Financial performance ranking of automotive companies in India using TOPSIS method
13 Sep 2018-International Journal of Business Excellence (Inderscience Publishers)-Vol. 16, Iss: 2, pp 149-162
TL;DR: In this paper, the authors have examined the financial performance ranking of the automotive industry using technique for order preference by a similarity to ideal solution (TOPSIS) method and provided ranks to each alternative (automotive companies) using TOPSIS method.
Abstract: The automotive industry is the fastest growing industries in India. It contributes 7.1% of the country's gross domestic product (GDP) in Indian market by IBEF reports. This research has examined the financial performance ranking of the automotive industry using technique for order preference by a similarity to ideal solution (TOPSIS) method. The primary objective of this paper is to: 1) calculate weight value of each financial ratio; 2) provide ranks to each alternative (automotive companies) using TOPSIS method. The period for assessment of automotive industry was from 2012 to 2016 and results indicate each year's automotive performance ranking. The results showed that MRF has the highest ranking in the years 2012, 2013, 2015 and 2016 and Eicher Motors in 2014. Every year different automotive firms had the lowest ranking.
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TL;DR: This study proposes a multicriteria decision-making process using analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in the context of an electric bus in the center of Ankara, and finds that EV-2 electric buses outperformed other electric bus alternatives based on the chosen criteria.
Abstract: Multicriteria decision-making tools are widely used in complex decision-making problems. There are also numerous points of decision-making in transportation. One of these decision-making points regards clean technology vehicle determination. Clean technology vehicles, such as electric buses, have some advantages compared to other technologies like internal combustion engine vehicles. Notably, electric vehicles emit zero tailpipe emissions, thereby ensuring cleaner air for cities and making these clean technologies preferable to other technologies, especially in highly populated areas for better air quality and more livable cities. In this study, we propose a multicriteria decision-making process using analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in the context of an electric bus in the center of Ankara. Six potential electric bus alternatives were evaluated under seven specific criteria. Overall, EV-2 electric buses outperformed other electric bus alternatives based on the chosen criteria. In addition, the stability of the results obtained under different scenarios using this method was established via sensitivity analysis.
51 citations
01 Jan 2022
TL;DR: In this paper , a relatively new and efficacious multi-criteria decision-making approach named best worst method (BWM) has been applied to assess and prioritise m-banking service quality dimensions.
Abstract: The usage of mobile banking (m-banking) services is becoming ubiquitous as it is an economical means of delivering banking services. This research proposes 08 critical m-banking service quality dimensions based on systematic review of literature and discussion with expert. A relatively new and efficacious multi-criteria decision-making approach named best worst method (BWM) has been applied to assess and prioritise m-banking service quality dimensions. Results of the study exhibited “reliability and security” as the most critical determinant of m-banking service quality. Findings of the study will be fruitful for both the industry and academics. It will apprise m-banking service providers about critical service quality dimensions that require due emphasis for attaining competitive advantage.
1 citations
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TL;DR: In this paper, a composite multi-dimensional index of financial inclusion (IFI) has been built by using three broad parameters of penetration, availability and usage of banking services, which can be used to compare the performance of states/regions over same/different periods.
Abstract: Purpose
The purpose of this paper is to combine the critical parameters used to study financial inclusion into a composite index. The idea is to rank Indian states and union territories (UTs) on the basis of this index, determine change in ranks during 2011 to 2014 and identify factors affecting high/low scores on the index.
Design/methodology/approach
Data for the study were collected from secondary sources published by Reserve Bank of India (RBI) and Central Statistical Organization. Applying technique of order preference by similarity to ideal solution (TOPSIS), a composite multi-dimensional index of financial inclusion (IFI) has been built by using three broad parameters of penetration, availability and usage of banking services. Factors significantly influencing scores of states/UTs on IFI were identified using multiple regression analysis.
Findings
The value of financial inclusion for India on composite IFI has increased by 0.045 points during the study period. Share of agriculture to state gross domestic product, literacy ratio, population density, infrastructure development and farmer suicides are significant factors affecting financial inclusion.
Practical implications
The multi-dimensional IFI is a useful tool to measure financial inclusion using several parameters for various states/regions. The index can also be used to compare the performance of states/regions over same/different periods.
Originality/value
This paper is unique in its attempt to construct multi-dimensional IFI for Indian states/UTs by applying TOPSIS. It will prove useful for future researchers by combining several aspects of financial inclusion into single index.
26 citations