Search results for: consumer’s risk

Authors: Ruchi Agarwal

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In today’s world, companies are operating in dynamic, uncertain and ambiguous business environments. Globally, more companies are failing due to Environmental, Social and Governance (ESG) factors than ever. Corporate governance and risk management are intertwined in nature. For decades, corporate governance and risk management have been influenced by internal and external factors. Three schools of thought have influenced risk governance for decades: Agency theory, Contingency theory, and Institutional theory. Agency theory argues that agents have interests conflicting with principal interests and the information problem. Contingency theory suggests that risk management adoption is influenced by internal and external factors, while Institutional theory suggests that organizations legitimize risk management with regulators, competitors, and professional bodies. The conflicting objectives of theories have created problems for executives in organizations in the adoption of Risk Governance. So far, there are many studies that discussed risk culture and the role of actors in risk governance, but there are rare studies discussing the role of risk culture in the adoption of risk governance from a leadership style perspective. This study explores the adoption of risk governance in two contrasting industries, such as the Insurance and energy business, to understand whether risk governance is influenced by internal/external factors or whether risk culture is influenced by leaders. We draw empirical evidence by comparing the cases of an Indian insurance company and a renewable energy-based firm in India. We interviewed more than 20 senior executives of companies and collected annual reports, risk management policies, and more than 10 PPTs and other reports from 2017 to 2024. We visited the company for follow-up questions several times. The findings of my research revealed that both companies have used risk governance for strategic renewal of the company. Insurance companies use a transactional leadership style based on performance and reward for improving risk, while energy companies use rather symbolic management to make debt restructuring meaningful for stakeholders. Overall, both companies turned from loss-making to profitable ones in a few years. This comparative study highlights the role of different leadership styles in the adoption of risk governance. The study is also distinct as previous research rarely studied risk governance in two contrasting industries in reference to leadership styles.

Keywords: leadership style, corporate governance, risk management, risk culture, strategic renewal

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Authors: Samuel Capintero, Ole H. Petersen

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This paper examines the utilization of public-private partnerships for the building and operation of wastewater treatment plants. Our research focuses on risk allocation in this kind of projects. Our analysis builds on more than hundred wastewater treatment plants built and operated through PPP projects in Aragon (Spain). The paper illustrates the consequences of an inadequate management of construction risk and an unsuitable transfer of demand risk in wastewater treatment plants. It also shows that the involvement of many public bodies at local, regional and national level further increases the complexity of this kind of projects and make time delays more likely.

Keywords: wastewater, treatment plants, PPP, construction

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Authors: Jayaletchumi T. Sambantha Moorthy, Suhaimi bin Ibrahim, Mohd Naz’ri Mahrin

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Most quality models have defined usability as a significant factor that leads to improving product acceptability, increasing user satisfaction, improving product reliability, and also financially benefiting companies. Usability is also the best factor that acts as a balance for both the technical and human aspects of a software product, which is an important aspect in defining quality during software development process. A usability risk can be defined as a potential usability risk factor that a chosen action or activity may lead to a possible loss or an undesirable outcome. This could impact the usability of a software product thereby contributing to negative user experiences and causing a possible software product failure. Hence, it is important to mitigate and reduce usability risks in the software development process itself. By managing possible involved usability risks in software development process, failure of software product could be reduced. Therefore, this research uses the Delphi method to identify mitigation plans to reduce potential usability risks. The Delphi method is conducted with seven experts from the field of risk management and software development.

Keywords: usability, usability risk, risk management, risk mitigation, delphi study

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Authors: Iqbal Pramukti, Mamat Lukman, Hasniatisari Harun, Kusman Ibrahim

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Introduction: People living with HIV had a higher risk of osteoporotic fracture than the general population. The purpose of this study was to predict the 10-year risk of fracture among people living with HIV (PLWH) using FRAX™ and to identify characteristics related to the fracture risk. Methodology: This study consisted of 75 subjects. The ten-year probability of major osteoporotic fractures (MOF) and hip fractures was assessed using the FRAX™ algorithm. A cross-tabulation was used to identify the participant’s characteristics related to fracture risk. Results: The overall mean 10-year probability of fracture was 2.4% (1.7) for MOF and 0.4% (0.3) for hip fractures. For MOF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use showed a higher MOF score than those who were not (3.1 vs. 2.5; 4.6 vs 2.5; and 3.4 vs 2.5, respectively). For HF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use also showed a higher HF score than those who were not (0.5 vs. 0.3; 0.8 vs. 0.3; and 0.5 vs. 0.3, respectively). Conclusions: The 10-year risk of fracture was higher among PLWH with several factors, including the parent’s hip. Fracture history, smoking behavior and glucocorticoid used. Further analysis on determining factors using multivariate regression analysis with a larger sample size is required to confirm the factors associated with the high fracture risk.

