Self-efficiency Assessment of Sustainable Dynamic Network Healthcare Service System under Uncertainty: Hybrid Fuzzy DEA-MCDM method

Hasani, Aliakbar; Mokhtari, Hadi

doi:10.24200/sci.2020.54452.3758

Cited by 6 publications

(5 citation statements)

References 48 publications

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“…Step 5. Calculate the optimal value of the function: Reference Methods [100] Fuzzy DEA, dynamic network, FDEMATEL, and BWM [99] BWM, FTOPSIS [98] AHP, FVIKOR [97] MARCOS [96] Fuzzy Delphi, grey-DEMATEL [95] DEMATEL, ANP [94] PIPRECIA, CoCoSo, MABAC, and MARCOS is research Delphi, SWARA, and ARAS…”

Section: A Novel Additive Ratio Assessment (Aras) Methodmentioning

confidence: 99%

“…Twenty-five factors were considered for evaluating 5 alternatives with Best-Worst Method (BWM) and fuzzy TOPSIS. Hasani and Mokhtari [100] implemented dynamic network fuzzy DEA and MCDM methods in the healthcare service industry. Hospital reputation, patient satisfaction, service quality, and social responsibility were the factors of this research.…”

Section: Application Of Mcdm Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Critical Success Factors for Competitive Advantage in Iranian Pharmaceutical Companies: A Comprehensive MCDM Approach

Yazdi

Muneeb

Figueiredo

et al. 2021

Mathematical Problems in Engineering

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The unprecedented COVID-19 outbreak strengthened the critical manifestation of the rapid development vs. survival for pharmaceutical companies, deploying strategic conduct worldwide. This study therefore explores the endogenous relationship among pharmaceutical companies’ manufacturing strategy and their performance indicators within the ambit of creating a long-lasting competitive advantage in turbulent times. Very often, it is not possible to launch a cause-effect relationship between performance and their drivers. To achieve this end, multiple-criteria decision-making (MCDM) techniques are employed in a hybrid fashion in this study. The notion has simultaneously ranked critical success factors (CSFs) in the manufacturing strategy and performance indicators in the limelight of managerial perceptions, while controlling the inherent bias concerning the causality direction in the ambit of these two entrenched concepts. A case study on the Iranian pharmaceutical companies is piloted to demonstrate this hybrid-fashion multifarious approach. Overall, the results revealed the most pertinent CSFs that reached superior-performance echelons in the Islamic Republic of Iran.

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Section: A Novel Additive Ratio Assessment (Aras) Methodmentioning

confidence: 99%

Section: Application Of Mcdm Modelsmentioning

confidence: 99%

Critical Success Factors for Competitive Advantage in Iranian Pharmaceutical Companies: A Comprehensive MCDM Approach

Yazdi

Muneeb

Figueiredo

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Thus, a high degree of risk and complexity is associated with the health supply chain in the health system. [4] It is important to note that the healthcare supply chain includes a flow of different types of products and the involvement of various stakeholders [5]. In order to meet the needs of suppliers, the main objective of this chain is to deliver goods and services promptly.…”

Section: Introductionmentioning

confidence: 99%

How to implemented Knowledge management in supply chain management Best-Worst with D-number

2024

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There is no doubt that in this hectic world, many companies seek to implement Knowledge Management (KM) as a part of their supply chain management (SCM). However, many factors affect them in many ways. As a result of this research, we will be able to find out which of these factors influenced the implementation of knowledge management in supply chain management in healthcare facilities. In order to identify the most prominent factors in this research, the Best-Worst Method (BWM) has been applied. Due to the fact that decision makers have to deal with a vague environment, DMs have to be integrated with proper methods in order to cope with this problem. The D-number is a kind of fuzzy number that is one of these methods, one of the types of fuzzy numbers. To find and prioritize the best criterion that will impact the implementation of Knowledge Management in Supply Chain Management with the Best-Worst Method, we conducted this research. This model of decision-making attempts to eliminate the pitfall of Analytical Hierarchy Process by using a Multi-Attribute Decision-Making strategy. Using multi-criteria decisionmaking in uncertain environments, this paper reviews the literature on knowledge management applied to Supply Chain Management (SCM). These methods have not been implemented in the healthcare industry in previous studies, both theoretically and methodologically. Based on the results of the study, it should be noted that, among the 12 criteria, two of them have been eliminated with the use of the Delphi method; culture capacity is the most important criterion and should be targeted by healthcare facilities companies.

