<div>This dissertation consists of three essays that study problems that decision-makers face when hitherto niche technologies scale up. Typically, scaling up involves market expansion with participation from a variety of agents with complex preferences, using the technology to maximize their utility. A major problem for the decision maker then is either one or a combination of the following: deciding policy for optimal business or social outcomes, implementing effcient demand allocation mechanisms or improving market design.</div>

Manufacturing hiring managers in the United States who fail to implement adequate recruitment strategies for skilled production workers experience reduced profits and sustainability challenges. The purpose of this multiple case study was to explore the strategies that successful manufacturing hiring managers in North Carolina used to recruit skilled production workers to sustain business profitability. Inductive analysis was guided by the human capital theory, and trustworthiness of interpretations was strengthened by member checking. The population for the study consisted of 4 business leaders who demonstrated the use of effective recruitment strategies to sustain profitability in manufacturing businesses in southeastern North Carolina. Data were collected from face-to-face interviews with the leaders and review of artifacts pertaining to employee recruitment strategies. Six themes emerged: fueling competition for local labor market, enhancing advertising methods, networking, providing job training, growing talent, and building new perceptions of manufacturing. The application of the findings from this study could contribute to positive social change by providing manufacturing business leaders with effective strategies for recruiting skilled workers. Business leaders could contribute to positive social change by increasing workplace stability and employees' abilities to support their families. Businesses and individuals could benefit from improved standards of living, thereby contributing to the sustainment and prosperity of communities.

<p dir="ltr">In my dissertation, I delve into the moderation and economic dynamics of online platforms. With the proliferation of platforms facilitating user interaction, it becomes imperative to grasp the mechanisms underlying content creation and the economic ramifications of such policies on diverse user groups. Comprising three essays, my dissertation examines the influence of crowd-sourced misinformation monitoring, the effects of privacy on content creation by fact-checkers, and the likelihood of platform acquisition.</p><p dir="ltr">In the first essay, I investigate the impacts of crowd-based misinformation monitoring programs by examining how implementing crowd-based monitoring affects both the quality and quantity of user-generated content. Using data from Twitter's Birdwatch program, I find that content quality, measured subjectively through cognition, improves, while objective measures like user engagement show no significant change. Additionally, there's a decrease in sentiment extremity and machine-learning-calculated misinformation, indicating a potential improvement in overall content quality and reduction in misinformation. However, the program's launch leads to fewer tweets suggesting a trade-off with reduced content volume. </p><p dir="ltr">In my second essay, I analyze how privacy measures affect fact-checkers' content creation. Using Twitter's Birdwatch program, which assigns aliases to fact-checkers, I study the impact of anonymity on their behavior. The results show that privacy measures lead to more content creation on the main platform without any impact to fact-checking activity. Additionally, the content becomes more neutral and less negative. Users also feel more comfortable discussing political topics on Twitter afterward. These findings underscore the importance of privacy measures for effective misinformation monitoring.</p><p dir="ltr">In my third essay, I examine the likelihood of platform company acquisitions, a trend on the rise. These companies' multi-sided nature increases their complexity, presenting both challenges and opportunities in acquisitions. While complexity can lead to information asymmetry, it also enhances attractiveness as an acquisition target. Analyzing Crunchbase data, I find a positive correlation between platform company complexity and acquisition likelihood. </p>

Lu, Lian. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 91-95). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.

