DOWNSIZING, COMPETITION, AND ORGANIZATIONAL CHANGE IN GOVERNMENT: IS NECESSITY THE MOTHER OF INVENTION?

Steven Kelman Weatherhead Professor of Public Management

Harvard University Kennedy School of Government

September 2003

DRAFT ONLY – NOT FOR COPYING OR DISTRIBUTION

Why don’t government organizations perform better? One view, common in the

academic “public choice” literature (e.g. Savas 1982; Chubb and Moe 1990) but also in

folk wisdom, is that governments perform poorly because resources come to them too

easily, more or less independently of their performance. They are monopolies, nobody is

ever fired, budgets are assured. When resources are assured, people get lazy: “the best

of all monopoly profits is the quiet life.” (Fisher l979: 10) This produces poor

performance. Partly, people don’t put enough effort into doing their existing tasks or to

keeping costs down. And partly as well, they don’t try hard enough to seek out ways of

changing their behavior to improve how they operate over time or to respond to new

demands from their environment. Thus, a prominent prescription for improving

government performance is to shake up agencies with a dose of crisis that interrupts the

assured flow of resources. This, it is argued, will provide a spur for organizational

change that will allow the organization to respond to crisis -- to stop the bleeding, or at

least to avoid the collapse that would occur if it tried to continue the old ways with fewer

resources. Organizational change under these circumstances would reflect the proverb

that “necessity is the mother of invention.” Two ways to implement this prescription that

have been followed in government are to downsize an organization’s workforce and to

eliminate an organization’s status as monopoly provider of services.

The view that crisis promotes organizational change is not just suggested

regarding government. A common proposition in pop-management business literature on

organizational change (e.g. Kotter l996: Ch. 3; Hammer and Stanton l995) is that

successful change occurs only in response to crisis. Since change is painful, employees

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must understand there is no alternative. As often put in consultant presentations about

initiating change, getting people to move requires a “burning platform.”1

Such arguments receive a more general formulation in Cyert and March’s theory

of problemistic search, presented in A Behavioral Theory of the Firm (1963: 120-22).

Cyert and March argue search is “problemistic”: absent problems, little motivation for

change exists. People look for new solutions when current ones aren’t working. “When

traditional organizational programs and procedures fail to increase results, learning

theorists suggest that innovative changes will occur as the organization’s search routines

increasingly deviate from solutions tried in the past.” (Mone et al 1998: 119)

This view, however, is controversial among scholars. In academic literature on

downsizing, many (e.g. Ocasio l995) maintain that crisis inhibits organizational change.

The most important argument for this view grows out of the theory of “threat rigidity”

(Staw et al 1981), which proposes that, faced with crisis, people tend to fall back on

familiar behavioral responses, rather than seeking out new ones. Staw et al base their

argument on psychological research suggesting that, “when placed in a threat situation,

an individual’s most well-learned or dominant response may be emitted.” (Ibid.: 502)

This is advantageous in situations where previously learned responses are the appropriate

behavior. Thus, in situations where heightened energy in applying traditional methods is

the appropriate response, threats improve performance. But where crisis requires changed

behavior, threat-rigidity decreases the likelihood of an appropriate response. (Ocasio

l995: 310-11) In this view, necessity serves not as the mother of invention but as the

mother of rigidity. (Mone et al l998: 117-19) A related argument is that time and

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workload pressures, which grow in crisis situations, inhibit creativity by reducing

freedom and exploration. (Amabile 1996: 14-15, 232-33; Amabile et al l996: 1172-75)

This paper seeks to shed light on this question by using a successful example of

organizational change in government, the reform in how the federal government buys

$200 billion a year of products and services, over 30% of discretionary spending.

(Federal Procurement Data Center 2001) In the context of a larger effort at management

reform during the Clinton Administration (“reinventing government”), offices

responsible for procurement succeeded in significantly changing how they do business.2

The specific kind of change that occurred was debureaucratization. Previously,

procurement offices corresponded to a stereotype of government bureaucracy. They were

rulebound, slow, and not results-driven. After the changes, they showed far less of these

characteristics. They became speedier and more nimble. They began to pay more

attention to quality in choosing suppliers, which required them to exercise judgment

more. Given the opportunity to use discretion, many developed novel ways to structure

contractual relationships.3

Procurement reform occurred in the context of crisis for many of these buying

offices -- significant downsizing of the workforce and elimination of the status of some

offices as monopoly providers of services for a designated group of end-users. This

paper examines whether crisis helped the change succeed or inhibited it (such that it

succeeded despite crisis rather than because of it). An answer to this question has

significance for the choice of tactics for achieving organizational change in government.

Additionally, the question of whether crisis promotes change may be seen as an example

of a larger debate -- between an economic approach to studying human behavior (crisis

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creates incentives to change behavior) and a psychological one (crisis creates

mechanisms in the mind that block behavior change). So an answer to the question about

crisis and change has implications for the more general questions that debate raises.

The paper adopts a frontline perspective on change: the unit of analysis is the

individual employee. Individuals worked in offices experiencing significant variation in

the degree of downsizing and introduction of competition. We will examine the impact

of such variations on the extent to which individuals changed their own behavior in the

context of procurement reform.

There are possible impacts of crisis on organizational performance other than any

impact on performance-improving organizational change. These include impacts on

overall work effort with regard to existing tasks and on the organization’s costs. These

will not be discussed here.

The Data

This paper is part of a larger study of change in the procurement system.4 The

data on which the study as a whole is based come mostly from a written survey of 1593

civil servants (frontline employees and first-line supervisors) in l9 buying offices,

undertaken after the change effort had gone on for five years. Five were in the Army,

four the Air Force, two the Defense Logistics Agency (which buys commercial items

such as food and pharmaceuticals), and the rest in five civilian cabinet departments,

including four that were units of a single department. The survey instrument was a

questionnaire for all frontline employees, administered on-the-job on behalf of the

researcher by each office.5 The survey included over 400 fixed-format attitudinal,

demographic, and other questions. Most were five-point scales where a respondent was

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presented a statement and asked to check “agree strongly,” “agree somewhat,” “mixed

feelings,” “disagree somewhat,” or “disagree strongly.” It was also possible to check a

box marked “no opinion,” and a respondent might also leave a question blank.6

Two questions were self-reports of the respondent’s attitude towards reform and

of the extent to which the respondent had changed behavior as a result of reform. The

attitude question used a technique called a “feeling thermometer.” (Alwin l997) The

instructions (taken from the standard way this question is asked) were:

The following is a list of concepts for you to rate on a “feeling thermometer.” A “feeling thermometer” has l00 degrees. Ratings between 50 degrees and l00 degrees mean that you feel favorable and warm toward that concept. Ratings between 0 degrees and 50 degrees mean that you don’t feel much for the concept. If you don’t feel particularly warm or cold towards the concept, you would rate the concept at the 50 degree mark. (emphasis in original)

Respondents were given a list of phrases to which to react; “acquisition reform” (called

here “PR,” for “procurement reform”) was the first on the list.

Behavioral change was measured through a question where respondents were

asked, “In terms of the way you do your job every day, how much impact has acquisition

reform had?” (PRIMPACT) The four alternatives (so answers were coded on a l-4 scale)

were: (l) “It has significantly changed the way I do my job,” (2) “It has had some impact

on the way I do my job,” (3) “It has had little impact on the way I do my job,” and (4) “It

has had no impact on the way I do my job.” Self-reported behavior change should reflect

some mixture of changes in how the individual did his or her job due to activities

organized by the individual’s superiors and changes an individual chose to make himself

or herself (the latter are very significant because many changes the reform promoted

authorized but didn’t require doing business differently from previously).

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Mean values on the attitude question PR was 69.6 and on the behavioral change

question PRIMPACT 1.75 (meaning somewhat higher than “some impact”).

Data on the extent of downsizing, introduction of competition, and changes in

workload pressures were available for each buying office. Such organization-level data

could be applied to an individual respondent because each respondent record included

information on where the respondent worked.

Downsizing and the Introduction of Competition

All but three of the l9 buying offices studied here experienced decreases in the

size of their procurement workforce (“downsizing”) during the period encompassed by

this research, ranging from cutbacks of 40 % to 6%, with most around 15-20%. Two

small offices, both in civilian agencies, increased the size of their procurement

workforce, by 5% and 29%, and another saw no change.7

Procurement workforce downsizing was part of a general reduction in federal

employment occurring pursuant to the pledge made in the Clinton Administration’s

“reinventing government” report to decrease federal employment by 250,000 (Gore l993:

iii). The reinvention effort targeted procurement employees (along with those in

personnel, budgeting, auditing, and supervision) for disproportionate cuts.

In addition, some of the buying offices studied began during this period to face

the introduction of competition for business as providers of contracting services to their

larger organizations. Defense Department customers no longer were required to purchase

from the Defense Logistics Agency supplies they had previously had to obtain through

them; henceforth DLA would receive no appropriated funds but only revenues from fees

levied on (voluntary) transactions. In the Army, senior procurement leadership

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announced that for some procurements, buying offices would compete to determine

which would manage the contract.

Although there are differences as well as similarities between downsizing and

introduction of competition, I use the term “organizational crisis” to encompass both,

since, in both cases, organizations faced new and significant reductions, or credible

threats of reduction, to assured resource flows.

Theories Relating Organizational Crisis to Organizational Change

Though the literature arguing that crisis might have a negative impact on

organizational change emphasizes threat rigidity as the source of such an impact, two

other arguments, not found in the literature, may be made for why crisis might discourage

change. Both involve possible negative impacts on behavior change from resentment

people feel over downsizing or introduction of competition.

