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Journal articles on the topic 'Risk Responses'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Borak, Jonathan, and Greg Sirianni. "Hormesis: Implications for Cancer Risk Assessment." Dose-Response 3, no. 3 (May 1, 2005): dose—response.0. http://dx.doi.org/10.2203/dose-response.003.03.011.

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Current guidelines for cancer risk assessment emphasize a toxicant's “mode of action”, rather than its empirically derived dose-response relationship, for determining whether linear low-dose extrapolation is appropriate. Thus, for reasons of policy, demonstration of hormesis is generally insufficient to justify a non-linear approach, although it may provide important insights into the actions of toxicants. We evaluated dose-response characteristics of four carcinogens reported to have hormetic dose-response curves: cadmium chloride; ionizing radiation; PAHs; and, 2,3,7,8-TCDD. For each, the study that documented hormesis in one organ also provided evidence of non-hormetic dose-responses in other organs or non-hormetic responses for seemingly similar carcinogens in the same species and organs. Such inconsistency suggests toxicologic reasons that the finding of hormesis alone is not sufficient to justify use of non-linear low-dose extrapolations. Moreover, available data in those examples are not sufficient to know whether hormesis is a property of the toxicants, the target organ, or the exposed species. From the perspectives of cancer risk assessment, the greatest informational value of hormesis may be that it provokes mechanistic studies intended to explain why hormesis occurs.

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2

Asravor, Richard. "Smallholder farmers’ risk perceptions and risk management responses." African Journal of Economic and Management Studies 9, no. 3 (September 3, 2018): 367–87. http://dx.doi.org/10.1108/ajems-10-2017-0250.

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Purpose The purpose of this paper is to identify the perceptions of farmers on the major sources of risk and to examine the effectiveness of the risk management responses of rural smallholder farm households in the semi-arid region of Northern Ghana from the socioeconomic perspective. Design/methodology/approach Both descriptive statistics and exploratory factor analysis were used on a Likert scale question to rank and identify the important risk perceptions and management strategies of the farmers. The linear regression model was used to highlight the significant factors that affect the farmers’ risk perception and management responses. Findings The effects of the variations in crop yield, fertiliser prices and crop price on household income were perceived as the three most relevant sources of risk. Stabilising household income by growing different crops, storing feed/seed reserves and spreading sales were the most effective risk management strategies. Factor analysis identified market risk, production risk and human risk as major risk factors whereas diversification, financial strategy, and off-farm employment were perceived as the most effective risk management strategies. Farm and farmer characteristics were found to be significantly associated with risk perceptions and risk management strategies. Risk perceptions significantly increase the risk management strategy adopted by the smallholder rural farmers. Practical implications The findings of the paper call for the integration of farmers’ risk perceptions and management strategies in the development of agricultural policies for the semi-arid regions of Ghana. Originality/value This paper deviates from the traditional technology adoption studies by modelling rural household perceptions and management strategies using, using descriptive, factor analyses, and linear regression.

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3

Ratnagar, Shereen, and Peter Garnsey. "Responses to Risk and Crisis." Social Scientist 18, no. 1/2 (January 1990): 83. http://dx.doi.org/10.2307/3517331.

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4

Pick, David, and Kandy Dayaram. "Reflexive Judgement, Risk and Responses." Journal of Human Values 12, no. 1 (April 2006): 55–64. http://dx.doi.org/10.1177/097168580501200105.

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5

&NA;. "Risk Management Scenarios and Responses." Gastroenterology Nursing 20, no. 3 (May 1997): 101–3. http://dx.doi.org/10.1097/00001610-199705000-00007.

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6

Rankin, Frederick W., and Todd L. Sayre. "Responses to risk in tournaments." Accounting, Organizations and Society 36, no. 1 (January 2011): 53–62. http://dx.doi.org/10.1016/j.aos.2010.12.001.

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7

Soofifard, Rahman, and Morteza Khakzar Bafruei. "Fuzzy multi-objective model for project risk response selection considering synergism between risk responses." International Journal of Engineering Management and Economics 6, no. 1 (2016): 72. http://dx.doi.org/10.1504/ijeme.2016.079838.

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8

Bafruei, Morteza Khakzar, and Rahman Soofifard. "Fuzzy multi-objective model for project risk response selection considering synergism between risk responses." International Journal of Engineering Management and Economics 6, no. 1 (2016): 72. http://dx.doi.org/10.1504/ijeme.2016.10000728.

