Search results for: risk management model

Authors: Shahnaz Bashir, Abel Usoro, Imran Khan

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Hofstede’s culture model is an important model to study culture between different societies. He collected data from world-wide and performed a comprehensive study. Hofstede’s cultural model is widely accepted and has been used to study cross cultural influences in different areas like cross-cultural psychology, cross cultural management, information technology, and intercultural communication. This study investigates the societal cultural aspects of knowledge sharing in virtual communities.

Keywords: knowledge management, knowledge sharing, societal culture, virtual communities

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Authors: Zohreh Hajiha

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Culture affects the ability of the organization in expressing and achieving the goals. Organizational culture influences the selection of instruments applied in the management of organizations. All the instruments applied in organizations to control, promote and create innovations are influenced by organizational culture. This research studies organizational culture based on the cultural model of Muijen and its relationship with applying management accounting innovations in Iranian listed firms. Management accounting innovations of this study include activity-based costing, activity-based management, balanced scorecard, target costing, standard costing, quality costing, Kaizen costing and dimensions of organizational culture include support orientation, innovation orientation, rules orientation and goal orientation. 105 questionnaires were sent to financial executives of production companies and 73 questionnaires were returned. The findings show that there is a significant difference between organizational culture of firms that have applied management accounting innovations and those which have used these innovations less. Also, dimensions of support orientation and culture goal orientation are the highest in groups that apply management accounting innovations. The findings suggest that proper organization culture could promote the use od management accounting tools in Iranian firms.

Keywords: organizational culture, innovation, management accounting, muijen model

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Authors: Joseph Paul Chunga

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The investment universe is awash with a myriad of financial choices that investors have to opt for, which principally culminates into a duality between aggressive or conservative approaches. Howbeit, it is pertinent to emphasize that the investment vehicles with an aggressive approach tend to take on more risk than the latter group in an effort to generate higher future returns for their respective investors. This study examines the conditionality effect that such partiality in financing has on the High-Tech and Public Utility companies listed on the Shenzhen Stock Exchange (SSE). Specifically, it examines the significance of the relationship between capitalization ratios of Total Debt Ratio (TDR), Degree of Financial Leverage (DFL) and profitability ratios of Earnings per Share (EPS) and Returns on Equity (ROE) on the Financial Risk of the two industries. We employ a modified version of the Panel Regression Model used by Rahman (2017) to estimate the relationship. The study finds that there is a significant positive relationship between the capitalization ratios on the financial risk of Public Utility companies more than High-Tech companies and a substantial negative relationship between the profitability ratios and the financial risk of the former than the latter companies. This then spells an important insight for prospective investors with regards to the volatility of earnings of such companies.

Keywords: financial leverage, debt financing, conservative firms, aggressive firms

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Authors: Anissa Mary Thomas Thattil, Nancy Angeline Gnanaselvam, B. Ramakrishna Goud

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Faecal sludge management (FSM) is an unorganized sector, and in India, there is an absence of regulations regarding the collection, transport, treatment, and disposal of faecal sludge. FSM has a high degree of occupational hazards that need to be thoroughly understood in order to shape effective solutions. On-field observations of five FSM operations were conducted in Anekal Taluk of southern Karnataka. All five of the FSM operations were privately owned and snowball method of sampling was employed. Two types of FS operations observed were: mechanical emptying involving direct human contact with faecal sludge and mechanical emptying without direct human contact with faecal sludge. Each operation was manned by 3-4 faecal sludge operators (FSOs). None of the observed FSOs used personal protective equipment. According to the WHO semi-quantitative risk assessment, the very high risk occupational hazards identified were dermal contact with faecal sludge, inhalation of toxic gases, and social stigma. The high risk hazards identified were trips and falls, injuries, ergonomic hazards, substance abuse, and mental health problems. In all five FSM operations, the collected faecal sludge was discharged untreated onto abandoned land. FSM in India is fraught with occupational and environmental hazards which need to be urgently addressed. This includes formalizing the institution of FSM, contextualized behaviour change communication, capacity building of local bodies, awareness programmes among agriculturists and FSOs, and designation of sites for the safe harnessing of faecal sludge as soil nutrient.

