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.

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.

Acceptable vs. marginal police officers' psychological ratings : a longitudinal comparison of job performance

Archival research was conducted on the inception of preemployment psychological testing, as part of the background screening process, to select police officers for a local police department. Various issues and incidents were analyzed to help explain why this police department progressed from an abbreviated version of a psychological battery, to a much more sophisticated and comprehensive set of instruments. While doubts about psychological exams do exist, research has shown that many are valid and reliable in predicting job performance of police candidates. During a three year period, a police department hired 162 candidates (133 males and 29 females) who received "acceptable" psychological ratings and 71 candidates (58 males and 13 females) who received "marginal" psychological ratings. A document analysis consisted of variables that have been identified as job performance indicators which police psychological testing tries to predict, and "screen in" or "screen out" appropriate applicants. The areas of focus comprised the 6-month police academy, the 4-month Field Training Officer (FTO) Program, the remaining probationary period, and yearly performance up to five years of employment. Specific job performance variables were the final academy grade average, supervisors' evaluation ratings, reprimands, commendations, awards, citizen complaints, time losses, sick time usage, reassignments, promotions, and separations. A causal-comparative research design was used to determine if there were significant statistical differences in these job performance variables between police officers with "acceptable" psychological ratings and police officers with "marginal" psychological ratings. The results of multivariate analyses of variance, t-tests, and chi-square procedures as applicable, showed no significant differences between the two groups on any of the job performance variables.

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.

Essays on Energy Economics and Industrial Organization

The dissertation consists of three chapters related to the low-price guarantee marketing strategy and energy efficiency analysis. The low-price guarantee is a marketing strategy in which firms promise to charge consumers the lowest price among their competitors. Chapter 1 addresses the research question "Does a Low-Price Guarantee Induce Lower Prices'' by looking into the retail gasoline industry in Quebec where there was a major branded firm which started a low-price guarantee back in 1996. Chapter 2 does a consumer welfare analysis of low-price guarantees to drive police indications and offers a new explanation of the firms' incentives to adopt a low-price guarantee. Chapter 3 develops the energy performance indicators (EPIs) to measure energy efficiency of the manufacturing plants in pulp, paper and paperboard industry.

Chapter 1 revisits the traditional view that a low-price guarantee results in higher prices by facilitating collusion. Using accurate market definitions and station-level data from the retail gasoline industry in Quebec, I conducted a descriptive analysis based on stations and price zones to compare the price and sales movement before and after the guarantee was adopted. I find that, contrary to the traditional view, the stores that offered the guarantee significantly decreased their prices and increased their sales. I also build a difference-in-difference model to quantify the decrease in posted price of the stores that offered the guarantee to be 0.7 cents per liter. While this change is significant, I do not find the response in comeptitors' prices to be significant. The sales of the stores that offered the guarantee increased significantly while the competitors' sales decreased significantly. However, the significance vanishes if I use the station clustered standard errors. Comparing my observations and the predictions of different theories of modeling low-price guarantees, I conclude the empirical evidence here supports that the low-price guarantee is a simple commitment device and induces lower prices.

Chapter 2 conducts a consumer welfare analysis of low-price guarantees to address the antitrust concerns and potential regulations from the government; explains the firms' potential incentives to adopt a low-price guarantee. Using station-level data from the retail gasoline industry in Quebec, I estimated consumers' demand of gasoline by a structural model with spatial competition incorporating the low-price guarantee as a commitment device, which allows firms to pre-commit to charge the lowest price among their competitors. The counterfactual analysis under the Bertrand competition setting shows that the stores that offered the guarantee attracted a lot more consumers and decreased their posted price by 0.6 cents per liter. Although the matching stores suffered a decrease in profits from gasoline sales, they are incentivized to adopt the low-price guarantee to attract more consumers to visit the store likely increasing profits at attached convenience stores. Firms have strong incentives to adopt a low-price guarantee on the product that their consumers are most price-sensitive about, while earning a profit from the products that are not covered in the guarantee. I estimate that consumers earn about 0.3% more surplus when the low-price guarantee is in place, which suggests that the authorities should not be concerned and regulate low-price guarantees. In Appendix B, I also propose an empirical model to look into how low-price guarantees would change consumer search behavior and whether consumer search plays an important role in estimating consumer surplus accurately.

