THE INVERTED U-SHAPED RELATIONSHIP BETWEEN BUSINESS
UNITS’ SLACK AND PERFORMANCE: THE CASE OF INDONESIA1
Fuad, Diponegoro University, Indonesia
fuad@undip.ac.id
ABSTRACT
This study reconciles the positive and negative views of behavioral theory of the firm and
economists regarding slack. This study tested the non-linear effect of business units’ slack to
its performance outcome on 135 manufacturing business units in Indonesia. Using nonmonotonic structural equations modeling, the study showed that corporate diversification
positively affects the budgetary slack while it provides little evidence for the significant effect
on financial slack. The study also indicated that both the financial and budgetary slack
increased the financial and non-financial performance at some “peak” levels, and beyond
them, they would hurt the business units performance.
Keywords: financial slack, budgetary slack, financial and non financial performance
INTRODUCTION
Slack that is defined as the excess of resources above the necessary minimum to produce a
given level of organizational output has been an important and intriguing domain in
management accounting literature. Particularly it is because of the opposing theoretical
streams among economists and behavioral accountants on the true role of slack that have led
confusions among the researchers to justify the conclusive, robust findings. Accounting
“behaviorists” for instance, have evoked the use of idle resources that may act as a buffer
from environmental pressures (Lin et al. 2008, Patzelt et al. 2008, Geiger & Makri 2006,
George 2008, Stede, 2000; 2001a; Cyert & March, 1963), or as a shock absorber (Merchant
1985), and as a buffer to engage in risk taking/innovative behavior (Yang et al. 2009, Herold
et al., 2006; Love & Nohria, 2005). These “idle resources” are, therefore, important in
providing organizations capabilities to act in ways that are not possible for other
organizations poorer in resources (Nohria & Gulati, 1996). George (2005) maintained that the
presence of slack can be used as an enactment of strategies. Lawson (2001) urged that
attempts to reduce slack may be ill-advised; and in a more provoking position, Martinez and
Artz (2006) even argued that “it is not possible for a firm to survive long without the
presence of resources above and beyond its immediate needs” (p.12)
On the other hand, economists such as Jensen (1986; 1993) and Jensen and Meckling (1986)
argued that slack reduces incentives to innovate and promotes undisciplined investment in
R&D activities. They further argued that this slack creation rarely yield economic benefits
and reflects the self-serving interest of managers. Bourgeois (1981) and Yasai-Ardekani
(1986) documented that slack promotes the creation of suboptimal systems, processes, and
structures that reduce a firm’s aggressive explorations of new responses (e.g. innovation,
1
The paper is funded by Indonesian Higher Degree General Directorate, Ministry of Education, Indonesia ,
under scheme No 238/E5/LL/2011
1
creativity). In fact, as been noted by Cheng and Kesner (1997), the term slack itself conjures
up a host of negative perceptions.
This study is not going to pick either side of this debate, but rather this study aims to provide
a way out of this intractable debate by reconciling the views of economists and accountants.
Particularly, this study proposes that there is a “curse” and at the same, “bless” for both
approaches. In simpler words, current study maintains that there is an inverted U-shaped
between slack and performance, in which the relationship is positive and may turn to negative
when the extent of slack reaches its optimum peak.
Although the positive and negative impact of slack have been recognized in the literature,
few research in management accounting has attempted to test whether slack is good or bad
for business units performance. Bourgeois (1981), trying to reconcile economists and
behaviorists, postulated a curvilinear relationship between slack and organizational
performance in general. Recent studies by Nohria and Gulati (1996), Geiger and Cashen
(2002) and Herold et al. (2006) have extended the non-linear argument between slack and
R&D intensity. They argued that R&D activities cannot be carried out without any slack
available; and on the other hand, too much slack may deteriorate the R&D due to wasted
spending and careless innovation projects.
