Exit and Entry Behavior as a Business Portfolio Management
Tatsuya Kikutani (Kyoto University)
Takashi Saito (Waseda University)
Keyword: business governance, exit, entry, selection and focus, business portfolio
management
Ⅰ．Introduction
Japanese firms once succeeded to recover from the long period of struggle following
the burst of the bubble economy, though today they face depression triggered by thecrisis in the U.S. financial markets. How was this remarkable comeback achieved? We
would like to examine this question, focusing on the business realignment thatJapanese diversified firms have carried out in the period from 1995 to 2003.
The corporate behavior of business realignment is often studied quantitatively
from the viewpoint of the change of diversification index and qualitatively by themethod of Rumelt(1974)1. However we adopt somewhat different way from the mostexisting studies. We analyze the business realignment through the behavior of exit andentry. When a diversified firm exits from an existing business, it means the focusing ofbusiness lines, and when it enters into new business, it enhances diversification. If a
firm executes both behaviors at once, it is true that the degree of diversification
remains unchanged, but the firm‟s configuration of lines of business is certainly
changed. Therefore taking our stand on the two-way behavior of the exit and entry
enable us to richen the analysis of the business realignment.
In order to investigate the qualitative characteristics of such behavior, we employ
two kinds of indicators, input relevance and marketing relevance which express therelationship between the core business existing and the business exited from or enteredinto. These indicators measure the resemblance between these businesses as to the
input and output structure in the interindutry-relations table. Using those enables us
to grasp the relevance of the business exited from or entered into in the relation to thecore business.
We analyze both quantitative and qualitative features of the business realignment
There are many researches that find diversification can impair firm values (Forexample, Berger and Mongomely(1988), Lang and Stulz(1994), and so on). Moreover,Comment and Jarrel(1995) argue that a focusing strategy is consistent with the
maximization of shareholder value. In addition, Denis, Denis and Sarin(1997) andBerger and Ofek(1999) suggest that focusing is caused by outside governance pressure.
However, recent studies such as Compa and Kedia(2002), Graham, Lemmon andWolf(2002) point out that diversification does not always destroy the firm value. There
researches commonly take the viewpoints of diversification or focusing.
11

of Japanese diversified firms to answer the following questions.
Question (i)How broadly was the tendency observed that Japanese firms exitedfrom existing businesses and entered to new businesses? What factors did determine
them and how did they affect?
Japanese firms made the business portfolio restructuring efforts in the end of 1990s
and the beginning of 2000s. They selected some businesses and withdrew from theother businesses; it is called the „selection and focusing‟ strategy. This tendency of thebusiness consolidation is observed broadly across Japanese firms regardless of theirsize based on our dataset and the tendency becomes strong recently. In addition, when
we focus on the relation between the core business and the businesses entered into orexited from, a firm with a steadily growing core business tends to withdraw from thebusiness other than the core business. It means that the firm actively consolidates inorder to strengthen its core business. In contrast, a firm with a less growing corebusiness extends to a new business. These actions are quite different from the tendency
that is generally believed – a firm with a lower performance withdraws from somebusinesses and a firm with a higher performance begins new businesses.
It is true that there was tendency of exiting from some businesses and entering
into new businesses during this period, but this does not mean one firm pursued bothbehaviors. Thus our next question is the relation between these exit and entry action.
Question (ii) Are exits and entries conducted by different firms? That is, do somefirms only exit and other firms only enter? Or does one firm conduct both of them atthe same time? In the latter case, do more entries accompany less exits (substituting
relation) or more exits (supplementary relation)?
Our analysis shows that there are many firms that do only exit and pursue
business consolidation. However, it is the important fact that there are quite many
firms that not only exit but also enter at the same time. It is impossible to grasp thistype of business restructuring from the viewpoint of diversifying or focusing as the past
analysis because the degree of diversification does not change if the degree of exit issame as the degree of entry. Therefore, it is crucial to understand the businessgovernance as the process of the business restructuring instead of the businessstructure as the result. To do it, we need the viewpoint of exit and entry.
The next question is why the firm undertakes both exit and entry at same time. It
seems to be contradictory, however, we can answer this question by investigating thefeatures of the industry that firms exit from or enter into. Implement both exit andentry is a replacement of business, in other words, it is the shift of business portfolio.
In this case, the problem is what type of the shift is.
Question (iii) What sorts of lines have been selected by firms as business from which2they exit or into which they enter, and what factors lead the firm to do so?
The results of our analysis are that the business which the firm exits is remotefrom its core business and the business which the firm enters is close to its corebusiness. As a result, the firm shifted from the business portfolio which were weak
relevancy between businesses to the business portfolio which is strong relevancy
between businesses, that is, to the related diversification (or it may be called as therelated consolidation if the degree of exit exceeds that of entry). This tendency of thebusiness action is observed broadly across Japanese firms regardless of their size from
our analysis. The feature of business restructuring and generality might prepare forthe recover of Japanese firms.
Literature on the qualitative features of the business is scarce2. One of the reason
is that it is not easy to quantification the qualitative features of the business. The
method mostly used in classifying the type of the diversification is Rumelt(1974) andYoshiwara et al.(1981), which divides into 4 and more categories, single, dominant,related, unrelated, and so on. However, it is difficult to use in an econometric analysis
because this has many types and this is not a continuous measure.
In this research, we employ two types of indicators, input relevance and marketing
relevance in order to measure relevancy between the business which the firm exits
from and the core business or between the business which the firm enters into and thecore business. The largest contribution of this study is to analyze the businessgovernance using these qualitative features.
The last problem is that these business portfolio management leads to improve theperformance of the firm. It is important because the purpose of the businessgovernance is to improve the performance of the firm3.
Question (iv) How does the feature of exit/entry behavior affect the performance ofthe firm?
We confirm that these improve the performance of the firm by the estimation using
the indicators of the input relevance and the market relevance.
Ⅱ．A Preliminary Analysis by Descriptive Statistics

Berger and Ofek(1995) find that unrelated diversification has negative effects on thevalue of the firm. Daley, Mehrotra and Sivakumar(1997) find that the firm can increase
its value through spinning off of the unrelated lines of business.
3 There are many relevant researches. Yoshihara et al.(1981), Ueno(1993), Genba and2

Kodama(1999), Hiramoto(2002), and Kikutani and Saito(2006b) analyze Japanesecase.
3

１．Data and definitions of exit and entry
Our research requires the data that indicates the business structure of the firm. For
instance, in the case of an analysis using segment information provided in financial
statements, only listed firms are covered. It is also difficult to compare businessstructures because each firm classifies its products, or segments, by its own standards.
Then we use Basic Survey of Japanese Business Structure and Activities(BSJBSA).
This is a compulsory survey by the METI(the Ministry of Economy, Trade andIndustry). The survey covers all firms of 50 or more employees and paid-in capital of¥30 million or more (except for financial institutions and firms belonging to some otherspecific sectors), which means this discussion is not limited to large listed firms. Firms
in the survey were asked to indicate their sales composition by product group, whichcorresponded to an industry group that was given a three-digit classification code.
Actual business structures should be more segmented than a mere three-digitclassification, but this common, standardized classification is meaningful in that it
enables comparison of business structures among firms.
In BSJBSA, a lot of business fields in the service industry are not assumed to be asurvey object and their ranges are not consistent by year, we limit our sample to thefirms whose core business is manufacturing, wholesale, or retail trade. (However, we
cover all the diversified business fields other than the core business.) We exclude
affiliate firms from our sample because this research doesn‟t deal with issue ①.
Moreover we exclude single business firms (firms which have one business unit at the
beginning of the period and the end of the term.) from our sample because we want toanalyze "exit from an existing business" or "entry into a new business." Then, we
have about 7,000 firms as the object of our analysis. We divide the post-bubble period
into Phase I - 1995-1999 and Phase II - 1999-2003. 2003 is the latest year when we canobtain data. We can learn the change of the way of the business restructuring bycomparing both periods.
Using the survey results on sales composition based on the three-digitclassification, the definition of exit from an existing business and entry into a new

business can be written as follows4,
Exit: The case that the firm ceased to report sales for a certain product category
during a designated period.
Entry: The case that the firm started to report sales for a new product category
during a designated period.
Morikawa(1998a) is the first paper that analyzed exits and entries by this method
using BSJBSA.
44

