HOW FIRMS SHAPE MANAGERS: THE INFLUENCE OF FIRM DEVELOPMENT
ACTIVITY ON TOP MANAGERS’ TURNOVER
Freek Vermeulen
London Business School
Regent’s Park
London
NW1 4SA
United Kingdom
E-mail: FVermeulen@london.edu
Phone: +44 (0)20 7262 5050
Fax: +44 (0)20 7724 7875
&
Harry Barkema
Department of Organization & Strategy
Tilburg University
PO Box 90153
5000 LE Tilburg
The Netherlands
E-mail: Barkema@kub.nl
Phone: +31 (0)13 466 2315
Fax: +31 13 (0)13 466 2875
We thank Maayke Brants for data collection, and seminar participants at London Business
School for useful comments.
HOW FIRMS SHAPE MANAGERS: THE INFLUENCE OF FIRM DEVELOPMENT
ACTIVITY ON TOP MANAGERS’ TURNOVER
Abstract:
An increasing body of literature suggests that the personal characteristics of top
managers influence the strategic development of the firms they head. In this paper,
we wish to add a new perspective to this literature, and argue that the development
path of a firm will also shape the manager. Involvement in strategic activities geared
towards the internal development of the firm makes managers build up commitment
and emotional investment in the organization. In contrast, managers who spend a lot
of time buying and selling off businesses will build up little social capital within the
firm. We apply this perspective to examine the influence of firm development activity
on top managers’ turnover, using event history analysis on the tenure of 437 top
managers. The results show that internal reorganizations, as well as organic
expansion decrease the likelihood that top managers will exit, irrespective of the
firm’s performance. Engaging in divestitures, as well as engaging in acquisitions
increases the probability that a top manager will leave the firm. Overall, the results
help paint a more complete picture of the relationship between top management and
firm strategy.
2
In response to the body of research that examines organizations from the
perspective of population ecology, pioneered by the work of Hannan and Freeman
(1977), and the resulting questions in the literature whether management actually
matters (e.g. Thomas, 1988), a stream of literature has emerged over the last decade
that examines the relationship between the characteristics of top managers and the
strategic decisions made by their firms. This research has made clear that individual
managers may have considerable influence on the strategic direction a firm takes.
Characteristics in terms of managers’ prior experiences, personality, and background
have been shown to determine their perceptions of strategic opportunities (Sutcliffe,
1994; Tyler and Steensma, 1998), investment decisions (Barker and Mueller, 2002;
Young, Charns, and Shortell, 2001), tendency to innovate and diversify (Bantel and
Jackson, 1989; Wiersema and Bantel, 1992), choice of organizational structure (Lewin
and Stephens, 1994; Miller and Droge, 1986) and, ultimately, financial performance
(e.g., Daily, Certo, and Dalton, 2000;Norburn and Birley, 1988). In addition to this
insight that different individuals make different strategic decisions, research by for
instance Hambrick and Fukutomi (1991) and Miller and Shamsie (2001) indicated that
the same manager may also make different choices at different points in time;
strategic decisions are influenced by the life and career stage of the executive; a
claim supported by research by Boeker (1997a) and Finkelstein and Hambrick
(1990), which also showed that executive tenure has an important influence on the
strategic actions of companies, what they do, and how successful they are.
A complementary topic, which has received attention in both the Finance (e.g.
Furtado and Karan, 1990; Weisbach, 1995) and Management literatures (e.g.
Boeker, 1997b; Miller, 1993), dealt with the consequences of top management
turnover, and found it to have considerable impact on both the state and performance
3
of a firm. Taken together the overall picture that these different bodies of research
paint is clear: different managers make different decisions, at different points in their
tenure and, therefore, if these top executives are changed, firms often undergo
strategic change as well. Notwithstanding these findings, we, however, believe that
this picture is a bit too static, or better, too uni-directional. Surely, individual managers
may have a considerable impact on the strategic development of an organization but
we believe that the relationship runs the other way around as well; the particular
development stage a firm is in (Quinn and Cameron, 1983; Vermeulen and Barkema,
2001) will affect what kind of work the executive is doing and what sorts of actions he
or she is undertaking. As a result of this, managers will develop different forms and
levels of commitment towards their organization. Particularly, in this paper, we argue
that the time spent on internal affairs, such as managing organic growth and
reorganizations, which we will call “cultivation”, will create internal networks for
managers and increases their commitment to the organization, making it more likely
that executives will choose to stay at the firm. External dealings, i.e. buying and
selling off businesses, which we will label “compilation” activities, creates more social
capital outside the firm, making it more easy for a top manager to switch positions
and leave the firm. Hence, we argue that top management and top management
turnover are not only the drivers of strategic actions, but that the particular strategic
development activities that they command in turn also influence the likelihood of their
turnover.