First, the “burning platform” view that organizational change requires crisis

assumes people on the front lines will always be hostile to a change effort. However, the

larger study of which this paper is a part found that, in the specific case of procurement

reform, that wasn’t true – the effort from the beginning had not just opponents but also

supporters as well; the larger study makes an argument for why this may frequently be

the case in change efforts.8 If frontline attitudinal opposition to a change effort should

not be taken for granted, then one must be concerned with factors that may reduce

attitudinal support for the change. If people believe leaders are to blame for the crisis,

and these same leaders are also promoting the change, this is likely to depress attitudinal

support. Assuming attitudes affect behavior,9 then crisis would act indirectly to reduce

behavior change by making people more attitudinally hostile to it.

8

Even if the crisis an organization faces comes impersonally from the environment,

such as through declining sales, leaders might get blamed for having made poor decisions

that caused the poor results. (Cameron et al l987: 128, 134; Kets de Vries and Balazs

l997: 19-20) If blame is an issue when the source of a crisis is external, it can be

expected to be more so where downsizing, or a decision to subject a government agency

to competition, is the form crisis takes. Identifiable individuals make these decisions:

environments don’t fire people, people fire people. Additionally, it is common in

business for the same leaders initiating downsizing also to be promoting change efforts

such as business process reengineering, which have often been complementary parts of

an overall effort to turn firms around. In the context of this study, leaders of “reinventing

government” in general and of procurement reform in particular were involved in both

downsizing and organizational change.

A second, separate impact of resentment might occur because employees believed

these measures violated a perceived “social contract” at the workplace. By such a “social

contract” is meant the expectation that “hard work, good performance, and loyalty would

be rewarded by employment security, fair treatment, and ‘good’ benefits.” (Osterman et

al 2001: 7-8. See also Heckscher l995: 4; Rousseau l995; Capelli 1999; Osterman et al

2001.) In the literature on the impact of downsizing on productivity, the argument has

been made that social contract violation through downsizing reduces employee morale,

motivation, and commitment, and that this in turn depresses productivity. (Cameron l994:

199; Kets de Vries and Balazs 1997: 18-19; Bewley l999: Ch. 4, 13) This argument,

however, has not appeared in literature on the impact of crisis on organizational change

in particular. However, it would appear to be relevant. Individual participation in a

9

change effort may significantly involve “organizational citizenship behavior,” i.e. actions

beyond one’s formal job description. (Organ l988; Organ and Lingl l995) The literature

argues that such behavior is strongly associated with morale and commitment.10

Three other factors may influence whether crisis promotes or hinders change.

First, an article by Mone et al (1998; see also Ford l985 and Ocasio 1995) argues that

whether necessity acts as mother of invention or rigidity depends on how people interpret

the crisis. A key interpretation variable Mone et al discuss is what they call

“controllability.” If people interpret the crisis as something that can be overcome through

measures they take, it will evoke problemistic search. If it isn’t, threat-rigidity responses

will predominate: why change if it offers no meaningful way out of crisis?

Second, if necessity acts as the mother of invention, it would probably act as an

extrinsic incentive – i.e. one imposed on individuals from outside themselves -- to change

behavior.11 There is a rich literature, mostly in social psychology, providing evidence

that extrinsic rewards have an undermining effect on any intrinsic motivation a person

has to undertake the behavior. (See Deci and Ryan l985 for a discussion of the theory

behind this proposition, and Deci et al l999 for a summary of empirical studies.) Given

that extrinsic incentives have a positive direct effect promoting the behavior incentivized,

one would therefore, if the “undermining effect” hypothesis is correct, predict different

effects of crisis on the behavior of those possessing and those lacking intrinsic motivation

to engage in reform-oriented behavior –i.e. those attitudinally supportive and opposed to

reform. Critics lack intrinsic motivation to undertake reform-oriented behaviors, because

they don’t like reform in the first place. No undermining occurs, because no intrinsic

motivation exists. The effect of extrinsic rewards is unambiguously to incentivize.

10

However, for supporters, the two effects go in opposite directions. The incentivizing

effect encourages behavior change, while the undermining effect discourages it. (Frey

and Jegan (200l) call this “crowding out.”) This consideration affecting the impact of

crisis on organizational change has not been discussed in the literature.

Third, if blaming change leaders for crisis reduces attitudinal support for change,

and if believing a crisis to be controllable promotes a problemistic search reaction,

change leaders may influence the impact of crisis on behavior change by persuading

people that leaders were not responsible for downsizing but rather that it was a quasi-

automatic response to impersonal environmental forces, or by promoting a controllability

interpretation of crisis. In making such arguments, leaders engage in “sensegiving” –

efforts “to provide a viable interpretation of a new reality and to influence stakeholders

and constituents to adopt it as their own.” (Gioia and Chittipeddi l99l: 443)

Empirical Studies of the Impact of Organizational Crisis on Performance

There are a considerable number of studies on the impact of downsizing, and

some on the impact of introducing competition in private or public monopolies, on

overall organizational performance, which show mixed impacts of downsizing on overall

performance and generally positive impacts of the introduction of competition12

The number of studies on the impact of crisis on organizational change is much

fewer. Three studies in the private sector (Chandler l962; Manns and March 1978;

McKinley l984) of the impact of organizational crisis, as measured by general resource

availability cutbacks due to economic problems rather than by downsizing, on

organizational change or innovativeness (new product introductions) all showed positive

effects. By contrast, two studies (Cameron et al 1987; D’Aunno and Sutton (l992) of

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government and non-profit organizations (colleges and drug-treatment centers) faced

with budget cutbacks, showed negative impacts. One difference between the context of

these studies is that the private-sector studies looked at the impact of declining revenues

due to general economic conditions or to profit declines due to poor marketplace

performance, while the public/non-profit studies looked at conscious decisions by

political overseers to cut budgets. The former situation would be expected to have

generated less employee resentment than the latter.

Two studies (McKinley l984; Amabile and Conti l999) examine the impact of

downsizing on behavioral innovativeness (measured by new product introductions).13

One found no effect, the other a negative effect. In the McKinley study, which was also

discussed above, while sales decline had a positive effect on the number of product

modifications introduced, there was no relationship either way between downsizing and

modifications. Thus, the literature suggests that downsizing produces a more negative

impact on change, as measured by new product introductions, than other forms of crisis.

Looked at in the context of the existing empirical literature, the results to be

presented here can add to our understanding of the impact of crisis on organizational

performance for a number of reasons. First, few existing studies focus on organizational

change efforts specifically, instead generally examining innovativeness, generally

measured by new product introduction. Such studies have some applicability to

organizational change, but the fit is imperfect. Procurement reform, like many other

change efforts, did encourage people to be innovative, but a good deal of the changed

behavior being sought didn’t require individual creativity, only new behavioral patterns.

Second, examining individual-level behavior makes it possible to test more directly for

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many hypothesized links between crisis and behavior change, in a way that is at best only

indirectly possible with organization-level data; for example, there are no existing

empirical tests of the controllability hypothesis, which requires examining individual-

level data. Finally, no existing studies look at government agencies.

Testing for the Impact of Crisis on Behavior Change

To test the impact of crisis on behavior change, two ordinary-least squares

regression models were developed. In the first, the individual’s own attitude towards

procurement reform (PR) was the dependent variable. In the second, the dependent

variable was the individual’s self-reported extent of behavior change. (PRIMPACT) By

plugging counterfactual values for PR into the second model (which includes attitudes as

a predictor of behavior), an overall impact of crisis on behavior change, including both its

direct impact and its indirect impact via impact on attitudes, can be estimated.14

The crisis variables included as predictors in both models were:

(1) downsizing: Information from each of the l9 buying organizations on the

number of contracting employees working in the organization in at the beginning of the

change effort, and five years later, was obtained. The variable DOWNUP was

constructed by calculating the percentage decrease or increase (compared with the

baseline) in the size of the organization’s contracting staff. The lower (i.e. more

negative) the value, the greater the downsizing.

(2) workload: Figures for the total dollar value of all contracts the office issued in

the baseline year and five years after were obtained. Using the information provided on

the number of employees, the new contract value per employee for each office for the

two years was computed. The measure of office workload change (WORKLOAD) was

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the percentage increase or decrease in new contract value per employee compared to the

office baseline. Thus, higher values meant higher workload increases. Only two offices

experienced a workload decline; for the others, increases ranged from 28% to l000%.15

(3) competition: This variable (COMPETE) measured introducing competition.

It took the value “l” if the office stopped being a required source of supply (three of the l9

offices in the sample, with the overwhelming majority coming from the two in the

Defense Logistics Agency), “2” if the organization sometimes had to compete (the Army

organizations), “3” otherwise.16

Modeling the Impact of Crisis on Attitudes Towards Procurement Reform

In addition to the crisis variables, the model with attitude as the dependent

variable included the following individual-level predictor variables:

I. personal fear of job loss

A question from the survey asked the respondent to agree or disagree with the

statement: “I am very worried about the risk of losing my job.” (DOWNSIZE) This was

included, in addition to variables representing objective organizational circumstances, to

see whether subjective fear of job loss, which might be based on a number of

considerations (such as a respondent’s age or generalized anxiety level), had a negative

impact on support for reform. It is commonly believed (Kelman l987: Ch. 10) that

opinions on public policies are determined by personal impacts those policies have on

them. If this is true, it might be expected that DOWNUP might turn be statistically

insignificant with DOWNSIZE in the model, if organization-level crisis exerts an impact

on individual attitudes only if job loss in the office had produced personal fear.

