Quality assessment of scientific outputs using the BWM

Salimi, Negin

doi:10.1007/s11192-017-2284-3

Cited by 59 publications

(35 citation statements)

References 48 publications

(76 reference statements)

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“…Furthermore, this paper aims to expand the spectrum of applications of this particular method by applying it in a multi‐actor setting of the food‐packaging industry. The implementation of BWM has been the topic of several scientific papers with objectives of supplier selection, the evaluation of power grid enterprise, evaluating the quality of scientific outputs, evaluating R&D performance of firms, evaluating the social sustainability of supply chains, evaluating airports and airline services, technology battles, and measuring quality of transit nodes and logistics performance index indicators among others.…”

Section: Methodsmentioning

confidence: 99%

Sustainable product‐package design in a food supply chain: A multi‐criteria life cycle approach

et al. 2018

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This paper presents a multi‐criteria decision‐making approach for the selection of a sustainable product‐package design, accounting for the different actors within a food supply chain. The study extends the focus of sustainable packaging design to the collective of all supply chain actors. Decision criteria are identified via a literature review, and current product‐package alternatives are collected via interviews. With the inputs of these criteria and the alternative designs, a multi‐criteria decision‐making problem is formulated and solved using Best Worst Method (BWM). BWM finds the weights of the criteria. Using these weights, the ranking of the alternatives is found. The implementation of the analysis took place for three selected products of the Kraft Heinz Company. Data on the preferences of the supply chain members of these selected products were collected, and the optimal package designs were selected. It is shown through sensitivity analysis that modifying the weights that decision makers assign to the preferences of the supply chain members and the importance of the dimensions of sustainability have an effect on the selection of the optimal design.

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Section: Methodsmentioning

confidence: 99%

Sustainable product‐package design in a food supply chain: A multi‐criteria life cycle approach

et al. 2018

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“…In this regard, BWM makes the judgment easier, faster and more understandable for decision makers. This method has been successfully applied in different studies in various fields such as risk assessment (Torabi, Giahi, and Sahebjamnia, 2016), supplier segmentation (Rezaei, Wang, and Tavasszy, 2015), supplier selection (Rezaei et al 2016, Gupta andBarua 2017), technological innovation assessment (Gupta and Barua 2016), Ph.D. efficiency assessment (Salimi and Rezaei 2016), Quality assessment of scientific outputs (Salimi 2017), and R&D performance assessment (Salimi and Rezaei 2018). But the BWM has not been used in the science and technology policy-making and determining technology priorities before.…”

Section: P3 Calculate the Priority Number Of Technology Fields Usingmentioning

confidence: 99%

A technology portfolio optimization model considering staged financing and moratorium period under uncertainty

Shaverdi

Yaghoubi

2021

RAIRO-Oper. Res.

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Technology commercialization needs a large amount of financial resources and governments in developed and developing countries play a critical role in resource allocation to the technology commercialization, especially through “Technology Development Funds (TDFs)”. But, because of resource limitations, determining high priority technologies with higher impact on the country’s innovative performance and the optimal resource allocation to technology development is very important for science and technology policymakers. “Technology portfolio planning” has been developed and applied in this regard. Accordingly, a two-phase decision-making framework has been proposed. At the first phase, the priorities of technology fields are determined by using the best-worst method (BWM) and at the second phase, a two-stage stochastic technology portfolio planning model is developed by considering technological projects' risks and export market, as one of the important factor in the “Global Innovation Index” (GII) ranking. It also has been considered technology fields’ priorities, staged-financing, moratorium period, reinvestment strategy, and technology readiness levels (TRL) in allocating financial resources to technological projects. The main advantages of our proposed model are considering uncertainty and early signaling about underperforming technological projects. Due to the uncertain nature of the problem, our solution methodology is based on the Sample Average Approximation (SAA). In order to demonstrate the applicability of this model, a real case study and its computational results are presented.

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“…erefore, the BWM yields two comparison vectors, and then the weights of criteria can be obtained by solving a mathematical programming model [24]. e BWM has been used widely in many areas, such as water scarcity management [25], supplier evaluation and selection [26,27], quality assessment of scientific output [28], and sustainable architecture [29]. Some researchers have combined rough numbers with the BWM to handle the MCDM problems:Željko et al proposed a rough BWM-SAW model to select wagons for the internal transport [30], a rough BWM-WASPAS model to determine the location selection for roundabout construction [31], and then a rough BWM-SERVQUAL model for quality assessment of scientific conferences [32]; Pamučar et al integrated rough numbers and fuzzy sets, proposed interval-valued fuzzyrough numbers (IVFRNs) to aggregate fuzzy evaluating values of the decision group, and presented an IVFRN-based BWM to obtain the weights of criteria [33]; and then Pamučar et al proposed a BWM-WASPAS-MABAC model based on interval rough numbers to evaluate the third-party logistics provider [34].…”

Section: Introductionmentioning

confidence: 99%

Rough-Number-Based Multiple-Criteria Group Decision-Making Method by Combining the BWM and Prospect Theory

Jia

Wang

2020

Mathematical Problems in Engineering

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Multicriteria group decision-making (MCGDM) problems have been a research hotspot in recent years, and prospect theory is introduced to cope with the risk and imprecision in the process of decision-making. To guarantee the effectiveness of information aggregation and extend the feasibility of prospect theory, this paper proposes a novel decision-making approach based on rough numbers and prospect theory to solve risky and uncertain MCGDM problems. Firstly by combining rough numbers and the bestworst method (BWM), we construct a linear programming model to calculate rough criteria weights, which are defined by lower limitations and upper limitations. en for the imprecision of value function and weighting function in prospect theory, we propose a novel method with the aid of combining rough numbers and prospect theory to handle the risk in decision-making problems. Finally, a numerical example involving investment is introduced to illustrate the application and validity of the proposed method.

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Quality assessment of scientific outputs using the BWM

Cited by 59 publications

References 48 publications

Sustainable product‐package design in a food supply chain: A multi‐criteria life cycle approach

Sustainable product‐package design in a food supply chain: A multi‐criteria life cycle approach

A technology portfolio optimization model considering staged financing and moratorium period under uncertainty

Rough-Number-Based Multiple-Criteria Group Decision-Making Method by Combining the BWM and Prospect Theory

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