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Performance and Management in the Public Sector: Testing a Model of Relative Risk Aversion

Nicholson-Crotty, Sean Nicholson-Crotty, Jill Fernandez, Sergio

PUBLIC ADMINISTRATION REVIEW; JUL-AUG 2017, 77 4, p603 12p.

WILEY

00333352

15406210

10.1111/puar.12619

Journal

English

000404376300018

Copyright (c) Clarivate Analytics Web of Science

Social Sciences Citation Index

Performance and Management in the Public Sector: Testing a Model of

Relative Risk Aversion.

Research has demonstrated that management influences the performance of public organizations, but almost no research has explored how the success or failure of a public organization influences the decisions of those who manage it. Arguing that many decisions by public managers are analogous to risky choice, the authors use a well‐validated model of relative risk aversion to understand how such choices are influenced by managers’ perceptions of organizational performance. They theorize that managers will be less likely to encourage innovation or give discretion to employees when they are just reaching their goals relative to other performance conditions. Analyses of responses to the 2011 and 2013 Federal Employee Viewpoint Surveys provide considerable support for these assertions. The findings have significant implications for our understanding of the relationship between management and performance in public organizations.

Related Content: Stanton (PAR July/August 2017)

Practitioner Points

Perceptions of performance influence the likelihood that public managers will engage in risk‐taking behavior.

Public managers are less likely to take risks as performance begins to meet expectations than when performance falls short of or exceeds expectations.

The willingness of public managers to embrace organizational change, such as process innovations or employee empowerment practices, is likely a function of current organizational performance.

Over the past several decades, a large and growing literature has demonstrated quite convincingly that management matters for the performance of public organizations. It has shown that the decisions public

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managers make—including whether to collaborate with stakeholders in the environment, create green rather than red tape within their organizations, and empower employees to innovate, among others—have a significant impact on the success of public organizations and programs (see, e.g., DeHart‐Davis [ 18] ; Fernandez and Moldogaziev [ 22] ; Meier and O'Toole [ 48] ). In many ways, the relationship between management and performance undergirds the modern administrative state and the systems that define it (Moynihan and Pandey [ 57] ).

Scholars typically treat the relationship between management and performance as nonreciprocal, assuming that one influences the other but that the inverse is not true. As a result, almost no work has explored how the success or failure of a public organization influences the decisions of those who manage it. This is a potentially significant oversight because if performance is in fact endogenous to management, this could cause us to substantially overestimate the importance of the latter. In other words, if public managers in high‐performing organizations make systematically different decisions than those in poor‐performing organizations, we might attribute organizational success to those choices when causality is actually running in the other direction.

Fortunately, very recent research has begun to address this shortcoming by theorizing about the impact of performance on managerial behavior in public organizations (Meier, Favero, and Zhu [ 46] ). While acknowledging the importance of that work, we will, for a variety of reasons, suggest an alternative approach to understanding the relationship between performance and management. Specifically, we use a relative risk model from the private management literature in order to understand how several major types of decisions made by public managers are influenced by the performance of their organizations. This is a well‐validated approach to decision making that suggests that risk tolerance is a function of performance relative to the decision maker's goals or aspirations. Many managerial behaviors advocated by modern management theories —including the encouragement of innovativeness and entrepreneurial behavior, employee empowerment, and decentralization of decision making authority—impose potential costs while having uncertain outcomes and therefore can be conceived of as risky choice. Drawing on relative risk theory, we develop specific hypotheses about the performance conditions under which managers are most likely to make these types of choices.

We test these hypotheses in analyses of responses to the 2011 and 2013 Federal Employee Viewpoint Surveys. In order to deal with endogeneity and help alleviate common source bias, we predict an individual employee's reports of managerial decisions regarding the encouragement of innovation, empowerment practices, and delegation of decision‐making authority in 2013 with average assessments of performance by managers within that employee's department in 2011. In an additional analysis, we test directly for the impact of a manager's performance assessment on his or her own reported innovativeness. Across six different dependent variables measuring managerial decisions, and in the presence of numerous control variables and fixed effects, the results are remarkably consistent with the theoretical prediction that key choices made by public managers are a function of organizational performance and relative risk tolerance. We conclude with a discussion of the implications for public management research.

Performance and Decision Making in the Public Management Literature As noted earlier, there is really not much to review when it comes to studies that have used organizational performance to predict how public managers will make decisions. Work in the private sector has frequently explored the ways in which performance feedback influences firms’ willingness to adopt behaviors either to address deficiency or to further leverage success (see, e.g., Chen [ 14] ; Iyer and Miller [ 32] ; Miller and Chen [ 51] ). However, application of this behavioral theory (see Cyert and March [ 17] ) to public organizations has been very rare. A notable exception is Salge ([ 62] ), who finds that negative performance feedback leads organizations to search for solutions while slack resources encourage innovativeness in a sample of English

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public hospitals. In a related article, Nielsen ([ 58] ) finds that negative performance information induces Danish school principals to reorder the multiple goals that their organizations are asked to pursue, emphasizing areas in which they are doing particularly poorly.

Despite these exceptions, attention to the impact of performance on managerial decisions in public organizations has been limited. Recognizing this significant oversight, Meier, Favero, and Zhu ([ 46] ) build a theory that imagines performance as a key driver of decision making by public managers. Specifically, the authors take a Bayesian approach in which the distance between current performance and the manager's prior regarding acceptable performance shapes the choices they make. They are clear that priors could be formed in a variety of ways but offer the intuitive expectation that information about previous performance and the performance of similar organizations is likely used by managers to update their beliefs about acceptable levels of current performance.

The theory suggests that “positive performance gaps,” where current performance falls below acceptable levels, should induce managers to be more innovative, seek opportunities by networking with those in the organizational environment, and centralize operations. They hypothesize that the functional form of these relationships will likely be quadratic, with managerial behaviors of the kind just described becoming more aggressive as the performance gap grows. Finally, the authors suggest that the theory can be extended to accommodate multiple goals, different levels of hierarchy, and other realities faced by public organizations.

Meier, Favero, and Zhu's approach is promising, particularly in its careful consideration of how managers decide what level of performance they expect from their organizations, and its attention to the impact of performance on management is long overdue. It is also, however, untested empirically. Additionally, the theory does not deal adequately with conditions when current performance exceeds the prior regarding an acceptable level. The authors acknowledge that this type of “negative performance gap” is likely to have an important impact on managerial behavior and speculate that it might “be translated into both additional resources and autonomy” (Meier, Favero, and Zhu [ 46] , 1232). They do not, however, generate precise expectations about the impact of exceeding performance expectations on managerial decision making. This is particularly important if, as noted earlier, we are concerned about overestimating the impact of management in high‐ performing organizations.

As a final challenge, there are some potential inconsistencies in the expectations offered by the theory. For example, the authors rely heavily on Miles et al.'s ([ 50] ) concept of prospector versus defender strategies to identify the decisions managers may make under different performance conditions. They suggest that poor performance should motivate managers to encourage innovation and expand contacts with the environment, which Miles et al. classify as prospector strategies. Meier, Favero, and Zhu also suggest that poor performance will cause managers to centralize authority, but Miles et al. argue that seeking “strict control of the organization” is a defender strategy. More importantly, they suggest that defenders and prospectors are essentially opposites of one another and that each has a “high degree of consistency among its solutions” to organizational problems. Meier, Favero, and Zhu do not offer sufficient explanation as to why they expect poor performance to cause such inconsistent reactions among managers. These issues will likely be worked out in future iterations of the theory and subsequent empirical tests, but for now, they suggest that it might be profitable to explore other lenses for examining the relationship between performance and management.

