Matching Items (186)
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Description
This paper analyzes China's transformative changes over the past four decades through a microeconomic lens focused on enterprises. Market-oriented non-state-owned enterprises have emerged as a pivotal force driving China's economic development within this context. The article investigates the determinants of their development. Notably, more than half of market-oriented non-state-owned enterprises

This paper analyzes China's transformative changes over the past four decades through a microeconomic lens focused on enterprises. Market-oriented non-state-owned enterprises have emerged as a pivotal force driving China's economic development within this context. The article investigates the determinants of their development. Notably, more than half of market-oriented non-state-owned enterprises have entered the inheritance stage, necessitating the exploration of novel attributes for sustained growth.The study's research scope is defined across four dimensions, with a specific focus on approximately 4,000 market-oriented non-state-owned enterprises. It investigates the driving factors behind sustained performance growth at various stages of these enterprises, emphasizing five variables: "partnership governance, entrepreneurial spirit, development strategy, incentive mechanisms, and innovation capability." Employing a combination of "typical case studies" and "group validation" methods, the research examines the factors influencing sustained growth in these enterprises and their interrelationships. The goal is to construct a model for enterprise succession and development, ultimately offering recommendations to foster sustained growth. The research paper is structured into an introduction, literature review and theoretical foundation, typical case studies, empirical research on a group, and a conclusion. ii Key findings include: Partnership governance positively impacts partners' entrepreneurial spirit, promoting sustained performance growth. Trajectory-oriented development strategies, effective incentive mechanisms, and leading innovation capabilities have a positive moderating effect on entrepreneurial spirit, fostering sustained performance growth. During the innovation development phase, partnership governance significantly influences entrepreneurial spirit with a noteworthy environmental moderation effect. The paper recommends implementing a "Dual-Factor Improvement Model" that enhances both partnership governance systems and the selection and functioning mechanisms of entrepreneurial spirit partners. This approach aims to boost partners' entrepreneurial spirit and facilitate high-quality succession in market-oriented non-state-owned enterprises,,ultimately achieving sustained high-quality growth. In conclusion, this research contributes to a deeper understanding of sustained performance growth in enterprises. It offers valuable insights for the succession and development of market-oriented non-state-owned enterprises and innovation-driven entrepreneurship. This research holds significant value in advancing sustained high-quality development among market-oriented non-state-owned enterprises in China, optimizing resource allocation, and nurturing talented individuals.
ContributorsDeng, Cheng (Author) / Shen, Wei (Thesis advisor) / Cheng, Shijun (Thesis advisor) / Wu, Fei (Committee member) / Arizona State University (Publisher)
Created2023
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Description
With the increasing aging population in China, the public's emphasis on health has been on the rise. Many innovative pharmaceutical companies have undertaken multiple rounds of financing, with some going public through IPOs. As a high-tech industry, it is essential to study the relationship between the level of corporate publicity

With the increasing aging population in China, the public's emphasis on health has been on the rise. Many innovative pharmaceutical companies have undertaken multiple rounds of financing, with some going public through IPOs. As a high-tech industry, it is essential to study the relationship between the level of corporate publicity and the financing process.This study collected information on the number of promotional articles, timing, and platforms of dozens of pharmaceutical companies that have already gone public through IPOs using Python. An analysis was conducted on the temporal variations of promotional articles for ten representative companies. It was found that the number of promotional articles experienced a significant increase in the month of IPO or the month before, and remained relatively high even after the IPO. Furthermore, the Pearson correlation coefficient method was used to analyze the correlation between the number of promotional articles and various stages of financing. The study found a positive correlation between the daily average number of promotional articles before IPO and the final financing amount. Additionally, a strong positive correlation was observed between the daily average number of promotional articles from 7 days before IPO to IPO day and the turnover rate on IPO day. Grey correlation analysis was also employed to analyze the impact of publicity on the financing amount of each ii financing round, revealing that the financing round and the Shanghai Composite Index had a significant influence. Finally, a multiple regression analysis was conducted to examine the relationship between the pre-IPO financing scale, IPO-day trading amount, and the level of corporate publicity. The regression results indicated that the pre-IPO financing scale was mainly influenced by the number of promotional articles in the 7 days preceding IPO, particularly for pharmaceutical companies listed on the A-share market. Moreover, a negative correlation was observed between the financing round and the financing amount, particularly among companies that experienced a decline in share price on the IPO day. However, the study found a weak association between the IPO-day trading amount and the level of corporate publicity, primarily observed among pharmaceutical companies listed on the A-share market.
ContributorsMiao, Yujia (Author) / Shen, Wei (Thesis advisor) / Jiang, Zhan (Thesis advisor) / Cheng, Shijun (Committee member) / Arizona State University (Publisher)
Created2024
Description
There exists extensive research on the use of twisty puzzles, such as the Rubik's Cube, in educational contexts to assist in developing critical thinking skills and in teaching abstract concepts, such as group theory. However, the existing research does not consider the use of twisty puzzles in developing language proficiency.

