00251740510626272

Management Decision
Situational and organizational determinants of turnaround
John D. Francis Ashay B. Desai
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Management Decision, Vol. 43 Iss 9 pp. 1203 - 1224
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Situational and organizational
determinants of turnaround
John D. Francis
Hagan School of Business, Iona College, New Rochelle, New York, USA, and
Ashay B. Desai
College of Business Administration, The University of Wisconsin Oshkosh,
Oshkosh, Wisconsin, USA
Abstract
Purpose – To test the ability of situational variables, manageable pre-decline resources, and specific
firm responses to decline to classify performance outcomes (turnaround vs non-turnaround) in
declining firms.
Design/methodology/approach – Using a longitudinal methodology and a multi-firm sample, the
paper studies the relative role of situational factors concerning the environment and a firm’s decline,
along with various internal resources and strategies that can enable a firm to recover from decline.
Findings – The results indicate that contextual factors such as the urgency and severity of decline,
firm productivity and the availability of slack resources, and firm retrenchment can determine the
ability of sample firms to turnaround. Overall, factors under the control of managers contribute more
to successful turnarounds than situational characteristics.
Research limitations/implications – This study does not identify the exact cause of firm decline.
The authors believe this is beyond the scope of this multi-firm study.
Originality/value – This study contributes to the existing research by theoretically explicating and
empirically testing the influences of multiple situational and organizational factors on turnaround
outcomes. While several studies have investigated conceptually unique sets of actions applied by
managers attempting to turn around declining firms, this paper integrate these actions as they can
often impact each other and the eventual turnaround. The authors believe their research design affords
a more holistic view to the turnaround process. In order to direct executives efforts, the findings are
summarized into some practical applications.
Keywords Management strategy, Management technique, Workplace training,
Professional associations, Performance appraisal, United States of America
Paper type Research paper
Introduction
Recently, the study of organizational decline and turnaround has taken on renewed
importance as we have seen record bankruptcies over the past few years. These
downturns are made more difficult by the dysfunctional consequences of declining
firms, which include shrinking resources, poor morale, skeptical stakeholders, conflict,
and turnover (Lohrke and Bedeian, 1998). The responses of such firms range from
denial of the problem, to reliance on stringent internal controls, to reduction of scale
and scope of operations, to top management turnover and the dissolution of the
organization (Schendel and Patton, 1976). With the broad domain of issues and
implications associated with decline and attempted recoveries (i.e. turnaround), the
ability to formulate appropriate strategic responses is of prime consideration for
management researchers and practitioners. Researchers have investigated many
critical questions yet some issues remain unsettled. For example: “What is the relative
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Determinants of
turnaround
1203
Management Decision
Vol. 43 No. 9, 2005
pp. 1203-1224
q Emerald Group Publishing Limited
0025-1747
DOI 10.1108/00251740510626272

effect of the environment, decline characteristics, and firm conditions on organizational
turnaround?” (Sudarsanam and Lai, 2001); “What types of organizational actions and
resources are appropriate for turnaround?”; and finally: “Is firm retrenchment an
essential strategy for turnaround, or are there situations where retrenchment is not
required?” Studies by Barker et al. (1998) and Castrogiovanni and Bruton (2000)
concluded that the debate concerning retrenchment and other factors that lead to
turnaround is open and needs research.
A primary weakness in the literature concerns the types of studies to date. Usually
studies isolate one aspect of the turnaround process and examine that aspect’s
influence on firm performance or firm activities. Arogyaswamy et al. (1995) argued that
the stages of the decline and turnaround process are closely linked. Successful
turnaround is a complex process that involves a combination of situational factors,
internal resources, and firm strategies that are relevant at various stages of the decline
and resulting improvement. Analysis of these factors entails a multi-period assessment
of the turnaround process. We expect this type of study to shed light on their respective
importance and criticality in the process and on some of the inconsistencies in this
literature. Through a longitudinal methodology, we study the relative role of
situational factors concerning the environment and a firm’s decline, along with various
internal resources and strategies on subsequent performance (turnaround outcome).
Theoretical framework and hypotheses
Past studies have suggested numerous factors that are important influences in the
decline and turnaround process, including situational factors such as environmental
characteristics, aspects of the decline situation, and specific organizational
characteristics and strategies (Castrogiovanni and Bruton, 2000). However, one
criticism is their limited focus on one stage of the decline and turnaround cycle. Second
is that many of the studies have been firm-specific and not generalizable. Therefore,
findings although detailed, are limited in their application and are inconsistent at times
(Lohrke and Bedeian, 1998).
In developing our research model to test the importance of several factors on firm
turnaround, we utilize the structure-conduct-performance (S-C-P) paradigm (Scherer,
1980). This paradigm suggests that conduct of the firm (e.g. capital investment,
retrenchment, etc.) in correspondence with the structural characteristics (such as size)
of the firm and the industry environment (such as growth) determines performance.
We view decline as a result of erosion of productive resources. Therefore, to manage a
turnaround, managers must focus on stemming the erosion of resources, effectively
using the existing resources and concurrently maintaining a firm’s ability to replace
and/or add to resources.