By definition, we can‟t find the exit or the entry behavior when there is an exit oran entry in same three-digit classification code. The number of exits or entries ismeasured in a designated period. If we measure the degree of diversification using thenumber of the businesses, the expansion of diversification in this meaning is thenumber of entries is more than the number of exits situation, oppositely, theconsolidating is the number of exits is more than the number of entries situation5.
Therefore, the expansion of diversification or consolidating diversification is merely theeffect of the net of the exit and the entry. In this sense, it can be said that the numberof exits or entries is more original variable than the degree of diversification.
First of all, let's take a general view of the characteristics of the sample used inthis study. Table1 shows that the number of firms, the average of total asset, the ratioof listing firm, the average number of businesses, the average number of entries andthe number of exits during PhaseI (1995～1999) and PhaseII (1999～2003), when we
divide our sample into following criteria, lower 10 percentile, lower 25 percentile,
median, upper 25 percentile, and upper 10 percentile of total asset in the beginning ofeach phase. The mean value and the median of the total asset are 30,348 million yen
and 4,371 million yen respectively in 1995, and 32,870 million yen and 4,447 million
yen respectively in 1999.
Table 1. Features of Sample and Average Numbers of Entry and Exit
Obs

Avg. Total
Assets(1 million Yen)

Number of Ratio ofRatio of
Avg.
Avg.
Avg.
SingleSingleListed Number of Number of Number ofsegment segment
Firms
Segments
Exit
Entry
Firms
Firms

Total Assets
Phase I(1995～99)
Lower 10 percentile739
875.080.14%
2.68200.73480.5467578
Between Lower 10- Lower25 %1076
1704.770.46%
2.76580.65330.5781
692
Between Lower 25-50 %1846
3100.00
1.25%
2.7844
0.63540.51841154
Between 50- Upper 25 %1801
7097.30
11.49%
2.86340.61800.5230975
Between Upper 25- Upper 10 %1109
19787.01
37.42%
3.11900.61050.5816443
Upper 10 percentile738
245346.70
81.03%
3.79000.69920.5705155
Phase II(1999～2003)
Lower 10 percentile694
895.460.00%
2.72480.9236
0.5778538
Between Lower 10- Lower25 %1041
1698.66
0.48%
2.78190.92510.5735621
Between Lower 25-50 %1734
3116.58
1.10%
2.83970.85700.54901035
Between 50- Upper 25 %1734
7136.18
10.15%
2.86790.79070.5271876
Between Upper 25- Upper 10 %1041
20142.38
40.63%
3.14120.84050.5101
380
Upper 10 percentile693
269667.50
82.40%
3.69410.90910.6032155
Source: Calculated from Basic Survey of Japanese Business Structure and Activities(Ministry of Economy, Trade and Industry)

43.9%
39.1%
38.5%
35.1%
28.5%
17.4%
43.7%
37.4%
37.4%
33.6%
26.7%
18.3%

The scale of total asset of upper 10 percentile of diversified firms is about 280~300
times larger than lower 10 percentile of them, and 12~13 times larger than the next
hierarchy, there is a large bias of the scale. We show the number of the firms whichhave one business in the right side of this table. The ratio of the firms which have one
business is high in the lower 10 percentile, however, the difference isn‟t large compared5

with the other classifications. Oppositely, in the upper 10 percentile, there are few
single business firms. (This corresponds to the fact that the number of businesses
described as follows increases in the firms within this range.)
The ratio of listed to stock markets rises rapidly as the size of a firm is large. It is
about 0~1% in the firms below the median and most firms are non-listed firms, while
the ratio of listed firms exceeds 80% in the upper 10 percentile.
２．Transition of exits and entriesLet‟s take a look at the business structure in the table 1. The average number ofbusiness is about 2.7 in the lower 10 percentile firms and it is about 3.7~3.8 in theupper 10 percentile firms, it increases as the scale of firm is large. The number ofbusinesses in the upper classification which contains a lot of listed companies is clearlylarger compared with the other classifications, however, the difference isn‟t large
considering the difference of scale. The differences of an average number of businesses
are only about one. Needless to say, the degree of diversification of small firms is also
small, nevertheless, we consider that there is no essential difference about thecharacter of the business governance problem that firms face when the effect of thescale is excluded in this study.
When we take a look at
Figure 1. Transition of the number of exits and entries

the business realignment, theaverage number of exits is
0.6~0.7

andtheaveragenumber of entries is 0.5~0.6
during

Phase

I.

1.0

In

0.8

any

hierarchy, the number of exits
is more than the number of

0.6

entries, so we confirm that thebusiness was consolidated in

0.4
Phase I

the wide range. The decreaseof number of businesses that is
equal

to

the

difference

Phase II

Average numbers of exit(whole sample)
Average numbers of entry(whole sample)
Average numbers of exit(manufacture)
Average numbers of entry(manufacture)
Average numbers of exit(whole sale and retail)Average numbers of entry(whole sale and retail)of

entries and exits is 0.2 at most,

Source: Same as Table 1.

however, we should not overlook here the fact that firms executed the three times ormore exits or entries behind the scene. That is, consolidating is only a net result of thebusiness realignment in both directions, this shows that the viewpoint of exit or entry

5

In this case, it will be assumed that sales of each business are equal.
6is indispensable to capture the business governance as the gross action6. Moreover, it issurprising that the number of exits and entries is almost constant regardless of the sizeof a firm or the number of businesses. It seems that reorganizing business is easy forthe small-scale firm because it is easy to exit from the small scale business or to enter
the niche market. These tendencies generally remained unchanged in Phase II. But the
proportion of firms that withdrew from an existing business increased to 60%
compared to 46% in Phase I. Companies that pursued only exit accounted for 31% of
the entire sample (those that pursued both entry and exit were 29% and those that
pursued only entry 10%). Seen in this context, business consolidation in Phase II
outpaced that in Phase I.
Next, let‟s see the transition of the number of exits and entries in another angle.
Figure1 shows it when we divide our sample into manufacturing, wholesale, and retailindustry. It is found that the number of exit increase in all three industries, however,
we can see that the number of exits of manufacturing industry is consistently morethan that of the wholesale and retail trade industry. And it is found that the number of
entries is level-off in all three industries. However, we can see that the number of
entries of manufacturing industry is also consistently more than that of the wholesale
and retail trade industry. This shows that the business reorganization of
manufacturing industry was more active on both sides of the exit and entry thanwholesale and retail trade industry. It is worth noting that there is no great divergenceinmanufacturing

and

the

Figure 2.1 Relationship between the core business growth rate
and the market growth rate(Part1)－Whole sample －wholesale retail trade whensuch a difference is excluded.