Keywords: HIV, PLWH, osteoporotic fractures, hip fractures, 10-year risk of fracture, FRAX

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Authors: Siti Dewi Aisyah

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The rise of the Internet in the late twentieth century rapidly gains information and understands the world through screens. The digital way of communication through the Internet becomes an ordinary daily pattern. In the digital era, Fashion has been tremendously shared on social media platform especially because of the emergence of #OOTD (Outfit of the Day). Fashion cannot survive without the media. The media have played a vital role in shaping fashion into the complex cultural phenomenon it has become, and fashion has become an intrinsic part of today’s visual culture, and vice versa. Islamic Muslim Fashion has become a trend in Indonesia. It is said that social media has a huge impact in its development. Indonesia is ranked among the most users of social media. That is why people who wear hijab also use social media for different purposes, one of this is to introduce hijab fashion. Consequently, they are becoming famous in social media. Social media has become a tool for communicating their beliefs as a Muslim as well as personal branding as a good hijabi yet with a fashionable style. This study will examine how social media especially Blog and Instagram can lead the movement of Islamic Modest Fashion in Indonesia, how it triggers the consumer culture to hijabi, how they visualize their style in their social media. This research had been conducted through in-depth interviews with several bloggers who created Hijabers Community who have made a new trend in Islamic fashion and also Instagrammers who made their feeds as a style inspiration. This research is based on empirical research with qualitative methods (text and picture analysis). The methodology used for this research is by analyzing Blog and Instagram through visual analysis on the social media especially about the Islamic Modest Fashion trend. This research also contains a literature review of a diverse group of works on topics related to the study. This research will be examined through several theoretical frameworks including the study of social media, visual analysis and consumer culture. Fashion and consumer culture are also two main topics because fashion furthermore leads to consumer culture. The benefit of this research is for gaining the insight how social media can visualize the trend in hijab fashion style of Indonesian people.

Keywords: blog, consumer culture, hijab fashion, instagram, style, visual analysis

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Authors: A. Ballard

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The ability to track goods and products en route in the delivery system, in the warehouse, and on the top floor is a huge advantage to shippers and retailers. Recently the emergence of radio frequency identification (RFID) technology has enabled this better than ever before. However, a significant problem exists in that RFID technology depends on the quality of the information stored for each tagged product. Because of the profusion of names for colours, it is very difficult to ascertain that stored values are recognised by all users who view the product visually. This paper reports the findings of a study in which 50 consumers and 50 logistics workers were shown colour swatches and asked to choose the name of the colour from a multiple choice list. They were then asked to match consumer products, including toasters, jumpers, and toothbrushes, with the identifying inventory information available for each one. The findings show that the ability to match colours was significantly stronger with the color swatches than with the consumer products and that while logistics professionals made more frequent correct identification than the consumers, their results were still unsatisfactorily low. Based on these findings, a proposed universal model of colour identification numbers has been developed.

Keywords: consumer preferences, supply chain logistics, radio frequency identification, RFID, colour preference

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Authors: Pitsanu Tongkhow, Pichet Jiraprasertwong

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This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.

Keywords: defective autoparts products, Bayesian framework, generalized linear mixed model (GLMM), risk factors

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Authors: Emmanuelle Merat, Arnaud Aubert, Sophie Cambos, Francis Vial, Patrick Beau

