Published May 15, 2023, 1:20 p.m. by Jerald Waisoki
When it comes to finance, there are a lot of different cultures out there. Some people believe that the corporate culture is the most important thing to focus on, while others believe that machine learning is the key to success.
No matter what your beliefs are, it's important to understand both sides of the argument before making a decision. The corporate culture can be a great thing or a terrible thing, depending on the company. If you're working for a company that values teamwork and communication, then the corporate culture can be a great thing. However, if you're working for a company that's all about greed and making as much money as possible, then the corporate culture can be a terrible thing.
Machine learning is also a very important aspect of finance. Some people believe that it's the future of finance, while others believe that it's just a fad. Either way, it's important to understand how machine learning works and how it can be used to improve your financial situation.
No matter what your beliefs are, it's important to understand both sides of the argument before making a decision. The corporate culture can be a great thing or a terrible thing, depending on the company. If you're working for a company that values teamwork and communication, then the corporate culture can be a great thing. However, if you're working for a company that's all about greed and making as much money as possible, then the corporate culture can be a terrible thing.
Machine learning is also a very important aspect of finance. Some people believe that it's the future of finance, while others believe that it's just a fad. Either way, it's important to understand how machine learning works and how it can be used to improve your financial situation.
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i
i just very much look forward to um
hearing your thoughts and feedback as i
will discuss and totally i can see uh
ray's hand so just raise hands and i can
let you ask questions so just like
michelle said um this culture is very
dear to us i guess personal experience i
was very lucky to be in a place with
great culture
so that i always think about exactly how
culture can affect corporate
uh
performance for example
so here let's motivate analysis also
just like michelle said this is in
everybody's mind so let's just motivate
that from the field so i just want to
highlight a number of ceos quotes
regarding culture so like
uh
so this is a formal ceo from ibm the
gastoner he talked about culture it's
the only game it's the only game and
also co-founder and ceo of costco that's
also this is the only thing so clearly
culture or organization culture or
corporate culture is very important
to
the to the corporate decision maker at
the very top including the ceos and also
the founders
what is also relevant to us is that
this is a quote from another co-founder
also navidia they talk about
uh
culture has to come from the top from
the tones and actions of its leaders
that's exactly where we're going to
measure corporate culture
did i already have a chat
oh no
so what is corporate culture it's
something it's a part of the grand
scheme of things the so-called
intangible so it's really you leave and
bracing it but might be just very hard
to capture so from ovhr
from management scholars culture is
defined as shared values and norms that
define appropriate attitude and behavior
for organizational members think you are
in a business school you're in a
corporation that's the shared values and
the norms within that particular
organization
moreover both management scholars and
also finance scholars have
come to the conclusion that corporate
culture is not static
it's dynamic but it's it's evolving
slowly evolving over time so it it you
can call that past dependent culture
comes from where it originally started
and culture can also be shaped by major
corporate events a event that is very
dear to michelle is going public no
doubt going public can change a
company's
culture so as a major uh deal making
like mnas
so does corporate culture matter from
the ceos yes
so but unfortunately we just do not have
a lot of large
large sample evidence about cultural
matters
so from management scholar from the
theory perspective uh
management scholars argue that culture
matters because in employees face
choices without guidance without right
incentive scheme um culture could
properly regulate uh employees so later
i'll talk about during covey how culture
matters so that's exactly um
in the second half of this presentation
of presenting empirical evidence that
firms with a strong culture now
surprisingly just like firms engage in
esg and the like that they are
they outperform their peers so later
i'll talk more about that
so what motivate this work is really
just because everybody thinks culture is
so important like empirical evidence
mainly from questionnaires and the
surveys
so that
there's really not that simple evidence
because it's just so everybody feels
about it but just so hard to measure it
so what is the methodological innovation
of this paper is to use machine learning
techniques i'm i read michelle's paper
