How Does Government Size and Structure Respond Empirically to Changes in its Organisational Environment?

Does government size and structure adapt to changes in government’s organisational environment (particularly to uncertainty and complexity) as predicted by organisational theory? We find – using a range of statistical analyses – support for each of the major theories of organisation adaptation (the contingency-based view, resource-based view, and the rational choice view). We find that both government size and structure change – holding other factors constant – for changes in the uncertainty and complexity of governments’ organisational environments. We find seven clusters of governments which adapt their organisational sizes differently in response to changes in the uncertainty and complexity of their organisational environments – and four clusters of governments with differing preferences for the way they adapt governmental structures. We also use the available data to divide governments according to the extent to which they adapt their organisational size and structure reactively (after changes occur in their organisational environment), contemporaneously or strategically (before these changes in their organisational environment occur).     

Can governments make credible promises? Insights from infrastructure projects in emerging economies

Despite deregulation and privatization, governments in emerging economies continue to play important roles in private infrastructure projects, thereby exposing private investors to the risk of government reneging. The government's role as deal maker—and deal breaker—in infrastructure investments stems from its role as financier, customer, supplier, competitor, and/or regulator. (The only role governments have shed as a result of recent economic reforms is that of producer.) Based on the literature, I propose three explanations for government reneging: (1) economic uncertainty, which necessitates contract renegotiation; (2) the logic of the “obsolescing bargain,” which makes deals less attractive to governments ex post than they were ex ante; and (3) political change, which puts new leaders in charge with incentives to renege on old promises. I assert that these risks can be contained, respectively, through contract design, investment strategy, and institutional design. Using this framework, I conclude that Enron's strategy in the controversial Dabhol project in India was sensitive to first of the three factors and relatively less mindful of the other two. The policy implication for MNCs is that they should be attentive to all three factors that cause government reneging rather than just one or two.     

Risk Communication as Government Agency Organizational Practice

The dynamics of organizational risk communication is an understudied topic in risk research. This article investigates how public officials at six government agencies in Sweden understand and relate to risk communication and its uses in the context of agency organizational work on policy and regulation. Qualitative interviews were used to explore the practitioners’ views on some key topics in the academic literature on risk communication. A main finding is that there is little consensus on what the goals of risk communication are; if, and how, uncertainty should be communicated; and what role is to be played by transparency in risk communication. However, the practitioners agree that dissemination (top down) to the public of robust scientific and expert knowledge is a crucial element. Dialogue and participation is used mainly with other agencies and elite stakeholders with whom agencies collaborate to implement policy goals. Dialogue with the public on issues of risk is very limited. Some implications of the findings for the practice of risk communication by government agencies are suggested.     

Risk analysis under attack: How risk science can address the legal,social, and reputational liabilities faced by risk analysts

The role of the risk analyst is critical in understanding and managing uncertainty. However, there is another type of uncertainty that is rarely discussed: The legal, social, and reputational liabilities of the risk analyst. Recent events have shown that professionals participating in risk analysis can be held personally liable. It is timely and important to ask: How can risk science guide risk analysis with consideration of those liabilities, particularly in response to emerging and unprecedented risk. This paper studies this topic by: (1) Categorizing how professionals with risk analysis responsibilities have historically been held liable, and (2) developing a framework to address uncertainty related to those potential liabilities. The result of this framework will enable individual analysts and organizations to investigate and manage the expectations of risk analysts and others as they apply risk principles and methods. This paper will be of interest to risk researchers, risk professionals, and industry professionals who seek maturity within their risk programs.     

Exploring Risk Judgments in a Trade Dispute Using Bayesian Networks

Bayesian networks (BNs) are graphical modeling tools that are generally recommended for exploring what‐if scenarios, visualizing systems and problems, and for communication between stakeholders during decision making. In this article, we investigate their potential for exploring different perspectives in trade disputes. To do so, we draw on a specific case study that was arbitrated by the World Trade Organization (WTO): the Australia‐New Zealand apples dispute. The dispute centered on disagreement about judgments contained within Australia's 2006 import risk analysis (IRA). We built a range of BNs of increasing complexity that modeled various approaches to undertaking IRAs, from the basic qualitative and semi‐quantitative risk analyses routinely performed in government agencies, to the more complex quantitative simulation undertaken by Australia in the apples dispute. We found the BNs useful for exploring disagreements under uncertainty because they are probabilistic and transparently represent steps in the analysis. Different scenarios and evidence can easily be entered. Specifically, we explore the sensitivity of the risk output to different judgments (particularly volume of trade). Thus, we explore how BNs could usefully aid WTO dispute settlement. We conclude that BNs are preferable to basic qualitative and semi‐quantitative risk analyses because they offer an accessible interface and are mathematically sound. However, most current BN modeling tools are limited compared with complex simulations, as was used in the 2006 apples IRA. Although complex simulations may be more accurate, they are a black box for stakeholders. BNs have the potential to be a transparent aid to complex decision making, but they are currently computationally limited. Recent technological software developments are promising.     

