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DECLINE, TURNAROUND, AND MANAGERIAL OWNERSHIP
John D. Francis, Hagan School of Business, Iona College
Eleni Mariola, Hagan School of Business, Iona College
ABSTRACT
This paper investigates the effect of managerial ownership and turnover on the probability of a
turnaround for companies that experience decline in their profitability. We also examine whether
CEO turnover determines the type of retrenchment strategy chosen so as to hasten the turnaround
process. In addition, we test the impact of environmental munificence, size, financial slack,
methods of retrenchment and corporate productivity on the probability of turnaround. Our
empirical results suggest that financial slack and productivity are the most important determinants
of a turnaround. Equity ownership by management and the board of directors does not appear to
have an impact on turnaround contrary to our hypothesis.
Key words: turnaround strategies, governance, agency theory
I. Introduction
The management literature has long sought to explain the issues of organizational decline and
turnaround. Reduced corporate profitability, particularly during periods of general economic
contraction, leads to a series of dysfunctional consequences, which include shrinking resources,
poor morale, skeptical stakeholders, conflict, turnover, and time constraints (Lohrke and
Bedeian, 1998; Hambrick and D’Aveni, 1988). Corporate responses range from denial of the
problem, reliance on stringent internal controls, reduction of scale and scope of operations, to the
dissolution of the organization (Schendel and Patton, 1976).
With the broad domain of issues and implications associated with decline and turnaround
process, the ability to formulate appropriate strategic responses is of prime consideration for
management researchers and practitioners. Despite the extensive investigations of the critical
questions in the turnaround efforts, the strategic management literature offers limited guidance
for reversing firm decline (Lohrke and Bedeian, 1998). In fact several primary issues remain
unsettled. For example, what is the relative effect of the environment and decline, and firm
actions on organizational turnaround? Also, what types of organizational action are required for
turnaround? Specifically, is firm retrenchment a necessary strategy for turnaround situations?
What organizational resources enable a firm to achieve improved performance? Finally, does
managerial ownership affect retrenchment strategies and corporate turnaround? Recently,
Barker, Mone, Mueller and Freeman (1998) and Castrogiovanni and Bruton (2000) reexamined
the factors associated with turnaround and concluded that the debate concerning retrenchment
and other factors that lead to turnaround is still open and in need for further research.
Arogyaswamy, Barker, and Yasai-Ardekani (1995) in review of the decline and turnaround
literature argue that decline and turnaround are closely linked as successful turnaround attempts
must both manage the decline and change the firm's strategy, and internal processes to secure
newer resources to deal with the causes of decline.
Our study extends previous research attempts by examining a broad range of internal and
external factors that impact on decline and turnaround. In particular, we focus on the effects of
the environment, the nature of the decline, the corporate financial characteristics, the
retrenchment policies and the corporate governance issues on whether the company achieves a
turnaround or not. Moreover, the study uses a broad array of factors considering the whole
turnaround process, with factors included in the study from before decline occurs, during the
decline, and the resulting performance. These factors are examined in the context of firms that
managed successful turnaround and those that did not, using declining firms from a wide range
of industries in order to develop generalizable findings.
In Section II, we develop our empirical hypotheses. Section III reviews the empirical
methodology and describes the data. Section IV summarizes the results, and Section V
concludes.
II.
Theory and Hypotheses
Past studies have suggested numerous factors that are important influences on turnaround
including, environmental characteristics, such as industry growth, government regulations, and
financial institutions (Gopinath, 1995), and deliberate tactics, such as improving operational
efficiency or changing the firm’s competitive strategy (Barker and Duhaime, 1997; Hambrick
and Schecter, 1983; Winn, 1997). Studies of declining firms tend to examine three basic areas:
(1) sources of decline, (2) organizational responses to decline, and (3) effects of decline on other
organizational activities (Lohrke and Bedeian, 1998; Whetten, 1987). Primarily, researchers
who have analyzed organizational decline have grappled with unresolved issues concerning the
appropriateness of a firm’s actions to effect turnaround (Castrogiovanni and Bruton, 2000;
Hambrick and Schecter, 1983; Robbins and Pearce, 1992; Pant, 1991).
One of the earlier studies on corporate turnaround by Schendel, Patton and Riggs (1976)
indicated that downturns in performance were a result of unfavorable environmental shifts
combined with organizational inefficiency or inappropriate competitive strategies. The authors
maintained that it took an organizational crisis for a firm to seriously address decline. Other
researchers have also argued that environmental factors such as industry conditions, government
regulations, external stakeholders, such as financial institutions limit the choices of management
to effect turnaround (Hubbard & Kosnik, 1996; Gopinath, 1995). Others have argued that the
decline situation itself influences organizational outcomes. For example, in Chowdhury &
Lang’s (1993) study, they found that firms experiencing crisis decline situations were more
successful in their turnarounds than those experiencing more gradual decline.
Most of the research in this area has focused on the actions management must take in
overcoming organizational decline (Arogyaswamy, et al, 1995: Barker & Mone, 1994; Bonnici
& Fredenberger, 1994; Robbins & Pearce, 1992). It was in this vein that Pant (1991) addressed
the issue of decline and turnaround using the industry structure-conduct-performance paradigm.