In particular, in this paper, we will present an event history analysis where
different variables measuring cultivation activities and variables measuring compilation
activities will be regressed on the probability that a top manager will leave the firm.
Modelling top management turnover is a logical choice since our theory emphasizes the
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consequences of organizational actions for the commitment of an executive to the firm.
Commitment, in social psychology, has been conceptualized as “a psychological state,
or mind-set, that increases the likelihood that an employee will maintain membership in
an organization” (Meyer and Allan, 1991). Therefore, we will build hypotheses on how
organizational actions, such as organic growth, reorganizations, acquisitions, and
divestitures, will influence the likelihood that top managemers will maintain or terminate
their tenure at their firms. We will test these predictions using a longitudinal database on
437 top managers, tracked over a period of over three decades (1966-1999). The
results strongly corroborate a key implication of our theory; that the particular strategic
actions that a manager experiences will impact his or her commitment to the firm and
ultimately, with it, their likelihood of departure.
HOW FIRM DEVELOPMENT PATHS DRIVE TOP MANAGERS’ TURNOVER
Organizational Commitment.
The form and level of commitment of an employee to an organization has
received considerable attention as a topic in social psychology research.
Commitment is seen as a person’s inclination to retain membership of an
organization (Meyer and Allan, 1991). Indeed, a number of studies have observed
strong relations between psychological measurements of organizational commitment
and actual turnover (for a review, see Mathieu and Zajac, 1990). In a series of studies
by Allen and Meyer (1990; Meyer and Allen, 1984; 1991) commitment was
conceptualized as consisting of three different types; affective commitment,
continuance commitment, and normative commitment, which was empirically
validated in later research by, for instance, Hackett, Bycio, and Hausdorf (1994),
5
Allen and Meyer (1996), and Herscovitch and Meyer (2002). Affective commitment
refers to a person’s emotional attachment to, identification with, and involvement in
the organization. Because individuals have an affective attachment to the
organization, they are committed to pursue its goals. Individual with strong affective
commitment to a firm enjoy membership of the organization (Allen and Meyer, 1990;
McFarlane Shore and Wayne, 1993). Continuance commitment, in contrast, refers to
commitment based on the costs that someone associates with leaving the
organization. It is more calculative, and a reflection of recognized, accumulated
interests (e.g. pensions, seniority, etc.). Finally, normative commitment refers to a
person’s feelings of obligation to stay with the organization.
Although commitment to an organization may partly be determined prior to an
individual’s entry – for instance, feelings of normative commitment may result from
the internalization of normative pressures exerted on the person through familial or
cultural socialization – most commitment will be build up following entry, through
organizational investments and socialization (Hackett, Bycio, and Hausdorf, 1994).
Hence, the specific experiences that individuals go through in an organization and the
actions that they undertake will shape their level of commitment to the firm (Dickter,
Roznowski, and Harrison, 1996). For instance, the commitment of top managers who
spend much time inside their organizations will form differently than managers who
are heavily involved in activities outside the firm. Thus, the concept of commitment is
related to issues of social capital and the value of internal and external networks
(Garguilo, 1993; Ibarra, 1993; Tsai and Ghoshal, 1998). Managers who are actively
involved in the internal development of their organization will interact with many
people inside the firm, and will build up firm-specific knowledge and internal
networks. This will make it costly for them to switch organizations, since they would
6
loose this firm-specific social capital, which would take considerable time and
investment to rebuild in a new organization. In contrast, managers who spend a
considerable amount of time outside the firm, heavily involved in deal-making, do not
build up these firm-specific investments. Moreover, they will obtain contacts outside
the firm, which may facilitate their changeover to a different employer. Thus,
commitment is driven by the experiences that people go through in their
organizations. For top managers this means that the strategic activities that a firm is
involved in as a whole, will shape the networks and social capital that they build and,
with it, their commitment to the organization.
Management as Cultivation versus Management as Compilation
We know from research on organizational life cycles (Greiner, 1972; Quinn
and Cameron, 1983) and firm development paths (Noda and Collis, 2001; Vermeulen
and Barkema, 2001) that firms go through different stages during their existence.