Furthermore, this study believes that lack of interpretable results between slack and its
outcome may not be looked on the relationships, per se. but the focus of the study must also
be directed to the slack conceptualization that we believe, is the source of those intractable,
unsolved debate. Slack creation, that can be traced back to the behavioral theory of the firm
(see seminal works of Cyert and March, 1963 and Bourgeois, 1980) is a multi-dimensional
construct, and not as observed variable that can be traced directly to the budgeting process of
a firm. The use of subjective measures per se raises some question about the accuracy in
measuring budgetary slack. Organizational theorists (e.g. Bourgeouis, 1981; Cyert & March,
1963) proposed objective measures of slack in organization that rarely put into considerations
in management accounting research, despite its flourishing use of its conceptualizations. Such
objective measures were usually operationalized using financial indicators of slack such as
absorbed and unabsorbed slack (Singh, 1986) and available (Ahuja, 2000, Combs & Ketchen,
1999), recoverable (Steensma & Corley, 2000) and potential slack (Simerly & Li, 2000, see
also Daniel et al., 2004 for a meta analysis). Therefore, in order to provide a more meaningful
result, this study looks at slack from the objective and subjective measures.
Therefore, this study aims to examine the non-linear pattern of multidimensional construct of
organizational slack to its performance outcome. As a consequence, this study also
contributes to the wide-array of accounting literature in several ways. First, this study is
among the first to test the non-linear attributes regarding the relationship between slack and
performance, in their higher order terms (multi-dimensional constructs). Second, this study
provides a way out of the intractable debate between behaviorists and economists by
reconciling those views. In particular, this study insists that there is “curse” in both “too few
slack” and “too much slack”. For instance, too few slack may inhibit the business units to
flexibly engage in their activities because there is no room to make maneuvers (as there is no
idle resource). On the other hand, too much slack reveals inefficiency and pursues the
business units to make insufficient, pet projects that may not yield economic benefits to the
organizations.
2
This study is decomposed into several sections. The next part of this study explains in detail
the literature review and hypotheses developments, while the methodology of the study is
explained in the third part. The fourth and fifth parts of the study elaborate the findings and
discussion, while the conclusion, limitations and avenues for further research are discussed in
the last section.
LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT
Nature of Organizational Slack
The leading view of financial (organizational) slack used in the literature is one based on
Cyert and March (1963), in their seminal work entitled A Behavioral Theory of the Firm.
They are credited and cited most often for their preconceived ideas on organizational slack.
Their impressive essence conceptualization of slack was excess of payments over the
minimum necessary required to maintain the organization that took an additional idea which
is so-called “reserved resources”. Thus, it is likely that members of the organization may
have a different resource needs and different slack requirement depending upon
environmental favorableness. Cyert and March (1963) suggest the need for slack as a buffer
by proposing that
…it seems to be useful in dealing with the adjustment of firms to gross shifts in
the external environment…When the environment becomes less favorable,
organizational slack represents a cushion. Resource scarcity brings on renewed
bargaining and tends to cut heavily into the excess payments introduced during
plush times…the cushion provided by organizational slack permits firms to
survive in the face of adversity. (pp. 37-38)
A great deal of authors have then defined slack into diverse conceptualizations (kindly
compare the works of Nohria & Gulati, 1996; George, 2005; Chattopadyay, 2001; Love &
Nohria, 2005; Martinez & Artz, 2006, among others). These various conceptualizations also
lead to the conflicting stands regarding the benefits and disadvantages of having slack in an
organization (refer to table 1)
3
Table 1: Positive and negative impacts of organizational slack.
Positive impacts of organizational slack
1.
enhance the fit between strategy
and structure (George 2005)
2.
influences ability of a firm to
adapt
to
its
environment
(Bourgeois, 1981;
Miller et.
1996)
facilitates innovation (Cyert &
March, 1963; Herold et al. 2006,
Martinez & Artz 2006; Nohria &
Gulati 1995)
Encourages increased risk-taking
(Martinez & Artz, 2006; Singh
1986)
Facilitates
creative
strategic
behavior
(Bourgeois
1981;
McGratch & macMillan, 2000;
George 2005)
Encourages
experimentation
(Bourgeois 1981)
3.
4.
5.
6.
7.
8.