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Basically, consumers are sensitive to many stimuli when applying a cream: brand, packaging and indeed formulation compositions. Many studies demonstrated the influence of some stimuli such as brand, packaging, formula color and odor (e.g. in make-up applications). Those parameters influence perceived quality of the product. The objective of this work is to further investigate the relationship between nude skincare basic compositions with different textures and consumer experience. A tentative final step will be to connect the consumer feelings with key ingredients in the compositions. A new approach was developed to better understand touch-related subjective experience in consumers based on a combination of methods: sensory analysis with ten experts, preference mapping on one hundred female consumers and emotional assessments on thirty consumers (verbal and non-verbal through prosody and gesture monitoring). Finally, a methodology based on ‘sensorial trip’ (after olfactory, haptic and musical stimuli) has been experimented on the most interesting textures with 10 consumers. The results showed more or less impact depending on compositions and also on key ingredients. Three types of formulation particularly attracted the consumer: an aqueous gel, an oil-in-water emulsion, and a patented gel-in-oil formulation type. Regarding these three formulas, the preferences were both revealed through sensory and emotion tests. One was recognized as the most innovative in consumer sensory test whereas the two other formulas were discriminated in emotions evaluation. The positive emotions were highlighted especially in prosody criteria. The non-verbal analysis, which corresponds to the physical parameters of the voice, showed high pitch and amplitude values; linked to positive emotions. Verbatim, verbal content of responses (i.e., ideas, concepts, mental images), confirmed the first conclusion. On the formulas selected for their positive emotions generation, the ‘sensorial trip’ provided complementary information to characterize each emotional profile. In the second step, dedicated to better understand ingredients power, two types of ingredients demonstrated an obvious input on consumer preference: rheology modifiers and emollients. As a conclusion, nude cosmetic compositions with well-chosen textures and ingredients can positively stimulate consumer emotions contributing to capture their preference. For a complete achievement of the study, a global approach (Asia, America territories...) should be developed.

Keywords: sensory, emotion, cosmetic formulations, ingredients' influence

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Authors: Jorge M. Uribe

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We propose a methodology for setting the price of an insurance contract targeted to manage the risk associated with weather conditions that affect variable renewable energy generation. The methodology relies on conditional quantile regressions to estimate the weather risk of a solar panel. It is illustrated using real daily radiation and weather data for three cities in Spain (Valencia, Barcelona and Madrid) from February 2/2004 to January 22/2019. We also adapt the concepts of value at risk and expected short fall from finance to this context, to provide a complete panorama of what we label as weather risk. The methodology is easy to implement and can be used by insurance companies to price a contract with the aforementioned characteristics when data about similar projects and accurate cash flow projections are lacking. Our methodology assigns a higher price to an insurance product with the stated characteristics in Madrid, compared to Valencia and Barcelona. This is consistent with Madrid showing the largest interquartile range of operational deficits and it is unrelated to the average value deficit, which illustrates the importance of our proposal.

Keywords: insurance, weather, vre, risk

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Authors: Abderrazek Ben Maatoug, Ibrahim Fatnassi, Wassim Ben Ayed

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In this paper we investigate the issue of market risk quantification for Middle East and North Africa (MENA) Islamic market equity. We use Value-at-Risk (VaR) as a measure of potential risk in Islamic stock market, for long and short position, based on Riskmetrics model and the conditional parametric ARCH class model volatility with normal, student and skewed student distribution. The sample consist of daily data for the 2006-2014 of 11 Islamic stock markets indices. We conduct Kupiec and Engle and Manganelli tests to evaluate the performance for each model. The main finding of our empirical results show that (i) the superior performance of VaR models based on the Student and skewed Student distribution, for the significance level of α=1% , for all Islamic stock market indices, and for both long and short trading positions (ii) Risk Metrics model, and VaR model based on conditional volatility with normal distribution provides the best accurate VaR estimations for both long and short trading positions for a significance level of α=5%.

Keywords: value-at-risk, risk management, islamic finance, GARCH models

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Authors: Seung Hun Lee, Sang Yeoup Lee

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Objectives: To investigate associations between degrees of obesity using correlations between obesity indices and cardiometabolic risk factors. Methods: BMI, waist circumference (WC), fasting insulin, fasting glucose, lipids, and visceral adipose tissue (VAT) area using computed tomographic images were measured in 113 obese female without cardiovascular disease (CVD). Correlations between obesity indices and cardiometabolic risk factors were analyzed in obese subgroups defined using sequential obesity indices. Results: Mean BMI and WC were 29.6 kg/m2 and 92.8 cm. BMI showed significant correlations with all five cardiometabolic risk factors until the BMI cut-off point reached 27 kg/m2, but when it exceeded 30 kg/m2, correlations no longer existed. WC was significantly correlated with all five cardiometabolic risk factors up to a value of 85 cm, but when WC exceeded 90 cm, correlations no longer existed. Conclusions: Our data suggest that moderate weight-loss goals may not be enough to ameliorate cardiometabolic markers in severely obese patients. Therefore, individualized weight-loss goals should be recommended to such patients to improve health benefits.

