The interdependence of the life cycle and strategic group concepts : theory and evidence

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FACULTY WORKING
PAPER NO. 961

The Interdependence of the Life Cycle and
Strategic Group Concepts: Theory and Evidence

Walter J. Primeaux, Jr.

Coliege of Commerce and Business Aaministration
Bureau of Economic and Business Research
University of Illinois, Urbane-Champaign

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FACULTY WORKING PAPER NO. 961
College of Commerce and Business Administration
University of Illinois at Urbana-Champaign
June 1983

The Interdependence of the Life Cycle and Strategic
Group Concepts: Theory and Evidence

Walter J. Primeaux, Jr. , Professor
Department of Business Administration

THE INTERDEPENDENCE OF THE LIFE CYCLE AND STRATEGIC GROUP
CONCEPTS: THEORY AND EVIDENCE

ABSTRACT

A life cycle theory of investment is developed by adapting models
presented by Kmenta and Williamson (1966). Data for firms from two
diverse industries (textiles and petroleum) are used to determine the
life cycle stage of each of the two industries, as well as the life
cycle stage of each strategic group within the industry. These
results are first generated for the strategic group designation
suggested by Porter (1979). Then, an alternative strategic group
designation suggested by the author was used for the same purpose.
Porter's designation developed superior results for the textile
industry; however, the alternative approach generated better results
for the petroleum industry.

The research results have important implications for future stra-
tegic management research, particularly subsequent studies dealing
with the strategic group and life cycle concepts. These implications
are elaborated upon in the paper.

INTRODUCTION
The strategic group concept and the industry life cycle are both
firmly established in the strategic management literature but they
were introduced at different times as independent ideas. Yet, by
their nature, they relate to each other in some important ways and
are, indeed, quite interdependent. The main purposes of this study
are: first, to examine the theoretical reasons for interdependence
between these two concepts, and second, to examine data which actually
reflect this mutual interdependence and to determine what this rela-
tionship means for empirical research.

PREVIOUS STUDIES

Strategic Groups

Although a germ of the idea can be found in earlier writing, Porter

(1979: 215) credits Hunt (1972) with coining the term strategic groups.

Later, Newman (1978: 417-27) and Porter (1979: 214-227) undertook

further empirical studies and added to Hunt's original contribution.

Porter (1979: 215) emphasized the interdependence of members within a

strategic group in the following statement.

An industry can be composed of clusters or groups
of firms, where each group consists of firms
following similar strategies in terras of the key
decision variables. Such a group could consist
of a single firm, or could encompass all of the
firms in the industry. I define such groups as
strategic groups. Firms within a strategic group
resemble one another closely and, therefore, are
likely to respond in the same way to disturbances,
to recognize their mutual dependence quite closely,
and to be able to anticipate each other's reactions
quite accurately. Between strategic groups, how-
ever, the situation is different.

-2-

Mobility barriers tend to prevent a firm from moving from one stra-
tegic group to another and barriers to entry tend to protect members of
a strategic group from entry by an outside firm. Porter (1980: 133).

The Life Cycle

There is some controversy about whether the life cycle applies to
individual products or to whole industries. (Porter 1980: 157). Rink
(1979) points out that the life cycle concept has been widely applied
to products and Porter (1980: 157) takes the position that the life
cycle concept also applies to industries. Sasser et. al. (1978),
Boulding (1962), and James (1974) further extend the life cycle notion
to the firm level. Some others who have discussed the life cycle con-
cept include: Patz (1981: 127-30), Rumelt (1979: 204-206; 208-209;
211-212; 215), Cooper (1979: 318-325). The propositions presented in
this study are quite compatible with the metamorphosis models pre-
sented in Pugh, et. al. (1969), James (1974), Scott (1971), Salter
(1970), Stopford (1968), and Franko (1974).

The industry life cycle concept presents the idea that growth of an
industry follows an S shaped curve which results from the innovation
process and new product diffusion. Porter (1980: 157) explains that
the life cycle concept has attracted some criticism. The first main
criticism argues that individual industries are different from one
another and that the length of life cycle stages varies significantly
from industry to industry: it is often not clear what stage of the
life cycle an industry is actually in. (Porter 1980: 158).