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9

Gamp, Martina, Harald T. Schupp, and Britta Renner. "Risk Perceptions After Receiving Multiple Risk Feedback." Personality and Social Psychology Bulletin 44, no. 9 (May 2, 2018): 1350–63. http://dx.doi.org/10.1177/0146167218767877.

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How do people respond to multiple risk feedback in a real-life context? Based on theoretical assumptions, three different predictions for risk perceptions were tested: (a) relative accuracy in risk perceptions, (b) self-defensive responses according to self-affirmation theory, and (c) compensatory responses according to the compensatory health belief model. Participants of a community health screening ( N = 725) received multiple risk indicator feedback for actual blood pressure, blood glucose, and blood lipid levels. Consistent multiple risk feedback profiles encompassed three consistent readings (three normal or three elevated readings). Mixed risk profiles included one elevated and two normal readings. Results indicate relative accuracy in responses: an elevated reading triggered higher risk perception of the respective risk factor. Importantly, the effect was not modulated by the presence of normal readings as assumed by the self-defensive or compensatory response perspective, indicating that people accurately integrate multiple risk indicator feedback as it is often provided in real life.

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10

Simpson, Jeremy. "Risk Management Responses to Armed Non-State Actor Risk in Afghanistan." International Review of Social Research 5, no. 3 (October 1, 2015): 156–66. http://dx.doi.org/10.1515/irsr-2015-0015.

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Abstract The article considers responses by different categories of actor to the threat of armed non-state actors in the international intervention in Afghanistan 2001-2015. Concepts from the sociology of risk, in particular risk-management and the distinction between operational and reputational risk, are related to field research in Afghanistan during the intervention. The ‘risk society’ approach of Beck (2009) is critiqued as relatively inapplicable to a discussion of differences in risks to and responses by different categories of actor. The article identifies some convergences of practice across three categories of intervening actor, civil-developmental, counter-insurgent and counter-terrorist, in particular tendencies to risk-transfer and remote-management that draws together theorisation of civil practice by Duffield (2010) and military practice by Shaw (2002). This is problematised relative to difficulties in managing tensions between operational risks to intervening actors and reputational risks vis-à-vis local actors.

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11

Tuomisto, Jouko, Juha Pekkanen, Hannu Kiviranta, Erkki Tukiainen, Terttu Vartiainen, Matti Viluksela, and Jouni T. Tuomisto. "Dioxin Cancer Risk — Example of Hormesis?" Dose-Response 3, no. 3 (May 1, 2005): dose—response.0. http://dx.doi.org/10.2203/dose-response.003.03.004.

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A recent case-control study implied an inverse correlation between the measured body burden of dioxins (polychlorinated dibenzo- p-dioxins and polychlorinated dibenzofurans, PCDD/F) and the risk of soft tissue sarcoma in normal population exposed to dioxins mainly via food. The surprising result could not be explained by biases or confounding. There is no a priori confounding by occupational chemicals in a random sample from general population, but exposures to other lipid soluble chemicals with similar sources might be expected to associate with that of dioxins. One such group is polychlorinated biphenyls (PCB). Therefore three most relevant dioxin-like PCB compounds PCB 77, PCB 126, and PCB 169 were now analyzed from the same patients. Cases were 110 soft-tissue sarcoma patients undergoing surgery for their disease, and referents were 227 patients operated for appendicitis. Dioxin and PCB concentrations were analyzed from subcutaneous fat samples by high-resolution gas chromatography—mass spectrometry and TCDD equivalent concentrations (WHO-TEq) were calculated by using toxicity equivalency factors of WHO. The highest risk of sarcoma was found in the septile with the lowest body burden of sum WHO-TEq, and the differences of septiles 2 and 6 from septile 1 were statistically significant. If soft sarcoma risk is true at high occupational levels of dioxins, the provocative result suggests that a possibility of a J-shaped dose-response curve should be taken into consideration and studied further. This is also supported by the similar J-shaped dose responses in animal studies.

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12

Ferrari, Maud C. O., Grant E. Brown, and Douglas P. Chivers. "Time-sensitive neophobic responses to risk." Behaviour 152, no. 12-13 (2015): 1623–35. http://dx.doi.org/10.1163/1568539x-00003296.

