The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 615
The Influence of Red Tape
on Bureaucratic Behavior:
An Experimental Simulation
Patrick G. Scott
Sanjay K. Pandey
Abstract
Understanding how certain organizational and individual attributes shape responses
to red tape is an area that has received little research attention. This study uses an
experimental simulation to address these questions. It examines the effect of red
tape upon the propensity to provide assistance to clients in a simulated public assistance agency. The findings showed that increasing levels of red tape produce in a
corresponding reduction in benefits provided to clients, but that this relationship is
strongly moderated by the respondent’s perceptions of clients. Clients perceived as
more sympathetic consistently received higher levels of benefits than those perceived
as less sympathetic. Education and professional training also played a role in influencing award decisions. © 2000 by the Association for Public Policy Analysis and
Management.
INTRODUCTION
Red tape is everywhere and everywhere it is abhorred.... [It] has taken its place with death and
taxes as an inevitability of life. It may even be more durable than they are (Kaufman, 1977, pp.
1, 97).
There are few if any organization studies topics that hold more promise. Red tape is not the
only remaining frontier for organization researchers, but it is certainly among those most
worthy of exploration. If systematic, empirical knowledge of red tape begins to emerge, confidence-inspiring prescriptive theory will likely follow closely (Bozeman, 1993, p. 300).
One would be hard pressed to disagree with either of these assertions. Despite
recent and well-publicized efforts to identify and eliminate red tape in government,
red tape is still very much with us. As Pandey (1995) notes, America in this century
has seen the formation of 10 different commissions to improve the effectiveness of
the federal government, the latest one of which declares boldly, “The federal
government does at least one thing well: it generates red tape (National Performance
Review, 1993, p. 11).”
Over the past 20 years the number of theoretical and empirical studies on red tape
has grown and has led to notable progress in our understanding. For example, sectoral
comparisons of red tape have both reinforced and challenged traditional beliefs about
the existence of higher levels of red tape in the public sector. In addition, the research
Manuscript received July 1998; revise and resubmit recommended October 1998; revision received April 2000; paper
accepted May 2000.
Journal of Policy Analysis and Management, Vol. 19, No. 4, 615–633 (2000)
© 2000 by the Association for Public Policy Analysis and Management
Published by John Wiley & Sons, Inc.
616 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
has led to improvements in how red tape is conceptualized and distinguished from a
closely related construct—formalization.
Red tape1 is commonly invoked to describe organizational procedures that are
viewed as wasteful, unnecessary, self-serving, and vexing; in fact, it connotes the very
worst of bureaucracy. The term is often used as an attention-getter to channel
resentment against all sorts of organizational maladies. Few phrases pack as much
punch as “red tape” and at the same time prove to be as elusive when one tries to
narrow down to a core meaning (Pandey, 1995).
Fortunately, over the past few years several studies have made advances in the
theoretical specification of the red tape concept, and as a result our understanding of
red tape is much sharper and more focused (Bozeman, 2000; Bozeman and Scott,
1996; Rosenfeld, 1984). This research has also led to the development of various
taxonomies of red tape, a better understanding of the origins and effects of red tape,
and clearer distinctions between red tape and closely related constructs employed by
organization theorists.
Although progress in conceptualization of red tape is a welcome development, the
research has not given as much attention to the more interesting and substantive
issue of how red tape may influence individual behavior. Why, for example, do some
individuals have a propensity to cut through red tape while others are less inclined to
do so? Do certain threshold levels compel individuals to no longer attempt to cut
through red tape? Alternatively, are there certain types of individual or organizational
attributes that facilitate “cut-through” behavior?
The purpose of this paper is to provide, first, a brief overview of some of the major
conceptual and empirical advances in red tape research. The paper then reports
findings from a study that simulates a bureaucratic decisionmaking environment to
study the effects of increasing levels of red tape upon an individual’s propensity to
assist clients. The paper concludes by focusing on the practical application of these
findings and their implications for future research on red tape.
RED TAPE: AN OVERVIEW OF CONTRIBUTING STUDIES
Theory-Based Efforts
The earliest scholarly treatments of red tape began with the work of sociologists who
highlighted the problems of bureaucratic inefficiency that potentially inhere in the
ideal-type formulations of Weber (Gouldner, 1952; Merton, 1940). In his study of the
bureaucratic personality, Merton (1940), for example, suggested that red tape often
results when generalized rules are invoked for particular, limited, or exceptional
circumstances. Adherence to formalized procedures interferes with the adaptation
of these rules in particular circumstances and, in such instances, those rules can
degenerate into red tape. Red tape can also result when following rules becomes an
objective unto itself.
Seeing red tape as more a social than an organizational malady, Gouldner (1952)
posited that red tape is a phenomenon grounded in individualistic perceptions. Red
tape is determined not only by the situation itself but also by the frame of reference
through which it is viewed. Gouldner was one of the first to suggest the possibility
1
A good working definition of red tape is provided in Bozeman (2000, p. 12), where red tape is defined as
“rules, regulations, and procedures that remain in force and entail a compliance burden but do not advance the legitimate purposes the rules were intended to serve.”
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 617
that red tape could be distinguished in terms of subjective and objective elements.
Gouldner considered red tape to be a social problem because red tape tends to correlate
positively with perceptions of powerlessness, alienation, lack of trust, and inability to
defer gratification.