Situational factors
Utilizing the structure-conduct-performance paradigm, the starting point for testing
the factors that influence turnaround lies in the external environment. Schendel et al.
(1976) found that downturns in performance were a result of unfavorable
environmental shifts combined with organizational inefficiency or inappropriate
competitive strategies. Other researchers argued that environmental factors such as
industry conditions, government regulations, and external stakeholders such as
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financial institutions limit the choices of management and therefore influence
performance (Hubbard and Kosnik, 1996).
We believe the environment can not only be one of the causes of a firm’s decline, but
also affect the eventual turnaround outcome. For example, Pfeffer and Salancik (1978,
p. 168) suggested that: “as potential environmental pressures confronting the
organization increase, the need for outside support increases as well”. The strategy
literature is replete with conceptualizations of the environment and its effect on
organizations. 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). Covin and Slevin (1989)
suggested 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, the following
hypothesis is offered:
H1. Environmental munificence will positively influence the turnaround outcome
of declining firms.
Other situational factors affecting the turnaround include elements of the decline itself.
We submit that aspects of decline are indications of the maintenance and effectiveness
of a firm’s resources in the midst of decline. Past research suggests that decline
characteristics are important because they either signal managers that current
strategies and resources are not effective and create pressure to change (Chowdhury
and Lang, 1993), or give managers some idea of how ineffective current resources are
and how fast they are deteriorating. As decline situations vary, they have the potential
to impact strategies and the eventual turnaround performance. Our study looks at
three aspects of decline, magnitude of decline (severity), how rapidly a firm’s
performance has deteriorated (suddenness) and a combination of the two (urgency).
The view that decline characteristics are signals to take action falls under the
cognitive school of thought (Kiesler and Sproull, 1982). Basically, this theory suggests
that declining firms in crisis will be more likely to take the drastic actions necessary to
achieve a performance recovery, as opposed to firms who experience a less severe
decline. Other researchers found that more severe declines make it more difficult for
firms to achieve a turnaround (Robbins and Pearce, 1992). They argue that situational
severity is the degree to which an organization’s survival is threatened (Pearce and
Robbins, 1993). Therefore, declining firms in less severe situations may implement a
multitude of strategies such as increased marketing to promote sales or moving into
more market niches (Lohrke and Bedeian, 1998), while those in severe situations are
close to bankruptcy and have limited range of actions due to acute resource depletion
(Robbins and Pearce, 1992). Under the auspices of the S-C-P paradigm, we expect that
Determinants of
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firms experiencing severe declines find it more difficult to achieve turnaround than
firms experiencing less severity.
A second aspect of firm decline is temporal and concerns how gradually or rapidly
the decline occurred. D’Aveni (1989) proposed 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. Suddenness of decline may positively influence managerial action in the
midst of decline. For example, rapid performance decline may make it more likely for
managers to overcome problems with inertia than if the decline were gradual.
Researchers have suggested that larger firms with mechanistic structures and decision
processes are part of the problem for managers making adaptive changes when faced
with a changing environment (Staw et al., 1981). Chowdhury and Lang (1993) found
that smaller firms respond better to crisis declines than to gradual declines. Tichy and
Devanna (1986) maintained that this is similar to the “boiled frog” syndrome, where a
frog will react instantaneously to hot water, but not to water that is heated gradually
over time.
Alternatively, firms undergoing rapid declines would have a shorter timeframe to
garner resources and implement effective actions to stem the decline. The overall
consequences of decline may lead to the exiting of employees who have valuable, firm
specific knowledge of products and services, processes or routines (Perry, 1986). With a
more gradual decline, the loss of these resources could be offset over a longer period of
time, with less potential to drastically impact a declining firm. Valuable routines and
processes require time to build sustained competitive advantage. Rapid declines may
lead a firm to focus mistakenly on operational actions instead of on developing
long-lasting sustainable resources. Therefore, we expect rapid declines to have a more
negative impact on turnaround than gradual declines.
We expect each of these situational decline factors, the speed at which the decline
occurred, and its severity, to influence turnaround negatively. Jointly, the severity of
decline and how rapidly it occurred can create a crisis situation for a struggling firm.
Firms in these situations have a harder time taking effective organizational actions due
to the magnitude of the problem, the state of their resources and the time constraints
involved. In light of these arguments, the following hypotheses are offered:
H2a. The severity of the decline will negatively influence the turnaround outcome
H2b. The suddenness of the decline will negatively influence the turnaround
outcome of declining firms.
H2c. The urgency (severity and suddenness) of the decline will negatively
influence the turnaround outcome of declining firms.
Manageable-pre-conditions
Under the S-C-P paradigm internal resources define durable competitive advantage
(Scherer, 1980). For declining firms, a key question is: “Which resources stand out as
enabling a firm to overcome its performance declines?”. We can find several firm
characteristics in the literature that enhance a firm’s ability to deal with decline.
Essentially, these resources offset the effects of the environment and the urgency of the
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decline situation. These buffering resources can give a firm time to respond
appropriately to decline and provide it with capabilities and resources to achieve a
successful turnaround.