Some periods may be characterized by internal development and growth, while others
demand restructuring and reorganization (Tushman and Romanelli, 1985). Moreover,
organizations may expand in different ways, for instance by acquiring other companies
or through the internal development of greenfield ventures. Firms are not restricted to
one of these modes, but may combine or alternate them over time (Vermeulen and
Barkema, 2001). These different strategic actions reflect in the activities that top
managers perform. Acquisitions, for instance, require top managers to spend a lot of
time on screening take-over candidates, price negotiation, etc. Internal firm
development requires close engagement in, for example, management programs
(Rodgers, Hunter, and Rogers, 1993). We distinguish between two broad sets of
activities that managers undertake. On the one hand, management actions that are
7
geared to grow and develop a firm organically. We label this organizational ‘cultivation’.
In order to do this, top executives must play an active role managing the internal
organization of the firm. On the other hand another important task of top management is
to manage the composition of the company’s portfolio of businesses. We label this
organizational ‘compilation’. Activities that a top manager employs for this task center
around the buying and selling of businesses.
The specific way in which a firm is developing will influence how much time
and effort top managers spend on activities of cultivation and compilation, and with it
how their organizational commitment evolves. Some periods may be characterized by
organizational cultivation, during which a top manager will spend a lot of time inside
the firm, building relationships and designing work processes and structures
(Hambrick, Nadler, and Tushman, 1998; Nahavandi and Malekzadeh, 1993). Activities
of compilation will imply that the networks and social capital that the top managers
develop, in interaction with the selling or acquiring corporations, investment banks,
etc., largely take place outside the firm. These external activities lead to external
networks and knowledge, and are much less, or not at all firm-specific.
Hypotheses
Cultivation and the likelihood of top managers’ exit. Firms change and
develop over time. Periods of stability often alternate with periods of reorganization
and restructuring (Miller and Friesen, 1980; Tushman and Romanelli, 1985). These
periods of reorganization are often difficult and painful for the people involved since
they usually require fundamental adaptations of work processes, responsibilities,
structures, and mental models. Effective reorganizations require the close
involvement and commitment of top management (e.g. Kotter, 1995; Rodgers,
8
Hunter, and Rogers, 1993; Wetlaufer, 1999). Engaging in internal reorganizations can
be expected to increase a manager’s commitment to an organization, in all its
dimensions. By reshaping a firm through programs of organizational transformation
top managers build ties with employees (Ibarra, 1993) and firm-specific knowledge
about products, work processes, internal power coalitions, etc. (Garguilo, 1993).
These ties imply costs of leaving and switching organizations. Moreover, top
managers may lose general credibility if they leave shortly after a fundamental
organizational re-design. Furthermore, reorganizations ask for a manager’s close,
emotional engagement, which will heighten identification with the goals of the firm
and its new course, increasing affective commitment. Likewise for normative
commitment. Top management will need to convince the people in the organization of
the purpose and necessity of the change, propagating the benefits of the renewed
organization. This will build a sense of obligation, and commitment to the future of the
firm. It will also bring about a forward-looking perspective in the manager’s relation
with the organization (McGrath, 1988). Reorganizations are experienced as a starting
point in time, rather than an endpoint (Ancona, Okhuysen, and Perlow, 2001). The
increased commitment, brought about by engagement in internal reorganizations,
makes it more likely that top managers will continue their tenure at the firm.
Hypothesis 1: Internal reorganizations are negatively related to the probability
of a top manager’s exit.
Likewise, setting up greenfield ventures is expected to decrease the likelihood
that individual top managers will leave a firm. Start-ups are often the initiative of top
management. As such they are associated with both affective and normative
commitment. New ventures offer a signal of what top management wants to achieve
9
with the firm, and the direction they want to take. They will usually be closely involved
in the decision making around the set up of the new subsidiaries. Although distinct
points in time, greenfields may bring about a more continuous and forward-looking
perception of time, in a manager’s relationship with his organization. The greenfields
are the beginning of a new venture, which will need to be nourished and grown into a
profitable operation. This will give managers a focus on the future (McGrath, 1988;
Zaheer, Albert, and Zaheer, 1999). Moreover, the management of a newly formed
subsidiary will often be carefully selected and hand-picked by the company’s top
management. This will lead to social relationships and effective network ties, all of
which strengthens a top manager’s bond with the firm, both emotionally and in terms
of continuance commitment, i.e. the costs associated with leaving and having to
rebuild such valuable relationships in a new company. Therefore, we expect that
setting up greenfields will make managers inclined to continue their tenure at a firm.
Hypothesis 2: Greenfield ventures are negatively related to the probability of a
top manager’s exit.