as well so we all got on that bandwagon
of machine learning so we're using word
embedding model
so that's a technique and i'll talk more
about that and the corpus we use so
places we try to capture corporate
culture is what ceos are saying during
earnings costs to matter corporate
culture
so for some of us who have done research
familiar with earnings calls it
typically involved top executives so
primary ceos cfo ceos and and the like
that they speak to analysts and review
so many talk about what they have done
to justify their performance and provide
guidance for future but in between
what this we are talking about it will
reveal the set of values that are
important to a company remember the uh
jensen once called from the video the
culture and culture is really come from
the top
but then how do we how do we get started
we start from
uh another prior work of us uh before us
that's fuso ital
they look at s p 500 firms so the
largest companies in the us look at
their website and look at so at a
particular point so early to uh 2012
also they look at what values those most
successful firms promote on their
website
and they came up with non-values and we
just going to use the top five
most mentioned values among the largest
companies in the us
so given that we introduce a new method
so it's important oh damn just moment
so how do i let attendees speak done
okay
more
can can you talk how do i make
uh dan can you talk now
um
yes can you hear me
uh hi
i want to uh
i wonder how to distinguish between uh
culture and employees bargaining
position like in your uh korean writing
case maybe in these firms the
employees are have a small part are more
powerful so they can ask the company to
provide more for them
which is different from culture that's
no that's a great one i think that part
you most likely you will great question
that most likely will get it from
glassdoor when employees really have a
free space to speak you remember
the places i'm measuring culture is not
even from 10k it's from q and a's so q
and a's are where ceos answer questions
from analysts it's just highly unlikely
uh analysis might ask yes she related
approach but it's just not going to be
the major one if you have seen enough
um
earnings called transcripts i think it's
going to be gaining more attraction
going forward but at least in our
setting
um that's not going to be a dominant
effect remember what i'm also going to
cover is because this is a new method
and also it's a new place to score
culture try to be convincing we need to
do a lot of validation
okay thank you yeah
but what you said correlated with
respect and teamwork and integrity it's
they are correlated a lot of the
positive attributes are firm yeah
so that's what we're going to do so we
start with somebody else has done uh
like and also very credible which is sp
500 firms what values they promote et
cetera we're just going to extend that
in in mass you know like large sample
over time we can build a panel data by
the way so the data we have is a little
uh it's available upon request
so here we are so also
related to dan's question right if we
start if we start like uh without some
deviation of what we have in mind we
might end up into not capturing culture
but something else so here is a total
transparency so this is a cut paste from
gilso it how jfe paper so remember so
these are the top five values they
identified from sp 500 firms so how do
you rate those five points so the first
one is like so that's what we're going
to capture the five values so integrity
teamwork innovation respect and quality
but what they also did uh something in
machine learning we call that a seed
word they actually did manually is to
look at um
about the integrity what are other words
companies also come frequently use to
support their claim about they care
about the integrity so the words after
integrity we call that with those seed
words so like teamwork really
straightforward there's only two
supporting o explanation for what they
make they mean teamwork it's
collaboration and cooperation so there's
only two seed words for that
what i also highlighting in yellow is
actually the words that show up on sp
500 the website they actually do not
show up that often
in earnings call or they show up in
earnings call for very different meaning
has nothing to do with integrity but
something else for example so those
yellow highlights we will exclude
ownership during earnings cost ownership
is really just about the share our
shareholder base has nothing to do with
integrity so we drop that to reduce some
noise
uh in our measure
so what is the wording vending model uh
so this project uh we started this
project almost four years ago so i think
now many people are doing what embedding
just in case uh for information so what
is the word embedding is just uh based
on a very uh
well established concept in linguistic
that is words of similar meaning of
means synonym tend to happen adjacent to
each other in a document so positive
words tend to cluster around each other
in a in a document and vice versa
negative words
so what we do in uh in large scale is to
use
the entire coppers which is earnings
calls
to develop what we we call the culture
