Using JOBS EV 1.0 To Estimate Employment Impacts of EV Manufacturing (Text Version)

This is a text version of the video for Using JOBS EV 1.0 To Estimate Employment Impacts of EV Manufacturing presented on Feb. 28, 2024.

AISHWARYA KRISHNAMOORTHY: Coalition network website, Clean Cities and communities, website in the next seven business days and may also be used internally. If you speak during the call or use video, you are presumed to consent to recording and use of your voice or image. And once we get the slides from our presenters, we'll also get them posted on the Toolbox website. Cass, if you could press record, please. Now, I will pass things over to Margaret Smith, Technology Manager in the US Department of Energy, Vehicle Technologies Office. Margaret is DOE's sponsor for Argonne's work on the JOBS EV tool. Go ahead, Margaret.
MARGARET SMITH: Thank you so much. Welcome, everyone, to our first webinar since Clean Cities announced our rebrand to Clean Cities and communities, a US Department of Energy partnership to advance clean transportation nationwide. We have a new name, new logo, and same great coalitions and stakeholders.
This webinar is part of DOE's Vehicle Technologies Office's ongoing efforts to educate Clean Cities and communities coalitions and stakeholders about the tools our DOE National Laboratory partners create. Today's webinar is on Argonne National Laboratories JOBS EV. A new tool in the job suite of tools. JOBS EV allows users to estimate the economic impacts associated with electric vehicle manufacturing.
As will be explained shortly, JOBS refers to a suite of related Excel-based models that allow non-economists to estimate economic impacts especially JOBS associated with deployment of new transportation fuels and technologies. Many stakeholders including state and local governments, economic development agencies, labor unions, industry associations, et cetera, are interested in employment impacts.
For this reason, the JOBS model results have been part of several state and regional analysis. Today's webinar also includes a brief discussion of investments in US EV and battery component production and supply chains funded by DOE's policy office and the Vehicle Technologies Office analysis program. And now I will hand it over to the Argonne National Laboratory team.
AISHWARYA KRISHNAMOORTHY: Thanks, Margaret. Today well– right now I'm going to introduce our presenters for today's session. Our presenters today are Yue Ke, an economist and engineer in Argonne's Energy Systems and Infrastructure Analysis Division, and Dave Gohlke, an Energy and Environmental Analyst from the same division.
Dave was recently awarded the DOE EERE Assistant Secretary's Outstanding Achievement Award for work on implementation of Inflation Reduction Act tax credits. And I'm going to switch over to our presenters presentation real quick. And let's get started. All right, Yue, take it away.
YUE KE: I mute myself. OK, I should be unmuted, yeah. Can anyone hear me?
DAVE GOHLKE: Sound good.
YUE KE: OK, cool. Always kind of nervous starting a presentation in Zoom. So thanks for sharing the slides. Awesome. So next slide. Cool. Yeah, so I'll talk about Margaret introduced the new JOBS tool that we've developed that looks at the economic impacts of manufacturing electric vehicles as well as utilization of electric vehicles at the state level or regional level or national level.
I'll briefly go over the method that we used for making this tool, how it works, the default data, and assumptions that are built into the tool. And then I'll show a quick demonstration of the tool in action to– just demo it and then I'll talk a bit about the future of this tool, and what we're doing to improve on it. And the next steps and then Dave will conclude with a presentation on company investment tracking. Next slide, please.
So as mentioned already, the JOBS models are a suite of Excel-based tools that help people understand the economic impacts of various alternative fuel infrastructure deployment and charging activities. So JOBS EV focuses on the electric vehicle manufacturing and use JOBS EVSE looks at electric vehicle charging station deployment and utilization. JOBS NG looks at natural gas, and then we also have models looking at hydrogen fueling and fuel cells and stationary storage. The URL for all of these tools are shown on the screen now. Next slide, please.
So overall, the JOBS tools and JOBS EV specifically we use a holistic approach to model economic impacts. So this includes looking at the impacts of the immediate direct activity. So for JOBS EV this is the manufacturing of vehicles, the deployment of EVSE the charging of vehicles, and eventually the end of life recycling of vehicles.
