A fuzzy-QFD approach for the enhancement of work equipment safety: a case study in the agriculture sector

The paper proposes a design for safety methodology based on the use of the Quality Function Deployment (QFD) method, focusing on the need to identify and analyse risks related to a working task in an effective manner, i.e. considering the specific work activities related to such a task. To reduce the drawbacks of subjectivity while augmenting the consistency of judgements, the QFD was augmented by both the Delphi method and the fuzzy logic approach. To verify such an approach, it was implemented through a case study in the agricultural sector. While the proposed approach needs to be validated through further studies in different contexts, its positive results in performing hazard analysis and risk assessment in a comprehensive and thorough manner can contribute practically to the scientific knowledge on the application of QFD in design for safety activities

Application of Artificial Neural Networks to Assess Student Happiness

The purpose of this study is to develop an analytical assessment approach to identify the main factors that affect graduate students\u27 happiness level. The two methods, multiple linear regression (MLR) and artificial neural networks (ANN), were employed for analytical modelling. A sample of 118 students at a small non-profit private university constituted the survey pool. Various factors including education, school facilities, health, social activities, and family were taken into consideration as a result of literature review in happiness assessment. A total of 32 inputs and one output variables were identified during survey design phase. The following survey conduction, data collection, cleaning, and preparation; MLR and ANNs were built. ANN models provided better classification performance with over 0.7 R-square and a smaller standard error of estimate compared to MLR. Major policy areas to improve student happiness levels were identified as career services, financial aid, parking and dining services

Co-opetition models for governing professional football

In recent years, models for co-creating value in a business-to-business context have often been examined with the aim of studying the strategies implemented by and among organisations for competitive and co-operative purposes. The traditional concepts of competition and co-operation between businesses have now evolved, both in terms of the sector in which the businesses operate and in terms of the type of goods they produce. Many researchers have, in recent times, investigated the determinants that can influence the way in which the model of co-opetition can be applied to the football world. Research interest lies in the particular features of what makes a good football. In this paper, the aim is to conduct an analysis of the rules governing the “football system”, while also looking at the determinants of the demand function within football entertainment. This entails applying to football match management the co-opetition model, a recognised model that combines competition and co-operation with the view of creating and distributing value. It can, therefore, be said that, for a spectator, watching sport is an experience of high suspense, and this suspense, in turn, depends upon the degree of uncertainty in the outcome. It follows that the rules ensuring that both these elements can be satisfied are a fertile ground for co-operation between clubs, as it is in the interest of all stakeholders to offer increasingly more attractive football, in comparison with other competing products. Our end purpose is to understand how co-opetition can be achieved within professional football

Modelling the Efficiency of Paddy Production in Peninsular Malaysia Using Principal Component Analysis and Data Envelopment Analysis (PCA-DEA)

Although the current paddy production in Peninsular Malaysia shows a satisfying self-sufficiency level, the countrys annual rough paddy production, however, will still have to increase over the next 10 years to sustain up with the local population growth and the growing demand level for this staple food. Thus, immediate action needs to be done to evaluate the efficiency of paddy production, so that the information obtained can help the government to come out with strategies to maximize the outputs with the current existing inputs. The objective of this study is to measure the efficiency of paddy production of 11 states in Peninsular Malaysia using a hybrid of Principal Component Analysis and Data Envelopment Analysis. The variables used as inputs include planted paddy area, number of rice farmers, amount of seeds usage and total budget allocation whereas the variables used as outputs cover paddy output, rice output and rice income. As the input and output variables are highly correlated, this study proposes the combination of Principal Component Analysis (PCA) and Data Envelopment Analysis (DEA) approaches to reduce the data dimensionality problem instead of eliminating the variables with multicollinearity problem from the analysis. PCA is applied separately on both sides of all inputs and all outputs, resulting in one principal component (PC) to represent the input and one PC to represent the output side. Both PCs were found to contribute greater than 70% of the data variation. The results from output-oriented DEA model under variable return to scale (VRS) indicate that Kedah is the most efficient state in producing the paddy output, leaving the rest of states with average efficiency scores ranging from 0.745 to 0.998. Further results show that Kelantan, Terengganu and Pahang were placed at the lowest three states in terms of efficiency levels. There is a need for the government to pay extra attention on these states in bringing off the significant factors that may disrupt the functioning of efficient paddy production