The size of the organization can be seen as a firm characteristic that affects the
eventual turnaround result (Haveman, 1993; Singh and Lumsden, 1990). The
relationship between size and consequences of a declining situation has been debated
in the literature. According to the resource-based theory, large firms are more insulated
(Hannan and Freeman, 1984) and possess the stability to overcome adverse economic
situations because of broader institutional systems (Haveman, 1993). In following the
logic of Thompson (1967), these characteristics can buffer an organization’s core from
the effects of the environment.
According to the cognitive perspective (Hambrick and D’Aveni, 1988), large firms
are likely to have tortuous internal procedures and multiple relationships with
stakeholders, which may slow down their ability to respond quickly. Therefore, the
presence of size-related inertia in large firms would negatively affect their ability to
enact turnaround strategies (Meyer and Zucker, 1989). Small firms may have less
complex organizational structures and may be able to react to changes faster than
larger firms. Arguments from both research streams have received mixed support in
the turnaround literature. Barker and Mone (1998) found no support for the positive
influence of size on turnaround. However, Haveman (1993) found that larger
organizations tend to respond better to declining performance and turbulent
environments, respectively. We contend that, under the conforms of the S-C-P
paradigm and resource-based theory, size of the firm plays an important positive role
in determining turnaround outcomes. Size is 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 divesting under-performing assets, reducing salary expenses or
closing ineffective operations.
Another buffering characteristic that enables a firm to respond appropriately to
decline is the availability of slack resources. Singh (1986, p. 567) specifically referred to
slack as either absorbed “excess costs in organizations”, or unabsorbed, “uncommitted,
liquid resources in organizations”. The presence of the latter type 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). Slack
resources help a firm absorb the effects of performance downturns or variability and
provide a base of resources to take effective actions. 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 (Barker and
Mone, 1998).Therefore, firms with more slack resources during decline have a better
chance of surviving and staging a turnaround.
One final attribute relating to the resource capabilities of the firm is their use,
specifically the productivity of the firm’s human and capital resources. Shetty and
Butler (1990) suggested 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 also a result of other
additional firm level factors such as existing market share or sales growth
(Arogyaswamy et al., 1995; Barker and Duhaime, 1997). A declining firm that has
Determinants of
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1207

relatively efficient operations is utilizing its resources more productively and
economically, enabling it to focus on other primary causes of decline. Overall, we argue
that firm resources specific to the organization’s buffering characteristics of
productivity, slack, and size will positively affect its capacity for absorbing the
effects of decline and enable its recovery strategies. In keeping with the previous
arguments, the following hypotheses are offered:
H3a. The size of the organization will positively influence the turnaround outcomes
H3b. The presence of slack resources will positively influence the turnaround
outcomes of declining firms.
H3c. Capital productivity will positively influence the turnaround outcomes of
declining firms.
H3d. Employee productivity will positively influence the turnaround outcomes of
declining firms.
Operational restructuring
Finally, the literature suggests that among the factors that may affect turnaround, the
content of the firm’s approach has important influences. Much of the research in the
area of decline and turnaround posits that management must take an active role in
overcoming organization decline (Barker and Mone, 1994). One area of debate concerns
the effectiveness of efficiency-pursuing actions generally classified as retrenchment.
According to Lorhke and Bedeian (1998, p. 5), “retrenchment encompasses not only
reducing investments in functional areas such as marketing, R&D, and production, but
may also include divesting or liquidating unprofitable units in an effort to generate
cash”. Robbins and Pearce’s (1992) study of retrenchment as a separate component of
the turnaround process found that firms that pursued retrenchment attained a better
than average improvement. Alternatively, Barker and Mone (1994) argued that there is
little evidence supporting the assertion that retrenchment is integral to turnaround;
instead, it is merely a consequence of performance declines. In a rebuttal paper, Pearce
and Robbins (1994) maintained that turnarounds can consist of both strategic and
operating elements, but that retrenchment remains integral to turnaround regardless of
what other recovery response is attempted.
Castrogiovanni and Bruton (2000) found that contraction activities do not influence
the turnaround of the firms in their sample. They suggest that retrenchment may be
context specific and needs to be studied in several industry contexts. In this study, we
contend that retrenchment is an overall organizational response to firm decline by
refocusing a firm’s resources on primary rent-generating activities. We expect that
retrenchment will have a positive effect on the eventual turnaround. Based on this
discussion, our final hypotheses are offered:
H4a. Asset retrenchment will positively influence the turnaround outcomes of
declining firms.
H4b. Expense retrenchment will positively influence the turnaround outcomes of
declining firms.
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Methodology
Sample description
To test the above hypotheses, we developed a sample of firms from the industrial and
commercial machinery and computer equipment-manufacturing category
distinguished in Standard Industry Classification (SIC) major group 35. We obtained
the sample from Standard & Poor’s COMPUSTAT and covers fiscal years 1980-1997.
