A methodological framework for modeling pavement maintenance costs for projects with performance-based contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

Community college faculty commitment to Florida performance -based funding indicators for academic programs

In 1996, the State of Florida implemented a performance-based funding program for the Associate in Arts degree offered by community colleges. Additional funds are allocated for distribution among public community colleges based on performance indicators. The indicators are comprised of 10 performance goals that refer to productivity indexed by overall degree completions as well as subgroups: special disadvantaged populations, transfers, job placements, and education acceleration. ^ This study examined the level of self-reported commitment of community college faculty to the 10 Florida performance-based funding indicators for academic programs. Also examined were the relationships between commitment and (a) self-efficacy in contributing to the achievement of the indicators and (b) personal financial reward expectation for contributing to the achievement of the indicators. The relationships between commitment and (a) gender, (b) academic rank, and (c) types of courses taught were analyzed based on secondary analyses. ^ The participants were 303 full-time faculty members of Miami-Dade Community College who taught courses taken by students pursuing the Associate in Arts degree. A questionnaire was developed to measure commitment, self-efficacy, and expectation of financial reward for each of the 10 indicators. ^ The mean composite commitment score for faculty members who responded to the survey was 4.07 in a scale of 1 to 5. Greater commitment was reported for indicators closely related to the traditional mission of community colleges (i.e., facilitating progress of special groups in earning the AA degree in preparation for transferring to a four-year university). Lower commitment was reported for indicators oriented to State priorities such as education acceleration mechanisms and job placements. Commitment was correlated with three variables: self-efficacy, expectation of financial reward, and types of courses taught. However, commitment was not related to gender and academic rank. Although a cause-effect relationship cannot be inferred from this study, the findings depict a positive relationship between faculty commitment to performance-based funding indicators and faculty self-efficacy to contribute to the achievement of the indicators. ^

A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

Adult education directors' perceptions of performance indicators for adult education programs in the state of Florida

Current demands for accountability in education emphasize outcome-based program evaluation and tie program funding to individual student performance. As has been the case for elementary and secondary programs, demands for accountability have increased pressure on adult educators to show evidence of the benefits of their programs in order to justify their financial support. In Florida, recent legislation fundamentally changes the delivery of adult education in the state by establishing a performance-based funding system that is based on outcomes related to the retention, completion, and employment of program participants.^ A performance-based funding system requires an evaluation process that stresses outcome indicators over indicators that focus on program context or process. Although the state has adopted indicators of program quality to evaluate its adult education programs, these indicators focus mostly on program processes rather than student outcomes. In addition, the indicators are not specifically tied to workforce development outcomes, a priority to federal and local funding agents.^ Improving the accountability of adult education programs and defining the role of these programs in Florida's Workforce Development System has become a priority to policy makers across the state. Another priority has been to involve adult education practitioners in every step of this process.^ This study was conducted in order to determine what performance indicators, as judged by the directors and supervisors of adult education programs in the state of Florida, are important and feasible in measuring the quality and effectiveness of these programs. The results of the study indicated that, both statewide and by region, the respondents consistently gave the highest ratings on both importance and feasibility to the indicators of Program Context, which reflect the needs, composition, and structure of the programs, and to the indicators of Educational Gain, which reflect learner progress in the attainment of basic skills and competencies. In turn, the respondents gave the lowest ratings on both importance and feasibility to the indicators in the areas of Return on State's Investment, Efficiency, Retention, and Workforce Training. In general, the indicators that received high ratings for importance also received high ratings for feasibility. ^

