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THE EFFECTS OF CORPORATE SOCIAL RESPONSIBILITY ON FINANCIAL PERFORMANCE
Title
THE EFFECTS OF CORPORATE SOCIAL RESPONSIBILITY ON FINANCIAL PERFORMANCE.
Creator
Mentor, Marly, Roberts, Robin, Gatchev, Vladimir, University of Central Florida
Abstract / Description
Companies have taken the initiative to be socially responsible over the years. In the past, the focus for companies has been on maximizing wealth. With the growth of corporate social responsibility (CSR), there has been many debates regarding its benefits. More companies are beginning to realize the value of being socially responsible and how critical it is to business function. This paper researches past studies on the relationship between corporate social responsibility and financial...
Show moreCompanies have taken the initiative to be socially responsible over the years. In the past, the focus for companies has been on maximizing wealth. With the growth of corporate social responsibility (CSR), there has been many debates regarding its benefits. More companies are beginning to realize the value of being socially responsible and how critical it is to business function. This paper researches past studies on the relationship between corporate social responsibility and financial performance. This relationship is then tested using a reliable source of data on corporate social responsibility performance. This study uniquely looks at the accounting and market-based measurements of financial performance. The dataset includes most of the S&P 500 firms and covers years 2005-2014. An empirical model is constructed which includes factors that were found significant in the works of Capon, Farley, and Hoenig (1990). The relationships are tested using cross-sector/panel data time-series regressions. Results indicate that CSR and the accounting measurements of financial performance are positively related. CSR and the market-based measurements of financial performance are negatively related. This suggests that CSR positively affects a company�s profits and negatively affects future stock returns. One interpretation of this result is that socially responsible stocks have a lower required rates of return. The results indicate that since investors are more willing to invest in CSR stocks, these firms end up experiencing lower future stock returns. The results are consistent with past studies and support the hypotheses.
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Date Issued
2016
Identifier
CFH2000047, ucf:45506
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH2000047
EFFECT OF SOURCE WATER BLENDING ON COPPER RELEASE IN PIPE DISTRIBUTION SYSTEM: THERMODYNAMIC AND EMPIRICAL MODELS
Title
EFFECT OF SOURCE WATER BLENDING ON COPPER RELEASE IN PIPE DISTRIBUTION SYSTEM: THERMODYNAMIC AND EMPIRICAL MODELS.
Creator
Xiao, Weizhong, Taylor, James S., University of Central Florida
Abstract / Description
This dissertation focuses on copper release in drinking water. Qualitative and quantitative assessment of Cu and Fe corrosion by process water quality was assessed over one year in a field study using finished waters produced from seven different treatment process and eighteen pilot distribution systems (PDSs) that were made from unlined cast iron and galvanized steel pipes, and lined cement and PVC pipes taken from actual distribution systems. Totally seven different waters were studied,...
Show moreThis dissertation focuses on copper release in drinking water. Qualitative and quantitative assessment of Cu and Fe corrosion by process water quality was assessed over one year in a field study using finished waters produced from seven different treatment process and eighteen pilot distribution systems (PDSs) that were made from unlined cast iron and galvanized steel pipes, and lined cement and PVC pipes taken from actual distribution systems. Totally seven different waters were studied, which consisted of three source waters: groundwater, surface, and simulated brackish water designated as G1, S1, and RO. With certain pre-established blending ratios, these three waters were blended to form another three waters designated as G2, G3, and G4. Enhanced surface water treatment was CFS, ozonation and GAC filtration, which was designated as S1. The CFS surface water was nanofiltered, which is S2. All seven finished waters were stabilized and chloraminated before entering the PDSs. Corrosion potential was compared qualitatively and quantitatively for all seven waters by monitoring copper and iron release from the PDSs. This dissertation consists of four major parts.(1) Copper corrosion surface characterization in which the solid corrosion products formed in certain period of exposure to drinking water were tried to be identified with kinds of surface techniques. Surface characterization indicated that major corrosion products consists of cuprite (Cu2O) as major underneath corrosion layer and tenorite (CuO), cupric hydroxide (Cu(OH)2) on the top surface. In terms of dissolution/precipitation mechanism controlling the copper concentration in bulk solution, cupric hydroxide thermodynamic model was developed.(2) Theoretical thermodynamic models were developed to predict the copper release level quantitatively based on controlling solid phases identified in part (1). These models are compared to actual data and relative assessment is made of controlling solid phases. (3) Non-linear and linear regression models were developed that accommodated the release to total copper for varying water quality. These models were verified using independent data and provide proactive means of assessing and controlling copper release in a varying water quality environment. (4) Simulation of total copper release was conducted using all possible combinations of water quality produced by blending finished waters from ground, surface and saline sources, which involves the comparison of copper corrosion potentials among reverse osmosis, nanofiltration, enhanced coagulation, lime softening, and conventional drinking water treatment.
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Date Issued
2004
Identifier
CFE0000042, ucf:46069
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0000042
Examining Multiple Approaches for the Transferability of Safety Performance Functions
Title
Examining Multiple Approaches for the Transferability of Safety Performance Functions.
Creator
Farid, Ahmed Tarek Ahmed, Abdel-Aty, Mohamed, Lee, JaeYoung, Eluru, Naveen, University of Central Florida
Abstract / Description
Safety performance functions (SPFs) are essential in road safety since they are used to predict crash frequencies. They are commonly applied for detecting hot spots in network screening and assessing whether road safety countermeasures are effective. In the Highway Safety Manual (HSM), SPFs are provided for several crash classifications for several types of roadway facilities. The SPFs of the HSM are developed using data from multiple states. In regions where jurisdiction specific SPFs are...