Drawing her conclusions based on a sample of firms from a variety of industries in the 1970s,
she argued that industry characteristics did not significantly explain turnaround, but that
deliberate management action was required.
Hofer (1980) provided a contingency theory for turnaround strategies where he compared
operational and strategic actions, in order to achieve a fit with prevailing environmental
conditions. Hambrick & Schecter (1983) tested this theoretical distinction on a group of
strategic business units and found that operational actions consisting primarily of reductions in
assets and costs or withdrawal from selective products and markets, influenced firm turnaround.
Similarly, several authors have found that improved financial performance is related to
efficiency-enhancing measures such as cost cutting or asset retrenchment (Ramanujam, 1984;
Thietart, 1988). These findings led to an emphasis on the importance of retrenchment strategies
for turnaround to the point where Robbins & Pearce (1992) argued that retrenchment is a
necessary element of any turnaround strategy.
The issues concerning retrenchment have become a debated topic in the literature. Barker &
Mone (1994) suggested there is little evidence for supporting the retrenchment assertion. Instead
turnaround is a response to steep decline and that the actual performance of retrenching firms is
not significantly better than that of non-retrenching firms. Similarly, Castrogiovanni & Bruton
(2000) contend that retrenchment strategies are not generalizable to all firms because they were
not beneficial to a sample of acquired firms that were in need of turnaround.
Other organizational responses to decline have also been investigated in the literature. Barker &
Duhaime (1997) examined strategic and entrepreneurial responses to organizational decline and
found that organizations belonging to declining industries are more likely to pursue strategic
change. Studies focusing on firm actions in the turnaround process have also investigated firm
activities such as environmental scanning, management or change styles, and organizational
structures (Armenakis, Fredenberger, Giles, Cherones, Field, & Holley, 1996; Grinyer, Mayes,
& McKiernan, 1990).
Overall, previous research considers a broad array of environmental and decline characteristics,
organizational resources and organizational actions as important influences on performance
turnarounds. The literature offers limited guidance on the importance of different factors within
the turnaround process and many of the studies have been industry specific and not
generalizable. Furthermore, this guidance has not only been inconsistent, but at times
contradictory (Lohrke and Bedeian, 1998). This, of course, is one of the causes of our failure to
generate a comprehensive theory of firm turnaround and one of the reasons why continued
research in this area is needed.
In researching the influence of several factors on organizational turnaround, we mainly utilize
the structure-conduct-performance paradigm and resource-based theory (Barnett, Greve, and
Park; 1994; Barney, 1991) to investigate the extent to which different situational and firm
variables influence improved corporate performance after a decline. We view decline as a result
of erosion of productive resources. Therefore, in order to manage a turnaround, managers must
focus on stemming the erosion of resources, effectively use the existing resources and
concurrently replace and/or add to resources.
The starting point for testing the factors that influence turnaround lies in the external
environment. Obviously, the environment is an important situational element since it has a strong
impact on a firm’s strategic direction, the process by which strategic direction is shaped and the
way firm’s resources are secured (Hamel and Prahalad, 1994). The strategy literature is replete
with conceptualizations of the environment and its effect on organizations. For example, Dess
and Beard (1984) categorized the external environment along three dimensions-- munificence,
dynamism and complexity, with each dimension comprised of a cluster of attributes influencing
the organization in a unique way. Of these categories, environmental munificence (the
environment’s capacity to accommodate firms) has particular relevance to organizational decline
and turnaround (Arogyaswamy et al., 1995). It has long been acknowledged in the organizational
ecology literature that low environmental munificence makes it difficult for organizations to
survive (Hannan and Freeman, 1977).
Other research indicates that environmental munificence is positively associated with the number
of strategic options available to firms and their chances of survival (Brittain and Freeman, 1980).
Similarly, Goll and Rasheed (1997) have found that munificence affects firm performance.
Alternatively, Covin and Slevin (1989) suggest hostile environments are characterized by
precarious industry settings, intense competition, harsh, overwhelming business climates, and the
relative lack of exploitable opportunities. It is likely that firms in munificent environments would
find it easier to turnaround, amidst strategic actions taken, due to higher demand for products,
more available resources and lower competition. Therefore, based on these arguments the
following hypothesis is offered:
Hypothesis 1: Environmental munificence will influence the turnaround outcome of declining
firms positively.
Another situational variable important in the turnaround process is the nature of the decline
itself. One aspect of corporate decline concerns its severity or depth. Robbins and Pearce (1992)
maintain that the severity of decline gauges the magnitude of the threat facing the organization.
From a resource-based perspective, a severe decline would indicate more critical problems with
the ongoing use of valuable resources and competencies. It is likely that firms experiencing
severe declines find it more difficult to achieve turnaround than firms experiencing less severity.