Several economic theorists have also addressed red tape (Alchian and Demsetz,
1972; Niskanen, 1971). These theorists try to explain why public organizations have
presumably higher levels of red tape than private organizations. Property rights
theorists (Alchian and Demsetz, 1972; Davies, 1971), for example, suggest that private
managers have direct rights to the economic returns of the organization, thus providing
a strong incentive to increase their personal gain by efficient use of resources in the
organization. Such incentives do not exist for the public manager and thus, the public
manager is more tolerant of red tape and inefficiency. In similar fashion, public choice
theorists (Buchanan and Tullock, 1962; Niskanen, 1971) suggest that red tape results
from the absence of market signals to serve as indicators for setting production levels
of public goods and services. Without such signals, public organizations are compelled
to rely on budgetary increases, staff growth, and other nonmarket indicators as criteria
for success. This creates the tendency among government organizations to produce
goods and services that exceed what is allocationally efficient for society.
Some organization theorists, by contrast, link red tape to an organization’s life cycle
(Greiner, 1972; Quinn and Cameron, 1983; Walsh and Dewar, 1987). As an organization
passes from its initial entrepreneurial and collectivity stages into its control stage, it
begins to enter into a phase marked by the elaboration of rules (formalization2). This
process has a positive effect on administrative efficiency and organizational effectiveness
early in an organization’s history because it provides a set of role expectations and
reduces uncertainty (Walsh and Dewar, 1987). Formalization can, however, contribute
to decline and ineffectiveness later in an organization’s life cycle as decision premises
become entrenched, new rules are added to changing circumstances without regard to
their effect upon existing arrangements, and rule compliance becomes equated with
effective organizational performance. Rules become ends in themselves, and as they
become the domain of vested interests, there is correspondingly little incentive to change
or reduce them (Walsh and Dewar, 1987). Procedures take precedence over problem
solving and declines in innovation and productivity follow. Such trends, if left unchecked,
can lead to inefficiency, red tape, and organizational decay.
One of the most highly quoted works on the topic is Herbert Kaufman’s Red Tape:
Its Origins, Uses and Abuses (1977). Kaufman argues that we as citizens are largely to
blame for red tape because most rules and regulations result from the multiplicity of
demands on government generated by a multiplicity of interests. According to
Kaufman, red tape is not the product of incompetent, scheming, or personal utilitymaximizing bureaucrats that public choice theorists might assert, but rather, is an
inevitable by-product of a political system that attempts to be accountable to diverse
and often-times competing interests. Red tape is the inevitable price we pay to ensure
fairness and equity in the treatment of citizens. To be sure, red tape should be
minimized where possible, but we must be careful about what we cut and how much
we cut. As Kaufman notes, efforts to eliminate red tape will ultimately fail because
“we would be appalled by the resurgence of evils and follies it currently prevents”
(1977, p. 97).
More recently, Bozeman (1993, 2000) has noted that a major flaw in most red tape
research is that the concept is too encompassing, Bozeman thus attempts to refine
2
Formalization has been defined and operationalized in several ways, but the term generally denotes the
extent to which rules, procedures, instructions, and communications within an organization are written
or codified (Hall, 1991).
618 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
red tape into several subdimensions. Bozeman defines “organizational red tape” as
rules, regulations, and procedures that remain in force and entail a compliance burden
for the organization, but are not effective in achieving their intended purpose. This is
distinguished from “stakeholder red tape,” defined as rules, regulations, and
procedures that entail a compliance burden but serve no object valued by a given
stakeholder group. Bozeman also distinguishes between “rule-inception red tape”
(rules that are dysfunctional at their origin) and “rule-evolved red tape” (rules that at
one time served legitimate purposes but have since evolved into red tape). Ruleinception red tape can occur when people creating the rule do not adequately
understand the problem the rule is intended to address. Rule-evolved red tape can
occur when the need for a rule no longer exists, yet people are still complying with
the rule.
Bozeman also provides a typology of red tape that involves its sources (internal and
external) and effects (also internal versus external). Red tape that originates inside
the organization and has external effects on clients or on other organizations is defined
as “ordinary red tape.” Internally generated red tape that affects those inside the
organization is called “intraorganizational red tape.” “External control red tape” is
red tape that is external to the organization but has internal organizational effects,
such as a rule being promulgated by a parent firm or oversight agency. Finally, “passthrough red tape” is generated externally and affects clients external to the
organization.
This typology suggests that the red tape clients experience (either ordinary or passthrough) could be quite different from that workers experience within an organization,
although Bozeman does not elaborate on the potentially differential nature of these
impacts. Bozeman (1993; 2000) also proposes various hypotheses regarding the
relationship between type of red tape and government ownership. For example, he
suggests that government ownership is positively related to ordinary red tape and
pass-through red tape but not intraorganizational red tape.
Empirical Studies of Red Tape
While the number of empirical studies on red tape has been steadily growing, it is
small in comparison to the many studies that have examined closely related constructs
such as formalization and rule intensity (Child, 1972; Hage and Aiken, 1967; Pugh et
al., 1968). In fact, several studies on red tape have used measures that are very similar
to scales used to measure formalization (for example, see Buchanan, 1975). This has
prompted concern among some scholars to draw explicit conceptual distinctions
between red tape and formalization (Bozeman and Scott, 1996).
Cumulatively, the empirical research has been limited mostly to sectoral comparisons
of red tape and has both challenged and reinforced common assertions. In one early
study, Buchanan (1975) found that managers in private organizations expressed greater
adherence and commitment to rules than did their public sector counterparts.
Bozeman and Rainey (1998) recently reported similar findings. Other studies (Baldwin,
1990; Lan and Rainey, 1992), however, have shown higher levels of formalization and
red tape perceived among public managers, and much of that is accounted for by the
presence of externally generated sources of formalization (for example, accountability
requirements imposed by government oversight agencies). External rules and laws
pertaining to personnel and procurement functions tend to be among the most
significant sources of red tape in government (Rainey, Pandey, and Bozeman, 1995).