Keywords: faecal sludge, faecal sludge management, FSM, occupational hazards, sanitation

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Authors: Karl-Erich Lindenschmidt, Apurba Das, Joel Trudell, Keanne Russell

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In this presentation, we explore options for mitigating ice-jam flooding along the Athabasca River in western Canada. Not only flood hazard, expressed in this case as the probability of flood depths and extents being exceeded, but also flood risk, in which annual expected damages are calculated. Flood risk is calculated, which allows a cost-benefit analysis to be made so that decisions on the best mitigation options are not based solely on flood hazard but also on the costs related to flood damages and the benefits of mitigation. The river ice model is used to simulate extreme ice-jam flood events with which scenarios are run to determine flood exposure and damages in flood-prone areas along the river. We will concentrate on three mitigation options – the placement of a dike, artificial breakage of the ice cover along the river, the installation of an ice-control structure, and the construction of a reservoir. However, any mitigation option is not totally failsafe. For example, dikes can still be overtopped and breached, and ice jams may still occur in areas of the river where ice covers have been artificially broken up. Hence, for all options, it is recommended that zoning of building developments away from greater flood hazard areas be upheld. Flood mitigation can have a negative effect of giving inhabitants a false sense of security that flooding may not happen again, leading to zoning policies being relaxed. (Text adapted from Lindenschmidt [2022] "Ice Destabilization Study - Phase 2", submitted to the Regional Municipality of Wood Buffalo, Alberta, Canada)

Keywords: ice jam, flood hazard, flood risk river ice modelling, flood risk

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Authors: Markus Stralla

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This study employs a GMM framework to examine the impact of potential regulatory intervention regarding the occupations of supervisory board members in cooperative banking. To achieve insights, the study proceeds in two different ways. First, it investigates the changes in board structure prior and following to the German Act to Strengthen Financial Market and Insurance Supervision (FinVAG). Second, the study estimates the influence of Ph.D.Share, professional concentration and supervisory power on bank-risk changes in consideration of the implementation of FinVAG. Therefore, the study is based on a sample of 246 German cooperative banks from 2006-2011 while applying four different measures of bank risk, namely credit-, equity-, liquidity-risk, and Z-Score, with the former three also being addressed in FinVAG. Results indicate that the implementation of FinVAG results in (most likely unintentional) structural changes, especially at the expense of farmers, and affects all risk measures and relations between risk measures and supervisory board characteristics in a risk-reducing and therefore intended way. To disentangle the complex relationship between board characteristics and risk measures, the study utilizes two-step system GMM estimator to account for unobserved heterogeneity and simultaneity in order to reduce endogeneity problems. The findings may be especially relevant for stakeholders, regulators, supervisors and managers.

Keywords: bank governance, bank risk-taking, board of directors, regulation

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Ali E. Abbas

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This paper highlights some of the normative issues that might result by setting independent thresholds in risk analyses and particularly with safety regions. A second objective is to explain how such regions can be specified appropriately in a meaningful way. We start with a review of the importance of setting deterministic trade-offs among target requirements. We then show how to determine safety regions for risk analysis appropriately using utility functions.

Keywords: decision analysis, thresholds, risk, reliability

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Authors: Tao Ding, Danjia Yan, Jinye Li, Chao Ren, Xinhua Hu

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The paper based on the research background of the current situation of water shortage in China and intelligent management of water resources in the information era. And the paper adopts WebGIS technology, combining the mathematical model of water resources management to develop a WebGIS-based water environment capacity inquiry and polluted water emission planning. The research significance of the paper is that it can inquiry the water environment capacity of Jinhua City in real time and plan how to drain polluted water into the river, so as to realize the effective management of water resources. This system makes sewage planning more convenient and faster. For the planning of the discharge enterprise, the decision on the optimal location of the sewage outlet can be achieved through calculation of the Sewage discharge planning model in the river, without the need for site visits. The system can achieve effective management of water resources and has great application value.

Keywords: sewerage planning, water environment capacity, water resources management, WebGIS

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Authors: Divine Kwaku Ahadzie

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Project management (PM) as a concept has evolved from the early 20th Century into a recognized academic and professional discipline, and indications are that it has come to stay in the 21st Century as a world-wide paradigm shift for managing successful construction projects. However, notwithstanding the strong inroads that PM has made in legitimizing its academic and professional status in construction management practice, the underlining philosophies are still based on cases and conventional practices. An important theoretical issue yet to be addressed is the lack of a universal theory that offers philosophical legitimacy for the PM concept as a uniquely specialized management concept. Here, it is hypothesized that the law of entropy, the theory of uncertainties and the theory of risk management offer plausible explanations for addressing the lacuna of what constitute PM theory. The theoretical bases of these plausible underlying theories are argued and attempts made to establish the functional relationships that exist between these theories and the PM concept. The paper then draws on data related to the success and/or failure of a number of construction projects to validate the theory.