COMPUSTAT compiles information required by the Securities and Exchange
Commission (SEC) and the Financial Accounting Standards Board (FASB) Statement
Number 14. Corporations are required to supply information on their lines of business
(industry segments). In the database, each corporation is required to detail information
on segments which account for 10 percent or more of consolidated sales, operating
profits, or assets (see Table I). The final sample of 97 firms displays the following three
characteristics:
(1) Two consecutive years of return on investment (ROI) above the risk-free rate of
return. (This 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 US Treasury notes at auction,
reported in the Economic Report of the President, was 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
decline. It has been proposed that a firm is failing in economic terms if it does
not earn a return greater than the risk-free rate.)
SIC code Name of industry Number of firms
3531 Construction machinery 5
3533 Oil field machinery 5
3537 Industrial trucks and tractors 2
3540 Metal working machinery and equipment 3
3541 Machine tools and metal cutting equipment 2
3555 Printing trades machinery 2
3556 Food products machinery 4
3559 Special industry machinery 10
3561 Pumps and pumping equipment 4
3562 Ball and roller bearings 2
3564 Blowers and fans 3
3565 Packaging machinery 1
3566 Speed changers, industrial-drivers and gears 2
3567 Industrial furnaces and ovens 1
3569 Industrial machinery 2
3570 Computer and office equipment 5
3571 Electronic computers 9
3572 Computer storage devices 8
3575 Computer terminals 4
3576 Computer communications equipment 6
3577 Computer peripheral equipment 11
3578 Calculating and accounting equipment 2
3579 Office machines 1
3585 Refrigerators and heating equipment 3
Table I.
Sample description
Determinants of
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(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).)
In line with the previous research (Barker and Mone, 1994; Lohrke and Bedeian, 1998),
we examined these firms longitudinally at four points in time during the overall decline
and turnaround cycle (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 criterion
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, generally is 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 retrenchment strategy, we gathered expense and asset data three years after Time
2. Time 4 pertains 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 for at least two more years (unsuccessful
turnarounds) (see Table II). This method allows for analysis of actions taken and
Figure 1.
Turnaround process –
sample inclusion criteria
and data collection time
periods
Class level information
Group Total firms Prior probability
Turnaround 49 0.51
Non-turnaround 48 0.49
Note: Total number of firms (n ¼ 97)
Table II.
Sample description
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turnaround outcomes over a reasonable period of time and is used in decline and
organizational failure studies (Moulton et al., 1996).
Variables and measures
Dependent variable. We measured turnaround outcome, at Time 4 by analyzing the
firm’s ROI compared 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, then the
firm had achieved turnaround.
Independent variables. We used Dess and Beard’s (1984) environmental munificence
variable measured as the degree of market/industry growth. We collected the data for
this measure from Predicasts Industry Reports, which details industry shipments for
each four-digit SIC code per year. Of the 97 firms, all but eight indicated at least
two-thirds of their sales in one four-digit SIC industry. For each of these eight firms, we
identified its major industry along with the percentage of firm sales attributed to it. We
used a weighted industry average. We collected data for this variable for each firm at
Time 1 and Time 2 and transformed it into a continuous variable (positive values
indicate a growing industry; negative values denote a contracting industry) as follows:
Industry growth ¼ Industry Shipments Time 2=Industry Shipments Time 1
À Á
2 1:
Severity of decline, has been well established in the strategy and finance literature
using Altman’s (1968) Z value method. We measured suddenness of decline, 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 indicates a rapid descent. We calculated the urgency of a firm’s decline as a
product of severity and suddenness of decline:
Urgency of decline ¼ suddenness of decline*severity of decline:
The third set of variables pertains to organizational buffering characteristics. Firm size
was measured as total revenues. Using Stickney’s (1990) method we calculated
organizational slack for each firm by using the following formula: Slack ¼ [1 2 (Total
debt/Total assets)] *100. Firms with higher values on this ratio have relatively greater
access to financial resources. Banks will lend money to unprofitable firms with good
credit ratings, and other stakeholders will continue to provide important resources to
such firms. We gathered the data for this variable at Time 2, the lowest point of decline.
Also, taken into consideration in this group of variables was firm size, which we
measured by sales of each firm at Time 1. We measured the third buffering variable
(i.e. productivity) using data on both employee and capital productivity. We divided a
firm’s total revenues (at Time 2) by the number of employees to determine an employee
productivity ratio. We examined this ratio relative to competing firms in an industry
for the same time period. For firms that participated significantly in more than one SIC
industry, we calculated weighted averages to determine a productivity figure. We
computed employee productivity for each firm by using the following formula:
Employee productivity ¼ Firm productivity=Industry average productivity:
Values greater than one indicate that the firm’s employees are more productive than
those of its rivals; values less than indicate less productivity. In the same manner, we
Determinants of
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determined the firm’s capital productivity by dividing both the firm’s and the
industry’s sales by property, plant, and equipment at Time 2. Thus, the following
formula indicates the variable for the capital productivity of each declining firm:
Capital productivity ¼ Firm capital productivity=Industry average productivity:
The last set of variables pertains to retrenchment activities. We gathered data
regarding expense and asset reductions from firm financial data at Time 2 and Time 3.