14

Somewhat relatedly, Shah (2000) found that employees who had lost personal

friends to downsizing had more negative attitudes towards their companies than those in

similarly downsized firms who had not. An interaction was therefore tested between

DOWNUP and a scale (SOCIABLE) with several questions measuring a respondent’s

psychological attachment to others.17 This tested for whether the attitudes of those who

placed a higher value on social ties were affected more negatively by downsizing than

those for whom such ties were less important.18

II. blaming reform for downsizing

If it is blaming reform leaders for downsizing that is associated with reduced

support for reform, one would expect an interaction effect between downsizing and

blaming: at a given level of downsizing, the negative impact on attitudes would be less,

the less a respondent blamed reform leaders for downsizing. It was hard to come up with

a good measure for blaming – a direct survey question might have been, “I blame

procurement reform for the downsizing of the procurement workforce”, but my view was

that such a question would have been too blunt. This hypothesis was therefore tested

using three interactions with DOWNUP, none perfect:

(1) One survey question asked respondents to agree or disagree with the

statement: “Acquisition reform is mostly a cover for downsizing the procurement

workforce.” (DSCOVER) This statement is far stronger and more ideological than

blaming, since one could blame reform leaders for downsizing without going the extra

step of conspiratorially suggesting the whole reform effort was staged to draw attention

away from the real goal, to downsize the workforce.

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(2) The reform leadership19 did try to engage in sensegiving activity, treating

downsizing as a sort of impersonal force of nature, resulting from popular distrust of

government and/or the end of the Cold War, rather than something they had promoted.20

The more a person was influenced by the views of top reform leaders, the less the person

would be expected to blame reform for downsizing.

The modeling strategy problem for measuring any impact of leader sensegiving

on attitudes is that top leadership views were not a variable – every individual respondent

worked in an environment where top leader views were the same (there was only one set

of top leaders, and they promoted reform). My strategy for dealing with this was to find

something that did vary to capture the influence of something that didn’t. Though top

leader support for reform didn’t vary, the extent to which people listen to what leaders

say does. If you didn’t listen to top leader statements, then these leaders had no ability to

influence you. If you did listen, the statements were potentially relevant -- they might or

might not have had an effect.21 The effect of listening to top leaders is thus a variable.

To measure leader sensegiving influence, I therefore included responses to the statement:

“I try to keep up with the statements being made about acquisition issues by the top

acquisition leadership of my agency and the White House.” (KEEPUP) The weakness of

this question was that it referred to a general tendency to listen to top leader views, not

specifically to top leader arguments about downsizing.

(3) Respondents with an underlying favorable inclination towards reform would

be expected to blame it less for downsizing. I therefore included the statement: “When I

first tried out some of the new ideas of acquisition reform, I was doing it mostly because

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my bosses told me to, not because I was convinced they made sense.” (TRYBOSS)22

The limitation of this measure is that it relates to only one reason not to blame leaders.

I hypothesized that, unlike downsizing, introduction of competition would not be

associated with more negative attitudes towards procurement reform. The specific reason

was that, in fact, introducing competition was not part of the procurement reform effort.

The Defense Logistics Agency lost its monopoly in l992, just before reform began.

Introduction of competition into Army buying offices was an internal Army decision,

unconnected to the reform leadership.23

III. Control Variables

(1) The relationship between blaming reform for downsizing (or personal fear of

job loss) and attitudes towards reform may be partly endogenous – in other words, a

respondent’s opinion of reform was partly explaining these predictor variables rather than

the other way around. This might occur because of the tendency to engage in “perceptual

confirmation” (Snyder et al 1977) whereby people interpret specific situations in ways

consistent with pre-existing general beliefs, so that people who like reform will tend not

to blame reform leaders for something they don’t like, such as downsizing.

Econometricians often deal with this using two-stage least squares regression, where one

seeks to develop an instrumental variable allowing a test of the extent to which x indeed

caused y. In this case, with no appropriate instrument available, I tried to deal with this

by developing, using questions from the survey, a variable called DISTORT, that controls

for variance in the tendency to engage in perceptual confirmation.24

(2) Almost all offices with high levels of crisis were in the Defense Department,

and almost all experiencing few such problems were in civilian agencies, though there

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were a number of Defense Department organizations experiencing modest downsizing

and workload increases, and no introduction of competition. Since the larger study of

which this paper is a part showed that working for the Defense Department was

associated with less positive attitudes to reform, a dummy variable (DEFCIV) reflecting

whether the respondent worked for a defense or civilian agency, was included.25

(3) There was considerable overlap between offices subjected to competition and

those whose local office heads were most strongly pro-reform; the first- order correlation

between the variable (CHIEFATT) measuring the attitude towards reform of the head of

the local buying office and COMPETE was .42.26 The overlap was coincidental, since

these local leaders were in place, and supportive of ideas that became associated with

reform, before their offices became subjected to competition. But, since the larger

analysis showed that CHIEFATT influenced frontline attitudes towards reform, it was

necessary to control for this variable to make sure any effects of COMPETE did not

simply reflect values on CHIEFATT.

(4) Three personality trait variables, reflecting individual cynicism or

perceptions of elite dominance over events, were included as control variables for

DSCOVER.27 These traits might be correlated both with a tendency to see reform

cynically as a cover for an effort by those at the top to hurt the “little people” at the

bottom, and more generally with attitudes towards any change process leaders were

pushing. Cynicism might have depressed support for reform even if no downsizing had

taken place, so these variables needed to be included as controls.

Results

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Results are shown in Table One, showing the impact of crisis on the l00-point PR

scale.28 Summarizing, one may state crisis did reduce support for change. The total

variance the crisis variables explained was not small (about .l2).29 More specifically:

(1) The more a respondent’s organization downsized, and the more its workload

increased, the less positive was the respondent towards reform. Running the model (not

shown here) without interactions, the negative effect was larger for workload increases

than for downsizing (standardized coefficients of .04 versus -.07).

(2) Controlling for the effects of office downsizing, there was no significant effect

of the respondent’s personal fear of job loss (p=.26). So the way this general policy

affected an individual’s judgment on an issue of general relevance (one’s attitude towards

reform) seems to have been via the impact of the policy on the organization as a whole,

not via its personal impact on the individual.30 This was the opposite from what would

have been predicted by the view that issue opinions reflect only self-interest. It is

consistent with findings that individual voting behavior is more influenced by a person’s

view of the general state of the economy than of changes in one’s personal economic

situation. (Kinder and Kiewiet 1979; Kinder 1981)

There was a significant interaction between DOWNUP and SOCIABLE,

suggesting a stronger attitudinal impact of losing friends to downsizing. For people with

the highest level of sociability (SOCIABLE=5), a twenty point downsizing was

associated with a decrease of 4.2 points on PR. For a respondent with the lowest level

(SOCIABLE=1), the same downsizing was associated with a trivial decline of 0.7 point.

(4) Two of the three interactions between DOWNUP and blame variables were

significant. Listening to messages from reform leadership, and having a positive

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C:\Greg's Documents\Kelman\Pub Mgt papers\Downsizing Competition and Org Change\TABLE ONE Impact of organizational adversity on attitudinal support for reform.doc, 9/17/2003 12:45 PM N’s OK, SS OK

TABLE ONE: IMPACT OF ORGANIZATIONAL ADVERSITY ON ATTITUDINAL SUPPORT FOR REFORM

Standardized

Coefficient Nonstandardized

Coefficient DOWNUP -0.06 -0.11 WORKLOAD -0.07(****) -0.02 COMPETE -0.11(****) -3.32 DOWNSIZE -0.03 -0.37 DSCOVER 0.18(****) 2.76 KEEPUP 0.01 0.20 TRYBOSS 0.09(**) 1.31 SOCIABLE 0.02 0.37 DOWNUP x TRYBOSS -0.16(****) -0.07 DOWNUP x KEEPUP 0.24(****) 0.12 DOWNUP x SOCIABLE 0.09(*) 0.04 Control Variables DISTORT 0.44(****) 0.5456 DEFCIV 0.13(****) 9.27 CHIEFATT -0.04(*) -2.19 EXPLOIT 0.10(**) 1.44 GRAB 0.01 .14 ESTAB 0.02 0.33 N = 1539 Adj R2 = 0.39

Source: Frontline Survey Statistical Significance Level + ≤.10 * ≤ .05 ** ≤ .01 *** ≤ .001 **** ≤ .0001 Other variables: DOWNSIZE.DONT = -0.02; DSCOVER.DONT = 0.04; KEEPUP.DONT = -0.11(****); TRYBOSS.DONT = 0.05(+); SOCIABLE.DONT = -0.9(**); DISTORT.DONT = -0.03; EXPLOIT.DONT = 0.06(+); GRAB.DONT = 0.08(*); ESTAB.DONT = 0.06(*)

predisposition to reform, eliminated negative effects of office downsizing on attitudes.

For a respondent who kept up the least with top leader statements, a twenty point

downsizing was associated31 with a decrease of 8.2 points in the respondent’s score on

PR. For one who kept up the most, the negative impact of the same downsizing

disappeared. For those with the most critical predisposition, a twenty point downsizing

was associated with a 5.5 point decline in support, while among those with the most

favorable predisposition, the negative impact also disappeared.32 Thus, listening to

leaders or having a favorable predisposition to reform encouraged people to interpret

personal experience with downsizing in a way that didn’t hurt reform support.

However, contrary to the hypothesis, the interaction between downsizing and

DSCOVER was insignificant (p=.74). One possibility is that this provides evidence

against the hypothesis that downsizing reduced attitudinal support for reform via blaming

leaders. However, DSCOVER was independently related to one’s attitude to reform,

controlling for DOWNUP, DOWNSIZE, and the cynicism/anti-establishment variables.

In fact, it had the highest standardized coefficient (.16) in the model. This suggests the

question tapped a general “ideological” interpretation of downsizing and reform policies,

not applied to interpretation of one’s personal experience of downsizing and thus not

interacting with actual downsizing.33 That such general views had a strong impact,

independent of personal experience, is also consistent with the Kinder and Kiewet results.