Keywords: concepts, construction, project management, universal theory

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Authors: Won-Seok Kim, Hyung-Ik Shin

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Self-rated health (SRH) is a subjective assessment of individual health and has been identified as a strong predictor for mortality and morbidity. However few studies have been directed to the factors associated with SRH in persons with disabilities (PWD). We used data of 7th Korean national survey for 5307 PWD in 2008. Multiple logistic regression analysis was performed to find out independent risk factors for poor SRH in PWD. As a result, indicators of physical condition (poor instrumental ADL), socioeconomic disadvantages (poor education, economically inactive, low self-rated social class, medicaid in health insurance, presence of unmet need for hospital use) and social participation and networks (no use of internet service) were selected as independent risk factors for poor SRH in final model. Findings in the present study would be helpful in making a program to promote the health and narrow the gap of health status between the PWD.

Keywords: disabilities, risk factors, self-rated health, socioeconomic disadvantages, social networks

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

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Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

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Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: Nicholas Bayfield, Liam Bibo, Charley Budgeon, Robert Larbalestier, Tom Briffa

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Introduction: Stress hyperglycaemia is common following cardiac surgery. Its optimal management is uncertain and may differ by diabetic status. This study assesses the in-hospital glycaemic management of cardiac surgery patients and associated postoperative outcomes. Methods: A retrospective cohort analysis of all patients undergoing cardiac surgery at Fiona Stanley Hospital from February 2015 to May 2019 was undertaken. Management and outcomes of hyperglycaemia following cardiac surgery were assessed. Follow-up was assessed to 1 year postoperatively. Multivariate regression modelling was utilised. Results: 1050 non-diabetic patients and 689 diabetic patients were included. In the non-diabetic cohort, patients with mild (peak blood sugar level [BSL] < 14.3), transient stress hyperglycaemia managed without insulin were not at an increased risk of wound-related morbidity (P=0.899) or mortality at 1 year (P=0.483). Insulin management was associated with wound-related readmission to hospital (P=0.004) and superficial sternal wound infection (P=0.047). Prolonged or severe stress hyperglycaemia was predictive of hospital re-admission (P=0.050) but not morbidity or mortality (P=0.546). Diabetes mellitus was an independent risk factor 1-year mortality (OR; 1.972 [1.041–3.736], P=0.037), graft harvest site wound infection (OR; 1.810 [1.134–2.889], P=0.013) and wound-related readmission (OR; 1.866 [1.076–3.236], P=0.026). In diabetics, postoperative peak BSL > 13.9mmol/L was predictive of graft harvest site infections (OR; 3.528 [1.724-7.217], P=0.001) and wound-related readmission OR; 3.462 [1.540-7.783], P=0.003) regardless of modality of management. A peak BSL of 10.0-13.9 did not increase the risk of morbidity/mortality compared to a peak BSL of < 10.0 (P=0.557). Diabetics with a peak BSL of 13.9 or less did not have significantly increased morbidity/mortality outcomes compared to non-diabetics (P=0.418). Conclusion: In non-diabetic patients, transient mild stress hyperglycaemia following cardiac surgery does not uniformly require treatment. In diabetic patients, postoperative hyperglycaemia with peak BSL exceeding 13.9mmol/L was associated with wound-related morbidity and hospital readmission following cardiac surgery.

Keywords: cardiac surgery, pulmonary embolism, pulmonary embolectomy, cardiopulmonary bypass

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Authors: Armana Huq, Wahidur Rahman, Sanwar Kader

