Corporate sustainability assessment through fuzzy TOPSIS

2018 ◽  
Author(s):  
Eleonora Bottani ◽  
Marta Rinaldi ◽  
Federico Solari
Keyword(s):  
Sustainability Assessment ◽  
Corporate Sustainability ◽  
Reference Value ◽  
Fuzzy Topsis ◽  
Analysis And Evaluation ◽  
Sustainability Performance ◽  
Order Preference ◽  
Pros And Cons ◽  
Topsis Approach ◽  
Corporate Level

"The aim of this paper is to propose a decisionmaking methodology that enables the analysis and evaluation of sustainability at the corporate level. The proposed methodology grounds on two tools, namely the technique for order preference by similarity to ideal solution (TOPSIS) approach and fuzzy logic. The integration of these tools offers an effective way to deal with two typical issues of sustainability assessment, i.e.: 1) the fact that the company’s performance should be frequently evaluated against qualitative key performance indicators; and 2) the fact that to be meaningful, the company’s sustainability performance needs to be compared to a reference value, e.g. a threshold or benchmark, to evaluating how the company is distant from a target. The proposed approach has been applied to a real firm, operating in the food machinery industry, for testing purpose. The main pros and cons of the approach are described."

The impact of Logistics 4.0 on corporate sustainability: a performance assessment of automated warehouse operations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Natnaree Nantee ◽  
Panitas Sureeyatanapas
Keyword(s):  
Performance Assessment ◽  
Sustainability Assessment ◽  
Corporate Sustainability ◽  
Worker Safety ◽  
Self Assessment ◽  
Content Type ◽  
Sustainability Performance ◽  
Technological Adaptation ◽  
Warehousing Systems ◽  
The Impact

PurposeThe purpose of this study is to gain a better understanding of the impacts of Logistics 4.0 initiatives (focusing on automated warehousing systems) on the economic, environmental and social dimensions of firms' sustainability performance. To achieve this objective, a new framework for the assessment of sustainable warehousing in the 4.0 era is developed.Design/methodology/approachThe framework, developed via the item-objective congruence index, Q-sort method and interviews with experts, is employed to assess performance changes through management interviews in two warehousing companies after the implementation of automation technologies.FindingsMost aspects of both companies' sustainability performance are considerably improved (e.g. productivity, accuracy, air emission, worker safety and supply chain visibility); however, the outcome for some criteria might be worsened or improved depending on each company's solutions and strategies (e.g. increasing electricity bills, maintenance costs and job losses).Practical implicationsThe findings provide insight into the effective implementation of warehousing technologies. The proposed framework is also a valid and reliable instrument for sustainability assessment for warehousing operators, which companies can utilise for self-assessment.Originality/valueThis paper contributes to establishing a body of literature that explores the previously unclarified effects of Logistics 4.0 on firms' sustainability performance. The proposed framework, which captures critical concerns of corporate sustainability and technological adaptation, is also the first of its kind for warehouse performance assessment.

scholarly journals A Conceptual Framework to Evaluate the Environmental Sustainability Performance of Mining Industrial Facilities

2020 ◽  
Vol 12 (5) ◽  
pp. 2135 ◽  
Author(s):  
Komninos Angelakoglou ◽  
Georgios Gaidajis
Keyword(s):  
Conceptual Framework ◽  
Environmental Sustainability ◽  
Sustainability Assessment ◽  
Reference Value ◽  
Threshold Values ◽  
Industrial Facilities ◽  
Sustainability Performance ◽  
Specific Assessment ◽  
Final Score

The aim of this study is to strengthen the capacity of mining industries to assess and improve their environmental sustainability performance through the introduction of a relevant framework. Specific assessment categories and respective indicators were selected according to predefined steps. Sustainability threshold values were identified for each indicator to enable the comparison of the facility’s performance with a sustainability reference value. The application of the framework results in the extraction of an Environmental Sustainability Assessment of Mining Industries Index (IESAMI). The framework was applied to evaluate a mining facility in Greece, with a view to improve its applicability in parallel. The final score of environmental sustainability for the examined facility was 3.0 points (IESAMI = 3.0 points), indicating significant room for improvement where the company should aim to further enhance its sustainability performance.