There exists extensive research on the use of twisty puzzles, such as the Rubik's Cube, in educational contexts to assist in developing critical thinking skills and in teaching abstract concepts, such as group theory. However, the existing research does not consider the use of twisty puzzles in developing language proficiency. Furthermore, there remain methodological issues in integrating standard twisty puzzles into a class curriculum due to the ease with which erroneous cube twists occur, leading to a puzzle scramble that deviates from the intended teaching goal. To address these issues, an extensive examination of the "smart cube" market took place in order to determine whether a device that virtualizes twisty puzzles while maintaining the intuitive tactility of manipulating such puzzles can be employed both to fill the language education void and to mitigate the potential frustration experienced by students who unintentionally scramble a puzzle due to executing the wrong moves. This examination revealed the presence of Bluetooth smart cubes, which are capable of interfacing with a companion web or mobile application that visualizes and reacts to puzzle manipulations. This examination also revealed the presence of a device called the WOWCube, which is a 2x2x2 smart cube entertainment system that has 24 Liquid Crystal Display (LCD) screens, one for each face's square, enabling better integration of the application with the puzzle hardware. Developing applications both for the Bluetooth smart cube using React Native and for the WOWCube demonstrated the higher feasibility of developing with the WOWCube due to its streamlined development kit as well as its ability to tie the application to the device hardware, enhancing the tactile immersion of the players with the application itself. Using the WOWCube, a word puzzle game featuring three game modes was implemented to assist in teaching players English vocabulary. Due to its incorporation of features that enable dynamic puzzle generation and resetting, players who participated in a user survey found that the game was compelling and that it exercised their critical thinking skills. This demonstrates the feasibility of smart cube applications in both critical thinking and language skills.
ContributorsHreshchyshyn, Jacob (Author) / Bansal, Ajay (Thesis advisor) / Mehlhase, Alexandra (Committee member) / Baron, Tyler (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Solar power, as an important part of renewable energy, has become one of the main choices for countries around the world in their energy strategic layout due to its cleanliness, renewability, and distributed attributes. In the context of the booming photovoltaic industry, China has emerged a large number of excellent

Solar power, as an important part of renewable energy, has become one of the main choices for countries around the world in their energy strategic layout due to its cleanliness, renewability, and distributed attributes. In the context of the booming photovoltaic industry, China has emerged a large number of excellent photovoltaic companies, driving the whole industry to reduce costs and increase efficiency, making many contributions to the grid parity of photovoltaic power generation. In the development lifecycle of the photovoltaic industry, various companies choose different competitive strategies to deal with industry cyclical changes and external uncertainty based on their core competitiveness and market opportunities. Vertical integration is one of the strategic paths chosen by many photovoltaic companies. Therefore, it is an important issue to explore the impact of vertical integration on the development of Chinese photovoltaic companies.Based on the data of China's A-share listed photovoltaic companies from 2018 to 2022, this paper uses panel fixed effect model to empirically test the impact of vertical integration on corporate valuation, explores its influencing mechanism, and further analyzes the moderating effect of enterprise heterogeneity factors. The research in this paper shows that: (1) under other conditions unchanged, vertical integration significantly improves the valuation level of enterprises, and this positive impact will not change with the measurement method of enterprise valuation level. This is because the higher the vertical integration degree of enterprises, the stronger their ability to respond to external uncertainty. The more enterprises can obtain capital market preferences, the higher the enterprise valuation will be. This also means that the higher the vertical integration degree of photovoltaic enterprises, the higher their market share is, and they are more able to avoid the impact of external uncertainty, thus obtaining a higher valuation level in the secondary market. (2) The intermediary effect test shows that the channel for vertical integration of photovoltaic enterprises to affect enterprise valuation levels is to increase their market share. (3) Further heterogeneity analysis shows that enterprise profitability and enterprise size positively regulate the impact of vertical integration on enterprise valuation, while enterprise management shareholding ratio and enterprise operating cost ratio will weaken the positive promotion effect of vertical integration. The research conclusions of this paper provide micro-empirical evidence for how photovoltaic companies can improve their enterprise valuation, and also provide some management references for other unlisted companies in the same industry. Keywords: Photovoltaic enterprises; Vertical integration; Corporate valuation; Fixed effect model
ContributorsZheng, Ren (Author) / Shen, Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Zhao, Yanfei (Committee member) / Arizona State University (Publisher)
Created2024
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Description
SLAM (Simultaneous Localization and Mapping) is a problem that has existed for a long time in robotics and autonomous navigation. The objective of SLAM is for a robot to simultaneously figure out its position in space and map its environment. SLAM is especially useful and mandatory for robots that want