An Alternative Approach to Modeling Performance and Management We suggest that models of relative risk aversion can be used to understand decisions that increase uncertainty for public managers. We will return in the next section to which tenets of modern management theory we

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believe fit in this category. Before that, however, it is important to acknowledge the advancements made in the study of risky choice in the public sector. Although some research continues to assert that public organizations have characteristics that can impede risk‐taking or entrepreneurial behaviors (see, e.g., Morris and Jones [ 54] ; Townsend [ 66] ), a growing number of studies have demonstrated that risk‐taking behavior is present and predictable in public organizations. In an early contribution, Bozeman and Kingsley ([ 10] ) test and refute the assertion that public managers are inherently more risk averse than their private sector counterparts. Subsequent research has demonstrated that hierarchy and red tape are negatively correlated with risk taking among public managers and employee–supervisor trust is positively associated (Nyhan [ 59] ; Turaga and Bozeman 2005).

One key difference between these studies on public management risk taking and the model we use is that they rely on an absolute rather than a relative risk‐aversion perspective. Absolute and relative risk approaches both assume that the utility of an outcome is a function of perceived risk. Each suggests that decision makers are risk averse when utility for an outcome diminishes as uncertainty about obtaining it increases and risk seeking when utility increases with uncertainty. However, the key feature of absolute risk tolerance is that the functional form of the relationship between utility and risk is fixed for each individual. In other words, each person is either risk averse or risk seeking. Under that assumption, performance cannot have any impact on propensity for risk taking.

Work on individual risk taking in other contexts, including private firms, has long rejected the idea of fixed risk tolerance in favor of relative risk aversion (see, e.g., Bromiley and Curley [ 12] ). In these models, the level of utility for an outcome is still a function of perceived risk, but the same person can be risk loving and risk averse depending on his or her performance relative to expectations. Perhaps the most well known of these approaches is prospect theory. Kahneman and Tversky ([ 34] ) offer a model of risky choice, which suggests that the weights assigned to potential gains and losses change depending on where decision makers feel they are relative to their desired goal. Specifically, the theory predicts that decision makers will be risk averse when in a domain of gain but risk seeking in a domain of loss. In other words, they will be more risk averse when they are “winning” rather than “losing” relative to some preestablished goal. Numerous studies have confirmed that individual risk preferences vary based on the reference point between gains and losses (see Tversky and Kahneman [ 68] for a review).

Research has extended these findings from individuals to the behavior of organizations and managers within them (e.g., Bowman [ 7] ; Bromiley [ 11] ; Fiegenbaum and Thomas [ 24] ). These studies argue that organizations have variable risk preferences based on their proximity to a preestablished reference point. More specifically, they expect that managers will engage in riskier behavior when performance and resources are below aspirational levels but become more risk averse as they begin to realize aspirations. Key insight into the matter emerged from early efforts to develop a behavioral theory of the firm. March and Simon ([ 43] ) argue that the rate of innovation in organizations increases as existing organizational structures and practices prove to be inadequate and actual performance lags behind expectations (see also Levitt and March [ 39] ). Elaborating on the notion that necessity is the mother of invention, Cyert and March ([ 17] ) argue that failure induces search, which often leads to the adoption of innovative solutions. They call these innovations “problem‐oriented innovations,” which are directly linked to a problem, in contrast to slack innovations, which are remotely related to a problem and are much easier to justify when resources are abundant and rules for allocating resources are relaxed.

March and Simon's ([ 43] ) and Cyert and March's ([ 17] ) research underscores the influence of performance and aspirations on managerial behavior, particularly exposing the organization to risk through innovation. In a

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similar vein, research on organizational learning has emphasized the impact of performance feedback on managerial decisions to engage in organizational change. Manns and March ([ 40] ) predict and find that poor financial performance, or financial adversity, leads university departments to adopt changes in their curriculum in order to improve their financial standing. Lant, Milliken, and Batra ([ 36] ) find that past failures increase the likelihood that firms will change their strategic orientation, although external attributions of failure weaken this relationship. Greve ([ 25] ) finds that the probability of major organizational change decreases as performance increases. Importantly, as performance meets and begins to exceed historical and social aspiration levels, the probability of major organizational change declines even more sharply, highlighting the behavioral consequences of performance relative to aspirations. Ironically, transformation efforts in response to performance shortfalls and other pressures from the external environment expose organizations to “liability of newness,” increasing the probability of failure in the future (Amburgey, Kelly, and Barnett [ 2] ). Even when change does not result in the demise of the organization, it has a disruptive effect that imposes significant costs on the organization (Barnett and Carroll [ 3] for a review of the evidence).

In a synthesis of existing work, March and Shapira ([ 41] , [ 42] ) offer a model of relative risk preference that suggests that a firm not facing bankruptcy but performing below its goals will begin to take greater risks in an attempt to rise to the aspirational or target level. As the firm approaches or rises just above the level of performance or resources it hopes to achieve, however, managers will once again become risk averse, overweighting the probability that risk taking could drop the organization back below an acceptable level of performance. Finally, the model hypothesizes that organizations will become less risk averse if they find themselves doing better than they hoped and may even become risk seeking at very high levels of success.[ 1] The model's assertion that organizations will become more tolerant of risk once aspirations are far exceeded build on the large literature on slack resources and innovation. That research, generally speaking, asserts that slack resources permit firms to more safely experiment with new strategies (Hambrick and Snow [ 27] ; Moses [ 55] ) and allows slack search, or the pursuit of projects that may not be immediately justifiable but have high potential (Levinthal and March [ 38] ).

March and Shapira use an empirically validated approach to understanding the relationship between performance and risk in the private sector (see Miller and Chen [ 51] ). Authors have also validated very similar aspirational models of the relationship between relative performance and risk taking in studies of private firms (see, e.g., Greve [ 25] , [ 26] ).

Applying the Model to Public Management Decisions A relative risk model can help us understand the relationship between performance and managerial decisions under conditions of risk. The foundational assumption of this approach is, of course, that the decisions of public managers are related in some way to performance. We believe that this should be a relatively uncontroversial proposition, however, both because of the ubiquity of performance measurement and management regimes in the public sector (Poister [ 60] ; Sanger [ 63] ) and the consistent findings that public managers go to great lengths to avoid poor performance assessments (see, e.g., Heinrich [ 30] ; Van der Waldt [ 69] ).

If we accept the premise that public managers are concerned about performance, then the next step in an application of the relative risk approach to the public sector is demonstrating that managerial decisions in that context are analogous to risky choice. Obviously, not every decision public managers make fits this criterion, but we believe that many do. More importantly, we believe that many of the managerial behaviors championed by the New Public Management (NPM) and other modern public management theories are best conceived of as risky choice.

