Calhoun: The NPS Institutional Archive

Faculty and Researcher Publications Faculty and Researcher Publications

1992

Organizational slack and risk-taking

behaviour: tests of product pricing strategy

Moses, O. Douglas

MCB University Press

Journal of Organizational Change Management, v.5, no.3, 1992, pp. 38-54

http://hdl.handle.net/10945/38012

JOCM 5,3

38

Organizational Slack and Risk-taking Behaviour: Tests of Product Pricing Strategy

O. Douglas Moses Naval Postgraduate School, Monterey, California, USA

Organizational change inevitably involves uncertainty and some degree of risk taking. What organizational conditions are associated with greater risk taking? This article examines the relationship between organizational slack and risk-taking behaviour. To the degree that slack is associated with risk taking, the presence or absence of slack is relevant to organizational change. To the degree that organizational change leads to the creation or reduction in slack, future risk-taking behaviour may be altered.

Traditional theories in economics and finance argue that individuals and organizations are risk adverse and that higher-risk projects or strategies will be undertaken only if there is a commensurate higher expected return. Such theories suggest that over the long run a positive association between risk and return should be exhibited. However, studies of the within-industry relationship between risk and return indicate that the observed relationship is most often negative (Bowman, 1980; Treacy, 1980). Termed the "risk-return paradox" (Bowman, 1982), this inverse relationship has been addressed by various authors (Cyert and March, 1963; March, 1981; March and Shapira, 1982) and can perhaps be explained in terms of a satisficing level of firm performance (March and Simon, 1958; Simon, 1976). Simply put, firms performing above their satisficing level may prefer a low risk (low variance) decision because it reduces the probability that subsequent performance will fall below the satisficing level, while firms performing below their satisficing level may prefer a high risk (high variance) decision because it increases the probability that subsequent performance will fall above the satisficing level.

Singh (1983, 1986) cited evidence both supporting and rejecting the hypothesis that poor performance motivates increased risk taking and argued that the contradictory empirical findings occur because performance and risk taking are linked in a complex manner. He posited two conceptually distinct processes that link performance and risk taking. In his model, good performance has a negative direct impact on risk taking because of the role of the satisficing level, mentioned above. On the other hand, there is also a positive impact, mediated by organizational slack. First, good performance increases organizational slack; then increased slack provides the opportunity for increased risk taking. Singh (1986) tested his model and found tentative support for both processes; measures of performance were negatively associated with some measures of risk, but performance was also positively associated with slack, which was positively associated with risk.

Journal of Organizational Change Management, Vol. 5 No. 3, 1992, pp. 38-54. © MCB University Press, 0933-4811

Slack and Risk Taking This article focuses on the relationship between slack and risk taking — one link in the Singh model — and presents a test of the hypothesis that increases in organizational slack are followed by more risky strategic decisions.

Slack implies the presence of resources in excess of what is required for "normal" efficient operation of a firm (Bourgeois, 1981). Greater risk implies greater uncertainty surrounding the future outcome of a present decision. The case for a positive relationship between slack and risk taking rests on the contention that slack allows the firm to interact with its environment more boldly (Bourgeois, 1981) and permits experimentation by providing a buffer against downside risk (Singh, 1986). This view follows from work on the relationship between slack and innovation: Hambrick and Snow (1977) suggest that slack provides the opportunity to experiment with new products or markets. Thompson (1969) argues that slack results in the legitimacy of experimentation being questioned less. Some support for these arguments are found in Mohr (1969) and Rosner (1968). Cyert and March (1963) argue that slack reduces the problem of scarce resources and supplies the funds for innovations that would not be possible given scarcity. Consequently, slack reduces the criteria by which actions are judged acceptable. They also see slack as a pool of emergency resources which can be used to absorb potential variability and uncertainty in a firm's environment.

While, like Singh (1983, 1986), this article empirically tests the relationship between slack and risk taking, there are differences between the approaches used. First, Singh tested for associations between slack and global measures of risk (developed from a questionnaire). This study instead isolates a specific strategic decision, characterizes alternatives in terms of risk, and tests for associations between slack and the alternative adopted. In short, the focus is on a specific, identifiable action. Second, Singh tested for contemporaneous associations between slack and risk measures. This study investigates the association between changes in slack and subsequent risk-taking behaviour. It may be more defensible to argue for a cause-effect association when the potential effect (risk taking) is observed at a point in time following the presumed cause (slack). Third, this study incorporates a wider set of measures to reflect slack and provides an analysis of the relationships between those measures. The specific strategic decision addressed in this study is pricing strategy for new products. Pricing strategy is investigated in a particular industry (aerospace) for a particular product type (major weapon systems) sold in a particular market (sales to the US Department of Defense).