Using a national sample of research and development labs, Bozeman, Reed, and
Scott (1992) employed a factor analysis that extracted four underlying contextual
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 619
dimensions of red tape: 1) funding for research; 2) approval of personnel decisions;
3) procurement of capital equipment; and 4) publication and release of research results.
The researchers found that the level of red tape within these laboratories was
influenced not only by the laboratory’s formal, legal status (public or private), but
also by the degree to which the laboratory was constrained by external political
authority, or “publicness” (Bozeman, 1987). Both of these variables were highly
influential in predicting a laboratory’s level of personnel and equipment-related red
tape, but were less influential in explaining other underlying dimensions of red tape.
In a survey of public and private managers, Rainey, Pandey, and Bozeman (1995)
found that public managers perceived higher levels of red tape than their private
sector counterparts, especially red tape associated with personnel procedures. In
addition, weak expectancies about extrinsic rewards, such as pay and promotion,
were related to higher perceived levels of red tape. The authors also found a relationship
between goal ambiguity and red tape that was independent of sectoral differences.
Managers who perceived high levels of goal ambiguity were more likely to initiate or
disseminate red tape than managers who perceived lower levels of goal ambiguity,
irrespective of the type of their organization.
While many empirical studies have operationalized red tape in terms of delays in
the performance of certain core organizational tasks, Pandey and Bretschneider (1997)
propose a unique measurement scheme based on statistical residuals obtained from
multiple regression models that use administrative delays as the dependent variable.
Pandey and Bretschneider suggest that the residuals obtained from regressing
administrative delays on region, size, and other variables represent delays that can
be ascribed solely to red tape. Examining the relationship between red tape and
managerial interests in new information technologies, the researchers found that
when managerial interest in new technologies is high and the level of red tape is high,
managers see the potential of these technologies as an effective means to ameliorate
red tape. On the other hand, if red tape is high but interest in technology is low, then
red tape is seen simply as a barrier to the adoption of new information technologies.
Despite previous research, several questions remain, in part because of the restrictive
use of methodologies employed (surveys) and populations studied (largely mid- and
upper-level managers). Accordingly, there is a need for additional studies that employ
a range of research methodologies, including case studies, surveys of non-managerial
personnel in different organizational and policy contexts, and field and laboratory
experiments. Of course, the choice of a particular research strategy requires careful
consideration of its advantages and disadvantages, as well as the overall purpose of
the study; but as Jick (1979) notes, theoretical progress is aided by the triangulation
of findings from a variety of research methods.
This study reported herein uses a laboratory experiment to assess how changes in
the level of red tape influence bureaucratic decisionmaking. One of the clear
advantages of experimental designs is their strength at indicating the presence of
causal relationships because they allow for the manipulation of variables of interest
while holding other factors constant (Berkowitz and Donnerstein, 1982). Experiments
help to rule out most of the major threats to internal validity and are thus considered
the “Cadillac” of research designs (Henshel, 1980). In addition, the use of an experiment
can help validate or qualify the findings obtained from surveys and case studies.
DATA AND PROCEDURES
The data from this study are based on a simulated training session for newly hired
caseworkers in a local public assistance agency. Subjects (graduate students and social
620 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
work practitioners) 3 were asked to review background case histories of four
hypothetical clients seeking public assistance. Subjects were then required to put
together a package of recommended benefits and services tailored to the needs of
each client. Those who agreed to participate in the study met in small groups, the
number, size, and time of which were dictated by the scheduling constraints of each
subject. Overall, 21 groups were formed. For the graduate student participants, group
meetings were held in a university campus conference room. For the practitioner
subjects, group meetings were held in a conference room on the premises of a county
social services agency.
Once each group was assembled, the participants were welcomed and informed
about their role in the study. Subjects were told that the researchers were serving as
a consultant for a local human services agency, charged with the task of developing a
set of prototype training modules for new employees. Subjects were told that their
role would be to assist in the development of this prototype by reviewing four case
files of clients seeking public assistance and recommending benefit and service levels
according to the needs of each client. Subjects were also informed that the clients
depicted in the case files were not actual clients, but rather, composite case files
based upon actual client histories.
Before beginning their review of the four case files, subjects were shown a slide
presentation about this local human services agency. The subjects were informed
that the slide presentation was similar to the one that newly hired employees were
shown during their initial training orientation and thus, this information would help
them get a better “feel” for what it would be like to work as a new employee.4 The
slide presentation included information about the agency’s mission, the types of
services provided, the number of clients served, client processing procedures, and
budgetary expenditures during the previous fiscal year.
Subjects then began their review of the case files, the order of which was completely
randomized.5 For each client, subjects read the background case history, filled out an
initial client evaluation form, and completed other supplemental forms consistent
with their evaluation of each client’s needs. After completing the study, subjects filled
out a post-experiment questionnaire. This instrument included questions designed
to serve as a validity check for the experimental treatment manipulations (independent
variables), as well as gauge subjects’ perceptions regarding the realism of the study.
At the conclusion of the protocol, subjects were debriefed and asked not to discuss
any aspects of the protocol with others yet to participate. For each group of
participants, total administration time averaged about 70 minutes.
3
One particular disadvantage that often accompanies the use of laboratory experiments is low external
validity. To some extent, this can be ameliorated by increasing the heterogeneity of the subjects employed.
Accordingly, we employed both students as well as practitioners as a way to deal with this shortcoming.