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Inland waterways in Bangladesh play an important role in providing comfortable and low-cost transportation. However, a maritime accident takes away many lives and creates unwanted hazards every year. This article deals with a comprehensive review of inland waterway accidents in Bangladesh. Additionally, it includes a comparative study between international and local inland research studies based on maritime accidents. Articles from inland waterway areas are analyzed in-depth to make a comprehensive overview of the nature of the academic work, accident and risk management process and different statistical analyses. It is found that empirical analysis based on the available statistical data dominates the research domain. For this study, major maritime accident-related works in the last four decades in Bangladesh (1981-2020) are being analyzed for preparing a bibliometric analysis. A study of maritime accidents of passenger's vessels during (1995-2005) indicates that the predominant causes of accidents in the inland waterways of Bangladesh are collision and adverse weather (77%), out of which collision due to human error alone stands (56%) of all accidents. Another study refers that the major causes of waterway accidents are the collision (60.3%) during 2005-2015. About 92% of this collision occurs due to direct contact with another vessel during this period. Rest 8% of the collision occurs by contact with permanent obstruction on waterway roots. The overall analysis of another study from the last 25 years (1995-2019) shows that one of the main types of accidents is collisions, with about 50.3% of accidents being caused by collisions. The other accident types are cyclone or storm (17%), overload (11.3%), physical failure (10.3%), excessive waves (5.1%), and others (6%). Very few notable works are available in testing or comparing the methods, proposing new methods for risk management, modeling, uncertainty treatment. The purpose of this paper is to provide an overview of the evolution of marine accident-related research domain regarding inland waterway of Bangladesh and attempts to introduce new ideas and methods to abridge the gap between international and national inland maritime-related work domain which can be a catalyst for a safer and sustainable water transportation system in Bangladesh. Another fundamental objective of this paper is to navigate various national maritime authorities and international organizations to implement risk management processes for shipping accident prevention in waterway areas.

Keywords: inland waterways, safety, bibliometric analysis, risk management, accidents

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Authors: A. A. Adebayo, O. Osibanjo

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Informal electronic waste (e-waste) processing is a crude method of recycling, which is on the increase in Nigeria. The release of hazardous substances such as heavy metals (HMs) into the environment during informal e-waste processing has been a major concern. However, there is insufficient information on environmental contamination from e-waste recycling, associated ecological risk in Alaba International Market, a major electronic market in Lagos, Nigeria. The aims of this study were to determine the levels of HMs in soil, resulting from the e-waste recycling; and also assess associated ecological risks in Alaba international market. Samples of soils (334) were randomly collected seasonally for three years from fourteen selected e-waste activity points and two control sites. The samples were digested using standard methods and HMs analysed by inductive coupled plasma optical emission. Ecological risk was estimated using Ecological Risk index (ER), Potential Ecological Risk index (RI), Index of geoaccumulation (Igeo), Contamination factor (Cf) and degree of contamination factor (Cdeg). The concentrations range of HMs (mg/kg) in soil were: 16.7-11200.0 (Pb); 14.3-22600.0 (Cu); 1.90-6280.0 (Ni), 39.5-4570.0 (Zn); 0.79-12300.0 (Sn); 0.02-138.0 (Cd); 12.7-1710.0 (Ba); 0.18-131.0 (Cr); 0.07-28.0 (V), while As was below detection limit. Concentrations range in control soils were 1.36-9.70 (Pb), 2.06-7.60 (Cu), 1.25-5.11 (Ni), 3.62-15.9 (Zn), BDL-0.56 (Sn), BDL-0.01 (Cd), 14.6-47.6 (Ba), 0.21–12.2 (Cr) and 0.22-22.2 (V). The trend in ecological risk index was in the order Cu > Pb > Ni > Zn > Cr > Cd > Ba > V. The potential ecological risk index with respect to informal e-waste activities were: burning > dismantling > disposal > stockpiling. The index of geo accumulation indices revealed that soils were extremely polluted with Cd, Cu, Pb, Zn and Ni. The contamination factor indicated that 93% of the studied areas have very high contamination status for Pb, Cu, Ba, Sn and Co while Cr and Cd were in the moderately contaminated status. The degree of contamination decreased in the order of Sn > Cu > Pb >> Zn > Ba > Co > Ni > V > Cr > Cd. Heavy metal contamination of Alaba international market environment resulting from informal e-waste processing was established. Proper management of e-waste and remediation of the market environment are recommended to minimize the ecological risks.

Keywords: Alaba international market, ecological risk, electronic waste, heavy metal contamination

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Authors: V. Davaakhuu, D. Tserendagva, D. Amarsaikhan, T. Altanstetseg

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In this study we aimed to detect main risk factors for diabetes in Mongolia and obtain data we used survey modified questionnaire. Survey data were obtained from 634 valid nurses (day work nurses-317, shift work nurses-317). Participants who were pregnant, less than 20 years old and no check for fasting glucose level were excluded from the survey in order to determine the risk factors of diabetes. Our study result shows the main risk factors of diabetes were physical inactivity, overweight and obesity, alcohol and tobacco use and lack of vegetable and fruit consumption. Peripheral blood glucose level was normal in subjects with BMI 26.28 ± 0.56, but 20 % of the subjects with normal blood glucose level were obese. Blood glucose level was higher in subjects with BMI 28.63 ± 2.32 and 36 % of them were obese. According to our study results, 3.62% of the surveyed population were identified having no diabetes risk factors, 52.3% were at risk, 28.8% were in higher risk for diabetes by the WHO criteria. In general, the prevalence of blood glucose were especially higher in shift work nurses.

