| Title |
Profit maximizing business model for electric vehicle industry incorporating fuzziness in the environment: Encompassing a case study from silicon valley of India |
| ID_Doc |
71525 |
| Authors |
Bhakuni, P; Das, A |
| Title |
Profit maximizing business model for electric vehicle industry incorporating fuzziness in the environment: Encompassing a case study from silicon valley of India |
| Year |
2024 |
| Published |
|
| DOI |
10.1016/j.eswa.2023.122828 |
| Abstract |
Electric vehicles (EVs) are among the most revolutionary breakthroughs by the context of decarbonization of road transport. The adoption of EVs has drawn increasing attention and is currently considered a potential route towards sustainable transportation. Businesses approaching the EV market must establish lucrative business models that overcome the adoption obstacles for EVs while assuring long-term growth. The intent of the current research exploration is to create a cutting-edge framework for EV enterprises that aims to maximize profit and save delivery time leading to high customer satisfaction. The volume discount strategy is used for profit escalation. The model presented in this paper is highly adaptable for a real-world problem as it incorporates uncertainty in the EV industry through generalized triangular neutrosophic numbers, an extension of fuzzy numbers. A modified version of the neutrosophic compromise programming approach is proposed in this paper. The results from this approach are validated using genetic algorithm. The proposed optimization -based framework is encapsulated in the form of study of a case from Bangalore city, in India. An in-depth exploration of two cases along with sensitivity analysis is carried out that helped in prioritizing some discrete customers and gave insights on which manufacturing site should be designated more focus. |
| Author Keywords |
Electric vehicle; Business model; Volume discount; Generalized triangular neutrosophic number; Neutrosophic compromise programming; Genetic algorithm |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001135189100001 |
| WoS Category |
Computer Science, Artificial Intelligence; Engineering, Electrical & Electronic; Operations Research & Management Science |
| Research Area |
Computer Science; Engineering; Operations Research & Management Science |
| PDF |
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