A second decline variable concerns how gradual or rapid the decline occurred. This factor
indicates how quickly the firm’s resources are depleted. D'Aveni (1989) proposes that there are
patterns to decline in terms of how resources deteriorate, and classified these patterns as either
sudden, gradual, or lingering. A sudden decline is characterized by moving from a perceived
situation of organizational health to one of poor performance and instability in a short period of
time. Firms experiencing this decline condition would have a shorter time frame to garner
resources and implement effective actions to stem the decline.
Overall, we suggest that the speed at which the decline occurred, combined with its severity,
create a very urgent situation. Firms finding themselves in these situations have a harder time
taking effective organizational actions due to the magnitude of the problem, the state of the
firm’s resources and the time constraints involved. Therefore, it is expected that firms in urgent
decline situations have more difficulty achieving turnaround. In light of these arguments, the
following hypothesis is offered:
Hypothesis 2: The higher the urgency of the decline the lower the probability of a turnaround
Resource-based literature suggests that internal resources define durable competitive advantage.
For declining firms, a key question is which resources stand out as enabling a firm to overcome
its performance declines? The turnaround literature suggests that there are several firm
characteristics that enhance a firm’s ability to deal with decline. Usually these characteristics are
discussed in terms of their ability to buffer the effects of the decline and the urgency of the
situation. Under the auspices of resource based theory, buffering characteristics enable a firm
time to respond appropriately to decline and provide it with capabilities and resources to achieve
a successful turnaround.
For example, the size of the organization can be seen as a firm characteristic that affects the
eventual turnaround result (Singh and Lumsden, 1990; Haveman, 1993). The relationship
between size and consequence of a declining situation has been debated in the literature. Large
firms are more insulated (Hannan and Freeman, 1984) and possess the stability to overcome
adverse economic situations because of broader institutional systems (Haveman, 1992). In
following the logic of Thompson (1967), these characteristics can buffer an organization’s core
from the effects of the environment.
Others argue that large firms are likely to have tortuous internal procedures and multiple
relationships with stakeholders, which may slow down their ability to respond quickly (Meyer
and Zucker, 1989). Therefore, according to the behavioral perspective (Hambrick and D’Aveni,
1988), the presence of size-related inertia in large firms would negatively affect their ability to
enact turnaround strategies.
Arguments from both research streams have received support in the turnaround literature.
Barker and Mone (1998) find no support for the positive influence of size on turnaround.
However, Zajac and Kraatz (1993) and Haveman (1993) find that larger organizations tend to
respond better to declining performance and turbulent environments, respectively. We contend
that size of the firm plays an important positive role in determining turnaround outcomes and
consider it an important tangible resource of the firm and a means for the organization to buffer
itself from the effects of the decline situation. Large firms have greater resources and more
options for initiating turnaround strategies, such as the divestment of under performing assets,
reduction of salary expenses or the closing of ineffective operations. We expect to see therefore:
Hypothesis 3: Larger firms being associated with successful turnaround strategies
Another buffering characteristic that enables a firm to respond appropriately to decline is the
availability of slack resources. Firms with immediately available (or unavailable) resources at
the time of the turnaround attempt would be less (or more) constrained in their ability to initiate
appropriate remedial measures (Hambrick and D’Aveni, 1988; Barker and Mone, 1998). It has
been suggested that the presence of slack resources, such as cash, inventory, or access to credit,
can provide a firm with the cushion necessary to implement a recovery strategy (Barker and
Duhaime, 1997). Mainly slack resources help a firm absorb the effects of performance
downturns or variability (Bourgeois, 1985) and provide a base of resources to take effective
actions. Therefore,
Hypothesis 4: Firms with more slack resources during decline have a better chance of surviving
and staging a turnaround.
One of the attributes relating to the resource capabilities of the firm is their use, specifically the
productivity of its human and capital resources. Shetty and Butler (1990) suggest that firm
productivity is an encompassing construct and evidence of a firm’s overall competitiveness and
effectiveness. Although firm productivity could be related to past cost reduction activities, it is
a result of other additional firm level factors such as existing market share or sales growth
(Arogyaswamy et al., 1995; Barker and Duhaime, 1997; Winn, 1997). A declining firm that has
relatively efficient operations is utilizing its resources more productively and economically,
enabling it to focus on other primary causes of decline. We hypothesize that:
Hypothesis 5: The higher the firm productivity, the higher the probability of a turnaround
Prior research on corporate governance reports that the components of CEO compensation are an
indicator of the influence he enjoys relative to the board of directors. Agency theory proposes
that managers' compensation packages should be designed to provide incentives for them to
pursue firm value-increasing projects, and Jensen and Murphy (1990) suggest that political
forces operating within the firm can influence the CEO performance/compensation relation.
Moreover, Berger, Ofek, and Yermack (1997) report that the degree of CEO entrenchment
affects firm leverage levels, and that entrenched CEOs take on less debt. They study several
measures of entrenchment including managerial equity ownership, fixed compensation (proxied
by salary and bonus), and CEO tenure. Following these authors we utilize cash salary and bonus
as a proxy for fixed compensation in our analysis, and propose that the percentage of salary and
bonus relative to total compensation is an informative indicator of managerial entrenchment.