Safety Regulations and the Uncertainty of Work-Related Road Accident Loss: The Triple Identity of Chinese Local Governments Under Principal–Agent Framework

This study examines how government safety regulations affect the uncertainty of work-related road accident loss (UWRAL) by considering the multi-identity of local governments in the relationship among the central government, the local governments, and enterprises. Fixed effects panel models and mediation analyses with bootstrapping were conducted to test the hypotheses using Chinese provincial panel data from 2008 to 2014. Given the complexity and nonlinear characteristics of road safety systems, a new approach based on self-organized criticality theory is proposed to measure the uncertainty of road accident loss from a complex system perspective. We find that a regional government with detailed safety work planning (SWP), high safety supervision intensity (SSI), and safety information transparency (SIT) can decrease the UWRAL. Furthermore, our findings suggest that SSI and SIT partially mediate the relationship between the SWP of regional governments and the UWRAL, with 19.7% and 23.6% indirect effects, respectively. This study also provides the government with managerial implications by linking the results of risk assessment to decision making for risk management.     

Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

基于多阶段随机规划模型的国债动态积极投资策略

本文提出国债组合投资的多阶段随机规划模型,导出基于未来利率市场不确定信息的具备动态调整特点的国债组合主动投资策略。该模型采用基于利率水平、斜率和曲率"三位一体"的离散情景树刻画未来利率期限结构动态演化过程,其中特别考虑了广义货币供给变动的影响;通过最小化国债组合收益的条件风险价值,对国债组合进行主动动态调整;同时兼顾国债投资安全性、流动性和收益性等要求,实现了国债组合投资管理中利率风险规避和收益能力的有效匹配。实证研究表明,与传统久期配比免疫模型相比,该模型确定的最优策略不仅能够为国债组合提供更强的抵御利率风险能力,而且能够稳步提升其收益空间,为金融机构实现国债投资的主动管理提供决策支持。     

Venture Survival in a Transitional Economy

Many formerly controlled economies have undergone discontinuous transformations in their approach to markets, institutional environments, and the role of government in economic activity. We study the factors that affect venture survival in a transitional economy through a two-stage study of private ventures in Hungary. We find that ventures survive under uncertainty, even without significant government support. Industry experience, networking activities, and the strategic orientation of the firms predict survival. Contrary to our predictions, SOE experience, access to infrastructure, and differentiation strategies do not significantly differentiate survivors.     

Government Risk Management Priorities: A Comparison of the Preferences of Asian Indian Americans and Other Americans

A survey was conducted of approximately 200 Asian Indian Americans and 200 other residents of New Jersey in order to understand the risk management priorities that they want government to have. We found that Asian Indian Americans, especially younger women, focused on personal/family risks, such as alcohol and drug abuse, sexual abuse, and domestic violence. The New Jersey comparison group, in contrast, placed war/terrorism and loss of health care services and insurance at the top of their priorities for government. These results suggest stressful acculturation-related issues within the Asian Indian community. Both populations want more risk management from government than they believe government is currently providing. Respondents who wanted more from government tended to dread the risk, be fearful of the consequences, trust government, and have a feeling of personal efficacy. Within the Asian Indian American sample, wide variations were observed by language spoken at home and religious affiliation. Notably, Muslims and Hindi language speakers tended not to trust government and hence wanted less government involvement. This study supports our call for studies of recent migrant populations and Johnson's for testing ethnic identity and acculturation as factors in risk judgments.     

Accommodating Uncertainty in Comparative Risk

Comparative risk projects can provide broad policy guidance but they rarely have adequate scientific foundations to support precise risk rankings. Many extant projects report rankings anyway, with limited attention to uncertainty. Stochastic uncertainty, structural uncertainty, and ignorance are types of incertitude that afflict risk comparisons. The recently completed New Jersey Comparative Risk Project was innovative in trying to acknowledge and accommodate some historically ignored uncertainties in a substantive manner. This article examines the methods used and lessons learned from the New Jersey project. Monte Carlo techniques were used to characterize stochastic uncertainty, and sensitivity analysis helped to manage structural uncertainty. A deliberative process and a sorting technique helped manage ignorance. Key findings are that stochastic rankings can be calculated but they reveal such an alarming degree of imprecision that the rankings are no longer useful, whereas sorting techniques are helpful in spite of uncertainty. A deliberative process is helpful to counter analytical overreaching.     