4
The extent to which subjects become engaged in the tasks of the experiment facilitates “experimental
realism”, a necessary condition for achieving internal validity. For a good overview, see Berkowitz and
Donnerstein (1982). We also attempted to enhance the level of both “mundane” and experimental realism
by ensuring that the client case histories, forms, and experimental tasks approached those actually found
in street-level bureaucracies and familiar to street-level practitioners. For a discussion surrounding the
tradeoff between mundane and experimental realism, see Bozeman and Scott (1993).
5
We randomized the presentation order using a complete counterbalancing strategy as a way to minimize
potential carryover effects (for example, fatigue, habituation) that are commonly associated with repeated
measures designs. With four case files, there are 4! or 24 possible order combinations. Because the study
employed 96 subjects, each of the 24 order combinations was assigned randomly to four different subjects, two in the high red tape treatment level and two in the low red tape treatment level (see Figure 1).
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 621
Experimental Treatments and Measures
Embedded within the experiment are two separate treatments or factors. The first
treatment, Red Tape, contains two levels—high and low—to which subjects were
randomly assigned. The two levels differed in terms of the procedural burden imposed
upon subjects as they processed each client case file. Subjects assigned to the high
red tape treatment level were required to fill out separate forms for each supplemental
benefit or service they recommended; each of the forms, moreover, required subjects
to provide specific narrative justification supporting their particular recommendation.
By contrast, subjects assigned to the low red tape treatment level were required to fill
out a simple checklist of benefits and services and indicate a corresponding dollar
amount where appropriate.6
Designing the red tape treatment required dealing with the same operationalization
problem that plagues much of the research on red tape: that is, how to make a clear
distinction between our operationalization and formalization. Clearly, there is a good
deal of overlap between the two constructs, and as Bozeman and Scott (1996) note,
several researchers have employed definitions of red tape that are virtually identical
to those used by researchers examining formalization. Still, it would be difficult to
argue that the operationalization of red tape used here is sufficiently discriminating
from formalization if the two red tape treatment levels differed only in terms of
procedural burdens.
Thus, also included in the operationalization scheme are different “cues” about the
internal administrative environment of the simulated local human services agency.
First, as part of the slide presentation about the agency, client-processing procedures
were contrasted between the two red tape treatment levels. In the high red tape
treatment, these procedures were depicted as very complex and cumbersome. In the
low red tape treatment, these procedures were depicted as relatively straightforward,
simplified, and streamlined. We also provided in the high red tape treatment
supplemental information about the agency, including a management report that
detailed productivity and error rates among agency employees, a memorandum from
the department head depicting strong concerns about recent slippages in quality, and
excerpts from the agency’s personnel manual describing specific rules and penalties
associated with dress codes, lunch breaks, arrival time, and sick leave. These cues,
designed to portray the agency as one that was “bound-up” by excessive and
unnecessary rules, were not presented to subjects assigned to the low red tape
treatment level.
This dual approach to operationalizing red tape—employing differences in
procedural burden and presenting contrasting information about the internal
administrative environment—would, in our view, create a sharper distinction between
red tape and formalization and lead to a greater perceived contrast between the low
and high red tape treatment levels. Unfortunately, this strategy also results in a more
diffuse operational definition of red tape. In other words, it is unclear whether any
observed effects of the red tape treatment can be attributed solely to differences in
procedural burdens, to the presence or absence of the particular environmental cues
employed, or to some combination of the two. While that is the inevitable tradeoff,
the authors believe it is an appropriate one in light of the formative stage of the
research. Moreover, it is worth noting that workers’ perceptions of red tape are usually
based upon both the general work climate, as well as specific procedures and tasks to
6
Information regarding all aspects of the experimental protocol may obtained from the authors on request.
622 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
which workers are assigned; in fact, it seems that the latter may well reinforce or
modify the effects of the former. Accordingly, the authors believe some benefit is to
be gained by incorporating both dimensions of red tape into the present study.
Naturally, an important strategy for future research would be to assess the degree to
which red tape and its effects are more a function of procedural elements (such as
red tape associated with documentation requirements and related procedural burdens)
vis-a-vis internal elements that comprise an organization’s culture (such as emphasis
on rule conformity).7
The second experimental treatment is a repeated measures variable that is
operationalized through the background case histories of two pairs of clients (one
male, one female). Within each pair the clients are depicted as having similar needs
and hence, are eligible for the same types of benefits and services, but the client
histories differ in their background circumstances so as to evoke different feelings of
compassion toward each client within the pair. Thus, for each pair, there is a “highcompassion” and “low-compassion” client.8 Together, these two treatments form a 2
x 2 repeated measure split plot factorial design, with two trials (Figure 1).
In addition to the two experimental treatments are several covariates. These were
obtained from a pre-experiment questionnaire and include: professional field of the
respondent (public administration or social work); years of education; gender; and
three personality measures—altruism; orientation toward bureaucratic norms; and
locus of control. The altruism measure is taken from Wrightsman (1991), a scale that
measures respondents’ attitudes along dimensions of unselfishness, sympathy, and
concern for others.9 The bureaucratic orientation scale (Gordon, 1968) is designed to
measure one’s adherence to norms embodied in bureaucratic organizations, such as
belief in the importance of rules and regulations.10 The locus of control measure11
(Paulhus, 1983) consists of three underlying dimensions of locus of control: personal
efficacy, interpersonal control, and sociopolitical control.12
Several of these attributes were selected because of their potential correlation with
the two experimental treatments. For example, it is possible that subjects’ responses
to the red tape treatment could be a function of one’s propensity to deviate from or
adhere to bureaucratic norms and standards. Alternatively, responses to the levels of
compassion exhibited in the four client case files could be tempered by subjects’
7
As a manipulation check, we included a question in the post-experiment questionnaire that queried
subjects on their perceptions of red tape in the agency. Using a Mann-Whitney U test, we found that the
high red tape subjects were much more likely to see the agency as having high levels of red tape when
compared to subjects assigned to the low red tape treatment level. This provides some evidence that the
high red tape subjects did, indeed, perceive the treatment as red tape and not simply as formalization.