Pricing Strategies Skimming and Penetration Firms introducing new products or technology typically use one of two broad product pricing approaches: penetration or skimming. Discussed by many authors (Albaum, 1975; Caferelli, 1980; Dean, 1969; James, 1969; Wasson, 1974; Wind, 1982), the two strategies are widely understood and used by business practitioners. The objectives of the two strategies differ. The skimming strategy

Organizational Slack and Risk-

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39

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calls for high initial prices followed by lower prices at later stages. The objective of the skimming strategy is to achieve the maximum profit in the shortest time by charging the highest price that the market will bear. Thus one advantage of skimming is a more rapid return on investment. In contrast, the penetration strategy calls for a low initial price with little or no price reduction over time. The objective of the penetration strategy is to develop wide product demand rapidly through a low initial price. Once a market has been established, the firm can take advantage of either price increases or cost reductions to earn additional profits.

Each of the two strategies can be described in terms of the relationship between two variables: the price of the first unit sold and the rate of price reduction over time. Skimmers exhibit a high first unit price and a steep price reduction curve, while penetrators exhibit a low first unit price and a flat price reduction curve.

Pricing Strategy and Risk The two strategies differ in the timing of profits (short-term versus long-term) and consequently in riskiness. With a high initial price, skimming maximizes short-term returns and provides a more rapid recovery of funds to finance the costs of product introduction and future expansion Games, 1969). By front-ending profit, skimming reduces the risk associated with uncertainty in the product's market (Dean, 1969). Skimming allows for greater flexibility; it is typically easier to introduce a product with a high price and then reduce the price as knowledge of the market is gained than it is to introduce at a low price and increase price later to cover unexpected costs or exploit product popularity (Dean, 1969). Skimming emphasizes short-run profits and consequently reduces the risks associated with predicting future demand and future costs.

The penetration strategy sacrifices short-run profits in an attempt to establish a market and generate profits over the long run. Penetration generally requires a greater commitment of the firm's resources, both because its long-run orientation may require greater investment in productive capacity and because the required investment may not be adequately financed out of the relatively lower initial profits (Caferelli, 1980). "High rewards are possible with this strategy but only if economies of scale occur as predicted. Therefore, it is often a high risk strategy as well, since the potential exists for disastrous losses if costs fail to decline as rapidly as expected. Production problems or unrealized sales volume can also undermine this strategy" (Small Business Report, 1985, p. 77). Penetration appears to be the more risky strategy.

Pricing Strategy in the US Defence Market Clearly defence contracting, particularly for major weapons systems, is specialized in nature. If competition to produce a major weapon system exists at all, that competition usually is based on system capability, not price. First, a contractor is selected to produce a weapon system. Then price is determined by negotiation and a contract agreed upon prior to actual production. Prices specified in the contract are typically based on costs incurred ("cost plus")

Organizational Slack and Risk-

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41

using some agreed upon formula. Hence, prices may seem to be a direct function of costs incurred, with little leeway allowed for contractor pricing discretion. However, prior research has explained how contractors may use accounting procedures to alter the pattern of costs incurred over time and hence "cost justify" different pricing strategies (Greer, 1983, 1984, 1985; Moses, 1991). Shifting costs to early years of a programme (and away from later years) justifies a relatively high initial price (and results in a declining price in later years) — consistent with skimming. Shifts costs away from early years is consistent with penetration.

A contractor for a new weapon system has two alternatives. The firm can skim to ensure profitability and the recovery of invested funds in the short run. Or the firm can agree to a low intitial price, "buying-in" to the programme (sometimes at an initial loss) in an attempt to get the programme established. The firm then presumes that subequent renegotiation or future contracts will result in satisfactory profits in the long run.

The penetration strategy has been argued to be more risky (Moses, 1989). The complexity, innovation, and high performance requirements associated with major weapon systems mean that their capability and reliability cannot always be assessed in advance. This creates uncertainties with respect to product acceptance and the future demand for additional units. Furthermore, the constantly changing economic and political environment creates uncertainties with respect to the willingness of congress or the executive branch to budget for additional units. This results in uncertainties with respect to programme curtailment or termination. Technical, political and economic consideration also affect the readiness of the Department of Defense to renegotiate[1]. Using pricing strategy as a strategic decision and treating penetration as the more risky strategy, the central hypothesis calls for a positive association between increases in organizational slack and adoption of the penetration strategy.

Sample, Data, Measures The Slope of the Price Reduction Curve As indicated before, the two strategies can be described in terms of the relationship between first unit price and the subsequent price reduction curve. Learning curves can be used to distinguish the two strategies. Learning curves were fit to actual price histories (in constant dollars) to create a measure of the slope of the price reduction curve.

This approach to operationalize pricing strategy follows prior research (Greer, 1985; Moses, 1989, 1991). Relatatively high slope values (flat slope) are consistent with penetration while lower slope values (steeper price reduction) are consistent with skimming. Given the central hypothesis that slack is associated with the more risky penetration strategy, a positive association between slack and price reduction slopes is predicted.

Sample Pricing strategies for major weapon systems were selected for examination because weapon systems are large-dollar items which represent a substantial

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segment of a contractor's business. Pricing strategy for such items is likely to be an important strategic decision. Two cost handbooks (Crawford, 1984; DePuy, 1983), containing cost history data for 126 distinct aerospace weapon system programmes — virtually the entire population of such programmes for a three-decade period — was the starting point for developing the sample.