Expense retrenchment occurred if the firm’s total expenses were 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, we computed the variables as:
Retrenchment of expenses ¼ Expenses at Time 3=Expenses at Time 2
À Á
2 1:
Assets retrenchment ¼ Assets at Time 3=Assets at Time 2
À Á
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.
Analysis and results
The objective of this study is to examine the simultaneous effects of both
organizational and environmental characteristics on turnaround outcomes. The
relationship tested in this study is:
Turnaround outcome ¼ f ðorganizational slack; size; severity of decline;
suddenness of decline: urgency of decline; capital productivity; employee:
productivity; industry growth; asset retrenchment and expenses retrenchmentÞ:
We use multiple discriminant analysis (MDA) to assess the ability of the relevant
variables to discriminate between the turnaround outcomes. This statistical technique
is used when the dependent variable is categorical and the independent variables are
continuous. Fisher’s Linear Discriminant Analysis (FLDA) allows us to access the
ability of relevant variables to discriminate between the two outcomes (turnaround and
non turnaround). Since our focus is on the turnaround outcome and not specifically on
the magnitude of performance, this method is appropriate. Table III provides the
sample descriptives for both groups together (turnaround and non-turnaround) and,
Tables IV and V provide separate sample descriptives for turnaround and
non-turnaround firm respectively. We ran two models: the first (Model 1) without
the variable – urgency of decline (calculated as a product of severity and suddenness),
and the second (Model 2) with the variable. Table VI contains the discriminant function
coefficients and loadings (correlations). The discriminant function is a linear
combination of the independent variables selected for their discriminatory power. The
discriminant coefficients indicate the relative importance of each independent variable
in discriminating between the two groups. While the discriminant loadings measure
the simple linear correlation between each independent variable and the discriminant
function. Loadings are considered more valid than function coefficients in determining
the strength of the relationship between the dependent and independent variables
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12345678910
1Severityofdecline1.000
2Organizationalslack20.1631.000
3Size0.1600.0811.000
4Employeeproductivity20.08620.02420.1191.000
5Capitalproductivity20.234*0.04220.1040.748**1.000
6Industrygrowth20.0820.03020.12720.0110.1291.000
7Retrenchmentofassets20.18620.06520.1130.339**0.263**0.0351.000
8Retrenchmentofexpenses20.08520.06320.1380.333**0.320**0.1290.581**1.000
9Suddennessofdecline20.0980.0620.14720.13220.0300.12920.275**20.202*1.000
10Urgencyofdecline0.930**20.1510.198*20.09420.211*20.10620.0930.00720.0211.000
Mean0.973250.2563,358.561.211.1180.1570.4070.2483.0102.69
SD2.269522.62379,596.401.1991.360.40740.5350.5001.0466.636
Notes:*p,0:05,**p,0:01;thenumberscolumnsoppositethevariablesindicatecorrelations.Forexample,severityofdeclinehasa0.16
(non-signiﬁcant)correlationwiththesize.1.00indicatescorrelationwithitself(100percentcorrelation)
Table III.
Sample descriptives for
both groups (correlation,
means and standard
deviation)
Determinants of
turnaround
1213

12345678910
3Size0.1680.0301.000
5Capitalproductivity20.23120.08220.1100.801**1.000
6Industrygrowth20.0410.12820.1880.0930.1701.000
7Retrenchmentofassets20.294*0.04720.1790.391**0.2640.0201.000
8Retrenchmentofexpenses20.19620.02720.2330.404**0.338*0.1240.698**1.000
9Suddennessofdecline20.01820.1080.298*20.14520.0200.22020.25820.1581.000
10Urgencyofdecline0.930**20.0600.27520.08520.22720.06820.09120.08120.0211.000
Mean0.603157.02333,337.151.39401.47050.18190.11620.12732.9801.7443
SD2.6255419.07669,024.481.374971.781380.500960.628900.573351.16357.07620
Notes:*p,0:05,**p,0:01;thenumberscolumnsoppositethevariablesindicatecorrelations
Table IV.
turnaround ﬁrms
(correlation, means and
standard deviation)
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12345678910
3Size0.1650.1261.000
5Capitalproductivity20.1010.03920.1790.695**1.000
6Industrygrowth20.15920.15020.05020.311*20.1751.000
7Retrenchmentofassets0.13020.329*20.0350.176*0.1510.0471.000
8Retrenchmentofexpenses0.26220.28020.0290.114*0.0750.1070.2741.000
9Suddennessofdecline20.2700.26520.02020.10120.04720.06520.309*20.2811.000
10Urgencyofdecline0.943**20.1680.12520.05220.08020.1690.1390.24920.0331.000
Mean1.351043.34773,380.411.02200.76000.133320.036320.07993.0423.6747
SD1.7864724.02691,0243.30.966980.526090.285590.410920.391060.92166.07441
Notes:*p,0:05,**p,0:01;thenumberscolumnsoppositethevariablesindicatecorrelations.Forexample,severityofdeclinehasa0.165
(non-signiﬁcant)correlationwiththesize.1.00indicatescorrelationwithitself(100percentcorrelation)
Table V.