scholarly journals Fuzzy TOPSIS for Multiresponse Quality Problems in Wafer Fabrication Processes

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Chiun-Ming Liu ◽  
Mei-Yu Ji ◽  
Wen-Chieh Chuang
Keyword(s):  
Integrated Circuit ◽  
Fuzzy Topsis ◽  
Quality Characteristics ◽  
Fabrication Process ◽  
Wafer Fabrication ◽  
Uncertain Environments ◽  
Real World Data ◽  
Multiple Quality Characteristics ◽  
Order Preference ◽  
Topsis Approach

The quality characteristics in the wafer fabrication process are diverse, variable, and fuzzy in nature. How to effectively deal with multiresponse quality problems in the wafer fabrication process is a challenging task. In this study, the fuzzy technique for order preference by similarity to an ideal solution (TOPSIS), one of the fuzzy multiattribute decision-analysis (MADA) methods, is proposed to investigate the fuzzy multiresponse quality problem in integrated-circuit (IC) wafer fabrication process. The fuzzy TOPSIS is one of the effective fuzzy MADA methods for dealing with decision-making problems under uncertain environments. First, a fuzzy TOPSIS methodology is developed by considering the ambiguity between quality characteristics. Then, a detailed procedure for the developed fuzzy TOPSIS approach is presented to show how the fuzzy wafer fabrication quality problems can be solved. Real-world data is collected from an IC semiconductor company and the developed fuzzy TOPSIS approach is applied to find an optimal combination of parameters. Results of this study show that the developed approach provides a satisfactory solution to the wafer fabrication multiresponse problem. This developed approach can be also applied to other industries for investigating multiple quality characteristics problems.

scholarly journals Identifying the Strategic Priorities of the Technical Factors for the Sustainable Low Carbon Industry Based on Macroeconomic Conditions

SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110163
Author(s):  
Haiyang Shang ◽  
Fang Su ◽  
Serhat Yüksel ◽  
Hasan Dinçer
Keyword(s):  
Decision Making ◽  
Research And Development ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Low Carbon ◽  
Macroeconomic Conditions ◽  
Order Preference ◽  
Technical Factors ◽  
Topsis Approach ◽  
Economic Criteria

This study aims to find out the strategic priorities of the technical factors to have sustainable low carbon industry. For this purpose, a hybrid multi-criteria decision-making (MCDM) is proposed that contains three different stages. First, the economic criteria required for sustainable development and the technical needs of the low carbon industry are defined by making a comprehensive literature review. After that, economic criteria are weighted by using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology. Finally, technical factors are ranked with the help of the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach. Moreover, another analysis is also performed by considering fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to evaluate the consistency of the analysis results. The main motivation of this study is to define the primary technical factors to minimize carbon emission problem by proposing a hybrid MCDM model. The findings indicate that research and development for renewable sources has the greatest importance for low-carbon industry. In addition, the analysis results of fuzzy TOPSIS and fuzzy VIKOR are quite similar. This situation demonstrates the consistency and coherency of the ranking results. Hence, it is recommended that countries should mainly give importance to the research and development investments so that the costs of renewable energy problems can be minimized. This situation can attract the attentions of the companies to invest in these projects. In this way, it will be possible to use a cleaner energy in industrial production.