dictionary so the key words that define
the values such as integrity or the
keywords that define the values such as
teamwork
so what inviting is allow us
to find those synonyms by vector
vectorizing
each word into a vector like 300 by one
vector and those vectors just capture
the frequency of the neighboring words
and those neighboring words essentially
explain the key word but once we
vectorize each word by a vector we can
do a vector representation and to find
the cosine similarity and we can extend
and through that
cosine similarity we can expand to
to build our own so like basically
create our own dictionary
of similar words of similar meanings
synonyms so that's what we do
that is uh we think integrity is
important but to score by the ibm has
high integrity which i need to develop
the dictionary that all the words that
relate to integrity and ibm use those
words a lot let me define that uh let me
come to the conclusion that ibm has high
integrity of course they're always us
concerned about the claimed value versus
what's actually going on so validation
becomes very important
so here just shows like a poor example
that there are three words assuming
you're not using a dictionary assuming
you have no knowledge of those three
words so suppose there are three words
called collective partnership and
governance we want to find out
how similar they are in meaning so what
we do is to go to a body of text to look
at the neighboring words around those
three words
and uh to then we get then we get a
vector representation for the three
words then we do cosine similarity to
define uh
uh to identify synonyms so here we are
so suppose the objective is to
understand the relation between these
three words so our ultimate goal is to
get a
dictionary of words say for integrity so
here assuming a toy example we want to
find the meaning how related the three
words are so we go to a body of text we
find it for collective uh the
neighboring words counts so horizontally
the first row so neighboring words
counter is like shear fruitful joint
oversight proper
and therefore partnership governance we
get all those counts so once we have the
three vectors we can do uh for e for the
meaning of each word based on the
frequency of the neighboring words we
can do a cosine similarity then we
realize
collective and partnership their
cosine similarity is higher than
collective and governance so that
suggests that collective is a closer
synonym for governance and partnership
so that's just a toy example
in reality world inviting is pretty well
established in computer science to
implement
so and it's so versatile that previously
people just use unigram like one word if
you do word inviting carefully you
actually can capture
phrases and idioms that really define a
particular
value so for example here
for innovation in our
you know our own dictionary words for to
define innovation capture innovation
when manager talk about say pushing the
envelope we know that is highly
correlated about their intent that the
firm is innovative
so like teamwork uh so there's a hundred
so like idioms could also be captured
through word embedding
so here for sanity test so first of all
to see just like the question before do
we capture what we intend to capture or
we just capture noise so here just
showing you under so remember our goal
is to score a company in five dimensions
say ibm is ibm innovative or is ibm high
on teamwork so here just showing you in
other so this is just like the culture
dictionary and we show you the top 30
words that define each value so for
innovation the top one is creativity the
innovative innova innovate etc
so that's just like to show what we are
doing
then in order to score a culture
given that earnings costs are frequently
done at quarterly frequency so each firm
will have multiple earnings calls so
we're just going to take a annual
frequency count of the frequency those
words i show you in the previous slide
for each firm year and just in case
there are any noise or volatility in
earnings called discussion of ultimate
measure is based on a three-year moving
average uh for
four particular firms a annual
copy corporate value score
so just uh like
so think about where we are today we are
in a knowledge economy so innovation
quality human capital intangible are the
passwords in everybody's mind so not
surprisingly so this just shows the
scope of our data which is
firm and the year so it's so from 01 to
2018 at roughly 2018. so here just shows
the raw scores for the sample so
a high level summary is that
innovation is the most frequently
mentioned the value
while this is again is during earnings
cost so integrity is at least the
frequent dimension the cultural value so
that's just like a first impression then
we also just like my response a moment
ago you can imagine because this is all
corporate values they are our virtues so
now surprisingly they will be positively
correlated that's indeed the case
and
innovation and the quality has the
highest correlation close to 0.5
while innovation and the integrity is
the lowest about point one so these are
some summary stats uh like just to help
you understand exactly like getting some
understanding what we are doing but