(5) The hypothesis was that COMPETE would not negatively affect attitudes

towards reform, because there was no reason for respondents to blame reform leaders for

introduction of competition. Actually, it turned out that subjecting an office to

competition had a positive impact on a respondent’s attitudes. The effect size was quite

20

large; in the model without interactions, the standardized coefficient was -.11, larger than

that in the other direction for downsizing. A plausible explanation is that respondents in

offices faced with competition became more positive towards reform out of a view that

reform provided a solution to the challenge competition created, by them to become more

effective. This result is consistent with a “necessity is the mother of invention” view.

One way to look at the impact of crisis on attitudes towards reform is to ask the

counterfactual question of what the mean value of PR would have been absent crisis. To

estimate that, I used the equation in Table One, set crisis-related variables at values

reflecting no crisis (that is, DOWNUP=0, COMPETE=3, WORKLOAD=0,

DOWNSIZE=5, and DSCOVER=5), and other variables at actual mean values.34 Using

these values, the predicted “no crisis” value for PR was 76.6, compared with an actual

mean (reflecting actual values crisis variables took) of 69.1.35 This suggests a fairly

strongly negative impact of crisis on attitudes towards reform. Furthermore, given that

one form of crisis (competition) had a positive impact on attitudes, the predicted mean

value for PR, except using the sample mean for COMPETE (rather than COMPETE=3,

meaning no competition) would have been even higher (80.1), showing an even more

negative impact from downsizing and increased office workload.

Testing for the Behavioral Impacts of Crisis

To test for the behavior impacts of crisis, an ordinary least-squares regression

model was developed with PRIMPACT as the dependent variable. The predictor

variables tested were:

I. Crisis variables

21

The same crisis variables were tested. Many different influences, discussed

earlier, were hypothesized to have an impact on the relationship between crisis and

behavior change. If more than one applies, this will produce some “net” impact of crisis

on behavior change.

Originally – keeping in mind that the relationship between crisis and change was

only a small part of a much larger project -- I had planned to test only for the overall

impact of downsizing and competition, modeling these as main effects hypothesized to

influence behavior change. As I began examining this question, I realized that, given the

many possible influences on the relationship, this simple test would not allow examining

specific hypotheses for why crisis might affect behavior change. So I switched strategy.

Wherever questions already in the survey (for some other reason) made this possible, I

use interaction effects between crisis variables and others to test various hypotheses about

the relationship between crisis and behavior change. The basic logic is that if some third

factor – say, for example, the view that crisis can be overcome by one’s own efforts – has

an impact on the relationship between crisis and behavior change, then that relationship

should be different at different values for that third factor. In some cases, no question

from the survey was available for use, or other problems prevent using the interaction test

strategy; where this is so, I will discuss the strategy employed and/or limitations in the

ability to draw conclusions from the data available.

II. Problemistic Search versus Threat-Rigidity Variables

The model included two variables testing for presence of work-related distress at

the individual level: (2) DOWNSIZE (the same question used in the previous model) and

(2) HIWORK: This was a question asking the respondent to agree or disagree with the

22

statement: “The workload is very high in my job.” If the problemistic search hypothesis

is correct, increased organizational crisis should, ceteris parabis, increase behavior

change. (This is the case ceteris parabis because other influences, such as a negative

reaction to social contract violation that would decrease behavior change as crisis

increases, may be greater than the impact of problemistic search, such that the net effect

of increased crisis might be to decrease behavior change, despite operation of

problemistic search.) However, if the organization-level crisis doesn’t get translated into

personal distress, we would expect this effect to be inhibited or blocked. Thus, we would

predict that the relationship between increased organizational crisis and more individual

behavior change would be less positive (or less negative, if another variable such as

social contract violation negatively affects the relationship between crisis and behavior

change) for those feeling no personal distress than for those feeling high distress. The

same would be the case if the threat rigidity hypothesis is true, though the difference

would be the opposite. Testing for an interaction between organizational crisis and

personal distress thus allows testing for both hypotheses. If there is no significant

interaction, neither is correct, and neither phenomenon would be influencing behavior

change. If there is a significant interaction, which hypothesis is supported depends on

whether, when comparing respondents with high and low personal distress, behavior

change increases or decreases with increased organizational crisis.36 By comparing

effects of crisis at different levels of distress and holding other variables constant, one has

controlled for other factors affecting the relationship between crisis and behavior change.

I hypothesized that introducing competition would have a smaller effect on

behavior change-- either as mother of invention or rigidity – than downsizing.

23

Downsizing presents a clear and present crisis. However, most customers of offices

newly facing competition are likely to stay with the traditional provider, at least for a

while.37 Pressures driving either problemistic search or threat rigidity are thus likely to

be less. We can test this by comparing effects of the same increases in downsizing and

competition.

III. “Social contract” violation

No questions in the survey measured the extent to which respondents valued or

expected job security as a feature of their job. Had such a question been present, an

analogous interaction between it and crisis could have been tested. Alternate strategies

are available, however. First, if we find a significant interaction for variables testing other

hypotheses linking crisis to behavior change – e.g. the test for problemistic search -- we

can set values for such variables where they can’t be influencing behavior. Say we

discover that for respondents with high personal distress, increased crisis was associated

with increased behavior change, compared to those experiencing low distress. For

respondents who strongly disagree their workload is high, we can say that, by hypothesis,

necessity can’t act as the mother of invention, since at this value, no necessity exists.

Under this condition, the coefficient for downsizing would express the relationship

between downsizing and behavior change where the influence of problemistic search had

been eliminated. If we could specify all influences other than social contract violation

using interaction terms, what would be left as an explanation for the impact of crisis

would be the impact of social contract violation. Under more realistic circumstances, this

would be a plausible conjecture.38

24

A second strategy is also available, based on the fact that two of the 19 offices

actually increased their workforce size during the period studied and one had no

change.39 For them, no social contract violation took place.40 This leads to the

prediction that, if social contract violation negatively affects behavior change, the impact

would be nonlinear across values for DOWNUP. For respondents in offices where

downsizing had occurred, greater downsizing would be associated with less behavior

change. However, that relationship would disappear, or at least become less steep, for

those in offices with no downsizing, since there no social contract violation had occurred.

So the slope for DOWNUP would change from positive to flat (or less steep) where

DOWNUP transitioned from being less than zero to zero or greater. The slope change

would produce a nonlinear relationship. The model therefore tested for a quadratic term

for DOWNUP. A significant quadratic term reflecting the change in slope predicted

above would give additional confidence that social contract violation was affecting the

relationship between downsizing and behavior change.41

I hypothesized that any negative impact of social contract violation would be less

strong for introduction of competition than for downsizing. While nobody welcomes

downsizing, some might welcome competition, since offices facing competition may

improve their situation compared to previously; competition provides the carrot of an

upside as well as the stick of a downside. This would be expected to reduce resentment.

To test this, one may compare the impact of moving from highest to lowest-crisis values

for DOWNUP and COMPETE, where interaction variables representing other influences

are not affecting behavior (e.g. where HIWORK=5), to see whether the residual impact of

competition on behavior change was weaker than for downsizing. A limitation of this

25

approach is that controllability, as will be noted below, would also be hypothesized to

influence the relationship between competition and behavior change in a way not testable

using an interaction variable, so any residual impact would reflect the combined

influence of social contract violation and controllability.

IV. Interpretation/controllability variables:

Reform leaders engaged in sensegiving efforts to persuade people that downsizing

was a controllable crisis by arguing that reform was a long-term source of job security –

if buying offices acted in ways that helped their agencies more in achieving the agency’s

mission, rather than simply as regulation-enforcers, their value would come to be

appreciated, and this would protect procurement people from further downsizing. The

model included a question measuring whether a respondent accepted this interpretation of

downsizing: “Long-term, acquisition reform increases job security for contracting people,

rather than decreasing it.” (HELPJOBS) The model tested for an interaction between

DOWNUP and HELPJOBS. If the Mone et al hypothesis is correct, increased

downsizing should produce more behavior change where HELPJOBS=1 than where it

=5, because a sense of controllability would evoke problemistic search.

Additionally, I tested for an interaction between downsizing and KEEPUP, the

question measuring top leader influence. The idea was to test for the possibility that

something else about leader behavior not captured in HELPJOBS was creating a sense of

controllability. This might involve leaders in some general way inspiring confidence that

efforts in response to downsizing could “make a difference,” a form of controllability

interpretation. The model also tested for a triple interaction involving DOWNUP,

HELPJOBS, and KEEPUP, to see whether both accepting a specific controllability

26

interpretation of downsizing and also being inspired by top leaders to believe the crisis

was controllable had a multiplicative effect.42

Seeing controllability as a variable suggests another difference between

introducing competition and downsizing as kinds of crisis. At one extreme of

controllability would be the one-shot public-private competitions that have become

increasingly common in government, where an agency workforce previously assured the

ability to perform certain work must bid against private firms in a contest over who will

perform the work in the future. Such a situation strongly evokes a controllability

interpretation -- the agency had better react by being willing to change, or else they will

quickly be replaced. More broadly, introduction of competition is likely to be seen as

controllable, since, again, by subjecting an office to competition, one hasn’t definitively

taken away resources; one might through one’s own efforts retain the resources (and

perhaps even get more). With downsizing, however, resources have already been taken

away, and people, particularly in government, where these decisions grow out of the

political process, may believe nothing they do has any prospect of getting them back.

If competition naturally, without leader sensegiving, suggests a controllability

interpretation, one cannot perform an interaction test to examine the impact of a

perception of controllability on the relationship between competition and behavior

change, since this perception is embedded in the idea of competition.43 Thus, any

(positive) impact of controllability evoked by competition would be embedded in the

same coefficient for the relationship between competition and behavior change where the

effect of social contract violation caused by introduction of competition also appears –

though of course these two influences would be expected to exert an influence in opposite

27

directions. So it will not be possible to make any distinction between the impact of the

two. We can only examine their joint, net effect.