Compilation and the likelihood of top managers’ exit. Another important
managerial task, which top managers of large corporations undertake, is managing
the composition of the company’s portfolio of businesses. It represents activities that
treat a company as a compilation of businesses. This implies buying and selling of
businesses, to alter, extend, or eliminate involvement in certain lines of activities, in
order to expand or change strategic direction. The reasons behind buying or selling
certain businesses may be multiple. They may mirror a firm’s particular development
stage (Greiner, 1972), need for revitalization (Vermeulen and Barkema, 2001), or the
individual preferences of top managers (Kets de Vries and Miller, 1984; Miller and
10
Shamsie, 2001). For instance, firms have been shown to refocus through divestitures
for reasons of poor performance, ineffective strategy, overdiversification, and
institutional pressures (Johnson, 1996; Markides, 1992).
Deal-making, whether it involves take-overs or sell-offs, however, is timeconsuming and requires much managerial effort and investment (Hitt, Hoskisson, and
Ireland, 1990, Hitt, Hoskisson, Ireland, and Harrison, 1991). The compilation activities
will affect the organizational commitment that a top manager develops. Divesting
companies, for example, will not lead to many useful social ties with people within those
divisions. More likely, spinning off or terminating businesses eliminates existing network
ties, making it less costly for a manager to terminate his or her tenure at the company,
and switch to a different firm. Hence, divestitures can be expected to decrease
continuance commitment. Likewise, affective commitment will likely not be stimulated
through divestment activity, since the top manager does not build up social
relationships. On the contrary, abstaining from strong affective and normative
commitment may actually facilitate divestment activity, since a strong emotional
attachment to the ventures could lead to escalation (Ross and Staw, 1986; Whyte,
1986). Furthermore, divestitures may give a manager a sense of completion, marking
an end point in time (Ancona, Okhuysen, and Perlow, 2001; Zaheer, Albert, and
Zaheer, 1999). The “mandate” of a manager (Hambrick and Fukutomi, 1991) may be to
“clean up the company’s portfolio”, making it easier for managers to terminate their
affiliation “after a job completed”. Hence, divestments may decrease top managers
emotional and social involvement with the organization and, hence, make it more likely
that they will discontinue their tenure. Thus:
Hypothesis 3: Divestment activity is positively related to the probability of a top
manager’s exit.
11
Likewise, engaging in acquisitions may decrease a top manager’s stay at the
firm. Managers engaged in acquisitions spend much time on making the deal
happen; screening and selecting candidates, engaging in negotiations, due diligence,
etc. All this time is spent outside the firm, i.e., not on building relationships within the
company (Hitt, Hoskisson, and Ireland, 1990, Hitt, Hoskisson, Ireland, and Harrison,
1991). The networks and knowledge acquired through these activities are not firmspecific. They can largely be transfered when a manager accepts a position at a
different firm. Hence, there are fewer costs associated with leaving a firm. Actually,
external networks are known to facilitate moving on to a new position (Granovetter,
1974; Lin and Dumin, 1986; Montgomery, 1992; Wegener, 1991). Furthermore, the
acquired parts of the company have existing social relationships in place, and existing
management and employees, not selected by top management. They do not share a
common history, that would create bonding and identification with one another (Schein,
1985). This lowers both affective and continuance commitment. Additionally, similar to
divestment activity, after deals have been completed top managers often have a
sense of achievement and the notion of the completion of a task. This makes it
justifiable to themselves and to the outside world to leave their position, i.e.,
normative commitment is relatively low after a period of intense acquisition activity.
Moreover, it leads people to have a discrete, backward looking notion of time
(Ancona, Okhuysen, and Perlow, 2001; McGrath, 1988), making it a natural point to
terminate an affiliation. Therefore, we predict that:
Hypothesis 4: Acquisition activity is positively related to the probability of a top
manager’s exit.
12
METHODOLOGY
Data
The hypotheses were tested on a database regarding a sample of 437 top
managers. We wanted to collect a longitudinal database tracking top managers
throughout their tenure, collecting data on all the reorganizations, greenfields,
divestitures, and acquisitions that occurred during their membership of the top
management team. In order to achieve this, we selected a sample of 25 Dutch nonfinancial, multinational companies listed on the Amsterdam Stock Exchange in the
year 1999. We selected firms that had been in existence for a considerable period of
time because this should enable us to build up a complete picture of the tenure of a
large number of top managers. Subsequently we traced back in time the complete
membership of their top team to the year 1966 – before which data sources became
scarce or non-existent – including all their reorganizations, greenfields, divestitures,
and acquisitions. This led to a total sample size of 3300 manager/year observations,
which is the models’ unit of analysis. We are aware that this procedure creates a bias
towards surviving firms, but it enabled us to have observations of both the entry and
the exit dates of a large number of managers. Indeed we managed to obtain
uncensored data on 342 of the 437 top managers. Moreover, this procedure
minimizes distortion in the data on management turnover due to bankruptcies etc.