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At its core, NPM involves an effort to infuse public management with ideas and practices from the private sector (Haynes [ 29] ). When contrasted with “traditional” public administration, these emphasize increased innovativeness and entrepreneurship on the part of managers, along with structures to incentivize such behavior. They encourage increased discretion throughout the organization and the empowerment of employees to make changes that improve services. Finally, modern management prescriptions suggest that managers need to focus some energy outward, collaborating and networking with those in the organizational environment, in order to improve the performance of their organizations and programs (see, e.g., Meier and O'Toole [ 47] ; Milward and Provan [ 52] ; Moore [ 53] ).

Risky choice is typically defined as behavior requiring investment or imposing potential costs when outcomes are uncertain. Thus, anything that may increase costs and has uncertainty surrounding benefits is a risk, and we believe that many modern prescriptions for public managers fit this definition. Indeed, scholars argue explicitly that innovating is risk taking because it involves a novel way of doing something that may or may not work (Cohen and Eimicke [ 15] ; DiIulio et al. [ 19] ; Feeney and DeHart‐Davis [ 21] ).[ 2] It is a well‐supported assumption that adopting a new way of doing something introduces uncertainty regarding outcomes and therefore is inherently risky (see, e.g., Massa and Testa [ 44] ; Mellahi and Wilkinson [ 49] ; Thomas and Mueller [ 65] ; Vargas‐Hernández [ 70] ; Vargas‐Hernández, Noruzi, and Sariolghalam [ 71] ).

Similarly, giving authority to another party creates both adverse selection and moral hazard problems because the true preferences of the agent are difficult for the principal to observe and information asymmetries make it hard for the latter to know the quality or efficiency of production by the former (see Bawn [ 4] ; Bendor, Glazer, and Hammond [ 5] ; Epstein and O'Halloran [ 20] ). These issues significantly increase uncertainty regarding outcomes. Finally, choosing to create or engage service delivery networks or collaborating with those in the organizational environment can create risk. Collaboration and interorganizational networks require significant resources, make management more challenging, introduce their own agency problems when contractors are used, and are often unsuccessful at producing desired outcomes (see Huxham and Vangen [ 31] ; Romzek and Johnston [ 61] ).[ 3]

Obviously, this is not an exhaustive list of managerial activities that are analogous to risky choice. It does demonstrate, however, that several decisions central to modern public management are likely correlated with risk tolerance. Because of that correlation, the model of relative risk outlined earlier should be able to generate accurate hypotheses about the relationship between organizational performance and those decisions. The theory predicts a quadratic relationship like the one presented in figure [NaN] , where managers are more risk averse when their organizations are just reaching performance goals relative to conditions where they are performing considerably better or worse than that level. In terms of the decisions mentioned above, this suggests the following:

Hypothesis 1: Public managers will promote more innovative activity when they believe their organizations are failing to meet or exceeding performance goals relative to when they are just meeting those goals.

Hypothesis 2: Public managers will empower employees with greater discretion when they believe their organizations are failing to meet or exceeding performance goals relative to when they are just meeting those goals.

The theory also suggests that managers will network and collaborate less when they are just achieving their goals relative to other performance conditions, but we do not have data to explicitly test this. Thus, we do not offer it as a formal hypothesis.

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The expectations outlined here may seem counterintuitive because they suggest that managers may act similarly at different levels of performance, but they are consistent with some observations of behavior in public organizations. For example, some research finds that managers may become more innovative when their organizations are under stress and when they are performing very well. The literature on organizational turnaround in the public sector suggests that organizational decline can often stimulate managerial innovation (see, e.g., Boyne [ 8] ; Jas and Skelcher [ 33] ; McKinley, Latham, and Braun [ 45] ), at least when there is a recognition of poor performance and sufficient managerial capacity.[ 4] These assertions are consistent with Miles et al.'s ([ 50] ) expectation that private sector managers would seek to be more innovative, and to more effectively exploit the environment, when their organizations are performing poorly.

Alternatively, many authors suggest that managers whose organizations are performing better than expected are the ones that are most likely to innovate and take risks. Berry ([ 6] ) finds a positive relationship between organizational slack and strategic innovation. Similarly, Boyne and Walker ([ 9] ) argue that a prospector strategy, which they define including “innovation and rapid organizational responses to new circumstances,” is most likely to be undertaken by public managers in organizations with slack resources. Finally, Carpenter ([ 13] ) demonstrates that agencies can undertake behaviors that are politically risky when they have used high performance in other activities to build support among clients.

A relative risk model can help us understand the relationship between performance and managerial decisions under conditions of risk.

Data, Variables, and Methods Testing these hypotheses requires data on both managerial perceptions of performance and the decisions that managers make regarding the promotion of innovation and awarding of discretion to employees. We find these data in responses to the 2011 and 2013 Federal Employee Viewpoint Surveys (FEVS). The U.S. Office of Personnel Management administered the 2013 FEVS to 781,047 employees in 81 federal government agencies, including cabinet‐level departments and independent agencies of all sizes. A total of 376,577 employees completed the survey, for a government‐wide response rate of approximately 48 percent in 2013. The 2011 FEVS was administered to a more limited sample and elicited more than 266,000 responses, for a response rate of 49.5 percent. The 81 agencies that participated in the two surveys make up approximately 97 percent of the federal executive branch workforce. The Office of Personnel Management uses a stratified sampling approach that generates representative samples for the federal government as a whole, for echelons within the federal government (nonsupervisor, supervisor, and executive), and for each of the individual departments and agencies participating in the survey. The surveys were administered electronically to employees who were notified by e‐mail; multiple follow‐up e‐mails were sent to increase response rates.

We are interested in examining the degree to which perceived performance influences managerial decisions, but these variables are likely endogenous to one another. We use time ordering in order to deal with the potential for reciprocal causation. Specifically, we use the average performance assessment of managers within a unit in 2011 to predict individual nonmanagers’ responses in 2013 regarding the degree to which their unit encourages innovation and creativity and empowers them to make important decisions regarding work processes.[ 5]

In order to have some confidence that we are matching employees and managers in a meaningful way, we need the smallest unit of aggregation possible, which in the 2011 FEVS is one tier below the agency level. There are 284 such units identified in the data; they include organizations such as the Employee Benefits Security Administration within the Department of Labor and the Agricultural Marketing Service within the

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Department of Agriculture. Every response in the FEVS is associated with an agency, such as the Department of Transportation or the Department of Health and Human Services. In 2013, about 82 percent of respondents identified a unit that the FEVS designates as one level below the agency, leaving approximately 310,000 total usable responses. When we match with those suborganizations identified by respondents in the 2011 data, we are left with approximately 229,000 responses. As noted earlier, we average the responses of supervisors within each unit and predict responses of individual employees in each. Taking managers out of the sample leaves us with 167,392 employees, which is reduced to an analysis sample of between 111,000 and 115,000 because of missing data. Nonetheless, there are not significant differences between this sample and the full sample of nonsupervisors in the 2013 FEVS.

Dependent Variables Our dependent variables in subsequent analyses measure the degree to which employees suggest that their organizations or managers create a culture of innovativeness and empower employees with adequate discretion. We take a multiple measures approach, modeling two distinct variables for the first concept and three for the second. For the concept of innovativeness culture, we first model encouragement to innovate, which is measured using the FEVS indicator “I feel encouraged to come up with new and better ways of doing things.” This measure represents the affective state or experience of feeling on the part of the respondent that makes him or her more inclined to innovate (Fernandez and Moldogaziev [ 22] ). The second dependent variable, rewarding innovation, is measured using the 2013 FEVS indicator “Creativity and innovation are rewarded.” This measure represents the degree to which the respondent feels his or her superiors in the agency reward efforts to generate innovative ideas and/or implement them. Available response categories range from 1 for “strongly disagree” to 5 for “strongly agree” for these measures.

