Sustainable Project Choice: Integrating Must-Be Kano and Fuzzy Logic for Optimal Project Selection
SSRN, ISSN: 1556-5068
2024
- 65Usage
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
In today's competitive global markets, organizations increasingly recognize the necessity of prioritizing projects that improve financial performance and address resource conservation, environmental protection, and community well-being. This study introduces a novel approach to enhance the Sustainable Project Selection (SPS) process, which is crucial for meeting these multidimensional demands. We present a two-stage methodology that combines the Fuzzy Kano model with a modified Fuzzy Inference System (FIS) for a comprehensive evaluation of projects across the triple bottom line: economic, environmental, and social. The first stage utilizes the Fuzzy Kano model to systematically cluster project requirements into categories, ensuring a deep understanding of the needs of customers and stakeholders. The second stage uses a modified FIS, rigorously evaluating projects against these needs. This integration improves project assessment, aligns with sustainability standards, and enhances decision-making. Applying this methodology in a case study in the automotive industry demonstrates its effectiveness in the SPS process. The results indicate improved accuracy and reliability in selecting projects, ensuring alignment with the triple-bottom-line concept of sustainability. This study contributes a unique perspective to sustainable engineering management, presenting a structured and analytical framework to help organizations make informed and strategically sustainable project selections, thus balancing financial performance with social and environmental responsibilities.
Bibliographic Details
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know