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Wang seeks to explain why one company committed securities fraud only during certain years and why some companies had a higher propensity to commit securities fraud. He finds evidence linking executive incentive compensation to securities fraud. Some corporate governance measures may also play a role in fraud control. Findings vary, however, depending on the stages of judicial proceedings at which securities fraud class action cases are examined. Researchers and practitioners from fields other than criminal justice, such as law and economics, management, and accounting, may find this work usef.

Problem statement and its relevance. One of the pioneers of Chinese contemporary piano art, whose creative activity certainly contributed to its formation, further rapid rise and recognition of creative achievements on the world art horizon, is a prominent pianist — Liu Shikun, who today has received complete recognition as a brilliant performer, composer and teacher thus marked the beginning of the so­called piano boom in China, and with it — the gradual formation and confident rise of the Chinese piano school. If various aspects of contemporary Chinese performing arts have repeatedly been subjected to musicological discourse in the scientific community, the direct and comprehensive coverage of Liu Shikun's leading role in the process of forming the foundations of Chinese piano performing arts, as well as careful analysis and representation of his creative achievements and pedagogical fields are still relevant for basic musicological research.
The purpose of this article is to highlight and analyze the main vectors of creative activity of the famous Chinese musician Liu Shikun in the context of the development of piano art in China in the second half of the XX — early XXI centuries.
The methodology of the work focuses on the principles of historicism and source studies, which provides coverage of Liu Shikun's musical work in a single context with cultural, historical and artistic phenomena and their interaction. In addition, methods of retrospective, structural­system analysis, interpretation of facts, argumentation and generalization are involved.
The results obtained during the achievement of the goal of this work focus on the representation and characterization of Liu Shikun's creative achievements in the field of concert performance, teaching and composition and the artist's contribution to the development of Chinese piano culture.
The topicality of the article lies in the first attempt in Ukrainian musicology to comprehensively cover the main directions of creative activity of the famous Chinese pianist Liu Shikun in the projection of his influence on the formation of the current state of Chinese piano art.
The practical significance of the facts and analysis of the main vectors of Liu Shikun's creative activity carried out in this work is the possibility of using this material in courses on the history and theory of modern piano art, in particular in sections on the Chinese piano school, as well as for further more thorough research of Liu Shikun's musical creativity, systematization of scientific information on his contribution to the development of musical art of this country.
Conclusions. Summarizing the above given material, it should be noted that the fruitful and multifaceted work of this artist directly influenced the development and professionalization of piano performance in China at that time. This influence was due to the comprehensive recognition of the artist's creative achievements by the world music community, in particular through numerous concert performances in leading countries (especially in partnership with leading orchestras and outstanding musicians); creation of original samples of concert repertoire on the basis and with specificity of the Chinese traditional melody; organization of a dense network of author's music schools (art centers) and formation of the foundations of the Chinese national piano pedagogy.

Tools used to evaluate transportation infrastructure investments are typically deterministic and rely on present value calculations, even though it is well-known this approach is likely to result in sub-optimal decisions in the presence of uncertainty, which is pervasive in transportation infrastructure decisions. This dissertation proposes a framework based on real options and advanced numerical methods to make better road infrastructure decisions in the presence of demand uncertainty. A real options framework was developed to find the optimal investment timing, endogenous toll rate, and road capacity of a private inter-city highway under demand uncertainty. Traffic congestion is represented by a BPR function, competition with an existing road is captured by user equilibrium, and travel demand between the two cities follows a geometric Brownian motion with a reflecting upper barrier. The result shows the importance of modeling congestion and an upper demand barrier – features missing from previous studies. The real options framework was extended to study two additional ways of funding an inter-city highway project: with public funds or via a Public-Private Partnership (PPP). Using Monte Carlo simulation, the value of a non-compete clause was investigated for both a local government and for private firms involved in the PPP. Since road infrastructure investments are rarely made in isolation, the real options framework was extended to the multi-period Continuous Network Design Problem (CNDP) to analyze the investment timing and capacity of multiple links under demand uncertainty. No algorithm is currently available to solve the multi-period CNDP under uncertainty in a reasonable time. A new algorithm called "Approximate Least Square Monte Carlo simulation" is proposed and tested that dramatically reduces the computing time to solve the CNDP while generating accurate solutions

An efficient transportation system requires adequate and well-maintained infrastructure to relieve congestion, reduce accidents, and promote economic competitiveness. However, there is a growing gap between public financial commitments and the cost of maintaining, let alone expanding the U.S. road transportation infrastructure. Moreover, the tools used to evaluate transportation infrastructure investments are typically deterministic and rely on present value calculations, even though it is well-known that this approach is likely to result in sub-optimal decisions in the presence of uncertainty, which is pervasive in transportation infrastructure decisions. In this context, the purpose of this dissertation is to propose a framework based on real options and advanced numerical methods to make better road infrastructure decisions in the presence of demand uncertainty. I first develop a real options framework to find the optimal investment timing, endogenous toll rate, and road capacity of a private inter-city highway under demand uncertainty. Traffic congestion is represented by a BPR function, competition with an existing road is captured by user equilibrium, and travel demand between the two cities follows a geometric Brownian motion with a reflecting upper barrier. I derive semi-analytical solutions for the investment threshold, the dynamic toll rates and the optimum capacity. The result shows the importance of modeling congestion and an upper demand barrier – features that are missing from previous studies. I then extend this real options framework to study two additional ways of funding an inter-city highway project: with public funds or via a Public-Private Partnership (PPP). Using Monte Carlo simulation, I investigate the value of a non-compete clause for both a local government and for private firms involved in the PPP.Since road infrastructure investments are rarely made in isolation, I also extend my real options framework to the multi-period Continuous Network Design Problem (CNDP), to analyze the investment timing and capacity of multiple links under demand uncertainty. No algorithm is currently available to solve the multi-period CNDP under uncertainty in a reasonable time. I propose and test a new algorithm called "Approximate Least Square Monte Carlo simulation" that dramatically reduces the computing time to solve the CNDP while generating accurate solutions.

In construction projects, improper quality behavior of a participant results in quality behavior risks, which can transmit to the downstream participants and may cause detrimental effects on the quality of the entity finally constructed. Controlling the transmission of quality behavior risks is the key to effectively supervising and ensuring the quality of construction projects. In this study, the effectiveness of the quality supervision system of construction projects in China was investigated by considering the transmission of quality behavior risks. A multi-player evolutionary game model consisting of the players of quality supervision of a government department, upstream participant (UP), and downstream participant (DP) was generated. By using the system dynamics theory, the game model was simulated to determine the stability of the evolutionary system and to evaluate the effectiveness of China's current quality supervision system under different scenarios. The results showed that there is no evolutionary stable strategy (ESS) in the evolutionary system of the current quality supervision system in China and there are fluctuations in the evolution process. It revealed that high risk exists in the current quality supervision system in China. To resolve the problem of the low efficiency of the current Chinese supervision system, a dynamic penalty and incentive method is developed, which has been proven to be able to effectively control the quality behavior risks in construction projects and hence ensuring the quality of the entity finally constructed.