We use three variables to capture the concept of employee empowerment. The first is personal empowerment, measured using the FEVS 2013 indicator “Employees have a feeling of personal empowerment with respect to work processes.” This variable captures management's propensity to share power to shape work processes with subordinates. The second variable in this set, leadership opportunities, is measured with the FEVS indicator “My supervisor/team leader provides me with opportunities to demonstrate my leadership skills.” This measure represents the extent to which employees exercise power or the authority to act. The final variable measuring empowerment is involvement in decisions, which we capture with the question “How satisfied are you with your involvement in decisions that affect your work?” This last indicator indicates the extent to which employees are allowed to influence decisions that affect them and their work. Combined, the three indicators represent elements of employee empowerment as a managerial approach (Fernandez and Moldogaziev [ 22] ). Again, the response categories for each of these range from 1 for “strongly disagree” to 5 for “strongly agree.”

Independent Variables Our key independent variable captures managers’ perceptions of performance. Specifically, we use the 2011 FEVS indicator “My agency is successful at accomplishing its mission.” Although there are obviously multiple goals that public organizations and the people within them might pursue, we believe that the accomplishment of mission is likely to be prominent among them. Available answers again range from 1 for “strongly disagree” to 5 for “strongly agree.” The reference or aspiration point is described in the literature as a point that is “psychologically neutral” between winning and losing (Kameda and Davis [ 35] ) or “the smallest outcome that would be deemed satisfactory by the decision maker” (Schneider [ 64] ). We assume, therefore, that each respondent is at their aspirational threshold somewhere between the answers “neither agree or disagree” and “agree.”

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Previous research using relative performance to predict behavior has devoted significant attention to the ways in which managers might set goals or aspirations for performance. Much of this work suggests that the aspirational threshold is determined through a comparison of current performance with previous performance, the performance of peers, or some combination of historical and social factors (Cyert and March [ 17] ; Haveman [ 28] ; Levinthal and March [ 38] ; Meier, Favero, and Zhu [ 46] ; Salge [ 62] ). The assumption is that managers can use these data as a decision heuristic to generate some prediction of future performance, which is assumed to become the aspiration or goal (see Greve [ 25] ).

Although we cannot observe these factors directly, our measure of perceived performance, which asks about the accomplishment of mission, likely captures both of these historical and social factors. In other words, managers’ responses are likely determined in part by how their agency did in the past and how peer agencies are doing. Additionally, because we directly measure responses regarding perceived performance, we do not have to infer managers’ perceptions of performance. We believe this is an improvement over previous studies because the theoretical model suggests that these perceptions, rather than actual performance, influence risk tolerance.

We average the responses to the question regarding mission accomplishment across all supervisors within a unit (one level below the agency level) and use the mean value to predict individual nonsupervisor responses within a unit to the questions discussed earlier. As noted in figure [NaN] , relative risk theory predicts a concave quadratic function, where managers are less willing to tolerate the risks associated with innovativeness and employee discretion when just achieving goals relative to conditions when their organization performing worse or better than that aspiration. In order to model this function, we also include the average managerial performance rating squared in each model. In order to provide support for our hypotheses, the linear term should be negatively signed, while the squared term should be positive.

Control Variables The models discussed here also include a variety of variables that control for alternative explanations for our dependent variables. The first set of these reflect individual characteristics that may influence the degree to which someone perceives themselves as innovative or believes that their organization is supportive of such activities. These individual‐level controls include respondent gender, age, minority status, pay category, and tenure in the federal service. Studies suggest that all of these characteristics may influence perceptions of innovativeness, entrepreneurial behavior, and autonomy, although the consistency and direction of the impact for these measures are mixed.

We also include a measure of job satisfaction as a control variable, assuming that this is likely to be correlated with an employee's attitudes about the degree to which they are encouraged to innovate or their feelings about empowerment. Specifically, we include responses to the question “Considering everything, how satisfied are you with your job?” This measure should correlate positively with the dependent variables.

Estimator All models discussed here are weighted least squares regressions using sample weights provided in the FEVS. Each model also includes fixed effects at the agency level to account for unmeasured organizational characteristics, such as policies related to employee empowerment, that might influence our dependent variables. Finally, standard errors in our primary models are clustered at one level below the agency level to account for the fact that employees within units may be more likely to answer similarly to one another. We use weighted ordinary least squares rather than an ordered probit estimator in our primary analyses because this allows for a more intuitive plot of predicted responses for the purpose of hypothesis testing.[ 6] However, to

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ensure that the findings are not biased by this choice of estimator, we present ordered probit models for each dependent variable in the appendix (table [NaN] ).

Findings Primary Models The findings from our primary analyses are presented in tables [NaN] and [NaN] . The first contains the models of encouragement to innovate (column 1) and rewarding innovation (column 2), which capture the degree to which employees feel that managers incentivize innovation. First, it is important to point out that the models perform quite well, explaining between 38 percent and 40 percent of the variation in more than 150,000 individual responses.

Relationship between Managers’ Perceptions of Performance and Employee Reports of Innovative Culture

Encouraged to InnovateRewarded for Innovation Accomplish mission (2011) −4.769 −6.657

(−2.18) (−2.34) Accomplish mission (2011) squared 0.630 0.888

(2.28) (2.47) Female 0.0644 0.0154

(5.20) (1.02) Minority 0.0143 0.0343

(1.41) (3.39) Pay category −0.0311 −0.0508

(−2.30) (−3.03) Tenure −0.0130 −0.0327

(−1.90) (−4.39) Job satisfaction 0.636 0.585

(101.07) (95.33) Intercept 10.10 13.27

(2.34) (2.36) N 111,774 108,773 R .33 .31 1 Notes: Models include sample weights and agency fixed effects; standard errors are clustered at the subagency level. T‐statistics in parentheses.

2 * p < .05;

3 p < .01;

4 p < .001.

Relationship between Managerial Perceptions of Performance and Employee Reports of Empowerment/Discretion

Personal EmpowermentLeadership OpportunitiesInvolvement in Decisions Accomplish mission (2011) −6.600 (−3.39) −6.932 (−2.47) −4.426 (−2.42) Accomplish mission (2011) squared 0.872 (3.56) 0.886 (2.48) 0.570 (2.47) Female −0.0480 −0.0331 −0.0158

(−4.07) (−2.66) (−1.56) Minority 0.109 −0.0378 0.0130

2

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(9.61) (−3.00) (1.29) Pay category −0.0181 −0.0473 −0.0159

(−1.38) (−3.47) (−1.16) Tenure −0.0312 −0.0418 −0.0308

(−3.48) (−5.71) (−6.26) Job satisfaction 0.606 0.572 0.658

(95.74) (97.62) (113.10) Intercept 13.36 15.21 9.528

(3.44) (2.75) (2.62) N 110,477 112,546 113,235 R .35 .29 .42

5 Notes: Models include sample weights and agency fixed effects; standard errors are clustered at the subagency level. T‐statistics in parentheses.