Risk based post closure care analysis for Florida landfills

Subtitle D of the Resource Conservation and Recovery Act (RCRA) requires a post closure period of 30 years for non hazardous wastes in landfills. Post closure care (PCC) activities under Subtitle D include leachate collection and treatment, groundwater monitoring, inspection and maintenance of the final cover, and monitoring to ensure that landfill gas does not migrate off site or into on site buildings. The decision to reduce PCC duration requires exploration of a performance based methodology to Florida landfills. PCC should be based on whether the landfill is a threat to human health or the environment. Historically no risk based procedure has been available to establish an early end to PCC. Landfill stability depends on a number of factors that include variables that relate to operations both before and after the closure of a landfill cell. Therefore, PCC decisions should be based on location specific factors, operational factors, design factors, post closure performance, end use, and risk analysis. The question of appropriate PCC period for Florida’s landfills requires in depth case studies focusing on the analysis of the performance data from closed landfills in Florida. Based on data availability, Davie Landfill was identified as case study site for a case by case analysis of landfill stability. The performance based PCC decision system developed by Geosyntec Consultants was used for the assessment of site conditions to project PCC needs. The available data for leachate and gas quantity and quality, ground water quality, and cap conditions were evaluated. The quality and quantity data for leachate and gas were analyzed to project the levels of pollutants in leachate and groundwater in reference to maximum contaminant level (MCL). In addition, the projected amount of gas quantity was estimated. A set of contaminants (including metals and organics) were identified as contaminants detected in groundwater for health risk assessment. These contaminants were selected based on their detection frequency and levels in leachate and ground water; and their historical and projected trends. During the evaluations a range of discrepancies and problems that related to the collection and documentation were encountered and possible solutions made. Based on the results of PCC performance integrated with risk assessment, projection of future PCC monitoring needs and sustainable waste management options were identified. According to these results, landfill gas monitoring can be terminated, leachate and groundwater monitoring for parameters above MCL and surveying of the cap integrity should be continued. The parameters which cause longer monitoring periods can be eliminated for the future sustainable landfills. As a conclusion, 30 year PCC period can be reduced for some of the landfill components based on their potential impacts to human health and environment (HH&E).

Evaluation of the evidential value of the elemental composition of glass, ink and paper by laser-based microspectrochemical methods

Elemental analysis can become an important piece of evidence to assist the solution of a case. The work presented in this dissertation aims to evaluate the evidential value of the elemental composition of three particular matrices: ink, paper and glass. In the first part of this study, the analytical performance of LIBS and LA-ICP-MS methods was evaluated for paper, writing inks and printing inks. A total of 350 ink specimens were examined including black and blue gel inks, ballpoint inks, inkjets and toners originating from several manufacturing sources and/or batches. The paper collection set consisted of over 200 paper specimens originating from 20 different paper sources produced by 10 different plants. Micro-homogeneity studies show smaller variation of elemental compositions within a single source (i.e., sheet, pen or cartridge) than the observed variation between different sources (i.e., brands, types, batches). Significant and detectable differences in the elemental profile of the inks and paper were observed between samples originating from different sources (discrimination of 87–100% of samples, depending on the sample set under investigation and the method applied). These results support the use of elemental analysis, using LA-ICP-MS and LIBS, for the examination of documents and provide additional discrimination to the currently used techniques in document examination. In the second part of this study, a direct comparison between four analytical methods (µ-XRF, solution-ICP-MS, LA-ICP-MS and LIBS) was conducted for glass analyses using interlaboratory studies. The data provided by 21 participants were used to assess the performance of the analytical methods in associating glass samples from the same source and differentiating different sources, as well as the use of different match criteria (confidence interval (±6s, ±5s, ±4s, ±3s, ±2s), modified confidence interval, t-test (sequential univariate, p=0.05 and p=0.01), t-test with Bonferroni correction (for multivariate comparisons), range overlap, and Hotelling's T2 tests. Error rates (Type 1 and Type 2) are reported for the use of each of these match criteria and depend on the heterogeneity of the glass sources, the repeatability between analytical measurements, and the number of elements that were measured. The study provided recommendations for analytical performance-based parameters for µ-XRF and LA-ICP-MS as well as the best performing match criteria for both analytical techniques, which can be applied now by forensic glass examiners.

Does Financial Performance Depend on Hotel Size? Analysis of the Financial Profile of the U.S. Lodging Industry

This research presents a financial profile of the U.S. Lodging Industry based on an analysis of 2,091 financial statements (fiscal year 2011) for individual hotels ranging in asset size of $500 thousand to $250 million. The study analyzes summary results of the financial position and profitability of hotels based on a common size analysis of Balance Sheets and Income Statements. Furthermore, the study analyzes 10 key performance benchmarks as measured by Liquidity, Solvency and Operating Ratios. The results of the study show a divergence in the hotel industry’s financial performance based on the size of the hotel and by upper, median and lower quartiles of the study sample.

Relationships between gifted selection criteria and performance in sixth -grade gifted science