non-turnaround ﬁrms
(correlation, means and
standard deviation)
Determinants of
turnaround
1215

Variables
Model1Model2
(Withoutthevariable“urgency”)(Withtheinteractionvariable“urgency)
Discriminanta
coefficientsCorrelationb
DiscriminantcoefficientsCorrelations
Organizationalslack0.7160.6660.7160.664
Severityofdecline20.14320.35120.08220.350
Employeeproductivity0.2230.3300.2410.329
Capitalproductivity0.6170.5680.6230.567
Industrygrowth20.0040.12620.0170.125
Retrenchmentofexpenses0.0520.4450.4190.443
Retrenchmentofassets0.3990.3020.0720.301
Suddennessofdecline20.06020.06220.03520.062
Size0.06720.0050.07620.005
Urgencyofdecline––20.23720.308
Eigenvalue0.2290.231
Cannonicalcorrelation0.4320.433
Wilk’sLambda0.8130.813
Chi-squared18.68218.682
Df910
Significance0.0280.044
Notes:a
Discriminantcoefficientsrepresenttherelativecontributionofeachvariabletothatfunction;variableswithlargerweightscontributemoreto
thediscriminatingpower.b
Correlationsmeasuresimplelinearcorrelationsbetweeneachindependentvariableandthediscriminantfunction.All
correlationsinitalicsaresignificant
Table VI.
Standardized canonical
discriminant function
coefficients and pooled
within groups
correlations between
discriminating variables
and canonical
discriminant function
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because of their correlational nature (for details see Hair et al., 1995). All variables
exhibiting loadings of 0.30 or higher, regardless of the sign, are considered significant.
The overall results for both models are significant, as the canonical discriminant
function meaningfully discriminates between the two groups profiled in the sample
(Klecka, 1980).
The results indicate support for several of the hypotheses. Of the variables used to
test the first model, severity of decline (H2a), slack resources (H3b), capital productivity
(H3c), employee productivity (H3d ), asset retrenchment (H4a) and expense
retrenchment (H4b) are found to be significant predictors of turnaround. The other
predictor variables have insignificant (at the 0.05 level) loadings and can be viewed as
less important. In light of these findings, H1 (environmental munificence), H2b
(suddenness of decline) and H3a (size of the firm) are not supported. The added variable
(urgency of decline – H2c) in Model 2 is significant. This suggests that urgency of
decline has an added impact on the turnaround outcome. The classification functions
are reported in Table VI. Analysis of group centroids (Table VII) suggests that the
groups are articulately separated by the derived function for both models, as centroids
for the two groups appear to lie on opposite sides of the discriminant function line.
The results indicate that 66 of 97 (68.0 percent) cases are correctly classified by the
discriminant function for Model 1, and 68 of 97 cases (70.1 percent) for Model 2
(Tables VIII and IX). This level of “hit rate” is higher than the 50 percent that would be
achieved by chance (Hair et al., 1995). Finally, in order to provide additional support for
the worthiness of this discriminant function, a measure of improvement over random
assignment (Press’s Q) is utilized. This measure compares the number of correct
classifications to the total sample and groups. The results of this test indicate that the
use of this discriminant function provides a value of 12.63 (for Model 1) and 15.68 (for
Model 2). The critical value for significance level of 0.01 is 6.63 (Hair et al., 1995). The
discriminant function provides a significant gain over random chance for predicting
turnaround firms from non-turnaround firms.
Type Actual number of cases
Predicted
membership for
Group 1
Predicted
membership for
Group 2
n (%) n (%)
Turnaround 49 34 69.4 15 30.6
Non-turnaround 48 16 33.3 32 66.7
Note: Percent of “grouped” cases correctly classified: 68.00 percent; Press’s Q ¼ 12:63
Table VIII.
FLDA classification
matrix for Model 1
Group number Type of firms
Function
Model 1 Model 2
Group 1 Turnaround firms 0.469 0.470
Group 2 Non-turnaround firms 20.479 20.480
Note: Group centroids are the mean discriminant values for each group and should be away from each
other
Table VII.
Group centroids
Determinants of
turnaround
1217

Discussion and conclusions
This study contributes to the existing research by theoretically explicating and
empirically testing the influences of multiple situational and organizational factors on
turnaround outcomes. Several researchers suggest that a widened scope for
understanding turnaround is needed (Lohrke and Bedeian, 1998). Yet, many studies
have not addressed the need to understand the influence of various variables in an
integrative manner. While several studies have investigated conceptually unique sets
of actions applied by managers attempting to turn around declining firms, we integrate
these actions as they can often impact each other and the eventual turnaround. We
believe this research design affords a more holistic view to the turnaround process.
Our analysis shows that the effects of organizational factors (in terms of buffering
characteristics and activities undertaken to manage resources) such as the presence of
slack resources and higher productivity, and a strategy of expense and asset
retrenchment on turnaround outcomes are stronger than environmental munificence.
