EV Two-Wheeler Purchase Intention in Nashik and Kolhapur: Subsidy Awareness, Charging Anxiety and UTAUT2 (SPSS + R)

Electric two-wheelers are no longer a metro novelty. Dealerships in Nashik, Kolhapur, Solapur and Chhatrapati Sambhajinagar now stock four or five e-scooter brands, and the price gap with a 110 cc petrol scooter has narrowed after central and state incentives. Yet showroom staff in tier-2 cities report the same pattern: plenty of test rides, far fewer bookings. This summer-internship project asks what actually drives, and what blocks, the intention to buy an electric two-wheeler among tier-2 buyers.

The study is carried out at a fictional multi-brand EV dealership, Godavari E-Motors, Nashik, with a branch in Kolhapur. Prospects who enquired or test-rode in the last six months are surveyed using the UTAUT2 model (performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value), extended with two context-specific constructs: subsidy awareness (PM E-DRIVE and the Maharashtra EV Policy) and charging and range anxiety.

Data from about 220 respondents is analysed in SPSS (reliability, exploratory factor analysis, regression) and in R (PLS-SEM using the seminr package). Tableau dashboards turn the findings into something the dealership can use: which objection to address first, for which buyer segment. The deliverable follows the SPPU MBA GC-13 Summer Internship Project format, with an external viva.

Abstract

This study examines the determinants of purchase intention for electric two-wheelers among prospective buyers in two tier-2 cities of Maharashtra, Nashik and Kolhapur. An extended UTAUT2 model adds subsidy awareness and charging/range anxiety to the original constructs. Primary data from about 220 showroom prospects is analysed using exploratory factor analysis and partial least squares structural equation modelling. The study identifies the strongest drivers and barriers and recommends dealership-level interventions such as subsidy explainers, home-charging audits and extended test rides.

Introduction

India's electric two-wheeler market has grown quickly since 2021, helped by FAME-II, the EMPS 2024 bridge scheme and, from October 2024, the PM E-DRIVE scheme, whose per-kWh incentive for two-wheelers was halved in its second year. Maharashtra has its own EV policy with additional benefits. Most published adoption studies, however, sample metro respondents or college students who are not in the market. Tier-2 buyers face different conditions: fewer public chargers, longer daily rides on mixed roads, older housing where a home socket is not always available, and strong word-of-mouth through family and local mechanics.

Literature gap

UTAUT2 (Venkatesh, Thong and Xu, 2012) has been applied to EV adoption in China, Europe and Indian metros. Indian studies usually measure attitude rather than intention among real prospects, rarely test whether buyers even know the subsidy amount, and treat range anxiety as a single item. No study we found compares two tier-2 cities using a sample drawn from a dealership's own enquiry register.

Proposed study

• Validate the extended UTAUT2 constructs on tier-2 prospects.
• Estimate which constructs significantly predict purchase intention.
• Test whether city and daily commute distance moderate the effect of charging anxiety.
• Convert the results into a prioritised objection-handling plan for the host.

Feasibility

• Technical: SPSS is available in the institute lab (GE-IL-11); R and Tableau Public are free.
• Operational: the host shares an enquiry register with names removed; the student surveys walk-in and test-ride prospects at both showrooms during the eight-week internship.
• Economic: printing, travel between Nashik and Kolhapur, and phone calls only.
• Ethical: informed consent, no Aadhaar, licence or phone numbers stored in the analysis file.

The host dealership converts only a small share of test rides into bookings, and its sales team cannot say which objection matters most: price, range, charging at home, resale value or the opinion of family members. Sales training is generic and borrowed from metro playbooks. At the same time, government incentives have changed several times in three years, and staff suspect that many prospects either do not know the current subsidy or believe it has ended. The dealership needs evidence, from its own prospects, on which factors drive purchase intention in a tier-2 market and which barriers it can realistically remove (for example, through a home-charging check or a subsidy explainer) rather than ones it cannot (such as public charger density). The problem for this project is therefore: to identify and quantify the determinants of electric two-wheeler purchase intention among tier-2 prospects in Nashik and Kolhapur, using an extended UTAUT2 model, and to translate them into dealership actions.

The study covers prospects who enquired about or test-rode an electric two-wheeler at the host's Nashik and Kolhapur showrooms in the previous six months, plus walk-ins during the internship. It covers high-speed (registrable) electric scooters and motorcycles, not low-speed models that need no registration. It measures intention, not actual purchase, and it does not evaluate individual brands or vehicle engineering. Findings apply to tier-2 urban Maharashtra and should not be generalised to metros or rural markets without further study.

Research design

Descriptive and causal research using a cross-sectional survey of real prospects, supported by secondary data from the Ministry of Heavy Industries (PM E-DRIVE notifications), the Maharashtra EV Policy and VAHAN registration dashboards for city-level sales trends.

Population, frame and sample

• Population: prospects in the host's enquiry register (≈ 1,600 over six months across both showrooms).
• Frame: register with serial IDs only, plus a walk-in log during the internship.
• Sample size: G*Power for multiple regression with 8 predictors, f² = 0.08, α = 0.05, power 0.90 gives about 206; the target is 220 completed responses (Nashik 130, Kolhapur 90, proportional to enquiries).
• Method: systematic sampling from the register (every 6th ID after a random start) for telephone and online responses; consecutive walk-ins at the showroom fill any shortfall, and the two sources are compared for bias.

Instrument

Seven-point Likert scales; bilingual Marathi/English form; back-translation checked by a Marathi-medium faculty member. Pilot n = 30, Cronbach's alpha ≥ 0.70 per construct.

Analysis plan

1. Descriptives and cross-tabs (city × occupation × intention level).
2. EFA in SPSS (KMO ≥ 0.60, Bartlett significant, loadings ≥ 0.50).
3. Measurement model in R seminr: composite reliability ≥ 0.70, AVE ≥ 0.50, HTMT < 0.85.
4. Structural model: bootstrapped path coefficients (5,000 resamples), R², f², Q².
5. Multi-group analysis (Nashik vs Kolhapur) and moderation by commute distance.
6. Importance-performance map to rank which constructs the dealership should act on.

Timeline (9 weeks)