However, if CEO compensation is comprised primarily of stock options and other profit-sharing
arrangements, then compensation is sensitive to performance, and this may be indicative of the
relatively limited influence that he exerts within the firm.
Hypothesis 6: The lower the percentage of salary to total compensation, the higher the
probability of turnaround.
We use the number of years of employment with the firm as a proxy for tenure. Prior research
reports an association between CEO tenure and CEO influence/power within the firm (Harrison,
Torres, and Kukalis (1988)). The longer he holds office, the more the CEO becomes
experienced with the firm's operations, establishes a power base, and becomes entrenched within
the firm. In such a case, the expectation is that poor performance by a CEO who has a long
tenure with the firm, will not necessarily lead to his dismissal. It is proposed that managerial
power increases at a decreasing rate the longer the CEO stays in office, and accordingly, tenure
is measured as the natural logarithm of the number of years of CEO employment with the firm.
Hypothesis 7: The longer the employment duration, the more entrenched the CEO will be, the
lower the probability of a turnaround.
Hypothesis 8: The longer the employment duration, the higher the probability the CEO will
choose to reduce assets rather than operating expenses.
Another line of research investigates the effect of managerial equity ownership on firm value,
and the need to design executive compensation contracts to ensure that management goals are
aligned with those of shareholders (Jensen and Meckling (1976), Lambert and Larcker (1985),
Murphy (1985), and Jensen and Murphy (1990)). The studies apply agency theory to the
analysis of the moral hazard problem that exists in the principal/agent (owner/manager)
relationship and gives rise to agency costs. These costs can be mitigated by structuring
management contracts to ensure that managers act in the shareholders' interests (Jensen and
Meckling (1976)).
The results of empirical studies indicate that as the manager's stake in the firm increases, he is
more likely to pursue activities that increase the value of the firm. Morck, Schleifer, and
Vishny (1988) evaluate the relation between board ownership and firm performance (proxied by
Tobin’s q, and the firm’s accounting profit ratio), for a number of Fortune 500 firms in 1980.
Using a sample of 371 firms, they report a positive relation between Tobin's Q and board equity
ownership levels of 0% to 5%; a negative relation for the 5% to 25% level; and a positive
relation for ownership levels above 25%. Similar results are obtained when profit rate is used as
the measure of firm performance.
Hypothesis 9: The higher the managerial ownership, the higher the probability of a turnaround.
III.
Methodology
A. Sample Description
To test the hypotheses we develop a sample of firms from multiple industries that have
undergone decline, and we examine them longitudinally at four points in time during the overall
turnaround cycle. The selection criteria for firms used in this study are developed from prior
studies in this area of research (Barker and Mone, 1994; Barker and Patterson, 1996; Lohrke and
Bedeian, 1998; Robbins and Pearce, 1992). Our study is based on a group of firms selected from
the industrial and commercial machinery and computer equipment-manufacturing category
distinguished in Standard Industry Classification (SIC) major group 35. This allows the testing
of different industries while at the same time limiting the broadness of the categorizations.
Our objective is to create a data set representing firms that had an appropriate amount of time
while facing performance declines to formulate strategic responses. The time frame of the
sample covers the fiscal years 1980 through mid 1990s and is appropriate for the research
questions incorporating cyclical recessions, growth, and stagnation, providing a wide range of
environmental conditions. The sample for this study is obtained from Standard&Poor’s
COMPUSTAT. All of the firms selected in the sample display the following characteristics:
1.
Two consecutive years of Return on Investment (ROI) above the risk-free rate of return
prior to the actual time of decline. This criterion excludes firms that are continually poor
performers and limits the study to firms that are truly in turnaround situations. As modeled by
Barker and Duhaime (1997), the return rate for six-month U.S. treasury notes at auction,
reported in the Economic Report of the President, is used as a proxy for the risk-free rate return.
2.
At least three consecutive years of ROI below the risk-free rate during the duration of the
decline. Porter (1980) proposes that a firm is failing in economic terms if it does not earn a
return greater than the risk-free rate.
3.
At least one year within the three years of decline with a negative net income. This is an
additional conservative criterion and represents a firm's inability to cover its costs (Barker,
1992).
The above criteria yield a final sample of firms that were performing adequately prior to a
decline in performance of at least three years, highlighted by a corresponding year of losses.
Initially, we achieved a sample of 110 firms for the study. Data were then collected for each of
the variables previously hypothesized as having an influence on the decline response of the
sample firm. Organizations for which the required data were not available were removed,
yielding a final sample of 97 firms (See Table 1).