The second criticism has to do with the certainty that the industry
will proceed from one stage to the next. It is argued that industry

-3-

growth does not always go through the S shaped curve. Stages are some-
times skipped and after a period of decline growth sometimes revitalizes,
(Porter 1980: 158).

The third criticism is concerned with the effect of firm activities
on the industry life cycle. The argument is that companies can affect
the shape of their growth curve through product innovation and reposi-
tioning. (Porter 1980: 162). Obviously, individual firm action could
affect the industry life cycle; this fact illustrates that the second
and third criticisms are closely related.

The above criticisms, at first thought, seem quite significant; yet,
a number of researchers have taken the position that life cycles are
vital constructs and must be used to develop correct analyses of busi-
ness problems. For some examples of these studies see Kimberley
(1980), Faziane (1968), Grabowski and Mueller (1975), Mueller (1972),
Kmenta and Williamson (1966), and James (1974).

The life cycle and strategic group models are both mentioned by
Rumelt (1979: 204-206; 208-209) as fruitful areas for further research.
The strategic group concept, according to Rumelt, constitutes a begin-
ning of a movement away from equating structure with concentration. He
explains, however, that further research on the subject is required.
Rumelt (1979: 212), in discussing the life cycle, says that the appli-
cation of Hatten (1974) and Patton (1976) methods to a competitive group
in Che growth phase and then again in the maturity phase of the life
cycle would be worthy of study. Although this particular study is some-
what different from the research called for by Rumelt, it does examine
life cycles and strategic groups, together, in the same analysis.

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This study also attempts to establish a technique which will be
useful for determining the phase of the life cycle an industry is in,
at a particular time, without requiring previous or future infor-
mation. This technique is essential for accomplishing the main pur-
poses of the study.

THE THEORY
The Firm and Industry Life Cycle

Both firms and industries go through life cycles similar to the
product Life cycle which is frequently described in the marketing
literature (Metzner et. al. 1975: 61-63; and Rink and Swan 1979: 219-
242). This does not mean that a firm or industry moves sequentially
from one stage to the next and ultimately dies as should be expected
according to Penrose (1952: 305-806). Instead, as Porter (1980: 158)
explains, sometimes stages of an industry life cycle are skipped and
sometimes industry growth revitalizes after a period of decline. Of
course, an industry is merely a collection of firms possessing very
similar prescribed characteristics; consequently, changes in an
industry occur because of changes which take place within firms in that
industry. As mentioned earlier, Sasser et. al. (1978: 538-541), James
(1974) and Boulding (1962) have developed analyses using a firm life
cycle.

A Strategic Group — Life Cycle Theory of Investments

The president of one of our largest oil companies, who
was pushing through a program of drastic decentraliza-
tion of management, stated recently that the last
thing he would delegate would be decisions about capi-
tal expenditures. This is understandable because
capital expenditure decisions form the framework for

-5-

a company's future development and are a major deter-
minant of efficiency and competitive power. The wisdom
of these corporate investment decisions, therefore,
has a profound effect upon a company's future earnings
and growth (Dean 1954: 571).

This quote from one of the foremost business consultants and academic
business economists indicates the significance of the investment deci-
sion. First, Dean indicates that it tends to be a top management deci-
sion; second, investment decisions form the framework for a company's
future development; third, investment decisions determine firm effi-
ciency and competitive power. It is important to point out that
investment, as used in this study, refers to investment in capital
equipment, such as plant and equipment, not financial investments,
such as stock or bonds.

Certainly, investment is an important strategic decision variable
as discussed by Hofer and Schendel (1978: 106-107) and Dean (1954:
571). Investment would qualify as a key decision variable in the
discussion by Porter (1979: 215). From the work of these authors, and
from the earlier discussion of the importance of corporate investment
decisions, it follows that a collection of firms following similar
strategies, in terms of their investment behavior, would constitute a
strategic grouop. James (1974) concludes that a single investment
model would be inappropriate for a given firm, all of the time. That
is, investment behavior of firms changes as they move through what
James calls a corporate life cycle.

