00:00:00
Well, we certainly know that Amazon is dominating the retail segment right now thanks to the growth of e-commerce, but
00:00:06
what do Amazon fulfillment centers mean for local economies in those towns or townships where those facilities are
00:00:15
located? Some research done uh earlier this year by our guest Sergey Netine who is a professor of operations,
00:00:22
information, and decisions here at the Wharton School. He's also senior vice
00:00:26
dean for innovation and global initiatives. He was part of the research team looking into this and he joins us
00:00:31
right now. Sergey, great to catch up with you again. How are you, sir? >> Very good. Thank you for having me, Dan.
00:00:37
>> Thank you. I think this is an interesting topic because we all I think most of us have communities where we've
00:00:45
seen a business come in, a big business, a well-known business, and you kind of wonder it's you think, "Wow, that's got
00:00:52
to be great for the community." But you you dive into the data as to whether or not or how much it is a great
00:01:01
thing for these local communities. First, I guess give us the backstory on why this was such an important or an
00:01:08
interesting piece for you and your team to look at. >> Certainly, Dan. So uh the backstory uh
00:01:15
is that uh there are lots of studies done previously on Walmarts and uh what we know is that when Walmart comes into
00:01:23
town um lots of bad things happen. First of all, uh prices go down which kills retail
00:01:32
around Walmart and many mom and pop stores um go bankrupt and then their employees get hired by Walmart at a much
00:01:41
lower wage. And so there are several papers over the years uh some back in the '9s that shows that essentially an
00:01:49
effect of Walmart coming into town if at best it's it's zero and and probably a
00:01:55
little bit of a negative. Um then there are some studies done on uh big factories um that employ thousands of
00:02:03
people and and we know that the effect is typically positive. Um beyond that we don't really know much about big
00:02:12
facilities coming into town and what's interesting about Amazon is that it has
00:02:17
many of those facilities. There are literally hundreds and hundreds of uh warehouses which are popping up all
00:02:23
around the world in the last decade or so. um and they employ significant number of people. So that was kind of
00:02:30
you know the the academic interest in me. >> But usually and I maybe this is a little
00:02:35
bit of the policy side of it. When a company like Amazon or UPS or whoever it is or or an automaker is looking to
00:02:43
build a facility in a certain area, the local government looks to bend over backwards to try and give that company
00:02:51
tax breaks, benefits, whatever, so that it makes it more palatable for the company to come into that uh into that
00:02:58
town and and uh and put up a facility. uh that is absolutely true and uh in our case we don't know how much local
00:03:09
governments uh contributed it it's it's a very complicated formula there are
00:03:13
some tax breaks there are some you know land subsidies and so on um in certain cases we see some local news about how
00:03:21
much the government tried to attract the facility certainly [clears throat] um there was lots of publicity about Amazon
00:03:28
HQ2 when it uh when it was open in in Virginia. Uh so we see bits and pieces. Um but that's not the data that we had
00:03:37
unfortunately. >> Right. And and so in terms of what you were looking at, I guess employment is
00:03:43
part of it. Uh median income is probably part of it and and I read that probably
00:03:48
poverty looking at the poverty side of this is also included as well. Exactly. Yeah. So we looked at those three
00:03:55
variables and we looked at the county level. You know there are different levels you can look at at state probably
00:04:00
at the state level uh it's hard to see an impact because states are big and you
00:04:05
know if you go all the way down to say zip code level or um you know census block level there's not much data
00:04:12
available. So typically these kind of negotiations with the local uh government they happen at the county
00:04:18
level and and that's where we find uh a significant increase in employment and
00:04:25
we find a significant decrease in poverty and we find a significant increase in uh median household incomes.
00:04:33
is the expectation that these I guess it has to be that there's a long-term element to having a facility like this.
00:04:41
Like if Amazon's going to make an investment to put a big fulfillment center in your area, the expectation is
00:04:47
they're going to keep it there for a while. And so that level of employment is probably somewhat constant as well
00:04:54
that it's going to be there for a while. >> Absolutely. and and the numbers that we
00:04:58
find they're average over the first three years but certainly uh they continue they persist for a long time
00:05:06
period. uh I think what is the most interesting thing that we find is that there is direct employment by Amazon say
00:05:14
you open a facility you have 3,000 people say working there some are smaller some are bigger but what we find
00:05:21
is that there is a multiplier effect of about two so for every direct job that Amazon creates by employing people
00:05:28
directly uh there is there are more jobs created around this facility and as you
00:05:33
can imagine many of those jobs are probably in deliveries right so Someone has to hire these people UPS, USPS. Then
00:05:41
uh then there are companies popping up that are delivery service providers for Amazon. Then there is Amazon Flex which
00:05:48
are gig workers uh also working and delivering packages. And then of course there is retail. You have to feed people
00:05:54
who work at the warehouse for a while. There is some construction going on. Then someone has to do maintenance and
00:06:00
so on. So that's kind of an important um important uh thing to know that actually
00:06:06
more people get jobs than what directly uh is offered by Aza and so are you able
00:06:12
to tell as well not only what happens to the incomes of the workers who are there
00:06:17
obviously you know they're going to get paid for the work they're doing but that
00:06:21
that other component that outside component like is is it somewhat of a rising tide raises all boats philosophy?