V. Extrinsic incentives variable

The model tested for an interaction between the crisis variables and PR, to see

whether its effect on behavior would be less for respondents with high levels of intrinsic

motivation (high attitudinal support for reform).

VI. Control Variables

Since PR was in the model, it also served as a control variable. With the

respondent’s attitude towards reform in the model, coefficients for the crisis variables

reflect behavioral impacts of crisis, over and above the (negative) impact of reduced

attitudinal support. Additionally, because PR is in the model, this controls for any impact

of the variable KEEPUP on behavior change that occurred through making people more

attitudinally pro-reform.44

The dummy variable reflecting whether the respondent worked for a defense or

civilian agency was included. The idea was that working in Defense, which correlated

with the extent of downsizing, also was likely to affect behavior change, even controlling

for its impact on attitudes (which was already in the model), because, for many working

on existing major weapons systems contracts, there were relatively few changes that

procurement reform could be expected to bring. CHIEFATT, as previously, was also

included as a control variable for COMPETE.

Results

Results are presented in Table Two, showing the impact of crisis on the four-point

behavior change scale. Table Three shows behavior changes for the various crisis

28

C:\Greg's Documents\Kelman\Pub Mgt papers\Downsizing Competition and Org Change\TABLE TWO The Impact of Crisis on Behavior Change.doc; Saved _ 9/17/2003 12:45 PM; N is OK, SS’s are OK

TABLE TWO: THE IMPACT OF CRISIS ON BEHAVIOR CHANGE

Standardized Nonstandardized Coefficient Coefficient

DOWNUP 0.90(****) 0.0573 DOWNUP2 0.14(***) 0.0002 WORKLOAD 0.01 0.0001 COMPETE -0.18(*) -0.19 Interacting Variables Downsizing

DOWNUP x HIWORK -0.20(****) -0.0042 DOWNUP x DOWNSIZE -0.23(**) -0.0031 DOWNUP x KEEPUP -0.26(**) -0.0045 DOWNUP x HELPJOBS -0.16(+) -0.0022 KEEPUP x HELPJOBS 0.05 0.01 DOWNUP x KEEPUP x HELPJOBS 0.19(+) 0.0008 DOWNUP x PR -0.27(**) -0.0002

Competition

COMPETE x DOWNSIZE -0.23(**) -0.04 COMPETE x KEEPUP 0.23(**) 0.05 COMPETE x PR 0.23(*) 0.00

HIWORK -0.09(*) -0.05 DOWNSIZE -0.01 -0.00 KEEPUP -0.27(**) -0.15 HELPJOBS -0.04 -0.02 Control Variables PR -0.26(+) -0.0089 PR2 -0.42(****) -0.0001 DEFCIV -0.03 -0.06 CHIEFATT -0.03 -0.05 DISTORT -0.00 -0.0001 HIWORK.DONT = -0.02; DOWNSIZE.DONT =-0.03; KEEPUP.DONT = -0.11(***);; HELPJOBS.DONT = -0.09(*); DISTORT.DONT = -0.07(*) Adj. R2 = .25 N = 1499 Statistical Significance Level + ≤ .10 * ≤ .05 ** ≤ .01 *** ≤ .001 **** ≤ .0001 Source: Frontline Survey

C:\Greg's Documents\Kelman\Pub Mgt papers\Downsizing Competition and Org Change\TABLE THREE- CHANGES IN PRIMPACT AT VARIOUS LEVELS OF VARIABLES IN INTERACTING WITH CRISIS VARIABLES.doc Saved _ 9/17/2003 2:11 PM

TABLE THREE: CHANGES IN PRIMPACT AT VARIOUS LEVELS OF VARIABLES IN INTERACTING WITH CRISIS VARIABLES

DOWNUP GOES FROM

-20 → -40 0 → -20 +20→ 0 HIWORK = 1 +.01 +.20 +.39 HIWORK = 5 -.32 -.14 +.05 DOWNSIZE = 1 +.07 +.26 +.45 DOWNSIZE = 5 -.18 +.01 +.20 PR = 40 +.04 +.23 +.42 PR = 70 -.09 +.10 +.28 PR = 90 -.18 +.01 +.20 COMPETE GOES FROM 3→1 DOWNSIZE = 1 +.14 DOWNSIZE = 5 -.16 PR = 40 -.19 PR = 70 -.04 PR = 90 +.06 KEEPUP = 1 -.20 KEEPUP = 5 +.17

Source: Calculated from Table Two. Assumes mean values for other variables interactng with DOWNUP. For COMPETE , numbers derived by taking coefficients for COMPETE and multiplying by two, the change from lowest to highest crisis values for the variable. Note: Figures are unit changes in PRIMPACT from moving the value of DOWNUP as noted.

C:\Greg's Documents\Kelman\Pub Mgt papers\Downsizing Competition and Org Change\TABLE FOUR PRIMPACT OF CONTROLLABILITY VARIABLES.doc Saved _ 9/17/2003 2:11 PM

TABLE FOUR: IMPACT OF CONTROLABILITY VARIABLES ON BEHAVIOR CHANGE

HELPJOBS = 1 HELPJOBS = 5 HELPJOBS=1 HELPJOBS=5

KEEPUP = 1 KEEPUP = 1 KEEPUP=5 KEEPUP=5 DOWNUP goes from -20 → -40 +.04 -.08 -.25 -.11 DOWNUP goes from 0 → -20 +.22 +.11 -.07 +.08 DOWNUP goes from +20→ 0 +.41 +.30 +.12 +.27

Note: Figures are unit changes in PRIMPACT from moving the value of DOWNUP as noted. PRIMPACT not reverse-coded. Source: Calculated from Table Two. Assumes mean values for other variables interactng with DOWNUP.

variables, at different values for variables interacting with crisis variables. (Since, as will

be seen shortly, there was a significant quadratic term for DOWNUP, coefficients are

different at different values of DOWNUP, complicating the presentation.)

The basic story these results tell is that (l) the view necessity serves as a mother of

invention was supported; (2) social contract violation exerted a powerful negative effect

on behavior change; (3) both the positive impact of problemistic search and the negative

impact of social contract violation were larger for downsizing than for introducing

competition -- competition was more of a trauma, generating less resentment, but also

less search; (4) on net, crisis hurt behavior change (controlling for its negative effect via

reduced attitudinal support), reflected in overall coefficients for the crisis variables,

reflecting impacts going in different directions. More specifically:

(1) Significant interactions existed between downsizing and both personal

distress variables in explaining behavior change, in ways consistent with problemistic

search. Looking (Table Three) at behavior change over the same change in downsizing –

say from -20 to -40 – moving from lowest to highest personal fear of downsizing

increased behavior change by .25 unit (had threat-rigidity been correct, the opposite

would have occurred). A similar change for HIWORK increased change by .33 unit.

Furthermore, when personal fear of job loss was highest, moving from medium to the

maximum downsizing (from -20 to -40) on net slightly increased behavior change, by .07

unit – so more downsizing was associated with more behavior change. For HIWORK,

there was a (tiny) increase of .01 unit. These are dramatic findings. They state that, in

conditions maximally promoting problemistic search, increasing downsizing to its

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maximum value slightly increased behavior change, even with the highly negative impact

of social contract violation reflected in the overall (net) coefficient.

For competition, only the interaction with DOWNSIZE was significant. At

DOWNSIZE=1, moving from none to maximum competition was associated with a .l6

unit increase in behavior change.

There was evidence for the hypothesis that interpreting crisis as controllable

encouraged a problemistic search response. Respondents who believed reform saved jobs

in the long run and kept up with the statements of top leaders reacted to downsizing with

increased behavior change. A triple interaction (Table Four) among DOWNUP,

HELPJOBS, and KEEPUP turned out to be marginally significant (p=.10), though not

exactly the way predicted. Instead, there were a number of odd transitions between

HELPJOBS=1 and =5, and odd relationships between HELPJOBS and KEEPUP. What

is key was the reaction of respondents with the strongest controllability interpretation

(HELPJOBS/KEEPUP=1) as the office moved from medium to highest downsizing,

compared with other possible combinations of HELPJOBS and KEEPUP for the same

downsizing change. (This is the first row of Table Four and controls for the impact of

social contract violation, since the change in downsizing is held constant.) As the

controllability hypothesis predicts, with the strongest controllability interpretation

necessity acted as the mother of invention. In fact, this situation, alone of all

combinations of these variables, was the only one with a small positive net impact of

increased downsizing on behavior change.

This finding is unambiguous. However, the least positive impact on behavior

change did not occur at the opposite extreme, where HELPJOBS/KEEPUP=5, which

30

might appear to be lowest perceived controllability. This was contrary to the predicted

effect and suggests interesting things going on with these questions; the patterns provide

further evidence for a problemistic search response, but are not relevant to the impact of a

controllability interpretation and therefore will be discussed in a footnote.45

Taken together, the positive impact of factors promoting problemistic search on

behavior change was very large. With maximum personal distress and controllability

interpretation,46 moving from DOWNUP=-20 to =-40 was associated with a net .30 unit

increase in behavior change.47 We can also compare a situation maximally encouraging

problemistic search with one maximally discouraging it. If one compares behavior

change when DOWNUP moved from 0 to -40 at highest versus lowest levels of these

variables,48 the difference was a massive l.75 units.49

The corresponding impact of introducing competition was much smaller. It would

not be appropriate to compare moving from none to maximum downsizing with moving

from none to maximum competition, because results might be driven by the maximum

downsizing (in this case, 40%) that happened to exist in the sample. So extra calculation

steps were taken to compute standardized coefficients in the presence of interaction

terms.50 As noted, only one problemistic search variable, DOWNSIZE, interacted with

COMPETE. Calculated this way, the impact of a one standard deviation change in

COMPETE at the highest versus lowest level of DOWNSIZE was a .l4 standard

deviation change in PRIMPACT. Restating the result from the previous paragraph, as

DOWNUP makes the same move, PRIMPACT moved .74 standard deviation.51

(2) “Social contract” violation exerted a strongly negative impact on behavior

change. Using the strategy described earlier, we may estimate the impact of social

31

contract violation by setting all problemistic search variables at extreme non-necessity

values.52 Under this condition, the predicted decrease in behavior change from moving

from none to maximum downsizing was a very large .97 unit.