But we also look at the impact on the supply chain. So this is sort of looking at when you have a vehicle manufactured you're going to have to manufacture also the wheels and the tires. And in the case of electric vehicles, the batteries and the various other electronic components, and so we also include those types of activities when we're looking at economic impacts.
And then we go further upstream to a raw material extraction. So all the steel and aluminum and plastics, we consider those impacts on the economy as well. And then we also look at the induced economic activity. So this is sort of like thinking about how if people will work at these manufacturing facilities they get paid, and then they use their wages in the larger economy to either go on vacations, or pay rent, or child care services, et cetera. Next slide, please.
So the JOBS EV tool we've scoped it in a way that the user can define their own scenarios based on the geographic regions of interest. This can either be the national level, the census regional level, or even the individual state levels. We also have the ability to do offline analysis looking at specific clusters of counties or states.
But that's not included in the publicly available tool because there's some back end work that we would need to do for that type of analysis to take place. As far as the user-defined scenarios go, for JOBS EV, we are looking at the type of vehicles that are being produced, the number of vehicles being sold and produced annually, any sort of manufacturing from upstream down to the vehicle coming out of the dealership. We've included in these this JOBS EV model.
And then for the utilization piece, we include part of what's already in JOBS EVSE specifically the electricity generation and then induced sales. However, unlike JOBS EVSE, we don't include the station development piece. So if you wanted to get the entire ecosystem for electric vehicles, you would need to run part of JOBS EVSE and then the entirety of JOBS EV.
So if there's interest and sort of making that process a little more straightforward, we can talk and that could probably be an easy next step for this model to do. So but overall, the expenditures are translated into these similar dollar flows among industries using the Department of Commerce's RIMS2 input-output model. So we use their multipliers. And with our sort of our tools default values, we can estimate these economic impacts. Next slide, please.
Probably skip this methodology slide. OK, cool. So yeah, input-output modeling is just a fancy way of saying we're looking at the entire economy and in the US or various states where we've simplified the economy into a series of equations so that every line in the equation represents one or more industries.
And then the inputs of one industry is the input of– sorry, the output of one industry is the input of another industry and itself. And so with sort of this system of equations, we can estimate how various industries affect each other. Next slide, please. And that lets us to look at sort of the entire economy and the upstream and downstream effects.
So I mentioned sort of these supply chain jobs are a couple of times already. These are just the jobs that are directly involved in the production, shipping, and installation, construction, et cetera, as well as supplying inputs to these direct activities. The induced jobs like I mentioned before is sort of the respending of wages or incomes by the supply chain job holders.
For vehicle manufacturing, we've looked at all of the major vehicle components. We've included options for variable quantities of components. So think different drivetrains, all wheel drive, two wheel drive, et cetera, we've included some of those variable part numbers or variable quantities of parts. We also include an install clause as well as the assembly costs associated with vehicle manufacturing.
We've included shipping expenditures, we look at the– well, it's a user input but we can have some flexibility on the number of vehicles and types of vehicles sold per year. For types of vehicles, I'll talk about it a little bit later during the demo of the tool. But essentially, we're in light duty vehicle world. But we do have some variability between passenger cars, pickup trucks, and SUVs, and then the two wheel and four wheel drive variations of those.
For vehicle operation expenditures, we've looked at annual Vehicle Miles Traveled or VMT as well as the charging that would be required to have those vehicles drive that number of miles. We've included various schedules for maintenance and repair as well as including the dealership costs or the costs of having a dealership sell vehicles, rather. For local shares, this includes the production, shipping, and assembling of each motor vehicle component as well as each motor vehicle. And also we assume that dealerships are a local share cost as well. Next slide, please.
So this is a really busy slide, and I apologize that it's going to be really difficult to read. I'll talk about this more in depth during the demo of the tool. But essentially, we've covered– we were trying to capture sort of all of the vehicle utilization expenses that one could incur as a state level as well as all the component expenses that would need to be produced in order to make a vehicle.