00:06:28
>> Uh exactly. So the median household income is for the entire county, right?
00:06:33
And so um and and we show that this increase is about 2.3% for the entire county which of course
00:06:41
means for people who got employed directly or indirectly the increase is probably much much higher. Um but uh
00:06:48
overall when you even aggregated for a much bigger county you still observe increase in uh in median. But the the
00:06:56
poverty question of this I think is is very important. It's very interesting as
00:07:00
well that if you have these components of rising employment and an element of of rising income, you would expect that
00:07:08
there's going to be a a downside impact on the poverty level in a particular
00:07:13
area. >> Exactly. other other work that we've done at Amazon where um uh we like looked at and
00:07:23
you know I have to say that I I am I am working at Amazon one day a week and that's where the data comes from data
00:07:30
come directly from Amazon so kind of a full disclosure there we do find that a lot of people join Amazon this is as a
00:07:40
first job so they did not have a job before they did not have income before and so for them it's kind of a drastic
00:07:46
increase uh in income. Uh others join from uh fast food and and services and other kind of retail and because Amazon
00:07:57
uh has substantially higher pay than many of those places. So you know Amazon established $15 minimal pay across the
00:08:04
company uh for a while since 2018 for example. uh that also leads to this increase in uh median householding. A
00:08:14
>> and so does data like this and and maybe this is part of the process that Amazon
00:08:19
had when they started to think about these facilities, but does it impact the decisions of where they put these
00:08:26
fulfillment centers so that they can have the maximum benefit for the people in a particular area?
00:08:33
>> Um absolutely. So there is a lot of thought that goes into locating a warehouse and and there are all kinds of
00:08:41
considerations going. One is of course being close to demand. Um so essentially what we see is uh there are very few
00:08:49
kind of uh uh counties with very small population where warehouses would be located and that makes sense. There is
00:08:55
just no one there to shop around. Um another one is locatedating close to supply. So you you really want some
00:09:03
people uh to work at the warehouse and if you locate in the middle of the desert there's no one going to be there
00:09:08
to work for. Um and so we had to account for this because it's not straightforward. It's not like warehouse
00:09:15
gets selected randomly. So if you just look at the impact of Amazon warehouse, you might get into this issue that
00:09:21
warehouses allocated within patch, >> right? And it's not like they're going
00:09:25
to put a, as you kind of alluded to, they're not going to put a facility in a
00:09:29
desert and then all of a sudden the town is going to pop up around it. >> No, no, you also have to have other
00:09:36
things, you know, some roadexes and, you know, some uh because trucks are going to be going back and forth and so on. Um
00:09:43
and of course if you look at big counties um all of the big counties which which would be uh million plus in
00:09:50
population they all have Amazon warehouse because that's demand that's supply right um and so we've been
00:09:57
looking mostly at mediumsize uh counties because the way we look at this this problem we look at the county that gets
00:10:05
an Amazon warehouse and then we compare its development to a county that did not
00:10:10
get an Amazon warehouse and then we see the differences. So that's kind of a
00:10:14
methodological design. >> Anything stand out that that really grabbed you from doing this research?
00:10:21
>> Um I I think what's remarkable is how strong the the effects are and you know
00:10:27
we used several methodologies. We also used some public data uh to uh to test robustness of our results and and
00:10:36
results were very very strong. Um there was some methodological challenges like because of the COVID we had to stop our
00:10:44
timeline in 2017 because CO is kind of weird. You lots of things went differently and so we could not look at
00:10:51
the most recent years and and and frankly the the biggest impact is probably more recently because Amazon
00:10:58
increased its uh minimum wage to $15 in 2018. So I think if anything uh our results are are very kind of a
00:11:07
conservative um on the conservative side. Uh so that I think is one thing. Um and then of course the multiplier. So
00:11:14
we found that multiplier is two. So for every person that Amazon hires another job is created elsewhere in the county.
00:11:21
So that is remarkable and this kind of results in the past academics found uh for big factories. Um but nothing like
00:11:30
that has ever been observed say for Walmart or you know for other uh retail facilities.
00:11:38
Thanks very much for your time today. >> Thank you. Thank you Dan for having me.
00:11:42
Great pleasure as always. >> Yes sir. Sergey Netine who is a professor of operations information and
00:11:47
decisions here at the Wharton School.