress that cause unbearable costs of sales loss and damage to brand image in business.

Design/methodology/approach

This study proposes a novel approach that combines several well-established multi-criteria decision making (MCDM) techniques, including fuzzy AHP (FAHP), TOPSIS, and ELECTRE, and innovatively apply to analyze supplier performance and prioritize potential fresh food suppliers. This hybrid business process model can enforce compliance to all the five non-compensatory sub-criteria of food safety. Since ELECTRE is a non-compensatory MCDM method, it is therefore particularly applicable for disqualifying high risk fresh food suppliers from further full scale supplier performance evaluation by FAHP and TOPSIS. This hybrid business process decision model is able to capitalize on the strengths of these MCDM methods and offset their deficiencies.

Findings

This study uses data of an international supermarket chain to validate feasibility of the proposed model. Results indicate that this model is able to assess the non-compensating food safety sub-criteria via the ELECTRE method in order to disqualify fresh food suppliers that cannot reach the minimum threshold for low probable food safety failure. Only the preferred suppliers with the required food safety capability can proceed to the second stage of the supplier selection process. Assessment via the TOPSIS method reveals the ranking order of those top performing suppliers according to their relative scores along all the supplier selection criteria. The TOPSIS ranking results with the selection of the suppliers C, E, A, and F are robust and consistent across all the different scenarios.

Practical implications

Application to the fresh food industry is possible with the aid of the MCDM methods. The contribution to the body of knowledge in this teaching and research field demonstrates the importance of first identifying the order qualifier for disqualifying those suppliers that do not satisfy the food safety requirements via the ELECTRE method. The proposed assessment procedure complies with the regulatory policy on food safety, and would influence public policy in applying the best practice of food safety regulation. Without first qualifying the potential suppliers on the basis of food safety, wrong decision can be made to select those high food risk suppliers that have relatively higher overall scores in other supplier selection criteria. Using the assessment results has positive economic and commercial impact on the purchasing managers to formulate appropriate purchasing and supplier development strategy to enhance supplier’s food safety performance, whilst maximizing the overall supplier portfolio performance. The improved supplier’s food safety performance will certainly benefit the society’s quality of life as well.

Originality/value

Based on the analytical MCDM methods of FAHP, TOPSIS, and ELECTRE, purchasing managers can operationalize the Hill’s framework of order qualifier and winner that has primarily been used in the literature and manufacturing industry. This study represents the first move to innovatively apply the FAHP, TOPSIS, and ELECTRE methods to operationalize the Hill’s framework of order qualifier and winner that has primarily been used in the literature and manufacturing industry. Application to the fresh food industry to validate the feasibility of the proposed model has been conceived and implemented in this study. Analysis of the data inputs of a supermarket chain via the three MCDM methods generate the results that fulfill the purpose of achieving the research objective of identifying and managing the supplier base that can deliver the best supplier performance, conditional on first passing the fresh food safety test.

Details

Business Process Management Journal, vol. 24 no. 3
Type: Research Article
ISSN: 1463-7154

Keywords

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