Bird strikes, a risk factor in the aviation industry, are a common problem in certain states of the USA, while they are extremely rare in other states. Similarly, the seasonal distribution of bird strikes is not proportional. This situation poses an unfair situation in the aviation insurance of airline companies in terms of routes taken. The current study, detecting a literature gap related to the principal-agent problem within the aviation sector, evaluates the possible differences in aviation companies' insurance costs, assuming bird strikes are spatially and temporally analyzed in the US, and airline companies are provided with complete information regarding bird-strikes. In this research, QGIS software served in spatial model mappings. In terms of the threshold value, the study results show that making bird-strike insurance aircraft in twenty-one states which were below the threshold value increased the aviation costs of these airline companies, while in the remaining twenty-nine states, non-insurance raised the cost. In this context, as of 2022, it has been determined that not paying an extra premium for bird strikes in twenty-one states below the threshold value will create efficiency, while expending an above-average insurance premium in twenty-nine states and the District of Columbia above the threshold value will create efficiency. The research seeks to answer the following question: Is it fair for airlines operating on routes with low or high bird strike risks to pay the same amount of insurance cost?
Within recent years, Financial Credit Risk Assessment (FCRA) has become an increasingly important issue within the financial industry. Therefore, the search for features that can predict the credit risk of an organization has increased. Using multiple statistical techniques, a variance of features has been proposed. Applying a structured literature review, 258 papers have been selected. From the selected papers, 835 features have been identified. The features have been analyzed with respect to the type of feature, the information sources needed and the type of organization that applies the features. Based on the results of the analysis, the features have been plotted in the FCRA Model. The results show that most features focus on hard information from a transactional source, based on official information with a high latency. In this paper, we readdress and -present our earlier work [1]. We extended the previous research with more detailed descriptions of the related literature, findings, and results, which provides a grounded basis from which further research on FCRA can be conducted.
Background: Stroke is not only an acute disease, but for the majority of patients, it also becomes a chronic condition. There is a major concern about the long-term follow-up with respect to activities of daily living (ADL) in stroke survivors.Some patients seem to be at risk for decline after a first-ever stroke. The purpose of this study was to determine the course of ADL from 3 months after the first-ever stroke and onward and identify factors associated with decline in ADL. Methods: A systematic literature search of 3 electronic databases through June 2015 was conducted. Longitudinal studies evaluating changes in ADL from 3 months post stroke onward were included. Cohorts including recurrent strokes and transient ischemic attacks were excluded. Regarding the course of ADL, a meta-analysis was performed using random-effects model. A best evidence synthesis was performed to identify factors associated with decline in ADL. Results: Out of 10,473 publications, 28 unique studies were included. A small but significant improvement in ADL was found from 3 to 12 months post stroke (standardized mean difference (SMD) 0.17 (0.04–0.30)), which mainly seemed to occur between 3 and 6 months post stroke (SMD 0.15 (0.05–0.26)). From 1 to 3 years post stroke, no significant change was found. Five studies found a decline in ADL status over time in 12–40% of patients. Nine factors were associated with ADL decline. There is moderate evidence for being dependent in ADL and impaired motor function of the leg. Limited evidence was found associated with insurance status, living alone, age ≥ 80, inactive state and having impaired cognitive function, depression and fatigue with decline in ADL. Conclusion: Although on an average patients do not seem to decline in ADL for up to 3 years, there is considerable variation within the population. Some modifiable factors associated with decline in ADL were identified. However, more research is needed before patients at risk of deterioration in ADL can be identified.