经济政策不确定性与风险承担:基于风险投资的证据

将经济政策不确定性引入风险投资的决策模型,从理论上证明经济政策不确定性既直接降低风险承担,也负向影响风险投资退出绩效间接降低风险承担.利用1996年~2016年中国经济政策不确定性与风险投资的匹配数据,实证结果支持理论预期.研究发现,经济政策不确定性较高时,风险承担显著更低,表现为风险投资对早期阶段企业和高科技企业的投资比例下降.退出绩效在经济政策不确定性与风险承担之间具有中介作用.经济政策不确定性较高时,风险投资通过IPO或者并购成功退出的交易数目更少、退出期限更长、退出收益更低,因而降低风险承担研究表明,为引导风险投资支持早期高科技企业,除通过财政、税收等政策扶 持奖励风险投资外,政府有必要维持相关政策的稳定性和延续性.     

The Failure of Theory to Predict the Way Public Sector Organisation Responds to its Organisational Environment and the Need for a Mosaic-View of Organisational Theory

What does theory predict about the way government size and structure adapts to changes in government’s organisational environment (particularly to uncertainty and complexity)? In this paper, we review the theory and evidence from the literature about the way government size adjusts to such changes -- particularly to changes in macroeconomic fundamentals like gross national product (GDP). We find that the traditional theories from the organisational theory literature—like the contingency-based view, resource-based view and the rational choice view -- fail to provide global explanations for much of the variation we see in the world around us. Instead, theorists need to adopt a “mosaic view” of organisational theory -- accepting that different theories may explain the way public sector size and structure responds to the uncertainty and variability in its (macroeconomic) organisational environment. We also provide several empirical hypotheses to test such a mosaic-view.     

Further Notes on Public Response to Uncertainty in Risks and Science

Given the prevalence of uncertainty and variability in estimates of environmental health risks, it is important to know how citizens interpret information representing uncertainty in risk estimates. Ranges of risk estimates from a hypothetical industry source elicited divergent evaluations of risk assessors' honesty and competence among New Jersey residents within one mile of one or more factories. A plurality saw ranges of risk estimates as both honest and competent, but with most judging such ranges as deficient on one or both dimensions. They wanted definitive conclusions about safety, tended to believe the high end of the range was more likely to be an accurate estimate of the risk, and believed that institutions only discuss risks when they are "high." Acknowledgment of scientific, as opposed to self-interested, reasons for uncertainty and disputes among experts was low. Attitude toward local industry seemed associated with, if not a cause of, attitudes about ranges of risk estimates. These reactions by industry neighbors appear to replicate the findings of Johnson and Slovic (1995, 1998), despite the hypothetical producer of risk estimates being industry instead of government. Respondents were older and less educated on average than were the earlier samples, but more diverse. Regression analyses suggested attitude toward industry was a major factor in these reactions, although other explanations (e.g., level of scientific understanding independent of general education) were not tested in this study.     

Fairness and nanotechnology concern

Research suggests that fairness perceptions matter to people who are asked to evaluate the acceptability of risks or risk management. Two separate national random surveys (n = 305 and n = 529) addressed Americans’ concerns about and acceptance of nanotechnology risk management in the context of the degree to which they view scientists and risk managers as fair. The first survey investigated general views about scientists across four proposed dimensions of fairness (distributional, procedural, interpersonal, and informational). The results show that respondents who believe that the outcomes of scientific research tend to result in unequal benefits (distributional fairness) and that the procedures meant to protect the public from scientific research are biased (procedural fairness) were more concerned about nanotechnology. Believing scientists would treat them with respect (interpersonal fairness) and ensure access to information (informational fairness) were not significant predictors of concern. The second study also looked at these four dimensions of fairness but focused on perceptions of risk managers working for government, universities, and major companies. In addition to concern, it also examined acceptance of nanotechnology risk management. Study 2 results were similar to those of study 1 for concern; however, only perceived informational fairness consistently predicted acceptance of nanotechnology risk management. Overall, the study points to the value of considering fairness perceptions in the study of public perceptions of nanotechnology.     

The Aggregation of Expert Judgment: Do Good Things Come to Those Who Weight?

Good policy making should be based on available scientific knowledge. Sometimes this knowledge is well established through research, but often scientists must simply express their judgment, and this is particularly so in risk scenarios that are characterized by high levels of uncertainty. Usually in such cases, the opinions of several experts will be sought in order to pool knowledge and reduce error, raising the question of whether individual expert judgments should be given different weights. We argue—against the commonly advocated “classical method”—that no significant benefits are likely to accrue from unequal weighting in mathematical aggregation. Our argument hinges on the difficulty of constructing reliable and valid measures of substantive expertise upon which to base weights. Practical problems associated with attempts to evaluate experts are also addressed. While our discussion focuses on one specific weighting scheme that is currently gaining in popularity for expert knowledge elicitation, our general thesis applies to externally imposed unequal weighting schemes more generally.     