Negative impacts of organizational slack
1. reflects organizational inefficiency
(Bourgeois, 1981; Jensen and
Meckling 1978)
2. encourages a lack of discipline
3. Diminishes incentives to innovate
(Jensen 1986)
4.
enhancing
the
non-optimizing
behavior (Bourgeois 1981, Jensen &
Meckling 1978)
5. Loosen the management control
systems (Davis & Stout 1992)
6. leads to wasted resources and
careless spending (McGrath &
MacMillan 2000)
Encourages increased risk-taking
(Singh 1986)
Supports
exploitation
of
opportunities (Bourgeois 1981)
Financial Slack
Slack resources can be measured using several financial indicators. Most prior researches
differentiate slack into three main typologies; which are available, recoverable, and potential
slack resources (Bourgeois, 1981; Bourgeois & Singh, 1983; Sharfman et al, 1988; Singh,
1986). Available slack (that can also be referred as unobserved slack) describes the resources
that are available but not yet committed for any particular allocation such as the funding for
innovation activities or dividend payments to shareholders (Martinez & Artz, 2006).
Recoverable slack (as it is sometimes referred as absorbed slack) represents resources that
have been allocated and absorbed by the organization but can be easily recovered through
cost-cutting and efficiency. One example of recoverable slack is the overhead costs for
executive salary. Nevertheless, as pointed out by Herold et al. (2006) and Hendrick (2006),
although recoverable slack is theoretically easy to recover, but in practice the recovery could
be difficult and may bring out some strong negative consequences. Potential slack on the
other hand is simply conceptualized as the organization’s future capability to earn resources.
Usually potential slack is basically operationalized as the extent of equity capital owned by
the company.
4
The presence of slack has been linked to the idle capacity of the firms. As company resources
increase, the presence of slack in organization also increases, but in a faster rate (e.g. Cyert &
March 1963). In contrary, when the company resources decrease, organizational slack
decreases, also at a faster rate. The financial mechanism of slack over time is a function of
sales growth, profitability, situational and behavioral factors. Leavins (1995) postulated that
the slack in the highly performing firms inherently tend to increase, but firms can find many
alternative ways to reduce the costs if they are forced to do so. This relationship was modeled
by Wolf (1971) as:
E
SGE
 0,
 0,
R
E
and
E
SGE

R
R
E
SGE
 0,
0,
R
R
and
E
SGE

R
R
Use of
resources in a
slack building
state
Use of
resources in a
slack
reduction
state
E indicates the change on profit on time t and t-1 while ΔR denotes the change on revenue,
while ΔSGE denotes the change on selling and general expenses. The models obviously
evoke the question why firms have lower change of profit while on the profitable situation,
and they still can operate normally and earn above-average profit even in a very fierce
situation, as is the case of some organizations in the crisis period.
Budgetary Slack
Earlier work defined budgetary slack as the result of management’s consciousness and
intentional behavior during the budgetary process as an outcome of rigid budgetary
evaluation (Schiff and Lewin 1968). Recently, Douglas et al. (2007) defined budgetary slack
as the variances of actual spending and budgeted spending and the difference between the
expected and actual performance. Garrison et al. (2006) proposed budgetary slack as the
consequence of self-imposed budget which might result in inefficiency and waste. On the
other hand, Yuen (2004) conceptualized budgetary slack as the building of excess resources
in a budget or understating productive capability and thus will make the budget easier to
attain. Douglas and Wier (2000) claimed that budgetary biasing behavior is the difference
between planned performance target and real performance capabilities. Leavin et al. (1995)
insisted that budgetary slack exist due to the results of management conscious and intentional
behavior during the budgetary process.
The non-linear relationship between slack and performance
Organizational slack which is the available resources above immediate, required needs is one
possible source of funding for many activities. Therefore, several researchers have linked the
needs of slack for innovation-lead performance activities. Nohria and Gulati (1996) insisted
5
that slack may increase the undisciplined investment and thereby deteriorating the innovation
activities.
A behavioral theory of the firm would maintain that slack to have some positive impacts on
performance in several ways (Cyert & March, 1963; Bourgeois, 1981). First, the presence of
slack may loosen the managerial controls rigidity of a particular organization (Cyert &
March, 1963), allowing manages to embark on discretionary steps in pursuing new projects
(Geiger & Makri, 2006). Second, the slack resources can be consumed during bad times and
thus becoming less vulnerable to the uncertainty of experimental projects and thereby
increasing the innovative cultures (Nohria & Gulati, 1996). Members of the organization are
also less likely to worry about the risk of failure in embarking a particular project because
they have resources as a buffer against the failure (Geiger & Makri, 2006).