Mobile Wallets: Theoretical and Empirical Analysis

2020 ◽  
pp. 097215092096125
Author(s):  
Ashwarya Kapoor ◽  
Rajiv Sindwani ◽  
Manisha Goel
Keyword(s):  
Service Quality ◽  
Quality Measurement ◽  
Fuzzy Topsis ◽  
Quality Factors ◽  
Customer Base ◽  
Order Preference ◽  
Quality Dimensions ◽  
Service Quality Dimensions ◽  
Topsis Approach ◽  
Topsis Technique

Mobile wallets (m-wallet) have played a prominent role in changing our system of payment from cash to digital payment. The current study employs a systematic review of articles published on m-wallets between January 2008 and January 2020. To identify the relevant studies, research databases are searched using different keywords. Research articles published on m-wallets are selected based on particular inclusion criteria and clustered on the basis of keywords, abstract and title. To ensure a reasonable accuracy in the selection and grouping of published literature, suggestions of experts are taken into consideration. The articles on m-wallets are categorized on the basis of their themes. Eight dominant themes are identified by the authors. The findings suggest that although m-wallets have been in existence for more than a decade, there is hardly any study related to m-wallet service quality measurement. Thus, the authors propose 10 dimensions to measure the service quality of m-wallets based on the extensive review of studies on electronic services (e-services) and m-wallets. The proposed dimensions of m-wallet service quality are prioritized using the fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach. The m-wallet service quality dimensions proposed in the article will help practitioners to develop strategies for building a customer base. Moreover, the results of the fuzzy TOPSIS technique employed in this study will apprise managers about critical quality factors that need sincere attention for gaining competitive advantage and retaining customers.

scholarly journals Assessing Food Supply Chain Sustainability Based on the Framework of Fussy TOPSIS

2020 ◽  
Vol 15 (8) ◽  
pp. 132
Author(s):  
Bao’e Song
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Food Supply ◽  
Sustainability Assessment ◽  
Fuzzy Topsis ◽  
Environmental Problems ◽  
Evaluation Framework ◽  
Food Supply Chain ◽  
Sustainability Performance ◽  
Food Supply Chains

Environmental degradation has been a great concern for Chinese people.  Sustainable management serves a critical avenue to solve environmental problems and has become increasingly popular and important in theoretical and practical terms. Sustainability assessment is conducive to the shift and improvement of sustainability performance. The aim of this article is to propose an evaluation framework through constructing a comparatively comprehensive set of indicators so as to measure one of the most significant yet complex supply chains. The assessment methodology is the Fuzzy TOPSIS methodology which is utilized to ascertain the weights of indicators as well as comparison of different food supply chains. The study enables stakeholders to gain a better understanding of food supply chain sustainability as well as further inform their decisions. Scholars and practitioners in the sphere of sustainable research in China could utilize the findings of the article to take corresponding countermeasures to enhance sustainability of food supply chain so as to relieve the increasingly severe environmental problems.

scholarly journals Sustainability Assessment of Public Transport, Part I—A Multi-Criteria Assessment Method to Compare Different Bus Technologies

2021 ◽  
Vol 13 (2) ◽  
pp. 825
Author(s):  
Jonas Ammenberg ◽  
Sofia Dahlgren
Keyword(s):  
Fossil Fuels ◽  
Sustainability Assessment ◽  
Public Procurement ◽  
Assessment Method ◽  
County Level ◽  
Participatory Process ◽  
Problem Context ◽  
The Public ◽  
Sustainability Performance ◽  
Sustainability Assessments

This article departs from the perspective of Swedish regional transport authorities and focuses on the public procurement of bus transports. Many of these public organizations on the county level have the ambition to contribute to a transition involving the continued marginalization of fossil fuels and improved sustainability performance. However, there are several renewable bus technologies to choose between and it can be difficult to know what alternative (or combination) is preferable. Prior research and the authors’ experiences indicate a need for improved knowledge and supportive methods on how sustainability assessments can support public procurement processes. The purpose of this article is to develop a multi-criteria assessment (MCA) method to support assessments of public bus technologies’ sustainability. The method, which was established in an iterative and participatory process, consists of four key areas and 12 indicators. The article introduces the problem context and reviews selected prior research of relevance dealing with green or sustainable public procurement and sustainability assessments. Further on, the process and MCA method are presented and discussed based on advice for effective and efficient sustainability assessments. In the companion article (Part II), the MCA method is applied to assess several bus technologies involving biodiesel, biomethane, diesel, electricity, ethanol and natural gas.