In order to adequately test the effects of the independent variables in a longitudinal study,
different time periods within the decline and turnaround cycle are specifically appropriate for
data gathering. By following the examples of previous research, the study includes data
collected at four points in time on a firm-by-firm basis (See Figure 1). Time 1 represents the
year of peak performance in the two years prior to the downturn and relates to the first sample
inclusion criteria mentioned previously. Time 2 represents the year in which the sample firm's
decline reached its lowest point and relates to the second and third inclusion criteria. Time 3
relates specifically to measuring retrenchment. Retrenchment, consisting primarily of asset and
expense reductions, is generally considered to extend from the onset of the turnaround situation
until the cost and asset reductions cease. For firms pursuing these actions, Time 3 represents the
year of the deepest reductions. For firms not pursuing this strategy, expense and asset data was
gathered three years after Time 2. Time 4 pertains specifically to overall turnaround
performance. It indicates either the point when a firm achieved turnaround, or for firms that
continue to perform poorly, four years after the start of the decline and continuing on for at least
two more years. The latter group of firms was classified as unsuccessful turnarounds. All
retrenching firms in the sample were checked to ensure that their years of deepest asset and
expense reductions (Time 3) came before their eventual turnaround performance was measured
(Time 4).
The shortest turnaround cycle for any firm in the sample would be eight years, starting with two
years of positive performance, three years of decline and poor performance, and three years of
positive performance. The longest time frame of any firm in the sample is fifteen years, which
is the length of the study design. Overall, this type of method allows for analysis of actions
taken and turnaround outcomes over a reasonable period of time and is commonly used in
decline and organizational failure studies (Barker and Patterson, 1996; Lohrke and Bedieian,
1998; Moulton, Thomas, and Pruett, 1996, Robbins and Pearce, 1992, 1993).
B. Variables and Measures
Dependent variable. Turnaround outcome, the dependent variable in this study, is measured at
Time 4 and captured by analyzing the firm's ROI in comparison to the risk-free rate of return. If
the firm was able to return its performance (ROI) to above the risk-free rate of return for at least
three years, continuing to and including the latest fiscal year before the data were collected then
the firm has achieved turnaround; if not, then the firm is still considered in decline. More
specifically we were interested in exploring the several external factors and internal efforts made
by firms in these two groups (turnaround and Non-turnaround) and whether they influenced
membership in one group of the other. Please note that although we look at performance, our
main focus is the general outcome, namely turnaround and not the magnitude of performance
increases (See Table 2).
Independent variables. We follow Dess and Beard (1984) by measuring environmental
munificence as the degree of market/industry growth or contraction for the three years prior to
decline. High industry growth represents a more munificent environment. The data for this
measure are collected from Predicasts Industry Reports, which details industry shipments for
each 4-digit SIC code per year. Of the 97 firms, all but eight indicated at least two-thirds of their
sales in one 4-digit SIC industry. For each of these eight firms, its major industry is identified
along with the percentage of firm sales attributed to it. A weighted industry average is used. Data
for this variable are collected for each firm at Time 1 and Time 2 and transformed into a
continuous variable. Positive values indicate a growing industry; negative values denote a
contracting industry as follows:
Industry growth = (Industry Shipments Time 2/Industry Shipments Time 1) - 1
The second group of variables concerns the urgency of the firm's decline, in terms of its degree
of severity and how rapidly or gradually it occurred. The first, decline severity, has been well
established in the strategy and finance literature and is determined by using Altman's (1968) Z
value method. This measure predicts financial health in terms of how close to bankruptcy an
organization is. It provides a score between one and five, with one being the most severe state.
Scores of three or above mean that one can confidently predict that a firm will not go bankrupt in
the short term. The data for this variable are gathered at Time 2, the lowest point of decline. The
second aspect of the urgency of decline, suddenness, is measured in terms of the number of years
it took for a firm to go from a healthy financial position measured at Time 1, to the lowest point
in its decline cycle measured at Time 2. A lower number of years indicate a rapid descent.
Overall, the urgency of a firm’s decline is calculated as a product of severity and suddenness of
decline.
Urgency of decline = suddenness of decline * severity of decline
The third set of variables pertains to various organizational buffering characteristics. One such
variable concerns the presence or absence of slack resources. Stickney (1990) suggests that the
firm's debt to asset percentage is an appropriate measure of slack. Banks will lend money to
unprofitable firms with good credit ratings, and other stakeholders will continue to provide
important resources such firms.
Slack = 1- [(Long term + Debt in current liabilities / Total assets) * 100]
An alternative specification of slack follows Cleary (1999).
Slack = cash + marketable securities + .5(inventory) + .7(accounts receivable) – short term loans.
The data for these variables are gathered at Time 2, the lowest point of decline. Also, taken into
consideration in this group of variables is firm size, which is measured by sales of each firm at
Time 1.
