Willingness to Purchase Electric Two Wheelers in Coimbatore District of Tamil Nadu
Notice bibliographique
Résumé
The low-speed category has seen negative growth in the past two quarters of 2021. The market share of the low-speed sector used to be upwards of 70 percent in all the previous years, and that has plummeted to less than 15 percent in the last quarter of October-December 2021. The low-speed electric two-wheelers are not subsidised under the FAME II programme that promotes only high-speed motorcycles depending on their battery capacity at Rs 15,000 kwh, which has made the entry-level high-speed electric two-wheelers cheaper than many of the low-speed ones. The electric two-wheeler market is classified into three divisions, low-speed, city-speed, and high-speed. While the low-speed category is dying away, the city speed segment (up to 50 km/h) is gaining popularity due to competitive price and lower replacement costs of batteries. Adoption in the high-speed sector, i.e. 70 km/h, is limited but may rise in the next several years as the battery prices come down. “We haven’t seen better days than the previous few months in the whole EV adventure. In the previous 15 years, we together sold roughly 1 million e2w, e-three wheelers, e-cars, and e-buses, and we will most likely sell the same 1 million units in only one year beginning January 22. The latest good developments in EV policy under FAME 2 are a game-changer.
 Aim: The aim of the study was to examine the willing to purchase decision of respondents about electric two wheelers.
 Methods: Primary data has been collected from 120 respondents through interview using well-structured questionnaire from Coimbatore district of Tamil Nadu. Probit analysis was used to know the clear picture about major influencing variable used as a deciding factor for purchase of electric two wheelers.
 Findings: The conclusion of this study was age, gender, monthly income, place of residence, source of information were influencing the willing to purchase decision of respondent about electric two wheelers. Electric two wheeler are protecting the global from global warming.
 Interpretation: From the study the respondents are shifting to battery based vehicles or bikes because some of respondents are concerns about environmental issue and society are stating that the COVID-19 pandemic has heightened awareness and concern about environmental issues.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».