Keywords: day work nurses, shift work nurses, BMI, WHR

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Authors: Nahashon Mwirigi

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The management of HIV/AIDS is a global challenge, demanding precise tools to predict disease progression and guide tailored treatment. CD4 cell count dynamics, a crucial immune function indicator, play an essential role in understanding HIV/AIDS progression and enhancing patient care through effective modeling. While several models assess disease progression, existing methods often fall short in capturing the complex, non-linear nature of HIV/AIDS, especially across diverse demographics. A need exists for models that balance predictive accuracy with clinical applicability, enabling individualized care strategies based on patient-specific progression rates. This study utilizes patient data from Kenyatta National Hospital (2003–2014) to model HIV/AIDS progression across six CD4-defined states. The Exponential, 2-Parameter Weibull, and 3-Parameter Weibull models are employed to analyze failure rates and explore progression patterns by age and gender. Model selection is based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to identify models best representing disease progression variability across demographic groups. The 3-Parameter Weibull model emerges as the most effective, accurately capturing HIV/AIDS progression dynamics, particularly by incorporating delayed progression effects. This model reflects age and gender-specific variations, offering refined insights into patient trajectories and facilitating targeted interventions. One key finding is that older patients progress more slowly through CD4-defined stages, with a delayed onset of advanced stages. This suggests that older patients may benefit from extended monitoring intervals, allowing providers to optimize resources while maintaining consistent care. Recognizing slower progression in this demographic helps clinicians reduce unnecessary interventions, prioritizing care for faster-progressing groups. Gender-based analysis reveals that female patients exhibit more consistent progression, while male patients show greater variability. This highlights the need for gender-specific treatment approaches, as men may require more frequent assessments and adaptive treatment plans to address their variable progression. Tailoring treatment by gender can improve outcomes by addressing distinct risk patterns in each group. The model’s ability to account for both accelerated and delayed progression equips clinicians with a robust tool for estimating the duration of each disease stage. This supports individualized treatment planning, allowing clinicians to optimize antiretroviral therapy (ART) regimens based on demographic factors and expected disease trajectories. Aligning ART timing with specific progression patterns can enhance treatment efficacy and adherence. The model also has significant implications for healthcare systems, as its predictive accuracy enables proactive patient management, reducing the frequency of advanced-stage complications. For resource limited providers, this capability facilitates strategic intervention timing, ensuring that high-risk patients receive timely care while resources are allocated efficiently. Anticipating progression stages enhances both patient care and resource management, reinforcing the model’s value in supporting sustainable HIV/AIDS healthcare strategies. This study underscores the importance of models that capture the complexities of HIV/AIDS progression, offering insights to guide personalized, data-informed care. The 3-Parameter Weibull model’s ability to accurately reflect delayed progression and demographic risk variations presents a valuable tool for clinicians, supporting the development of targeted interventions and resource optimization in HIV/AIDS management.

Keywords: HIV/AIDS progression, 3-parameter Weibull model, CD4 cell count stages, antiretroviral therapy, demographic-specific modeling

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Authors: Haruna Abdu Usman, J. Mohammed Umar, U. M. Bashir

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Solid waste management continued to be the biggest threat to the sustainability of urban centers of developing countries. Most streets corners of these urban centers are characterized by heaps of uncollected wastes at drains, public spaces and road sides destroying the aesthetic qualities and environmental ecosystems of these cities. Also, harboring disease vectors and rodents putting the health of the populace at risk, thus posing a serious challenge to the municipalities who are in most cases responsible for the solid waste management in these cities. The typical or commonest method adapted by these agencies in dealing with the solid waste management is the conventional approach; focusing mainly on waste collection ,treatment(composting and incineration)and disposal giving little consideration to the 3RS, of waste reduce, re-used and recycled. The resultant consequence being huge budget spending in solid waste management as high as 80% but little collection rate as low as 50%. This paper attempt to analyze the impacts and effects of the conventional solid waste management practices on the stakeholders in solid waste management; the municipal authorities, the communities, formal and informal waste managers, the NGOs and CBOs and suggests appropriate measures that would lessen the effects.