On the other hand, slack has been argued to have some negative impacts on performance as
the managers may utilize the slack resources for less risky activities thereby may decrease the
experimentation and innovation activities (Denis et al., 1999; Jensen, 1986). Agency
perspective also warned the use of slack not as to foster experimentation and innovation,
rather as a resource to maximize their own personal wealth or interests. On the other hand, XEfficiency theory of Leibenstein (1978) view slack as wasteful and incompetence of business
units. These two views of theories would maintain that slack should be reduced and if
possible eliminated.
Reconciling the behavioral theory of the firm and economics, it is interesting to note that
slack can be a blessing and a curse, implying the presence of curvilinear relationship between
slack and performance. The advocates of slack (a behavioral theory of the firm) maintained
that slack as a resource facilitating proactive strategic actions and thereby increasing
performance (Daniel et al., 2004). In contrary, those who assume slack as idle resources
denotes for inefficiency (X-Efficiency (Leibenstein, 1966; theory of the firm of Jensen &
Meckling, 1978) and diminish long term organizational performance. This inefficiency
paradigm also posits that slack can encourage satisfying or self-serving behavior that hurt
performance. For instance, Jensen and Meckling (1978) and Jensen (1986) maintained that
the presence of excess resources may enhance the managers tendency to pursue self-serving
projects.
It is therefore, interesting to figure out whether there is a “curse” in both the economics and
behavioral perspectives. In this vein, organization must have excess resources to absorb for
the unforeseen contingencies but not too much so that preventing the self-serving behavior of
the managers.. Therefore, this study predicts that the relationship between slack and
performance is inverted U-Shaped.
METHODOLOGY
The population frames of current study, where the source of data were gathered, were from
several sources. Corporate parents’ annual reports and Indonesian Capital Market Directory
(ICMD) 2006 & 2007 were used to identify the number of business units being controlled
and firms-specific financial attributes. ICMD periodically published a concise public firm’s
financial statements. Firm’s annual reports were then utilized to identify the business units.
Another set of directory that was used in this study is Indonesian Manufacturing Industry
Directory (IMID) that is issued periodically. This directory was useful in identifying
6
addresses, primary products and employment of business units. The total manufacturing
companies per December 2006 is 20,890 companies.
In order to ensure the validity of the findings, the study restricts the sampling procedure into
a subsidiary of a corporate with a 50% ownership minimum and must at least own two
subsidiaries. Therefore, this study was conducted at the business units’ level in order to
understand the ways, effectiveness and appropriateness of control and monitoring activities
placed by the corporate parents.
The cover letter involving questionnaires were sent via mail (in stamped addressed envelope)
directly to the top and middle level manager in a respective business unit since they are the
ones that have considerable contact with the corporate. The cover letters also assured that
there would be no responses attributed to any individual or business unit, and only statistical,
summary data from the total responses from several business units would be published.
The questionnaires were developed using 6 item Liker scale. The use of six items Likert scale
has been commonly employed in social sciences and in fact, may result in greater efficiency
and reliability (Chang 1994). A study conducted by Infosurv (2006) and CICIES (2007)
indicates that some respondents prefer the 6-items Likert Scale because the respondents have
to commit to either positive or negative values, without any neutral point.
Operationalization of Variables
Organizational Slack
Business units’ slack, in this study, is conceptualized as the excess of actual or potential
resources that could assist the organization to absorb the environmental pressures and shocks
(Bourgeouis, 1980). This variable is a multidimensional constructs consist of two
dimensions: financial (business units’ slack and budgetary slack).
Financial slack represents the extent to which the organizations have the access to the
resources to be further utilized during unexpected shocks or take immediate actions for the
emergent opportunities (Martinez & Artz, 2006). With regard to this financial slack,
agreement has been reached pertaining to its operationalizations. Usually, it consists of
available slack, potential slack and recoverable slack. For these variables, two steps were
employed. The study use archival, objective measures of business units slack generated from
annually financial statements and/or annual report. If these data were not available, survey
method will be conducted. Business units managers will be asked to indicate the amount of
slack (proxied by several financial ratios) in their business units. If both data are available,
objective measures will be used since there is no social obligation from managers to report
good results thereby increasing the validity of the data.
