Evaluating firms’ R&amp;D performance using best worst method

Salimi, Negin; Rezaei, Jafar

doi:10.1016/j.evalprogplan.2017.10.002

Cited by 214 publications

(102 citation statements)

References 54 publications

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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%

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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%

“…Criteria categorization along the triple bottom line outputs, 50 evaluating R&D performance of firms,51 evaluating the social sustainability of supply chains, 52 evaluating airports and airline services,[53][54][55] technology battles,56,57 and measuring quality of transit nodes58 and logistics performance index indicators 59 among others.…”

mentioning

confidence: 99%

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

et al. 2018

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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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“…Considering about the simplicity and the superiority of the BWM, it is extensively employed in many research fields [43][44][45][46][47]. The procedures of the BWM are introduced as below:…”

Section: The Bwmmentioning

confidence: 99%

Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory

2018

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Abstract:As useful supplements and effective support for large-scale electric power networks, micro-grid systems are the development tendency of future electric power systems. The planning performance of a micro-grid not only affects its security, reliability and economy, but also has a profound influence on the stable operation of large-scale electric power networks with the increasing penetration of micro-grids. Hence, studies related to micro-grid planning program evaluation are of great significance. This paper established a novel multi-criteria decision making (MCDM) model combining the best-worst method (BWM), the entropy weighting approach, and grey cumulative prospect theory for optimum selection of micro-grid planning programs. Firstly, an evaluation index system containing 18 sub-criteria was built from the perspectives of economy, electricity supply reliability and environmental protection. Secondly, the weights of sub-criteria were calculated integrating the subjective weights judged by the BWM and the objective weights computed by the entropy weighting method. Then, the cumulative prospect theory (CPT) combined with grey theory was employed to select the optimal micro-grid planning program. The empirical result indicates that the program with 100 kWp photovoltaic power generation unit, 200 kW wind power generation unit and 600 kWh NaS battery energy storage system is the optimal micro-grid planning program. To verify the robustness of obtained result, a sensitivity analysis related to values change of parameters under different risk preferences was conducted, and the result indicates that the selected optimal micro-grid planning program will not be influenced by various risk preferences of decision makers (DMs) and investors. The novel MCDM proposed in this paper is applicable and feasible in the micro-grid planning programs evaluation and selection.

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Evaluating firms’ R&D performance using best worst method

Cited by 214 publications

References 54 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

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

Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory

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