6 p < .05;

7 p < .01;

8 p < .001.

Before turning to the key independent variables, we can quickly note the impact of the controls. The measure of satisfaction is positively correlated with both dependent variables. The results also suggest that nonsupervisors in a higher pay category and those with longer tenure both feel less encouraged to innovate and less certain that creativity and innovation will be rewarded. Identifying as a minority is positively and significantly related to both dependent variables, although it fails to reach traditional levels of statistical significance in the model of rewarding innovation. Female employees feel that managers are more likely to reward innovation and creativity, but they are not significantly more likely to feel that they are encouraged to innovate.

Female employees feel that managers are more likely to reward innovation and creativity, but they are not significantly more likely to feel that they are encouraged to innovate.

The real variables of interest are the measure of average managers’ assessments of performance within a unit and the squared term. Both are highly statistically significant in both models. The negative coefficients on the first terms coupled with the positive coefficients on the squared terms suggest a concave quadratic function in which values decrease until an inflection point and then increase after that point. These results are easier to conceptualize graphically. Figure [NaN] shows the predicted quadratic form of the relationship between performance and the two innovation variables, with the associated 95 percent confidence intervals.

We turn now to table [NaN] , which presents the models of personal empowerment, leadership opportunities, and involvement in decisions, which capture the degree of empowerment and decision‐making discretion that employees believe managers of their organizations provide. These models also perform well, explaining 35 percent, 29 percent, and 42 percent of the variation in employee perceptions. As with the models of innovation, employee satisfaction is strongly and positively correlated with all three dependent variables. Female respondents are consistently less likely to report that they feel empowered, have sufficient leadership opportunities, or are adequately involved in decisions affecting their work. The other control variables perform relatively inconsistently across the three models.

2

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The key variables of interest, including managers’ assessment of performance and assessment of performance squared, are again significant and in the expected direction in all models. As in the case of the innovativeness culture models, signs on the two terms suggest a concave quadratic function. Again the relationship between performance and employee assessments is easier to present graphically, which we do in figure [NaN] .

An Additional Analysis The analyses presented here provide considerable evidence in support of a relative risk approach to the relationship between organizational performance and managerial decision making. This section will provide an additional analysis focusing on individual managers that is designed to increase confidence in those results.

As noted earlier, we believe that using aggregate manager assessments of performance calculated in 2011 to predict individual employee assessments in 2013 is a good approach because it establishes time order between the independent and dependent variables and helps overcome the common source bias problem. However, the findings discussed earlier are more convincing if we can show a correlation between an individual manager's perceptions of performance and statements about his or her own behavior. We restrict the sample for this analysis to the approximately 62,000 FEVS respondents who identified themselves as supervisors in 2013. We acknowledge that such a design cannot deal with issues of endogeneity and common method bias, and thus we suggest that these results only be interpreted as supplementary to the findings discussed earlier.

There is only one item in the FEVS that reflects a response by managers about their own behavior, and we use that question as the dependent variable in this analysis. Specifically, we model responses to the item “I am constantly looking for ways to do my job better.” This measure captures the behavioral aspect of innovativeness. Such behavior may include searching for ideas generated and implemented elsewhere, developing new ideas through experimentation, vicarious learning and other behavior, and refashioning the ideas of others to achieve a better fit with extant conditions (Altshuler and Zegans [ 1] ; Fernandez and Wise [ 23] ).

We again use responses to the item “My agency is successful at accomplishing its mission” to create the independent variable. In this analysis, however, we create individual indicators for different response categories. We create a single measure titled below threshold, from responses of “strongly disagree” and “disagree,” because there are relatively few responses in the former category.[ 7] We use “neither agree or disagree” responses as the threshold where managers do not feel they are doing overly well or overly poorly. Finally, we create an indicator titled above threshold using the “agree” response category. We use “strongly agree” as the excluded category. Based on the relative risk approach, we expect that the coefficients on these indicators will form a U‐shaped pattern that matches figure [NaN] , where managers are least likely to innovate when they are just reaching performance goals, relative to other conditions.

The model includes controls for the manager's gender, minority status, pay category, federal tenure, and satisfaction with his or her job. It also includes sample weights and fixed effects at the agency level. This reduces the analyzed sample to 51,970, but is important to control for unmeasured characteristics that may influence innovativeness. Standard errors are again clustered at one level below the agency level.

The results from the analysis of individual managers are presented in table [NaN] . The model is highly significant and explains a reasonable amount of the variation in individual manager response. Female and minority bureaucrats, along with those who were more satisfied with their job and in a higher pay category,

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report more personal innovation. After controlling for those factors, the amount of time in the federal service is negatively correlated with the dependent variable.

Relationship between Individual Managers’ Perceptions of Performance and Their Reports of Personal Innovativeness

Personal Innovation Below threshold −0.275

(−12.75) Aspirational threshold −0.344

(−23.58) Above threshold −0.260

(−34.92) Female 0.0665

(9.60) Minority 0.0486

(4.77) Pay category 0.00738

(0.91) Tenure −0.0554

(−10.13) Job satisfaction 0.138

(15.83) Intercept 4.173

(118.24) N 51,970

9 Notes: Models include sample weights and agency fixed effects; standard errors are clustered at the subagency level. T‐statistics in parentheses.

10 * p < .05;

11 p < .01;

12 p < .001.

The key independent variables are the indicators of managerial performance assessment. The impacts of those dummy variables relative to our theoretical expectations are most easily assessed visually. Figure [NaN] graphs those coefficients, with associated 95 percent confidence intervals. Beginning at the right side of the figure, the plot suggests that managers who just agree, rather than strongly agree, that their organization is meeting its goals report significantly less personal innovation. Moving left across the x‐axis, reports of personal innovativeness drop significantly for those managers responding “neither agree nor disagree” to the statement about the agency accomplishing its mission. This represents the lowest point in reported innovativeness. When we move to managers who disagree or strongly disagree with the statement about agency performance, the coefficient becomes significantly less negative, indicating that managers are more likely to report personal innovativeness at that performance condition.

Discussion The results presented here strongly support our expectations that managers in public organizations become more risk averse when they are just accomplishing their goals relative to higher and lower performance

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conditions. The findings presented in table and figure [NaN] confirm that managers are less likely to foster innovation and entrepreneurial behavior in their organizations when they are just meeting performance aspirations. Relative risk approaches suggest that this is what we should expect because managers are more likely to overweight losses, and the probability of backsliding, when they are just realizing acceptable levels of performance. These results suggest that a relative risk approach might offer some theoretical clarity to previous, somewhat counterintuitive observations that public managers are more likely to seek out innovative solutions both when their organizations are in decline (Jas and Skelcher [ 33] ) and when they are flush with high performance (Boyne and Walker [ 9] ).

The findings presented in table and figure [NaN] support our expectations that managers will be more risk averse, and thus less likely to cede discretion to employees, when they are just meeting performance goals. They also appear less likely to give leadership opportunities to employees or to create an environment in which subordinates feel they have an adequate voice when their agencies are just meeting expectations relative to performing at either a higher or a lower level. Again, this is what we would expect given the predictions of relative risk theory.