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Prey animals that experience a high background level of risk are known to exhibit considerable phenotypic plasticity in their responses to unknown predators. When background risk is high, prey exhibit neophobic responses to unknown odours, i.e. they show a fear response to any new stimulus. Here, we examine whether temporal variation in the pattern of risk to which prey are exposed influences neophobic responses. To establish prey groups with different temporal patterns of risk, embryonic woodfrogs (Lithobates sylvaticus) were exposed to conspecific alarm cues each morning and control cues in the evening, or conspecific alarm cues each evening and control cues in the morning, for their entire embryonic period. After the tadpoles hatched they were tested at both times of day for known risk cues (alarm cues), unknown predator odours or water control. Tadpoles responded to alarm cues at any time of day, but showed neophobic responses to predator odours only if their test time matched their embryonic risk exposure time. These results demonstrate a high level of sophistication of neophobic responses and points to temporal variation in risk as a key driver of antipredator decision making.

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13

Kimball, Miles S., Claudia R. Sahm, and Matthew D. Shapiro. "Imputing Risk Tolerance From Survey Responses." Journal of the American Statistical Association 103, no. 483 (September 2008): 1028–38. http://dx.doi.org/10.1198/016214508000000139.

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14

Lybbert, Travis J., and Christopher B. Barrett. "Risk Responses to Dynamic Asset Thresholds." Review of Agricultural Economics 29, no. 3 (September 2007): 412–18. http://dx.doi.org/10.1111/j.1467-9353.2007.00354.x.

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15

GRANGER, D. NEIL, STEPHEN F. RODRIGUES, ALPER YILDIRIM, and ELENA Y. SENCHENKOVA. "Microvascular Responses to Cardiovascular Risk Factors." Microcirculation 17, no. 3 (April 2010): 192–205. http://dx.doi.org/10.1111/j.1549-8719.2009.00015.x.

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16

Pasman, J. W., J. J. Rotteveel, B. Maassen, R. de Graaf, and A. A. Kollée. "Neonatal risk factors and risk scores including auditory evoked responses." European Journal of Pediatrics 157, no. 3 (February 25, 1998): 230–35. http://dx.doi.org/10.1007/s004310050801.

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17

Jun, Hyoyeun, and Yen-I. Lee. "The Role of Risk Tolerance in Publics’ Health Risk Perception and Responses." Proceedings of the International Crisis and Risk Communication Conference, Volume 2 2, no. 2019 (March 2019): 20–22. http://dx.doi.org/10.30658/10.30658/icrcc.2019.6.

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To better understand how uncertainty influences publics’ risk perception and responses, this study introduced risk tolerance as a new concept to public relations literature and then investigated how publics react to health risks with different temporal distances: climate change and foodborne illness. Through an online survey, this study found out that uncertainty, induced by risk temporal distance, leads to varied risk tolerance, which subsequently influences where and how people seek and share risk information.

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18

Jun, Hyoyeun, and Yen-I. Lee. "The Role of Risk Tolerance in Publics’ Health Risk Perception and Responses." Proceedings of the International Crisis and Risk Communication Conference, Volume 2 2, no. 2019 (March 2019): 20–22. http://dx.doi.org/10.30658/icrcc.2019.6.

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To better understand how uncertainty influences publics’ risk perception and responses, this study introduced risk tolerance as a new concept to public relations literature and then investigated how publics react to health risks with different temporal distances: climate change and foodborne illness. Through an online survey, this study found out that uncertainty, induced by risk temporal distance, leads to varied risk tolerance, which subsequently influences where and how people seek and share risk information.

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19

Patrick, George R., Paul N. Wilson, Peter J. Barry, William G. Boggess, and Douglas L. Young. "Risk Perceptions and Management Responses: Producer-Generated Hypotheses For Risk Modeling." Journal of Agricultural and Applied Economics 17, no. 2 (December 1985): 231–38. http://dx.doi.org/10.1017/s0081305200025243.

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AbstractFarm level risk analyses have used price and yield variability almost exclusively to represent risk. Results from a survey of 149 agricultural producers in 12 states indicate that producers consider a broader range of sources of variability in their operations. Significant differences exist among categories with respect to the importance of the sources of variability in crop and livestock production. Producers also used a variety of management responses to variability. There were significant difference among categories in the importance given to particular responses and their use of them. These results have implications for research, extension, and policy programs.