The selection of surviving firms does not create a bias towards any of our
hypotheses, although obviously care should be applied when discussing
generalizability of our results.
The companies in the database were active in a large variety of businesses: in
the manufacture of office equipment, precision machinery, paper and packaging, food
13
products, and pharmaceutical and chemical products and brewing, publishing and
printing, retailing, trading, tank storage, and many other industries. The companies
are large, but not so large that management of individual divisions are the main
driving force behind strategy and development routes, rather than the top
management team of the whole company. For instance, the average number of
employees over the period 1966-1999 was 11,449. The 25 firms undertook a total of
108 major reorganizations, initiated 401 greenfields, desinvested 724 businesses,
and engaged in 1491 acquisitions. An advantage of using Dutch firms is that
companies in the Netherlands are all headed by a clearly defined “Raad van
Bestuur”, which is considered the firm’s top management team. The average top
team consisted of 4.3 members. Average number of years that people stayed on as
members of the top management team (excluding censored observations) was 9.3
years, with a standard deviation of 6.2 years.
For each of the 25 firms, and all of their managers, a historical overview was
made in terms of membership and turnover in the top team, all internal
reorganizations, greenfield ventures, divestments of subsidiaries, acquisitions, and a
number of control variables, spanning the period 1966-1999. We used a variety of
archival sources, such as annual reports, management lexicons, who-is-who in the
Netherlands, and sometimes archival records provided for by the firms. In addition, all
companies were contacted by telephone and fax to verify information. This led to fully
time-variant data regarding all the variables in the study.
Dependent variable and analysis
The hypotheses were tested using survival analysis, or event history analysis.
We used Cox’s semiparametric proportional hazard model (Kiefer, 1988) because we
14
had no apriori knowledge of how the baseline hazard is distributed across tenure, i.e.
how the probability that a manager will exit depends on tenure duration. Cox’s
semiparametric hazard model does not require assumptions about this distribution,
instead it only uses the time order in which the manager is observed, i.e. t 0 < t1 < t2 <
… < tk , and not the length between observations (which is why it is called a semiparametric model). Hence, the dependent variable is the instantaneous rate that a
manager will exit, building on the information whether or not a manager exited and
how many intervals had passed. Note that this model is equivalent to a piecewise
exponential survival model, with the number of time intervals equal to the number of
distinct times that a manager is observed (Vermunt, 1996). Thus, the dependent
variable can be interpreted as the probability that a manager will leave the team. All
models were estimated using White, heteroscedasticity robust standard errors.
Alternatively, to avoid heteroscedasticity, we also estimated models stratified by
company, which allows the baseline hazard function to differ per company. This led to
results identical to the ones reported below with all coefficients significant in the same
direction. Furthermore, we estimated models controlling for time using a free time
polynoom, that is, a variable indicating calendar time and several of its powers, which
also produced results which were virtually identical.
Because we measure time in a discrete way – that is, we have yearly
observations while time in reality is continuous – we also re-estimated the models
shown below through discrete-time analysis using a logistic regression model
(Vermunt, 1996). All the results, as shown below, were clearly replicated, with all the
variable signs in the same direction, at at least similar levels of statistical significance.
Independent variables
15
Reorganizations. Internal reorganizations are initially coded as a dummy
variable in a certain year if the company in their annual report makes notice of a
formal reorganization and transformation program within (part of) the company. This
can be a company wide program or a reorganization within a division.
Reorganizations in service departments were excluded in the models shown below
but their inclusion did not change the results. From this variable we subsequently
constructed a moving average of the three years preceding the observation, to take
into account possible clustering of reorganizations within a certain time period and
because experiences that raise the chance of turnover to some extent accumulate
over time (Hackett, Bycio, and Hausdorf, 1994). This variable was lagged one year to
ensure causality. We also estimated models adding reorganizations over a number of
years, with the older years discounted through various rates (cf. Ingram and Baum,
1997), which produced highly similar results.
Greenfield ventures. Similarly, we measured greenfield ventures as the
moving average of the number of greenfield expansions over three years, lagged one
year, preceding the year of observation. Greenfields were newly established
companies, reported as separate entities in the company’s annual report.
Divestitures. Likewise for divestitures. We counted the number of divestitures
over three years, and lagged this measurement with one year. A divestiture could be
the outright dissolution or the sell-off of a previously reported subsidiary. In our
theory, concerning the effect on managerial organizational commitment, it does not
matter whether the subsidiary gets sold to a different company or whether it is
dissolved altogether. In both cases the venture ceases to exist as part of the
manager’s organization.