And so we've provided default data within the tool for that since we understand it's pretty difficult to have a good grasp on how much these components cost. But like any other model, having better data input will only lead to better results. So we encourage if you know these types of expenses for your use case or your scenario then to use your data instead of relying on the default data. Next slide, please.
So unlike the previous versions of the JOBS tools, this time around we've improved some of our outputs, so they're a little more easily understood. And we added color to them because hooray, color. So this is just a sample of some of the outputs that the tool will provide. Going clockwise from the top left, pie chart is just sort of a summary of user inputs.
For now, we've shown passenger cars, but we have sort of this type of pie chart for the other vehicle types as well. And then the next bar graph looks at the employment utilization of employment, sorry. Given some– I think I just put some dummy values in for that to generate it, but you can see the amount of employment over time or within a single year. And then we can break that employment out into various sectors shown on the bar graph on the bottom. So next slide, please. So I'm going to try to share my screen if that's allowed to show the tool. And I'm also going to turn my camera off.
AISHWARYA KRISHNAMOORTHY: Yeah, I'm going to stop my share, and then share yours.
YUE KE: OK. So hopefully you can see an Excel document.
YUE KE: Awesome. So there's this copyright page that everyone ignores and you can ignore as well. The structure of the tool is going to be very similar to the previous JOBS suite tools. We've tried to be as consistent as possible. So if you're used to using JOBS EVSE for instance, it'll be pretty easy to transition to JOBS EV.
Just like JOBS EVSE, the first few sheets in this tool are primarily informational. So we've got sort of this organizational sheet that will look very similar to JOBS EVSE. We've stuck with the same color coding scheme with the cells, so it'll just be easier if you already know how those prior tools operate.
And then we've updated the default values and definitions to be focused on JOBS EV instead of having JOBS EVSE content. The initial setup for these scenarios is going to be very similar as well. First, you can select either the state or region. So we've got all 50 states plus DC as well as the US national, and then the various census regions that you can select in the dropdown.
And then the economic scenarios, you can either select to only look at vehicle manufacturing, to look at vehicle utilization and marketing, or to look at a combination of both. For now, we can select just the combination of both so you can see all the steps on the screen eventually. So kind of like JOBS EVSE this is 2.0. You can select your year that you want to start the analysis for, and the year range.
We have a maximum allowable 10 year range that's just a limitation of the input-output model. But we can update that over time as well. So I've kind of mentioned this already. We've got several types of light duty electric vehicles that we're modeling. This includes passenger cars, compact SUVs, SUVs, and pickup trucks.
We also divide between the turbo drive and four wheel drive variants primarily because there's a different number of powertrain components. As you can imagine, the all wheel drive has twice the number of certain widgets that two wheel drive vehicles have. So the way the tool works is you fill out step one. So you would select for instance passenger car, two wheel drive.
And then that would kind of tune the rest of the tool so that you can only input the passenger car related values instead of being bombarded by all of the potential BEV types that the tool does cover. So you would eventually fill out the steps one by one. And so I'm just going to click through so you can see the way the tool works.
We've added some error checking to the tool so that if you decide to accidentally or intentionally skip a step, a pop up window will appear that says that, hey, you've skipped this step, Are you sure you want to continue? And you can choose to ignore it or you can go back and edit it as necessary.
So the tool will be available or is available rather online at that URL that was in the slide previously. So feel free to download it and play with it yourself. When you're done with inputting what you want to input, you can either look at the summary of your inputs or just go to the results.
OK, cool. So I left a couple of steps blank, and now the tool is going to be mad at me. I'm just going to continue anyway and hope for the best. Since I didn't actually put in any vehicles manufactured, to no surprise there's no BEVs manufactured in the US. And so all of this is– I'm actually going to go back and put in some numbers, I apologize. Let's put in 100. Passenger car, two wheel drive, and 2023. This is just kind of a dummy variable just to generate some type of results.
OK, so here we see that there's 200 vehicles produced. This is sort of just the summary of the user inputs. So not super interesting. It's a good way to double check that you've put in the values that you want to put in. And then these are the breakdowns based on the default data. If you use your own data of course, the BEV expenditures pie charts will be different. But this just reflects the default data for now.