Keywords: correlation, cardiovascular disease, risk factors, obesity

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Authors: Shervin Alaei, Reza Moradi

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Trading in financial markets is subject to risks due to their high volatilities. Here, using an LSTM neural network, and by doing some risk-based feature engineering tasks, we developed a method that can accurately predict trends of the Tehran stock exchange market index from a few days ago. Our test results have shown that the proposed method with an average prediction accuracy of more than 94% is superior to the other common machine learning algorithms. To the best of our knowledge, this is the first work incorporating deep learning and risk factors to accurately predict market trends.

Keywords: deep learning, LSTM, trend prediction, risk management, artificial neural networks

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Authors: Pubudu K. Hitigala Kaluarachchilage, Champike Attanayake, Sasith Rajasooriya, Chris P. Tsokos

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Operating system (OS) security is a key component of computer security. Assessing and improving OSs strength to resist against vulnerabilities and attacks is a mandatory requirement given the rate of new vulnerabilities discovered and attacks occurring. Frequency and the number of different kinds of vulnerabilities found in an OS can be considered an index of its information security level. In the present study five mostly used OSs, Microsoft Windows (windows 7, windows 8 and windows 10), Apple’s Mac and Linux are assessed for their discovered vulnerabilities and the risk associated with each. Each discovered and reported vulnerability has an exploitability score assigned in CVSS score of the national vulnerability database. In this study the risk from vulnerabilities in each of the five Operating Systems is compared. Risk Indexes used are developed based on the Markov model to evaluate the risk of each vulnerability. Statistical methodology and underlying mathematical approach is described. Initially, parametric procedures are conducted and measured. There were, however, violations of some statistical assumptions observed. Therefore the need for non-parametric approaches was recognized. 6838 vulnerabilities recorded were considered in the analysis. According to the risk associated with all the vulnerabilities considered, it was found that there is a statistically significant difference among average risk levels for some operating systems, indicating that according to our method some operating systems have been more risk vulnerable than others given the assumptions and limitations. Relevant test results revealing a statistically significant difference in the Risk levels of different OSs are presented.

Keywords: cybersecurity, Markov chain, non-parametric analysis, vulnerability, operating system

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Authors: James Kinsella

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There is currently very little understanding of how the interaction between in- vestors, consumers, the firms (agents) affect a) the transmission of information, and b) the creation and transfer of value and wealth between these two groups. Employing scholarly ideas from multiple research areas (behavioural finance, emotional finance, econo-biology, and game theory) we develop a conceptual the- oretic model (the ‘bow-tie’ model) as a framework for considering this interaction. Our bow-tie model views information transfer, value and wealth creation, and transfer through the lens of “investor-consumer connection facilitated through the communicative medium of the ‘firm’ (agents)”. We confront our bow-tie model with theoretical and practical examples. Next, we utilise consumer and business confidence data alongside index data, to conduct quantitative analy- sis, to support our bow-tie concept, and to introduce the concept of “investor- consumer connection”. We highlight the importance of information persuasiveness, knowledge, and emotional categorization of characteristics in facilitating a communicative relationship between investors, consumers, and the firm (agents), forming academic and practical applications of the conceptual bow-tie model, alongside applications to wider instances, such as those seen within the Covid-19 pandemic.

Keywords: behavioral finance, emotional finance, economy-biology, social mood

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Authors: Kitti Leangkrua

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This paper presents a risk-based maintenance strategy of a power transformer in order to optimize operating and maintenance costs. The methodology involves the study and preparation of a database for the collection the technical data and test data of a power transformer. An evaluation of the overall condition of each transformer is performed by a program developed as a result of the measured results; in addition, the calculation of the main equipment separation to the overall condition of the transformer (% HI) and the criteria for evaluating the importance (% ImI) of each location where the transformer is installed. The condition assessment is performed by analysis test data such as electrical test, insulating oil test and visual inspection. The condition of the power transformer will be classified from very poor to very good condition. The importance is evaluated from load criticality, importance of load and failure consequence. The risk matrix is developed for evaluating the risk of each power transformer. The high risk power transformer will be focused firstly. The computerized program is developed for practical use, and the maintenance strategy of a power transformer can be effectively managed.