Finally, the findings from the analysis of individual‐level managers, presented in table and figure [NaN] , strongly support our theoretical expectations regarding managerial behavior at the aspirational threshold, when they feel their organizations are just reaching or just about to reach their goals. The correlation between individual managers’ assessments of performance and their reported innovativeness form a U‐shaped pattern, similar to the concave quadratic function revealed in analyses using average manager attitudes about performance to predict employee reports about managerial behavior. Moreover, the inflection points, where relative risk theory suggests that managers are most risk averse and least willing to make risky decisions, are quite similar in both analyses. This provides confirmation of the results reported here in a different sample and at a different unit of analysis.

Conclusion The relationship between performance and managerial decision making in public organizations has gone essentially unexplored until very recently. In order to address this gap, we propose that relative risk aversion theories can help us understand when managers make decisions that impose potential costs but have uncertain payoffs—in other words, when they make decisions that are analogous to risky choice. Empirical analyses of responses from the 2011 and 2013 Federal Employee Viewpoint Surveys illustrate the value of such theories for understanding and predicting when public managers will take risks.

These results have significant implications for our understanding of public management. A large and growing literature suggests that differences in performance across public organizations can be attributed to the actions of public managers. Our findings suggest the degree to which “management matters” could be misestimated in this work. If public managers do more to encourage innovation or empower employees when they are in organizations that are already performing highly, then researchers could find artificially large effects for these behaviors when they use them to predict performance in a sample of such organizations. Our results suggest that managers in low‐performing organizations will also be more willing to delegate discretion to employees and to encourage innovation. In a cross‐sectional study, this could lead to the conclusion that these management activities reduce performance, when in fact the low levels of performance are causing the observed management behavior.

Our results also imply that the effectiveness of recent public sector reforms designed to incentivize innovation and entrepreneurial behavior, such as performance pay and employee empowerment, likely depend in part on

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the existing level of organizational performance. These reforms are typically designed to increase the benefits or decrease the costs of innovation, creativity, and risk taking. Our results suggest that such reforms may be most effective in organizations that are far exceeding or falling far short of their performance goals because those are the organizational contexts in which public managers will be most willing to take risks and, therefore, most likely to embrace such reforms.

The effectiveness of recent public sector reforms designed to incentivize innovation and entrepreneurial behavior, such as performance pay and employee empowerment, likely depend in part on the existing level of organizational performance.

Obviously, these conclusions are tentative and need to be confirmed in subsequent research. At the very least, however, our results suggest that studies of public entrepreneurship and the organizational characteristics that contribute to it must take account of the relationship between goal accomplishment and risk tolerance. More generally, they suggest that performance matters for management.

Appendix Table A1 Results from Models Estimated Using Ordered Probit Regression

EncourageRewardedEmpowermentLeadershipInvolvement Accomplish mission (2011) −5.440 −7.528 −8.069 −7.980 −6.323

(2.294) (3.147) (2.235) (3.140) (−1.95) Accomplish mission (2011) squared 0.718 1.003 1.066 1.021 0.820

(0.290) (0.399) (0.281) (0.399) (2.01) Female 0.0695 0.0199 −0.0547 −0.0273 −0.0375

(0.0136) (0.0169) (0.0138) (0.0142) (−2.11) Minority 0.0154 0.0365 0.126 −0.0340 0.0148

(0.0107) (0.0109) (0.0122) (0.0143) (1.30) Pay category −0.0327 −0.0564 −0.0214 −0.0500 −0.0133

(0.0147) (0.0187) (0.0152) (0.0151) (−0.72) Tenure −0.0181 −0.0384 −0.0391 −0.0518 −0.0409

(0.00785) (0.00844) (0.0105) (0.00868) (−5.82) Job satisfaction 0.690 0.662 0.714 0.618 0.827

(0.00913) (0.00727) (0.00609) (0.00879) (81.99) N 111,774 108,773 110,477 112,546 113,235 Footnotes 1 The model also suggests that managers will become risk averse when facing bankruptcy, but because public organizations do not face organizational death in the same way as private firms, we focus here on the other expectations offered by the model.

2 See also studies that separate concepts of entrepreneurship, innovation, and risk taking (e.g., Covin and Slevin 16; Morris and Jones 54).

3 However, it is important to note literature that suggests that networks and collaboration may help organizations manage uncertainty, and by extension risk, under certain conditions (see, e.g., Moynihan 56).

4 See Levine (37) for the argument that managers may also engage in retrenchment during periods of decline.

5 Creating our independent and dependent variables using responses from different groups within an organization in different years also helps overcome the common source bias problem. It is important to

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acknowledge that it may still exist, however, because of shared experiences by managers and employees within the same unit.

6 Ordinary least squares allows us to show one plot of the predicted category into which each respondent falls on each dependent variable across the range of the performance measure rather than the separately plotting the conditional probability of being in each category.

7 Results do not change substantially if we create different indicators for each response category. “Strongly disagree” is not statistically distinct from “disagree” in the coefficient plot.

8 Related Content: Stanton (PAR July/August 2017)

References Altshuler, Alan A., and Marc D. Zegans. 1997. Innovation and Public Management: Notes from the State House and City Hall. In Innovation in American Government: Challenges, Opportunities, and Dilemmas, edited by Alan A. Altshuler, and Marc D. Zegens, 68 – 80. Washington, DC : Brookings Institution.

Amburgey, Terry L., Dawn Kelly, and William P. Barnett. 1993. Resetting the Clock: The Dynamics of Organizational Change and Failure. Administrative Science Quarterly 38 ( 1 ): 51 – 73.

Barnett, William, and Glenn Carroll. 1995. Modeling Internal Organizational Change. Annual Review of Sociology 21 : 217 – 36.

Bawn, Kathleen. 1995. Political Control versus Expertise: Congressional Choices about Administrative Procedures. American Political Science Review 89 ( 1 ): 62 – 73.

Bendor, Jonathan, Amihai Glazer, and Thomas Hammond. 2001. Theories of Delegation in Political Science. Annual Review of Political Science 4 : 235 – 69.

Berry, Anthony J. 1994. Spanning Traditional Boundaries: Organization and Control of Embedded Operations. Leadership and Organization Development Journal 15 ( 7 ): 4 – 10.

Bowman, Edward. 1982. Risk Seeking by Troubled Firms. Sloan Management Review 23 ( 4 ): 33 – 42.

Boyne, George A. 2004. A “3Rs” Strategy for Public Service Turnaround: Retrenchment, Repositioning and Reorganization. Public Money and Management 24 ( 2 ): 97 – 103.

9 Boyne, George A., and Richard M. Walker. 2004. Strategy Content and Public Service Organizations. Journal of Public Administration Research and Theory 14 ( 2 ): 231 – 52.

10 Bozeman, Barry, and Gordon Kingsley. 1998. Risk Culture in Public and Private Organizations. Public Administration Review 58 ( 2 ): 109 – 18.

11 Bromiley, Philip. 1991. Testing a Causal Model of Corporate Risk Taking and Performance. Academy of Management Journal 34 ( 1 ): 37 – 59.

12 Bromiley, Philip, and Shawn Curley. 1992. Individual Differences in Risk Taking. In Risk‐Taking Behavior, edited by J. Frank Yates, 87 – 132. Chichester, UK : Wiley.