could
like whether it's consistent with
intuition for us this is consistent with
our tuition is that quality and
innovation would also go hand in hand
what is we also want to show is uh for
some of you you're doing cultural
research on national culture we know
that
national culture also slowly evolving so
here in a very dynamistic economy like
u.s we want to show that culture
so firms corporate culture evolve over
time as i mentioned before shaped by
going public shaped by mnas and also
firms could excel in multiple dimensions
of culture so this is just like an
overview of what i i'm saying so our
sample is like 21 years what we did is
divided 21 years into three
seven year period
and then so this shows among top
five top um sp 500 firms
um what are the firms that score high
along those dimensions uh so
so across industry and also over time so
i'm highlighting a number of them so the
blue box shows procter gamble so we know
that is consumer goods uh conglomerate
they excel in innovation across all
three periods of uh the sample period
and this so they basically always top
10 firms along innovation
in uh yellow box i saw i saw salesforce
so a company like salesforce could also
excel in multiple dimensions of
their values so that's innovation and
the quality yeah so this just shows that
a firm can outperform their peers
consistently but there's also changes
over time for firms to be in and out of
the top performing list in terms of
culture and firm council can excel in
multiple dimensions
what's really also revealing for us is
we also sort
provide a time series plot across 12
industries and in the we are still in
the in the public health crisis so this
shows that for health care industry
among
pharma french 12 industries they really
stand out in terms of integrity and also
teamwork
to us this is consistent with our
intuition people in that in that
particular industry these are the really
important attributes for success and
also important for us as customers to
that industry
so
i had the first question before that
from then that
how do i know i'm measuring what i
intend to measure and this is a very
valid concern that is we all know
there's a in finance we know there's a
window dressing so there's always
concern that what they say especially
management is not what they practice
so
we're going to address that concern in
multiple dimensions
so the very first thing is to validate
our measure using some well established
markers for best practice a simple
example is innovation there's so much
work have done in innovation there's so
many different matters for corporate
strengths in innovation including their
number of patents citations expenditure
as well as
scoring of a firm's r d strength like
used to be called kld
so that's like one place we're going to
uh
to look into is cross-validate look at
the known markers for innovation and to
see all those known markers are the
highly correlated with our score for
corporate culture innovation
so the other thing that we're going to
do is uh the other thing we're going to
do is we know that earnings call could
be just a show but the earnings call has
two components one is presentation so
prepared remarks
where gaming or claim or otherwise
advertising a particular value is more
likely but
well q and a is like just spontaneity
it's hard but as again earnings call is
really for firm to justify what they
have done and what they will be doing
earnings call venue is really not a
place for firm to promote culture uh so
all provided promote their virtues so
that's also another reassuring factor in
our analysis
so here just showing you a bit of our
validation of apologies for this really
not great uh size the font so here like
for quality so left hand side so the
variable quality is our score the
product quality safety
from kld top brand from a marketing
company so we see consistent correlation
across two out of three matters
then for respect again we rely um a kld
for diversity but also from the ranking
of best employers and to get a
validation
and what i also want highlighting
okay because i changed the font
so uh innovation so innovation we really
want to highlight is that our measure is
so comprehensive it capture corporate
innovation beyond the europe matters
like patents aren't spending
uh innovation strength is from kld so
for some of us who do research
innovation they know that there's severe
missing data problem for r d expenditure
like 40 of firms has missing information
on that and for patents maybe like
majority of the firms do not have any
patents so in our case our innovation
measure is based on any firm who holds
earnings cost so we have far more
comprehensive measure for that
oh great
so
yes uh just a moment
hi kai it's michelle um can you hear me
yes ah perfect very well i was wondering
just out of curiosity have you looked at
whether your measures predict what would
happen in the future so i could imagine
a firm talking about innovation
if they wanted to start becoming more
innovative or talking more about
integrity if they were
like worried that oh you know some
analysts it's you know expressed doubt
we need to
beef up on this measure it could be a
signal of things to come
