جستجوی مقالات مرتبط با کلیدواژه "Best Worst Method (BWM)" در نشریات گروه "صنایع"

In today's world, international exchanges have become more prosperous due to trade and globalization. In this competitive environment, availability of products is as important as price, quality of materials, and construction. This issue doubles the importance of logistics in today's era. In this paper, a new hybrid multi-criteria decision-making MCDM technique for choosing third-party logistics service providers is developed. With having the necessary capacities and facilities, third-party logistics, or 3PLs, can take on logistic activities in a specialized manner so that manufacturers can focus on the important issues related to production optimization. To outsource logistics activities, evaluation, ranking, and selection of 3PLs are strategic decisions. By using the BWM, Best-Worst Method, the identified criteria were weighted to evaluate the financial and operational performance of third-party logistics companies. After that, the EDAS technique was used to rank 3PLs listed on Tehran Stock Exchange. According to the calculations made in this research, Tidewater Co was ranked first, Iran Shipping Co was ranked second, and Tuka Transport, Persian Gulf Transportation, and Rail Seyr Co was ranked third to fifth.

One of the important issues in Iran is to monitor imports and business processes as well as exchange rates. Given the government’s supportive policies for traders, how to implement these policies is challenging. An strategy to implement targeted oversight and policies is to control the actions of active traders based on their background. Data Envelopment Analysis (DEA) is one of the key tools to achieve this goal. The present research is based on Slack-Based Measure DEA Model (SBM-DEA) with an output-based approach which rates traders using real data as well as their background. In this model, 30 input indicators and six output indicators were first considered. Subsequently, given the correlation between them, the number was reduced to five input and four output indicators. After the extraction of effective input and output indicators, traders’ efficiency was measured and rated using DEA model. Then, well-respected traders would receive facilities and various supports. To evaluate the performance of the model, the traders also were ranked using the Best Worst Method (BWM and after results shows better performance of the DEA model. Another result and application is the use of reference decision-making units, who indicate traders that are expected to have good performance by the market knowledge. Recognizing these units allows policy-makers to reduce other traders’ risk by disseminating their behavior. Another important application is traders’ classifications. By knowing the traders, the policy-maker reference can make a good classification of them, which is necessary for different resource allocation or facilitating policies.

Governments use online platforms to keep track of transactions in the supply chain (SC) of subsidized foods to prevent fraud. Although regular checks of warehouses and documents were conducted, current platforms failed to resolve the issue. Blockchain technology (BT) provides governments with the ability to access transparent and real-time data to address these challenges. In this paper, we examine the key challenges influencing the implementation of a BT platform for managing subsidized food products in Iran. The barriers appear to be interconnected. We present a model that integrates the Best-Worst method (BWM) for obtaining independent weights and the Weighted Influence Non-Linear Gauge System (WINGS) using a rescaling scheme for considering the interrelatedness between the criteria. Expert opinions and literature reviews are used to identify critical factors. According to the findings, the costs of implementing and maintaining the system, as well as the regular restructuring of government rules regarding the data to be collected, are the two main challenges of implementing this new technology. Moreover, there are concerns about the cooperation with downstream entities of SC, cultural differences among partners, and their knowledge level, which may affect the complexity of downstream implementation. The results of sensitivity analysis show that WINGS gives greater weight to factors that have more impact on others. Conversely, the weight of factors that are interwoven with other factors and factors that aren't influenced by other factors is reduced as compared to the independent relative importance obtained from BWM.

The majority of sustainability assessments of the bio based industries are primarily focused on the environmental and economic aspects, while social impacts are rarely considered. While overlooking social dimension can have a serious harmful impact across supply chains. To address this issue, this study proposes a modified systemic approach for a social sustainability impact assessment of the technology treatment for converting municipal solid waste to bioenergy based on a review on the common methodologies for assessing social impacts. To show the applicability and efficiency of the proposed framework, a sample of 8 experts were used to evaluate and prioritize social sustainability criteria, using a multi-criteria decision-making method called the ‘best worst method’ (BWM). The criteria are ranked according to their average weight obtained through BWM. The results of this study help bio industry managers, decision-makers and practitioners decide where to focus their attention during the implementation stage, to increase social sustainability in their bioenergy supply chains derived waste and move towards sustainable development.

The majority of sustainability assessments of the bio based industries are primarily focused on the environmental and economic aspects, while social impacts are rarely considered. While overlooking social dimension can have a serious harmful impact across supply chains. To address this issue, this study proposes a modified systemic approach for a social sustainability impact assessment of the technology treatment for converting municipal solid waste to bioenergy based on a review on the common methodologies for assessing social impacts. To show the applicability and efficiency of the proposed framework, a sample of 8 experts were used to evaluate and prioritize social sustainability criteria, using a multi-criteria decision-making method called the ‘best worst method’ (BWM). The criteria are ranked according to their average weight obtained through BWM. The results of this study help bio industry managers, decision-makers and practitioners decide where to focus their attention during the implementation stage, to increase social sustainability in their bioenergy supply chains derived waste and move towards sustainable development.