So we can look at the results by clicking the View Results button. It's going to take a while as it does the calculations on the back end and then it'll display various charts as well as the data tables for your own analysis. So because I've only put on one year of data, so there's going to be 100 vehicles manufactured. There's only one year of data in the outputs, or sorry, one year of results rather in the outputs. And then we can break that down into the various industries that are affected and so on and so forth.
We also include in addition to the economic impacts for employment we have economic impacts in terms of wages or earnings. And then as well as regional product or gross domestic product. So those options are present in the tool as well. I think that's the extent of the very rapid tool demo. I'd be happy to go into it if there are questions at the end about it. But I think in the interest of time we can proceed with the rest of the slide deck, if you don't mind.
Cool. So next steps. We're– next slide, please, sorry. So like I said, the two does reside online. This is just the fact sheet that was generated for a prior version of the JOBS tools. We will be updating this so that JOBS EV will also be mentioned in addition to JOBS EVSE within the AFDC website, the JOBS there's a link to our website that hosts all of the JOBS tools including the new JOBS EV 1.0, as well as the previous versions of the JOBS tools. Next slide, please.
So the immediate next steps of JOBS EV is the posting of the model tutorial and the presentation that is today's presentation, as well as additional documentation on how to use the tool where the default data came from, et cetera on the ANL JOBS website. For JOBS EV 1.1, we're planning on doing a more granular state-specific defaults for upstream manufacturing in order to better capture the local share components.
And then also we're thinking of how to better incorporate end of life for electric vehicles within our model. Looking further ahead into the future for JOBS EV 2.0, we want to include medium and heavy duty electric vehicle manufacturing utilization. As well as improving integration with JOBS EVSE so that you can just run one of these tools to get the entire sort of picture of the economic impacts of EVs in your region or your geographic area of interest. Instead of having to run half of one tool and then half of another tool and then adding the results on your own. So that's what we're looking forward to doing in the future. I think that might be the end of my slides. Yes. So I'll just turn it over to Dave to finish out.
DAVE GOHLKE: Thank you, Yue. Very interesting presentation on the modeling side of things. I'm going to shift gears just a little bit and talk a little bit more about the data side of things. So in addition to the economic modeling, we are working on understanding the landscape of investments in the United States for clean energy technologies.
And so with this, I've got a kind of a few things that are kind of right hot-off-the-presses showing some of these high-level summaries. In a sense, this data is kind of, Are these automakers or these suppliers putting their money where their mouth is? So we can look at what projections for the future of electric vehicles may be. For instance, is there going to be sufficient manufacturing capacity to satisfy those that demand for vehicles? That's one of the things that we're after here.
And so as such, we're very carefully tracking these corporate announcements for manufacturing investments. And so right here on the bottom left is a graphic from looking at EV assembly and component. And the size of each bubble here are the number of jobs at each investment. With this particular graphic, I really am narrowing down simply on things in the EV supply chain. So if a company unlike what Yue was just saying with tires and the body, for instance, those investments we are tracking them but they're not included here. This is really just looking at EV assembly or the EV powertrain here.
And I'm happy to note, actually, that this graphic in spite of saying data as of February 26, 2024, is already out of date because the afternoon of February 26 the next day we caught an announcement from a powertrain manufacturer in Ohio with another $200 million investment. And so these investments are very rapidly growing.
And what we've seen is during the Biden administration, for instance, we've seen a lot of investment. We've seen over $40 billion in committed announcements of we're going to build these manufacturing facilities. This is spread across 150 different sites, and this is electric vehicle assembly, electric vehicle components, or charger manufacturing. There's much lower economic investment on that, but there are some gray dots there that represent EVSE manufacturing.
And across all of these investments there are over 50,000 potential new jobs. People want to dive into this particular data set. They're welcome to do so. There is a version hosted at which includes EV and battery supply chains, as well as other clean energy technologies such as solar, offshore wind, heat pumps, and so on. The next slide, please.