This study examined the relationships between gifted selection criteria used in the Dade County Public Schools of Miami, Florida and performance in sixth grade gifted science classes.^ The goal of the study was to identify significant predictors of performance in sixth grade gifted science classes. Group comparisons of performance were also made. Performance in sixth grade gifted science was defined as the numeric average of nine weeks' grades earned in sixth grade gifted science classes.^ The sample consisted of 100 subjects who were formerly enrolled in sixth grade gifted science classes over two years at a large, multiethnic public middle school in Dade County.^ The predictors analyzed were I.Q. score (all scales combined), full scale I.Q. score, verbal scale I.Q. score, performance scale I.Q. score, combined Stanford Achievement Test (SAT) score (Reading Comprehension plus Math Applications), SAT Reading Comprehension score, and SAT Math Applications score. Combined SAT score and SAT Math Applications score were significantly positively correlated to performance in sixth grade gifted science. Performance scale I.Q. score was significantly negatively correlated to performance in sixth grade gifted science. The other predictors examined were not significantly correlated to performance.^ Group comparison results showed the mean average of nine weeks grades for the full scale I.Q. group was greater than the verbal and performance scale I.Q. groups. Females outperformed males to a highly significant level. Mean g.p.a. for ethnic groups was greatest for Asian students, followed by white non-Hispanic, Hispanic, and black. Students not receiving a lunch subsidy outperformed those receiving subsidies.^ Comparisons of performance based on gifted qualification plan showed the mean g.p.a. for traditional plan and Plan B groups were not different. Mean g.p.a. for students who qualified for gifted using automatic Math Applications criteria was highest, followed by automatic Reading Comprehension criteria and Plan B Matrix score. Both automatic qualification groups outperformed the traditional group. The traditional group outperformed the Plan B Matrix group. No significant differences in mean g.p.a. between the Plan B subgroups and the traditional plan group were found. ^

Risk Based Post Closure Care Analysis for Florida Landfills

Subtitle D of the Resource Conservation and Recovery Act (RCRA) requires a post closure period of 30 years for non hazardous wastes in landfills. Post closure care (PCC) activities under Subtitle D include leachate collection and treatment, groundwater monitoring, inspection and maintenance of the final cover, and monitoring to ensure that landfill gas does not migrate off site or into on site buildings. The decision to reduce PCC duration requires exploration of a performance based methodology to Florida landfills. PCC should be based on whether the landfill is a threat to human health or the environment. Historically no risk based procedure has been available to establish an early end to PCC. Landfill stability depends on a number of factors that include variables that relate to operations both before and after the closure of a landfill cell. Therefore, PCC decisions should be based on location specific factors, operational factors, design factors, post closure performance, end use, and risk analysis. The question of appropriate PCC period for Florida’s landfills requires in depth case studies focusing on the analysis of the performance data from closed landfills in Florida. Based on data availability, Davie Landfill was identified as case study site for a case by case analysis of landfill stability. The performance based PCC decision system developed by Geosyntec Consultants was used for the assessment of site conditions to project PCC needs. The available data for leachate and gas quantity and quality, ground water quality, and cap conditions were evaluated. The quality and quantity data for leachate and gas were analyzed to project the levels of pollutants in leachate and groundwater in reference to maximum contaminant level (MCL). In addition, the projected amount of gas quantity was estimated. A set of contaminants (including metals and organics) were identified as contaminants detected in groundwater for health risk assessment. These contaminants were selected based on their detection frequency and levels in leachate and ground water; and their historical and projected trends. During the evaluations a range of discrepancies and problems that related to the collection and documentation were encountered and possible solutions made. Based on the results of PCC performance integrated with risk assessment, projection of future PCC monitoring needs and sustainable waste management options were identified. According to these results, landfill gas monitoring can be terminated, leachate and groundwater monitoring for parameters above MCL and surveying of the cap integrity should be continued. The parameters which cause longer monitoring periods can be eliminated for the future sustainable landfills. As a conclusion, 30 year PCC period can be reduced for some of the landfill components based on their potential impacts to human health and environment (HH&E).

C-MEMS Based Micro Enzymatic Biofuel Cells

Miniaturized, self-sufficient bioelectronics powered by unconventional micropower may lead to a new generation of implantable, wireless, minimally invasive medical devices, such as pacemakers, defibrillators, drug-delivering pumps, sensor transmitters, and neurostimulators. Studies have shown that micro-enzymatic biofuel cells (EBFCs) are among the most intuitive candidates for in vivo micropower. In the fisrt part of this thesis, the prototype design of an EBFC chip, having 3D intedigitated microelectrode arrays was proposed to obtain an optimum design of 3D microelectrode arrays for carbon microelectromechanical systems (C-MEMS) based EBFCs. A detailed modeling solving partial differential equations (PDEs) by finite element techniques has been developed on the effect of 1) dimensions of microelectrodes, 2) spatial arrangement of 3D microelectrode arrays, 3) geometry of microelectrode on the EBFC performance based on COMSOL Multiphysics. In the second part of this thesis, in order to investigate the performance of an EBFC, behavior of an EBFC chip performance inside an artery has been studied. COMSOL Multiphysics software has also been applied to analyze mass transport for different orientations of an EBFC chip inside a blood artery. Two orientations: horizontal position (HP) and vertical position (VP) have been analyzed. The third part of this thesis has been focused on experimental work towards high performance EBFC. This work has integrated graphene/enzyme onto three-dimensional (3D) micropillar arrays in order to obtain efficient enzyme immobilization, enhanced enzyme loading and facilitate direct electron transfer. The developed 3D graphene/enzyme network based EBFC generated a maximum power density of 136.3 μWcm-2 at 0.59 V, which is almost 7 times of the maximum power density of the bare 3D carbon micropillar arrays based EBFC. To further improve the EBFC performance, reduced graphene oxide (rGO)/carbon nanotubes (CNTs) has been integrated onto 3D mciropillar arrays to further increase EBFC performance in the fourth part of this thesisThe developed rGO/CNTs based EBFC generated twice the maximum power density of rGO based EBFC. Through a comparison of experimental and theoretical results, the cell performance efficiency is noted to be 67%.