Financial slack is measured using three indicators: 1) available slack that is determined
according to current ratio (i.e. current assets/current liabilities) which a reflection of
organizations’ resources availability on terms of liquid assets that can be used as a buffer
from the negative implications of environmental shocks (Herold et al., 2006). Current assets
in this study are simply defined as the assets that can be easily converted into cash within a
short time. It consists of cash, marketable securities, receivables, inventories and other short
term assets. Current reliabilities on the other hand is the financial obligations that have to be
settled within a short period of time. 2) potential slack, that is defined as the firm’s ability to
7
have new capital resources through debt borrowings (Martinez & Artz, 2006). Following
Palich et al. (2000) and Simerly and Li (2000) suggestions, this study measures potential
slack as debt-equity ratio. 3) recoverable slack, that is also known as absorbed slack, is the
extent to which resources are embedded in firms as excess costs but could be recovered
through when firms experience financial difficulty (Singh, 1986). Following Geiger and
Makri (2006), recoverable slack is measured by selling, general and administrative expenses
divided by sales.
Budgetary slack, on the other hand, is defined as manager’s likelihood to set the budgets
lower by underestimating the budgeted revenues and overestimating the budgeted costs so
that the budget targets becomes easier to achieve. (Lukka, 1988). This variable was measured
by Dunk (1993) and Stede’s (2000; 2001) measurement consists of 5 items (items 1-4, using
6 items Likert’s scale from strongly disagree to strongly agree, and item 5 is fully anchored
question asking whether the budget is very easy to attain until impossible to attain).
Following Stede (2001, p. 41), the questionnaires include: 1. Succeed to submit budgets that
are easily attainable; 2. Budget target induce high productivity in my business unit (reverse
coded); 3. Budget target requires cost to be managed carefully in my business unit; 4. Budget
target have not caused me to be particularly concerned with improving efficiency in my
business unit; and 5. a fully anchored question: “My Business unit budget is…” from very
easy to attain to impossible to attain
Performance
Current study adopted two widely used of financial performance, which are Return on Assets,
Return on Equity, operating profit and sales growth. Moreover, subjective measures of
business unit performance were also employed. Using financial, objective measures of
performance will increase the likelihood the presence of 1 or more year lag relationship
between slack and performance. For instance, slack resources may not affect the performance
on its current year, but it probably affects performance on its 1 or more year a head. While
subjective, non-quantitative measures of performance are created using the measurements of
Birkinshaw et al. (2005). In this vein, the performance of business units managers are
evaluated, relative to other business units, on the basis of their productivity, quality, supplier
relationships, labor costs, productivity improvements, technology and customer development
on a six point scale, ranging from 1=significantly worse than competitors, and 6 =
significantly better than competitors.
Data Analyses
Structural Equation Modeling (SEM) was employed in this study for several reasons. First,
SEM allows the analysis of multiple relationships simultaneously that cannot be conducted
by other conventional multiple regressions analyses. Thus, SEM accounts for the presence of
structural errors. Ignoring these errors may lead to the specification errors affecting validity
of the results. Second, SEM provides measures of overall model fit. These measures were
important to figure whether the model is acceptable given a particular data. Third, and most
importantly, SEM explains the significance of each relationship between the variables
hypothesized. SEM also allows for testing the indirect effects between variables. Fourth,
unlike regression models and path analysis, SEM may account for the effects of measurement
errors in multi-item variables (constructs). Since constructs were measured using multiple
indicators, it is unreasonable to assume that these constructs are error-free, and instead, there
are potential errors in those indicators.
8
In testing the non-monotonic relationship of the hypothesis, this study adopts an approach
suggested by Ping (2004, 1995) and Cohen et al. (2003) involving two steps. In the first step,
the measurement model is evaluated by Confirmatory Factor Analysis. The measurement
model assessed whether all items in a given scale represented the same latent factor. Second,
the structural model then examined to ensure whether the variables hypothesized were fit. On
the next step, an estimation technique is proposed for quadratic latent variables in structural
equation modeling specifying these quadratic latent variables with a single indicator (Ghozali
& Fuad, 2004). With regard to this single indicator approach, the quadratic product (x:x) of
slack is specified as [x1 + x2 + … + xn]2. The loadings (λx:x) are given by [λx1 + λx2 + …+ λn]2
and measurement errors (θx:x) are fixed by [4(λx1 + λx2 + …+ λn)2. VAR(X). (θε.x1 + θε.x2 + …
+ θε.xn). As been suggested by Anderson and Gerbing (1988), use of a measurement model
must be separated from model structure issues. Therefore, besides using the measurement
model to ensure unidimensionality of the constructs, parameter estimates from a linear-term
measurement model can be used to compute the values of λx:x and θx:x (fixed loadings and
fixed errors, respectively). This approach may eliminate the substantial differences in the
estimated parameters of measurement models and structural models (Ping, 1995).