The above discussion shows that firm investment decisions are
influenced by two key determinants; first, their strategic group mem-
bership and second the corporate life cycle to which they belong. The

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above discussion reveals that there is significant interdependence,
through investment decisions, between strategic group membership and
the life cycle of a firm. That interdependence is the central focus
of this research.

Overall, future earnings and growth of the business are affected
in a significant way by the investment decisions of a firm. All of
this leads to the conclusion that investment decisions impact upon
firm strategy in very important ways; this fact is confirmed by Hofer
and Schendel (1978: 106-107).

Strategic Groups Within an Industry

Primeaux (1983) argues that since industries are composed of stra-
tegic groups, that all firms within an industry are not necessarily in
the same stage of the industry life cycle. Indeed, in the life cycle
theory of investment, presented by Kmenta and Williamson, all firms
within an industry do not react in the same way to particular events
and conditions existing in their economic environment. These hypo-
theses are all consistent with the corporate life cycle theory pre-
sented by James (1974: 49-55).

The main point is, that individual firms within an industry are not
all in the same position with respect to strength and opportunities, so
they will follow individual strategies which may differ significantly
from those employed by other firms within the same industry; yet, as
Porter (1979: 215) explains, an industry is composed of a cluster of
firms, each group following similar strategies in terms of key decision
variables. These clusters of firms constitute strategic groups.

-7-

From the above it follows that the industry life cycle concept Is
really an average life cycle of all firms within the industry and all
firms or strategic groups within an industry are not in the same stage
of the industry life cycle. (Primeaux 1983).

Two questions emerge from the above discussion. First, whether
any strategic group study should also simultaneously examine industry
life cycle influences upon firms within the particular strategic group
being examined. Second, should any industry life cycle study also
consider influences of strategic group differences within the
industry. Research results developed in the following section are
useful for answering these two important questions.

THE MODELS

As mentioned earlier, James (1974) has established that firm
investment follows a life cycle pattern as a business adjusts its
capital expenditures to the circumstances in which it finds itself.
These conclusions are consistent with earlier empirical results devel-
oped by Kmenta and Williamson (1966: 172-181). These researchers have
shown that a single investment model is inappropriate for all stages
of an industry's lifetime. Since an industry is merely a collection
of firms of similar characteristics, the variation in industry invest-
ment behavior must originate from changes in firm investment behavior
through time.

Multiple regression analysis was used to develop the statistical
results used in this research. Kmenta and Williamson's industry life
cycle models were adapted for the firm strategic group — life cycle anal-
yses which are central to this investigation. The entire theory upon

-8-

which these adapted models are based is presented in the Appendix and
only a very abbreviated discussion is presented here.

Kmenta and Williamson' s empirical research found a three stage
cycle as reasonable and logical; an initial stage of adolescence, a
second period of maturity and a third stage of senility. Their analy-
sis can be profitably extended to firms instead of industries. It is
important to repeat that these stages need not occur sequentially;
stages may be skipped, and a firm could reposition itself to an
"earlier" stage by strategic action taken by its management.

Model of Adolescence Stage

The model of the adolescence stage follows:

(1) I* = aQ + hXt.2 - a2Kt_2 + a3(1r*/K)t_2 + *p*t-C**-2>

+ Vt-1 + V + \

N
where I = net investment.

X ■ operating revenue.

K = capital stock at the end of each period,
ir* = net operating income after depreciation.
r , = interest rate proxy variable.

t = R&D proxy variables

U = error term
The constant term, a_, provides for the existence of autonomous
investment. A more extensive discussion of the variables used in
equation (1) and the equations which follow is presented in an
appendix.

-9-

Model of Maturity Stage

The model of maturity stage is:

(2) ij - aQ + alXt.2 - a3Kt.2 + a.r^ + a5c + S,.

The variables in equation (2) are defined as in equation (1).