The third buffering variable (i.e., Productivity) is measured using data concerning both
employee and capital productivity. To determine an employee productivity ratio, the firm's total
revenues (at Time 2) are divided by the number of employees. The ratio is then examined in
relation to competing firms in its industry for the same time period. For firms that significantly
participated in more than one SIC industry, weighted averages are again calculated to determine
a productivity figure. Employee productivity for each firm is computed by using the following
formula:
Employee productivity = Firm productivity/Industry average productivity
Values greater than one indicate that the firm's employees are more competitive than its rivals;
values less than one provide evidence that its productivity is less. In the same manner, the firm's
capital productivity is determined by calculating both the firm’s and the industry's sales divided
by property, plant, and equipment at Time 2. Thus, the following indicates the computation of
the variable for the capital productivity of each declining firm:
Capital productivity = Firm capital productivity/Industry average productivity
The fourth set of variables pertains to retrenchment activities to effect turnaround. Independent
variables concerning expense and asset reductions are gathered from firm financial data at Time
2 and Time 3. Expense retrenchment is said to occur if the firm's total expenses are reduced
during this time frame. Total expenses include cost of goods sold and selling, and administrative
expenses. Asset retrenchment occurred if the firm reduced total assets over this same time
period. To create continuous variables, the variables were computed as:
Retrenchment of expenses = (Expenses at time 3/Expenses at time 2) - 1
Assets retrenchment = (Assets at time 3/Assets at time 2) - 1
A negative value for these dependent variables indicates retrenchment; a positive value denotes
an increase in assets or expenses over this time period. The value itself equals the percentage
change in either assets or expenses from Time 2 to Time 3.
The last set of variables captures the corporate governance issues. Salary to total compensation,
CEO tenure and managerial ownership data are collected from Value Line and the corporate
proxy statements at Time 2.
C. Econometric Model
The hypotheses presented in the previous section are tested using the following binomial logit
model:
Prob (turnaround)= eX/(1+ eX)
where  is the vector of parameters and X is the matrix of the independent variables below
Munif
= Environmental munificence
Urgency
= Urgency of decline (product of severity and duration of decline)
Size
= Size of the firm as measured by corporate sales
Slack
= Financial slack
Eprod
= Employee productivity
Cprod
= Capital productivity
Rexp
= Retrenchment through reduction in expenses
Rassets
= Retrenchment through reduction in assets
Iown
= Percent of ownership by the board of directors and management
Tenure
= CEO tenure
Comp
= CEO compensation
IV.
Empirical Results
Table 1 provides a description of the type of industry included in our sample along with the
number of firms chosen from each industry. All firms studied have a two-digit SIC code of 35.
Table 2 provides the descriptive statistics of our sample. The first panel summarizes the
statistics of our variables for the entire sample. The second and third panels provide summary
statistics for the two sub-samples of companies that demonstrate turnaround and no turnaround
respectively. The percent of ownership by management and the board of directors is 17.43 for
the entire sample similar to the percentages reported by Denis and Kruse (2000) and Mikkelson
and Partch (1989).
For the two sub samples we find that companies that achieved a turnaround had on average a
lower percent of ownership (16.5) than those that were not able to turnaround (18.4), had a less
severe decline (1.7 vs. 3.7), had higher financial slack, higher productivity of both employees
and capital, and finally they did not apply any retrenchment activities (a reduction in expenses or
assets) to affect turnaround as indicated by the positive values of rexp and rassets.
Table 3 provides the correlation matrix and the probability that the correlation coefficient is
significantly different from zero for the variables for the entire sample of the firms. The
correlation coefficient is found in the first row for each independent variable and the probability
that the correlation is significantly different from zero is found in the second row for each
independent variable. Some of the variables are significantly correlated with each other such as
eprod with cprod and rexp with rassets. We do run our logit regressions by keeping only one of
these variables at a time i.e. eprod only to capture the effect of productivity on turnaround or
rexp to capture the impact of retrenchment on turnaround. These results are not reported since
they are qualitatively similar to those reported below.
The results from the logistic regressions are presented in Table 4. As hypothesized, we find that
the probability of a turnaround increases with financial slack as indicated by the positive and
statistically significant (at the 1 percent level) coefficient for slk. The coefficients for urgency
and sales (proxy for size) have the expected sign but are not statistically significant at the
conventional levels. There is a positive and statistically significant at the 3 percent level
coefficient for cprod that lends support to our hypothesis that increased productivity leads to
higher probability of a turnaround. Methods of retrenchments do not seem to affect the
probability of a turnaround as demonstrated by the positive but not statistically significant
coefficients for rexp and rassets.
When ownership data are included in the regressions, none of the independent variables is
statistically significant at the conventional levels. This may be due to the fact that the number of
observations drops precipitously from 97 to 30 and the overall significance of the regression
equation is also reduced as indicated by the p-value of .41 as opposed to the p-value of .0018
obtained for the model without the percent ownership.
V.
Conclusion
The management and finance literature have long sought to identify the variables that allow
companies to overcome decline in their performance. In this paper we concentrate on industry
characteristics as well as firm specific attributes that might affect turnaround. In addition we
explore the impact of corporate governance issues on a company's ability to improve
performance. The central argument was that effectiveness of a particular recovery strategy
would be contingent upon external influences and internal firm characteristics. Our analysis
shows that the effects of firm-level factors (in terms of buffering characteristics and activities
undertaken to manage resources) on turnaround outcomes are stronger than industry effects and
are consistent with other studies (Moulton et al., 1996; Pant, 1991; Sudarsanam and Lai, 2001).
Our results indicate that financial slack and productivity are the most important determinants of
the probability of a turnaround.