9
ε1
x1
ε2
x2
ε3
x3
ζ1
x4
ε5
x5
ε6
ε7
η1
Bus.Unit
Slack
Prfrmance
x8
y2
y2
y3
y3
y4
y4
y5
Y5
y6
y6
y7
y7
y8
y8
y9
y9
N.F.P
FIN.SLK
ξ2
ε8
F.P.
ζ3
x6
x7
y1
BUDSLK
ξ1
ε4
y1
ζ4
ζ2
ζ5
η2
1
1
y10
y10
y11
y11
Figure 1: the structural model of second order performance outcome of business units’ slack.
10
This model is estimated using this polynomial technique by (1) estimating the measurement
model parameters, (2) calculating the equations above to generate the loading (λx:x) and error
variances (θx:x) for the quadratic latent variable, and (3) estimating the structural model with the
fixed values of λx:x and θx:x. This method employed Linear Structural Relationship using
Maximum Likelihood approach. This procedure requires mean-centered indicators for both
exogenous and endogenous latent variables, which is created by subtracting the indicator’s mean
with its each value in the data set per case (i.e. [xi - µx]; where xi denotes for observation i-th of x
manifest variables and µx denotes for mean of a particular manifest variable x). the model fit was
tested by several indices. Table 2 portrays important indices and their respective cut-offs.
RESULTS
The profile of business units are clearly portrayed in table 5.6. Business units with public-listed
corporate parent comprise 55% of the sample while the remaining 45% are business units with
non-public listed corporate parent. Regarding the size of the firm (in terms of average sales),
sixty seven business units are considered large as they earn more than Rp 10 billion on sales,
fifty one are considered medium as they make Rp.5-10 billion sales while seventeen are regard
as small since their average sales are less than Rp 5 billion. Regarding the types of the business
units, seventy five business units are local based-company seeing that their products are aimed
for local markets, while sixty business units are multi-national company. Regarding the business
units tenure, eighty one business units have been in operation for more than ten years, while fifty
three business units have been in operation for 6-10 years.
Pertaining to the production type, fifty one business units engage in food and beverages industry,
thirty one in textile mill products, twenty nine in lumber and wood products, and twenty three
business units enroll in chemical and allied products. Regarding the focus of their market, forty
five business units focus on local market and twenty one business units focus on export market.
Sixty nine business units focus on both local and export market. All of the respondents reveal
that they are involved in the budgeting process, but only sixty nine of one hundred thirty five
receive full autonomy from the corporate parent, while the remaining sixty six business units
hold no/partial autonomy.
11
Table 2: Business units’ characteristics.
Frequency
Percent
Corporate Status
- Public Listed
- Non-public listed
74
61
54.8
45.2
Type of Business Units
- Local based Company
- Multi-national Company
75
60
55.6
44.4
Business Units Tenure
- 1-5 years
- 6-10 years
- More than 10 years
1
53
81
0.07
39.3
60
51
31
29
37.8
23
21.5
23
17
1
0.07
Type of Products
- Consumer products
- Industrial products
- Both or others
77
52
6
57
38.5
4.4
Autonomy
- Full Autonomy
- Partial/No autonomy
69
66
48.9
51.1
Production Type
- Food and Beverage
- Textile Mill Products
- Lumber and Wood
Products
- Chemical and Allied
Products
- Others
The result of Confirmatory Factor Analysis (CFA) in the first step is conducted in order to
calculate the fixed loadings and error variances for the second step are portrayed in table 3. The
results below did not used for measurement models testing. Rather, this step is conducted in
order to uncover the fixed and constrained values for the single indicator of quadratic latent
variables of financial and budgetary slack.
