An Intelligent Multiattribute Group Decision-Making Approach With Preference Elicitation for Performance Evaluation

Duman, Gazi Murat; El-Sayed, Ahmed; Kongar, Elif; Gupta, Surendra M.

doi:10.1109/tem.2019.2900936

Cited by 32 publications

(9 citation statements)

References 64 publications

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“…To achieve this, enabler, criteria, and attributes related to retail operations are identified from literature review and evaluated by collecting importance weight and performance rating to assess the current level of retail operation.In second phase, graph‐theoretic approach classifies the factors as very weak, weaker, and stronger factors to develop an exit strategy for BS events. Moreover, GT will be helpful for analyzing interrelationship between these factors and select the appropriate factors to improve the performance of retail operations (Calafut et al, 2021 ; Duman et al, 2020 ; Manimuthu et al, 2019 ). Further, GT groups the factors that can be used as triggering variables in exit strategy.The third phase, machine learning (ML)‐based prediction, is used to predict customer retention for retail shopping.…”

Section: Methodsmentioning

confidence: 99%

Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco

et al. 2022

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Novel coronavirus disease (COVID‐19) and resulting lockdowns have contributed to major retail operational disturbances around the globe, forcing retail organizations to manage their operations effectively. The impact can be measured as a black swan event (BSE). Therefore, to understand its impact on retail operations and enhance operational performance, the study attempts to evaluate retail operations and develop a decision‐making model for disruptive events in Morocco. The study develops a three‐phase evaluation approach. The approach involves fuzzy logic ( to measure the current performance of retail operations ), graph theory ( to develop an exit strategy for retail operations based on different scenarios ), and ANN and random forest‐based prediction model with K‐cross validation ( to predict customer retention for retail operations ). This methodology is preferred to develop a unique decision‐making model for BSE. From the analysis, the current retail performance index has been computed as “Average” level and the graph‐theoretic approach highlighted the critical attributes of retail operations. Further, the study identified triggering attributes for customer retention using machine learning‐based prediction models (MLBPM) and develops a contactless payment system for customers' safety and hygiene. The framework can be used on a periodic basis to help retail managers to improve their operational performance level for disruptive events.

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Section: Methodsmentioning

confidence: 99%

Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco

et al. 2022

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“…A weighted supermatrix is obtained via normalizing each column in the supermatrix. The weighted super-matrix needs to be limited by raising it to a sufficiently large power s until it converges and becomes a long-term stable super-matrix lim → [143].…”

Section: Anp Analysismentioning

confidence: 99%

Improving Online Learning Experience Using Facial Expression Analysis

Zel

Duman

Kongar

2021

IEEE Eng. Manag. Rev.

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“…The successful execution of LSS make an organization enable to reduce its defect level, wastes, and helps to stay competitive in global market [4] [5]. In the recent scenario, increased customer focus towards sustainable products has forced the industries to cut current level of emissions [6] [7]. Although LSS leads to improved organizational performance and profitability, it is not able to address environmental issues.…”

Section: Introductionmentioning

confidence: 99%

Exploration and Investigation of Green Lean Six Sigma Adoption Barriers for Manufacturing Sustainability

Kaswan

Rathi

Garza‐Reyes

et al. 2023

IEEE Trans. Eng. Manage.

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The increased awareness about effect of operations on sustainability dynamics and governmental pressure to cut emission rates has forced industries to adopt sustainable approaches like Green Lean Six Sigma (GLSS). Despite increasing interest in GLSS, very limited research has focused on its implementation and no research has investigated barriers that hinder GLSS execution. This study investigates GLSS implementation barriers, their relationship, and removal of same in manufacturing sector. In this research, 18 GLSS barriers have been recognized through literature review and formulated into logical groups using principal component analysis. This study pioneers with decision making trial and evaluation laboratory (DEMATEL) with intuitionistic fuzzy set to prioritize barriers and handle the important and causal relationship among the same.The results of the study were validated through intuitionistic fuzzy best worst method (IF-BWM). The results reveal that management-related barriers are the top-ranked followed by environmental and organization barriers with BWM weights 0.5283, 0.1704, and 0.1035 respectively. This provides impetus to policymakers for induction of GLSS in business organization to make harmony between economic development and environmental sustainability.

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An Intelligent Multiattribute Group Decision-Making Approach With Preference Elicitation for Performance Evaluation

Cited by 32 publications

References 64 publications

Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco

Managing the retail operations in the COVID‐19 pandemic: Evidence from Morocco

Improving Online Learning Experience Using Facial Expression Analysis

Exploration and Investigation of Green Lean Six Sigma Adoption Barriers for Manufacturing Sustainability

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