The findings show that the presence of firm-level buffering characteristics influence a firm’s
turnaround performance positively. Our findings agree with previous research in that the
available resources either limit or enhance the options for firms attempting a turnaround strategy
(Robbins and Pearce, 1992). These results support the perspective that appreciable levels of
unabsorbed slack decrease sensitivity to hardship and afford firms with an advantage over their
counterparts in similar situations (Barker and Duhaime, 1997; Grinyer et al., 1988). Firms with
available slack resources in the midst of decline are in a superior position to correct weak
operating or strategic capabilities, as the slack resources provide a cushion necessary to
implement recovery strategies in general.
Also, organizational productivity provides a firm with a core capability that is critical for
organizational success. Therefore, while not a likely cause of decline for these firms (in our
sample), it is likely that these capabilities can be utilized in efforts to achieve turnaround. This
finding could also explain the absence of environmental munificence as a predictor. It can be
argued that firms participating in growing industries may not benefit unless they raise their
capacity utilization and improve their productivity figures.
The other major result of our study indicates the influence of retrenchment in the turnaround
model. Several turnaround studies have debated whether that firms recovering from decline
genuinely achieve efficiencies relative to firms that continue to decline (Hambrick and Schecter,
1983; Ramanujam, 1984), as increased efficiency may coincide with increased sales and/or
retrenchment (e.g., Hofer, 1980). Our study indicates that retrenchment does not appear to
impact the eventual turnaround.
External influences such as environmental munificence and decline characteristics were not
empirically supported. Lastly, managerial ownership impacts did not appear significant in our
study. These findings are merely exploratory, particularly those concerning ownership due to
problems with data collection. We plan on extending our research in order to capture a larger
sample of firms and data.
Another limitation concerned the sample of industries. While our sample consisted of firms from
several different types of industries and controlled for any industry-specific performance cycle
(within a four digit SIC code), it was limited to manufacturing companies in the major group 35.
How firms in specific industries achieve turnaround in response to industry-specific causes
would be an interesting area of further research. Third, although we attempted to offer an
expanded perspective of turnaround strategies, it is not a comprehensive set.
Finally, given the high rates of business failures, developing an understanding of how firms
manage to recover from declining performance is an area of study that warrants more research.
There are many unanswered questions about what characteristics differentiate successful
turnaround and organizational failure. We plan to continue our study in order to provide
additional insights into the relative importance of several determinants of turnaround outcomes.
Future research could retest these variables to see if their generalizability holds true across other
samples of firms.
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Figure 1
Turnaround Process
SIC code
3531
3533
3537
3540
3541
3555
3556
3559
3561
3562
3564
3565
3566
3567
3569
3570
3571
3572
3575
3576
3577
3578
3579
3585
Table 1. Sample Description
Name of Industry
Construction Machinery
Oil Field Machinery
Industrial Trucks and Tractors
Metal working machinery and equipment
Machine tools and Metal cutting Equipment
Printing trades Machinery
Food Products Machinery
Pumps and Pumping equipment
Ball and roller Bearings
Blowers and fans
Packaging Machinery
Speed changers, drivers and gears
Industrial furnaces and ovens
Industrial machinery
Computer and office equipment
Electronic computers
Computer Storage devices
Computer terminals
Computer communications equipment
Computer peripheral Equipment
Calculating and accounting Equipment
Office machines
Refrigerators and heating equipment
Number of firms
5
5
2
3
2
2
4
10
4
2
3
1
1
1
2
5
9
8
4
6
11
2
1
3
Table 2
Descriptive Statistics
The table provides descriptive statistics of the variables for the entire sample of the firms and for the
sub-samples of companies that achieved a turnaround (=1) and those that did not (turnaround=0).
iown is the percentage equity ownership of all of the firm’s board of directors and officers, munif is
the environmental munificence and represents the environment's ability to accommodate firms,
urgency refers to severity and speed of the decline and is given by the product of the two, sales
represents the level of firm sales, slk measures the financial slack of the company, eprod is the
employee productivity as measured by the ratio of employee productivity and industry average
productivity, cprod represents capital productivity and is given by the ratio of firm capital
productivity and industry average productivity, rexp represents reduction in expenses as measured by
(expenses at time 3/expenses at time 2)-1, rassets is the reduction in assets given by (assets at time
3/assets at time 2)-1.