Keywords: conventional waste management, solid waste, waste stakeholders, developing countries

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Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska

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Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.

Keywords: safety climate, occupational health, civil engineering, productivity

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Jihene Jebeniani

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We proposed an approach combining both the techniques of experimental economy and the flexibility of discrete choice models in order to test the loss aversion. Our main objective was to test the loss aversion of the Cumulative Prospect Theory (CPT). We developed an experimental laboratory in the context of the financial investments that aimed to analyze the attitude towards the risk of the investors. The study uses the lotteries and is basing on econometric modeling. The estimated model was the ordered probit.

Keywords: risk aversion, behavioral finance, experimental economic, lotteries, cumulative prospect theory

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Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

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Authors: Min-Ming Wen

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Applying the U.S. lodging and tourism industry as a research sample, we examine the relation between the corporate governance structure and managerial risk-taking behavior. In light of the global financial crisis, the importance of effective governance structures is essential in protecting claimholder interests. We propose a governance structure consisting of shareholder governance measured by anti-takeover provisions to examine whether the governance structure has a significant impact on managerial risk-taking behaviors in terms of the investment policy. We will use capital expenditure and R&D investment to measure managerial risk-taking and the firm’s investment policy. In addition, we will examine whether the effects of governance on investment policy differ significantly between speculative and investment-grade firms.

Keywords: corporate governance, risk-taking, firm value, lodging industry

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Authors: Lana Singleton

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Achieving a sufficient global solution to climate change seems elusive through disappointing climate agreements and lack of cooperation. However, is this reluctance of coordination deep rooted on a more individual, societal level within countries due to a fundamental lack of social and institutional trust? The risks of climate change are illustrious and widely accepted, yet responses on an individual level are also largely inadequate. This research looks to further investigate types of trust, risk perception of climate change, and their interaction to build a greater understanding of whether a social trap (Rothstein, 2005) – where an absence of trust can overwhelm an individuals’ risk perception and result in minimal action despite knowing the dangers of no action – exists and where it is more prevalent. Presence of the social trap will be analysed for willingness to act in favour of climate change mitigation as well as attitude (acceptance) of different types of renewable energy forms. Using probit models with cross-sectional survey data on four developed European countries (UK, France, Germany, and Norway), we find evidence of the social trap in the aggregated data model, which highlights the importance of social trust regarding willingness to act in favour of climate mitigation as there is a high probability of action regardless of risk perception of climate change when social trust is high. In contrast, the same is not true for renewables, as interactions were mainly insignificant, although there were interesting findings involving institutional trust, gender, and country specific results for particular renewables.

Keywords: climate risk, renewables, risk perception, social trap, trust, willingness to act

Procedia PDF Downloads 95

Authors: Pangkaj Kumar Mahanta, Md. Rafizul Islam

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The rapid growth of the population causes a substantial amount of increase in household waste all over the world. Waste management is becoming one of the most challenging phenomena in the present day. The most environmentally friendly final disposal process of waste is sanitary landfilling, which is practiced in most developing countries. However, in Southeast Asia, most of the final disposal point is an open dump site. Due to the ignominy of proper management of waste and monitoring, the surrounding environment gets polluted more by the open dump site in comparison with a sanitary landfill. Khulna is 3rd largest metropolitan city in Bangladesh, having a population of around 1.5 million and producing approximately 450 tons per day of Municipal Solid Waste. The Municipal solid waste of Khulna city is disposed of in Rajbandh open dump site. The surrounding air is being polluted by the gas produced in the open dump site. Also, the open dump site produces leachate, which contains various heavy metals like Cadmium (Cd), Chromium (Cr), Lead (Pb), Manganese (Mn), Mercury (Hg), Strontium (Sr), etc. Leachate pollutes the soil as well as the groundwater of the open dump site and also the surrounding area through seepage. Moreover, during the rainy season, the surface water is polluted by leachate runoff. Also, the plastic waste flowing out from the open dump site through various drivers pollutes the nearby environment. The health risk assessment associated with heavy metals was carried out by computing the chronic daily intake (CDI), hazard quotient (HQ), and hazard index (HI) via different exposure pathways following the USEPA guidelines. For ecological risk, potential contamination index (Cp), Contamination factor (CF), contamination load index (PLI), numerical integrated contamination factor (NICF), enrichment factor (EF), ecological risk index (ER), and potential ecological risk index (PERI) were computed. The health risk and ecological risk assessment results reveal that some heavy metals possess strong health and ecological risk. In addition, the child faces higher harmful health risks from several heavy metals than the adult for all the exposure pathways and media. The conversion of an open dump site into a sanitary landfill and a proper management system can reduce the problems associated with an open dump site. In the sanitary landfill, the produced gas will be managed properly to save the surrounding atmosphere from being polluted. The seepage of leachate can be minimized by installing a compacted clay layer (CCL) as a baseline and leachate collection in a sanitary landfill to save the underlying soil layer and surrounding water bodies from leachate. Another important component of a sanitary landfill is the conversion of plastic waste to energy will minimize the plastic pollution in the landfill area and also the surrounding soil and water bodies. Also, in the sanitary landfill, the bio-waste can be used to make compost to reduce the volume of bio-waste and proper utilization of the landfill area.