Show moreSafety performance functions (SPFs) are essential in road safety since they are used to predict crash frequencies. They are commonly applied for detecting hot spots in network screening and assessing whether road safety countermeasures are effective. In the Highway Safety Manual (HSM), SPFs are provided for several crash classifications for several types of roadway facilities. The SPFs of the HSM are developed using data from multiple states. In regions where jurisdiction specific SPFs are not available, it is custom to adopt nationwide SPFs for crash predictions then apply a calibration factor. Yet, the research is limited regarding the application of national SPFs for local jurisdictions. In this study, the topic of transferability is explored by examining rural multilane highway SPFs from Florida, Ohio, and California. That is for both divided segments and intersections. Traffic, road geometrics and crash data from the three states are collected to develop one-state, two-state and three-state SPFs. The SPFs are negative binomial models taking the form of those of the HSM. Evaluation of the transferability of models is undertaken by calculating a measure known as the transfer index. It is used to explain which SPFs may be transferred tolerably to other jurisdictions. According to the results, the transferability of rural divided segments' SPFs of Florida to California and vice versa is superior to that of Ohio's SPFs. For four-leg signalized intersections, neither state's models are transferable to any state. Also, the transfer index indicates improved transferability when using pooled data from multiple states. Furthermore, a modified version of the Empirical Bayes method that is responsible for segment specific adjustment factors is proposed as an alternative to the HSM calibration method. It is used to adjust crash frequencies predicted by the SPFs being transferred to the jurisdiction of interest. The modified method, proposed, outperforms the HSM calibration method as per the analysis results.
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Date Issued
2015
Identifier
CFE0006298, ucf:51604
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006298
APPLICATION OF THE EMPIRICAL LIKELIHOOD METHOD IN PROPORTIONAL HAZARDS MODEL
Title
APPLICATION OF THE EMPIRICAL LIKELIHOOD METHOD IN PROPORTIONAL HAZARDS MODEL.
Creator
HE, BIN, Ren, Jian-Jian, University of Central Florida
Abstract / Description
In survival analysis, proportional hazards model is the most commonly used and the Cox model is the most popular. These models are developed to facilitate statistical analysis frequently encountered in medical research or reliability studies. In analyzing real data sets, checking the validity of the model assumptions is a key component. However, the presence of complicated types of censoring such as double censoring and partly interval-censoring in survival data makes model assessment...
Show moreIn survival analysis, proportional hazards model is the most commonly used and the Cox model is the most popular. These models are developed to facilitate statistical analysis frequently encountered in medical research or reliability studies. In analyzing real data sets, checking the validity of the model assumptions is a key component. However, the presence of complicated types of censoring such as double censoring and partly interval-censoring in survival data makes model assessment difficult, and the existing tests for goodness-of-fit do not have direct extension to these complicated types of censored data. In this work, we use empirical likelihood (Owen, 1988) approach to construct goodness-of-fit test and provide estimates for the Cox model with various types of censored data.Specifically, the problems under consideration are the two-sample Cox model and stratified Cox model with right censored data, doubly censored data and partly interval-censored data. Related computational issues are discussed, and some simulation results are presented. The procedures developed in the work are applied to several real data sets with some discussion.
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Date Issued
2006
Identifier
CFE0001099, ucf:46780
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001099
Estimation for the Cox Model with Various Types of Censored Data
Title
Estimation for the Cox Model with Various Types of Censored Data.
Creator
Riddlesworth, Tonya, Ren, Joan, Mohapatra, Ram, Richardson, Gary, Ni, Liqiang, Schott, James, University of Central Florida
Abstract / Description
In survival analysis, the Cox model is one of the most widely used tools. However, up to now there has not been any published work on the Cox model with complicated types of censored data, such as doubly censored data, partly-interval censored data, etc., while these types of censored data have been encountered in important medical studies, such as cancer, heart disease, diabetes, etc. In this dissertation, we first derive the bivariate nonparametric maximum likelihood estimator (BNPMLE) Fn(t...
Show moreIn survival analysis, the Cox model is one of the most widely used tools. However, up to now there has not been any published work on the Cox model with complicated types of censored data, such as doubly censored data, partly-interval censored data, etc., while these types of censored data have been encountered in important medical studies, such as cancer, heart disease, diabetes, etc. In this dissertation, we first derive the bivariate nonparametric maximum likelihood estimator (BNPMLE) Fn(t,z) for joint distribution function Fo(t,z) of survival time T and covariate Z, where T is subject to right censoring, noting that such BNPMLE Fn has not been studied in statistical literature. Then, based on this BNPMLE Fn we derive empirical likelihood-based (Owen, 1988) confidence interval for the conditional survival probabilities, which is an important and difficult problem in statistical analysis, and also has not been studied in literature. Finally, with this BNPMLE Fn as a starting point, we extend the weighted empirical likelihood method (Ren, 2001 and 2008a) to the multivariate case, and obtain a weighted empirical likelihood-based estimation method for the Cox model. Such estimation method is given in a unified form, and is applicable to various types of censored data aforementioned.
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Date Issued
2011
Identifier
CFE0004158, ucf:49051
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004158