Chapter 3, joint with Gale Boyd, describes work with the pulp, paper, and paperboard (PP&PB) industry to provide a plant-level indicator of energy efficiency for facilities that produce various types of paper products in the United States. Organizations that implement strategic energy management programs undertake a set of activities that, if carried out properly, have the potential to deliver sustained energy savings. Energy performance benchmarking is a key activity of strategic energy management and one way to enable companies to set energy efficiency targets for manufacturing facilities. The opportunity to assess plant energy performance through a comparison with similar plants in its industry is a highly desirable and strategic method of benchmarking for industrial energy managers. However, access to energy performance data for conducting industry benchmarking is usually unavailable to most industrial energy managers. The U.S. Environmental Protection Agency (EPA), through its ENERGY STAR program, seeks to overcome this barrier through the development of manufacturing sector-based plant energy performance indicators (EPIs) that encourage U.S. industries to use energy more efficiently. In the development of the energy performance indicator tools, consideration is given to the role that performance-based indicators play in motivating change; the steps necessary for indicator development, from interacting with an industry in securing adequate data for the indicator; and actual application and use of an indicator when complete. How indicators are employed in EPA’s efforts to encourage industries to voluntarily improve their use of energy is discussed as well. The chapter describes the data and statistical methods used to construct the EPI for plants within selected segments of the pulp, paper, and paperboard industry: specifically pulp mills and integrated paper & paperboard mills. The individual equations are presented, as are the instructions for using those equations as implemented in an associated Microsoft Excel-based spreadsheet tool.

Towards a Resilience Metric Framework for Cyber-Physical Systems

Resilience is widely accepted as a desirable system property for cyber-physical systems. However, there are no metrics that can be used to measure the resilience of cyber-physical systems (CPS) while the multi-dimensional nature of performance in these systems is considered. In this work, we present first results towards a resilience metric framework. The key contributions of this framework are threefold: First, it allows to evaluate resilience with respect to different performance indicators that are of interest. Second, complexities that are relevant to the performance indicators of interest, can be intentionally abstracted. Third and final, it supports the identification of reasons for good or bad resilience to improve system design.

Identifying the Impact of Incomplete Datasets on Process Cycle Time Prediction in an Aerospace Assembly Line

Supply Chain Simulation (SCS) is applied to acquire information to support outsourcing decisions but obtaining enough detail in key parameters can often be a barrier to making well informed decisions.
One aspect of SCS that has been relatively unexplored is the impact of inaccurate data around delays within the SC. The impact of the magnitude and variability of process cycle time on typical performance indicators in a SC context is studied.
System cycle time, WIP levels and throughput are more sensitive to the magnitude of deterministic deviations in process cycle time than variable deviations. Manufacturing costs are not very sensitive to these deviations.
Future opportunities include investigating the impact of process failure or product defects, including logistics and transportation between SC members and using alternative costing methodologies.

Intellectual Capital and Performance in Higher Education Organizations

This paper intends to explore the relative importance of different Intellectual Capital (IC) dimensions regarding their contribution to the perceived performance of an Higher Education Organization (HEO). It also seeks to discuss the role of IC and performance measurement in these organizations. This is done through a case study conducted in a Portuguese HEO. The particularities of this type of organization turns it into a very interesting empirical ground for IC research. Evidence suggests that although human, structural and relational capital should contribute as a “whole” to the performance of an HEO, human resources have an added importance as source of knowledge. Results also suggest an ‘overlap’ between IC and performance indicators. Despite the validity of the interpretations provided in the context of the case study, generalization to other situations should only be conducted in a theoretically framed manner. This paper contributes to the development of IC research in a specific type of organization: an HEO. This empirical context is still underexplored, namely regarding the relationship between IC and performance. This study provides important managerial implications for HEOs and their members, who are concerned with its performance and competitiveness.

PI Toolset Methodology for Virtual Enterprise Performance Assessment and Governance

Part 16: Performance Measurement Systems

Essays on mixed-frequency data : forecasting and unit root testing

Doutoramento em Economia

Importância da certificação ISO 9001 na performance das empresas de transportes em Portugal

Mestrado em Gestão e Estratégia Industrial

Technical performance profile of the four-time Costa Rican senior basketball league championship team

The purpose of this study was to analyze and compare the technical performance profile of the four-time Costa Rican Senior Basketball League championship team. A total of 142 games was recorded throughout the 2007, 2008 and 2009 seasons. Performance indicators selected were: two and three-point shots (converted, missed, effectiveness rates), free throws (converted, missed, effectiveness rates), points, offensive and defensive rebounds, fouls, turnovers, assists and ball steals. The information was described based on absolute and relative frequency values. Data was compared by season and by playing period based on the following non-parametric techniques: U-test, Friedman test and Chi-square. In all cases, SPSS version 15.0 was used with a significance level of p ≤ 0.05. Results showed a better profile of technical performance in the 2008 season, characterized by better percentages of two-point shots, free throws, fewer turnovers and more ball steals and assists. In relation to the playing period, the team showed a better technical performance profile during the second half of the matches. In general, the effectiveness rate of two-point shots and free throws was above 60% in both playing periods, while the three-point shot percentage ranged between 26.4% and 29.2%. In conclusion, the team showed a similar technical performance profile to that reported in the literature, as well as a clear evidence of the importance of recording and following up on technical performance indicators in basketball.

Performance determinants For Swedish Financial Monetary Institutions: Panel Data evidence between 2010-2014.