8
Information contained in the background histories was first pre-tested on a panel of judges comprised of
public administration and social work faculty, as well as human services practitioners. As a manipulation
check for this treatment, we asked subjects in the post- experiment questionnaire to rank order each of the
four clients in terms of the degree to which they evoked feelings of compassion on the part of the respondent. Consistent with the responses provided by the pre-test panel of judges, all subjects consistently
ranked the high-compassion clients ahead of their low-compassion counterpart.
9
Robinson, Shaver, and Wrightsman (1991) report that this scale has a split-half reliability of 0.74 and
test–retest reliability of .83. No specific validity information is reported.
10
Gordon (1968) reports that the coefficient alpha reliability for this scale is 0.91. No other validity or
reliability information is reported.
11
Originating for Rotter’s social learning theory (Rotter, 1966), “locus of control” is a term that denotes an
expectancy concerning the connection between personal characteristics and experienced outcomes.
12
Robinson and colleagues (1991) report that the alpha reliabilities of the personal, interpersonal, and
sociopolitical subscales are 0.75, 0.77, and 0.81 respectively; combined, the Alpha reliability is 0.78. For all
three subscales, test–retest correlations average above 0.90 after four-week intervals. Robinson and colleagues (1991) also report that these subscales correlate well with other locus of control measures.
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 623
Client Case Files
(Two Pairs)
Red Tape
Treatment Level
S1,25
S2,26
S3,27
.
High
.
.
S24,48
FH
FL
MH
.
.
.
ML
FL
MH
FH
.
.
.
MH
MH
ML
FL
.
.
.
FL
ML
FH
ML
.
.
.
FH
S49,73
S50,74
S51,75
.
.
.
S72,96
FH
FL
MH
.
.
.
ML
FL
MH
FH
.
.
.
MH
MH
ML
FL
.
.
.
FL
ML
FH
ML
.
.
.
FH
Low
Sx,y indicates subjects
FH
FL
MH
ML
=
=
=
=
Female Client, High Compassion
Female Client, Low Compassion
Male Client, High Compassion
Male Client, Low Compassion
Figure 1. Repeated measures design using complete counterbalancing
general feelings of altruism. It is also possible that subjects’ decisions could be
influenced by their professional background; perhaps the social work subjects might
exhibit a tendency to provide more benefits and services to clients than the public
administration subjects because of differences stemming from professional
socialization processes.
The dependent variable is represented by two summative measures, both of which
are calculated according to a range of options available to the decisionmaker. The
first measure denotes the overall level of financial assistance recommended for each
client, while the second indicates the overall number of supplementary benefits and
services recommended. Table 1 shows how these two dependent variables were
calculated.
Subject Characteristics
Of the 96 subjects who participated in the actual experiment, 49 had prior professional
training or experience in public administration while 47 had a professional background
624 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
Table 1. Benefits and corresponding parameters.
Recurrent (Monthly Benefits)
Type of Service or Benefit
Range of Options
1.
Supplemental Food Allowance
(In addition to food stamps which had already
been calculated for each client)
($0 – $200)
2.
Clothing Allowance
($20 – $40)
3.
Exceptional Circumstances Supplemental Cash Assistance
(An option that increases the overall Basic Monthly Allowance)
($0 – $200)
Non-recurrent (One Time Only)
4.
Clothing Expense Voucher (for employment purposes)
($0 – $100)
5.
Moving Expense Voucher
($0 – $200)
6.
Special Supplemental Diet Allowance
($0 – $200)
7.
Furniture Requisition Voucher
($0 – $400)
8.
Day Care Voucher (Female Clients Only)
Yes/No
9.
Substance Abuse Counseling
Yes/No
10. Job Training/Employment Counseling
Yes/No
11. Medical/Psychological Screening
Yes/No
Other benefits (i.e., housing vouchers, food stamps) were already calculated for each subject
based upon formula/statutory criteria. These benefits did not vary within each pair of clients.
Calculation of Dependent Measures:
Dependent Variable I = Sum of 1–7 (dollar value)
Dependent Variable II = Number of benefits chosen from 1, 3, 4, 5, 6, 7, 8, 9, 10, 11
in social work. Table 2 reports means for age, education, work experience, and
personality attributes, presented by professional field. As the table shows, the social
work participants tended to be older and have less education and more work experience
than the public administration participants. Also of interest, though not shown in the
table, is the ratio between the male and female subjects. For the public administration
participants, males outnumbered females (28 versus 21) while for the social work
participants the pattern is reversed (29 to 18).
Given these differences, it was important to ensure that subject characteristics were
randomly distributed across the two red tape treatment levels, thereby enhancing the
likelihood that any observed differences in responses could be ascribed to the
experimental treatment manipulation. To test the effectiveness of the randomization,
several significance tests were employed to compare various demographic means of
subjects across the two red tape treatment levels (for example, age, level of education,
and locus of control scores), in hope of seeing no significant differences. This would
assure that the two groups were relatively similar in makeup and thus bolster
confidence that the randomization process achieved what it was intended to. In the
various means tests employed, no significant differences were seen in mean subject
characteristics, with one exception, suggesting that subject characteristics were
distributed randomly across the two red tape treatment levels.