So we're taking that data and not just trying to understand where these investments are occurring, but also, What is the big deal with it? And so one graphic here we see on the right, that battery production. So I can say you've probably read news articles that there is a lot of battery production that's been planned for the United States.
And we find that this is in similar locations to the historical production of vehicles. So communities that have active auto-manufacturing currently there's a bit of a concern of, What's going to happen with the electric vehicle transition? Well, we are seeing that the batteries at least are tending to be built in similar locations. And so we see a nice swath from Quebec down to Georgia with relatively high volumes of manufacturing of batteries. These aren't exclusively here in what's sometimes referred to as the battery belt. The bible belt is a different location that crosses that.
These are similar locations to the auto manufacturing. But we also see a large manufacturing of batteries out in the West, Nevada, California, and Arizona, cluster out there as well. These battery investments are growing very rapidly. So in terms of the total investments here, this line chart on the bottom left shows that we've had over $200 billion in announced investments throughout the battery supply chain, battery and EV supply chain since 2000.
3/4 of that has been in the last three years, and half in the last year and a half. So these investments are very rapidly growing. If you look at that line chart, you can see these abbreviations, IIJA and IRA. It's not exclusively caused by policy drivers, but the Inflation Reduction Act, IRA and the Bipartisan Infrastructure law which is formally the IIJA have really acted as catalysts for some of this manufacturing in the United States. And so the next slide, please.
And on this slide, we show what happens with all of these companies, with all of these manufacturing, What's the big deal there? There we go. And so we're tracking the material and component production to compare this with the demand. And so for instance, if I tell you there's been $100 billion in battery cell plants and tens of thousands of jobs announced, that's very important information to know for these individual communities.
But we're also looking at this holistically and saying, all right, across all of these, How much battery manufacturing is that? And we see that in North America that 1300 gigawatt hours of batteries have been announced per year of production. And that might not mean too much, but that's roughly as a quick rule of thumb probably about 10 to 15 million electric vehicles worth of batteries, as well as batteries for stationary storage and other uses.
So we're looking at this. We're also looking up the supply chain at that cathode and anode material separators, electrolytes, raw minerals. There's technical analysis on these topics to be published next month, next week, even. So we've got a report here. So I'm kind of proud to announce that hey, we've got this report coming out that people can look into this in greater detail.
And we're also going to be releasing a database along with this so that people can really look at the hundreds of investments that we've– hundreds of investment announcements that we've been tracking and look at these in greater detail. So with that, I'll kind of wrap it up, and we can get over to the questions, the final slide is a thank you slide. And thank you all for your attention.
AISHWARYA KRISHNAMOORTHY: Thank you, Dave. All right, folks, any questions, feel free to drop them in the chat or raise your hand in Zoom, and you and Dave will answer them.
DAVE GOHLKE: Yep. And there's a technical question for you, actually, Aishwarya. How can we gain access to the presentation and recording after this session?
AISHWARYA KRISHNAMOORTHY: Great question. So these slides and the recording will be available posted on the Clean Cities website. And my colleague, Cass, is also typing a response in the chat so everyone can see it. Quiet crowd today.
If there aren't any specific questions, maybe Yue, if you would like to dig a little more into the demo since you were saying if there's time you you'd be willing to walk through a couple more things.
YUE KE: Sure. Let me– just give me one minute to find that window again. I apologize. I don't use Zoom very often. So struggling to find the share my screen button.
AISHWARYA KRISHNAMOORTHY: All good. We do have a question in the chat in the meantime. Marianne asks, How do local shares affect JOBS EV results?
YUE KE: It's a good question, Marianne. The short answer is that the local shares represents the amount of as you would imagine, a local activity in the economy. And so for the tool currently we have some defined defaults for local shares. But they're very sensitive to local activities, and so our defaults aren't great. And if you have better ideas, it's better to use your data for that.
But to answer the question more directly, local shares they can swing the results significantly. If there are a lot of local shares for instance, then the geographic area of interest will have– or will reflect that in the sense that there will be large increases in estimated numbers of jobs or increases in GDP or wages.