that's a great question we didn't look
at that because we were so worried just
to like try to be convincing i'm not
totally convinced but no no no but there
are there are issues michelle you asked
that's a great one that is um so they're
always concerned about aspiration versus
what they do so culture to be honest
there is aspirational component
right like we all know that like our
school aspire to do so and they put on
that that's our values right exactly but
it might be that you could use this to
your benefit as well right because as
you highlighted in the beginning culture
is dynamic it does it's not just static
over time so if you could use your
measure
perhaps you know with the word bundling
approach you know what other words occur
around it you might be able to capture
some of those dynamic aspects in ways
that would be really cool
yes yes duly noted uh we didn't do that
but so also it's very hard is you know
that what what you just suggest is
predictive that's great but still i mean
beyond corporate finance is uh
industriality is all over the place so
right so the analysis in this particular
project is just established association
but you're right yeah no i totally
understand yeah
yeah so some of the analysis later will
show a little bit of predictive but
that's a corporate event which means
culture congruency
associated with deal uh incidents
but that's just events i like uh instead
what you have in mind but what you just
said it's also a little bit tricky
because of data that is my innovation
measure uh is any firm has earned its
call i would have like six i have eight
to nine thousand unique firms but in
reality innovation especially like
pattern producing corporations only like
the largest ones
so for the smaller ones we might still
not and also you know that's also i just
claimed our measure is a broader than
the euro matrix which um narrow and
rewarding largest firms so if you had
better data on innovation or analysis
doing more surveys etc maybe there will
be even close a tighter connection as
you have suggested yeah
yeah anyway it's interesting thanks
thank you no so you see we we do have
trouble like integrity as well how do
you like validate the integrity so we
just have to be quite creative to use
like
like the the opposite side like firm has
a track record of receiving the all back
dating yeah
yeah
now that makes sense
so um
so that was just like cross-validation
but like what we also do is we are not
the first one at the same time people
also other people thinking to matter
corporate culture so what we want to do
is to make sure our measure is
relatively clean um is to
entertain alternative ways or mandarin
culture the very first one which is very
easy for us our main measure is based on
q and a because spontaneity less likely
to be window dressing so the alternative
measure is to use the full cup which
including prepared
remarks which is the so-called
presentation part
second is why go out why uh like
go
uh take a machine learning route if that
gilso is how in their gfe paper already
listed
uh the values and also the seed words so
another
alternative approach is just do a simple
count of the words uncovered by kyuso
ital and see how they perform relative
to us using machine learning approach
third is that uh earnings call um
earnings call is to analyst so firm also
has other
dissemination channel michelle also used
that in her work like uh prospectors
annual reports so annual reports so why
not just look at annual reports where
managers has a management discussion
analysis that's commonly used
in accounting research so we could also
score culture just using a partic
particular section section 7 of 10k
um so here oh so this is just showing
you uh so we run a horse race so just
give you an example because we have five
measures we just use one here that is
innovation so there are four different
measures of innovation so this one is
from us the rest alternative approach we
look at the strength of correlation of
our measure versus
uh
the alternatives this uh in relation to
the common markers for innovation so
that's like number pattern spending and
innovation strength from kld so you see
that
culture mattered elsewhere uh they they
actually showed up negative correlated
with the common markers of innovation
but that's also who knows like maybe
people can also argue patterns aren't
expanding not the full picture of
innovation so that's that's aside that's
not our concern uh here
so the other we also in addition to use
different method different corpus
like textual data we also do
um
like the question before uh there are
more data now is from what so right so
earnings call is what top people saying
about their values how about the rank
and file employees at the bottom say
about their firm of course bearing in
mind the glass door is the prerequisite
for glassdoor is you have to some
typically are people looking for jobs so
there might be some negative influence
there but for us when we started four
years ago i do not know today
glassdoor's coverage is relatively
patchy as compared to earnings call
which started in early 2000 due to
regulation fd
so that and for textual analysis we need