7/19/2021 Roadrunner Search Discovery Service

https://eds.a.ebscohost.com/eds/delivery?sid=4ecb0120-79db-47cc-ae30-f2627ec8909b%40sdc-v-sessmgr03&vid=2&ReturnUrl=https%3a%2f%2f… 17/21

13 Carpenter, Daniel P. 2001. The Forging of Bureaucratic Autonomy: Reputation, Networks, and Policy Innovation in Executive Agencies. Princeton, NJ : Princeton University Press.

14 Chen, Wei‐Ru. 2008. Determinants of Firms’ Backward‐ and Forward‐Looking R&D Search Behavior. Organization Science 19 ( 4 ): 609 – 22.

15 Cohen, Steven, and William Eimicke. 1998. The Use of Citizen Surveys in Measuring Agency Performance: The Case of the New York City Department of Parks and Recreation. Paper presented at the Annual Meeting of the American Society for Public Administration, Seattle, WA, May 9–13.

16 Covin, Jeffrey G., and Dennis P. Slevin. 1991. A Conceptual Model of Entrepreneurship as Firm Behavior. Entrepreneurship Theory and Practice 16 ( 1 ): 7 – 25.

17 Cyert, Richard M., and James G. March. 1963. A Behavioral Theory of the Firm. Englewood Cliffs, NJ : Wiley.

18 DeHart‐Davis, Leisha. 2009. Green Tape and Public Employee Rule Abidance: Why Organizational Rule Attributes Matter. Public Administration Review 69 ( 5 ): 901 – 10.

19 DiIulio, John J., Jr., Geoffrey P. Alpert, Mark H. Moore, George F. Cole, Joan Petersilia, Charles H. Logan, and James Q. Wilson. 1993. Performance Measures for the Criminal Justice System. Discussion paper, Bureau of Justice Statistics–Princeton University Study Group on Criminal Justice Performance Measures. http://www.bjs.gov/content/pub/pdf/pmcjs.pdf [accessed July 18, 2016].

20 Epstein, David, and Sharyn O'Halloran. 1999. Asymmetric Information, Delegation, and the Structure of Policy‐Making. Journal of Theoretical Politics 11 ( 1 ): 37 – 56.

21 Feeney, Mary K., and Leisha DeHart‐Davis. 2009. Bureaucracy and Public Employee Behavior a Case of Local Government. Review of Public Personnel Administration 29 ( 4 ): 311 – 26.

22 Fernandez, Sergio, and Tima Moldogaziev. 2013. Employee Empowerment, Employee Attitudes, and Performance: Testing a Causal Model. Public Administration Review 73 ( 3 ): 490 – 506.

23 Fernandez, Sergio, and Lois R. Wise. 2010. An Exploration of Why Public Organizations “Ingest” Innovations. Public Administration 88 ( 4 ): 979 – 98.

24 Fiegenbaum, Avi, and Howard Thomas. 1988. Attitudes toward Risk and the Risk‐Return Paradox: Prospect Theory Explanations. Academy of Management Journal 31 ( 1 ): 85 – 106.

25 Greve, Henrich R. 1998. Performance, Aspirations, and Risky Organizational Change. Administrative Science Quarterly 43 ( 1 ): 58 – 86.

26 Greve, Henrich R. 2003. A Behavioral Theory of R&D Expenditures and Innovations: Evidence from Shipbuilding. Academy of Management Journal 46 ( 6 ): 685 – 702.

27 Hambrick, Donald C., and Charles C. Snow. 1977. A Contextual Model of Strategic Decision Making in Organizations. Academy of Management Proceedings 1977 : 109 – 12.

28 Haveman, Heather A. 1993. Follow the Leader: Mimetic Isomorphism and Entry into New Markets. Administrative Science Quarterly 38 ( 4 ): 593 – 627.

7/19/2021 Roadrunner Search Discovery Service

https://eds.a.ebscohost.com/eds/delivery?sid=4ecb0120-79db-47cc-ae30-f2627ec8909b%40sdc-v-sessmgr03&vid=2&ReturnUrl=https%3a%2f%2f… 18/21

29 Haynes, Philip. 2003. Managing Complexity in the Public Services. New York : Routledge.

30 Heinrich, Carolyn J. 2002. Outcomes‐Based Performance Management in the Public Sector: Implications for Government Accountability and Effectiveness. Public Administration Review 62 ( 6 ): 712 – 25.

31 Huxham, Chris, and Siv Vangen. 2013. Managing to Collaborate: The Theory and Practice of Collaborative Advantage. New York : Routledge.

32 Iyer, Dinesh, and Kent Miller. 2008. Performance Feedback, Slack, and the Timing of Acquisitions. Academy of Management Journal 51 ( 4 ): 808 – 22.

33 Jas, Pauline, and Chris Skelcher. 2005. Performance Decline and Turnaround in Public Organizations: A Theoretical and Empirical Analysis. British Journal of Management 16 ( 3 ): 195 – 210.

34 Kahneman, Daniel, and Amos Tversky. 1979. Prospect Theory: An Analysis of Decision under Risk. Econometrica: Journal of the Econometric Society 47 ( 2 ): 263 – 91.

35 Kameda, Tatsuya, and James Davis. 1990. The Function of the Reference Point in Individual and Group Risk Decision Making. Organizational Behavior and Human Decision Processes 46 ( 1 ): 55 – 76.

36 Lant, Theresa K., Frances J. Milliken, and Bipin Batra. 1992. The Role of Managerial Learning and Interpretation in Strategic Persistence and Reorientation: An Empirical Exploration. Strategic Management Journal 13 ( 8 ): 585 – 608.

37 Levine, Robert J. 1978. The Role of Assessment of Risk‐Benefit Criteria in the Determination of the Appropriateness of Research Involving Human Subjects. In The Belmont Report: Ethical Principles and Guidelines for the Protection of Human Subjects of Research, appendix, vol. II. Washington, DC : National Commission on the Protection of Humans Subjects of Biomedical and Behavioral Research. https://videocast.nih.gov/pdf/ohrp_appendix_belmont_report_vol_1.pdf [accessed July 18, 2016].

38 Levinthal, Daniel A., and James G. March. 1981. A Model of Adaptive Organizational Search. Journal of Economic Behavior and Organization 2 ( 4 ): 307 – 33.

39 Levitt, Barbara, and James G. March. 1988. Organizational Learning. Annual Review of Sociology 14 : 319 – 40.

40 Manns, Curtis L., and James G. March. 1978. Financial Adversity: Internal Competition and Curriculum Change in a University. Administrative Science Quarterly 23 ( 4 ): 541 – 52.

41 March, James G., and Zur Shapira. 1987. Managerial Perspectives on Risk and Risk Taking. Management Science 33 ( 11 ): 1404 – 18.

42 March, James G., and Zur Shapira. 1992. Variable Risk Preferences and the Focus of Attention. Psychological Review 99 ( 1 ): 172 – 83.

43 March, James G., and Herbert A. Simon. 1958. Organizations. New York : Wiley.

44 Massa, Silvia, and Stefania Testa. 2008. Innovation and SMEs: Misaligned Perspectives and Goals among Entrepreneurs, Academics, and Policy Makers. Technovation 28 ( 7 ): 393 – 407.