SLAM (Simultaneous Localization and Mapping) is a problem that has existed for a long time in robotics and autonomous navigation. The objective of SLAM is for a robot to simultaneously figure out its position in space and map its environment. SLAM is especially useful and mandatory for robots that want to navigate autonomously. The description might make it seem like a chicken and egg problem, but numerous methods have been proposed to tackle SLAM. Before the rise in the popularity of deep learning and AI (Artificial Intelligence), most existing algorithms involved traditional hard-coded algorithms that would receive and process sensor information and convert it into some solvable sensor-agnostic problem. The challenge for these sorts of methods is having to tackle dynamic environments. The more variety in the environment, the poorer the results. Also due to the increase in computational power and the capability of deep learning-based image processing, visual SLAM has become extremely viable and maybe even preferable to traditional SLAM algorithms. In this research, a deep learning-based solution to the SLAM problem is proposed, specifically monocular visual SLAM which is solving the problem of SLAM purely with a singular camera as the input, and the model is tested on the KITTI (Karlsruhe Institute of Technology & Toyota Technological Institute) odometry dataset.
ContributorsRupaakula, Krishna Sandeep (Author) / Bansal, Ajay (Thesis advisor) / Baron, Tyler (Committee member) / Acuna, Ruben (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Frontend development often involves the repetitive and time-consuming task of transforming a Graphical User interface (GUI) design into Frontend Code. The GUI design could either be an image or a design created on tools like Figma, Sketch, etc. This process can be particularly challenging when the website designs are experimental

Frontend development often involves the repetitive and time-consuming task of transforming a Graphical User interface (GUI) design into Frontend Code. The GUI design could either be an image or a design created on tools like Figma, Sketch, etc. This process can be particularly challenging when the website designs are experimental and undergo multiple iterations before the final version gets deployed. In such cases, developers work with the designers to make continuous changes and improve the look and feel of the website. This can lead to a lot of reworks and a poorly managed codebase that requires significant developer resources. To tackle this problem, researchers are exploring ways to automate the process of transforming image designs into functional websites instantly. This thesis explores the use of machine learning, specifically Recurrent Neural networks (RNN) to generate an intermediate code from an image design and then compile it into a React web frontend code. By utilizing this approach, designers can essentially transform an image design into a functional website, granting them creative freedom and the ability to present working prototypes to stockholders in real-time. To overcome the limitations of existing publicly available datasets, the thesis places significant emphasis on generating synthetic datasets. As part of this effort, the research proposes a novel method to double the size of the pix2code [2] dataset by incorporating additional complex HTML elements such as login forms, carousels, and cards. This approach has the potential to enhance the quality and diversity of training data available for machine learning models. Overall, the proposed approach offers a promising solution to the repetitive and time-consuming task of transforming GUI designs into frontend code.
ContributorsSingh, Ajitesh Janardan (Author) / Bansal, Ajay (Thesis advisor) / Mehlhase, Alexandra (Committee member) / Baron, Tyler (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Since the early 2000s the Rubik’s Cube has seen growing usage at speedsolving competitions and as an effective tool to teach Science, Technology, Engineering, Mathematics (STEM) topics at hundreds of schools and universities across the world. Recently, cube manufacturers have begun embedding sensors to enable digital face tracking. The live