a lot of data so that so-called story is
a little bit out for us
lastly we what we did our method is
create our own culture dictionary by
using word embedding to find the synonym
another very uninformed but also
powerful uh textual analysis um is
actually uh topic modeling so just you
only uh
you only need to tell like say say
earnings call you only need to say
uh i pre-specified there's going to be
30 or 50 topics uh in earnings just give
that and
and you get the output about topics so
here we tried from
20 to 200 topics we have that in the
internet appendix you just look at the
word cloud which give you a rough idea
about what the key
uh things uh in earnings calls for us is
mostly about performance really not uh
so if you do a very
non-supervised machine learning with our
approach is semi-supervised you do not
get what you want to capture which is
culture
but that's also a good thing it means
unintended consequence of earnings for
us because we have some guidance we are
able to capture culture it's unintended
managers are really not with the full
purpose to promote certain values so
that help us to some extent
so the application we did
is to you look at the mnas so there's so
much work done in mnas about sources of
synergies and the drivers of m a's the
one area we want to look at is called
culture feed so we want to look at
acquire a target firm among those five
cultural dimensions are they close or
they are further apart so you can have a
story of substitution or complementarity
uh that's the same same like in real
life about finding a partner like do
people have similar or opposite the
personality would be better or a good
better or worse fit but anyway what we
find is actually really cultural
congruency
that is firms uh closer in cultural
value are more likely to get together
what's also interesting for us and also
one of the themes from this research is
uh
corporate culture is evolving over time
shaped by major corporate events so
going public definitely a classical
example is goldman goldman's going
public so there are a lot of discussion
about their culture change
so here we also find something from
human us like
anthropology social and uh
uh
yeah sociology and anthropology this
concept called acculturation that is
when two tribes get together the
combined tribe actually reflect uh
capture characteristics of those two
emerging tribes so we call that a
culture region
so how do we uncover that is so so say
ibm acquired red hat is very recent but
just as example so what we show is that
one to three years down the road look at
the surviving form ibm their ceos
talking about their culture so what we
find is that combined firm the surviving
firm one year to three years down the
road very strikingly that there are
always traces of the target uh cultural
values correlated with the subsequent
surviving firms a culture so that's what
we call that culture is shaped by amino
ace in in fact ibm's culture down the
road will also be shaped by the
entrepreneurial characteristics of red
hat
so this is the first half
so what we do here is uh using the word
embedding model so this is the amount of
data we have so really grateful to
regulation fd that earnings cost of
public information so this is the amount
of earnings called transcript we
obtained to get the score of five
cultural values
for almost 70 000 firm years and over
almost yeah so also 18 years so the data
is available upon request
so what we show is that uh in our
measure of innovation is broader than
the euro measure of innovation like just
based on the expenditure or patterns
which tend to suffer from severe missing
data problem
we i didn't show in this presentation
but in the paper we also showed that
culture correlates with business outcome
but not what michelle suggests like
predictive we managed to show uh uh
association
so lastly in the paper we also showed
that a culture shaped by major corporate
events so not in our work by others they
show about the ipo so that's good so we
thought they had a case study but in our
case we had a systematic evidence
showing that
target culture will have its imprint
over the combined firm going forward
so before i move on and this is perfect
time for me to take a pause to see if
there are any
follow-up questions
i'll ask one question and then hopefully
some other people jump in as well um i'm
intrigued by the last piece of evidence
how corporate culture is shaped by
mergers
um
i'm just sitting here wondering did you
do anything that did you explore what
types of mergers have the biggest
effects like in some ways i could think
that maybe an international merger would
have a bigger effect because it's sort
of more different
but then on the other hand maybe the
prediction goes the other way because
i'm acquiring a firm that's located in
china the employees perhaps are not
really interacting
on a regular basis day-to-day compared
to a merger that's between two silicon
valley firms
so i could see the predictions going
either way i was wondering if you all
have thought about that
no that's a
that's a great one so what we did is
totally domestic but as you're fully
aware
at the international setting actually a
lot of like uh catastrophic um
