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AbstractThe usefulness of control theory techniques in economic simulations is examined. A model of the capital investment accelerator is used for illustration. It is shown that behavior approaching optimality can be achieved in a highly nonlinear system with simple heuristics based on linearization and constant state feedback with an appropriate choice of desired closed‐loop poles. Applications to real‐life situations are discussed, and suggestions are made for approaching potential problems using similar control theory techniques.

This paper presents problem solving using heuristics and operational research in order to make appropriate decisions in emergency situations with a particular emphasis on the application of a heuristic model of team training for emergency situations. It is intended for military command and teaching personnel as well as for civil defense personnel (Department of Emergency Management) and local government authorities (administrative district chiefs and mayors commanders). The heuristic approach to problem solving should enable adequate decision making for command staff from the local to the national level after the proclamation of emergency and a state of emergency in some regions or the whole territory of Serbia. ; This paper presents problem solving using heuristics and operational research in order to make appropriate decisions in emergency situations with a particular emphasis on the application of a heuristic model of team training for emergency situations. It is intended for military command and teaching personnel as well as for civil defense personnel (Department of Emergency Management) and local government authorities (administrative district chiefs and mayors commanders). The heuristic approach to problem solving should enable adequate decision making for command staff from the local to the national level after the proclamation of emergency and a state of emergency in some regions or the whole territory of Serbia.

This study examines the relationship between the construct Internal Work Motivation and the use of Extrinsic Guides, concerns for Personal Advancement, and Religion/Moral Beliefs for making ethical journalistic decisions. The study reports that journalists who use extrinsic guides such as peers, employers, or the law as ethical heuristics are motivated to perform well on the job. Journalists who use concerns for personal advancement as an ethical motivation are not motivated to perform well on the job. Journalists who use religion/moral beliefs as an ethical motivation may or may not be motivated to perform well on the job depending on how they would deal with an ethical dilemma.

State restrictions on nongovernmental organizations (NGOs) have become increasingly pervasive across the globe. Although this crackdown has been shown to have a negative impact on public funding flows, we know little about how it affects private philanthropy. How does information about crackdown abroad, as well as organizational attributes of nonprofits, affect individual donors' willingness to donate internationally? Using a survey experiment, we find that learning about repressive NGO environments increases generosity in that already-likely donors are willing to donate substantially more to legally besieged nonprofits. This generosity persists when mediated by two organizational-level heuristics: NGO issue areas and main funding sources. We discuss the implications of our results on how nonprofits can use different framing appeals to increase fundraising at a time when traditional public donor funding to such organizations is decreasing.

UX has coalesced from a multiplicity of perspectives and approaches, and is held together by a focus on the user. In order to create the flexibility necessary to accommodate the wide range of projects and perspectives, it is necessary to narrow down the UX team concerns and goals before the project management approach is selected. Rather than depending upon a narrow definition of project management that grows out of an overall work style—whether, Agile, lean, or waterfall—the UX project can usefully benefit from a tailored project management approach that matches the project demands. To narrow down the team focus, the authors propose four heuristics to locate: 1. project scope, 2. project agents, 3. evaluation timing, and 4. evaluation criteria. Once those four questions are answered, the UX team can then better locate what kind of project management approaches and genres will best accomplish the team goals.

Indonesians often consume online news presenting figures of survey results, not only political news but other news as well, for instance, a news headline stated that 63 percent of people on average agreed to a cabinet reshuffle. Strangely enough, it was not stated 37 percent of people on average did not agree to a cabinet reshuffle, which has the same meaning. An attractive frame of online news will potentially get clicks from its audience. In theories of framing effect, news framing in general has a cognitive effect on the audience, including the framing of survey results. However, an opposing view suggests that the advent of new media, especially the internet and Web 2.0 technology, has changed the fundamental order of mass communication, which leads to a minimum effect of new media framing and difficulty in measuring them due to the emergence of preference-based effects as a natural attribute of the online media environment. This interesting research tries to examine the effects of framing in the realm of psychology, which is still quite rarely done in studies on framing effects, by using experimental quantitative methods that test individual evaluation heuristics. The framing of survey results turned out to have an effect on the heuristic assessment of the individual reader. The study prove that the framing effects remain even in new media platforms. The findings presented in this article are expected to contribute to the development of framing theories and media effects.

Informed voting is costly: research shows that voters use heuristics such as party identification and retrospection to make choices that approximate enlightened decision-making. Most of this work, however, focuses on high-information races and ignores elections in which these cues are often unavailable (e.g. primary, local). In these cases, citizens are on their own to search for quality information and evaluate it efficiently. To assess how voters navigate this situation, we field three survey experiments asking respondents what information they want before voting. We evaluate respondents on their ability to both acquire and utilize information in a way that improves their chances of voting for quality candidates, and how this varies by the sophistication of respondents and the offices sought by candidates. We find strong evidence that voters use "deal-breakers" to quickly eliminate undesirable candidates; however, the politically unsophisticated rely on unverifiable, vague, and irrelevant search considerations. Moreover, less sophisticated voters also rely on more personalistic considerations. The findings suggest that voters' search strategies may be ineffective at identifying the best candidates for office, especially at the local level.

