Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection

Maghsoodi, Abteen Ijadi; Mosavat, Mojan; Hafezalkotob, Ashkan; Hafezalkotob, Arian

doi:10.1016/j.cie.2018.11.018

Cited by 75 publications

(27 citation statements)

References 66 publications

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“…Subjective significance coefficients may be computed by applying various methods like the ANP, AHP, and BWM. It is recommended to use hierarchical weighting methods such as the hierarchical group BWM suggested by Maghsoodi et al [68], in order to reach the optimal weights based on a group decision-making approach. Fifth, the validation framework could also be implemented in many other applications with the input content of statistical values, such as the effect of influential factors on performance appraisal.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the Influencing Factors on Job Satisfaction Based on Combination of PLS-SEM and F-MULTIMOORA Approach

et al. 2018

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A primary issue that is being discussed nowadays in organizations is continuous improvement of the organization itself, because the procedure of periodic evaluation is an important tool to maintain the improvement of the organization. An essential factor in any organization is the human resources as a key asset to guide organizations to sustain their competitive advantages by employing particular knowledge and skills to form a comprehensive and sustainable human resource management. Evaluation of job satisfaction has become a part of the strategic approach toward incorporating business policies and human resource actions in modern day organizations. The current research study presents a novel hybrid validation framework to evaluate and appraise the factors influencing job satisfaction based on the fuzzy MULTIMOORA approach and partial least-squares path modeling (PLS-PM). The proposed fuzzy MCDM technique and statistical method validate each other to present an optimal assessment of influencing factors in job satisfaction. Eventually, a real-world case study in regard to influential factors in job satisfaction has been suggested in this study, to show that the proposed framework is a practical and accurate method to tackle an assessment problem in a real-world application of influencing factors in job satisfaction in a cross-industrial multi-national construction and geotechnical engineering organization in Iran.

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Section: Discussionmentioning

confidence: 99%

Evaluation of the Influencing Factors on Job Satisfaction Based on Combination of PLS-SEM and F-MULTIMOORA Approach

et al. 2018

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“…A recent list of the BWM integrations include the integrated DEA 4 and BWM (Omrani et al, 2020); the Euclidean BWM (Kocak et al, 2018); the PHFE 5 and the BWM (Li et al, 2019); the Z-number extension of the BWM (Aboutorab et al, 2018); the mixed grey-based BWM and TODIM 6 (Bai et al, 2019); the hybrid fuzzy BWM and COPRAS 7 method (Amoozad Mahdiraji et al, 2018); the integrated BWM and VIKOR method Gupta, 2018a;Garg and Sharma, 2018); the hybrid fuzzy TOPSIS and the BWM (Gupta, 2018b;Gupta and Barua, 2018;Lo et al, 2018); the hybrid BWM and ELECTRE 8 method (Yadav et al, 2018); the fuzzy BWM and fuzzy MULTIMOORA 9 (Liu et al, 2018a); rough numbers and the BWM (i.e. RBWM) and VIKOR (Liu et al, 2018b); the integrated IRN 10 and the BWM (IRN-BWM) (Pamucar et al, 2019); the MILM 11 to provide better approximate solutions to the original NLM 12 in the BWM (Beemsterboer et al, 2018); the fuzzy BWM (Guo and Zhao, 2017 Hafezalkotob, 2017;Maghsoodi et al, 2019); the IF-BWM 13 (Mou et al, 2017) and the IFM-BWM 14 (Mou et al, 2016).…”

Section: The Best-worst Methodsmentioning

confidence: 99%

A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria

et al. 2020

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The best-worst method (BWM) is a multiple criteria decision-making (MCDM) method for evaluating a set of alternatives based on a set of decision criteria where two vectors of pairwise comparisons are used to calculate the importance weight of decision criteria. The BWM is an efficient and mathematically sound method used to solve a wide range of MCDM problems by reducing the number of pairwise comparisons and identifying the inconsistencies derived from the comparison process. In spite of its simplicity and efficiency, the BWM does not consider the decision-makers' (DMs') confidence in their pairwise comparisons. We propose a neutrosophic enhancement to the original BWM by introducing two new parameters as the DMs' confidence in the best-to-others preferences and the DMs' confidence in the others-to-worst preferences. We present two real-world cases to illustrate the applicability of the proposed neutrosophic enhanced BWM (NE-BWM) by considering confidence rating levels of the DMs.

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“…Compared to AHP, BWM uses less comparison (BWM= 2n − 3, AHP= n(n − 1)/2), yet the consistency is better [48,54]. BWM is used to solve various problems, namely, supplier selection [55], location selection [50,53,56], service quality improvement [57], product design selection [49,58,59], supply-chain management [60], and performance evaluation [52,61]. BWM allows the decision-maker to select the best and the worst criteria to be transformed into the weight of each criterion using linear programming.…”

Section: Step 4: Best-worst Methodsmentioning

confidence: 99%

On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs

2020

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Improving service logistics is crucial in order to reciprocate customer needs. The paper aims to validate the Logistics Service Provider (LSP) Lifecycle Model for re-designing logistics service in three LSP case studies in Thailand. The lifecycle-stage evaluation was adapted to identify the current status in its lifecycle. Afterward, logistics service strategies were implemented according to the voice of the customer by Quality Function Deployment (QFD). The study combined the Logistics Service Provider (LSP) Lifecycle Model with the application of Industry 4.0 (I4.0) to improve service logistics. Case studies showed the implementation of the service logistics strategies with the feasibility solution of Industry 4.0.Sustainability 2020, 12, 2394 2 of 17 real-time information, and Circular Economy (CE) [21] are now among the basic customer requirements. Furthermore, customer behavior has changed too. Quick and immediate responses are expected. Information Technology (IT) has been increasingly used in the global business to satisfy the customer in terms of supply [22,23]. Today, Industry 4.0 is being used to accomplish the customer target, operation, and improvement in manufacturing [24,25]. Some examples of the advancement of Industry 4.0 are applying to self-learning automation, big data analytics, real-time information, Internet of Things (IoT), and smart sensors [26,27]. This improvement expands to the logistics industry in the form of, for example, on-demand delivery which offers an abrupt response to the customer [28,29]. The trend has changed rapidly around the world and the logistics service is demanded to support it. Therefore, LSPs need to innovate and create new service to address these complicated customer trends [30]. This paper demonstrates the use of the LSP Lifecycle Model to re-design the logistics service using three case-study LSPs in Thailand. It aims to address the research questions of whether the developed LSP Lifecycle Model is valid and if the Industry 4.0 concept is applicable and can be beneficial for LSPs. Firstly, the study identified the stage of the service. Secondly, services were re-designed using QFD. Thirdly, customer requirements were prioritized using the Multiple-Criteria Decision-Making (MCDM) tool. Finally, the Industry 4.0 concept was mapped to address these demands. Literature Review

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Hybrid hierarchical fuzzy group decision-making based on information axioms and BWM: Prototype design selection

Cited by 75 publications

References 66 publications

Evaluation of the Influencing Factors on Job Satisfaction Based on Combination of PLS-SEM and F-MULTIMOORA Approach

Evaluation of the Influencing Factors on Job Satisfaction Based on Combination of PLS-SEM and F-MULTIMOORA Approach

A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria

On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs

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