Advanced survival modelling for consumer credit risk assessment: addressing recurrent events, multiple outcomes and frailty

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Statistics and EconometricsThis thesis worked on the application of advanced survival models in consumer credit risk assessment, particularly to address issues of recurrent delinquency (or default) and recovery (cure) events as well as multiple risk events and frailty. Each chapter (2 to 5) addressed a separate problem and several key conclusions were reached. Chapter 2 addressed the neglected area of modelling recovery from delinquency to normal performance on retail consumer loans taking into account the recurrent nature of delinquency and also including time-dependent macroeconomic variables. Using data from a lending company in Zimbabwe, we provided a comprehensive analysis of the recovery patterns using the extended Cox model. The findings vividly showed that behavioural variables were the most important in understanding recovery patterns of obligors. This confirms and underscores the importance of using behavioural models to understand the recovery patterns of obligors in order to prevent credit loss. The findings also strongly revealed that the falling real gross domestic product, representing a deteriorating economic situation significantly explained the diminishing rate of recovery from delinquency to normal performance among consumers. The study pointed to the urgent need for policy measures aimed at promoting economic growth for the stabilisation of consumer welfare and the financial system at large.Chapter 3 extends the work in chapter 2 and notes that, even though multiple failure-time data are ubiquitous in finance and economics especially in the credit risk domain, it is unfortunate that naive statistical techniques which ignore the subsequent events are commonly used to analyse such data. Applying standard statistical methods without addressing the recurrence of the events produces biased and inefficient estimates, thus offering erroneous predictions. We explore various ways of modelling and forecasting recurrent delinquency and recovery events on consumer loans. Using consumer loans data from a severely distressed economic environment, we illustrate and empirically compare extended Cox models for ordered recurrent recovery events. We highlight that accounting for multiple events proffers detailed information, thus providing a nuanced understanding of the recovery prognosis of delinquents. For ordered indistinguishable recurrent recovery events, we recommend using the Andersen and Gill (1982) model since it fits these assumptions and performs well on predicting recovery.Chapter 4 extends chapters 2 and 3 and highlight that rigorous credit risk analysis is not only of significance to lenders and banks but is also of paramount importance for sound regulatory and economic policy making. Increasing loan impairment or delinquency, defaults and mortgage foreclosures signals a sick economy and generates considerable financial stability concerns. For lenders and banks, the accurate estimation of credit risk parameters remains essential for pricing, profit testing, capital provisioning as well as for managing delinquents. Traditional credit scoring models such as the logit regression only provide estimates of the lifetime probability of default for a loan but cannot identify the existence of cures and or other movements. These methods lack the ability to characterise the progression of borrowers over time and cannot utilise all the available data to understand the recurrence of risk events and possible occurrence of multiple loan outcomes. In this paper, we propose a system-wide multi-state framework to jointly model state occupations and the transitions between normal performance (current), delinquency, prepayment, repurchase, short sale and foreclosure on mortgage loans. The probability of loans transitioning to and from the various states is estimated in a discrete-time multi-state Markov model with seven allowable states and sixteen possible transitions. Additionally, we investigate the relationship between the probability of loans transitioning to and from various loan outcomes and loan-level covariates. We empirically test the performance of the model using the US single-family mortgage loans originated during the first quarter of 2009 and were followed on their monthly repayment performance until the third quarter of 2016. Our results show that the main factors affecting the transition into various loan outcomes are affordability as measured by debt-to-income ratio, equity as marked by loan-to-value ratio, interest rates and the property type. In chapter 5, we note that there has been increasing availability of consumer credit in Zimbabwe, yet the credit information sharing systems are not as advanced. Using frailty survival models on credit bureau data from Zimbabwe, the study investigates the possible underestimation of credit losses under the assumption of independence of default event times. The study found that adding a frailty term significantly improved the models, thus indicating the presence of unobserved heterogeneity. The major policy recommendation is for the regulator to institute appropriate policy frameworks to allow robust and complete credit information sharing and reporting as doing so will significantly improve the functioning of the credit market

E-Commerce Audit Judgment Expertise: Does Expertise in System Change Management and Information Technology Auditing Mediate E-Commerce Audit Judgment Expertise?