16
Acquisitions. Acquisitions were measured in a similar way; a moving average
over three years, lagged one year. Acquisitions concerned the take-over of a different
existing company or part of a company.
Control variables. We included several control variables on the level of the
manager: a dummy variable measuring whether the executive is the CEO of the
company, a dummy whether the manager had a technical background, since
engineers may be more focused on internal growth, and a dummy for legal
background since lawyers may be more focused on deal-making (Barker and Mueller,
2002). On the firm level we controlled for profitability, through return on assets, for
instance because managers may be inclined to use financial slack to engage takeovers (Jensen, 1986). We controlled for profitability growth/decline through the
percentage change in return on assets. Unfortunately, we had no direct information
whether an exit was voluntary or forced, for instance for reasons of bad performance.
However, forced exit can be expected to be quite rare in our sample, since it is
notoriously difficult for top managers in the Netherlands to be fired for reasons of poor
financial performance. However, together these two variables, return on assets and
change in return on assets, should control for the effects of (involuntary) turnover due
to performance. Any other reasons, causing forced exit, will simply form part of our
error term.
RESULTS
Table 1 displays summary statistics and the correlation matrix of the
independent variables. There are no exceptionally large correlations between the
variables, but it is noteworthy, however, that the correlations between our predictors
17
are not negative. This is an indication that managers do not necessarily focus on
either cultivation (i.e. internal reorganizations and greenfield expansions) or
compilation activities (i.e. divestments and acquisitions); apparently these activities
do not need to be mutually exclusive. Note that our theory does not suggest that
managers engage in either cultivation or compilation, but that cultivation activities
increase organizational commitment, while compilation reduces the inclination of top
managers to remain at the firm, independent of the correlation between the two.
----- Please insert Table 1 about here -----
Table 2 displays the results of the event history analyses. Recall that, since we
had no apriori knowledge of the shape of the baseline function between tenure
duration and the hazard, i.e. the probability of exit, we estimated our models using
Cox’s partial likelihood approach, to avoid making assumptions about this
relationship. Therefore, we first examined the estimated cumulative baseline hazard
(using model 2), which is displayed in Figure 1a, and its logical converse the
estimated baseline survival function, which indicates the proportion of managers
remaining, displayed in Figure 1b. These graphs show that the hazard is
monotonically increasing; the longer the manager is in function, the higher the chance
becomes that he or she will leave. This relationship is stronger at higher levels of
tenure, which makes sense; the chance of departure increases more between, for
example, year 15 and 16 than between year 2 and 3. This suggests that if future
research would like to estimate parametric hazard models, and hence make
assumptions about the form of the baseline hazard, it would be better to opt for, for
18
instance, a Weibull distribution, rather than a loglogistic or lognormal distribution
(Allison, 1984; Kiefer, 1988).
----- Please insert Figures 1a and 1b about here --------- Please insert Table 2 about here -----
Test of the hypotheses
Model 1 in Table 2 concerns the model with estimates of the effect of the
control variables only. The first column depicts the coefficients, while the second
column displays the size of the so-called multiplier, or the hazard ratio of the
variable’s effect. The size of coefficients in an event history model cannot be
interpreted directly, since it is a multiplicative rather than an additive model, but they
can be transformed into the multiplier (which is simply e β). The multiplier shows the
influence that one (additional) unit of the variable has on the probability of a
manager’s exit. For instance, the model shows that CEO’s have a lower probability of
exit; hence the negative coefficient in first column of model 1. The multiplier in the
second column shows that the probability that a CEO will exit at a certain point in
time is 69% of the probability that a regular member will leave the top team.
Furthermore, the model indicates that Dutch top managers are more likely to leave in
times of high profitability, rather than when return on assets is low. Previous research
has shown managers to leave both in times of poor performance and in times of high
performance, supposedly due to favorable labor market effects (Salancik and Pfeffer,
1980; Wagner, Pfeffer, and O'Reilly, 1984). Adding a square term to our variable to
capture non-linear effects did not alter the results; the estimate was wholly insignificant.
Hence, the probability of turnover of Dutch top managers seems to be influenced by
19
high performance, rather than low performance. The estimates on the variable change
in profitability, however, show that managers are more likely to leave when performance
in declining. Taken together, these results indicate that Dutch top managers are most
likely to leave their company when its performance trend is just ‘over the hill’.
