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Analysing the Relevance of Corporate Social Responsibility Programs in Value Chain of an Organization during COVID-19 Pandemic
Published in Dinesh Kumar, Kanika Prasad, Making Complex Decisions toward Revamping Supply Chains amid COVID-19 Outbreak, 2022
Rishi Dwivedi, Smita, Ratnesh Chaturvedi, Arup Mukherjee, Amar Eron Tigga, Amanpreet Kaur, Piyush Rai
Here, the more pertinent and demanding query is not about whether to undertake those CSR programs but about investing in education and livelihood, environment, healthcare, and entrepreneurship programs to accomplish the mutually beneficial and co-dependent social, ecological, and financial goals. Hence, there is an inherent need to evaluate the various CSR programs of the selected organization. Technique for order preference by similarity to ideal solution (TOPSIS) is one of the decision-making methods which helps rank different alternatives based on various considered criteria. The motive of this tool is to first arrive at the positive ideal solution (PIS) and a negative ideal solution (NIS), and then find an option that is closest to the perfect positive solution and far from the NIS. The PIS maximizes the profit parameters and minimizes the cost criteria, whereas the NIS maximizes the cost parameters and minimizes the benefit criteria. Then, according to the closeness to the PIS, the ranking of various alternatives is carried out. Thus, this paper applies the TOPSIS model for evaluating different CSR projects of the chosen Indian organization to satisfy the diverse needs of various stakeholders of the value chain.
Introduction to Multi-Attribute Decision-Making in Business Analytics
Published in William P. Fox, Mathematical Modeling for Business Analytics, 2017
The technique for order of preference by similarity to ideal solution (TOPSIS) is a multicriteria decision analysis method, which was originally developed in a dissertation from Kansas State University (Hwang and Yoon, 1981). It has been further developed by others (Yoon, 1987; Hwang et al., 1993). TOPSIS is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution and the longest geometric distance from the negative ideal solution. It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalizing the scores for each criterion, and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion. An assumption of TOPSIS is that the criteria are monotonically increasing or decreasing. Normalization is usually required as the parameters or criteria that are often with incompatible dimensions in multicriteria problems. Compensatory methods such as TOPSIS allow trade-offs between criteria, where a poor result in one criterion can be negated by a good result in another criterion. This provides a more realistic form of modeling than noncompensatory methods, which include or exclude alternative solutions based on hard cutoffs.
Data Analysis
Published in Shyama Prasad Mukherjee, A Guide to Research Methodology, 2019
Among all MADM methods, the technique for order preference by similarity to ideal solution (TOPSIS) is quite an effective one in terms of its intuitive appeal, nice construction and computational simplicity. TOPSIS uses the intuitive principle that the selected alternative should have the shortest distance (Euclidean) from the best solution and the farthest distance from the worst solution. A solution is a point with coordinates as the attribute values/levels. In a higher the better situation (originally or after an inverse transformation of an attribute), the best solution contains the maximum attainable values of the attributes and the minimum values constitute the worst solution.
A novel approach of RSM-based TOPSIS-JAYA algorithm for optimization of ECM process parameters
Published in Journal of the Chinese Institute of Engineers, 2023
Anil Chourasiya, C. M. Krishna
Some other researchers used TOPSIS for optimization of MRR and SR in the area of un-conventional machining processes while treating the problem in multi-objective context. Santhi, Ravikumar, and Jeyapaul (2013) optimized ECM parameters by applying fuzzy set theory, desirability function analysis, and TOPSIS methodology for Ti6Al4V. They optimized MRR and SR by taking feed, voltage, and electrolyte concentration as input parameters. They used analysis of variance (ANOVA) to investigate the effect of each input parameter on MRR and SR. Khan and Maity (2016) applied TOPSIS for seven modern manufacturing processes and found that TOPSIS was straight forward, systematic, and analytical multi-criteria decision-making technique for optimization. Manivannan and Kumar (2016) applied TOPSIS for micro EDM parameters and improved the optimum level of process variables. Geethapriyan, Muthuramalingam, and Kalaichelvan (2019) applied TOPSIS method for obtaining optimum values of ECM parameters and found that MRR was greater when they used sodium chloride as electrolyte. Similarly, better surface finish and better radial cut were obtained when they used sodium nitrate as an electrolyte. Saravanan, Thanigaivelan, and Soundarrajan (2021) used sodium nitrate as electrolyte along with magnetic field strength and UV rays for electrochemical micromachining. They used Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR), TOPSIS, and gray relational analysis for optimization and found that electrolyte concentration had significant effect on output parameters.
Optimum Site Selection of Hybrid Solar Photovoltaic (PV) - Hydro Power Plants in off Grid Locations in Cameroon using the Multi-Criteria Decision Analysis (MCDA)
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2023
Chu Donatus Iweh, Guy Clarence Semassou, Roger Houèchénè Ahouansou
There are several methods of MCDM available in literature, namely: Fuzzy Analytical Hierarchy Process (FAHP), Data Envelopment Analysis (DEA) model, entropy method, TOPSIS, and Weighted Aggregated Sum Product Assessment (WASPA), Analytical Hierarchy Process (AHP) (Almeida 2019; Fatemi and Rezaei-Moghaddam 2019). TOPSIS is an acronym for Technique for Order Preference by Similarity to an Ideal Solution developed in 1989 by the scholars in (Hwang and Yoon 1981). Site selection problems mostly have several objectives; ambiguous and uneven framework that makes modeling quite challenging. Another promising ranking method is the ELECTRE (Election et Choix Traduisant la Realite) (Rey, Soriano, and Stampfli 1995) used to reconcile solutions obtained from several criteria. These methods are used by scholars to address problems of choice of site, idea, equipment, etc. The siting problem is prevalent in gas station siting, fast food outlets placement to landfills and power plants location.
An integrated assessment method for the sustainability of the opaque building envelope in residential buildings with Italian GBC-HOME certification
Published in Architectural Engineering and Design Management, 2022
Giacomo Di Ruocco, Roberta Melella, Vittorio Marino
The algorithm is configured as a compensatory aggregation method, a feature that allows the trade-off between the criteria: a poor result in one criterion can be compensated by a good result in another criterion. It is believed, therefore, the TOPSIS method is the one that comes closest to the objectives of this work, and in particular it is suitable for evaluations in the field of architectural design (Jabbarzadeh, 2018; Nesticò & Sica, 2017; Yongtao, Liyin, Craig, & Yan, 2010). The TOPSIS lends itself better as a method of comparison by virtue of the simple ‘physical’ or, better, geometric understanding of the way in which the decisional problem is approached and the possibility of visualizing the reciprocal position of the different alternatives in the space of the criteria, including also the ideal and negative-ideal solutions. Conversely, it is believed that other methods such as ELECTRE or VIKOR are more suitable, by their nature, for other scenarios, i.e. decision-making problems with few criteria and numerous alternatives.