Conversely, if the local shares percentage is relatively low, then the employment and earnings and other impacts would be also relatively low. So you can imagine, for instance, for a state like Michigan, for instance, that has a lot of manufacturing. It would have a much larger local share for EV manufacturing because they have– there's a lot of component manufacturing of businesses there as well.
And so the number of jobs for, let's say, 100 pickup trucks that are EVs manufactured in Michigan will generate more jobs in Michigan than going to the complete opposite end of the spectrum, 100 EVs manufactured in Alaska because there aren't many component manufacturers in Alaska. The local share there will be very low. And so it'll be a much smaller number of jobs reflected.
Patricia asks, What is the definition of local share? It's also a good question. The summary answer is that local share is sort of the percentage of economic activity that happens within the geographic area of interest contrasted to the overall share or the overall amount of economic activity that is both in region and out of region. I don't know if that really answers– does that answer the question, Patricia? Oh, so I have no idea how to share my screen. I can't find the button. I'm sorry.
AISHWARYA KRISHNAMOORTHY: It should be at the bottom you of your Zoom.
AISHWARYA KRISHNAMOORTHY: Platform, there's a green share screen button.
YUE KE: Great, thank you. So this is sort of the landing page again. I'm just going to stay with USA National and stay with the manufacturing utilization. You can choose the BEV types like I said. And so let's just go with passenger cars and well, Americans really like SUVs, so let's go with passenger cars and SUVs. And we can put in the number of vehicles manufactured annually. So for ease, I'm just going to put in 100 across the board.
So these are the default data that we've kind of painstakingly tracked down. We've organized them in a way that it's hopefully somewhat intuitive. The first three rows are parts that are unique to BEVs. These include the eMotor drive and transmission, the battery cell and pack, as well as any sort of power electronics.
And then the next set of rows are the other vehicle parts that are going to be common to internal combustion engines but also exist in battery electric vehicles. So this includes like wheels and tires, climate control, chassis, sort of the other parts of the vehicle that has to exist in order to have a vehicle but isn't unique to BEVs. So we've included this intentionally so that we can capture the full range of economic impacts. So it's not just battery and eMotor manufacturing, it's the entire vehicle.
And then the second set of tables within this step of the tool looks at the quantity of components. So for instance, with the passenger car that only has two wheel drive, we assume there's only going to be D1 eMotor, there's going to be four wheels and four tires, of course. And then there's passenger restraints refers to the number of seats. Our default assumption is that there's going to be five seats.
But you can see that the eMotor drive transmission numbers change for all wheel drive vehicles. This just reflects that there's an additional set of motors for the back wheels and the front wheels for those vehicles. And this has some effect on the number of jobs that would be required to support these types of vehicles being manufactured. So on the single vehicle level it's a somewhat trivial difference. But once we start thinking of like 100 or hundreds of thousands of vehicles being manufactured, suddenly the extra eMotor is something that we need to be able to take account of when we think about economic impacts.
And then we have sort of the shipping components. Or sorry, the shipping expenditures of the components because not all of these components are made at once one site. Frequently, there's sort of interstate trade going on. We capture that activity as well within our model. So we have that holistic of point of view.
And then the fourth step of this tool gets into that local share question that Marianne and Patricia had asked earlier. So this is the component share of the end region manufacturing across the various automaker brands. So the minimum amount of a local share is going to be 0%. There's no such thing as a negative local share. And then the maximum would be 100%. 100% indicates that all of the manufacturing occurs in that state, that state has or that region, rather.
And so in terms of states, it doesn't make a whole lot of sense because there's not a single state that's going to have 100% of let's say all battery cell production within the US. But if you're looking at– if your geographic unit is a country, then it could very well be that all of the vehicles that you're kind of modeling are made of components that are made in the US for various reasons. And so you can put in 100% there for the local share.
So this is just a fraction kind of representation of the economic activity that occurs in the geographic region of interest be it state, local, regional, or national. And so our defaults we've set the defaults to be 100% for national analysis. But if you have more specific data for your region or your scenario that you're looking at, then feel free to replace the 100% with some other number.