Keywords: asset management, risk-based maintenance, power transformer, health index

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Authors: Minjuan Sun

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Ever since the late 1990s, China has experienced explosive growth in consumer lending, especially in short-term consumer loans, among which, the growth rate of non-bank lending has surpassed bank lending due to the development in financial technology. On the other hand, China does not have a universal credit scoring and registration system that can guide lenders during the processes of credit evaluation and risk control, for example, an individual’s bank credit records are not available for online lenders to see and vice versa. Given this context, the purpose of this paper is three-fold. First, we explore if and how alternative digital footprint data can be utilized to assess borrower’s creditworthiness. Then, we perform a comparative analysis of machine learning methods for the canonical problem of credit default prediction. Finally, we analyze, from an institutional point of view, the necessity of establishing a viable and nationally universal credit registration and scoring system utilizing online digital footprints, so that more people in China can have better access to the consumption loan market. Two different types of digital footprint data are utilized to match with bank’s loan default records. Each separately captures distinct dimensions of a person’s characteristics, such as his shopping patterns and certain aspects of his personality or inferred demographics revealed by social media features like profile image and nickname. We find both datasets can generate either acceptable or excellent prediction results, and different types of data tend to complement each other to get better performances. Typically, the traditional types of data banks normally use like income, occupation, and credit history, update over longer cycles, hence they can’t reflect more immediate changes, like the financial status changes caused by the business crisis; whereas digital footprints can update daily, weekly, or monthly, thus capable of providing a more comprehensive profile of the borrower’s credit capabilities and risks. From the empirical and quantitative examination, we believe digital footprints can become an alternative information source for creditworthiness assessment, because of their near-universal data coverage, and because they can by and large resolve the "thin-file" issue, due to the fact that digital footprints come in much larger volume and higher frequency.

Keywords: credit score, digital footprint, Fintech, machine learning

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Authors: Marc S. Paolella, Pawel Polak

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The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

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Authors: Lina Zhong, Sunny Sun, Rob Law

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Artificial intelligence has been developing rapidly. Previous studies have evaluated hotel technology either from an employee or consumer perspective. However, impacts, which mainly include the social and economic impacts of hotel robots, are unknown as they are newly introduced. To bridge the aforementioned research gap, this study evaluates hotel robots from contextual, diagnostic, evaluative, and strategic aspects using framework analysis as a basis to assist hotel managers in real-time hotel marketing strategy management, adjustment and revenue achievement. Findings show that, from a consumer perspective, the overall acceptance of hotel robots is low. The main implication is that the cost of hotel robots should be carefully estimated, and the investment should be made based on phases.

Keywords: application, evaluation, framework analysis, hotel robot

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Authors: Wlodzimierz Ogryczak, Michal Przyluski, Tomasz Sliwinski

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In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules.

Keywords: portfolio optimization, reward-risk ratio, mean absolute deviation, linear programming

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Authors: Worku Dejene Bekele, András Marczika Csilla Sörös

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Silver nanoparticles are silver metal with a size of 1-100nm. The most common source of silver nanoparticles is inorganic salts. Nanoparticles can be ingested through our foods and constitute nanoparticles and silver ions, whether as an additive or by migrants and, in some cases, as a pollutant. Silver nanoparticles are the most widely applicable engineered nanomaterials, especially for antimicrobial function. Ag nanoparticles give different advantages in the case of food safety, quality, and overall acceptability; however, they affect the health of humans and animals, putting them at risk of health problems and environmental pollution. Silver nanoparticles have been used widely in food packaging technologies, especially in water treatments, meat and meat products, fruit, and many other food products. This is for bio-preservation from food products. The primary goal of this review is to determine the safety and health impact of Ag nanoparticles application in food packaging and analysis of the human organs more affected by this preservative technology, to assess the implications of a nanoparticle on food safety, to determine the effects of nanoparticles on consumers health and to determine the impact of nanotechnology on product acceptability. But currently, much research has demonstrated that there is cause to believe that silver nanoparticles may have toxicological effects on biological organs and systems. The silver nanoparticles affect DNA expression, gastrointestinal barriers, lungs, and other breathing organs illness. Silver particles and molecules are very toxic. During its application in food packaging, food industries used the thinnest particle. This particle can potentially affect the gastrointestinal tracts-it suffers from mucus production, DNA, lungs, and other breezing organs. This review is targeted to demonstrate the knowledge gap that industrials use in the application of silver nanoparticles in food packaging and preservation and its health effects on the consumer.

