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AbstractAn emerging risk is characterized by scant published data, rapidly changing information, and an absence of existing models that can be directly used for prediction. Analysis may be further complicated by quickly evolving decision‐maker priorities and the potential need to make decisions quickly as new information comes available. To provide a forum to discuss these challenges, a virtual conference, "Decision Making for Emerging Risks," was held on June 22–23, 2021, sponsored jointly by the Decision Analysis Society of the Institute for Operations Research and the Management Sciences and the Decision Analysis and Risk specialty group in the Society for Risk Analysis. Speakers reflected on the work to support decision‐makers related to the COVID‐19 pandemic as well as experiences in emerging risks across domains from cybersecurity, infrastructure, transportation, energy, food safety, national security, and climate change. Here, we distill the key findings to propose a set of best practice principles for a "decision‐first" approach for emerging risks. These discussions underscore the importance of scoping the decision context and the shared responsibility for the development and implementation of the analysis between the analyst and the decision‐maker when the context can evolve rapidly. Emerging risks may also favor simpler analytical approaches that increase transparency, ease of explanation, and ability to conduct new analyses quickly. Continued dialogue by the decision and risk analysis communities on the use and development of models for emerging risks will enhance the credibility and usefulness of these approaches.

Many public agencies now face dual pressures to meet external accountability demands on one hand, and improve their internal performance on the other. This begs the question whether the demands that are made on public agencies to externally report on their performance have a limited or wide ranging impact on the utilization of performance indicators (PIs) for internal improvements. This article addresses this question via a small group of public agencies and public accountability authorities in Australia. It also examines the main factors that affect the use of PIs for decision making. The evidence suggests that the agencies use PIs more for meeting external reporting requirements than for achieving internal improvements. Various constraints on the use of PIs were identified, mainly technical problems, and to a lesser extent, political and organizational issues. Adapted from the source document.

Many public agencies now face dual pressures to meet external accountability demands on one hand, and improve their internal performance on the other. This begs the question whether the demands that are made on public agencies to externally report on their performance have a limited or wide ranging impact on the utilization of performance indicators (PIs) for internal improvements. This article addresses this question via a small group of public agencies and public accountability authorities in Australia. It also examines the main factors that affect the use of PIs for decision making. The evidence suggests that the agencies use PIs more for meeting external reporting requirements than for achieving internal improvements. Various constraints on the use of PIs were identified, mainly technical problems, and to a lesser extent, political and organizational issues.

We provide a systematic empirical study of the diffusion and adoption patterns of data-driven decision making (DDD) in the U.S. Using data collected by the Census Bureau for a large representative sample of manufacturing plants, we find that DDD rates nearly tripled (11%-30%) between 2005 and 2010. This rapid diffusion, along with results from a companion paper, are consistent with case-based evidence that DDD tends to be productivity-enhancing. Yet certain plants are significantly more likely to adopt than others. Key correlates of adoption are size, presence of potential complements such as information technology and educated workers, and firm learning.

This article explains the role of mental models and the need of their change to make effective decisions. It is substantiated that the mental model rests on changes to save the system and minimize the risk. An example of this resistance is the complicated and slow process of political reform in Ukraine, which forms a new national mentality model. Political initiatives are aimed at creating a new legitimate mental model, which should be more effective than the previous, in a new environment. But from 2014 to 2017 of the nearly five thousand proposed legislative proposals, the Verkhovna Rada of Ukraine has only adopted a few dozen. It is noted that the review of mental models is a complex process that requires additional energy expenditure, such as stress, loss of comfort, security, money, etc. The ability to change the mental model may require personal courage, creativity, independence, and imagination. To view mental models, the leader must apply the appropriate leadership power and styles, establish an appropriate organizational culture and climate, show positive and optimistic behavior to encourage team members and motivate them to change. It is noted that in the new environment, the decision maker can fluctuate closely to the so-called "line of comfort" for making a decision. This is a line of psychological comfort according to the existing mental model. For better and faster decision-making, you may need to create a new "line of comfort" by looking at the mental model. Thus, in a new environment, the decision maker can again make decisions on the basis of a new mental model. It is proved that mental models are relatively stable, but changing the environment makes them look. The growing conflict between the system and the environment inevitably forms a new mental model, which should again balance the system.

This article explains the role of mental models and the need of their change to make effective decisions. It is substantiated that the mental model rests on changes to save the system and minimize the risk. An example of this resis- tance is the complicated and slow process of political reform in Ukraine, which forms a new national mentality model. Political initiatives are aimed at creating a new legitimate mental model, which should be more effective than the previ- ous, in a new environment. But from 2014 to 2017 of the nearly five thousand proposed legislative proposals, the Verkhovna Rada of Ukraine has only adopted a few dozen. It is noted that the review of mental models is a complex process that requires additional energy expenditure, such as stress, loss of comfort, security, money, etc. The ability to change the mental model may require personal courage, creativity, independence, and imagination. To view mental models, the leader must apply the appropriate leadership power and styles, establish an appropriate organizational culture and climate, show positive and optimistic behavior to en- courage team members and motivate them to change.It is noted that in the new environment, the decision maker can fluctuate closely to the so-called "line of comfort" for making a decision. This is a line of psychological comfort according to the existing mental model. For better and faster decision-making, you may need to create a new "line of comfort" by looking at the mental model. Thus, in a new environment, the decision maker can again make decisions on the basis of a new mental model.It is proved that mental models are relatively stable, but changing the envi- ronment makes them look. The growing conflict between the system and the en- vironment inevitably forms a new mental model, which should again balance the system.

This article describes and investigates a model of strategic sequential decision making in networked policy-making environments with three agents. The primary interest is the effect of network structure on sequential policy making and information aggregation. The model and results illustrate how individual policy decisions of varying weight (in terms of a decision maker's unilateral effect on policy outcomes) can enable information aggregation in decentralized environments. In the studied environment, the incentive compatibility conditions for information aggregation are not invariant to network isomorphisms: individuals' positions in the network matter. The study derives exact conditions for every acyclic network of three or fewer agents and illustrates the counterintuitive nature of comparative statics with respect to both network structure and individual agents' policy preferences and discretionary authority.

In every decision context there are things we know and things we do not know. Risk analysis uses science and the best available evidence to assess what we know--and it is intentional in the way it addresses the importance of the things we don't know. Primer on Risk Analysis: Decision Making Under Uncertainty lays out the tasks of risk analysis in a straightforward, conceptual manner that is consistent with the risk models of all communities of practice. This primer tackles the question, "what is risk analysis?" Distilling the common principles of the many risk tribes and dialects int

We advance the literature on faultlines by theorizing about how and why perceived faultlines (i.e., realized subgroupings as perceived by team members) not only influence team characteristics (e.g., decision-making structures), but also change in response to these team characteristics over time. Drawing on current team theories, we reason that strong perceived faultlines lead teams toward a decentralized decision-making structure (i.e., distributed decision-making responsibility), but a decentralized decision-making structure weakens future perceived faultline strength. We also build a theory suggesting a decentralized decision-making structure mitigates the dysfunctional effect of perceived faultlines on team performance. We find support for our theory in a sample of 230 undergraduate students in 48 teams, and we discuss implications for faultline and team research.