0.20

0.15

３ ． Exits/entries and core
0.10

business growth rate
We next see the features of

0.05

the firm that executed exit orentry in detail. Figure 2.1
shows

the

betweentherelationship
core

0.00

-0.05
Phase I

business

growth rate and the growthrate of market to which thecore business belongs. The coreCore business growth rate

Source: Same as Table 1.
Note: The core business growth rate is the average growth rates in the salesof a firm's core business. The market growth rate is the average growth rate in
the sales of "the entire market" to which the core business (3 -digits
classification) of the concerned firm belongs.

business growth rate is the6

Phase II
Market growth rate

However, Kikutani et al.(2006) pointed out this point.
7

average growth rates in the sales of a firm's core business (the largest businesssegment (in 3-digits classification) in terms of sales within each firm's businessportfolio) over a period of time, and the "market" growth rate of the core business is theaverage growth rate in the sales of "the entire market" to which the core business(3-digits classification) of the concerned firm belongs over a period of time. It isnecessary to note that sales in the entire market are the total sales of the concernedbusiness of all firms which sum up their sales to the business regardless of the corebusiness or the side business. According to this figure, the core business growth ratealways exceeds "Market" growth rate of the core business. That is, in general, it isunderstood that the performance of managing the business as a core business is higher
than managing it as a side business on average. This "every man does his own businessbest" effect explains that the performance of diversified firms is low andsimultaneously becomes one powerful grounds that justify the consolidating related tothe core business type which will be explained in next section.
The

above-mentioned

factsuggests that investigating therelativity of the growth potentialof the core business and theexit/entry action is fruitful. Then,

Figure 2.2 Relationship between the core business growth rate
and the market growth rate(Part2)－ Exit vs not exit and entry vs not entry－
0.20

0.15

0.10

first of all, let's compare the corebusiness growth rate of the firmsthat executed withdrawal and

0.05

0.00

the firms that didn't do it.
According to Figure 2.2, it is-0.05
Phase I

Phase II

found that the core business

Average core business growth rate of firms which exit

growth rate of the firms that

Average core business growth rate of firms which enter

executed

withdrawalisconsistently higher than that of

Average core business growth rate of firms which don't exit
Average core business growth rate of firms which don't emter
Source: Same as Table 1.
Note: We devided our sample into firms which exit(entry) and do not exit(entry). The core businessgrowth rate and the market growth rate are same as figure 2.1.

the firms that didn‟t do it. Thisshows that the firm with a high core business growth rate promoted the withdrawal
from businesses other than the core business, and attempted to return to the corebusiness. That is, despite the word "business restructuring" is usually associated with
the image of major operation under the adversity, it is possible to say that the businesswithdrawal strengthens the core business.
Next, let's compare the core business growth rate of the firms that launched new
businesses and the firms that didn't do it. In this case, conversely, the core businessgrowth rate of the firms that launched new businesses is consistently lower than that8

of the firms that didn‟t do. This still shows that the firm with a high core businessgrowth rate limits to launch new businesses and takes the strategy to place importancein the core business. Conversely, however, firms enter to a new business when the corebusiness growth rate is low. It shows the positive attitude of the firm that tries to break
the predicament.
When we put together the above considerations about exits and entries, it isfound that high growth rate of the core business causes business reorganization to thecore business by promoting to

Figure 2.3 Relationship between the core business growth rate
and the market growth rate(Part3)－Core business growth rate and market growth rate of thewithdraw from the businesses
other than the core business andsimultaneously

limiting

toentry/exit industry－

0.20

0.15

launch a new business.
Figure 2.3 shows how themarketgrowth

rate

of

the

0.10

0.05

entry/exit industry of the firmthat launched new business orwithdrewfromchanged

and

the
how

business
the

0.00

-0.05

core

Phase I

business growth rate of thesefirmschanged.

The

marketgrowth rate of the exit/entry
industry is an average value ofPhase II

Core business growth rate of firms which exit
Market growth rate of the industry from which firms exit
Core business growth rate of firms which enter
Market growth rate of the industry into which firms enter
Source: Same as Table 1.
Note: We used only the data from firms which exit/enter. The core business growth rate is same as Figure
2.1. The market growth rate of the exit/entry industry is an average value of the growth rate of four years ofsales of "the entire market" of the exit/entry industry. If a firm executed two or more exits/entries, thisvalue is the weighted average of the sales of the beginning/end of the term.

the growth rate of four years ofsales of "The entire market" of the exit/entry industry (3-digits classification). The salesof the entire market are total value of the sales of the concerned industry of the firms
regardless of the core business or the side business. If a firm executed two or moreexits/entries, this value is the weighted average of the sales of the beginning/end of theterm.
We see from this figure that the market growth rate of the entry industry is large
and much larger than the growth rate of core business. This suggests that firms
correctly selected the entry industry. It is worth noting that the market growth rate of
the exit industry rises and is larger than the growth rate of core business in Phase II.
This suggests that the firm may withdraw from the industry though the market growthrate is high or it seems to be promising industry. We will consider it again at theanalysis concerning the business characteristic of the withdrawal type of business insection 4.

9

４. Simultaneously pursuing exit and entry by firm
It is necessary to confirm that

Table 2. Combination of exits and entries
Exits
Phase INo
Yes
No①
40.09% ②
20.60%
ExitsYes③
13.91% ④
25.40%
Entries
Phase II
No
Yes
No
①
29.57% ②
31.02%
EntriesYes③
10.31% ④
29.10%
Source: Same as Table1.

there is the tendency that the entry
number is nearly equal to the exit
numberatindividual

firmlevel.

Because we previously have seen thistendency in each scale hierarchy, but
this is a tendency at the aggregate levelin each hierarchy. It is possible that the number of firms that do only the entry ismerely equal to the number of firms that do only exit. Table2 shows that the ratio of(1)the firms don‟t neither exit or entry, (2)the firms only do exit, (3)the firms only do
entry, (4)the firms do both exit and entry in each phase to all sample respectively. Thatis, it indicates whether each firm undertakes the exit and entry simultaneously. Thisshows that (1) is the largest group (40%) and (4) is next largest group(25%) at PhaseI.
That is, the ratio of the firms do both entry and exit and the firms don‟t neither entry
or exit is 65%. It indicates that the entry number is nearly equal to the exit number at
individual firm level. Moreover, it can be said that there is a supplementation between
the two in this sense. But at PhaseII, (3) becomes the largest group(31%) and (1) has
decreased more than 10% point.
In Figure 3, we provide the correlation coefficient between the number of exit andentry, which are continuous variables rather than binomial variables such as whether
the firm do exit/entry.
The correlation coefficient is positive and significant (at 5% level). That is, the firmthat does many exits also does
many

entries.

And

we

can

Figure 3. Correlation coefficients of the number of exits and entries
0.35

confirm the simultaneousness ofthe number of exit and entry.
Furthermore,

0.30

the

correlation coefficient at PhaseII

0.25

is smaller than at PhaseI when
we take all sample and when we
divideoursampleinto

manufacturing

and

the

0.20

0.15
Phase I

Phase II

wholesale/retail industries. This

Correlation coefficient of the number of exits and entries(Whole sample)

may be because the firms that

Correlation coefficient of the number of exits and entries(Wholesale and retail)

Correlation coefficient of the number of exits and entries(Manufacture)

Source: Same as Table 1.

do only exit increase at PhaseII
as is shown in Table 2.