Model of Senility Stage

The model of the senility stage is as follows:

(3) I» = aQ + a1Kt_1 + a3»**t_1 + .f^ * f * U£

The variables common to equation (1) are defined as in that equation;
and tt** is net income (including non-operating income).

The statistical evidence developed from the above equations is
presented in the following section.

THE EVIDENCE
Method

The statistical analysis used in this research is ordinary least
squares regression analysis.

The three investment life cycle equations, presented in the above
section, were run for firms in the textile and petroleum industries.
The petroleum industry is certainly more capital intensive than the
textile industry. It was thought that this diversity could affect
investment strategies of the strategic groups within the industries
and that the contrast would be worthy of examination. Moreover, the
number of industries was limited to simplify exposition of the

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research results without only limiting this information to summary
tables.

The research uses available data since World War II; 1961-1980,
representing twenty years of operations. The raw firm data for the
selected industries were taken from Compustat tapes.

Data for all firms included in the sample from a given industry
were summed to obtain industry data; then, the three investment life
cycle equations, adapted from Kmenta and Williamson (1966), were indi-
vidually estimated with the same industry data. The model of the
stage which best reflects industry investment behavior would identify
the stage of the life cycle the industry is actually in. This method
permits a researcher to gain a better understanding of the investment
strategy and behavior of the industry as a whole and the life cycle
stage of the industry is clearly identified through this procedure.

Textile Industry

Table 1 presents the multiple regression equation for the three
stages of the textile industry life cycle. The industry equations
are: (1), (4), and (7). The results show that equation (1), repre-
senting the adolescence stage of the life cycle, seems to best fit

—2
the data for the textile industry. That is, according to R , the

adolescence equation explains a greater percentage of change in net

investment for the whole textile industry (.80) than either the

maturity stage (.35) or the senility stage (.42). This procedure,

therefore, identifies the textile industry (that is the aggregate of

all firms) as being in the adolescence stage of the industry life

cycle. Whenever autocorrelation was indicated to be present in these

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regressions and those presented throughout this paper, the problem was
corrected by employing the Cochrane and Orcutt Interactive Least
Squares Method as discussed in Murphy (1973: 314-316).

(Place Table 1 Here)

The above procedure identifies the life cycle stage the shoe
industry is actually in but it does not establish whether or not all
firms within the industry are in the same stage of the life cycle. The
strategic group concept, in conjunction with the procedure discussed
above, was used to generate further useful information in an attempt to
answer this question.

Porter divided each industry in his sample into two parts, which he
designated as leaders and followers and the relative size of a firm in
its industry was used as a proxy for its strategic group membership
(Porter 1979: 220). Firms in the textile industry were divided into
two categories, leaders and followers, according to Porter's method of
identifying strategic groups. Leaders were defined as the largest
firms in the industry (accounting for approximately 30 percent of
industry revenue); remaining firms constituted the follower group.
Data from each subset of firms were summed to obtain the two strategic
groups of the industry. The three life cycle investment equations
were then run for each strategic group in the industry.

The same investment life cycle stage equation would best explain
the investment behavior of both strategic groups, only if the two stra-
tegic groups are in the same stage of the life cycle. However, the
conclusion would be that the two strategic groups are in two different

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stages of the industry life cycle if one life cycle equation best ex-
plains one strategic group's investment behavior and another explains
the investment of the other strategic group.

Equations (2), (3), (5), (6), (8) and (9) in Table 1, present the
results of the strategic groups multiple regressions for the textile
industry, using the (30 percent-70 percent) designation presented

by Porter (1979: 214-227). Equation (2) is the best equation for the

—2
leading firms, with R of .855. This indicates that the leading

firms in the textile industry reflect investment behavior charac-
teristic of the adolescence stage of the industry life cycle. The

following firms, however, reflect investment behavior characteristic

—2
of the maturity stage; R for the following firms was .374. These

results reveal that when Porter's strategic group designation is used,

leaders and followers are not in the same stage of the life cycle.