Evaluation of the Evidential Value of the Elemental Composition of Glass, Ink and Paper by Laser-Based Micro-Spectrochemical Methods

Elemental analysis can become an important piece of evidence to assist the solution of a case. The work presented in this dissertation aims to evaluate the evidential value of the elemental composition of three particular matrices: ink, paper and glass. In the first part of this study, the analytical performance of LIBS and LA-ICP-MS methods was evaluated for paper, writing inks and printing inks. A total of 350 ink specimens were examined including black and blue gel inks, ballpoint inks, inkjets and toners originating from several manufacturing sources and/or batches. The paper collection set consisted of over 200 paper specimens originating from 20 different paper sources produced by 10 different plants. Micro-homogeneity studies show smaller variation of elemental compositions within a single source (i.e., sheet, pen or cartridge) than the observed variation between different sources (i.e., brands, types, batches). Significant and detectable differences in the elemental profile of the inks and paper were observed between samples originating from different sources (discrimination of 87 – 100% of samples, depending on the sample set under investigation and the method applied). These results support the use of elemental analysis, using LA-ICP-MS and LIBS, for the examination of documents and provide additional discrimination to the currently used techniques in document examination. In the second part of this study, a direct comparison between four analytical methods (µ-XRF, solution-ICP-MS, LA-ICP-MS and LIBS) was conducted for glass analyses using interlaboratory studies. The data provided by 21 participants were used to assess the performance of the analytical methods in associating glass samples from the same source and differentiating different sources, as well as the use of different match criteria (confidence interval (±6s, ±5s, ±4s, ±3s, ±2s), modified confidence interval, t-test (sequential univariate, p=0.05 and p=0.01), t-test with Bonferroni correction (for multivariate comparisons), range overlap, and Hotelling’s T2 tests. Error rates (Type 1 and Type 2) are reported for the use of each of these match criteria and depend on the heterogeneity of the glass sources, the repeatability between analytical measurements, and the number of elements that were measured. The study provided recommendations for analytical performance-based parameters for µ-XRF and LA-ICP-MS as well as the best performing match criteria for both analytical techniques, which can be applied now by forensic glass examiners.

The impact of CEO compensation and CEO horizon on a firm's discretionary research and development expenditures

Agency costs are said to arise as a result of the separation of ownership from control inherent in the corporate form of ownership. One such agency problem concerns the potential variance between the time horizons of principal shareholders and agent managers. Agency theory suggests that these costs can be alleviated or controlled through performance-based Chief Executive Officer (CEO) contracting. However, components of a CEO's compensation contract can exacerbate or mitigate agency-related problems (Antle and Smith, 1985). According to the horizon hypothesis, a self-serving CEO reduces discretionary research and development (R&D) expenditures to increase earnings and earnings-based bonus compensation. Agency theorists contend that a CEO's market-based compensation component can mitigate horizon problems. This study seeks to determine whether there is a relationship between CEO earnings- and market-based compensation components and R&D expenditures in the largest United States industrial firms from 1987 to 1993.^ Consistent with the horizon hypothesis, results provide evidence of a negative and statistically significant relationship between CEO cash compensation (i.e., salary and bonus) and the firm's R&D expenditures. Consistent with the expectations of agency theory, results provide evidence of a positive and statistically significant relationship between market-based CEO compensation and R&D.^ Further results of this study provide evidence of a positive and statistically significant relationship between CEO tenure and the firm's R&D expenditures. Although there is a negative relationship between CEO age and the firm's R&D, it was not statistically significant at the 0.5 level. ^

A qualitative analysis of the lived experience of nursing staff developers in the process of changing to a new educational model