Keywords: food preservatives, health impact, nanoparticle, silver nanoparticle

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Authors: Ljiljana Seric, Vladimir Divic, Marin Bugaric

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This paper presents methodology for spatial analysis of GIS data that is used for assessing the microlocation risk index from potential damages of high winds. The analysis is performed on freely available GIS data comprising information about wind load, terrain cover and topography of the area. The methodology utilizes the legislation of Eurocode norms for determination of wind load of buildings and constructions. The core of the methodology is adoption of the wind load parameters related to location on geographical spatial grid. Presented work is a part of the Wind Risk Project, supported by the European Commission under the Civil Protection Financial Instrument of the European Union (ECHO). The partners involved in Wind Risk project performed Wind Risk assessment and proposed action plan for three European countries – Slovenia, Croatia and Germany. The proposed method is implemented in GRASS GIS open source GIS software and demonstrated for Case study area of wider area of Split, Croatia. Obtained Wind Risk Index is visualized and correlated with critical infrastructures like buildings, roads and power lines. The results show good correlation between high Wind Risk Index with recent incidents related to wind.

Keywords: Eurocode norms, GIS, spatial analysis, wind distribution, wind risk

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Authors: Renee Fabian, Jordan Davidson

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Current research on non-suicidal self-injury (NSSI) provides ample insights on best practices for caregivers and clinicians to address and reduce NSSI behavior among adolescents. However, the efficacy of evidenced-based NSSI interventions and their delivery from the perspective of adolescent patients does not receive significant attention, creating a gap between the efficacy of research-based NSSI interventions and adolescent perceptions of NSSI treatment and adolescent willingness to engage in NSSI interventions. To address the gap between practice and patient perspectives and inform more effective treatment outcomes, the current survey aims to identify major patient-reported adverse reactions to NSSI disclosures from caregivers, treating mental health clinicians, and medical professionals using a mixed methods survey of 2,500 people with a history of NSSI completed by editors at a consumer-facing health publication. Based on the analyzed results of the survey, a majority of adolescents with a history of NSSI found parents and caregivers ineffective at empathetically addressing NSSI, and a significant number of participants reported at least one treating mental health professional inadequately responded to NSSI behaviors, in addition to other findings of adverse reactions to NSSI disclosures that serve as a barrier to treatment. NSSI is a significant risk factor for future suicide attempts. Addressing patient-reported adverse reactions to NSSI disclosures in the adolescent population can remove barriers to the effectiveness of caregiver and clinician NSSI interventions and reduce the risk of NSSI-related harm and lower the risk of future suicide attempts or completions.

Keywords: adolescent self-injury, non-suicidal self-injury, patient perspectives, self-harm interventions

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Authors: Pegah Farshadmanesh, Jamshid Mohammadi, Mehdi Modares

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In nearly all earthquakes of the past century that resulted in moderate to significant damage, the occurrence of postearthquake fire ignition (PEFI) has imposed a serious hazard and caused severe damage, especially in urban areas. In order to reduce the loss of life and property caused by post-earthquake fires, there is a crucial need for predictive models to estimate the PEFI risk. The parameters affecting PEFI risk can be categorized as: 1) factors influencing fire ignition in normal (non-earthquake) condition, including floor area, building category, ignitability, type of appliance, and prevention devices, and 2) earthquake related factors contributing to the PEFI risk, including building vulnerability and earthquake characteristics such as intensity, peak ground acceleration, and peak ground velocity. State-of-the-art statistical PEFI risk models are solely based on limited available earthquake data, and therefore they cannot predict the PEFI risk for areas with insufficient earthquake records since such records are needed in estimating the PEFI model parameters. In this paper, the correlation between normal condition ignition risk, peak ground acceleration, and PEFI risk is examined in an effort to offer a means for predicting post-earthquake ignition events. An illustrative example is presented to demonstrate how such correlation can be employed in a seismic area to predict PEFI hazard.