Consequently, their investment strategies are different. Moreover,

they probably differ in several other important respects as suggested

in the life cycle research such as James (1974), Sasser et. al.

(1978), and Boulding (1962).

Moreover, the results also show that all strategic groups are not
in the same stage of the industry life cycle. In this industry, the
leader strategic group is in the adolescence stage as is the industry;
yet, the follower group is in the maturity stage.

Porter (1979: 220) refers to his 30 percent-70 percent strategic
group designation as arbitrary. Indeed, as McGee (1983) points out, a
number of possible methods exist for determining strategic groups
within an industry.

-13-

The appropriate designation of strategic groups is actually beyond
the purposes of this research. The objectives here were to determine
whether alternative strategic group designations would yield different
statistical results and to tentatively determine whether the methods
applied here could also be used for establishing appropriate strategic
group designations in future research.

Toward accomplishing the major purpose of this research, assume the
alternative strategic group designation suggested in Primeaux (1983);
instead of Porter's 30-70 percent size designations, three strategic
groups may exist, and the appropriate breakdowns should be, say, one
strategic group accounting for 20 percent of sales, another accounting
for 30 percent and another accounting for 50 percent.

Table 2 presents, the life cycle equations for. the 20-30^-50 percent
alternative strategic group designation for the textile industry.
This assessment requires a comparison of equations (2) and (3) of
Table 1, with (1), (2), and (3) of Table 2; a comparison of (5) and
(6) of Table 1 with (4), (5), and (6) of Table 2; and a comparison of
(8) and (9) of Table 1 with (7), (8), and (9) of Table 2. From the
alternatives in the two tables, equations (3) and (6) of Table 1 are
the best. In this instance, the results of Porter's designation sur-
pass those of the suggested alternatives. The 20-30-50 percent stra-
tegic group designation does not provide regression results which are
as good. However, the alternative designation does yield superior
results for the petroleum industry which is discussed below.

(Place Table 2 Here)

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Petroleura Industry

The same methods and procedures used to develop equations for the
textile industry were also used to develop equations for the petroleum
industry.

Primeaux (1983) has previously examined the petroleum industry

using Porter's method of strategic group determination, and presented

statistical results identical to that in Table 3. He reached the

following conclusions for the petroleum industry as a whole:

The results show that equation (1), representing the
adolescence stage of the industry life cycle seems
to best fit the industry data. That is, according to
r2, the adolescence equation explains a greater per-
centage of change in net investment for the whole
petroleum industry (.79) than either the maturity
stage (.25) or the senility stage (.31).

(Place Table 3 Here)

Table 3, equations (1), (4), and (7) support the above statement; the

petroleum industry seems to be in the absolescence stage of the

— 2
industry life cycle (R » .79).

The strategic group designation developed by Porter, however, does

not fare as well as the alternative designation for the petroleum

industry. Primeaux (1983), using Porter's strategic group designation,

identified the leading firms as being in the senility stage of the life

—2
cycle (Table 3, R = .43) and the follower as being in the adolescence

—2
stage (Table 3, R = .81). Table 4, however, reveals that Porter's

strategic group designation (in Table 3) for the petroleum industry does

not seem to be as effective as the Primeaux alternative.

(Place Table 4 Here)

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The alternative strategic group designation, using 20 percent, 30

percent and 50 percent, identifies the top 20 percent group as being

— 2
in the maturity stage (R = .78); the next 30 percent group as being

— 2
in the adolescence stage (R = .95); and the remaining 50 percent

_2
group as also being in the adolescence stage (R = .46). These

results are clearly superior to those developed with Porter's strate-
gic group designation. These results, along with those developed for
the textile industry, confirm two important facts. First, Porter's
designation is, indeed, arbitrary as he suggested. That his, his
30-70 percent strategic group designation is not appropriate in every
circumstance. Second, it is very likely true that different
industries require a different strategic group designation. While
Porter's designation is superior for the textile industry, it was
clearly inferior for the petroleum industry. This does not claim that
the alternative procedure provides the most appropriate strategic
group designation; however, it does demonstrate how the statistical
technique presented here can be used in future research to select the
appropriate strategic group designation from among several reasonable
alternatives.