We've also included the assembly expenses because we've– well, the previous sections only look at the manufacturing of parts. And so parts do have to be assembled in order to make a vehicle. So we've included those manufacturing jobs or assembly jobs in our model as well. So that's a bit of a unique take.
A lot of the existing sort of models that look at electric vehicle impacts they don't really separate between being able to tell whether or not it's a component manufacturing assembly or a combination of the two. So here we've kind of divided that into discrete steps in case you're interested in what the difference is between the two.
From step six onwards, this sort of looking at the utilization of electric vehicles within the area of interest. We start with the number of vehicles sold, and then we move on to the utilization. Utilization is proxied by the number of miles traveled by BEVs in the region of interest as well as the number of vehicles on the road that are BEVs.
We can take that information and get at the amount of charging needed which is a utilization expense. We also look at the maintenance and repair expenses. And so we've kind of cobbled together a sample of maintenance repair cost at a sort of a very generalized level and how much it would cost for these various services.
So for instance, we've got battery replacement, tire rotation, tire replacement, et cetera. The scheduling the user can change that as they need to better reflect their local fleets. And then we've also included this BEV shipping-related expenses as well as the BEV dealership expenses. These two kind go hand in hand.
They kind of represent this idea that vehicles that may– you may have vehicles produced in one state that are sold in another state. And so that shipping activity, that's also generating economic impacts, and so we're going to capture that as well as the dealership. The dealership consists of some economic activity happening from sort of the vehicle being shipped from the factory to being sold. And so we capture that in our model as well.
And so that's why we say that the JOBS EV model is a holistic one because we're going from individual part manufacturing all the way to the buyer purchasing a vehicle from a dealership, to the utilization of that of vehicles on the road and considering how much expenses and sort of how much the impacts are– sorry, how much impacts there are from the utilization of those vehicles in terms of charging. Are there any other questions?
AISHWARYA KRISHNAMOORTHY: There's question in the chat. Michael asks, What support is available to someone who chooses to use the tool?
SPEAKER: Can they contact you directly, Yue?
MARIANNE MINTZ: Can I comment on that?
SPEAKER: Of course.
MARIANNE MINTZ: Well, basically, we get a number of questions that come to us often via email. In fact, one just came today from an EVSE manufacturer who had used the tool and was asking some questions. So yes, there is information in the– I believe it's in the overview pages, at the beginning of the tool, which provide contact information for the developers.
And they can be contacted directly and that would include Yue and myself, Marianne Mintz. And then also obviously there's information on the website. Just more general information but we would encourage people if they do have a specific question to just send us an email, and we're happy to respond.
YUE KE: Hello.
YUE KE: Hey, I'm back. Sorry. Yeah, we'll also put a tutorial on how to use the tool in a document form on our website at some point in the near future.
MARIANNE MINTZ: That reminds me, there is one already on the website for the EVSE tool. Isn't that correct, Yue?
YUE KE: That is correct.
MARIANNE MINTZ: Yeah, so there is such a YouTube video. And yeah, that's an excellent idea. We should put one up for the EV tool as well.
SPEAKER: I think the recording of this webinar will have a link to that in the tool on the landing page.
MARCY ROOD: Marianne and Yue, I just– this is Mercy Rood. I just wanted to add that if any of the Clean City directors who are on, I mean, one opportunity would be for the directors to ask for their regional manager to include Yue or Marianne to demonstrate the tool at a regional meeting or maybe a monthly call. So that's another opportunity.
AISHWARYA KRISHNAMOORTHY: All right, any other questions from the group today? Cool. All right, if there aren't any other questions, I just put back up the slide with contact info for our presenters today. Feel free to reach out if you have anything further. Otherwise, I think that we are good to end unless Yue and Dave, is there anything else you would like to present about today?
SPEAKER: Thank you.
AISHWARYA KRISHNAMOORTHY: Great. Thank you all for attending. Like I said, we'll have a recording, and the copy of the slides up on the Clean Cities and Communities Website in the next few business days. Thanks again.
YUE KE: Thank you so much, goodbye.
MARCY ROOD: Thank you, bye, bye.