Programmes were deleted from the sample for the following reasons: First, programmes were excluded if price histories were not available for at least three years (n = 42). Three years of data were necessary in order to calculate meaningful price reduction slopes. Second, programmes where learning curves fit to the price history data provided a poor "fit" were eliminated (n = 8). Since the objective was to use price reduction curves to reflect pricing strategy; only programmes with well defined price reduction slopes were included. An R2 value in excess of 0.6 was used as a cutoff for programme inclusion. Third, some weapon systems had multiple manufacturers and the handbooks provided no separate price history by manufacturer. Since pricing strategy of individual firms is of interest, these programmes were not useful (n = 9). Fourth, programmes were deleted if financial statement data for the manufacturer were not available for two years prior to the start of the programme (n = 13). The primary reason for the lack of financial data was that some manufacturers were privately held. The surviving sample consisted of 53 programmes.

The Measurement of Organizational Slack The concept of slack is widely used in the organizational theory and business strategy literatures, but there is no single consensus definition. However, most definitions suggest the idea of "excess" resources that provide "buffers" or "opportunities". Slack thus involves excess resources rather than just total resources. Because excess resources are difficult to identify, operationalizing measures of slack for empirical purposes has proved to be problematic and approaches have varied widely. Individual accounting-based measures, such as the level of expenditures (DePuy, 1983), operating expenses (Wolf, 1971), return on investment (Litschert, 1978, Odell, 1972), profit (Dimick and Murray, 1978), and sales (Litschert, 1978), have most frequently been employed. Each of these individual measures uses a rather narrow aspect of a firm's condition as a proxy for the broader excess resources concept implied by slack.

Research by Bourgeois and Singh (1983, 1986) has developed a composite set of measures, based on publicly available financial accounting data, to capture slack. They offer a three-category formulation of the dimensions of slack, which rests on the idea of "ease-of-recovery":

(1) Available slack: Resources not yet assimilated into the technical design of the organization (e.g. excess liquidity).

(2) Recoverable slack: Resources that have been absorbed into the system as excess costs, but may be recovered (e.g. excess overhead costs).

(3) Potential slack: The capacity of the organization to generate extra resources from the environment (e.g. ability to raise capital).

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Bourgeois and Singh (1983) provided several accounting based measures within each category. The specific measures used in this study follow their framework (with modifications noted below) and are outlined in Table I.

Some comment on the individual measures is perhaps necessary. Bourgeois (1981) said that the extent to which resources generated by profits are distributed as dividends or retained is a matter of managerial policy and provides a source of slack. He suggested that "net income minus dividends" or the "change in retained earnings" scaled by sales, are appropriate measures of slack from this source. Neither dividend nor retained earnings data was available for the sample. Two measures, Profit Margin and Equity Change, are designed to approximate his measures using data that was available.

Working Capital measures the net resources the organization has tied up in current or operating assets, relative to the level of activity. Ceteris paribus, large stores of current resources (e.g. cash, receivables, inventories) should be an indication of slack. Relying on the "ease-of-recovery" idea, Bourgeois and Singh (1983) decomposed Working Capital into three separate measures: Quick Assets, Receivables and Inventory. All four measures, then, are conceptually related and all capture aspects of the level of current resources relative to activity.

Fixed Assets extends the concept of resources relative to the activity level to non-current assets. Non-current assets reflect capacity and, when deflated by sales, may capture excess capacity. Bourgeois (1981) discussed excess capacity as an indicator of slack, but measures related to plant, equipment and other non-current assets were omitted in the Bourgeois and Singh framework.

General Expense measures the level of selling and administrative expenses relative to activity and captures the idea that slack is absorbed in various period costs such as salaries.

Current Debt and Long-term Debt are both measures of capital structure and are designed to reflect the difficulty or cost of generating additional resources

Variables

Available slack: Profit margin Equity change Quick assets

Recoverable slack: Working capital Receivables Inventory Genera] expense Fixed assets

Potential slack: Current debt Long-term debt

Calculation

Net income/sales Change in stockholder equity/sales (Cash + marketable securities — current liabilities)/sales

(Current assets — current liabilities)/sales Accounts receivable/sales Inventory/sales Selling and administration expense/sales Non-current assets/sales

Current liabilities/stockholder equity Long-term liabilities/stockholder equity

Association with slack

+ +

+

+ + + + +

-- Table I.

Slack Measures

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from the environment by short or long term financing. (Analogous measures scaled by sales or total assets provided similar findings.)

Some comments on the variables collectively are necessary. The Bourgeois/Singh measurement framework is designed to generate relative rather than absolute measures of slack. The measures are relative in two senses: First, they incorporate a control for size or the level of organizational activity (generally by deflating by sales). Second, the measures are designed to be used in measuring changes in the amount of slack in a system over time. Focusing on the change in slack is important. Theories linking strategic behaviour to slack tend to see behaviour as a reaction to increases or decreases in slack rather than its absence or presence (Bourgeois, 1981). This is the case in the innovation literature (Cyert, 1963; Kay, 1979; Thompson, 1969) from which Singh developed his hypothesis concerning slack and risk taking. Bourgeois argues that it is more valid — from the standpoint of causal inference — to observe behaviour following changes in slack than to cross-sectionally compare behaviour among firms based on differences in the amount of slack[2].