10Then, what does the fact that the firm does many exits also does many entries
mean?
５．What industry does the firm does exit from or enter into? : The qualitative
relevance to core businessIn this section, we provide the analyses of the qualitative feature of the exit/entry
and answer the previous question. First of all, we explain how we grasp the qualitative
feature. When we classify the type of diversification, if the industry at 3-digit level
corresponds with the core business at 2-digit level, then we often regard this type ofdiversification as related7. However this method has the disadvantage that the numberof 3-digit industries included in a 2-digit industry varies widely. (For example, in thecase of manufacturing industry of BSJBSA, the maximum value is 6 and the minimum
value is 1.) So we employ the Fan and Lang(2000) method and grasp the relevance
between the core business and the exit/entry industry from the relation between input
and output.
The input relevance index measures technical similarities between two products interms of how they are produced (the combination of goods and resources required fortheir production), whereas the marketing relevance index measures similarities
between two products in terms of their market channels. Analysis using either of theseindexes found that firms tend to exit from businesses further from (less proximate to)their core business and are inclined to enter new businesses closer (more proximate) totheir core business. We can understand easily the difference between the input
relevance and the marketing relevance the through following example. As for apassenger car and a track, they have similar combination of inputs (high input
relevance) but the usage is different (low market relevance). Oppositely, as for awooden steering wheel and a plastic steering wheel, they have different combination of
inputs (low input relevance) but the usage is similar (high market relevance). Of course,
there can be the combination both of them are high.
To specify the relation between input and output(marketing) of inter-business, we
use the input coefficient matrix of the input-output table. The input relevance between
the core business(industry m) and the exit industry(industry i, i≠m ) is the correlation
coefficient between column m and column i in the input coefficient matrix. The
marketing relevance is the correlation coefficient between row m and row i in the input
coefficient matrix. It is possible that the firm undertakes exits from two or moreindustries, we use the weighted average of the sales of each industry at the beginning11

of the period in this case. We can define the input/market relevance between the corebusiness and the entry industry quite similarly to these. However, if the firm
undertakes entries into two or more industries, we use the weighted average of sales ofeach industry at the end of the period.
Figure4relevanceshows

betweenthethe

Figure 4. Relevance between the exit/entry industry and the core business.

exit/entry industry and the core

0.55

business. We see from thisfigurethat

theExpanding

0.50

relevance

between the exit industry and0.45

the core business is always
lower

than

the

0.40

relevance

between the entry industry and0.35

the core business. This means

0.30
Phase I

that the firms withdraw frombusinesses remote from the corebusiness

andexpandbusiness.

Such

Input relevance between the entry industry and the core business
Market relevance between the exit industry and the core business

intobusinesses close to the core

Phase II

Input relevance between the exit industry and the core business

Market relevance between the entry industry and the core business
Source: Same as Table 1.
Note: To calculate the relevance between the exit/entry industry and the core business, we use
only the data from firms which exit/entry

businessrealignment shifts the business portfolio of the firm to the one that has strong
relevance to the core business. We previously mentioned that there is the tendency thatfirms simultaneously execute exit and entry. This action seems to be contradicted, but
it shows that the business portfolio of the firm is shifted to the one with strong
relevance to the core business by both direction of the withdrawal and the expansion.
We can reasonably explain such an action only after seeing "Qualitative feature" of theexit industry and the entry industry.
We next consider two relevance indexes separately. As for the input relevance, therelevance between the exit industry and the core business decreases but the relevance
between the entry industry and the core business increases at Phase II compared with
Phase I. That is, the tendency that the firms withdraw from businesses remote fromthe core business and expand into businesses close to the core business became more
remarkable. Moreover, this tendency is demonstrated by extending gap between the
input relevance of exit and entry industry as shown by Figure 4. Especially, thisqualitative tendency of the exit extends to more firms since the number of exit
increases at Phase II. We can summarize that it is remarkable that the tendency which
the business portfolio is consolidated to the one with higher input relevance becomes7

Needless to say, the data of profitability of each businesses is unavailable.
12strong in the 2000's, and we can say that this is accelerated on both sides of exit andentry.
As for the marketing relevance of exit industry and that of entry industry, both ofthese are level off. Since the market relevance of exit industry is lower than that ofentry industry, so the fact that the market relevance of the business portfolio iscomparatively strengthen unchanged. However, unlike the input relevance, we cannot
say “it is accelerated.”
Finally, let‟s consider the relation between the consequence of this section‟s
analyses and the fact that firms withdraw from the business whose growth rate is highat Phase II as we saw from Figure 2.3. It is likely that firms withdraw from thebusiness which is remote from the core business even if the growth rate of this businessis high, since firms regard the merit of consolidation as important.
In table 3, we provide descriptive statistics for variables used in our regression
analysis which will be presented following sections. We will describe details of eachvariable in the next section.
Table 3. Basic Statistics of Variables
Variable
Year
Obs.
Mean
Std. Dev. MinMax
GROWTH
1999-2003
6937
0.02910.1283-0.4059
3.3359RISK
1999-2003
6937
0.1852
0.23700.00207.2790MGROWTH
1999-2003
6937
0.00160.1021-0.1163
6.2226
ASSET
1999
6937
8.64961.42364.543315.3160
ROA
1999
6937
0.02930.0464-0.30640.9613
LEVERAGE
1999
6937
0.24710.18480.00001.7349
SEG
1999
6937
2.9572
1.26342.000013.0000
CRATIO
1999
6937
0.76940.18790.09330.9999
LIST
1999
6937
0.17210.3775
0
1
FOREIGN1999
6937
0.00890.03940.00000.6412
W&RIND
1999
6937
0.35530.478701
Adjusted ROA
2003
6600 -0.0026
0.0503-1.93070.4987
Adjusted ROE
20036600 -0.0221
1.0189 -35.3477
47.8296

III Econometric Analysis on Exit and Entry Behavior
In this section, we approach our problem (i)~(iv) which were presented in section 1
by using the econometric analysis.
１．Determinants of exit and entry: Problem(i)We first analyze what factors determine exit from current business and entry into
new business and how these determinants affect these behaviors.
(1)Methods of estimation and hypothesis
The feature of the core business is the most important factor to determine exit andentry. Of course, firm‟s financial performance is also important, but this is a short-term
factor. However, it is likely that the core business is more important than financial