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 625
Regression Analysis
To investigate the effects of red tape on subjects’ decision patterns, a regression analysis
was employed using the two experimental treatments as independent variables, along
with the control variables noted above. Both the low red tape treatment level and the
low compassion client are coded as 0, while the high red tape treatment and high
compassion client are coded as 1. Professional field is also coded as a dichotomous
variable, with 0 indicating subjects having a background in public administration
and 1 indicating subjects having a background in social work. The altruism and rule
orientation measures are scored in the positive direction while the locus of control
measure is keyed for scoring in the internal direction. The last attribute, gender, is
coded as 0 for male subjects and 1 for female subjects. Each of the regression tables
below report parameter estimates, standardized regression coefficients, corresponding
t statistics, and adjusted R2.13
Table 3A examines regression results for the variable denoting the total level of
assistance subjects provided to the four clients. It is important to recall that the clients
were depicted as having similar needs within each pair, but not across the two pairs.
This made the total “universe” of benefits available to the clients to be slightly different
for each pair. For example, one of the benefits—day care vouchers—was an option
available only for the female clients. Because the dependent variables were calibrated
differently depending upon the gender of the client, this necessitated running separate
regression analyses for each pair of clients. For the female clients, the results show
that about 25 percent of the overall variance in the dependent variable is explained
by the model; for the male clients, approximately 23 percent of the variance is
explained. For both sets of comparisons the two experimental treatment variables
were statistically significant. The high compassion clients received an average of about
$170 ([$246 + $93]/2) more in total benefits than those exhibiting lower levels of
Table 2. Mean age, level of education, work experience, and selected personality
attributes by professional field.
Variable
Age*
Public Admin (N=49)
Mean
SD
Social Work (N=47)
Mean
SD
T-Value
29.93
6.76
37.51
8.96
–4.69
Education*
(years - post high school)
6.58
2.23
5.02
1.38
4.14
Work Exp.*
(years - post high school)
4.59
5.85
11.77
8.91
–4.68
0.61
2.28
6.39
4.97
–7.37
–1.62
Human Service
Work Exp. (Yrs)*
Altruism Score
2.18
10.49
5.87
11.81
Locus of Control
34.80
16.82
34.34
16.30
0.13
Rule Orientation
24.57
6.90
26.47
6.22
–1.41
* p <0.001
13
Several regression diagnostics were employed, including the use of variance inflation factors to test for
multicollinearity and a series of Goldfield-Quandt tests to detect the presence of heteroscedasticity. These
tests suggested that neither condition was problematic.
626 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
Table 3A. Regression results testing the effects of red tape, compassion, and selected
covariates.
Dependent Variable: Total Dollar Value of Assistance Provided
I. Female Client Comparison (Adj. R2 = 0.25)
Independent
Variable
Red Tape
Compassion
Professional Field
Years of Education
Altruism
Locus of Control
Rule Orientation
Gender
Unstandardized
Coefficient
Standardized
Coefficient
–261.34
245.93
87.89
19.92
2.28
0.71
–2.21
11.81
–0.36
0.34
0.12
0.11
.07
0.03
–0.04
0.02
T-Value
–5.28***
5.35***
1.66*
1.53
1.03
0.48
–0.59
0.23
II. Male Client Comparison (Adj. R2 = 0.23)
Independent
Variable
Red Tape
Compassion
Professional Field
Years of Education
Altruism
Locus of Control
Rule Orientation
Gender
Unstandardized
Coefficient
Standardized
Coefficient
–175.07
92.80
57.93
14.76
1.74
0.11
2.12
11.81
–0.40
0.21
0.13
0.14
0.09
0.01
0.06
0.08
T-Value
–5.88***
3.35***
1.82*
1.88*
1.30
0.12
0.93
1.16
*p < 0.10
**p < 0.05
***p < 0.01
compassion. By contrast, an increase in the level of red tape was associated with an
average decrease of about $218 ([$261 + $175]/2) in total benefits. The data also show
that the social work participants provided an average of about $73 ([$88 + $58]/2)
more in total benefits than the public administration participants.
For the comparison of the female clients, the standardized regression coefficients
show that the two experimental treatments exhibited about the same influence on
subjects’ decisions, and that both were about three times as influential as the variable,
professional field. For the male clients, however, the red tape variable was the most
influential—about twice as influential as the client compassion variable and almost
three times as influential as the respondents’ professional field or level of education.
Interestingly, none of the personality attributes were statistically significant influences
on the level of assistance provided to either pair of clients.
The comparisons shown in Table 3B involve the total number of benefits and services
provided to the two pairs of clients. For both pairs the regression model explains
approximately 35 percent of the overall variance in the dependent variable. As with
the results shown in Table 3A, both of the experimental treatments were statistically
significant influences, although in this case the red tape factor was from three to four
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 627
Table 3B. Regression results testing the effects of red tape, compassion, and selected
covariates.