These findings support the importance of overarching factors and strategies for firms
attempting turnaround (Castrogiovanni and Bruton, 2000). Our study indicates how
different aspects of firm decline affect recovery. If the erosion of resources is severe
(magnitude) and rapid (time), firms have more difficulty in executing a turnaround.
When tested separately, our results indicate that the severity of decline plays a greater
role than the suddenness of the decline. There is a debate between those who believe that
lingering decline may be more dangerous than a sudden decline, as managers may tend
to overlook how severe the deterioration in resources is (Kiesler and Sproull, 1982), and
those who believe that a sudden decline may severely handicap a firm due to threat
rigidity response (D’Aveni, 1989). Our findings indicate that severity of decline in terms
of magnitude is more relevant than the time aspect of decline (suddenness). In other
words, a sudden decline in non-critical factors may be not as grave as one that is gradual
impacting greater resources. In highly severe situations, a firm may not have the
resources to promote turnaround strategies. However, when the magnitude is combined
with time it creates a greater impact depending on how urgent the situation is.
Our findings agree with previous research in that the availability of resources either
limit or enhance the options for firms attempting a turnaround strategy (Robbins and
Pearce, 1992). 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). Also, both capital and employee
productivity are positively related to firm turnaround. This finding is consistent with
research suggesting that firms recovering from decline focus on enhancing their
productivity performance. Winn (1997) suggested that declining firms that ignore
Type Actual number of cases
Predicted
membership for
Group 1
Predicted
membership for
Group 2
n (%) n (%)
Turnaround 49 35 69.4 14 30.6
Non-turnaround 48 15 31.3 33 68.8
Note: Percent of “grouped” cases correctly classified: 70.1 percent; Press’s Q ¼ 15
Table IX.
FLDA classification
matrix for Model 2
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productivity do so at their peril. We believe that organizational productivity provides a
firm with a core buffering capability that is critical for recovery by more effectively
employing firm resources as a firm attempts turnaround. The last buffering
characteristic, organization size, was not found to be a significant contributor to a
successful turnaround. This is interesting because it suggests that although
conceptually large size may assist strategic reorientation through access to greater
internal resources and linkages with external constituents, its impact on affecting
turnaround outcomes is not significant. This result could be attributed to other side
effects discussed in the strategy literature concerning firm size. Hannan and Freeman
(1984) suggest that large organizations have inbred strategic inertia, which may inhibit
rapid or sizable changes in the organization. Organization size may not be a relevant
indicator of organizational buffering, as any resulting inertia may offset advantages
that size provides to a firm in a turnaround situation.
The other result of our study indicates the importance of retrenchment (both asset
and expense) in the turnaround model. Several turnaround studies have debated
whether firms recovering from decline genuinely achieve efficiencies relative to firms
that continue to decline (Ramanujam, 1984), as increased efficiency may coincide with
increased sales and/or retrenchment. In order to address this issue in a more in-depth
manner, we focused on retrenchment of assets and expenses separately. We did this as
the impact of divesting assets may play a different role than reduction of expenses in
achieving turnaround (in general) and on the magnitude of increase in subsequent
performance.
Subsequent analysis of our sample revealed that roughly half (44) of the firms
pursued both types of retrenchment, 32 utilized one form of retrenchment and 21 firms
pursued neither. Of the last group (21 firms), 16 firms achieved a turnaround in
performance and all 16, had high levels of pre-decline productivity. In other words, 76
percent (16 out of a sub-group of 21) of the firms that were high in productivity and
attempted no retrenchment achieved a turnaround. Moreover this portion of our
sample (16 out of 97 firms) that did not retrench in any way achieved turnaround,
which could indicate support for Hofer’s (1980) concept of strategic turnarounds,
whereby firms change their methods of competing to increase revenues, rather than
focus on improving operating effectiveness and decreasing expenses.
Out of the 76 firms (first two groups), 68 firms were low in at least one type of
productivity and attempted some form of retrenchment, 39 percent (28 out of 68)
achieved a turnaround. However, while applying a similar sub-group analysis to the
magnitude of performance changes, the importance of retrenchment increases greatly.
For example, performance of 84 percent (36 out of 44) of the firms from the first group
improved after they used both forms of retrenchment. These results may suggest that
retrenchment is not essential for improving firm performance, but they do provide a
reason for the pervasive use of this strategy.
Put together, these findings reinforce several things. First, although retrenchment is
a positive organizational strategy for many firms in decline, it is may not be absolutely
necessary to achieve a turnaround particularly if the firm is extremely productive in
utilizing its resources. This finding does not support Robbins and Pearce’s (1994)
primary assertion of the “essential” nature of retrenchment for every firm in need of a
turnaround. For firms that are not efficient, retrenchment may be more appropriate to
improve performance but may not necessarily lead to turnaround. Finally, asset
Determinants of
turnaround
1219

retrenchment influenced the magnitude of performance increases, while expense
retrenchment had no effect. Changes in assets, terms of divestment, asset liquidation,
and plant closings have long been considered key strategies for turnaround. From the
post hoc analyses, it appears these strategies also have the ability to impact
improvement from performance declines more than from reductions in expenses.