13

performance because the growth potential of the core business is a middle-term factor
as well as exit/entry strategy. Furthermore, the feature of individual business is hidden
since the subject of this analysis is diversified firm and firm‟s financial performance issum up all businesses8. In this sense, it is necessary to investigate the feature of thecore business (We use firm‟s financial performance as the other firm‟s feature). In
addition, it is reasonable to think that the feature of the core business has a big
influence on the strategic behavior such as exit/entry in diversified firms as implied by
the PPM theory that the growth potential of the business determines firm‟s businessportfolio.
Therefore, we estimate the following model. We assume a priori that thedetermination factors of exit and those of entry are same and we judge whether they
actually affect or not from the result of the estimate.
number of exit = f1（factors of core business，the other factors of firm，phasedummy） … (1)number of entry = f2（factors of core business，the other factors of firm，phasedummy） … (2)It is appropriate to employ SUR (Seemingly Unrelated Regressions) instead of
estimating these two equations separately because it is unlikely that firms separately
determine the number of exit and that of entry.
We use following three explanatory variables to represent the factors of the corebusiness, GROWTH, RISK, CRATIO. The definition of these variables and expected
sign are as follows.
i) Factors of the core business
GROWTH
Growth is mean sales growth rate in core business in each phase. This represents
the growth potential of the core business. A firm with a faster growing core businessmay increases the number of exit since it faces less demand to stay at segments otherthan the core business. It may decrease the number of entry since it faces less need totake a risk to enter new segments. We thus expect that the growth of the core businessis positively correlated with entry while it is negatively correlated with exit. In otherwords, the growth potential enlarges the merit that a firm concentrates its
There is a method that defines related/unrelated by the entropy as a diversificationindex. (Genba and Kodama(1999), Jacquemin and Berry(1979)）This index, however, issame as other indexes in regard to use SIC code.
814management resources to its core business and accelerates consolidation of business.
RISK
Risk is standard deviation of sales growth rates in core business in each phase.
This represents riskiness of the core business. We use this variation because importantstability of potential growth of the core business is important as well as highness of it.
We expect that the risk of the core business is negatively correlated with exit while it ispositively correlated with entry. If core business growth is equal, a firm whose corebusiness faces higher market uncertainty refrains from exit from segments andattempts to enter other segment in order to distribute risk among businesses.
CRATIOCRATIO is ratio of sales of core business to total sales. The ratio of the corebusiness is important for a diversified firm. In order to avoid risk, a firm which highly
depends on its core business should decrease exit and increase entry. Even though risk
may be completely controlled by RISK, we can consider the other effect. If high
CRATIO indicates superiority of the core business, the firm increases exit anddecreases entry in order to recur to the core business.
CRATIO also represents the degree of consolidation after controlling the number ofsegments. If the number of segments is equal but CRATIO is high, the businesses otherthan the core business are relatively small, and then it is easy to exit because of its
small cost.
ii) Other firm-specific factors
The factors of a firm other than the core business are as follows.
ASSET is natural logarithm of initial total assets. We use this as the measure ofscale of the firm. A large firm has accumulated managerial resources, so it may havehigh organizational capability to enter new business. A larger firm has moremanagerial resources for sustaining loss-making business and larger organization isslower in decision-making. We thus expect that it is negatively correlated with exit
while it is positively correlated with entry.
ROA is initial ratio of operating income to total capital. We use this as theperformance measure of the firm. As a firm‟s performance is higher at the beginning of
the phase and it has more cash flow, it is easy to do business restructuring in order tostrengthen its business. Hence the initial ROA may be positively correlated with exitand entry. However, if a firm is content with the good performance and neglects theeffort of the business restructuring, ROA may be correlated with exit and entry.

15

LEVERAGE is initial ratio of book value of fixed debt to total asset. We use this as
the measure of balance sheet status. According to so-called “the discipline-of-debt
effect”, the higher the fixed debt ratio is, the firm is more likely to be urged to dobusiness restructuring. Thus it may be positively correlated with exit and entry. Notehowever if financing cost is high due to firm‟s higher fixed debt ratio, entry may be
restricted.
SEG is the initial number of business segments. We use this as the measure offirm‟s diversification. Many business segments represent plenty of managerial resource
accumulated and high organizational capacity. We thus expect that it is positively
correlated with entry. If a firm has many segments, the other businesses can easily
absorb the shock of exit. Moreover, after controlling firm size, many segments
represent that each business is relatively small, thus exit cost may be small. Thus SEG
may be positively correlated with exit. On the other hand, however, it is likely that afirm with many segments doesn‟t need to diversify anymore because it has diversified
enough. In addition, if there is a diversification discount, SEG may hurt profitability.
Hence SEG may be positively correlated with exit and negatively correlated with entry.
W&RIND is a dummy variable indicating whether a firm belongs to the wholesaleindustry or the retail industry. Our sample contains manufacturing, wholesale, andretail industries, so we use this in order to control industry effects on decision-making.
MGROWTH is mean total sales growth rate in the industry which is the corebusiness of the firm concerned in each phase. We use this as market growth potentialof the industry which is the core business of the firm. A firm in a faster growing
industry may be relatively growing slowly, thus we expect that MGROWTH have theopposite sign to GROWTH. However, we cannot deny another possibility. If the
expansion of the market represents the growth potential of firm‟s core business, we can
expect that MGROWTH have the same sign as GROWTH.
LIST is a dummy variable indicating whether a firm is listed on the Japanesestock market. FOREIGN is the proportion of shares held by foreign entities if a firm islisted, or it is 0 if a firm is not listed. These are the variables that capture corporate
governance. We expect that they are positively correlated with both entry and exit if
the discipline of the stock market works well.
PHASE II is a dummy variable taking the value of 1 if the phase is II and taking
the value of 0 if the phase is I. We use this in order to control for differences indecision-making among phases.
(2)Estimation Resultsi) Factors of the core business16

Table 4[1] presents the estimation results concerning entry and exit variables.
The coefficients of GROWTH are negative and significant for exit and positive andsignificant for entry. We confirm that exit is promoted while entry is restrained when
the core business steadily grows. Therefore, the number of segments decreases. That is,
the steadily growth of core business causes the firm to move toward focusing.
RISK has positive and significant effect on exit and negative and significant effecton entry. It suggests that risk in the core business encourage the firm to enter new
business segments in order to distribute the risk. In addition, if GROWTH is controlled,
the increase in RISK leads to fewer exits. In this case, eventually, the number ofsegments increases and diversification is advanced.
The coefficients of CRATIO are positive and significant for exit and negative andsignificant for entry. Controlling the number of segments, a firm with high ratio ofsales of core business inclines to consolidate its business. It suggests that it isadvantageous for a firm to specialize in the core business.
ii) Other firm-specific factors
ASEET has negative and significant effect on exit. Controlling the number ofsegments, we find that the larger the firm is, the less exit is pursued. It is interestingthat this result corresponds to the fact that the larger the firm is, the slower the firmmakes decision to exit.
The coefficients of ROA are all positive and significant for both exit and entry. This
result implies that a firm with high profitability engages in business restructuring
more actively through both entry and exit. This suggests that it is necessary for a firm
to accumulate enough cash flow to do such a business restructuring.
LEVERAGE also has positive and significant effects on both exit and entry. That is,a firm with easier access to external funds engages in business restructuring more
actively. In other words, we conjecture that such a firm raised funds necessary forentry and exit through borrowing. It is ambiguous that whether these actions lead todiversifying or focusing. We will answer this question in the next section (3) where we
conduct estimation on diversification.
The effects of SEG on entry and exit are positive and significant, too. Thus a firmwith more segments actively engages in exit and entry.
W&RIND has negative and significant effects on both exit and entry. Comparedwith a firm in wholesale and retail industry, a firm in manufacturing industry engages
in exit and entry more actively. We will confirm whether these actions lead todiversifying or focusing in next section.
The coefficients of MGROWTH are positive and significant on both exit and entry.