To capture change in slack, each of the measures in Table I (except Profit, Margin, Equity Change and General Expense) were transformed as follows:

where t = one-year prior to programme start. These change measures conceptually indicate the change in slack during the period from two years to one year prior to production and delivery of items manufactured by a contractor under a weapon system acquisition programme. Profit Margin, Equity Change and General Expense (measured one year prior to programme start) were not transformed because they already reflect "flows" of resources into or out of an organization over a period of time and consequently provide direct proxies for change in slack.

Control Variables In Singh's investigation (1983, 1986) of risk-taking discussed earlier, performance was positively associated with slack and slack positively associated with risk taking, but performance alone was negatively associated with risk taking. This suggests a need to control for firm performance. An overall measure of firm performance, Return on Stockholders' Equity, was calculated for each firm in the year prior to product introduction. The expectation was for a negative relationship between Return and risk taking and thus a negative association with price reduction slope.

Pricing strategy can be expected to be associated with many additional factors, such as competition, industry and general economic conditions, the political environment, and the nature of the product. A preliminary study (Moses, 1989) was conducted to identify factors explaining pricing strategy on defence programmes in the aerospace industry. Results of that study indicated that five factors are significantly associated with pricing strategy. Variables reflecting each

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45

of these five factors were additionally included as controls. The five variables (and their expected association with the dependent variable, price reduction slope) are as follows:

(1) The growth in industry capacity utilization prior to programme initiation (-);

(2) The level of defence spending prior to programme initiation (-); (3) The initial (first year) government appropriations for a programme (+); (4) Programme length (+); (5) Whether a programme was a "follow-on" modification of a previous

programme (+). Discussion of the links between these variables and pricing strategy, as well as issues related to measuring the variables are contained in the earlier study.

Analysis The Interrelationship among Slack Measures Descriptive statistics and Pearson correlations for the slack variables are presented in Table II. The ten measures of slack are each designed to reflect changes in slack resouces during the period shortly before production and delivery of items occurs. Given the multiple measures, two questions arise: Are the measures independent? and do the three categories (available, recoverable, potential) provided in the Bourgeois and Singh framework represent distinct dimensions of slack? Observation of the table indicates that 20 of the 45 pairwise correlations are significant and the associations between measures cut across the three categories. Consequently the assumption of independent measures and distinct categories of measures appears inappropriate.

To analyse the interrelationships a factor analysis was conducted. Principal components factor analysis with varimax rotation (retaining factors with eigenvalues greater than one) resulted in four factors with the factor loading pattern reported in Table III. Each variable (except Quick Assets) is unambiguously associated with a single one of the four factors. Given the significant interrelationships between the individual slack measures, factor scores were used in the subsequent analysis. Consequently, some explanation of the dimensions is necessary.

Factor 1 (Investment) captures both decreases in slack (as measured by Quick Assets) and increases in slack (Receivables, Inventory, Fixed Assets). As an overall indicator of slack change, its meaning is ambiguous. However, an interesting pattern exists. Quick Assets is as a measure of available slack. The other three variables fall within the recoverable slack category. Instead of indicating an overall increase or decrease in slack, factor 1 captures a shift in terms of "ease of recovery". Factor 1 indicates an "investment" of liquid resources into a form that is less readily available. This permits a test of a secondary hypothesis. Singh (1983, 1986) found that risk taking was associated with measures of recoverable slack but not with measures of available slack. He concluded that when slack is unabsorbed by a system (i.e. available) it plays

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46 1. Profit margin

2. Equity change

3. Quick assets

4. Working capital

5. Receivables

6. Inventory

7. General expense

8. Fixed assets

9. Current debt

10. Long-term debt

* p< 0.05

** p< 0.01

*** p< 0.001

Mean

0.023

0.015

-0.173

-0.041

0.062

0.029

0.105

0.111

0.085

0.077

SD

0.072

0.055

0.710

0.419

0.368

0.422

0.171

0.415

0.439

0.586

1

1.00

0.59"*

0.10

0.45***

0.03

0.01

-0.16

0.22

-0.44***

-0.34*

2

1.00

0.14

0.59***

-0.10

0.05

0.04

0.30*

-0.61***

-0.46***

3

1.00

0.27*

-0.60***

-0.48***

0.17

-0.18

-0.63***

-0.07

4

1.00

0.07

0.23

-0.02

0.27

-0.68***

-0.19

5

1.00

0.50***

-0.08

0.34*

0.39**

0.32*

6

1.00

-0.07

0.41**

0.23

0.15

7

1.00

-0.01

0.01

0.28*

8

1.00

-0.05

0.01

9

1.00

0.47***

10

1.00

Table II. Slack M

easures: Descriptive Statistics and Correlations

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taking Behaviour

47

Profit margin Equity change Quick assets Working capital Receivables Inventory General expense Fixed assets Current debt Long-term debt Eigenvalues Percentage of variance