7/19/2021 Roadrunner Search Discovery Service

https://eds.a.ebscohost.com/eds/delivery?sid=4ecb0120-79db-47cc-ae30-f2627ec8909b%40sdc-v-sessmgr03&vid=2&ReturnUrl=https%3a%2f%2f… 19/21

45 McKinley, William, Scott Latham, and Michael Braun. 2014. Organizational Decline and Innovation: Turnarounds and Downward Spirals. Academy of Management Review 39 ( 1 ): 88 – 110.

46 Meier, Kenneth M., Nathan Favero, and Ling Zhu. 2015. Performance Gaps and Managerial Decisions: A Bayesian Decision Theory of Managerial Action. Journal of Public Administration Research and Theory 25 ( 4 ): 1221 – 46.

47 Meier, Kenneth J., and Laurence J. O'Toole, Jr. 2001. Managerial Strategies and Behavior in Networks: A Model with Evidence from U.S. Public Education. Journal of Public Administration Research and Theory 11 ( 3 ): 271 – 94.

48 Meier, Kenneth J., and Laurence J. O'Toole, Jr. 2002. Public Management and Organizational Performance: The Effect of Managerial Quality. Journal of Policy Analysis and Management 21 ( 4 ): 629 – 43.

49 Mellahi, Kamel, and Adrian Wilkinson. 2008. A Study of the Association between Downsizing and Innovation Determinants. International Journal of Innovation Management 12 ( 4 ): 677 – 98.

50 Miles, Raymond E., Charles C. Snow, Alan D. Meyer, and Henry J. Coleman, Jr. 1978. Organizational Strategy, Structure, and Process. Academy of Management Review 3 ( 3 ): 546 – 62.

51 Miller, Kent D., and Wie‐Ru Chen. 2004. Variable Organizational Risk Preferences: Tests of the March‐ Shapira Model. Academy of Management Journal 47 ( 1 ): 105 – 15.

52 Milward, H. Brinton, and Keith G. Provan. 2006. A Manager's Guide to Choosing and Using Collaborative Networks. Washington, DC : IBM Center for the Business of Government.

53 Moore, Mark H. 1995. Creating Public Value: Strategic Management in Government. Cambridge, MA : Harvard University Press.

54 Morris, Michael H., and Foard F. Jones. 1999. Entrepreneurship in Established Organizations: The Case of the Public Sector. Entrepreneurship Theory and Practice 24 ( 1 ): 71 – 91.

55 Moses, O. Douglas. 1992. Organizational Slack and Risk‐Taking Behaviour: Tests of Product Pricing Strategy. Journal of Organizational Change Management 5 ( 3 ): 38 – 54.

56 Moynihan, Donald P. 2008. Learning under Uncertainty: Networks in Crisis Management. Public Administration Review 68 ( 2 ): 350 – 65.

57 Moynihan, Donald P., and Sanjay K. Pandey. 2005. Testing How Management Matters in an Era of Government by Performance Management. Journal of Public Administration Research and Theory 15 ( 3 ): 421 – 39.

58 Nielsen, Poul A. 2014. Learning from Performance Feedback: Performance Information, Aspiration Levels, and Managerial Priorities. Public Administration 92 ( 1 ): 142 – 60.

59 Nyhan, Ronald C. 2000. Changing the Paradigm: Trust and Its Role in Public Sector Organizations. American Review of Public Administration 30 ( 1 ): 87 – 109.

60 Poister, Theodore H. 2010. The Future of Strategic Planning in the Public Sector: Linking Strategic Management and Performance. Special issue, Public Administration Review 70 : s246 – 54.

7/19/2021 Roadrunner Search Discovery Service

https://eds.a.ebscohost.com/eds/delivery?sid=4ecb0120-79db-47cc-ae30-f2627ec8909b%40sdc-v-sessmgr03&vid=2&ReturnUrl=https%3a%2f%2f… 20/21

61 Romzek, Barbara S., and Jocelyn M. Johnston. 2005. State Social Services Contracting: Exploring the Determinants of Effective Contract Accountability. Public Administration Review 65 ( 4 ): 436 – 49.

62 Salge, Torsten O. 2011. A Behavioral Model of Innovative Search: Evidence from Public Hospital Services. Journal of Public Administration Research and Theory 21 ( 1 ): 181 – 210.

63 Sanger, Mary B. 2013. Does Measuring Performance Lead to Better Performance? Journal of Policy Analysis and Management 32 ( 1 ): 185 – 203.

64 Schneider, Sandra L. 1992. Framing and Conflict: Aspiration Level Contingency, the Status Quo, and Current Theories of Risky Choice. Journal of Experimental Psychology: Learning, Memory, and Cognition 18 ( 5 ): 1040 – 57.

65 Thomas, Anisya S., and Stephen L. Mueller. 2000. A Case for Comparative Entrepreneurship: Assessing the Relevance of Culture. Journal of International Business Studies 31 ( 2 ): 287 – 301.

66 Townsend, William. 2013. Innovation and the Perception of Risk in the Public Sector. International Journal of Organizational Innovation 5 ( 3 ): 21 – 34.

67 Turaga, Rama Mohan R., and Barry Bozeman. 2005. Red Tape and Public Managers’ Decision Making. American Review of Public Administration 35 ( 4 ): 363 – 379.

68 Tversky, Amos, and Daniel Kahneman. 1991. Loss Aversion in Riskless Choice: A Reference‐Dependent Model. Quarterly Journal of Economics 106 ( 4 ): 1039 – 61.

69 Van der Waldt, Gerritt. 2004. Managing Performance in the Public Sector: Concepts, Considerations and Challenges. Johannesburg, South Africa : Juta and Company.

70 Vargas‐Hernández, José G. 2011. Modeling Risk and Innovation Management. Journal of Competitiveness Studies 19 ( 3–4 ): 45 – 57.

71 Vargas‐Hernández, José G., Mohammad Reza Noruzi, and Narges Sariolghalam. 2010. Risk or Innovation: Which One Is Far More Preferable in Innovation Projects? International Journal of Marketing Studies 2 ( 1 ): 233 – 44.

Graph: Theoretical Relationship between Performance and Risk Tolerance

Graph: Plots of Relationship between Performance and Managerial Choices Regarding Innovation

Graph: Plots of Relationship between Performance and Managerial Choices Regarding Discretion and Empowerment

Graph: Plot of Impacts of Different Levels of Perceived Performance on Managers’ Reports of Personal Innovativeness

~~~~~~~~ By Sean Nicholson‐Crotty; Jill Nicholson‐Crotty and Sergio Fernandez

Sean Nicholson‐Crotty is professor in the School of Public and Environmental Affairs at Indiana University, Bloomington. His research focuses on the management of public organizations, intergovernmental relations,

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and the diffusion of policy innovations among governments. E‐mail:

Jill Nicholson‐Crotty is associate professor in the School of Public and Environmental Affairs at Indiana University, Bloomington. Her research focuses on the management of public and nonprofit organizations as well as on the role of race, gender, and representation on the outcomes of public programs. E‐mail:

Sergio Fernandez is associate professor in the School of Public and Environmental Affairs at Indiana University, Bloomington, and visiting professor in the Department of Public Management and Governance at the University of Johannesburg, South Africa. His research focuses on organizational behavior in the public sector, government contracting and procurement, and representative bureaucracy. E‐mail:

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