Due to the rapid changes that governs the Swedish financial sector such as financial deregulations and technological innovations, it is imperative to examine the extent to which the Swedish Financial institutions had performed amid these changes. For this to be accomplish, the work investigates what are the determinants of performance for Swedish Financial Monetary Institutions? Assumptions were derived from theoretical and empirical literatures to investigate the authenticity of this research question using seven explanatory variables. Two models were specified using Returns on Asset (ROA) and Return on Equity (ROE) as the main performance indicators and for the sake of reliability and validity, three different estimators such as Ordinary Least Square (OLS), Generalized Least Square (GLS) and Feasible Generalized Least Square (FGLS) were employed. The Akaike Information Criterion (AIC) was also used to verify which specification explains performance better while performing robustness check of parameter estimates was done by correcting for standard errors. Based on the findings, ROA specification proves to have the lowest Akaike Information Criterion (AIC) and Standard errors compared to ROE specification. Under ROA, two variables; the profit margins and the Interest coverage ratio proves to be statistically significant while under ROE just the interest coverage ratio (ICR) for all the estimators proves significant. The result also shows that the FGLS is the most efficient estimator, then follows the GLS and the last OLS. when corrected for SE robust, the gearing ratio which measures the capital structure becomes significant under ROA and its estimate become positive under ROE robust. Conclusions were drawn that, within the period of study three variables (ICR, profit margins and gearing) shows significant and four variables were insignificant. The overall findings show that the institutions strive to their best to maximize returns but these returns were just normal to cover their costs of operation. Much should be done as per the ASC theory to avoid liquidity and credit risks problems. Again, estimated values of ICR and profit margins shows that a considerable amount of efforts with sound financial policies are required to increase performance by one percentage point. Areas of further research could be how the individual stochastic factors such as the Dupont model, repo rates, inflation, GDP etc. can influence performance.

Technologies for urban and rural internet of things

Nowadays, application domains such as smart cities, agriculture or intelligent transportation, require communication technologies that combine long transmission ranges and energy efficiency to fulfill a set of capabilities and constraints to rely on. In addition, in recent years, the interest in Unmanned Aerial Vehicles (UAVs) providing wireless connectivity in such scenarios is substantially increased thanks to their flexible deployment. The first chapters of this thesis deal with LoRaWAN and Narrowband-IoT (NB-IoT), which recent trends identify as the most promising Low Power Wide Area Networks technologies. While LoRaWAN is an open protocol that has gained a lot of interest thanks to its simplicity and energy efficiency, NB-IoT has been introduced from 3GPP as a radio access technology for massive machine-type communications inheriting legacy LTE characteristics. This thesis offers an overview of the two, comparing them in terms of selected performance indicators. In particular, LoRaWAN technology is assessed both via simulations and experiments, considering different network architectures and solutions to improve its performance (e.g., a new Adaptive Data Rate algorithm). NB-IoT is then introduced to identify which technology is more suitable depending on the application considered. The second part of the thesis introduces the use of UAVs as flying Base Stations, denoted as Unmanned Aerial Base Stations, (UABSs), which are considered as one of the key pillars of 6G to offer service for a number of applications. To this end, the performance of an NB-IoT network are assessed considering a UABS following predefined trajectories. Then, machine learning algorithms based on reinforcement learning and meta-learning are considered to optimize the trajectory as well as the radio resource management techniques the UABS may rely on in order to provide service considering both static (IoT sensors) and dynamic (vehicles) users. Finally, some experimental projects based on the technologies mentioned so far are presented.

Sustainability and environmental impact of the Italian ceramic tile industry

The increasing consumption rates among citizens and the uncontrolled exploitation of natural resources have made environmental pollution and management of waste the main problems facing humanity in its upcoming future. Together with generation of energy and transport, industrial production certainly plays a key role in the genesis of these problems. It is for this reason that the concepts of environmental, social and economic sustainability have emerged over the years as the cornerstones for future development. In light of this, the most forward-looking industries have begun to study their impact on environment and society in order to improve their performances and, at the same time, to anticipate the increasingly rigorous environmental regulations. In this work, various performance indicators related to the Italian ceramic tile sector will be presented and discussed. In particular, the emission factor of characteristic pollutants will be reported on a period of up to fifteen years while data regarding waste management, concentration of pollutants and emission legal limits for the last decade will be here disclosed as a result of a vast analysis on recorded data. The collected information describes the present level of performance of the ceramic tile manufacturing industries in Italy and shows how recycling is now a consolidated reality and how some pollutants, such as particulate matter, fluorine and lead are actually disappearing from production processes and how others, such as volatile organic compounds, are increasing instead. Moreover, the adoption of alternative raw materials for the production of ceramic tiles is discussed and the implementation of the recycling of various waste is addressed at experimental or industrial scale. Finally, the development of a new ceramic engobe with high content of waste glass (20%) is presented as an experimental example of reutilization of resources in the ceramic tile industry.