Dependent Variable: Total Number of Non-Recurrent Benefits and Services
I. Female Client Comparison (Adj. R2 = 0.35)
Independent
Variable
Red Tape
Compassion
Professional Field
Years of Education
Altruism
Locus of Control
Rule Orientation
Gender
Unstandardized
Coefficient
–2.23
0.85
–0.34
0.02
0.01
0.01
–0.01
–0.06
Standardized
Coefficient
–0.56
0.21
–0.01
0.02
0.05
0.04
–0.04
–0.02
T-Value
–8.92***
3.60***
–1.25
0.33
0.73
0.72
–0.56
–0.24
II. Male Client Comparison (Adj. R2 = 0.36)
Independent
Variable
Red Tape
Compassion
Professional Field
Years of Education
Altruism
Locus of Control
Rule Orientation
Gender
Unstandardized
Coefficient
–2.32
0.53
0.15
0.05
0.02
0.00
–0.01
0.49
Standardized
Coefficient
–0.61
0.14
0.04
0.05
0.09
0.03
–0.02
0.13
T-Value
–9.74***
2.40***
0.61
0.79
1.48
0.44
0.33
2.00**
*p < 0.10
**p < 0.05
***p < 0.01
times as influential as the client compassion variable. The only other significant
influence is gender, which occurs only with respect to the male client comparison.
One other finding of interest concerns the degree to which the two experimental
treatments reinforce or work against each other. This can be shown by examining average
levels of assistance provided to both pairs of clients across the two red tape treatment
levels. In Table 4, the average level of assistance provided to the high compassion female
client in the low red tape treatment is $1419.27, while the average level of assistance
provided to the low compassion female client in the high red tape setting is $907.21.
This difference of about $512 is quite large, especially when compared to the difference
in means between the low compassion/low red tape client versus the high compassion/
high red tape client ($20.21). A similar pattern can be seen in the diagonal contrasts for
the male clients, although the differences are not as pronounced.
DISCUSSION
The findings from this study underscore how differences in the level of red tape can
influence subjects’ decision patterns. Across all four client case files, an increase in
628 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
Table 4. Mean level of assistance provided by client and red tape treatment level.
High Compassion
Female
Level of
Red Tape
Low
High
Low Compassion
Female
Mean
SD
Mean
SD
1419.27
1203.77
301.41
298.31
1223.98
907.21
372.07
299.27
High Compassion
Male
Level of
Red Tape
Mean
Low
High
861.94
688.31
Low Compassion
Male
SD
Mean
SD
237.66
192.36
773.27
591.38
213.07
114.13
the level of red tape resulted in an average decrease in benefits of about 21 percent.
Breaking this down further, the high red tape subjects provided about 15 percent less
in benefits for the high compassion female client when compared to subjects in the
low red tape treatment group. This difference increased to 20 percent for the high
compassion male client, 24 percent for the low compassion male client, and 26 percent
for the low compassion female client. One possible implication is that clients, having
similar needs and similar eligibility thresholds, may end up being treated quite
differentially solely as a function of the level of red tape involved in the benefit
determination process.
At the same time, other factors associated with the decision context can moderate
or exacerbate the tendencies that stem from high levels of red tape. For example,
despite the fact that the clients within each pair of cases were depicted as having
similar needs, subjects consistently recommended higher benefits for the high
compassion client. Service providers were willing to engage in “cut-through” behavior
for those clients perceived as sympathetic but were less inclined to go the extra mile
for those perceived as less deserving.14 As some research suggests, it is not uncommon
for service providers and other professionals to vary assessments on the basis of the
moral “worth” of clientele, as well as other factors extraneous to the actual conditions
or task at hand (Roth, 1972). From the clients’ perspective the implications are clear:
how they present themselves may well determine the level of benefit obtained,
especially under conditions of high red tape.
The findings also showed that one’s professional background and training may
play a role in the level of benefits provided. As the findings indicate, the social work
participants tended to provide slightly more in total benefits than the public
administration participants. Perhaps these findings reflect differences in the types of
norms emphasized within the two professions or the social work participants’ greater
14
This pattern persisted even under conditions of high red tape. As one reviewer pointed out, this finding
provides evidence that the study participants were highly engaged in the tasks of the experiment, thereby
reflecting a high level of experimental realism. This not only facilitates internal validity, it also reduces the
degree of artificiality that often accompanies laboratory experiments.
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 629
familiarity with the intricacies of the client intake process. But in comparison to the
two experimental treatment manipulations, the statistical influence of this variable
was small.
One of the more surprising findings was the lack of statistical significance among
the individual personality variables (altruism, locus of control, or rule orientation).
This was unexpected in light of the growing research that has demonstrated a
relationship between various personality characteristics and red tape (Bozeman and
Rainey, 1998; Pandey, 1995; Pandey and Kingsley, forthcoming). Much of this work
traces its lineage to the earlier scholarship of Alvin Gouldner (1952), who, as noted,
stated that red tape is a function of both objective and subjective elements. Victor
Thompson (1961) and Robert Merton (1940) have contributed to this line of reasoning
by holding that personal characteristics of certain bureaucrats make them prefer
elaborate rules and regulations. In this vein, Bozeman and Rainey (1998) examined
attributes such as alienation and powerlessness and found that managers who scored
higher on these measures indicated a greater preference for rules. Pandey and Kingsley
(forthcoming) similarly found a positive relationship between alienation and
perceptions of red tape among both public and private managers.
These are important contributions, to be sure, in part because they suggest that
much more work is needed to understand better the interplay between personality
and structural attributes in shaping bureaucratic behavior. One of the more pressing
needs, for example, is a better understanding of how individual attributes actually
lead to differential responses to red tape. In other words, simply knowing that an
individual perceives higher levels of red tape or indicates a greater preference for
rules says very little about his or her actual behavior under high or low levels of red
tape. While some may be more alienated than others, does the level of alienation
have any significant bearing on cut-through behavior? Related to this, do higher
perceptions of red tape lead someone to exhibit greater tolerance or intolerance for
red tape?