A global survey of 203 E-commerce auditors was conducted to investigate the perceptions about the potential determinants of expertise in E-commerce audits. We hypothesize and find evidence indicating that information technology and communication expertise are positively related to expertise in E-commerce audit judgment. We also find that system change management expertise and information technology audit expertise mediate this relationship.E-commerce Audit Judgment, IT Audit, Structural Equations Modeling

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method

Pricing Survivor Bonds with Affine-Jump Diffusion Stochastic Mortality Models

Bravo, J. M. (2021). Pricing Survivor Bonds with Affine-Jump Diffusion Stochastic Mortality Models. In 2021 The 5th International Conference on E-Commerce, E-Business and E-Government ICEEG '21, April 28-30, 2021, Rome, Italy. Association for Computing Machinery (ACM). https://doi.org/10.1145/3466029.3466037 ---------------------------------------------------------------- Funding Information: The author acknowledges financial support by Portuguese national funds through FCT under the project UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC). Publisher Copyright: © 2021 Association for Computing Machinery. All rights reserved.Capital-market-based solutions are an interesting alternative to reinsurance-based options for managing systemic longevity risk in pension funds, insurance companies and annuity providers. The pricing of longevity-linked securities depends both on the stochastic process for the underlying risk factors (age-specific mortality rates, interest rate) and on investor's risk attitude. This paper proposes a pricing approach for survivor bonds using affine-jump diffusion stochastic mortality models. The model structure uses a non-mean reverting square-root jump diffusion Feller process combined with a Poisson process with double asymmetric exponentially distributed jumps to account for both negative and positive jumps. The model offers analytical tractability, fits well data and allows for closed-form expressions for the survival probability. Illustrative empirical results on the pricing of survivor bonds are provided using U. S. mortality data for representative cohorts. The results suggest the cost of hedging longevity risk by issuing survivor bonds would be acceptable for the issuer.authorsversionpublishe

Drawing Down Retirement Financial Savings: A Welfare Analysis using French data

Bravo, J. M., & Freitas, N. E. M. D. (2021). Drawing Down Retirement Financial Savings: A Welfare Analysis using French data. In 2021 The 5th International Conference on E-Commerce, E-Business and E-Government (ICEEG '21) (pp. 152-158). Association for Computing Machinery (ACM). https://doi.org/10.1145/3466029.3466041 -------------------------------------------------------------- Funding Information: Najat El Mekkaoui acknowledges support by Groupama Gan Vie, Groupama Asset Management and Deloitte. Jorge M. Bravo acknowledges financial support by Portuguese national funds through FCT under the project UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC). Publisher Copyright: © 2021 ACM.In recent decades, most countries have responded to increased longevity, population ageing, and low market returns with systemic and/or gradual parametric pension reforms. The trend towards individual accounts in public and private funded pension schemes augmented the importance of studying the decumulation phase of pensions. This paper uses a simulation design to empirically investigate the individual welfare generated from alternative annuitization and self-managed fixed, variable and hybrid drawdown strategies. A time-separable utility function is used to represent an individual's preferences towards consumption and bequest, risk aversion and intertemporal discounting and to quantitively assess the range of retirement outcomes from competing decumulation designs. The setting comprises a stochastic mortality and investment risk framework calibrated to French interest rate, stock market and mortality data from 2010 to 2019. The results show that self-managed variable decumulation strategies may generate higher income at the expense of high risk taking, more volatile income streams and no longevity insurance. Annuitization strategies involving longevity-linked life annuities and hybrid solutions provide higher expected lifetime utility at the expense of bequest motives.authorsversionpublishe

Efficiency, stability and asset quality of Islamic vis-à-vis conventional banks: evidence from Indonesia

urpose – This paper aims to examine how Indonesian Islamic banks differ from conventional banks in terms of their business model, asset quality, stability and efficiency. Design/methodology/approach – Based on data from 2008 to 2012, the authors use t-test, z-score and data envelopment analysis (DEA) to assess the business model, as well as the asset quality, stability and efficiency of both the Islamic and conventional banks. Findings – The results indicate that there are significant differences between the two – Islamic banks appear to not follow the conventional business model. Secondly, Islamic banks seem to have better asset quality and to be more stable than their conventional counterparts. Originality/value – Finally, the DEA results also indicate that Islamic banks are relatively more efficient than conventional banks, as shown by their higher overall efficiency, as well as technical efficiency