Factor 1 Investment

0.15 0.12

-0 .64 0.26 0.82 0.81

-0.06 0.64 0.31 0.27 2.44

31.5

Factor 2 Financing

0.65 0.77

-0.07 0.26

-0.18 -0.06 -0.12

0.28 -0.45 -0 .82

2.10 27.1

Factor 3 Funds

0.35 0.42 0.65 0.85

-0.12 0.04 0.01 0.15

-0 .77 0.03 2.09

27.0

Factor 4 Expense

-0.10 0.18 0.15 0.03

-0.10 -0.07

0.96 0.20

-0.01 0.26 1.11

14.4 Table III.

Factor Pattern — Slack Measures

a different, and lesser, psychological role in motivating risk taking. Since factor 1 measures a shift away from available slack to less easily recovered slack, if Singh's conclusion holds in the current study, one would expect a positive association between factor 1 and risk taking.

Profit Margin and Equity Change both load postively on factor 2. It was explained previously that they are two alternative proxies for the same idea (excess resources generated through profitable operations). Long-term Debt loads negatively. The link between the three is interpretable. Profitable operations (Profit Margin) should be reflected in increases in stockholders' equity (Equity Change) which, ceteris paribus, should result in a decreasing proportion of debt in a firm's capital structure (Long-term Debt). Thus factor 2 seems to reflect relative changes in the source of "Financing" from debt to equity. Given the hypothesized relationship of each of the three slack variables with risk taking, the expected association of factor 2 with risk taking is unambiguous. A positive sign is hypothesized.

The three variables loading on factor 3 (Funds) are readily associated. Decreases in current liabilities should cause increases in the net liquid (Quick) asset of a firm and the net working capital. The label "funds" denotes the liquid or operating resources of a firm. A positive association of factor 3 with risk taking is hypothesized.

Only one variable loads on factor 4 (Expense) so a positive association with risk taking, consistent with the expected sign for the individual variable, is hypothesized. The Association of Changes in Slack with Pricing Strategy Table IV shows pairwise correlations between the slack factors and the control variables. While some correlations are significant, the most important association would appear to be between Return and Financing (0.73). The effects of this will be commented on later.

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Table IV

. C

orrelations between

Regresser V

ariables

1. Investment

2. Financing

3. Funds

4. Expense

5. Return

6. Capacity utilization

7. Defence spending

8. Appropriations

9. Programme length

10. Follow-on programme

* p< 0.05 **p< 0.01

*** p< 0.001

Mean

0

0

0

0

0.155

0.017

0.445

0.203

5.69

0.481

SD

1

1

1

1

0.238

0.083

0.146

0.166

3.02

0.504

1

1.00

0.00

0.00

0.00

0.10

0.08

-0.07

0.38**

-0.08

-0.16

2

1.00

0.00

0.00

0.73

-0.10

-0.06

-0.28*

-0.09

-0.24

3

1.00

0.00

0.41***

-0.41**

-0.33*

-0.06

0.29*

0.23

4

1.00

0.08

0.01

-0.05

-0.14

0.12

0.24

5

1.00

-0.29*

-0.18

-0.17

0.07

0.15

6

1.00

0.16

0.10

-0.21

-0.05

7

1.00

0.11

-0.13

-0.08

8

1.00

-0.52***

0.06

9 10

1.00

0.11 1.00

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taking Behaviour

49

To test for relationships with pricing strategy, a forward stepwise regression was run, regressing price reduction slopes on the slack factors and the control variables. Individual variables were allowed to enter the regression as long as their coefficients were significant (p < 0.05) and the adjusted R2 of the model increased. Both these criteria were met for six variables. The resulting model[3] is in Table V.

Observation of Table V shows that three control variables explain pricing strategy, and each has the hypothesize sign. Of more direct interest, three slack factors are also significantly associated with pricing strategy[4]. The positive association of Funds with price reduction slope indicates a tendency for firms with increases in excess liquid resources to adopt the penetration strategy. The positive sign for Expense indicates that firms with excess resources tied up in period expenses also adopt penetration. The sign for Investment is contrary to hypothesis. The findings suggest that as excess resources are shifted from liquid form toward investment in less liquid assets adoption of the penetration strategy is less, rather than more, likely.

Discussion Central Hypothesis Findings from the study are consistent with the central hypothesis. Increase in slack, as measured by Funds and Expense, was associated with the adoption of the more risky penetration pricing strategy. This supports the conclusions of Singh (1983, 1986) that organizational slack and risk taking are related. There are two broad implications of the result. First, it emphasizes the importance of organizational variables such as slack in risk-taking behaviour. Traditional economic theories of risk taking typically emphasize the risk versus expected return aspects of decision alternatives and stress the trade-offs between the two. In theory, alternatives can be assessed in terms of risk and expected return and risk averse decision makers will accept a greater risk alternative only if

