Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/588504
Title: | Studies of Select Issues of Low Carbon Supply Chain Practices in Indian Business Environment |
Researcher: | Gupta, Vivek |
Guide(s): | Jayant, Arvind and Singh, Kulwant |
Keywords: | Engineering Engineering and Technology Engineering Mechanical |
University: | Sant Longowal Institute of Engineering and Technology |
Completed Date: | 2024 |
Abstract: | Eleven barriers (K1 K11) were developed based on both the literature and recommendations of business and academic experts. Those hurdles are determined by various elements, such as governmental restrictions, financial anxieties, environmental issues, and absence of knowledge, among others. Furthermore, using multi-criteria decision-making (MCDM) approaches like ISM, DEMATEL, ANP, and TOPSIS, an attempt is being made to quantify the most optimal relevant barriers. newline newlineMICMAC analysis is used to estimate the sensitivity and priority of barriers determined by driving and dependent powers. Within the current work, just one barrier is considered as an autonomous barrier which has a low impact on driving and reliance power, that barrier is a less consideration for low-carbon management (K8) . It demonstrates a low influence of driving power and a significant impact of dependent power. In the current study, only three barriers are identified in this region, which are less government support (K9) , less financial support for this system (K10) , and competitive market challenge and system uncertainty (K11) . The third sector components, titled linkage variables, demonstrate a significant impact of driving force and a significant impact of reliance power. In the current study, four barriers are identified in this sector, which are, a lack of industrial leadership and support (K2) , inadequate experience and application knowledge (K3) , random industrial system (K4) , and less technological applicability in industry (K7) . newline newlineUsing this method leads to the following conclusion: With a rating of 9.553, supplier C6 is the most significant in the case study problem. The highest positive value (R-C) for criterion C5, with a value of 2.123, indicates the most significant supplier out of all of the variables. C4 has the lowest overall (R-C) value of all, at -2.348, indicating that it has benefited from the greatest impact from other providers. newline newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/588504 |
Appears in Departments: | Department of Mechanical Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf.pdf | Attached File | 251.81 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 1.13 MB | Adobe PDF | View/Open | |
03_content.pdf.pdf | 368.02 kB | Adobe PDF | View/Open | |
04_abstract.pdf.pdf | 287.55 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf.pdf | 1.02 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf.pdf | 424.52 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf.pdf | 777.39 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf.pdf | 2.1 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf.pdf | 2.03 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf.pdf | 1.53 MB | Adobe PDF | View/Open | |
11_chapter 7.pdf.pdf | 1.64 MB | Adobe PDF | View/Open | |
12_chapter 8.pdf.pdf | 369.07 kB | Adobe PDF | View/Open | |
13_annexures.pdf.pdf | 1.68 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 417.76 kB | Adobe PDF | View/Open |
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