cross-border transactions is like it's
claimed due to uh culture misfit so like
thumbnail and chrysler that's a
historical that's like a classic example
so it also become very challenging just
like you said there'll be two types of
culture there's a national then there's
an organizational so it'd be really fun
to disentangle when we wrote the paper
we didn't get into international because
there's already prior work by
jfe so they already looked at a culture
misfit in an international setting right
i mean what is that also very good one
they do not we need the earnings call
data to school yeah i mean you could
even there's this old paper on vc's by
um
oh my gosh who's it by it'll come to me
in a second and he showed that the
characteristics of these seeds west
coast versus east coast it was just
dramatically different which you could
imagine right like california is
different than new york city so perhaps
you could even look at that right
um yes
yes
and so that would i mean you know we all
know that there's a difference between
the east coast of this country and the
west coast and the middle so
uh perhaps you don't even need to go
international you could do sort of the
same kind of thing closer anyway i just
thought you know that's a great one but
you think about the other top hot topic
is political polarization
yeah no that's right that's going to be
yeah yeah so
potentially you're going to run a horse
race yeah
i'm going food for thought
yes no that's why people are here so i'm
going to uh ask a waiting to speak then
yeah
hi
uh can you hear me yes very well um so
um a very interesting paper and thank
you for presenting it and um so
my understanding of the innovation
culture here does that also include like
um innovation
or new product development instead of
like scientific innovation
because when i look at the table
represented like the top um top firms
who have the highest innovation
innovative culture are like those
retailers um
so
i i was surprised that those repellers
actually have high scientific innovation
um culture and i was thinking is that
like more of per new product development
and different you know different
different design different type of
products um is that included in this
innovation
absolutely continues like the question
really provide a great transition to my
second half of the presentation i saw my
closer for the second paper it's also
here um so
that is uh
it's broader so in fact um it's any it's
anything you can imagine about the
innovation so next we're going to show
you exactly what you said products
services
as well as very prompt people pivoting
from physical presence to online
presence so this uh our measure capture
that
oh thank you
so sean
yes can you hear me now yes yes thank
first of all thank you for this
wonderful presentation i'm very
intrigued i also i'm glad to hear that
you see the data is available which i
think what you did is basically opens up
a lot of very interesting to study but
just to relate to what you are getting a
little bit at the end towards the end
you said you had a evidence that
corporate culture is shaped by major
crop even particularly the target that
the post-merger
uh companies start to bear reflect some
part of the target one i also wonder
since you're already studying mma did
you also take a look at the m.a
announcement effect because
in ma is also well known that
culture is also big factor
affect the successfulness of failure of
this merger do you see
that if the parent versus the target i
mean acquire and target if their culture
is closer more uh
aligned then also it would be predict a
more successful merger so which we may
expect a
better announcement effect than those
where the culture is
less aligned no um shannon that's a
great one so if i recall i think a high
italian international setting they have
a look at the price of action so for us
what we did is we did a merger pairing
analysis you also think in the us
shareholder activism shareholder value
creation is a big deal so in our uh like
predictive analysis is what kind of
firms getting together we show that
firms that uh
has culture feet so they share same
value for innovation for quality or
teamwork they are more likely to get
together well firms that are not they
are not close in cultural dimension they
do so the counterfactual they just do
not get together so not as a result
we actually do not
show
um we do not see price election i guess
the other thing is culture is something
intangible maybe the market didn't
recognize that
for two reasons the market didn't
recognize uh deeply appreciate it the
other is bad ones that will receive
negative price election because if they
know that they are not good fit they
just decided not to get together
so that's right so we didn't find a
significant uh
like our measure of culture congruency
culture fit and price of action yeah we
don't
okay yeah that's also possible
[Music]
any other questions
did i have um
okay so maybe
remove your raised hand otherwise it's
still there but it's fine um so my
collaborator from the sec second
approach project convey is also
inaudible so i'm going to continue with
the application
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