86 research outputs found
AN INTEGRATED SWOT – FUZZY PIPRECIA MODEL FOR ANALYSIS OF COMPETITIVENESS IN ORDER TO IMPROVE LOGISTICS PERFORMANCES
On the question: how to react in a particular situation, the management of the company must have a quick answer. In the time of fast and huge changes in production, the management must know what resources are available in the company and what kind of environment it faces. To respond promptly to the requirements of the environment, the company must define a clear strategy for its business. To define a strategy, management must know the state of the company. From these reasons, in this research it was conducted SWOT analysis of specific company, and after that the elements of the SWOT matrix were ranked using fuzzy PIPRECIA method. This ranking shows on which element company should pay the most attention
Supplier evaluation and selection in fuzzy environments: a review of MADM approaches
In past years, the multi-attribute decision-making (MADM)
approaches have been extensively applied by researchers to the
supplier evaluation and selection problem. Many of these studies
were performed in an uncertain environment described by fuzzy sets.
This study provides a review of applications of MADM approaches
for evaluation and selection of suppliers in a fuzzy environment. To
this aim, a total of 339 publications were examined, including papers
in peer-reviewed journals and reputable conferences and also some
book chapters over the period of 2001 to 2016. These publications
were extracted from many online databases and classified in some
categories and subcategories according to the MADM approaches,
and then they were analysed based on the frequency of approaches,
number of citations, year of publication, country of origin and
publishing journals. The results of this study show that the AHP and
TOPSIS methods are the most popular approaches. Moreover, China
and Taiwan are the top countries in terms of number of publications
and number of citations, respectively. The top three journals with
highest number of publications were: Expert Systems with Applications,
International Journal of Production Research and The International
Journal of Advanced Manufacturing Technology
Enhancing the cosmetics industry sustainability through a renewed sustainable supplier selection model
The cosmetics industry requires a long-term sustainable strategy to balance its continuously growing trend worldwide and its resources consumption. In this view, the suppliers' selection process is gaining more attention affecting products' overall sustainability. The objective of this contribution is hence to develop and validate the Cosmetics Sustainable Supplier Selection (C-SSS) model allowing the selection of sustainable suppliers for the cosmetic industry, evaluating them in an objective and balanced manner. The model was built relying on both scientific and grey literature, by incorporating the characteristics of existing SSS models usually used separately. The C-SSS enabled to integrate the EMM approach (to reduce the subjectivity), the ANP approach (to evaluate criteria interconnections), and the TOPSIS and ELECTRE models (to create a hybrid compensation model) to support managers in objectively selecting the most sustainable suppliers. The C-SSS model was applied and validated through an industrial use case in a cosmetics Italian company
An overview of fuzzy multi-criteria decisionmaking methods in hospitality and tourism industries: bibliometrics, methodologies, applications and future directions
Stakeholders in hospitality and tourism industries are involved in
many decision-making scenarios. Multi-criteria decision-making
(MCDM) methods have been widely used in hospitality and tourism
industries. Although some articles summarised the applications of
MCDM models in hospitality and tourism industries, they ignored the
fuzziness of individual cognition in an uncertain environment. In addition,
these surveys lacked a comprehensive overview from the perspective
of bibliometrics analysis and content analysis regarding the
whole hospitality and tourism industries. To analyse the applications
of fuzzy MCDM methods in hospitality and tourism industries and
further explore future research directions, this article reviews 85
selected papers published from 1997 to 2022 regarding fuzzy MCDM
models applied in hospitality and tourism industries. Through analysing
the results of bibliometric analysis, methodologies and applications,
we found that analytic hierarchy process (AHP) and TOPSIS
methods are the most widely used MCDM methods, and tourism
evaluation, hotel evaluation and selection, tourism destination evaluation
and selection are the most attractive research issues in hospitality
and tourism industries. Finally, future research directions are
proposed from three aspects. This article provides insights for
researchers and practitioners who have interest in fuzzy MCDM models
in hospitality and tourism industries
Uncertain Multi-Criteria Optimization Problems
Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems
Strategic Logistics Outsourcing:Integrated Models for Evaluating and Selecting Logistics Service Providers (LSPs) Upstream/Downstream Supply Chain Comparison
This research aims to maximize the logistics outsourcing benefits through developing new hybrid models for evaluating and selecting Logistics Service Providers (LSPs). The growing demand for logistics outsourcing and the increase in the number and type of LSPs highlight the increasing importance of the LSP evaluation and selection process. Firms use various approaches to evaluate and select their LSP partners. Most of these approaches seem to have overlooked the strategic side of the logistics outsourcing process. Additionally, the uncertainty issue of data, the complexity of the decision and the large number of criteria involved increase the attractiveness of the Multi-Criteria Decision-Making (MCDM) approaches.
A comparative literature review was used in order to identify crucial factors and methods that are used in logistics literature in fragmented ways and therefore, to establish and design a conceptual framework and models for logistics outsourcing. First, a long list of evaluation criteria was developed. Three main dimensions were identified: logistics performance, logistics resources and logistics services. Then a conceptual framework was developed using the three main dimensions with their related factors. Based on the comparative literature review outcomes, a number of integrated models have been developed and used to achieve this aim with emphasis given to FDEMATEL, FTOPSIS and FQFD techniques. Whereas the FDEMATEL technique contributed to construct influence relationships between factors under each dimension, develop impact-relationship maps and identify dependent and independent success factors (ISFs), the FTOPSIS technique used the weighted success factors to evaluate, rank and select the best LSP in three case studies. Twenty-one ISFs have been identified to be used in the final approach. These ISFs consist of eight LKPIs, seven logistics services and six logistics resources and capabilities. All of the factors were used to evaluate and select the best LSP alternative and ISFs were used to conduct the evaluation process. Different sensitivity analysis tests are used to confirm models’ robustness. Based on the outcomes of both cases, decision makers can use independent factors alone to evaluate and select the best LSP, which simplified the logistics outsourcing process in our study. The FQFD technique was used to link the LSUs strategic objectives with logistics requirements and the ISFs to develop a new strategic logistics outsourcing approach. Finally, two case studies representing the supply chain upstream and downstream are used to demonstrate the new hybrid approach effectiveness. The comparison of both cases’ findings highlighted their differences in terms of strategic objectives, logistics requirements and ISFs
An integrated group fuzzy best-worst method and combined compromise solution with Bonferroni functions for supplier selection in reverse supply chains
Choosing the right supplier has a significant impact on the efficiency and productivity of a supply chain (SC). Different supplier selection models and approaches have been developed for reverse SCs. The lean, agile, resilient, and green (LARG) strategy is an innovative paradigm for supply chain competitiveness and sustainability. This study proposes a fuzzy-based methodology that integrates the fuzzy group best-worst method (FG-BWM) and the fuzzy combined compromise solution (FCoCoSo) method for supplier selection in reverse SCs within a LARG strategic paradigm. The FG-BWM is used to measure the importance weights of the supplier selection criteria. Subsequently, FCoCoSo is coupled with the normalized weighted geometric Bonferroni mean functions to select the most suitable supplier. The BWM is used for its simplicity and efficacy. The CoCoSo model is used for its unique ability to produce a compromise solution. The Bonferroni functions are used to capture the interrelationships among the decision attributes and eliminate the influence of extreme data. The main proposed framework aims at providing an easy-to-implement but reliable method to help manufacturers active in recycling and concerned with sustainability issues to rank and select suppliers. We present a real-world case study whose results demonstrate the applicability of the proposed integrated framework to supplier selection in reverse SCs, focusing in particular on the wood and paper industry
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