Keywords: ecological risk, health risk, open dump site, sanitary landfill

Procedia PDF Downloads 193

Authors: Mohammed Alquraish

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Saudi Arabia and other emerging nations have faced significant challenges in the sustainable construction industry. This paper presents a quantitative approach to assessing sustainability risk in the Saudi Arabian construction industry and offers insights into holistic sustainability design in industry operations. The implementation of sustainable construction industry practices in the manufacturing sector has been susceptible to several risk factors that need to be identified. In order to successfully execute sustainable building projects, decision makers in the fields of construction and industry can benefit greatly from the advice this study offers by promoting the elements that motivate sustainability implementation. Sustainability risk can be measured from combining failure probability with cumulative effects from sustainability factors: social, environmental, and economic; that affect the integrity of the construction industry. The cumulative effects of sustainability risk are measured by classifying the outcomes resulting from these consequences. Operators of industrial construction can strategically manage and minimize potential disruptions affecting long-term sustainability incentives by measuring sustainability risk. Thus, the suggested strategy greatly reinforces the crucial role of the construction industry.

Keywords: sustainability, risk, construction industry, Saudi Arabia

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Authors: Mina Henneb, Rafik Belabbas, Safia Zenia

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The objective of this study was to determine the prevalence and to identify the risk factors of Eimeria spp. and Giardia spp. infection in rabbits from the local population of four localities in northern Algeria. Dung samples were collected from 16 farms, totalling 111 rabbits, and were analysed by the flotation method. Additional, data regarding the farms and management practices were obtained by means of a questionnaire used in the surveys and interviews. The results revealed that the prevalence of Eimerias pp. contamination was 68.75% (11/16) for farms and 58.56% (65/111) for rabbits, respectively. The prevalence of Giardia spp. was respectively 56.25% (9/16) for farms and 11.7% (13/111) for rabbits. The analyses showed that the prevalence of Eimeria spp. was significantly higher in the farms that did not comply with hygiene and non-conventional feeding and watering. However, the prevalence of Giardia spp. was significant in rabbits kept in poor conditions of rearing. In conclusion, this study showed that the prevalence of these two parasites in rabbits from the local population is relevant and may have important implications for the rabbit industry and public health, especially in rural areas.

Keywords: Algeria, digestive parasites, prevalence, rabbits, risk factors

Procedia PDF Downloads 171

Authors: Siti Rohana Mohd Yatim, Ku Halim Ku Hamid, Kamariah Noor Ismail, Zulkifli Abdul Rashid

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The aim of this study is to investigate odour emission profiles from storage of food waste and to assess the potential health risk caused by exposure to volatile compounds. Food waste decomposition process was conducted for 14 days and kept at 20°C and 30°C in self-made bioreactor. VOCs emissions from both samples were collected at different stages of decomposition starting at day 0, day 1, day 3, day 5, day 7, day 10, day 12 and day 14. It was analyzed using TD-GC/MS. Findings showed that various VOCs were released during decomposition of food waste. Compounds produced were influenced by time, temperature and the physico-chemical characteristics of the compounds. The most abundant compound released was dimethyl disulfide. Potential health risk of exposure to this compound is represented by hazard ratio, HR, calculated at 1.6 x 1011. Since HR equal to or less than 1.0 is considered negligible risk, this indicates that the compound posed a potential risk to human health.

Keywords: volatile organic compounds, decomposition process, food waste, health risk

Procedia PDF Downloads 520