The purpose of this study was to document and critically analyze the lived experience of selected nursing staff developers in the process of moving toward a new model for hospital nursing education. Eleven respondents were drawn from a nation-wide population of about two hundred individuals involved in nursing staff development. These subjects were responsible for the implementation of the Performance Based Development System (PBDS) in their institutions.^ A purposive, criterion-based sampling technique was used with respondents being selected according to size of hospital, primary responsibility for orchestration of the change, influence over budgetary factors and managerial responsibility for PBDS. Data were gathered by the researcher through both in-person and telephone interviews. A semi-structured interview guide, designed by the researcher was used, and respondents were encouraged to amplify on their recollections as desired. Audiotapes were transcribed and resulting computer files were analyzed using the program "Martin". Answers to interview questions were compiled and reported across cases. The data was then reviewed a second time and interpreted for emerging themes and patterns.^ Two types of verification were used in the study. Internal verification was done through interview transcript review and feedback by respondents. External verification was done through review and feedback on data analysis by readers who were experienced in management of staff development departments.^ All respondents were female, so Gilligan's concept of the "ethic of care" was examined as a decision making strategy. Three levels of caring which influenced decision making were found. They were caring: (a) for the organization, (b) for the employee, and (c) for the patient. The four existentials of the lived experience, relationality, corporeality, temporality and spatiality were also examined to reveal the everydayness of making change. ^

Essays on the impact of stakeholders' sentiment on the financial decision making process

The most important factor that affects the decision making process in finance is the risk which is usually measured by variance (total risk) or systematic risk (beta). Since investors’ sentiment (whether she is an optimist or pessimist) plays a very important role in the choice of beta measure, any decision made for the same asset within the same time horizon will be different for different individuals. In other words, there will neither be homogeneity of beliefs nor the rational expectation prevalent in the market due to behavioral traits. This dissertation consists of three essays. In the first essay, “ Investor Sentiment and Intrinsic Stock Prices”, a new technical trading strategy was developed using a firm specific individual sentiment measure. This behavioral based trading strategy forecasts a range within which a stock price moves in a particular period and can be used for stock trading. Results indicate that sample firms trade within a range and give signals as to when to buy or sell. In the second essay, “Managerial Sentiment and the Value of the Firm”, examined the effect of managerial sentiment on the project selection process using net present value criterion and also effect of managerial sentiment on the value of firm. Final analysis reported that high sentiment and low sentiment managers obtain different values for the same firm before and after the acceptance of a project. Changes in the cost of capital, weighted cost of average capital were found due to managerial sentiment. In the last essay, “Investor Sentiment and Optimal Portfolio Selection”, analyzed how the investor sentiment affects the nature and composition of the optimal portfolio as well as the portfolio performance. Results suggested that the choice of the investor sentiment completely changes the portfolio composition, i.e., the high sentiment investor will have a completely different choice of assets in the portfolio in comparison with the low sentiment investor. The results indicated the practical application of behavioral model based technical indicator for stock trading. Additional insights developed include the valuation of firms with a behavioral component and the importance of distinguishing portfolio performance based on sentiment factors.

Essays on the Impact of Stakeholders' Sentiment on the Financial Decision Making Process

The most important factor that affects the decision making process in finance is the risk which is usually measured by variance (total risk) or systematic risk (beta). Since investors' sentiment (whether she is an optimist or pessimist) plays a very important role in the choice of beta measure, any decision made for the same asset within the same time horizon will be different for different individuals. In other words, there will neither be homogeneity of beliefs nor the rational expectation prevalent in the market due to behavioral traits. This dissertation consists of three essays. In the first essay, Investor Sentiment and Intrinsic Stock Prices, a new technical trading strategy is developed using a firm specific individual sentiment measure. This behavioral based trading strategy forecasts a range within which a stock price moves in a particular period and can be used for stock trading. Results show that sample firms trade within a range and show signals as to when to buy or sell. The second essay, Managerial Sentiment and the Value of the Firm, examines the effect of managerial sentiment on the project selection process using net present value criterion and also effect of managerial sentiment on the value of firm. Findings show that high sentiment and low sentiment managers obtain different values for the same firm before and after the acceptance of a project. The last essay, Investor Sentiment and Optimal Portfolio Selection, analyzes how the investor sentiment affects the nature and composition of the optimal portfolio as well as the performance measures. Results suggest that the choice of the investor sentiment completely changes the portfolio composition, i.e., the high sentiment investor will have a completely different choice of assets in the portfolio in comparison with the low sentiment investor. The results indicate the practical application of behavioral model based technical indicators for stock trading. Additional insights developed include the valuation of firms with a behavioral component and the importance of distinguishing portfolio performance based on sentiment factors.