Variable

Investment Funds Expense Return Defence spending Appropriations Intercept

Model statistics F Value: 7.33 Significance: 0.0001

* p < 0.05 ** p < 0.01

*** p < 0.001

Variable type

Slack Slack Slack

Control Control Control

R2: 0.49 Adjusted R2

Hypothesized sign

+ + + --+

0.42

Coefficient

-0.017 -0.044

0.020 -0.006 -0.230

0.215 1.047

t

-3.28** 4.10*** 2.25*

-2.88** -2.56*

2.94** 13.88***

Table V. Regression of Price Reduction Slope on

Explanatory Variables

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there is a compensating greater expected return. Decision makers can be perceived as having an indifference curve which describes the trade-offs they are willing to accept. The indifference curve is exogenous. The results here suggest that slack is a variable that influences how the risk/return trade-off may be made. In short, slack may be an organizational variable that influences the shape of the indifference curve.

Second, the results reinforce the notion of slack as a variable having behavioural consequences for the firm. Risk taking is likely permitted because slack provides the source of resources to cushion or absorb failure. Given such behavioural effects of slack, one might question the completeness of organizational theories (Wolf, 1971), economic views (Leibenstein, 1976; Shelton, 1967) and accounting/budgeting studies (Lowe and Shaw, 1968; Schiff and Lewin, 1970, 1967) that stress efficiency and consequently assume that slack is necessarily undesirable.

On the Dimensions and Measurement of Slack The Bourgeois and Singh (1983) measurement framework was used initially to identify measures of slack. While the arguments underlying their three ease-of-recovery categories are intuitively appealing, the findings from the correlation and factor analysis indicate that the different categories are not empirically distinct. Interrelationship between the various individual slack measures is not entirely unexpected; year-to-year changes in a firm would likely be captured by various measures. The implications are twofold: First, a warning. Attempting to draw conclusions about the separate roles of "available", "recoverable" or "potential" slack by using a single measure from one of the categories would be inappropriate; measures from different categories co-vary. Second, an opportunity. Since the measures co-vary, a subset of the measures used in this study may adequately capture some important dimensions of slack.

With this in mind, some specific results from Singh (1983, 1986) seem relevant. He found two measures of slack (Working Capital and General Expense) significantly associated with risk taking. In this study, those same two measures had the highest loadings on the Funds and Expense factors, which similarly proved to be significantly associated with risk taking. This suggests that the level of working capital and the level of selling, administrative and operating expenses of a firm may be appropriate places to start when attempting to operationalize slack[5]. Future research is perhaps necessary to establish whether these two dimensions of slack are consistent predictors of strategic actions in other situations or even if they represent distinct factors in other samples. However, studies of financial ratios (Chen and Shimerda, 1981) indicate that these two dimensions align well with distinct factors that have been shown to consistently exist in financial accounting data.

Absorbed Slack, Unabsorbed Slack and Risk Taking While Working Capital and General Expense were associated with risk taking in the Singh study, a third variable he tested, Quick Assets, was not. From this result he concluded that absorbed (recoverable) slack may motivate increased

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risk taking but unabsorbed (available) slack has no effect. The findings reported here are not consistent with that conclusion. The Investment factor directly reflected a shift of excess resources from liquid to less liquid form, i.e. a shift from unabsorbed to absorbed slack. And that shift was inversely related to risk taking. It is possible that once resources are absorbed by organizational activities they are less readily available to cushion the firm against risks. Williamson (1963) suggests this view, implying that slack, once absorbed, is not readily recovered because managers are hesitant to yield the benefits derived from slack. Admittedly, the two studies differ with respect to industries, and the method of operationalizing risk taking. The appropriate inference may be that it is premature to draw final conclusions with respect to the relative importance of absorbed and unabsorbed slack as strategic variables.

Performance and Risk Taking While not of central interest to this study, the finding that adoption of the penetration strategy was inversely associated with organizational performance (Return) is also of note. This confirms the findings of others (Bowman, 1980, 1982; Singh, 1983, 1986; Treacy, 1980) that risk taking and performance may be negatively related, and is consistent with theories that see risk taking as dependent on the relationship between the level of actual performance and the satisficing level. Recall that Singh's model of the relationship between performance and risk taking called for both direct and indirect (mediated by slack) links. The findings for the Return variable are supportive of the direct link Singh hypothesized.

Concluding Remarks The broad conclusions of this study can be briefly summarized as follows:

(1) Increases in organizational slack appear to be followed by more risky decisions;

(2) Slack is a multi-dimensional construct, but focusing on the level of working capital and expenses appears to provide measures of slack that are useful in explaining strategic behaviour;

(3) The relative role of absorbed versus unabsorbed slack in motivating risk taking behaviour is an open question.

These conclusions must be tempered by two limitations. First only one specific risk-taking decision, product pricing strategy, was investigated. The choice of pricing strategy for the sample firms investigated was not a trivial one; the monetary value of the defence programmes involved was large. Nonetheless, only one type of strategic decision was examined; additional research is required to explore the links between slack and other types of risky decisions.