Keywords: fire risk, post-earthquake fire ignition (PEFI), risk management, seismicity

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Authors: Timur Zhukov, Yuko Yamashita

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Music as a product of hedonic consumption has been researched at least since the early 20th century, but little light has been shed on how language affects its consumption process. At the intersection of music consumption, language impact, and consumer behavior, this research explores the influence of language on music consumption in Japan. Its aim is to clarify how listening to music in different languages affects the listener’s purchase intention and sharing intention by conducting a survey where respondents listen to three versions of the same song in different languages in random order. It uses an existing framework that views the flow of music consumption as a combination of responses (emotional response, sensory response, imaginal response, analytical responses) affecting the experiential response, which then affects the overall affective response, followed by the need to reexperience and lastly the purchase intention. In this research, the sharing intention has been added to the model to better fit the modern consumption model (e.g., AISAS). This research shows how positive and negative emotions and imaginal and analytical responses change depending on the language and what impact it has on consumer behavior. It concludes by proposing how modern music businesses can learn from the language differences and cater to the needs of the audiences who speak different languages.

Keywords: AISAS, consumer behavior, first language, music consumption, second language

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Authors: Jiyoung Lee, Andrew D. Gershoff, Jerry Jisang Han

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Most extant research on consumer privacy concerns and their willingness to share personal data has focused on contextual factors (e.g., types of information collected, type of compensation) that lead to consumers’ personal information disclosure. Unfortunately, the literature lacks a clear understanding of how consumers’ incidental psychological needs may influence consumers’ decisions to share their personal information with companies or brands. In this research, we investigate how social exclusion, which is an increasing societal problem, especially since the onset of the COVID-19 pandemic, leads to increased information disclosure intentions for consumers. Specifically, we propose and find that when consumers become socially excluded, their desire for social connection increases, and this desire leads to a greater willingness to disclose their personal information with firms. The motivation to form and maintain interpersonal relationships is one of the most fundamental human needs, and many researchers have found that deprivation of belongingness has negative consequences. Given the negative effects of social exclusion and the universal need to affiliate with others, people respond to exclusion with a motivation for social reconnection, resulting in various cognitive and behavioral consequences, such as paying greater attention to social cues and conforming to others. Here, we propose personal information disclosure as another form of behavior that can satisfy such social connection needs. As self-disclosure can serve as a strategic tool in creating and developing social relationships, those who have been socially excluded and thus have greater social connection desires may be more willing to engage in self-disclosure behavior to satisfy such needs. We conducted four experiments to test how feelings of social exclusion can influence the extent to which consumers share their personal information with brands. Various manipulations and measures were used to demonstrate the robustness of our effects. Through the four studies, we confirmed that (1) consumers who have been socially excluded show greater willingness to share their personal information with brands and that (2) such an effect is driven by the excluded individuals’ desire for social connection. Our findings shed light on how the desire for social connection arising from exclusion influences consumers’ decisions to disclose their personal information to brands. We contribute to the consumer disclosure literature by uncovering a psychological need that influences consumers’ disclosure behavior. We also extend the social exclusion literature by demonstrating that exclusion influences not only consumers’ choice of products but also their decision to disclose personal information to brands.

Keywords: consumer-brand relationship, consumer information disclosure, consumer privacy, social exclusion

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Authors: Izzudin Busnaina

Abstract:

An important question for marketers in the international arena is whether the consumer’s responses (i.e., sentiment and behavioral aspects) toward the global marketing programs in developing countries depend on culture. In a study representing a large sample of consumers and four different home appliances country-of-origin global operators in Libya, the author explores the potential role of culture on Arab consumers' responses toward foreign marketing programs. Results indicate that although the foreign companies have a tendency to adopted standardization perspective, this does not impact on consumers’ responses in a single cultural context toward marketing. The findings reveal that buying behavior was more a function of individual difference than of national cultural context. Further, the results suggest that for mainstream home appliances, segmenting on the basis of nationality is probably unnecessary and that a standardized approach would likely be successful across an increasingly relevant Arab world; and that continuing perceptions of Arab insularity are likely to be misplaced. Faced with the effectiveness of globally efficient marketing programs, local manufacturers would need to work hard to identify particular niche segments where a culturally-specific appeal might be more successful.