17That is, the higher the growth rate of the market that a firm belongs to, the more
actively the firm engages in exit and entry. The findings implies that when the rival
firm whose core business is same to the firm is steadily growing, the firm engages inbusiness restructuring in order to compete it. Whether the increase in MGROWTH
leads to diversifying or focusing will be answered in the next section.
LIST and FOREIGN do not have any significant effects on both exit and entry. The
result implies that the discipline of the stock market has no effects on exit and entry at
individual firm level. However, as we will see in the next section, it has negative effecton the number of segments that is composed effect of exit and entry.
PHASE II has positive and significant effect on exit while it does not havesignificant effect on entry. That is, the number of segments decreases in phase II
compared with phase I. This means that firm engages in “selection and focus” at Phase
II.
(3) Determinants of diversification
If an explanatory variable affects entry and exit in the same direction, it isambiguous that which effect is stronger. To answer this question, we must estimate as
the net effect of entry and exit.
The coefficients of explanatory variables obtained from the estimations of exit andentry basically have opposite signs. In these cases, there are two possibilities. Firstly,
when a factor brings a positive effect on exit and a negative effect on entry, it drives thefirm to focusing. Secondly, when a factor has a negative effect on exit and a positiveeffect on entry, it drives the firm to diversifying. However, some coefficients of
explanatory variables, such as ASSET, SEG, W&RIND, MGROWTH, and PHASE II,
have the same sign. In these cases, whether the factor leads to diversifying or focusing
is ambiguous. Therefore we need to estimate on diversification in order to clarify on
which of entry or exit the factor has a larger effect using the number of segments to beat the end of the phase as a dependent variable9.
Table 4[2] presents the results of the estimation. It is roughly corresponding to theresult obtained from the estimation of exit and entry.
We concentrate here on the explanatory variables whether each of them leads todiversifying or focusing is unclear in the estimation of exit and entry. The effect of SEG
on the number of segments at the end of the phase is positive and significant. That is,
the more diversified a firm, the more it increases the number of business, ceterisparibus. Neither of LEVERAGE nor MGROWTH have significant effects, probably
This estimation is equivalent to the partial adjustment model about diversification.
See Kikutani et al.(2006).
918

Table 4. Estimations of Entry, Exit, and Diversification（Factors of the core business）
GROWTHRISKCRATIO（Other firm-specific factors）
ASSET
ROA
LEVERAGE
SEG
W&RIND
MGROWTHLIST
FOREIGN（Phase dummy）
PHASE IIEXIT and ENTRY

Diversification

SUR
[1]

Interdependency of EXIT and
ENTRY
３SLS
[3]
EXIT
ENTRY

EXIT

ENTRY

OLS
[2]
SEG

0.561***(0.069)-0.262***(0.035)0.596***(0.040)-1.524***(0.071)0.772***(0.036)-0.0997**(0.041)-2.085***(0.25)
1.034***(0.11)-0.701***(0.052)

1.818***(0.089)-0.899***(0.045)0.679***(0.040)-1.968***(0.072)0.979***(0.037)-0.572***(0.045)-0.0818***(0.0064)0.280**(0.14)
0.130***(0.036)
0.371***(0.0061)-0.153***(0.014)0.295***(0.086)0.0236(0.024)0.247(0.21)

0.00398(0.0065)
0.327**(0.15)
0.183***(0.037)0.0746***(0.0062)-0.0430***(0.014)0.375***(0.088)-0.0277(0.024)0.324(0.22)

0.0849***(0.0085)0.0466(0.19)
0.0500(0.043)0.703***(0.011)0.109***(0.017)0.0773(0.13)-0.0492*(0.029)0.0856(0.31)-0.0851***(0.0063)0.0101(0.14)-0.0215(0.037)0.309***(0.0066)-0.118***(0.014)-0.0136(0.086)
0.0464**(0.023)-0.0204(0.21)

0.0687***(0.0070)
0.106(0.14)
0.0807**(0.037)-0.219***(0.014)0.0782***(0.015)0.141(0.087)-0.0463*(0.024)0.129(0.21)

0.198***(0.013)0.0213(0.013)-0.176***(0.017)0.180***(0.013)-0.135***(0.015)（Interdependency of Exit and Entry)
EXIT

0.791***(0.035)ENTER

0.825***(0.037)
const-0.147**0.213***
0.373***-0.323***0.329***(0.064)(0.066)(0.095)(0.064)(0.065)
Obs.
14326
14326
14326
14326
14326
adj. R2
0.25
0.05
0.53
0.02
-0.15
Likelihood-33222-18081
Notes: Figures in parentheses are standard deviation adjusted for heteroscedasticity(White's correction). ***, **, and *denote coefficients significant at the 1%, 5%, and 10%.

because these factors encourage both entry and exit, and hence these effects cancel out.
The coefficient of W&RIND dummy is positive and significant. It suggests that theeffect of entry exceeds that of exit in the wholesale and retail industry, thus the degreeof diversification increases. The coefficient of Phase II dummy is negative andsignificant. The degree of diversification at phase II is smaller than that at phase I
since exit effect is stronger than entry effect at phase II. The effect of LIST, which is
not significant in the estimation of exit and entry, is negative and significant in thisestimation. A listed firm engages in business consolidation more actively than
non-listed firm ceteris paribus. The result shows that there is market discipline of the19stock market.
2. Interdependency of exit and entry: Problem(ii)i) Estimation methods and hypothesis
In this subsection, we analyze the problem (ii). In above section, we estimated exitand entry separately, however, as showed in table 2 and figures in section 2, there isinterdependency of exit and entry. Therefore we must estimate the following modelthat clearly assumes that exit and entry directly affect each other.
number of exit = f1（number of entry, factors of core business，the other factors of
firm，phase dummy） … (3)number of entry = f2（number of exit, factors of core business，the other factors of
firm，phase dummy） … (4)Now, the number of entry is correlated with the error term in equation (3) and thenumber of exit is correlated with the error term in equation (4) since we assume thatexit and entry affect each other. In this case, OLS may be inappropriate since thecoefficient will be biased and OLS cannot provide consistent estimators. In addition, it
is likely that the error terms of two equations are correlated as well as (1) and (2)equations. We thus employ 3SLS (Three-stage least squares) estimation in order toeliminate the biases which occur from interdependency of exit and entry and obtain theeffect of exit on entry and the effect of entry on exit respectively. At the first stage of
3SLS, we add entry and exit at the beginning of the phase as the explanatory
variables.
As we see in Figure 3, the number of exit is positively correlated with the numberof entry. However, it is necessary to estimate these equations system in order toconfirm whether this finding is true ceteris paribus. If both of the coefficient of entry inequation (3) and the coefficient of exit in equation (4) are positive, there is acomplementary relation between exit and entry. If both of them are negative, there is a
substitutional relation. If the two signs are different, neither of these relations is
satisfied. We don‟t describe the other explanatory variables, such as factors of the corebusiness, the other factors of the firm, phase dummy variable since they are used inabove estimation.
ii) Estimation results
Table 4[3] report the 3SLS estimation results concerning the interdependency
effects of exit and entry. Controlling other factors, entry is positively correlated with20