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“…DEA is valuable compared to other frontier techniques as it does not entail the predetermined weights attached to each input and output. Despite many advantages, DEA possesses two major limitations: (i) it measures the performance of entities statically, i.e., it evaluates efficiency over a particular time and ignores the inter-relationship of periods among each other that leads to misleading efficiency results, and (ii) it necessitates precisely defined input-output data; however, the data for variables like environment pollution, customer satisfaction [50], service quality, social responsibility, and hospital reputation [15], etc. is not always available in a precise form for many real applications.…”

Section: Introductionmentioning

confidence: 99%

“…Olfat et al [29] presented fuzzy dynamic DEA models to deal with trapezoidal interval type-2 fuzzy data and evaluated the system and period efficiency of 28 Iranian airports over two periods. Hasani and Mokhtari [15] developed a hybrid fuzzy DEA model to measure the system efficiency as well as period efficiencies of Iranian hospitals in a dynamic environment comprising two periods in the presence of undesirable inputs/outputs. Zhou et al [50] evaluated the system and period efficiencies of 20 suppliers over three periods in the dynamic environment with customer satisfaction (desirable output) as a triangular fuzzy number.…”

Section: Introductionmentioning

confidence: 99%

A novel dynamic data envelopment analysis approach with parabolic fuzzy data: Case study in the Indian banking sector

Kaur

Puri

2022

RAIRO-Oper. Res.

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Data envelopment analysis (DEA) is a non-parametric approach that measures the efficiency of a decision-making unit (DMU) statically and requires crisp input-output data. However, as a performance analysis tool, DEA overlooks the inter-relationship present among periods, and in many real applications, it is challenging to define the information for variables like customer satisfaction, service quality, etc. in precise form. To fix this, the present paper develops a novel parabolic fuzzy dynamic DEA (PFDDEA) approach that not only measures the system and period fuzzy efficiencies of DMUs by considering the inter-dependence among periods in the presence of undesirable resources but also handles data as parabolic fuzzy numbers (PFNs). It evaluates fuzzy efficiencies in a dynamic environment by distinguishing the role of links as inputs/outputs. In the proposed approach, system fuzzy efficiencies are estimated by solving the proposed PFDDEA models based on the α-cut approach that guarantees the shape of the membership function of the system fuzzy efficiencies obtained at different α-levels as PFNs. Further, an algorithmic approach for measuring period fuzzy efficiencies based on the concept of α-cuts and Pareto’s efficiency is developed that leads to the estimation of the shapes of their membership functions. Finally, a relationship has been derived between upper (lower) bound system efficiency and upper (lower) bound period efficiencies at each α-level. To the best of our knowledge, this is the first attempt that dynamically evaluates fuzzy efficiencies (system and period) of DMUs when the data for the inputs/outputs/links are PFNs. To validate the applicability and robustness of the proposed approach, it is applied to eleven Indian banks for two periods 2019-2020 and 2020-2021, including loss due to non-performing assets (NPAs) as an undesirable output and unused assets as a link between periods. Here, NPAs are the bad loans that cease to generate income for the banks. The findings of the study (i) depict the system and period efficiencies as PFNs, (ii) conclude that the Federal Bank (FB) is the most efficient and Punjab National Bank (PNB) is the least efficient bank in the system and all periods, and (iii) provide implications that are highly valuable for bank experts to consider the impact of NPAs and unused assets for improving underperformed banks. These findings indicate that the proposed PFDDEA approach is highly useful for ranking/benchmarking in a dynamic manner keeping in view the presence of uncertain data variables represented as PFNs.

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Self-efficiency Assessment of Sustainable Dynamic Network Healthcare Service System under Uncertainty: Hybrid Fuzzy DEA-MCDM method

Cited by 6 publications

References 48 publications

Critical Success Factors for Competitive Advantage in Iranian Pharmaceutical Companies: A Comprehensive MCDM Approach

Critical Success Factors for Competitive Advantage in Iranian Pharmaceutical Companies: A Comprehensive MCDM Approach

How to implemented Knowledge management in supply chain management Best-Worst with D-number

A novel dynamic data envelopment analysis approach with parabolic fuzzy data: Case study in the Indian banking sector

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