Problem
Purpose Statement
The purpose of this regression quantitative correlational study is to determine the relationship between the affordability of zero-emission vehicles and the cost-of-living for California residents in 2035.
Theories
Researchers published in the Journal of Industrial Economics studied the interdependence between electric vehicle (EV) adoption and charging station deployments leading to multiple equilibria. Under certain market conditions, the issue of critical mass arises and a market failing to overcome this hurdle would revert to a no-adoption outcome. According to Zhou et al. (2018), "when the EV price is sufficiently high, no-adoption is the only long-run outcome and, in this case, the market will eventually revert to no-adoption no matter where it starts." Policymakers are too ambitious with technologies at times which will result in a financial burden or strain on the California residents.
Kumar et al. (2023), "LIBs (Lithium-ion batteries) are the dominant recharging technology for batteries the next few years, but the problem with lithium-ion batteries is the cost of the materials used to make the LIB." Materials costs can be transferred from the manufactures to the consumers. Once the federal tax incentives are gone but materials costs is still to high for EV's will EV's continue to sell? Will car prices come down to reasonable prices?
Jenn and Highleyman (2022), "there are many challenges associated with the electrification of vehicles, including how they interact with the electricity grid"; furthermore, "In our highest adoption scenario of 6 million electric vehicles in California, we find that across PG&E's service territory, 443 circuits will require upgrades (nearly 20% of all circuits) and merely 88 of these feeders have planned upgrades in the future." The CA electrical grid already suffers with outages and high electrical costs. When more EV's are purchased how will the CA electrical grid support these new energy suckers? Will energy prices rise for CA residents making the CPI grow?
According to Sheldon et al. (2017) since the start of 2015 vehicle sales have not been spread evenly throughout California. "Through October of 2014, neighborhoods ranked in the top 25% by socio-economic status had purchased over 10 times more PEVs than neighborhoods in the bottom 25%, a divergence that appears to be widening over time" (Sheldon et al., 2017). Sheldon et al. (2017) confirms a household's income and housing value have a huge correlation with PEV sales.
Task
Hows do these theories help support the purpose statement and the progression of a dissertation?