Hypothesis 1 predicted that internal reorganizations decrease the probability
that top managers will exit. The results in model 2 show that the effect of
reorganizations is indeed negative and significant. The size of the multiplier indicates
that each reorganization decreases the probability that a manager will leave with
39%. Likewise for the effect of greenfield ventures; this variable too is negative and
highly significant, which corroborates hypothesis 2. The size of the effect is
comparable; each greenfield decreases the probability of managers’ exit with 41%.
Note, however, that greenfield ventures are less rare than internal reorganizations; an
average of .53 per year, versus an average of .14. Therefore, in total the influence of
greenfields on managers seems more prominent. Together, these results support the
notion that activities of organizational cultivation increase managers’ commitment to
their organization.
Hypothesis 3 and 4 addressed the influence of compilation activities; buying
and selling businesses. The coefficient on desinvestments is indeed positive and
highly significant. In fact, a desinvestment of a subsidiary during a top manager’s
tenure increases the chance that he or she will leave the firm with 27%. Take-overs
also significantly increase the probability of top management exit; each acquisition
increases the chance of a manager’s departure with 9%. Together, the estimates
corroborate the idea that deal-making, or compilation activities, increases the
likelihood that managers will subsequently leave their position. On average,
desinvestments take place about once a year (i.e. .99), while the average number of
20
acquisitions that the managers in our database experienced was 1.7. Hence, the
effect of divestments on the probability of managers terminating their tenure is the
strongest influence in our model, taking into account how often the different events
take place.
We also estimated models with interactions between our four predictors and
the control variables indicating performance, return on assets and change in return
on assets. One could suspect that the relationship between managerial actions (i.e.
reorganizations, divestments, etc.) is moderated by performance; for instance,
reorganizations might only lead to sustained management tenure if they result in
improved performance, or acquisitions lead to higher turnover if they do not work out,
i.e. if firm performance suffers as a result, etc. None of these interactions, however,
were significant. Apparently, in support of our theory regarding the effect of the
predictors on managerial commitment, the results displayed in Table 1 are not
conditional on their influence on firm performance.
DISCUSSION
The findings in this study help to further complete the picture of the
relationship between top managers and their firms. Over the last decade, a stream of
research has emerged that has shown, in various ways, how managers shape firms;
the strategic development of organizations is influenced by the particular individual
characteristics and preferences of their top managers. Our study adds a new
perspective to this literature: how firms shape managers. Our longitudinal study
shows that the particular strategic developments firms are undergoing have
repercussions for the top managers at the helm of these organizations. In particular,
21
we examined the effect on managers’ organizational commitment, or their inclination
to remain at, or leave a firm. We argued that development targeted at the internal
development of organizations, such as reorganizations and greenfield ventures –
something we labeled cultivation activities – lead to increased managerial
commitment, and thus lengthen management tenure. Firm development building on
largely external activities, such as buying and selling businesses – which we labeled
compilation – was thought to decrease commitment and therefore shorten
management tenure. These views were strongly corroborated through our event
history analysis on the probability of individual managers’ turnover.
Alternative explanations and study limitations
An alternative explanation for our study’s findings would be that the managers
in our sample did not change due to the particular experiences that they go through
with their firms but that the managers who are committed to their organizations have
a preference for cultivation and the managers who are less committed to begin with
emphasize organizational compilation. That is, for example, the people who do a lot
of acquisitions were prone to leave early anyway. Although we think this scenario is
relatively unlikely anyway, since we examined top managers in general, rather CEO’s
alone, and hence the strategic development of these firms is not influenced by these
individual managers only, plus we know that firms go through certain periods of
growth and decline independent of managers’ preferences (Greiner, 1972;
Vermeulen and Barkema, 2001), we performed a series of analyses to restrict this
possibility. Firstly, we ran a number of OLS regression analyses whether firms indeed
emphasize either cultivation or compilation activities. Hence, we for instance defined
number of reorganizations as the dependent variable and regressed it on greenfields,
22
divestments, and acquisitions, controlling for, among others, firm size and firm
specific effects (using firm dummies). Likewise, for the other three predictors, which
we set as dependent variables. If the above alternative explanation were to hold true,
we should see a negative partial correlation between cultivation activities and
compilation activities. As already suggested by the correlation matrix (Table 1) this
was not the case; firms and their managers do not do one or the other thing.
Cultivation and compilation activities often take place at the same time. A
management team may be performing both types of activities concurrently, it is just
that one increases commitment while the other one has negative influence on
commitment.
A direct test of the above alternative explanation would be to control for
manager-specific effects in our models, for instance adding 436 (= n-1) manager
dummies or, the equivalent, running fixed-effects models on our database.