12
Table 3: First step of Ping (2004) approach in non-linear Structural Equations Modeling.
Items
BUDSLK1
BUDSLK2
BUDSLK3
BUDSLK4
BUDSLK5
CRT
DERT
SLEXT
Loading
0.39
0.55
0.38
0.39
0.40
0.21
-0.31
0.38
Errors
0.84
0.69
0.85
0.85
0.84
0.96
0.90
0.86
R2
0.16
0.31
0.15
0.15
0.16
0.04
0.1
0.14
Applying the generated loadings to [λx1 + λx2 + …+ λn]2 yield the constrained loadings for
budgetary slack of 2.01 and financial slack of 0.1296. Furthermore, applying the generated error
variances to [4(λx1 + λx2 + …+ λn)2. VAR(X). (θε.x1 + θε.x2 + … + θε.xn) yield constrained error
variance about 73.528 for budgetary slack and 1.399 for financial slack. Thus, the measurement
model for non-linear outcome performance equation is:
 x1   x1.1
 x  
 2   x 2.1
 x3   x 3.1
  
 x 4   x 4.1
 x5   x 5.1
 
 x6   0
 x7   0
  
 x8   0
x   0
 9 
 x10   0
0
0
0
0
0
 y1.2
 y 2.2
 y 3.2
0
0
 1 




 2 

 3 
0
0 



0
0  1    4 
0
0   2    
 

0
0   3    6 
0
0   4    7 



0
0 
 8 
73.528
4.4944
0 



0
0.1296
 1.399 
0
0
0
0
The constrained error variances and loadings generated then used to calculate the nonmonotonic relationships hypothesized in this study. The results are depicted in table 4. The
results indicate that there is an inverted U-shaped () relationship between financial slack and
financial performance ( = -0.027, t = -6.90). However, the proposed inverted relationship
between financial slack and non-financial performance cannot be accepted ( = -0.0035, t = 1.18).
13
Table 4: Results of Non-linear Structural Equations Modelings.
The Effect of…
Financial Slack
Budgetary Slack
Financial Slack2
Budgetary Slack2
Financial Slack
Budgetary Slack
Financial Slack2
Budgetary Slack2
To…
Financial Performance
Financial Performance
Financial Performance
Financial Performance
Non-Financial Performance
Non-Financial Performance
Non-Financial Performance
Non-Financial Performance
Estimates
0.73
-0.25
-0.034
0.0082
0.28
0.52
-0.0043
-0.0061
t-values
7.37*
-2.45*
-6.96*
1.02
3.84*
6.39*
-1.15
-7.90*
Interestingly, this study found that there is no quadratic effect of budgetary slack to financial
performance ( = 0.002, t = 1.10), but hinted the presence of non-linear relationship () between
budgetary slack and non-financial performance ( = -0.013, t = -7.90).
The results can also be elaborated to figure-out the optimum level of slack. For instance, the
results above indicate that there is a non-linear relationship between financial slack and financial
performance. For a simple non linear function of Y = b1 X + b2X2 +e, the maximum value of
vertex (peak value of the parabolic graph) would be –b1/2b2. Kindly recall that the non-linear
structural equation function is FP = 0.73*FS + -0.034*FP+0.28 therefore, the maximum value of
the vertex would be = 0.73/(2*-0.034). The graph below visualizes the non linear relationship
between financial slack and financial performance.
Financial
Performance
21
17
15
19
Financial Slack
13
11
9
7
5
3
Series1
1
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
S1
Figure 1: The non-linear relationship between financial slack and financial performance.
DISCUSSION
This study cannot test the effect of higher order business units’ slack to higher order overall
performance as the model did not fit well with the data. Rather, this study examines the nonmonotonic impacts of lower order exogenous variables of business units’ slack (e.g. financial
and budgetary slack) to lower order endogenous variables of performance (e.g. financial and
14
non-financial performance). The acceptance or rejection of the hypothesis therefore, is based on
this assumption.