Risk/Benefit Assessments of Human Diseases: Optimum Dose for Intervention

A simple procedure is proposed in order to quantify the tradeoff between a loss suffered from an illness due to exposure to a microbial pathogen and a loss due to a toxic effect, perhaps a different illness, induced by a disinfectant employed to reduce the microbial exposure. Estimates of these two types of risk as a function of disinfectant dose and their associated relative losses provide information for the estimation of the optimum dose of disinfectant that minimizes the total expected loss. The estimates of the optimum dose and expected relative total loss were similar regardless of whether the beta-Poisson, log-logistic, or extreme value function was used to model the risk of illness due to exposure to a microbial pathogen. This is because the optimum dose of the disinfectant and resultant expected minimum loss depend upon the estimated slope (first derivative) of the models at low levels of risk, which appear to be similar for these three models at low levels of risk. Similarly, the choice among these three models does not appear critical for estimating the slope at low levels of risk for the toxic effect induced by the use of a disinfectant. For the proposed procedure to estimate the optimum disinfectant dose, it is not necessary to have absolute values for the losses due to microbial-induced or disinfectant-induced illness, but only relative losses are required. All aspects of the problem are amenable to sensitivity analyses. The issue of risk/benefit tradeoffs, more appropriately called risk/risk tradeoffs, does not appear to be an insurmountable problem.     

Naturally Occurring Preferences and Exogenous Laboratory Experiments: A Case Study of Risk Aversion

Does individual behavior in a laboratory setting provide a reliable indicator of behavior in a naturally occurring setting? We consider this general methodological question in the context of eliciting risk attitudes. The controls that are typically employed in laboratory settings, such as the use of abstract lotteries, could lead subjects to employ behavioral rules that differ from the ones they employ in the field. Because it is field behavior that we are interested in understanding, those controls might be a confound in themselves if they result in differences in behavior. We find that the use of artificial monetary prizes provides a reliable measure of risk attitudes when the natural counterpart outcome has minimal uncertainty, but that it can provide an unreliable measure when the natural counterpart outcome has background risk. Behavior tended to be moderately risk averse when artificial monetary prizes were used or when there was minimal uncertainty in the natural nonmonetary outcome, but subjects drawn from the same population were much more risk averse when their attitudes were elicited using the natural nonmonetary outcome that had some background risk. These results are consistent with conventional expected utility theory for the effects of background risk on attitudes to risk.     

The Role of Quantitative Risk Assessments for Characterizing Risk and Uncertainty and Delineating Appropriate Risk Management Options, with Special Emphasis on Terrorism Risk

The purpose of this article is to discuss the role of quantitative risk assessments for characterizing risk and uncertainty and delineating appropriate risk management options. Our main concern is situations (risk problems) with large potential consequences, large uncertainties, and/or ambiguities (related to the relevance, meaning, and implications of the decision basis; or related to the values to be protected and the priorities to be made), in particular terrorism risk. We look into the scientific basis of the quantitative risk assessments and the boundaries of the assessments in such a context. Based on a risk perspective that defines risk as uncertainty about and severity of the consequences (or outcomes) of an activity with respect to something that humans value we advocate a broad risk assessment approach characterizing uncertainties beyond probabilities and expected values. Key features of this approach are qualitative uncertainty assessment and scenario building instruments.     

Strategic planning in an age of uncertainty

Strategic planning and decision making in the face of uncertainty have always presented a serious challenge to top management, but the present scale of uncertainty is unprecedented. Decision makers used to be able to rely on the past to predict the trends of the future. Now they are increasingly being forced to make important decisions that depend upon highly uncertain external factors for which the past offers little guidance. In all areas of business and government, there is a vital need to understand and implement procedures that enable decision makers to deal more effectively with uncertainty for planning and allocating their organizations' resources.Because of differences in their social, political and economic environments, European and Japanese managers are today affected by many acute areas of uncertainty— such as industrial democracy, floating exchange rates, changing social and political values, growing environmental awareness, government regulation, technological change, pollution control regulation, energy cost, and raw material availability—earlier than their counterparts in the U.S.A. These uncertainties affect not only private sector manufacturing industries, but also financial and service industries as well as nationalized industries and government organizations.This article shows how ineffective methods of dealing with uncertainty can lead to serious mistakes with costly consequences. The cost of overconfidence and people's natural but futile tendency to ignore or to try to eliminate uncertainty is illustrated by the crises seen recently in the world steel and shipbuilding industries. The article then demonstrates how decision analysis procedures that focus directly on the major decision points in the strategic plan enable executives not only to include uncertainty directly in their strategic planning, but also to increase their understanding of the decision process and their ability to communicate the results to others.