Second, while financial accounting-based variables have been widely used in past research to measure slack, such measures are only proxies for the idea of "excess" resources implied by the slack concept. Conclusions should be interpreted with this in mind. Validation of accounting-based measure against

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alternative measures (perhaps developed via questionnaires or interviews of organizational members) would be a useful direction for future research.

Two other directions for future research are also apparent. One is the relative role of absorbed and unabsorbed slack mentioned above. Does the ease of recovery of slack matter and how? The second follows from a look at the difference between the penetration and skimming pricing strategies used in this study. While they differ in risk, they also tend to differ in long-run versus short-run orientation. Perhaps the presence of slack, by relaxing short-run pressures, permits the firm to take a long-run view. Tests of the relationship of slack to other decisions where a long-run/short-run choice is apparent may provide insight on this issue.

Notes 1. There are some risks for a firm that secures a contract with a skimming strategy.

Contractors that skim may risk programme termination or curtailment due to excessive price, and may risk competitor entry by encouraging the government to seek lower prices elsewhere (termed "second sourcing"). But these risks are minimal. The high start­up costs associated with the manufacture of major weapon systems typically make second sourcing an unattractive alternative for the government, and the flexibility afforded by the high initial price permits the skimmer to respond to termination threats with a price reduction.

2. Since slack implies excess resources, not total resources, it is also more meaningful to use the measures to reflect changes in slack rather than the absolute amount of slack. As absolute measures of slack, the variables have meaning only if certain assumptions hold. Take for example Working Capital. If it is assumed, first, that there is some constant "necessary" level of working capital for a given firm when operations are "normal", second, that deviations from the necessary levels indicate slack, and, third, that firms in the same industry have the same necessary level, then cross-sectional differences in working capital (for firms in the same industry) would imply cross-sectional differences in slack. Although previous research has adopted these assumptions when measuring slack (Singh, 1983, 1986), they are strong assumptions.

The measures are more meaningful when used to reflect changes in slack over time. It is more defensible to argue that there is some necessary level of a given measure for the "normal" operations of a particular firm. Then changes in the measures would reflect changes in slack for the particular firm. This is not unreasonable since the individual measures are adjusted for the level of activity (generally, by deflating by sales). Consider again Working Capital. Analysts usually project working capital needs as a constant percentage of sales (Bourgeois, 1981). If working capital increases at a faster rate than sales (i.e. an increase in Working Capital over time) then it is not unreasonable to assume that there is an increase in liquidity in excess of that necessary to support the increase in activity; in short, an increase in slack. Bourgeois and Singh indicated that their measures are most appropriate when used to reflect changes in slack.

3. Two other approaches were attempted. First, instead of using factor scores, the individual slack variables that loaded highest on each factor (assumed to be representative of the factor) were used in the regression. Results were substantially the same; the variables representing factors 1, 3 and 4 were significant, while the variable representing factor 2 was not. Second, an ordinary (non-stepwise) regression model including all slack factors and control variables was constructed. The only change from the model reported in Table V was that Return and Expense ceased to be significant. Given the collinearity between some of the variables (particularly Return and Financing), this is not surprising. When two highly correlated variables are included in the same regression the individual coefficients are less reliable and the chance of either being significant is reduced.

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4. The fourth slack factor, Financing, was not significantly associated with pricing strategy. However, letting the stepwise procedure continue, it was the next variable to enter, with a negative coefficient (significant only at p = 0.29). Note that while a positive coefficient was hypothesized for Financing, a negative coefficient was hypothesized (and found) for the control variable Return, and recall that Financing and Return were highly correlated. This suggests that the Financing factor may be capturing aspects of firm performance confounding its meaningfulness as a measure of the increase in slack.

5. It should also be noted that, in addition to different samples and methodological approaches, the Singh study also differed from this study in the specific manner of measuring slack. This study measured slack change over time. Singh measured the "amount" of slack for firms cross-sectionally. The fact that working capital and general expenses proved significant measures in both approaches tends to confirm their value.

References Albaum, G. (1975), "Objective and Strategy in Price Formulation", in Westing, J. and Albaum,

G. (Eds), Modern Marketing Thought, 3rd ed., Macmillan Publishing Co., New York. Bourgeois, L. (1981), "On the Measurement of Organizational Slack", Academy of Management

Review, pp. 29-39. Bourgeois, L. and Singh, J. (1983), "Organizational Slack and Political Behavior among Top

Management Teams", Academy of Management Proceedings, pp. 43-7. Bowman, E. (1980), "A Risk-Return Paradox for Strategic Management", Sloan Management Revieiw

pp. 17-31. Bowman, E. (1982), "Risk Seeking by Troubled Firms", Sloan Management Review, pp. 3342. Caferelli, E. (1980), Developing New Products and Repositioning Mature Brands, John Wiley &

Sons, New York. Chen, K. and Shimerda, T. (1981), "An Empirical Analysis of Useful Financial Ratios", Financial

Management, Spring, pp. 51-60. Crawford, D. et al. (1984), US Military Missile Cost Handbook, TR-8203-3, Management Consulting

and Research, Inc., Cyert, R. and March, J. (1963), A Behavioral Theory of the Firm, Prentice-Hall, Englewood Cliffs, NJ. Dean, J. (1969), "Pricing Pioneering Products", Journal of Industrial Economics, July, pp. 180-7. DePuy, S. et al. (1983), US Military Aircraft Cost Handbook, TR-8203-1, Management Consulting

and Research, Inc. Dimick, D. and Murray, V. (1978), "Correlates of Substantive Policy Decisions in Organizations:

The Case of Human Resource Management", Academy of Management Journal, Vol. 21, pp. 611-23.