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20

Lewis, James. "The fluidity of risk." Disaster Prevention and Management: An International Journal 28, no. 5 (October 7, 2019): 636–48. http://dx.doi.org/10.1108/dpm-01-2019-0014.

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Purpose Considered alone, risk is static; the purpose of this paper is to illustrate risk not as static but as a fluid condition dependent, for example, upon circumstances of its context in changeable vulnerability and behavioural responses of people facing risk. Design/methodology/approach Psychology provides strong evidence of behavioural response when facing hazards; technological disasters providing more evidence of behavioural responses to hazards and risk than response to disasters assumed to be “natural”. Initial and subsequent behavioural responses may critically affect ultimate outcomes. Post-event inquiries into technological disasters have revealed actions and inactions which created or aggravated subsequent consequences and their aftermath. Findings Decisions taken at a Japanese school between the 2011 earthquake and tsunami, and details of the 2017 fire at a tower-block in London, UK, indicate, in spite of training, that rigidity, uncertainty, hesitation or waver may affect critical decisions and their consequences. Pre- and post-disaster behaviour may not follow preferred patterns. Fear of imagined or real events may induce unanticipated denial of the reality of risk. Physical changes made after assessments of risk may not be recognised as affecting risk. Research limitations/implications Few published examples exist of public inquiries following disasters assumed to be from natural causes. Practical implications Reports of inquiries into technological disasters provide significant examples of behavioural responses which, if replicated, may influence outcomes of disasters labelled as “natural”. Social implications Awareness of risk as a fluid condition will facilitate realisation of effects upon risk of uncompleted or ongoing works, inappropriate behavioural responses, undeveloped resilience and of the need for regular reassessments of risk. Originality/value This study encourages comprehension of risk as an evolving and fluid condition.

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21

Beazer, Quintin H., and Daniel J. Blake. "Risk Is Relative: Heterogeneous Responses to Institutional Risks for Foreign Investment." International Studies Quarterly 65, no. 3 (June 1, 2021): 594–605. http://dx.doi.org/10.1093/isq/sqab043.

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Abstract Are economic actors equally sensitive to institutional conditions? While existing research recognizes that institutions can have varying effects on actors’ interests, the implicit assumption is that actors are homogeneous in how sensitive they are to their institutional environment. We investigate this assumption in the context of foreign direct investment, arguing that actors from countries with weaker institutions will be less affected by information about host country institutional conditions—both good and bad. We test this argument using survey data from a diverse group of managers-in-training at an international business school. We find that when asked to evaluate a potential foreign investment location, respondents from developing countries are significantly less sensitive to information about the host country’s courts than their counterparts from developed economies. In contrast, we find that economic actors from both developed and developing countries respond similarly to information about the stability of economic policies. The findings suggest that sensitivity to the risks and safeguards of certain institutional conditions vary systematically across actors, depending on both the home environment to which economic actors have been exposed and the type of host institution.

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22

Chen, Chu-Chih, and James J. Chen. "Benchmark Dose Calculation for Ordered Categorical Responses." Risk Analysis 34, no. 8 (January 20, 2014): 1435–47. http://dx.doi.org/10.1111/risa.12167.

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23

Fukuda, Hirokatsu, and Hiroaki Kuwano. "THE MATHEMATICAL MODEL OF PROJECT RISK RESPONSES IN PROJECT RISK MANAGEMENT." Journal of the Operations Research Society of Japan 60, no. 2 (2017): 192–200. http://dx.doi.org/10.15807/jorsj.60.192.

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24

Robinson, James C. "Worker Responses to Occupational Risk of Cancer." Review of Economics and Statistics 72, no. 3 (August 1990): 536. http://dx.doi.org/10.2307/2109365.

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25

Burrus, Robert, Christopher Dumas, and Edward Graham. "Coastal Homeowner Responses to Hurricane Risk Perceptions." Journal of Housing Research 17, no. 1 (January 1, 2008): 49–60. http://dx.doi.org/10.1080/10835547.2008.12091985.

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26

Levin, Aaron. "Postdisaster Stress Responses May Predict Cardiovascular Risk." Psychiatric News 43, no. 5 (March 7, 2008): 24–32. http://dx.doi.org/10.1176/pn.43.5.0024a.