CONCLUSIONS
This study shows that there is substantial interdependence between
the strategic group and the life cycle concepts. Indeed, it actually
seems impossible to discuss one without considering the other; these
results seem to show that future research should deal jointly with
these ideas.

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The life cycle concept cannot be ignored; yet, it seems crucial
that the concept be applied to strategic groups within an industry,
rather than to an industry as a whole. The results show that, in the
textile and petroleum industries, different strategic groups are in
different stages of the life cycle. The analyses also show that the
life cycle of an industry differs from the life cycles of the strate-
gic groups within an industry. These findings do not diminish the
value of the industry life cycle concept. Instead, they suggest that
it is important to also consider strategic group life cycles whenever
life cycles are discussed.

The strategic group concept is firmly entrenched in the strategic
management literature. Yet, past research has not determined the most
appropriate approach for determining strategic group membership. The
results of this study shows that alternative strategic group designa-
tions yield significantly different results. The implications of
these findings for future research are rather clear. It is crucial
that future research be concentrated on methods of strategic group
membership determination to enhance the value and integrity of future
strategic management studies.

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D/129

APPENDIX
EXPLANATION OF VARIABLES USED IN REGRESSION MODELS

N
I is net investment deflated by q (in millions of dollars).

X is operating revenue deflated by q (in millions of dollars).

K. is capital stock deflated by q (in millions of dollars).

tt* is net operating income before depreciation deflated by q (in
millions of dollars).

it** is total net income deflated by q (in millions of dollars).

IT*

rr— in (1) is given in percentage rates.
K

r the interest rate proxy variable is the real corporate bond rate,
lagged 1 year. Specifically, the industrial average was used for
the industry equations; the triple A (AAA) rate was used for the
leading firms; and the double A (AA) rate was used for the follow-
ing firms.

t the R&D proxy. A time trend (1 for the first time period, n in
the final time period.

q is the price deflator. (The implicit price deflator for producers
durable equipment.) From the Economic Report of the President.

APPENDIX A

THEORY-LIFE CYCLE INVESTMENT

The following theoretical discussion of a three stage life cycle
is an adaptation from the industry analyses presented in Kmenta and
Williamson (1966: 175-177). These discussions draw heavily from their
work and explain how the three life cycle stages differ from one
another as well as the firm investment behavior characteristic of each
stage. The industry and firm behavior, reflected in each stage, are
discussed simultaneously. The theory presented here is the basis of
the multiple regression models which are developed in the text of the
paper.

Adolescent Stage .

In the adolescent stage, entry of firms into the industry is rela-
tively frequent. New investment is undertaken by firms already in the
industry and in part from firms entering the industry for the first
time. The "old" firms operate with a given quantity of fixed capital
constructed in the past in anticipation of future long-run demands.
Existing capital stock within the industry "...might be considered
optimal for a given anticipated demand for output, which may include a
certain degree of planned excess capacity." (Kmenta and Williamson
1966: 17 5). If the demand for the product or service increases, capa-
city will be inadequate to satisfy consumer needs. Provided excess
capacity exists, absolute levels of profits and profit rates will in-
crease. If a firm is already operating at full capacity, higher per
unit cost must be incurred to satisfy increases in demand. Higher

• -2-

prices will then result, or firm profits will cease to grow or even
begin to decline. The firm may attempt to charge higher prices and/or
expand fixed capital by increasing investment. Increases in price are
less likely to be made in theory. (This action comes from a strategy
of attempting to restrict competition.) "Old" firms may not wait until
all excess capacity is eliminated; instead, they may undertake new
investment as capacity utilization increases and full capacity is
approached. The investment decision of firms already in the industry
will probably be based on the relationship "...of the existing stock of
capital to that which would be optimal under prevailing output condi-
tions." (Kraenta and Williamson 1966: 175).