The quadratic term for DOWNUP was also significant in a way consistent with

the hypothesis that downsizing reduced behavior change through resentment over social

contract violation: there was a larger net negative impact on behavior change as

downsizing increased. This shows up in Table Three through more negative (or less

positive) impacts of downsizing on behavior change across the rows, as downsizing

increased, at any given level of problemistic search. Thus, for example, where the

workforce was downsized from -20 to -40, even the highest perceived workload was only

able to bring about only a .0l increase in behavior change, while in the case of a similar

decrease (but at more modest crisis levels) from 0 to -20, the same highest perceived

workload was able to bring about a much larger .20 unit increase. Put another way, the

20 point move from DOWNUP=-20 to =-40 created a .l9 unit greater decrease in

behavior change than did the same percentage-point move from DOWNUP=0 to =-20.

For competition, there were also social contract violation effects, but these were

much smaller. Given the assumption, discussed earlier, that competition naturally

generated a controllability interpretation, one may isolate comparative effects of social

contract violation alone for downsizing and competition by, for downsizing, setting

interacting variables where problemistic search was minimized but controllability

maximized,53 while for competition, where problemistic search was minimized.54

Under these conditions, a one standard deviation change in competition affected behavior

change by .07 standard deviation,55 while the same downsizing change had a .21 effect.56.

32

(3) There was evidence downsizing acted as an extrinsic incentive, producing

more behavior change among reform critics than supporters. For respondents with low

attitudinal support for reform (PR=40), moving from DOWNUP=-20 to -40 was

associated on net with a small increase (.04 unit) in behavior change. So for those with a

low level of intrinsic motivation to change, crisis acted as a source of extrinsic

motivation, increasing change. With the same increase in downsizing, high attitudinal

support (PR=90) was associated with less change (a decrease of .l8 unit). For those with

high intrinsic motivation, the extrinsic incentive crisis provided had a negative impact.57

(4) Some interactions for introducing competition were different than for those

involving downsizing. There was a significant interaction between COMPETE and PR in

explaining behavior change, but it was the opposite from downsizing and from the

prediction of the undermining effects hypothesis. Here, reform supporters changed

behavior more than critics – at values for PR over 78, competition was associated with

more behavior change. This finding, however, follows logically from the one that people

in offices facing competition became more likely to become attitudinal supporters of

reform. Clearly, if a person became more supportive of reform as a way to respond to

competition, it would be pointless to fail to carry that attitude into reform-oriented

behavior, for without the corresponding behavior, the attitude wouldn’t help survival. So

the earlier findings provide a logical explanation for this result.

Second, the results unexpectedly showed that the more respondents kept up with

statements of systemwide leaders, the less they reacted to competition by increasing

behavior change -- the opposite to downsizing. (The prediction was that this interaction

would be insignificant, because competition was not associated with reform, nor

33

discussed by reform leaders.) A possible explanation is that respondents focusing on

their office, in an environment where the office faced competition, rather than “taking

their eye off that ball,” became more likely to change behavior.

A simple way of stating these results is that there were basically two impacts of

crisis, a positive impact from problemistic search and a negative one from social contract

violation. The result of these conflicting forces was that, with both downsizing and

competition, for about half the sample affected by crisis, greater crisis was associated

with more behavior change, and for about half it was associated with less. If one looks

only at respondents in buying offices where downsizing occurred (i.e. DOWNUP<0) and

takes actual respondent values for the variables in the model, we can estimate that for

50.2% of the sample, increased downsizing was associated with more behavior change.58

Calculating the same way,59 for 45.2% of the sample, increased competition produced

more behavior change.

To examine the net direct impact of crisis on behavior change, excluding indirect

effects via lowered attitudinal support, I plugged into the model in Table Two the same

no-crisis values for crisis variables used earlier, along with mean sample values for the

other variables, including PR. At these values, the predicted “no crisis” value for

PRIMPACT was l.65, somewhat lower than the actual sample mean of 1.81.60 So, even

controlling for its effect on attitudes, crisis had a negative impact on behavior change.

Thus, crisis reduced pro-reform behavior, both through reducing attitudinal support and a

negative direct impact on behavior.

What about the overall impact of crisis, accounting both for its indirect effects via

lowered attitudinal support and its direct ones? I performed the same calculation, except

34

for entering 76.6 as the value for PR, reflecting the predicted value of PR with no crisis.

Here the predicted value for PRIMPACT was l.5l, suggesting that, overall, crisis had a

noticeably negative overall impact on behavior change.61 If one separates the total

impact of downsizing and of introducing competition, downsizing had a somewhat more

negative net impact on behavior change than competition.62

Discussion

As noted, in much of the scholarly literature on the organizational performance

implications of downsizing, the debate has been posed as one between problemistic

search and threat-rigidity. These data suggest the economists get the better of that debate

with psychologists: the evidence was that necessity was the mother of invention, not

rigidity. Although widely cited, the threat-rigidity argument seems problematic even

theoretically. The examples Staw et al give of situations evoking this response (l981:

503-05) involve sudden, traumatic events -- threats of electric shock in the lab or natural

disasters such as earthquakes. This raises questions about the relevance of threat-rigidity

to an organizational crisis lasting over a significant period of time.

However, these results suggest crisis may have a negative impact on behavior

change, not because of threat rigidity, but because problemistic search has been

overwhelmed by negative effects growing out of resentment over the pain of crisis. Thus

an economic approach to human behavior may have won the battle but lost the war.

The prescription for creating crisis in government organizations to counteract

sloth due to overly assured resource flows suffers from sloppy analogies with business

firms. In firms, with competition assumed, there is no reason to expect it to produce

resentment. Also, it is easier, though, as noted earlier, far from assured, for a company to

35

escape resentment from downsizing or (increased) competition if employees believe

crisis emanated purely from the environment, with management mere robot-like

executors of impersonal forces. In government, this sell is well-nigh impossible, since

downsizing, or introduction of competition, seems clearly a policy decision.

Furthermore, given that expectations of job security (and monopoly-like status) were

traditionally greater in government, the social contract would likely have been stronger

and hence resentment at violation greater. All these differences imply that crisis-related

performance improvements in business are likely to be greater than in government: if

resentment is absent, only problemistic search effects remain, a result consistent with the

standard literature on the salutary effects of competition on performance.

The finding that, overall, crisis reduced behavior change might be argued to

reflect a short-term rather than long-term reaction. We saw in the data strong evidence

necessity acted as a mother to invention. But resentment over crisis overwhelmed those

effects to produce an overall negative impact. Many have argued (e.g. Capelli l999) that,

in the wake of downsizing in the private sector beginning in the l980’s, there has emerged

a new social contract where employees no longer assume permanent employment (and

have reduced employer loyalty in return). If such a revised social contract develops, one

might expect resentment over downsizing will decline, leaving only problemistic search

effects and increasing the positive effect of crisis on behavior change.

There is a problem with this argument, however. If necessity stops taking with

one hand, it may also stop giving with the other. The same distress that creates

resentment in a world where the old social contract prevails also creates pressure for

behavior change. If distress due to downsizing declines because the social contract is

36

rewritten, the same change-inhibiting reduction of resentment this produces would also

produce a reduction in change-promoting problemistic search. (A version, albeit not

exact, of this tradeoff appears in these data regarding comparative impacts of downsizing

and introduction of competition, where there was little net difference in impacts on

behavior change.) So there’s no reason the long run will necessarily show different

effects from the short run. It is possible, though this is speculative, that eventually

competition might become as much a matter of course in some government agencies as in

private business firms, such that it generates no resentment, in which case in the long run

competition might produce effects in the public sector similar to those produced in firms.

It is also plausible that resentment is not an equal danger to all change efforts.

Resentment probably applies more to frontline employees than managers. The more a

change requires, as did procurement reform, voluntary frontline collaboration, the more

the negative impact of resentment is a problem. The more it involves organizational

redesign management executes (as with one-shot competitions where government offices

compete for jobs with contractors), the less resentment might impede change.

Finally, it should be noted again that these results apply directly only to one

impact of imposing crisis as a tool for improving government performance, namely the

impact on performance-improving organizational change. Downsizing and introduction

of competition are likely to have positive impacts on costs. And these results do not

address overall impacts on work effort on existing tasks, though there are reasons to

suspect that resentment-related effects might counteract potentially positive direct

impacts on work effort. Nonetheless, this paper suggests caution regarding a popular

prescription for how to improve government performance.

37

38

1 This is a reference to what it takes to rouse drilling workers on oil rigs from complacency.

2 Buying offices consist of functional specialists who buy products and services on behalf of end-users, generally people working on an agency’s substantive activities.

3 The researcher was responsible for leading this reform effort as administrator of the Office of Federal Procurement Policy in the Office of Management and Budget; the research was undertaken upon the author’s return to academia. For more detail about the kinds of changes that took place, see Kelman (forthcoming: Ch. 2).

4 Kelman (forthcoming)

5 For a further discussion of issues related to the survey, including the weighting procedure used to account for the overrepresentation of Defense Department employees in the unweighted sample, see the Appendix, “Sampling Issues and Survey Administration,” available at http://ksghome.harvard.edu/~.skelman.academic.ksg/MS/Appendix.pdf.