AbstractDo policymaker perceptions reflect actual citizen needs? A vast literature has explored the extent to which policy is responsive to public opinion, but there is little systematic work on policymaker perceptions of socialproblems. We quantify social problems with a unique dataset of the number of phone calls placed by citizens to a free service that connects Michigan residents to service providers. We combine these data with a survey of local policymakers' perceptions of social problems facing their own city shows, consistent with theories of bounded rationality, that policymakers use heuristics to make judgments about the extent of constituent needs in their city, and that policymaker perceptions reflect the prevalence of needs. However, partisan perceptions of needs diverge, with Democrats consistently perceiving greater needs than Republicans. There is no evidence that policy activity on the needs in the sample is responsive to constituent needs. We conclude with implications for theories of policy making and avenues for future research.

The increasing throughput of DNA sequencing technologies creates a need for faster algorithms. The fate of most reads is to be mapped to a reference sequence, typically a genome. Modern mappers rely on heuristics to gain speed at a reasonable cost for accuracy. In the seeding heuristic, short matches between the reads and the genome are used to narrow the search to a set of candidate locations. Several seeding variants used in modern mappers show good empirical performance but they are difficult to calibrate or to optimize for lack of theoretical results. Here we develop a theory to estimate the probability that the correct location of a read is filtered out during seeding, resulting in mapping errors. We describe the properties of simple exact seeds, skip seeds and MEM seeds (Maximal Exact Match seeds). The main innovation of this work is to use concepts from analytic combinatorics to represent reads as abstract sequences, and to specify their generative function to estimate the probabilities of interest. We provide several algorithms, which together give a workable solution for the problem of calibrating seeding heuristics for short reads. We also provide a C implementation of these algorithms in a library called Sesame. These results can improve current mapping algorithms and lay the foundation of a general strategy to tackle sequence alignment problems. The Sesame library is open source and available for download at https://github.com/gui11aume/sesame. ; We acknowledge the financial support of the Spanish Ministry of Economy, Industry and Competitiveness (Centro de Excelencia Severo Ochoa 2013–2017, Plan Estatal PGC2018-099807-B-I00), of the CERCA Programme/Generalitat de Catalunya, and of the European Research Council (Synergy Grant 609989). RC was supported by the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement 608959. We also acknowledge support of the Spanish Ministry of Economy and Competitiveness (MEIC) to the EMBL partnership.

In flood risk management, the choice of vulnerability functions has a remarkable impact on the overall uncertainty of modelling flood damage. The spatial transferability of empirical vulnerability functions is limited, leading to the need for computation and validation of region-specific vulnerability functions. In data-scarce regions however, this option is not feasible. In contrast, the physical processes of flood impact model chains can be developed in these regions because of the availability of global datasets. Here we evaluated the implementation of a synthetic vulnerability function into a flood impact model. The function bases on expert heuristics on a targeted sample of representative buildings (targeted heuristics). We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that targeted heuristics can be a valuable alternative for developing flood impact models in regions without any data or only few data on flood damage.

In flood risk management, the choice of vulnerability functions has a remarkable impact on the overall uncertainty of modelling flood damage. The spatial transferability of empirical vulnerability functions is limited, leading to the need for computation and validation of region-specific vulnerability functions. In data-scarce regions however, this option is not feasible. In contrast, the physical processes of flood impact model chains can be developed in these regions because of the availability of global datasets. Here we evaluated the implementation of a synthetic vulnerability function into a flood impact model. The function bases on expert heuristics on a targeted sample of representative buildings (targeted heuristics). We applied the vulnerability function in a meso-scale river basin and evaluated the new function by comparing the resulting flood damage with the damage computed by other approaches, (1) an ensemble of vulnerability functions available from the literature, (2) an individual vulnerability function calibrated with region-specific data, and (3) the vulnerability function used in flood risk management by the Swiss government. The results show that targeted heuristics can be a valuable alternative for developing flood impact models in regions without any data or only few data on flood damage.

This paper focuses on iterated local search heuristics for the maximum cut‐clique (MCC, or clique neighborhood) problem. Given an undirected graph G = (V,E) and a clique C of G, the cut‐clique is the set of edges running between C and V\C, establishing the cut (C,V\C). The MCC in G is to find a clique with the largest number of edges in the neighborhood of the clique, also known as the maximum edge‐neighborhood clique. This problem has been recently introduced in the literature together with a number of applications, namely, in cell biology instances. However, it has only been addressed so far by exact methods. In this paper, we introduce the first approximate algorithms for tackling the MCC problem, compare the results with the exact methodologies, and explore a new application within marketing analysis, which provide a new alternative perspective for mining market basket problems. ; This work has been partially supported by the Portuguese National Funding by FCT (project PEst-OE/MAT/UI0152), Pedro Martins; and by the Ministerio de Economía y Competitividad (Spanish Government), A. Ladrón-de-Guevara (ECO2011-27942) and H. Ramalhinho (TRA2013-48180-C3-2-P).