Greer, W. (1985), "Early Detection of a Seller's Pricing Strategy", Program Manager, November-December, pp. 6-12.

Greer, W. and Liao, S. (1983), "Cost Analysis for Duel Support Weapon Procurement", Naval Postgraduate School Technical Report, NPS 54-83-011, Monterey, CA, October.

Greer, W. and Liao, S. (1984), "Cost Analysis for Competitive Major Weapon System Procurement: Further Refinement and Extension", Naval Postgraduate School Technical Report, NPS 54-84-023, Monterey, CA, September.

Hambrick, D. and Snow, C. (1977), "A Contextual Model of Strategic Decision Making in Organizations", Academy of Management Proceedings, pp. 109-12.

James, B. (1969), "A Contemporary Approach to New Product Pricing", in Taylor, B. and Wills, G. (Eds), Pricing Strategy, Staples Press Ltd, London.

Kay, N. (1979), The Innovating Firm: A Behavioral Theory of Corporate R&D, St Martins Press, New York.

Leibenstein, H. (1976), Beyond Economic Man: A New Foundation for Microeconomic, Harvard University Press, Boston, MA.

JOCM 5,3

54

Litschert, R. and Bonham, T. (1978), "A Conceptual Model of Strategy Formulation", Academy of Management Review, April, pp. 211-19.

Lowe, A. and Shaw, R. (1968), "An Analyis of Managerial Biasing: Evidence from a Company's Budgeting Process", The Journal of Management Studies, pp. 304-15.

March, J. (1981), "Decisions in Organizations and Theories of Choice", in Van de Ven, A. and Joyce, W. (Eds), Assessing Organizational Design and Performance, Wiley Interscience, New York.

March, J. and Shapira, Z. (1982), "Behavioral Decision Theory and Organizational Decision Theory", in Ungson, G. and Braustein, D. (Eds), New Directions in Decision Making: An Interdisciplinary Approach to the Study of Organizations, Kent Publishing Co., Boston, MA.

March, J. and Simon, H. (1958), Organizations, John Wiley & Son, New York. Mohr, L. (1969), "Determinants of Innovation in Organizations", American Political Science Review,

Vol. 63, pp. 111-216. Moses, O.D. (1989), "Determinants of Contractor Pricing Strategy", Program Manager, July-

August, pp. 32-43. Moses, O.D. (1991), "The Impact of Accounting Procedures on Learning Rates", Journal of

Cost Analysis, Spring, pp. 19-54. Odell, H. (1972), "Organizational Slack as a Measure of the Discretionary Allocation of Resources

by the Business Firm", unpublished PhD dissertation, Graduate School of Business, Indiana University.

Rosner, M. 0968), "Economic Determinants of Organizational Innovation", Administrative Science Quarterly, Vol. 12, pp. 614-25.

Schiff, M. and Lewin, A. (1968), "Where Traditional Budgeting Fails", Financial Executive, Vol. 36, pp. 51-62.

Schiff, M. and Lewin, A. (1970), "The Impact of People on Budgets", The Accounting Review, pp. 259-68.

Shelton, J. (1967), "Allocative Efficiency versus X-Efficiency", American Economic Review, pp. 1252-8.

Simon, H. (1976), Administrative Behaviour, 3rd ed., Free Press, New York. Singh, J. (1983), "Performance, Slack and Risk Taking in Strategic Decisions, unpublished doctoral

dissertation, Graduate School of Business, Stanford University, February. Singh, J. (1986), "Performance, Slack, and Risk Taking in Organizational Decision Making",

Academy of Management Journal, September, pp. 562-85. "The Pricing Decision: Part I — The Cornerstone of the Marketing Plan" (1985), Small Business

Report, Vol. 10 No. 5, May, pp. 71-7. Thompson, V. (1969), Bureaucracy and Innovation, University of Alabama Press, Tuscaloosa, AL. Treacy, M. (1980), "Profitability Patterns and Firm Size", working paper, Sloan School of

Management, MIT, Cambridge, MA. Wasson, C.R. (1974), Dynamic Competitive Strategy and Product Life Cycles, Challenge Books,

Long Beach, CA. Williamson, O. (1963), "A Model of Rational Managerial Behaviour", in Cyert, R. and March,

R. A Behavioural Theory of the Firm, Prentice Hall, Englewood Cliffs, NJ. Wind, Y. (1982), Product Policy: Concepts, Methods and Strategy, Addison-Wesley, Reading, MA. Wolf, C. (1971), "An Investigation into the Theory of Organizational Slack", unpublished PhD

dissertation, Graduate School of Business, New York University.