6 In the data analysis, so as not to lose cases to these missing values, a respondent answering “don’t know” or leaving a question blanked was coded “0” in the response to that question and “l” on a separate dummy variable, given the variable’s name with DONT added on. Respondents who answered the question were coded with the response they gave and “0” on the DONT dummy. I am grateful to my colleague Jim Stock, who suggested this method to me.

7 In only one of the organizations were any employees fired, through “reductions in force” (RIF’s). In an additional three (all military), RIF’s were being seriously discussed, though none had taken place. In the other offices, all downsizing occurred through attrition, including “buyouts” Congress authorized for the federal workforce as a whole, which allowed agencies to offer monetary incentives to employees not eligible for retirement to leave government.

8 See Kelman (forthcoming), Ch. 3.

9 The larger study did find a strong relationship between attitudinal support for procurement reform and behavioral change.

10 These two impacts of resentment are different: the first involves people perceiving that the same people they hold responsible for crisis are also those promoting the change effort, while the second does not.

11 There exist no studies about whether environmental “states of nature” encouraging or discouraging certain behaviors get perceived similarly to extrinsic incentives, though arguments in the literature for why extrinsic incentives reduce intrinsic motivation would not appear to apply to such situations. However, even if a crisis originating in the environment (or from the decisions of senior organization leadership, who are people not in any real position to provide direct incentives to frontline employees to behave a certain way) does not create extrinsic incentives, a person’s superiors might turn crisis into an occasion to provide extrinsic incentives by tying rewards to behavior designed to counter crisis.

12 See McKinley et al (2000) for a brief summary of the literature on downsizing and for bibliographic references to existing studies. For a summary of studies on the performance impacts of the introduction of

39

competition into business monopolies, see generally Winston (l998) and in particular the chart on p. 99, and La Porta and Lopez-de-Silanes (l997).

13 A third study (Dougherty and Bowman 1995) found a negative effect of downsizing on product innovation, though their sample was small (twelve firms). Their finding was completely driven by downsizing-driven breakups in informal networks innovators used to “work the system” to gain support across intraorganizational boundaries, an effect not relevant to any of the hypotheses under consideration here and not really relevant to change efforts within an organizational unit that don’t require this.

14 One might have constructed one structural equation model with both direct paths to the dependent variable and indirect ones mediated through attitude. But this would have been an unwieldy model; also, structural equation models don’t handle interaction effects very well, and these are central to testing many of my hypotheses.

15 Because of changes in agency spending over the period, the correlation of values for these two variables was essentially nonexistent (.03).

16 I was concerned this variable might be ordinal rather than interval. A scatterplot against PR showed no evidence of nonlinearity across the three values of the variable.

17 The scale consisted of responses to the following statements in the survey, developed from other instruments measuring sociability: (a) “Generally, I prefer to be by myself,” (b) “I like spare time activities which allow me to get away from people,” (c) “I would prefer a quiet evening at home to attending a social event,” (d) “I like spare time activities which allow me to get away from people,” (e) “I only telephone friends when there is something important to discuss,” (f) “I like eating alone,” (g) “This is a good job for a loner,” (h) “I would rather telephone a friend than read a magazine in my spare time,” and (i) “I like to talk with my colleagues on the job whenever I have the chance.” Respondents needed to have answered half the questions to be included in the scale. The last two questions were reverse-coded. The Cronbach’s alpha for SOCIABLE was .6l, below the normally desired level of .7. One reason is that the length of the survey increased the proportion of random answers, producing more noise, which reduces the internal structure of a scale and lowers the alpha coefficient Second, the scales virtually all involve questions measuring psychological dispositions. My guess is that, in a survey presented as being about procurement, a significant number of respondents were puzzled by or resentful of questions having nothing to do with that topic, such as whether one liked to plan trips carefully or respect the authority of management, producing greater randomness in answers and hence answered these questions randomly because they resented being asked to answer them at all. One piece of evidence for this explanation is that generally a much larger percentage of respondents (often around 15%) left these questions blank, or responded “don’t know,” than for the more procurement-related questions; one way to deal with a question one doesn’t want to answer is by leaving it blank, while another is to answer randomly. By contrast, the Cronbach’s alpha for the one scale in the larger study using questions related to the respondent’s job in procurement did have an acceptable alpha coefficient of .70. The alpha coefficients certainly suggest significant structure to the scales. The presence of noise suggested by low coefficients makes it harder to demonstrate statistical significance in a relationship, and hence makes these results a conservative test.

18 SOCIABLE is a somewhat different measure of the phenomenon discussed in the Shah paper, since it measures the extent to which people value social ties rather than whether they had lost a personal friend.

19 Including myself.

20 In a literal sense, this was true, since the reform leadership hadn’t been involved in or consulted about the downsizing decisions, which proceeded our arrival in the government.

21 Another way of putting the same point is to note that if the top-leadership message had no influence, it wouldn’t matter how much a person listened to it.

40

22 Note that higher values for TRYBOSS reflect a more positive initial attitude towards reform.

23 The model thus includes no competition-related variable analogous to DSCOVER.

24 The variable was developed as follows. A question in the survey asked respondents: “What’s your best guess about the proportion of your co-workers (at your office) whom you would regard as supportive of acquisition reform?” However, since I knew not only what buying office the respondent worked for but also what workgroup within the buying office, we know what proportion of a respondent’s coworkers actually were supporters (i.e. PR>50). To form DISTORT, the actual percentage of supportive coworkers was subtracted from the respondent’s perception of coworker support. (The categories on the survey question were “almost everyone,” “about two-thirds,” “about half,” “about one-third,” and “very few.” To make these calculations, “almost everyone” was assumed to be 90% and “very few” assumed to be 20%.)

The result could be a positive number (the respondent overestimated coworker support for reform), a negative number (respondent underestimated), or zero (respondent estimated correctly). To determine a respondent’s value for DISTORT, if there was a positive value from this calculation and the respondent’s own score for PR was greater than 50, the value for DISTORT was equal to the calculated number. The same was the case if there was a negative value from the calculation and the respondent’s own score for PR was less than or equal to 50. If the value from the calculation was zero, or if the respondent overestimated support and was himself or herself critical of reform, or underestimated support while being personally supportive of reform, the value of DISTORT was set at zero; it was also set at zero if the respondent gave the response alternative “don’t know” to the question about coworker support.

DISTORT therefore measured the extent to which, if one was positive towards reform, one overestimated the extent of reform support among coworkers, and, if one was negative, one underestimated it. The higher the value for DISTORT, the more a reform supporter engaged in perceptual confirmation. The lower the value for DISTORT, the more a critic engaged in it. Values around zero show a low degree of perceptual confirmation. In a regression equation with a variable subject to perceptual confirmation, DISTORT controlled for operation of perceptual confirmation that would make reform supporters give values for the variable that were exaggeratedly high and critics gave values exaggeratedly low – for example, that supporters underestimated the extent to which leaders were to blame for downsizing and opponents overestimated the extent it to which they were. In other words, it measured the extent to which self-reported positive or negative views on (or experiences with) reform were explained by the tendency of a person’s reaction to be influenced, either positively or negatively, by perceptual confirmation.

Also, since the model included the variable TRYBOSS, reflecting initial predispositions to like reform, coefficient for DSCOVER/DOWNSIZE also control for the respondent’s initial attitude towards reform.

25 It took the value “l” if the respondent worked for a civilian agency, zero otherwise.

26 Information on attitudes towards reform of local office heads of the buying offices in the survey was gathered from on-site interviews. As coded (see the discussion in Kelman forthcoming), CHIEFATT was a dummy variable separating the most enthusiastic office heads from everybody else; this office-level variable was then assigned to the individual respondent.

27 These were the following questions: (l) “People are just out to get what they can from you” (EXPLOIT); (2) “In this world, you have to get there first and grab what you can” (GRAB); and (3) “No matter how wonderful the ideas you are trying to get across may be, you cannot do a thing unless you have the powers that be on your side” (ESTAB)

28 Both standardized and non-standardized coefficients are presented. I present results involving

standardized coefficients whenever possible, except for interaction effects, difficult to present as standardized coefficients.

41

29 This was after the variables DISTORT, DEFCIV, TRYBOSS, KEEPUP, and SOCIABLE, which did not relate to crisis, were eliminated from the model.

30 The level of downsizing in the office might well have influenced the individual’s subjective fear of job loss. However, in such a case, subjective perceptions would mediate the relationship between objective circumstances and the dependent variable, and, statistically, one would expect an ordinary least-squares regression to show a relatively higher coefficient for DOWNSIZE and a lower one for DOWNUP. (James and Brett l984) This was therefore a conservative test that underestimated the total (direct and mediated) influence of DOWNUP and overestimated the influence of DOWNSIZE. The insignificant coefficient for DOWNSIZE thus is an even stronger statement.

31 This assumes mean values for the other three variables in the model with significant interaction effects with DOWNUP. This procedure will also be applied for other results involving interactions presented here.

32 There is reason, however, to be concerned that the coefficient for the interaction between DOWNUP and KEEPUP included both the influence of KEEPUP on inhibiting the negative attitudinal impact of downsizing and also the possibility that respondents who were bothered about downsizing and more hostile to reform started paying less attention to statements of pro-reform top leaders. If one leaves KEEPUP out of the model because of worries about these confounding effects and just leaves in TRYBOSS (this alternative version is not shown here), the effect for TRYBOSS remained.