Unfortunately, fixed effects are not possible in log-linear analysis such as event
history analysis or logit models. However, to explore within group estimates, we ran
fixed-effects, linear probability models (Amemiya, 1981) on our panel data with as a
dependent variable a dummy whether or not a manager left in a certain year. In
effect, these models only compare the observed manager with him or herself; for
example, they model whether the probability of an average manager’s exit increases
due to an acquisition, beyond his or her specific probability of exit before the
acquisition. Note that these linear probability models will create unbiased estimates of
the coefficients but will produce biased standard deviations, hence the reported
significance levels should be interpreted with care. We first ran the models displayed
in Table 2 using linear probability estimates, without the fixed effects condition, which
led to highly identical results as the ones displayed. Adding the fixed effects produced
23
the same results for all predictors but the coefficient on reorganizations, which was
insignificant. The statistical significance for the other three variables was at least
p<.001. Again, this is likely to be a very conservative test of our hypotheses and the
results should therefore be interpreted with care, but it does lead to further support
that at least our findings on the influence of greenfield ventures, divestments, and
acquisitions are not due to unobserved manager specific influences, in conformity
with our theory. Thus, it leads to further confidence that our models indicate that firm
experiences are changing managers, rather than that different managers experience
different things.
Conclusion
Previous research has shown that managers shape firms. Different managers
do different things (Chaganti and Sambharya, 1987; Hambrick and Mason, 1984). But
part of these preferences are shaped by the experiences that they have gone
through. Some of these experiences are formed by the actions that they have
undertaken at the helm of their companies. Our study emphasizes how their
experiences shape the commitment that they feel towards their organizations.
Managers that employ many external activities such as acquiring and selling
businesses were found to leave their firms more quickly than managers who invest a
lot of time cultivating the internal organization of their firms through reorganizations
and setting up and fostering internal ventures.
A conclusion of these findings is that the life cycle of top executives is not fixed
(Miller and Shamsie, 2001), but dependent on what they do during this cycle. In that
sense, we do not reject the view that managers shape their firms, but argue that this
is a reciprocal relationship; different managers do different things, brought about by
24
different institutional circumstances, different periods in time, different development
stages, or because they find themselves in a different phase during their career and
tenure. Thus, managers emphasize different actions during their tenure (Miller and
Shamsie, 2001), but how long this tenure prolongs is in turn affected by these
actions. Previous research has emphasized that organizational change is provoked
by management turnover (Furtado and Karan,1990; Weisbach, 1995). Our study
shows that this turnover is not exogenous, but that there is a dynamic interplay
between firms and the people that govern them.
25
Table 2. Event history analysis on the probability of manager exit
Model 1
Model 2
Variable
coefficients multiplier
coefficients multiplier
Control variables
Ceo
Technical background
Legal background
Return on assets
Change in ROA
-.374**
-.029
.146
2.49***
-1.96***
.69
.97
1.2
12.2
.14
Predictors
Internal reorganizations
Greenfield ventures
Desinvestments
Acquisitions
Log likelihood
*** p<.001, ** p<.01, * p<.05
-1583
-.359**
.018
.094
2.11**
-1.98***
.69
1.02
1.10
8.24
.14
-.502*
-.534***
.239***
.090***
.61
.59
1.27
1.09
-1503
26
Table 1. Summary statistics and correlation matrix
Variable
Mean
SD
Min
Max
1
1. chairman
0.23
0.42
0.00 1.00
1.00
2. technical
0.20
0.40
0.00 1.00
0.06
3. legal
0.12
0.32
0.00 1.00
0.01
4. roa
0.54
0.71
-0.32 1.10 -0.01
5. change in roa
0.00
0.07
-1.05 1.00 -0.00
6. reorganizations
0.14
0.24
0.00 1.00 -0.01
7. greenfiels
0.53
0.76
0.00 5.67 -0.03
8. desinvestment
0.99
0.96
0.00 4.67 -0.00
9. acquisitions
1.70
1.68
0.00 9.67 -0.02
* correlations exceeding .035 are significant at the .05 level
2
3
4
5
1.00
-0.18
-0.04
0.00
0.04
-0.06
-0.06
-0.08
1.00
0.01
0.01
0.03
-0.06
-0.01
0.04
1.00
0.56
0.10
-0.14
-0.14
0.15
1.00
0.06
-0.03
-0.06
-0.03
6
1.00
-0.01
0.07
0.02
7
1.00
0.31
0.13
8
1.00
0.17
9
1.00
Figure 1a: Estimated cumulative
baseline hazard
7
6
hazard
5
4
3
2
1
0
0
10
20
30
years
Figure 1b: Estimated baseline survival
function
proportion surviving
1
0.8
0.6
0.4
0.2
0
0
10
20
years
30
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