Keywords: arab world, buyer’s characteristics, consumer behavior, home appliances, marketing program

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Authors: Evelyne Nguegwouo, Raoul Fonkem Sonfack Tsakem, Abel Wade, Gabriel Nama Medoua, Kamgaing Theophile

Abstract:

Fresh and smoked fish are widely consumed in Cameroon. The traditional nature of smoking, the lack of hygiene in production, the poor preservation of stocks and the long storage time for certain types of fish considerably favor the contamination of products by molds, which secrete toxic molecules called mycotoxins. Today there are more than 400 types of mycotoxins, Aflatoxins being the most formidable. These toxins are considered carcinogenic in humans. It is in this perspective that we proposed to evaluate the total Aflatoxins in the fish marketed and consumed by the populations of the city of Yaoundé in Cameroon. On the one hand, it was a question of conducting a survey of fish consumers and sellers in points of sale, sampling fish of three species [Marquereau (Scomber scombrus), Cod (Gadus morhua) and Bifaka (Ethmalosa fimbriata)], randomly in some markets of the city to evaluate the total Aflatoxins contents (B1, B2, G1, G2) by the quantitative ELISA method and finally to estimate the level of exposure of the populations. It emerges from this study that of the 30 samples analyzed, 96.1% contained total Aflatoxins and two samples had total Aflatoxins levels above the standard, which is 20 ppb. These first results show that the risk is present in Cameroon and in order to improve the quality of marketed fish in terms of mycotoxins, a more thorough control must be done from the production chain to the consumer.

Keywords: aflatoxins, evaluation, exposure, mycotoxins, fish

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Authors: Sunita Patel

Abstract:

Cardiovascular diseases are the leading cause of morbidity as well as mortality in India. Objective of this study is to examine CVDs prevalence and identify their behavioral and cultural risk factors with the help of SAGE-2007 data conducted on 6th states in India. Findings reveal that 18.3% of people diagnosed with CVDs in India. Higher disease occurs in an increasing rate between ages of 30-39 having OR 2.45 (CI: 1.66-3.63) and 70+ age OR 7.45 (CI: 4.82-11.49) times higher compare to 18-29 age group respectively. Wealth quintile higher CVD occurs as 3rd in 60% (CI: 1.16-2.21) and in richest 5th quintile 58% (CI: 1.13-2.21) contrast to lowest quintile. Relative risk depicted that 22.4% in moderate and 44% in vigorous activity have less chance of diseases compare to who performed no work and those who consumed alcohol. Results reveal that policy prospect should be recommended and that it would be beneficial for awareness of people and their future.

Keywords: behavioral risk, cultural risk, cardio-vascular diseases, wealth quintile

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Authors: George Mariano Soriano

Abstract:

In this study, a Rapid Earthquake Risk Ranking Criteria was formulated by integrating various existing maps and databases by the Department of Public Works and Highways (DPWH) and Philippine Institute of Volcanology and Seismology (PHIVOLCS). Utilizing Geographic Information System (GIS) software, the above-mentioned maps and databases were used in extracting seismic hazard parameters and bridge vulnerability characteristics in order to rank the seismic damage risk rating of bridges in the National Capital Region.

Keywords: bridge, earthquake, GIS, hazard, risk, vulnerability

Procedia PDF Downloads 383

Authors: A. Grilec, S. Petrak, M. Mahnic Naglic

Abstract:

Technological development and the globalization in production and sales of clothing in the last decade have significantly influenced the changes in consumer relationship with the industrial-fashioned apparel and in the way of clothing purchasing. The Internet sale of clothing is in a constant and significant increase in the global market, but the possibilities offered by modern computing technologies in the customization segment are not yet fully involved, especially according to the individual customer requirements and body sizes. Considering the growing trend of online shopping, the main goal of this paper is to investigate the differences in customer perceptions towards online apparel shopping and particularly to discover the main differences in perceptions between customers regarding three different body sizes. In order to complete the research goal, the quantitative study on the sample of 85 Croatian consumers was conducted in 2017 in Zagreb, Croatia. Respondents were asked to indicate their level of agreement according to a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). To analyze attitudes of respondents, simple and descriptive statistics were used. The main findings highlight the differences in respondent perception of 3D body scanning, using 3D body scanning in Internet shopping, online apparel shopping habits regarding their body sizes.

Keywords: consumer behavior, Internet, 3D body scanning, body types

Procedia PDF Downloads 136