exit and exit is positively correlated with entry. That is, a firm conducts exit and entry
complementary. Moreover, they have a considerably large impact since the coefficientsare 0.8 respectively.
Compared with the result of SUR presented in table 4[1], the effect of the numberof segments changes to negative in the result of 3SLS. One interpretation of thedifference between the two estimations is that SEG has positive effect in SUR because
the coefficient of SEG is the components of direct effect and indirect effect, while SEG
has negative effect in 3SLS because the coefficient of SEG is direct effect only. The
direct effect is the one of number of segments on the degree of entry. The indirect effectis the effect of exit which is affected by the number of segments. Therefore the numberof segments has negative effect on entry directly; however, it simultaneously has
positive effect on exit. This suggests that it is likely that the surplus managerial
resource emerge from exit encourages enter to new business. Such indirect effectexceeds direct effect.
Finally, we briefly review the effects of other points which is different from theresult of SUR. W&RIND has a positive and significant effect on entry in 3SLS while it
has a negative effect in SUR. It also suggests that indirect effect exceeds direct effect.
We next analyze the implication of the tendency that both of exit and entry issimultaneously undertaken from the viewpoint of features of the industry of exit orentry.
IV．Features of exit or entry
In this section, we examine Problem (iii). We analyze what sorts of businesses havebeen selected by firms as areas from which they exit or into which they enter and what
factors lead the firm to do so. This analysis is the central thesis of this study. We
employ two types of indicators, input relevance and marketing relevance, which are
explained in section 2, as the features of exit or entry industry.
1. Estimation method and hypothesis
When we analyze what factors determine the feature of entry or exit industry, it isimportant to note that we only observe the features of exit industry for the firm exits
from business and the features of entry industry for the firm enters into new business.
In this case, an OLS regression using the selected sample leads to inconsistentestimation due to a sample selection bias. In order to eliminate such a bias, we employ
the Heckman‟s two-step Estimator. The first step estimates a probit model of thedecision of whether to exit/enter or not, the second step estimates the feature ofexit/entry industry. We estimate the exit/entry equation separately rather than a21system estimation such as SUR or 3SLS for simplicity. The model for the estimation as
follows.
<Estimation for exit>
1st-step : exit dummy = f（factors of core business，the other factors of firm，phasedummy） … (5)2nd-step : feature of exit industry = g（factors of core business，the other factors of
firm，phase dummy, λ）… (6)<Estimation for exit>
1st-step : entry dummy = （f factors of core business，the other factors of firm，phasedummy） … (7)2nd-step : feature of entry industry = g（factors of core business，the other factorsof firm，phase dummy, λ） … (8)Exit(Entry) is dummy variable indicating whether a firm enters(exits). The
variables for the feature of Exit(Entry) industry are input relevance and marketing
relevance to the core business. The other explanatory variables are same as used forthe estimations in section 3. λ is the inverse Mill‟s ratio.
The first step estimation is basically same as the SUR estimation in section 3.1,
except that the dependent variable is the dummy variable. The purpose of the second
step estimation is to examine the hypothesis as mentioned in section 2.5. That is, afactor leads to exit will be negatively correlated with the relevancy of exit industry to
the core business; whereas a factor leads to entry will be positively correlated with therelevancy of entry industry to the core business.
2. Estimation Results
Table 5 presents the results. The results of the first step estimation are basicallysimilar to the SUR estimation except that RISK, MGROWTH, and ROA are notsignificant.

22

Table 5. Estimations of the Features of Exit/Entry Industry
Features of Exit Industry
HeckitHeckit
[4]
[5]
Input
Market
EXIT
EXIT
Relevance
Relevance（Factors of the core business）
GROWTHRISKCRATIO（Other firm-specific factors）
ASSET
ROA
LEVERAGE
SEG
W&RIND
MGROWTHLIST
FOREIGN

Features of Entry Industry
HeckitHeckit
[6]
[7]
Input
MarketENTER
ENTER
Relevance
Relevance

1.582***(0.22)
0.178(0.21)
1.343***(0.11)-0.0882***(0.032)0.0434***(0.016)-0.0210(0.020)1.596***(0.22)
0.170(0.22)
1.336***(0.11)

0.0414(0.029)-0.0219(0.014)-0.0582***(0.021)-2.249***(0.16)
1.122***(0.080)-0.141**(0.068)0.0476(0.051)
0.0614**(0.030)0.0264(0.028)-2.052***(0.14)
1.026***(0.069)-0.151**(0.063)-1.053***(0.092)0.577***(0.042)-0.0516(0.039)-0.106***(0.012)0.106(0.24)
0.152**(0.064)0.424***(0.015)-0.239***(0.025)0.371*(0.22)
0.0275(0.041)
0.575(0.40)-0.00255(0.0032)-0.0663(0.066)-0.00793(0.018)0.00288(0.0031)0.0745***(0.0071)
0.0614(0.067)-0.00695(0.012)0.221**(0.11)-0.107***(0.012)
0.0963(0.24)
0.154**(0.064)0.422***(0.015)-0.240***(0.025)0.278(0.19)
0.0280(0.041)
0.585(0.40)-0.000313(0.0034)
0.00238(0.065)-0.0416**(0.018)-0.0251***(0.0049)
0.147***(0.0071)-0.114(0.097)0.00508(0.012)-0.227**(0.095)-0.00690(0.011)0.480**(0.24)
0.280***(0.063)0.105***(0.010)-0.0780***(0.025)1.426***(0.34)-0.00183(0.040)0.337(0.33)-0.0152***(0.0041)0.265***(0.097)0.0302(0.025)-0.0192***(0.0037)-0.0337***(0.0090)0.139**(0.056)0.0276*(0.016)0.180(0.12)-0.0181*(0.0099)
0.593***(0.23)
0.248***(0.060)0.0743***(0.0092)-0.139***(0.026)1.085***(0.21)
0.00388(0.038)0.133(0.29)-0.00983(0.0062)0.497***(0.14)
0.0844**(0.038)0.0291***(0.0059)
0.0836***(0.018)0.237***(0.061)-0.0260(0.023)-0.0183(0.18)（Phase dummy）
PHASE II

0.366***-0.0563***0.367***-0.00152
0.01820.0337***0.0383*0.00764(0.022)(0.0064)(0.022)(0.0077)(0.022)(0.0082)(0.020)(0.012)
const-1.475***0.437***-1.455***0.485***-0.638***0.689***-0.402***-0.249***(0.19)(0.033)(0.19)(0.039)(0.11)(0.048)(0.10)(0.066)
λ-0.0553***-0.0109-0.0898***
0.616***(0.0098)(0.023)(0.016)(0.016)arc hyperbolic tangent ρ-0.208***-0.0412-0.285***2.609***(0.037)(0.086)(0.050)(0.18)
lnσ-1.312***-1.328***-1.129***-0.474***(0.0074)(0.0069)(0.011)(0.022)
Obs
14326
14326
14326
14326
Likelihood
-9504
-9474
-10773-11018Notes: Figures in parentheses are standard deviation adjusted for heteroscedasticity(White's correction). ***, **, and * denote coefficients significant at the 1%, 5%,
and 10%.

The results of the second step estimation are as follows. First, we review the exit
industry. MGROWTH, LEVERAGE, SEG, CRATIO, and PHASE II, which are
positively correlated with exit in the first step, are negatively and significantly
correlated with the input or market relevancy. These findings suggest that firms tend
to exit from businesses further from (less proximate to) their core business. These
factors, however, have an effect only on input relevancy or market relevancy. The
coefficients of RISK and W&RIND are positive and significant. Since these variables
are negatively correlated with exit, therefore, exit is promoted when these variable aresmall. In this case, the firm exits from businesses further from their core business.
FOREIGN, which represent the corporate governance, has a positive and significant
effect on the input relevancy while it has a negative and significant effect on themarket relevancy.
Second, we review the entry industry. RISK, LEVERAGE, MGROWTH, and
PHASE II, which are positively correlated with entry in the first step, are positively
and significantly correlated with the input or market relevancy. The findings suggestthat the firms are inclined to enter new businesses closer (more proximate) to their23