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27

Sotala, Kaj, and Roman V. Yampolskiy. "Responses to catastrophic AGI risk: a survey." Physica Scripta 90, no. 1 (December 19, 2014): 018001. http://dx.doi.org/10.1088/0031-8949/90/1/018001.

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28

Phillips, James G., Rowan P. Ogeil, and Alex Blaszczynski. "Behavioural responses to risk on remote outcomes." Behaviour & Information Technology 34, no. 3 (December 13, 2013): 239–46. http://dx.doi.org/10.1080/0144929x.2013.857433.

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29

Jalan, Jyotsna, and Martin Ravallion. "Behavioral responses to risk in rural China." Journal of Development Economics 66, no. 1 (October 2001): 23–49. http://dx.doi.org/10.1016/s0304-3878(01)00154-7.

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30

Hiscock, Peter. "Technological responses to risk in Holocene Australia." Journal of World Prehistory 8, no. 3 (September 1994): 267–92. http://dx.doi.org/10.1007/bf02221051.

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31

Koh, Jaehan, Bin Wang, Lai C. Liu, and Kai S. Koong. "Asymmetric responses, risk seeking and internet bubble." International Journal of Electronic Finance 4, no. 4 (2010): 323. http://dx.doi.org/10.1504/ijef.2010.035728.

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32

Kim, Seonghoon, and Kwan Ok Lee. "Potential crime risk and housing market responses." Journal of Urban Economics 108 (November 2018): 1–17. http://dx.doi.org/10.1016/j.jue.2018.09.001.

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33

Cox, Anthony D., Dena Cox, and Gregory Zimet. "Understanding Consumer Responses to Product Risk Information." Journal of Marketing 70, no. 1 (January 2006): 79–91. http://dx.doi.org/10.1509/jmkg.2006.70.1.79.

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34

Cox, Anthony D., Dena Cox, and Gregory Zimet. "Understanding Consumer Responses to Product Risk Information." Journal of Marketing 70, no. 1 (January 2006): 79–91. http://dx.doi.org/10.1509/jmkg.70.1.079.qxd.

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35

Waters, Erika A., Jennifer L. Hay, Heather Orom, Marc T. Kiviniemi, and Bettina F. Drake. "“Don’t Know” Responses to Risk Perception Measures." Medical Decision Making 33, no. 2 (February 2013): 271–81. http://dx.doi.org/10.1177/0272989x12464435.

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36

Teplitsky, C., S. Plénet, and P. Joly. "Tadpoles' responses to risk of fish introduction." Oecologia 134, no. 2 (January 2003): 270–77. http://dx.doi.org/10.1007/s00442-002-1106-2.

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37

Bailer, A. John, and Kyoungah See. "Individual-based risk estimation for count responses." Environmental Toxicology and Chemistry 17, no. 3 (March 1998): 530–33. http://dx.doi.org/10.1002/etc.5620170326.

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38

Schembari, Blaire C., David A. Jobes, and Ryan J. Horgan. "Successful Treatment of Suicidal Risk." Crisis 37, no. 3 (May 2016): 218–23. http://dx.doi.org/10.1027/0227-5910/a000370.

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Abstract. Background: In this article we focused on analyzing surveyed patient-generated responses based on two outcome questions derived from a suicide-specific framework called the Collaborative Assessment and Management of Suicidality (CAMS): Q1 – "Were there any aspects of your treatment that were particularly helpful to you? If so, please describe these. Be as specific as possible." Q2 – "What have you learned from your clinical care that could help you if you became suicidal in the future?" Aims: To develop a reliable coding system based on formerly suicidal patients' responses to two open-ended prompts and examine most frequently identified themes. Method: The present study utilized a consensual qualitative research process to examine responses of clinically resolved suicidal patients, based on the CAMS resolution criteria (i.e., three consecutive CAMS sessions reporting the effective management of suicidal risk), to two Suicide Status Form (SSF) outcome questions (n = 49 for Q1, and n = 52 for Q2). Results: Reliable coding systems were developed and used to determine major themes of successful patient responses. Conclusion: The results of this study provide insight into patients' experiences of a successful treatment for suicidal risk with larger implications for suicide-specific treatments in general.