Variable
N
Mean
Minimum
Maximum
Std
iown
munif
urgency
sales
slk
eprod
cprod
rexp
rassets
iown
munif
urgency
sales
slk
eprod
cprod
rexp
rassets
30
97
97
97
97
97
97
97
97
All data
17.4360
1.4000
-0.8421
-1.7137
2.6995
-23.4280
3358.5600
4.7600
50.2569
5.5100
1.2098
0.0300
1.1188
0.0400
0.0201
-0.9551
0.0407
-0.8799
61.4000
1.9624
12.4000
68940.6300
109.8800
8.1100
11.8600
1.9008
2.2108
14.6489
0.4074
6.6364
9596.4100
22.6233
1.1991
1.3604
0.5041
0.5351
15
48
48
48
48
48
48
48
48
Turnaround = 0
18.3873
1.4000
-0.8667
-1.7134
3.6747
-23.4280
3380.4100
20.7900
43.3489
5.5100
1.0220
0.2200
0.7602
0.0600
-0.0865
-0.7788
-0.03634
-0.6242
61.4000
-0.3559
12.4000
68940.6300
109.8800
5.3400
2.8600
1.9008
2.2108
16.7691
0.2856
6.0744
10243.3200
24.0267
0.9670
0.5259
0.3930
0.4109
47.5000
1.9624
11.4800
39752.6300
102.5400
8.1100
11.8600
1.6843
2.1888
12.7030
0.5010
7.0762
9024.4900
19.0764
1.3749
1.7822
0.5784
0.62890
Turnaround=1
iown
munif
urgency
sales
slk
eprod
cprod
rexp
rassets
15
49
49
49
49
49
49
49
49
16.4847
-0.8180
1.7443
3337.1600
57.0239
1.3937
1.4700
0.1247
0.1162
2.0000
-1.7137
-21.7520
4.7600
17.3100
0.0300
0.0400
-0.9551
-0.8799
Table 3
Correlation Matrix
The table provides the correlation matrix and probability of the correlation is significantly different from zero for the
variables for the entire sample of the firms. iown is the percentage equity ownership of all of the firm’s board of directors
and officers, munif is the environmental munificence and represents the environment's ability to accommodate firms,
urgency refers to severity and speed of the decline and is given by the product of the two, sales represents the level of
firm sales, slk measures the financial slack of the company, eprod is the employee productivity as measured by the ratio
of employee productivity and industry average productivity, cprod represents capital productivity and is given by the
ratio of firm capital productivity and industry average productivity, rexp represents reduction in expenses as measured by
(expenses at time 3/expenses at time 2)-1, rassets is the reduction in assets given by (assets at time 3/assets at time 2)-1.
Correlations that are significant at least at the 5% level are in bold.
Variable
iown
munif
urgency
sales
slk
eprod
cprod
rexp
rassets
iown
munif
urgency
sales
slk
eprod
cprod
rexp
rassets
1.0000
0.0510
0.7890
1.0000
0.0654
0.7313
-0.1060
0.3015
1.0000
-0.2901
0.1199
-0.1270
0.2153
0.1979
0.0521
1.0000
-0.1633
0.3885
0.0301
0.7696
-0.1513
0.1392
0.0811
0.4296
1.0000
0.1707
0.3670
-0.0110
0.9147
-0.0943
0.3581
-0.1194
0.2443
-0.0240
0.8153
1.0000
-0.1304
0.4922
0.1291
0.2075
-0.2111
0.0380
-0.1041
0.3103
0.0417
0.6851
0.7482
<0.0001
1.0000
0.0463
0.8079
0.1258
0.2195
0.0020
0.9849
-0.1441
0.1590
-0.0725
0.4804
0.3364
0.0008
0.3226
0.0013
1.0000
0.2239
0.2342
0.0352
0.7325
-0.0928
0.3660
-0.1132
0.2698
-0.0646
0.5294
0.3392
0.0007
0.2632
0.0092
0.5836
<0.0001
1.0000
Table 4
Logit Regressions
Results of logit regressions for corporate turnaround. The dependent variable equals one if a company achieved a turnaround and zero
otherwise. The regressions reported measure the probability of a turnaround. The first column reports the set of the independent
variables with the expected sign of the parameter estimates in parentheses. iown is the percentage equity ownership of all of the firm’s
board of directors and officers, munif is the environmental munificence and represents the environment's ability to accommodate
firms, urgency refers to severity and speed of the decline and is given by the product of the two, sales represents the level of firm
sales, slk measures the financial slack of the company, eprod is the employee productivity as measured by the ratio of employee
productivity and industry average productivity, cprod represents capital productivity and is given by the ratio of firm capital
productivity and industry average productivity, rexp represents reduction in expenses as measured by (expenses at time 3/expenses at
time 2)-1, rassets is the reduction in assets given by (assets at time 3/assets at time 2)-1. Parameter estimates that are significant at
least at the 3% level are in bold.
Variable
intercept
iown
(+)
munif
(+)
urgency (-)
sales
(+)
slk
(+)
eprod
(+)
cprod
(+)
rexp
(+)
rassets (+)
L
Without Ownership (N=97, Turnaround = 49)
Parameter Estimate
p
-2.3431
0.0103
-0.0962
0.8801
-0.0351
0.4483
0.000010
0.6573
0.0338
0.0036
-0.2734
0.4159
0.9843
0.0343
0.9509
0.1479
0.0777
0.8984
Chi-Square
24.5666
p
0.0018
With Ownership (N=30, Turnaround =15)
Parameter Estimate
p
-2.1710
0.4914
0.0088
0.8264
3.5506
0.1414
-0.0580
0.7479
0.0001
0.2686
0.0414
0.1499
2.0916
0.3575
0.8641
0.4826
-1.2153
0.4990
-2.2802
0.5288
Chi-Square
9.3005
p
0.4100