One underlying assumption is essential to the above theory. This
assumes that firms believe the increases in demand to be permanent;
without this expectation, there would not be any rational basis for
enlarging capital stock on the basis of past increases in demand.

Research and development, of course, can be an important force
affecting investment decisions within a firm. This effect is largely
caused by the cost reducing effects of certain types of investments.
This effect, of course, is not even. Kmenta and Williamson (1966: 176)
found this effect to be unimportant in the railroad industry, however,
it would probably be significant in most other industries.

The rate of interest, of course, affects investment decisions in
most businesses. Firms must weigh the cost of anticipated additional
investment against the expected rewards from that investment; interest
costs cannot be ignored in this type of decision.

-3-

For the industry as a whole, investment is carried out both by firms
already in the industry as well as new firms entering. New firms
obviously face a greater risk, element. "The firmest basis for esti-
mates of future returns on capital is the profit experience of the
existing firms. New firms will be induced to enter if the existing
firms are exhibiting high profit rates, and especially if profits are
showing an upward trend. . .because of the time needed for decision-
making, capital raising and construction, a two-year lag is likely to
be most appropriate." (Kmenta and Williamson 1966: 176). The two
types of investment behavior, discussed above, can be combined into a
single model of the adolescence stage of the industry life cycle.

(1) I* - aQ + alXt_2 - a2Kt_2 + a3(,*/K)t_2 + a4(,r*t_i - f^) +

acr . + a, t + U
5 t-1 6 t

N
where I = net investment

X = operating revenue

K. = capital stock at the end of each period

n* = net operating income after depreciation

r = interest rate proxy variable

t = R & D proxy variable

The constant term, a , provides for the existence of autonomous

investment.

Maturity Stage

This stage of the industry life cycle "...is characterized by con-
solidation of the existing firms since there is now very little room

-4-

for opening up of new territories, and thus only a limited opportunity
for new entries." (Kmenta and Williamson 1966: 177).

In the maturity stage, significant reorganization takes place
within the industry because of the new pattern of market distribution,
mergers occur "...at a peak rate, and profits run at a relatively high
and secularly stable level." "Old" firms within the industry still
undertake new investment, if their existing capacity is inadequate.
Disinvestment may take place if significant excess capacity exists.
New entries are rare in this phase of the life cycle, "...the profit
variables are less likely to be relevant." (Kmenta and Williamson
1966: 177). The investment function for the second stage (its middle
age) of the industry's life cycle is:

(2) I* = aQ + aft_2 - a3V2 ♦ Vtrl * a5t + St

The variables in equation (2) are defined as in equation (1).

Senility Stage

This stage is one of slow growth or even decline as substitutes are
developed or consumers lose interest in the products produced within the
industry. Some firms leave the industry; net investment is motivated
by technological changes. In this stage growth is not the main concern,
it is survival. External sources of funds become more difficult to
obtain; moreover, firms are disinclined to go to capital markets for
financing for fear of losing control. Profits are plowed back into the
business to enhance survival possibilities and internal financing is of
much importance in this stage of the life cycle.

-5-

Because of the overall conditions existing in this stage of the
life cycle, changes in output and profitability "...are largely irrele-
vant for investment decisions because they have very little relation to
the long-run prospects of the industry." (Kraenta and Williamson 19 66:
177).

The financial situation of firms will now become
relevant since the firm's earning level is the
major source of finance. The level of past profits
thus assumes a new role. Instead of being an indi-
cator of future profitability, profits now become
an indicator of the availability of funds. (Kmenta
and Williamson 1966: 177).

The investment function for the third stage of the industry's life cycle

is:

(3) I* = aQ + alVl + y-^ + Vtrt + a5t + 0t

The variables common to equation (1) are as defined in that equation;
and ir** is net income (including non operating income). This modifica-
tion was made in the third stage model because income from all sources
is relevant when availability of finance becomes crucial. The lag is
changed from two years to one year because in this stage there is
probably a decline in the importance of investment of longer gestation
and the investment planning horizon is probably shortened to the
fullest extent possible.

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IBound -To-Pk-a,^ N. MANCHESTER
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