Customers Who Do NOT Use E-ZPass (New York)

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Anti-EZ Pass Persona

New Jersey drivers are most affected by MTA-operated cash rates. Most drivers from New Jersey are female. In New Jersey, 38.1% of the adult population has a Bachelor's degree or higher.

Helpful findings

Research strategy

In order to provide helpful findings, the research team has relied on an assumption that most people who don't use the E-ZPass system in the greater NYC area come from New Jersey. We support this assumption with the fact that the majority of the E-ZPass overcharged cash rate payers live in New Jersey. Our logic behind the assumption was that drivers from New Jersey are the most dissatisfied by E-ZPass, since they were the most affected by the 2012-2016 cash rates. Thus, we provided demographic and psychographic information surrounding people living in New Jersey (New Jersey drivers where available).

Methodology

We were not able to provide an exhaustive demographic and psychographic profile of NYC individuals who do not use the EZ pass system. First, we have scoured the E-ZPass Group website, along with various local sources such as NNY360, NYTimes, hoping to locate pre-compiled demographic and psychographic analyses surrounding New Yorkers who do not use E-ZPass. Our idea was that the authorities in charge of E-ZPass likely know this specific information and might disclose it publicly, either on their website or in local press releases. No relevant information was located, although some scattered information surrounding reasons New Yorkers don't use E-ZPass was found.

Because our search determined direct demographic information on people without E-ZPass is not available, we decided to leverage the early findings and search, particularly for demographic information surrounding tourists, underbanked individuals and those who distrust the local authorities, specifically in the New York City. To find this information, we deployed the following strategies:

1. We examined business and demographic publications and databases, including but not limited to Reuters, Data USA, Media Post. There, we had hoped to find demographic analyses of tourists that visit New York City, underbanked households in New York City and locals who distrust NYC authorities; however, no relevant information was found. The available information on these types of sources focused on irrelevant data such as the general travel or unbanked households spending information, rather than demographic insights.

2. Next, we turned to market research agencies such as Pricewaterhouse Coopers, Ipsos, McKinsey Company. These types of sources usually publish survey-based analyses. Thus, our goal was to locate reports on the topics of NYC tourist demographics, underbanked or unbanked individuals, that focus on their ages, education levels and so on. Our search has determined no relevant demographic analyses specifically focused on NYC, but rather provided more general, irrelevant information such as countries that visit US the most.

3. We have also checked for relevant case studies, in research databases such as Research Gate, Google Scholar; however, all we were able to find were general tourism industry demographics that did not focus on the city of New York.

4. Lastly, we searched local governmental entities and publications, such as NYTimes and The New York State Senate, hoping to find relevant demographic information. This way, we were able to find demographic information on tourists who visit the Times Square. Although some information regarding increase in underbanked households was available in governmental resources, no demographic information was available either regarding underbanked individuals or those who distrust local authorities, which is why this strategy also failed.

Because we were not able to find sufficient data surrounding the three groups of people who are, according to the early findings, most likely not to own E-ZPasses in New York City, we decided to make the assumption that because New Jersey E-ZPass holders have been affected by E-ZPass cash rates in NYC the most, they are likely the most dissatisfied with E-ZPass and are most likely not to own E-ZPasses. Thus, we attempted to find demographic information specifically surrounding New Jersey drivers to use this information as a proxy to create a demographic profile of a person that is most likely not to own an E-ZPass. To find this information, we applied the following strategies:

1. We searched statistical databases, such as Statista, USA Gov. There, we managed to obtain age and gender dispositions of New Jersey drivers; however, no further demographic information was available.

2. Next, we scoured case studies on sites such as Research Gate and Semantic Scholar, as well as governmental resources such as the Census Bureau. Relevant information on these types of sources focused on a broader, state-wide level, rather than specifically on drivers and there was no way to filter out information that applied to drivers in particular.

3. As a last resort, in an attempt to locate additional demographic insights surrounding New Jersey drivers, we scoured through local publications including North Jersey, NJ BIZ, NJ Advance Media; however, no demographic insights specifically regarding NJ drivers were found. Due to the lack of available demographic data specifically relating to New Jersey drivers, we provided some demographic information on the general population of New Jersey.
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