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39

Bonnet, Agnès, Lydia Fernandez, Annie Piolat, and Jean-Louis Pedinielli. "Changes in Emotional States Before and After Risk Taking in Scuba Diving." Journal of Clinical Sport Psychology 2, no. 1 (March 2008): 25–40. http://dx.doi.org/10.1123/jcsp.2.1.25.

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The notion of risk-taking implies a cognitive process that determines the level of risk involved in a particular activity or task. This risk appraisal process gives rise to emotional responses, including anxious arousal and changes in mood, which may play a significant role in risk-related decision making. This study examines how emotional responses to the perceived risk of a scuba-diving injury contribute to divers’ behavior, as well as the ways that risk taking or non-risk taking behavior, in turn, affects emotional states. The study sample consisted of 131 divers (risk takers and non-risk takers), who either had or had not been in a previous diving accident. Divers’ emotional states were assessed immediately prior to diving, as well as immediately following a dive. Results indicated presence of subjective emotional experiences that are specific to whether a risk has been perceived and whether a risk has been taken. Important differences in emotion regulation were also found between divers who typically take risks and those who do not.

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Mitchel, R. E. J. "Cancer and Low Dose Responses in vivo: Implications for Radiation Protection." Dose-Response 5, no. 4 (October 1, 2007): dose—response.0. http://dx.doi.org/10.2203/dose-response.07-014.mitchel.

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The Linear No Threshold (LNT) hypothesis states that ionizing radiation risk is directly proportional to dose, without a threshold. This hypothesis, along with a number of additional derived or auxiliary concepts such as radiation and tissue type weighting factors, and dose rate reduction factors, are used to calculate radiation risk estimates for humans, and are therefore fundamental for radiation protection practices. This system is based mainly on epidemiological data of cancer risk in human populations exposed to relatively high doses (above 100 mSv), with the results linearly extrapolated back to the low doses typical of current exposures. The system therefore uses dose as a surrogate for risk. There is now a large body of information indicating that, at low doses, the LNT hypothesis, along with most of the derived and auxiliary concepts, is incorrect. The use of dose as a predictor of risk needs to be re-examined and the use of dose limits, as a means of limiting risk needs to be re-evaluated. This re-evaluation could lead to large changes in radiation protection practices.

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Stoltz, Amanda Daria, Manoj Shivlani, and Robert Glazer. "Fishing Industry Perspectives on Sea-Level Rise Risk and Adaptation." Water 13, no. 8 (April 20, 2021): 1124. http://dx.doi.org/10.3390/w13081124.

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Sea-level rise, already occurring over Florida’s coast, stands to generate a significant impact on the state’s fishing industry and coastal communities, exposing vulnerable areas and populations to extreme events and disrupting established patterns of fishery and marine resource use. Using a semi-structured interview approach, this study evaluated fishing industry perspectives on sea-level rise risk and adaptation in three Florida coastal communities. The results showed that adaptation responses vary across industry sectors and communities and are strongly influenced by experience, community dynamics, and age. Generally, older fishers are less willing to relocate due to social factors, such as strong place attachment, compared to younger fishers, who are more likely to retreat and/or work from a less vulnerable location. These findings suggest that adaptation responses, while influenced by experience, are mediated by age, attachment to place, and worldviews, and that these factors need to be accounted for when crafting adaptation strategies across coastal communities.

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42

Bruine de Bruin, Wändi, and Katherine G. Carman. "Measuring Subjective Probabilities: The Effect of Response Mode on the Use of Focal Responses, Validity, and Respondents’ Evaluations." Risk Analysis 38, no. 10 (August 16, 2018): 2128–43. http://dx.doi.org/10.1111/risa.13138.

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43

Chatterjee, Chiradip, and Pallab Mozumder. "Understanding Household Preferences for Hurricane Risk Mitigation Information: Evidence from Survey Responses." Risk Analysis 34, no. 6 (March 27, 2014): 984–96. http://dx.doi.org/10.1111/risa.12196.

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44

MacIntosh, Kevin, Derek Williamson, Matthew Armstrong, Leo Brewster, and Ricardo Arthur. "BARBADOS COASTAL RISK ASSESSMENT AND MANAGEMENT PROGRAMME." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 52. http://dx.doi.org/10.9753/icce.v36.risk.52.