Overall, these results emphasize the role of manageable conditions; productivity prior
to decline is most effective for enabling a turnaround, regardless of whether a firm
combines this with some type of retrenchment strategy.
Implications, limitations and suggestions for future research
For a start, companies do not necessarily go wrong because they are in chronically
difficult industries. Our findings concerning the degree of industry growth or decline
indicate no effect on turnaround. However, once a company hits trouble, many
executives misdirect their efforts. These problems are more intensified when the
decline is dramatic or severe.
The firms that succeeded in turning around had more slack resources, higher
productivity, and undertook greater expense and asset retrenchment compared to
those firms that did not recover. In order to direct executives’ efforts, our other findings
can be summarized into some critical applications. First, critical in a turnaround is to
offset any cash problems. CEO of Nissan, Carlos Ghosn maintains that turning around
a company is a bit like Formula One racing. To take the highest-speed trajectory, one
has to “brake and accelerate” all the time. The revival plan, therefore, was a
combination of looking into the future and cutting costs (braking). We could not say,
“There will be a time for cost reduction and then a time for growth” – we had to do
both at once (Ghosn, 2002). Overall, our study compares the importance of multiple
variables for firm turnaround. The results of our study indicate that the ability of firms
to achieve successful turnaround largely depends on actions under the control of
managers, either in pre-decline conditions or in specific responses to decline. Therefore,
when managers are faced with the question: “Which actions are likely to result in
stemming the decline and assisting a successful turnaround?” our analysis indicates
that the most effective answer involves a combination of cost cutting measures,
developing unabsorbed slack resources, and using of the firm’s assets astutely.
In regard to braking the decline, if a company has slack resources available, such as
access to credit, this can help alleviate cash flow problems. Also, firms can undertake
particular moves that can help raise or save cash. Our study indicates that managers
who employ this strategy are more likely to lead their companies to a turnaround. Poor
performing firms can brake a decline by reducing expenses such as salaries, marketing
and inventories to free up cash. Development of unabsorbed slack (e.g. excess liquidity
or ability to raise capital) is important as it is possible that once resources are absorbed
by organizational activities, they are less readily available to cushion the firm against
decline. Albeit the notion that large organizations may have greater accumulated
resources that can be used as buffers against lower performance these resources are
essentially absorbed slack. As our finding indicates, larger size may not assist the
turnaround process.
A second important application of our study is the necessity of improving internal
efficiency and productivity in a turnaround. A related issue is timing in the turnaround
process. Our analysis of factors embedded in various time periods of the turnaround
MD
43,9
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process provides more insight into the dynamics of corporate revival than analysis of
single-period effects. Turnaround strategies are not singular actions, but are
interrelated with the prevalent contextual factors. Thus, the temporal pattern may
reveal the effectiveness of using recovery strategies. For example, a firm’s productivity
as measured in this study is a capability that was developed prior to decline. Also, as
previously mentioned organizational slack can be a buffering characteristic
maintained during firm decline. These two findings may indicate that continuous
development of these organizational resources enable a firm to withstand performance
downturns and achieve effective organizational turnarounds. Many firms in
turnaround situations implement multiple tactics focusing on this aspect of
performance improvement. Nissan added cross-functional teams and restructured
compensation by focusing on performance and productivity by building in options and
cash bonuses for high achievers, up to a third of their salaries. Another example is
Harley-Davidson which created a stronger link between employee empowerment and
accountability for productivity and performance. Other firms can make even more
radical steps by divesting assets. For example, Nissan initiated a sell-off of Keiretsu
investments almost immediately after he took over as CEO in the late 1990s, which
started a trend among Japanese automobile manufacturers. The investments in
automobile parts manufacturers were too small to have any leverage over their
partners and they did not actually care as long as Nissan remained their customer.
As in any other research, our study has limitations. Our sample consisted of
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. Our study used one measure to identify environmental
munificence. Perhaps this explains the lack of findings in this area. Other
environmental dimensions, such as turbulence (Aldrich, 1979), have been posited as
drivers of organizational strategy and are relevant to this research domain. Such
factors should be considered for future research in this area. Finally, the timeframe of
our study looks at a firm’s turnaround cycle and is limited to approximately seven
years. Lengthier studies could provide a richer perspective on turnaround in terms of
long term versus short-term improvements. Also, our study does not identify the exact
cause of firm decline. We believe this is beyond the scope of this multi-firm study.
Research focusing on one firm may be a valid way of studying such situations.
One aspect of this study is how firm-level characteristics (factors that are within the
firm’s control) are vital at different stages of the overall turnaround process. A logical
extension of the current study would be to examine these elements more closely as they
apply to various time periods of the turnaround cycle. In this way, we can gain a
greater understanding of the capabilities that firms need to develop before problems
occur that can enable turnaround if necessary. 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 hope that our study has provided 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.
Determinants of
turnaround
1221

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turnaround schools. Journal of Educational Administration 46:1, 74-98. [Abstract] [Full Text] [PDF]

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