This study found that there is a non-monotonic relationship between financial slack and financial
performance. In particular, this study found that the relationship between financial slack and
financial-performance is inverted U-Shaped. It means that the relationship between financial
slack and financial performance is positive, until it reaches the peak point and then turn to
negative. Hence, it signifies that there is a “curse” in both very few financial slack and too much
financial slack pertaining to its effect with financial performance.
This non monotonic () relationship implicitly concurs with several arguments on the slackperformance relationships (Latham & Braun 2008; George, 2005; Tan and Peng, 2003; Nohria
and Gulati, 1996). This finding substantiates the joint roles of behavioral theory of the firm as
well as economist perspectives. The behavioral theory of the firm argues that slack as good and
may increase the innovative ideas and to absorb the shock of environmental turbulent and thus
may increase the firm’s financial performance. After some level, based upon the perspective of
economist, too much slack may inhibit the innovative ideas as there is a great chance that the
business units will be investing in pet-, non productive projects, and therefore may inhibit
financial performance.
However, it is interesting to figure out that the alternative hypothesis of the non-linear effect of
financial slack to non-financial performance cannot be accepted. One main possible explanation
for this failure is probably due to the presence of lag effect financial slack to non-financial
performance. In particular, the presence of financial slack may not directly affect the nonfinancial performance in a timely manner, rather, it is plausible that the effect can only be seen
within the next few years a head. Or simply stated, current financial slack may impinge on future
non-financial performance (e.g. productivity, product quality, supplier relationship, productivity
improvement, technology, customer development and labor cost). However, this speculation
cannot be further tested as this study is cross-sectional in nature and such longitudinal data are
very hard to attain. The use of objective, pure quantitative data may also be blamed for such a
finding.
Furthermore, the result of this study indicates the rejection of the alternative hypothesis
regarding non-monotonic relationship between budgetary slack and financial performance.
Rather, this study found the negative, linear effect of budgetary slack to financial performance.
Several arguments are offered regarding the non-acceptance of non-linear effects of budgetary
slack ton financial performance and acceptance of negative linear effect of budgetary slack to
financial performance. First, the sample of this study is the business units that are held
accountable on terms of the cost spent and revenues generated, or simply stated the samples were
profit centers of the corporate parents. With this regards, the slack creation during the budgeting
process implicitly means the flexibility, innovativeness and creativeness that are transformed into
operating actions that shall yield in short-term profit or performance. Indeed, there is a
possibility that the positive effects of budgetary slack to financial performance may not be exist
in the long-run, as they may in fact impair the long-term profitability. Nevertheless, this
argument cannot be further tested in this particular finding as longitudinal or pooled, cross-series
study should play a major approach for this type of study.
15
Furthermore, as expected, this study found the presence of non-monotonic relationship between
budgetary slack and non-financial performance. This finding indicate that slack creation during
the budgeting process yields the intangible performance, but again, too much budgetary slack
may in fact impair the stability of the firms’ particularly on terms of its intangible performance
relative to business unit’s performance. This finding apparently solve the intractable debate
between “behavioral accountants” (Stede 2000; 2001, Davis et al., 2006; among others) and the
economists (so called “theorists of the firm” such as Jensen, 1986; Jensen & Meckling, 1976
among others) regarding the non (discretionary) use of budgetary slack to the performance.
CONCLUSION
The findings of these studies need to be considered in light of several limitations. First, the
research was confined to a manufacturing industry in Indonesia, and thus generalizations to other
industries should be used with extra cautions. It is very plausible that the pattern of relationships
between the slack and performance may be different than those found in this study.
In order to provide fruitful findings, as well as robust generalizations of the estimated
parameters, further study should consider other industries, particularly in Indonesia. Martinez
and Artz (2006), Hendrick (2006), Combs and Ketchen (1999), Hitt et al. (1991), and many
others argued that slack requirement may be different among different industries, and thus the
reasons and its outcome may be different from one industry to another.
Second, it is necessary to acknowledge the limitation of cross sectional based survey research, as
such this study design prevent any test on causal statement on the time series basis. Besides,
slack creation can be an accumulation of several periods phenomenon. In particular, the slack
creation may not affect the performance in the timely manner, but they may be transformed and
require time period to show its real effect. For instance, slack may affect future performance,
instead of current performance. With this regard, future research should also consider the time
series properties of the data, particularly on the contextual variables affecting business units’
slack and slack outcome to performance.
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