scholarly journals Sustainability Performance Assessment Using Self-Organizing Maps (SOM) and Classification and Ensembles of Regression Trees (CART)

2021 ◽  
Vol 13 (7) ◽  
pp. 3870
Author(s):  
Mehrbakhsh Nilashi ◽  
Shahla Asadi ◽  
Rabab Ali Abumalloh ◽  
Sarminah Samad ◽  
Fahad Ghabban ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Sustainability Assessment ◽  
Regression Trees ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Sustainability Performance ◽  
Learning Techniques ◽  
Self Organizing

This study aims to develop a new approach based on machine learning techniques to assess sustainability performance. Two main dimensions of sustainability, ecological sustainability, and human sustainability, were considered in this study. A set of sustainability indicators was used, and the research method in this study was developed using cluster analysis and prediction learning techniques. A Self-Organizing Map (SOM) was applied for data clustering, while Classification and Regression Trees (CART) were applied to assess sustainability performance. The proposed method was evaluated through Sustainability Assessment by Fuzzy Evaluation (SAFE) dataset, which comprises various indicators of sustainability performance in 128 countries. Eight clusters from the data were found through the SOM clustering technique. A prediction model was found in each cluster through the CART technique. In addition, an ensemble of CART was constructed in each cluster of SOM to increase the prediction accuracy of CART. All prediction models were assessed through the adjusted coefficient of determination approach. The results demonstrated that the prediction accuracy values were high in all CART models. The results indicated that the method developed by ensembles of CART and clustering provide higher prediction accuracy than individual CART models. The main advantage of integrating the proposed method is its ability to automate decision rules from big data for prediction models. The method proposed in this study could be implemented as an effective tool for sustainability performance assessment.

scholarly journals An integrated fuzzy intuitionistic sustainability assessment framework for manufacturing supply chain: a study of UK based firms

2021 ◽  
Author(s):  
Alok Choudhary ◽  
Arijit De ◽  
Karim Ahmed ◽  
Ravi Shankar
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Mixed Method ◽  
Sustainability Assessment ◽  
Assessment Framework ◽  
Mixed Method Approach ◽  
Sustainability Performance ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Topsis ◽  
Method Approach

AbstractThe increasing importance of sustainability has put pressure on organisations to assess their supply chain sustainability performance, which requires a holistic set of key performance indicators (KPIs) related to strategic, tactical and operational decision making of firms. This paper presents a comprehensive set of KPIs for sustainable supply chain management using a mixed method approach including analysing data from the literature survey, content analysis of sustainability reports of manufacturing firms and expert interviews. A 3-level hierarchical model is developed by classifying the identified KPIs into key sustainability dimensions as well as key supply chain decision-making areas including strategic, tactical and operational. A novel multi-attribute decision-making (MADM) based sustainability assessment framework is proposed. The proposed framework integrates value focussed thinking (VFT), intuitionistic fuzzy (IF) Analytic Hierarchy Process (AHP) and IF Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The novelty of the research lies in (1) using a rigorous mixed method approach for KPIs identification and industrial validation (2) the development of a novel integrated intuitionistic sustainability assessment framework for decision making and (3) the innovative application of the proposed framework and associated methodologies in the context not explored before. The practical data on the performance ratings of various KPIs were obtained from the experts and a novel intuitionistic fuzzy TOPSIS was applied to benchmark the organisations for their sustainability performance. Furthermore, the case study shows the applicability of the proposed framework to evaluate and identify the problem areas of the organisations and yield guidance on KPIs by recognising the most significant areas requiring improvement. This research contributes to the practical implication by providing an innovative sustainability assessment framework for supply chain managers to evaluate and manage sustainability performance by making informed decisions related to KPIs.

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