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Monitoring of coastal environments is critical to understanding the responses of the natural environment to human interventions. The ability to definitively attribute impacts to a development versus those which are part of the natural variation of a dynamic system is a valuable tool to understanding the successes and failures of coastal zone management planning. The Coastal Zone Management Unit of the Government of Barbados (CZMU) undertook the Coastal Risk Assessment and Management (CRMP) project to define the baseline conditions and risks for the entire coastline of Barbados in order to have this comprehensive database upon which to base future decisions and coastal planning. This paper will focus on three of the nine baseline studies and the unique approaches used, and challenges encountered, along the way.

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45

Yang, Jun, and Ellen Goddard. "Canadian Consumer Responses to BSE with Heterogeneous Risk Perceptions and Risk Attitudes." Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie 59, no. 4 (June 30, 2011): 493–518. http://dx.doi.org/10.1111/j.1744-7976.2011.01225.x.

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46

Sarkar, Asani. "Liquidity risk, credit risk, and the federal reserve’s responses to the crisis." Financial Markets and Portfolio Management 23, no. 4 (October 13, 2009): 335–48. http://dx.doi.org/10.1007/s11408-009-0116-z.

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47

Melby, Jeffrey A., Alex Taflanidis, Norberto Nadal-Caraballo, Victor Gonzalez, and Fatima Diop. "SURROGATE MODELING OF STORM RESPONSE." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 91. http://dx.doi.org/10.9753/icce.v36.risk.91.

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Surrogate models are yielding simple, fast and accurate storm response predictions. Surrogate modelling is being applied to compute regional response or compute thousands of realizations in seconds. These tools are useful for forecasting, scenario analysis and risk assessments. Approaches used for coastal application include artificial neural networks (ANN), Gaussian process regression (Kriging), and response surface techniques (e.g. Kim et al. 2015, Jia et al. 2013,). These previous approaches were limited to hurricane suites that were already optimally preconfigured using joint probability methods. The results were surprisingly effective in large part because the simulation suites were already optimized and the high dimensional parameter space was well correlated in time and space. The kriging method was applied for the study reported here to: 1) Optimize the parameter space and resulting selection of storms for high fidelity modelling, and 2) Construct surrogate models for both extratropical and tropical storm suites and for wave transformation as well as hurricane surge and other hurricane responses. The results were used for forecasting, scenario analysis, and risk assessments.

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Nguyen, Kiet Tuan, Chi Huu Phuong Ho, and Duc Cong Trinh. "Risks and risk responses of rice farmers in the Mekong Delta, Vietnam." Letters in Spatial and Resource Sciences 15, no. 1 (November 17, 2021): 129–44. http://dx.doi.org/10.1007/s12076-021-00290-5.

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Visvizi, Anna, and Miltiadis D. Lytras. "Government at risk: between distributed risks and threats and effective policy-responses." Transforming Government: People, Process and Policy 14, no. 3 (July 20, 2020): 333–36. http://dx.doi.org/10.1108/tg-06-2020-0137.

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Purpose The purpose of this paper is to contextualise and examine critically the collection of the papers dealing with the broad and multi-faceted question of risk, threats and challenges governments are exposed to in the 21st century. To this end, the concept of ‘distributed risks and threats’ is introduced to account of challenges spread across the context, in which governments are embedded. Design/methodology/approach This paper offers a critical insight into the content of the issue. Findings The key argument that this paper advances is that while the nature of risks, threats and challenges that governments are exposed to today is qualitatively new and their scope unprecedented, a lot of governments’ capacity remains idle, i.e. ready to be deployed to address these risks, threats and challenges. Research limitations/implications As a review paper, the points conveyed in this paper sketch and highlight, rather than explore in-depth, the possible and new research avenues that the collection of papers prompts. Practical implications This paper highlights that the – developed over the centuries – capacity of the government to act and address risks and threats is incommensurate with the agility of challenges borne in the 21st century. Originality/value This paper introduces the concept of ‘distributed risks and threats’ to account of the qualitatively new and hybrid challenges spread across the context, in which governments are embedded. This conceptualization of risks and threats, or challenges, offers a handy way to contextualize the variety of ways in which the government is challenged today.

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Razzaghi, Mehdi. "Beta-normal distribution in dose–response modeling and risk assessment for quantitative responses." Environmental and Ecological Statistics 16, no. 1 (January 12, 2008): 25–36. http://dx.doi.org/10.1007/s10651-007-0072-6.

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