Since the early 2000s the Rubik’s Cube has seen growing usage at speedsolving competitions and as an effective tool to teach Science, Technology, Engineering, Mathematics (STEM) topics at hundreds of schools and universities across the world. Recently, cube manufacturers have begun embedding sensors to enable digital face tracking. The live feedback from these so called “smartcubes” enables a new wave of immersive solution tutorials and interactive educational games using the cube as a controller. Existing smartcube software has several limitations. Manufacturers’ applications support only a narrow set of puzzle form factors and application platforms, fragmenting the ecosystem. Most apps require an active internet connection for key features, limiting where users can practice with a smartcube. Finally, existing applications focus on a single 3x3x3connection, losing opportunities afforded by new form factors. This research demonstrates an open-source smartcube application which mitigates these limitations. Particular attention is given to creating an Application Programming Interface (API) for smartcube communication and building representative solve analysis tools. These innovations have included successful negotiations to re-license existing open-source Rubik’sCube software projects to support deployment on multiple platforms, particularly iOS. The resulting application supports smartcubes from three manufacturers, runs on two platforms (Android and iOS), functions entirely offline after an initial download of remote assets, demonstrates concurrent connections with up to six smartcubes, and supports all current and anticipated smartcube form factors. These foundational elements can accelerate future efforts to build smartcube applications, including automated performance feedback systems and personalized gamification of learning experiences. Such advances will hopefully enhance the Rubik’s Cube’s value both as a competitive toy and as a pedagogical tool in educational institutions worldwide.
ContributorsHale, Joseph (Author) / Bansal, Ajay (Thesis advisor) / Heinrichs, Robert (Committee member) / Gary, Kevin (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Recommendation systems provide recommendations based on user behavior andcontent data. User behavior and content data are fed to machine learning algorithms to train them and give recommendations to the users. These algorithms need a large amount of data for a reasonable conversion rate. But for small applications, the available amount of data is

Recommendation systems provide recommendations based on user behavior andcontent data. User behavior and content data are fed to machine learning algorithms to train them and give recommendations to the users. These algorithms need a large amount of data for a reasonable conversion rate. But for small applications, the available amount of data is minimal, leading to high recommendation aberrations. Also, when an existing large scaled application with a high amount of available data uses a new recommendation system, it requires some time and testing to decide which recommendation algorithm is best suited to get higher conversion rates. This learning curve costs highly when the user base and data size are significantly high. In this thesis, A/B testing is used with manual intervention in the decision-making of recommendation systems. To understand the effectiveness of the recommendations, user interaction data is compared to compare experiences. Based on the comparisons, the experiments conclude the effectiveness of A/B testing for the recommendation system.
ContributorsVaidya, Yogesh Vinayak (Author) / Bansal, Ajay (Thesis advisor) / Findler, Michael (Committee member) / Chakravarthi, Bharatesh (Committee member) / Arizona State University (Publisher)
Created2023
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Description本文通过分析F证券公司某营业部13000余名投资者从2019到2021年的交易和持仓数据,以及研究投资者处置效应的各主要性质,本文发现,投资者的处置效应造成了相当一部分交易损失。在投资者个人特征方面,风险评级越高的投资者处置效应越弱,印证了处置效应与风险厌恶的关系。更为重要的是,投资者的投资组合分散程度与处置效应负相关、投资组合彩票性质与处置效应正相关。这分别印证了风险厌恶和主观概率作为累积前景理论的核心组成部分,对处置效应的影响。本研究由此得出针对散户投资者的投资建议:在分散化投资的同时,有意识地克服出盈保亏的倾向;侧重于配置安全边际高的股票,减少对于彩票型股票的配置。
ContributorsGong, Haifeng (Author) / Shen, Wei (Thesis advisor) / Wu, Fei (Thesis advisor) / Li, Xianglin (Committee member) / Arizona State University (Publisher)
Created2023
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Description在日趋复杂动态的环境中,如何提高企业的绩效不仅是企业家最感兴趣的事情,也是众多学者进行企业管理方面研究的落脚点。从目前战略执行力的研究现状来看,一些学者对战略执行力的性质和构成进行了研究,并取得了一定的成果。但这些研究多为描述性分析,实证研究较少,且较为分散,尚未形成较为完整的分析框架。对于战略执行力、员工生产力与企业绩效关系的研究则更少。因此,本研究将通过对现有文献的分析和梳理,研究战略执行的本质及其构成并进一步研究战略执行力与企业绩效的关系及其作用机理。
ContributorsLiu, Baozhong (Author) / Shen, Wei (Thesis advisor) / Shi, Weilei (Thesis advisor) / Huang, Xiaochuan (Committee member) / Arizona State University (Publisher)
Created2023