Sustainability Indicator Selection by a Novel Triangular Intuitionistic Fuzzy Decision-Making Approach in Highway Construction Projects

The construction industry has been criticized as being a non-sustainable industry that requires effective tools to monitor and improve its sustainability performance. The multiplicity of indicators of the three pillars of sustainability—economic, social, and environmental—complicates construction sustainability assessments for project managers. Therefore, prioritizing and selecting appropriate sustainability indicators (SIs) is essential prior to conducting a construction sustainability assessment. The main purpose of this research is to select the most appropriate set of SIs to address all three pillars of highway sustainability by a new group decision-making approach. The proposed approach accounts for risk attitudes of experts and entropy measures under a triangular intuitionistic fuzzy (TIF) environment, to handle the inherent uncertainty and vagueness that is present throughout the evaluation process. Furthermore, new separation measures and ranking scores are introduced to distinguish the preference order of SIs. Eventually, the approach is implemented in a case study of highway construction projects and the applicability of the approach is examined. To investigate the stability and validity of computational results, a sensitivity analysis is carried out and a comparison is made between the obtained ranking outcomes and the traditional decision-making methods.

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

Annals of Operations Research ◽

10.1007/s10479-019-03452-3 ◽

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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Intuitionistic Fuzzy Decision Making Based on OWA and Distance Measures

Communications in Computer and Information Science - Information Computing and Applications ◽

10.1007/978-3-642-34041-3_35 ◽

2012 ◽

pp. 243-248 ◽

Cited By ~ 1

Author(s):

Shouzhen Zeng ◽

Jiaqin Chen

Keyword(s):

Decision Making ◽

Distance Measures ◽

Fuzzy Decision Making ◽

Fuzzy Decision ◽

Intuitionistic Fuzzy

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Atanassov’s Intuitionistic Fuzzy Sets as a Promising Tool for Extended Fuzzy Decision Making Models

Fuzzy Sets and Their Extensions: Representation, Aggregation and Models - Studies in Fuzziness and Soft Computing ◽

10.1007/978-3-540-73723-0_17 ◽

2007 ◽

pp. 335-355 ◽

Cited By ~ 6

Author(s):

Eulalia Szmidt ◽

Janusz Kacprzyk

Keyword(s):

Decision Making ◽

Fuzzy Sets ◽

Intuitionistic Fuzzy Sets ◽

Fuzzy Decision Making ◽

Fuzzy Decision ◽

Intuitionistic Fuzzy ◽

Promising Tool ◽

Decision Making Models ◽

Atanassov’S Intuitionistic Fuzzy Sets

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Selection of resilient suppliers in manufacturing industries post-COVID-19: implications for economic and social sustainability in emerging economies

International Journal of Emerging Markets ◽

10.1108/ijoem-09-2021-1393 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Abhijit Majumdar ◽

Jeevaraj S ◽

Mathiyazhagan Kaliyan ◽

Rohit Agrawal

Keyword(s):

Decision Making ◽

Incomplete Information ◽

Emerging Economies ◽

Supplier Selection ◽

Fuzzy Decision Making ◽

Ideal Solution ◽

Fuzzy Decision ◽

Content Type ◽

Intuitionistic Fuzzy ◽

Selection Of

PurposeSelection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.Design/methodology/approachA group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.FindingsA closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.Originality/valueThe presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

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Novel Intuitionistic Fuzzy Decision Making Models in the Framework of Decision Field Theory

Uncertainty and Operations Research - Several Intuitionistic Fuzzy Multi-Attribute Decision Making Methods and Their Applications ◽

10.1007/978-981-15-3891-9_4 ◽

2020 ◽

pp. 63-86

Author(s):

Zhinan Hao ◽

Zeshui Xu ◽

Hua Zhao

Keyword(s):

Field Theory ◽

Decision Making ◽

Fuzzy Decision Making ◽

Fuzzy Decision ◽

Decision Field Theory ◽

Intuitionistic Fuzzy ◽

Decision Making Models

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Intuitionistic Fuzzy Decision Making Towards Efficient Team Selection in Global Software Development

10.4018/978-1-6684-3702-5.ch084 ◽

2022 ◽

pp. 1756-1775

Author(s):

Mukta Goyal ◽

Chetna Gupta

Keyword(s):

Decision Making ◽

Software Development ◽

Global Software Development ◽

Fuzzy Decision Making ◽

P Value ◽

Software Project ◽

Team Members ◽

Intuitionistic Fuzzy ◽

Team Selection ◽

Manual Selection

For successful completion of any software project, an efficient team is needed. This task becomes more challenging when the project is to be completed under global software development umbrella. The manual selection of team members based on some expert judgment may lead to inappropriate selection. In reality, there are hundreds of employees in an organization and a single expert may be biased towards any member. Thus, there is a need to adopt methods which consider multiple selection criteria with multiple expert views for making appropriate selection. This article uses an intuitionistic fuzzy approach to handle uncertainty in the expert's decision in multicriteria group decision making process and ranking among the finite team members. An intuitionistic fuzzy Muirhead Mean (IFMM) is used to aggregate the intuitionistic criteria's. To gain confidence between criteria and expert score relationship, the Annova test is performed. The results are promising with p value as small as 0.02 and one-tail t-test score equals to 0.0000002.

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