In the methodological realm of the randomized experiment—where the ability to
infer causality is greatest—essentially no such relationship was found between
individual attributes and the level of benefits recommended. Under both red tape
conditions, attributes involving altruism, locus of control, and bureaucratic orientation
(a proxy for rule preference) paled in comparison to the role of external factors
contained within the four client case histories. These findings thus seem to support
Guy’s (1985) general assertion that factors such as the exigencies of the work situation
and the immediacy of the task at hand are more influential determinants of
bureaucratic behavior than individual characteristics. If nothing else, more research
seems to be needed to assess in clearer terms the causal interplay between both
individual and structural attributes in determining cut-through behavior.
One last finding of note relates to how red tape may affect organizational outputs
or outcomes. Traditionally, structural theorists claim that one of the benefits of
formalization is the enhanced likelihood of achieving greater levels of consistency,
predictability, and reliability in terms of organizational outputs (Hall, 1991; Scott,
1992). Higher levels of formalization are intended to limit individual discretion
and thus minimize the variance in outputs that is often accompanied by such
discretion. The findings from this study, however, suggest that higher levels of
formalization, when perceived as red tape, might actually lead to less consistency
in organizational outputs. This can be seen by calculating the difference in benefits
between the low and high compassion clients in each of the two red tape treatment
levels. As Table 4 indicates, the spread between the high and low compassion clients
was actually greater in the high red tape treatment when compared to the low red
tape treatment level. Thus, it seems that the tendency to provide differential
630 / The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation
responses to clients can be exacerbated by increases in the number and level of
procedural requirements associated with client processing. These findings
underscore the need for street-level managers to consider carefully the present level
of formalization within their organization and be aware of how marginal increases
in formalization can create unintended outcomes such as greater variance in terms
of how clients are processed.
CONCLUSION
Red tape is an organizational problem that touches people at all levels of government,
from managers at the very highest echelons to service providers who labor in relative
obscurity at the street level. Yet, a disproportionate share of scholarly energy, both in
terms of empirical and prescriptive work, has been devoted to the study of high-level
managers (Allison, 1983; Ban, 1995; Lewis, 1980; Riccucci, 1995). Despite the fact
that the combined impact of the day-to-day activities of street-level workers probably
has a larger impact, how service providers deal with red tape remains an understudied
topic. The authors believe that a better understanding of the propensity to engage in
“cut-through” behavior at the street level can provide an important theoretical basis
for building a more responsive bureaucracy.
So what is it that motivates cut-through behavior? This study, taken together with
findings from other studies, points to the importance of situational factors and thus
underscores the need to consider several different categories of variables that may be
influential in motivating or constraining cut-through behavior. Such factors may
include the nature of the decision or the policy context, organizational mission and
culture, and various structural attributes such as the level of centralization. Ban (1995),
in fact, shows how managers implement certain mechanisms to cope with external
bureaucratic constraints that are guided, in part, by the particularistic cultures of
their organization. As an example, the open and informal culture at the Environmental
Protection Agency (EPA), along with its need for highly trained, technical personnel,
creates conditions that lead EPA managers to fight hard to overcome, avoid, or use to
their best advantage personnel rules when compared with managers working in other
federal agencies, such as the Department of Agriculture. These findings reinforce the
need for future research to consider such factors as a basis for developing a better
understanding of how individuals respond under varying levels and types of red tape.
Implicit throughout this study has been the view that cut-through behavior is an
activity that should be encouraged. Several streams in the public management
literature bid us to “smash” or “break-through” bureaucracy (Barzelay, 1992; Osborne
and Plastrik, 1997), perhaps without a full appreciation of their concomitant
implications. Making bureaucracy more responsive, more client-oriented, more
customer-friendly, etc., are laudable objectives, to be sure; but at the same time we
should remain mindful of the concerns voiced by scholars such as Thompson (1975)
and Davis (1969) who warn what can happen when democratic institutions allow
their workers to willy nilly apply the rules in manners they choose—even if done in
the name of cut-through behavior. Thompson (1975), for example, questions whether
the interests of democracy are served when the de facto formation of public policy
becomes captive to the personal whims or caprices of the individual service provider.
In a different vein, scholars such as Chisholm (1995) and Landau (1969, 1991) argue
compellingly as to why red tape is not only justified, but even beneficial to public
organizations. Certain forms of procedural redundancies are necessary because they
ensure overall “system” reliability and even organizational survival. In such cases,
engaging in cut-through behavior undercuts the fundamental logics behind these
The Influence of Red Tape on Bureaucratic Behavior: An Experimental Simulation / 631
built-in redundancies and thus may create outcomes detrimental to the organization.
These concerns, then lead to the obvious questions, “Under what conditions should
cut-through behavior be viewed as legitimate and when should cut-through behavior
be discouraged?” While such questions are beyond the scope of this study, speculations
would seem to be better informed through the accumulation of evidence that examines
empirically the degree to which people engage in cut-through behavior. The authors
agree with the views of scholars like Herbert Kaufman and Barry Bozeman that red
tape cannot, nor should it be, eliminated in its entirety, but it may be possible to
moderate some of the more deleterious effects of red tape through systematic
advancements in research. Ultimately, more conscientious and systematic efforts to
enhance both research and theory should lead not only to a better understanding of
red tape, they should also enhance our ability to provide better prescriptions for
dealing with red tape. In the words of the familiar prayer, such efforts should enable
us to “accept the red tape we cannot change,” to “change the red tape that we can,”
and, if we are especially fortunate, to gain some “wisdom to know the difference.”
This would be a good outcome indeed.
PATRICK G. SCOTT is Associate Professor, Department of Political Science, Southwest
Missouri State University.
SANJAY K. PANDEY is Assistant Professor, Graduate Department of Public Policy and
Administration, Rutgers University.
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