33 There were correlations of .l0 and .27 respectively between DOWNUP/DOWNSIZE and DSCOVER, suggesting the possibility of a mediated relationship whereby one’s experience produced an ideological interpretation, which in turn produced reduced attitudinal support. However, when one removes DSCOVER from the model, DOWNSIZE was still not significant (p=.98), supporting the conclusion that no such mediation occurred. (Also with DSCOVER removed from the model, the standardized coefficient for DOWNUP in a model without interaction terms – used for ease of interpreting the impact of DOWNUP – increases only from .04 to .05, suggesting only very modest mediation.) These results taken together suggest that a respondent’s ideological interpretation of reform (DSCOVER) influenced attitudes towards reform only when the ideological interpretation was not related to personal experience.

34 I set DOWNSIZE/DSCOVER=5 because, in the non-crisis counterfactual, people would presumably have strongly disagreed with these statements. EXPLOIT, GRAB, and ESTAB remained in the model, so cynicism-related determinants of answers to DSCOVER, which would still be present influencing attitudes even if no downsizing had occurred, were in this version of the model. I set a mean value for the dummy variable DEFCIV, though, strictly, dummy variables do not have mean values.

35 Since “no crisis” values nonetheless reflect reactions in a general environment where crisis had occurred, these estimates should be treated cautiously; there are reasons to believe some of these “no crisis” counterfactual values underestimate the impact of crisis on support for reform, while others overestimate it.

Even in buying offices that had themselves experienced no change in employment or workload, people nonetheless were in an environment where downsizing and workload increases were occurring in other organizations. These environmental effects might well have caused some level of hostility towards reform, even though the crisis had not (yet) affected their own offices; since the counterfactual presumes no crisis, the actual values DOWNUP/WORKLOAD=0 would in such a case fail fully to take crisis into account and thus underestimate negative reactions. On the other hand, if other causes of responses to DSCOVER relating to factors other than downsizing itself (in addition to the three variables in the model) were missing and were correlated with PR, setting DSCOVER=5 would have eliminated factors that would have remained as influencers of attitudes towards reform even absent downsizing, thus exaggerating the impact of the “non-crisis” value for this variable, and biasing the estimate of the impact of no crisis upward (since the unmeasured influences on DSCOVER would have remained even absent a crisis and would have influenced attitudes towards reform).

42

36 Recall that behavior change could occur due both to activities local leaders or supervisors organized and to behavior changes individual employees chose to undertake, given that many features of reform involved changes individuals were empowered but not required to make. This interaction tests only for the impact of crisis on changes individuals choose whether to make, not for the impact of crisis on steps local leaders/supervisors might take.

37 Typically, developing an internal capacity will be costly, and there are often not a huge number of competing sources of supply.

38 Note that the test for problemistic search versus threat rigidity includes only individual-choice effects and not office-induced ones. If problemistic search is correct, this will mean that any negative coefficient for social contract violation would be too low (making the test a conservative one), while if threat-rigidity is correct, the opposite would be the case.

39 In all, 15% of weighted sample respondents worked in offices experiencing no downsizing.

40 People in these organizations might have experienced some sort of a social contract violation through seeing downsizing occur in other organizations. Such environmental effects, if they existed, would presumably have affected all respondents equally, certainly at least all respondents in non-downsized organizations, and thus not influenced the slope of any relationship between lack of downsizing and behavior change.

41 One might imagine yet another hypothetical variable that would behave in a similar way for people in downsized and non-downsized offices, but such hypothetical alternatives become ever-more far-fetched.

42 Another possibility would be that HELPJOBS had a problemistic-search inducing impact only for respondents who had developed the idea based on listening to the views of top leadership rather than on their own.

43 Though, as noted, reform leaders did not specifically promote a controllability interpretation for downsizing, the model nonetheless tested for an interaction between COMPETE and KEEPUP, in case such an effect (perhaps through boosterism) occurred anyway.

44 A PR quadratic term was also included, because the larger analysis had shown a nonlinear effect of attitudes on behavior, where for reform skeptics, there was little relationship between attitude and behavior, while for reform supporters, there was a strong relationship. Also, interactions of the crisis variables with PR, and PR was correlated with these variables, I also included a PR quadratic term. At the same time, the quadratic term also allowed controlling for an alternative explanation for significant interaction effects between PR and third variables in explaining PRIMPACT. Since an interaction is a multiplicative term, like a quadratic term, what appears as a significant interaction between PR and a variable correlated with PR might in effect be a quadratic term for PR itself, simply reflecting that PR’s relationship to PRIMPACT is curvilinear. (I would like to thank my colleague Dani Rodrik for discussing this issue with me.)

45 What seems to have been going on is that HELPJOBS=1 represented a controllability interpretation (“we can counteract downsizing by embracing reform”) to those who heard this argument from listening to systemwide leaders. However, for many respondents, the HELPJOBS statement (“long-term, acquisition reform increases job security for contracting people, rather than decreasing it”) seems to have tapped subjective perceptions of necessity, like HIWORK and DOWNSIZE, rather than controllability; it seems to have reflected a subjective perception that “the system won’t save us” from job loss. For these respondents, the HELPJOBS=5 response (“reform won’t save jobs”) apparently reflected a general view that jobs continued to be in danger, a perception evoking a problemistic search reaction similar to that occurring where personal distress was high. Such a reaction was strongest for those who didn’t listen to top leaders, and therefore were unable to put the HELPJOBS statement into the ideological context in which the leaders put it. Thus, in Row l, the smallest falloff from the behavior change-encouraging response to a

43

strong controllability interpretation occurred among people who kept up with top leader statements (and thus might have been encouraged by top-leader boosterism) and for whom HELPJOBS=5, which for some respondents implied strong perceived necessity, balancing the situation for those who simply disagreed with leaders’ controllability interpretation. However, if a respondent didn’t keep up with top leader statements, behavior change was actually considerably lower if HELPJOBS=1 than if HELPJOBS=5, not higher as was originally predicted: for people who didn’t keep up with leader statements, responses to HELPJOBS seemed to reflect simply whether one feared job loss and not involve controllability at all, so those for whom HELPJOBS=1 felt less a pressure of necessity than those for whom HELPJOBS=5, and thus their behavior change decreased. The most negative impact on behavior change therefore occurred for those for whom KEEPUP=5 and HELPJOBS=1: these respondents saw the HELPJOBS question as involving fear of job loss (because they didn’t keep up with leader statements and thus didn’t understand the controllability argument), and they felt the lowest fear of job loss, discouraging problemistic search. This is why these data should be seen as additional evidence for presence of a problemistic search response.

46 I.e. HIWORK/DOWNSIZE/HELPJOBS/KEEPUP=1

47 This figure is calculated from the model in Table Two, using the polynomial for DOWNUP, along with the other variables, to calculate the impact on the dependent variable. Mean values for all other variables in the model were assumed.

48 I.e. the problemistic-search encouraging values above versus their opposite (HIWORK/DOWNSIZE/KEEPUP=5, HELPJOBS=1).

49 These calculations assume a mean value for attitudinal support for change. If one sets PR=40 instead, reflecting the finding that the incentive to undertake problemistic search is an extrinsic incentive that operates most strongly on those with negative attitudes towards reform, then the impact of crisis on those most inclined to show a problemistic search response would have been even higher.

50 I would like to thank Justin Wolfers for his assistance on methods for doing so.

51 The results using non-standardized coefficients, with actual sample minimum and maximum values for downsizing, were comparable.

52 These were HIWORK/DOWNSIZE/KEEPUP=5 and HELPJOBS=1.

53 HELPJOBS/KEEPUP=1 for maximum controllability, HIWORK/DOWNSIZE=5 for minimum problemistic search

54 i.e. DOWNSIZE=5

55 All other interacting variables were set at mean values. This assumes competition automatically generates a maximum controllability interpretation, which is doubtless at least somewhat exaggerated.

56 This assumes a one standard-deviation move from DOWNUP=-20, which was approximately the mean value of the variable. Since DOWNUP had a significant quadratic term, this number would be greater for a one standard deviation move at a lower value for DOWNUP, less at a higher value. With resentment increases disproportionately smaller where there was little downsizing, a one standard deviation move starting from DOWNUP=0 was associated with a .06 standard deviation change, about the same as a one standard deviation move in COMPETE.

57 Thus, the effect of downsizing as a force generating extrinsic incentives served to reduce the negative impact on behavior of the decline in attitudinal support crisis had produced. Crisis made people more negative toward reform, and more negative attitudes dampened behavior change. However, this

44

relationship was attenuated because the same downsizing making people more attitudinally critical also created an extrinsic incentive for those critics to change their behavior.

58 DOWNUP (and COMPETE) interacted with other variables, so to determine the percentage of respondents for whom increased downsizing was associated with less behavior change, the formula for the conditional effect of DOWNUP (conditioning on the variables with which it interacted) was used. The value of these variables for each respondent was entered to find the conditional effect of DOWNUP (or COMPETE); the total number that were negative counted and the percentage calculated. My research assistant Chris Hans suggested this method.

59 That is, including only respondents for whom COMPETE=1,2.

60 This suggests that, although almost half the sample had positive coefficients for DOWNUP and COMPETE, the negative effects for those with negative coefficients were on average greater than the positive coefficients for those with positive ones.

61 However, crisis was not a major determinant of the extent of behavior change. The three crisis variables, if run in a simple model (not shown here) without other variables or interaction effects, explained under 2% of the variance in behavior change.

62 If we set all the crisis variables at no-crisis values except for COMPETE, which is set at the sample mean value, while setting PR equal to the predicted value it would have taken under the same condition, with COMPETE at its sample mean (the predicted value for PR under this condition was 80.l), then the predicted value of PRIMPACT is 1.49. If one performs an analogous calculation setting COMPETE at its no-crisis value and DOWNUP/WORKLOAD at sample means (the predicted value for PR under this condition was 72.3), the predicted value for PRIMPACT was l.58.

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