core business. MGROWTH has a negative effect on market relevancy, but it is likelythat this is because MGROWTH is negatively correlated with entry. SEG and
W&RIND have negative and significant effects on the input relevancy while they havepositive and significant effects on the market relevancy.
V Portfolio restructuring and performance : Problem(iv)
In this section, we analyze how portfolio restructuring affects performance of the
firm. Do the feature of exit/entry industry, which are investigated above section, affecton performance?
1. Estimation method and hypothesis
We now estimate the effect of feature of business portfolio restructuring on thefirm performance. The model to be tested is as follows.
PERF=f(OnlyEXIT, OnlyENTRY, BOTH, EXTFEAT, ENTFEAT, OTHERFEAT,
PHASE II) … (9)PERF is the performance of the firm. It is measured by ROA(operating income
divided by total assets) or ROE(operating income divided by equity).
We define the explanatory variables representing the combination of exit and entry
as follows. OnlyEXIT is a dummy variable indicating whether a firm only exited but
not entered, OnlyEnter is a dummy variable indicating whether a firm only entered
but not exited, and BOTH is a dummy variable indicating whether a firm
simultaneously entered and exited. The case in which a firm neither enters nor exits istaken as a base. Kikurani et al.(2006) shows that restructuring only with entry or exit
does not lead to improvement in performance unless both entry and exit are pursued
simultaneously. Hence BOTH may be positively correlated with PERF whereas thecoefficients of OnlyEXIT and OnlyEntry may be insignificant.
Next, we explain the explanatory variables representing the feature of exit orentry industry. EXTFEAT is interaction term of exit dummy and input relevancy ormarket relevancy. ENTFEAT is interaction term of entry dummy and input relevancy
or market relevancy. The performance of the firm may improve when the firm exits
from businesses remote to the core business or enter new businesses closer to the corebusiness. We thus expect that EXTFEAT is negatively correlated with PERF while
ENTFEAT is positively correlated with it.
We also include OTHERFEAT, which contains SEG, ASSET, LEVERAGE, LIST,FOREIGN, W&RIND, and PHASE II, as explanatory variables. SEG may be negatively

24

correlated with PERF because there may be the diversification discount.
Table 6. Estimations of Portfolio Restructuring Effect on Performance
OLS
OLS
[8]
[9]
Adj. ROA（Combination of Exit and Entry）
OnlyEXIT
OnlyENTRY
BOTH（Features of Exit/Entry Industry）
EXTFEAT
EXIT×Input Relevance

Adj. ROE

0.00000930(0.0010)-0.000623(0.0012)0.000810(0.0012)0.0205(0.053)-0.0356(0.047)-0.0369(0.044)-0.00461**(0.0023)-0.174**(0.077)

EXIT×Market Relevance

OLS
[10]

OLS
[11]

Adj. ROA

Adj. ROE-0.0000293(0.0010)-0.000793(0.0012)0.000565(0.0012)0.0227(0.052)-0.0357(0.047)-0.0342(0.042)-0.00129(0.0018)-0.158***(0.059)0.00548***(0.0014)0.155**(0.064)

ENTFEATENTRY×Input Relevance

0.00624***(0.0015)

0.195**(0.096)ENTRY×Market Relevance（Other firm-specific factors）
ASSET
LEVERAGE
SEG
W&RINDLIST
FOREIGN

0.00159***
0.00882(0.00052)(0.012)0.000522
0.331***(0.0036)(0.12)-0.000995*** -0.00440(0.00032)(0.010)-0.00148
0.0394(0.00099)(0.037)0.00417***-0.0789***(0.0015)(0.029)0.0207-0.0882(0.013)(0.17)

0.00161***0.00919(0.00051)(0.012)0.000527
0.333***(0.0036)(0.12)-0.000934*** -0.00267(0.00032)(0.010)-0.00175*
0.0379(0.00098)(0.036)0.00416***-0.0792***(0.0015)(0.029)0.0208*-0.0923(0.013)(0.17)（Phase dummy）
PHASE II

0.0000498
0.02680.000191
0.0261(0.00084)(0.033)(0.00084)(0.033)Const-0.0151***-0.198*-0.0158***-0.206*(0.0044)(0.12)(0.0043)(0.12)
Obs.
13182
13182
13182
13182
adj. R2
0.01
0.00
0.01
0.00
Notes: Figures in parentheses are standard deviation adjusted for heteroscedasticity(White's correction).
***, **, and * denote coefficients significant at the 1%, 5%, and 10%.

2. Estimation Results
Estimate results are summarized in Table 6. The coefficients of OnlyExit,
OnlyEntry, and BOTH are insignificant. In other words, there is no significant

25difference between performance of the firm which undertakes exit and/or entry andthat of the firm which does not undertake. However, EXTFEAT and ENTFEAT havesignificant effects on FEAT. The interaction term of entry dummy and input relevancy
and term of entry dummy and market relevancy are positively and significantly
correlated with ROA and ROE. The interaction term of exit dummy and input
relevancy is negatively and significantly correlated with ROE and the interaction termof exit dummy and market relevancy is negatively and significantly correlated with
ROA and ROE.
Our estimation results show that conducting exit and/or entry simply does not leadto improvement in performance. If a firm enters into the business which is close to thecore business and/or exits from the business which is remote from the core business,
the firm succeeds in improving its performance. if the firm undertakes both of themsimultaneously, these two effects improve the performance. Regardless of the type, thefirm comes to have a set of businesses around the core business by implementing
business restructuring. It is likely that the firms implementing such strategic
realignment obtain the better business results.
Finally, we briefly review the coefficients of other explanatory variables. SEG has anegative and significant effect on ROA, and then we confirm there is a diversification
discount effect. The coefficient of ASSET is positive and significant on ROA.
Controlling the types of portfolio restructuring and the degree of diversification, thelarger a firm is, the higher the performance of the firm is. LEVERAGE has a positiveand significant effect on ROE, this suggest there exists the so-called “debt discipline.”
Controlling this effect, LIST has a positive and significant effect on ROA whereas it has
a negative and significant effect on ROE. FOREIGN sometimes has a positive effect on
ROE. The coefficient of W&RIND on ROA is sometimes negative and significant. The
coefficient of PHASE II is insignificant.
VI Concluding remarks
This study has investigated the business portfolio restructuring of the diversified
company in Japan. In particular, we focus on the "exit from an existing business" andthe "entry into a new business." This consideration gives us the more effective
information than the previous method of only investigating the change in a firm‟sdegree of diversification because many Japanese firms are inclined to engage in both
exit and enter instead of single-mindedly pursuing exit or enter. To strengthen a set ofbusinesses around the core business, firms implement strategic business realignmentthat combines both offensive and defensive measures. Our analysis shows that a firmwith a faster growing core business exits from existing businesses while a firm with a26

slower growing core business enters into new businesses. It seems to be contradictorythat a firm simultaneously pursues exit and entry. However, it is quite reasonable tothink that a business realignment behavior undertaken by firms is to withdraw frombusinesses remote from the core business and, at the same time, to expand intobusinesses close to the core business.
Moreover, it is the most important that this tendency is observed broadly acrossJapanese firms regardless of their size. It is often said that Japanese firms are slower
in business portfolio restructuring than U.S. and Europe firms, however, our analysis
shows that Japanese firms have engaged in active and reasonable businessrealignment strategy. It is likely that that the extensive employment of such strategy
paved the way for their across-the-board comeback.
Last, let us summarize some future research issues. First, we need to analyze thedecentralization of business governance as we mentioned at first section. It is aninteresting question how division and affiliated company are different in the businessgovernance. In particular, how the business governance change by changing from adivision to an affiliated company by shifting to the pure holding company. Second, we
also need to analyze the business governance as company group including affiliatedcompanies. For instance, the business that a parent company withdrew is transferred
to an affiliated company; and a parent company succeeds the business of an affiliatedcompany. It is also important to examine the decision making process of thesestrategies.
Acknowledgement
We also thank METI for its permission to use the firm-level data from government
statistics.

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