從文件系統設計的角度,我們探索了利用重復數據删除技術來消除硬盤陣列存儲設備當中的重復數據。我們提出了ScaleDFS,一個重復數據删除技術的文件系統, 旨在硬盤陣列存儲設備上實現可擴展的吞吐性能。ScaleDFS有三個主要的特點。第一,利用多核CPU並行計算出用作識別重復數據的加密指紋,以提高寫入速度。第二,緩存曾經讀取過的重復數據塊,以顯著提高讀取速度。第三,優化用作查找指紋的內存數據結構,以更加節省內存。ScaleDFS是一個以Linux系統內核模塊開發的,與POSIX兼容的,可以用在一般低成本硬件配置上的文件系統。我們進行了一系列的微觀性能測試,以及用42個不同版本的Linux虛擬鏡像文件進行了宏觀性能測試。我們證實,ScaleDFS在磁盤陣列上比目前已有的開源重復數據删除文件系統擁有更好的讀寫性能。 / We explore the use of deduplication for eliminating the storage of redundant data in RAID from a file-system design perspective. We propose ScaleDFS, a deduplication file system that seeks to achieve scalable read/write throughput in RAID. ScaleDFS is built on three novel design features. First, we improve the write throughput by exploiting multiple CPU cores to parallelize the processing of the cryptographic fingerprints that are used to identify redundant data. Second, we improve the read throughput by specifically caching in memory the recently read blocks that have been deduplicated. Third, we reduce the memory usage by enhancing the data structures that are used for fingerprint lookups. ScaleDFS is implemented as a POSIX-compliant, kernel-space driver module that can be deployed in commodity hardware configurations. We conduct microbenchmark experiments using synthetic workloads, and macrobenchmark experiments using a dataset of 42 VM images of different Linux distributions. We show that ScaleDFS achieves higher read/write throughput than existing open-source deduplication file systems in RAID. / Detailed summary in vernacular field only. / Ma, Mingcao. / "October 2012." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 39-42). / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.2 / Chapter 2 --- Literature Review --- p.5 / Chapter 2.1 --- Backup systems --- p.5 / Chapter 2.2 --- Use of special hardware --- p.6 / Chapter 2.3 --- Scalable storage --- p.6 / Chapter 2.4 --- Inline DFSs --- p.6 / Chapter 2.5 --- VM image storage with deduplication --- p.7 / Chapter 3 --- ScaleDFS Background --- p.8 / Chapter 3.1 --- Spatial Locality of Fingerprint Placement --- p.9 / Chapter 3.2 --- Prefetching of Fingerprint Stores --- p.12 / Chapter 3.3 --- Journaling --- p.13 / Chapter 4 --- ScaleDFS Design --- p.15 / Chapter 4.1 --- Parallelizing Deduplication --- p.15 / Chapter 4.2 --- Caching Read Blocks --- p.17 / Chapter 4.3 --- Reducing Memory Usage --- p.17 / Chapter 5 --- Implementation --- p.20 / Chapter 5.1 --- Choice of Hash Function --- p.20 / Chapter 5.2 --- OpenStack Deployment --- p.21 / Chapter 6 --- Experiments --- p.23 / Chapter 6.1 --- Microbenchmarks --- p.23 / Chapter 6.2 --- OpenStack Deployment --- p.28 / Chapter 6.3 --- VM Image Operations in a RAID Setup --- p.33 / Chapter 7 --- Conclusions and FutureWork --- p.38 / Bibliography --- p.39

動態頻譜共享(dynamic spectrum sharing) 允許不具有執照的無線電用戶(坎級用戶)擇機使用具有執照的無線電用戶(主用戶)的頻譜，因此被認為是一種有效解決頻譜低效利用問題的方案。本論文研究次級用戶如何智能地實現高效率的動態頻譜共享。我們考慮兩種智能共享模式:社交智能(social intelligence) 以及個體智能(individual intelligence) 。 / 對於社交智能，次級用戶基於社交互動(social interactions) 來協作地共享頻譜。受到電子商務工業的推薦系統(recommendation sYstem) 的啟發，我們提出了一種基於推薦的社交頻譜共享機制。其中，次級用戶相互協作，彼此推薦良好的信道， 并動態接入信道。我們設計了種基於馬爾科夫決策過程( Markovdecision process) 的自適應信道推薦算法。該算法可突現良好的系統通信性能。同時，我們也提出種基於模仿(imitation) 的社交頻譜分享機制。其中，次級用戶根據自身觀察來估計自己的期望通信速率并彼此分享。如果鄰近用戶的期望通信速率更高，該用戶則模仿鄰近用戶的信道接入。我們證明該機制能夠有效地收斂到模仿均衡。如果次級用戶的數目較多，收斂的模仿均衡即是納什均衡(Nashequilibrium) 。該均衡是個次級用戶相互滿意的頻譜共享結果。 / 對於個體智能，次級用戶基於策略互動(strategic interactions) 來競爭地共享頻譜。對於基於空間複用(spatial reuse) 的競爭性頻譜共享，我們提出了種新穎的空間頻譜接入博弈框架。我們研究了不同的干擾圖形結構對於納什均衡的存在性的影響。同時，我們設計了種基於用戶自身觀察的分佈式學習算法。該算法適用於所有空間頻譜接入博弈，并能夠有效地收斂到近似納什均衡(approximateNash equilibrium) 。對於基於數據庫的電視頻譜(white-space spectrum) 無線AP(access point)網絡，我們運用博弈理論方法為分佈式AP 信道選擇問題以及分佈式次級用戶AP 連接問題建立理論模型。我們證明了分佈式AP信道選擇博奔以及分佈式次級用戶AP 連接博弈屬於勢博弈(potential game) 的範疇。基於勢博莽的有限改進性質(finite improvement property) ，我們設計了分佈式算法能夠有效地收斂到納什均衡。 / Dynamic spectrum sharing enables unlicensed secondary wireless users to opportunistically share the spectrum with licensed primary users, and thus is envisioned as a promising solution to address the spectrum under-utilization problem. This thesis explores the intelligence of secondary users for achieving efficient distributed spectrum sharing. We consider two types of intelligences: social intelligence and individual intelligence. / For the social intelligence, secondary users share the spectrum collaboratively based on social interactions. Inspired by the recommendation system in the electronic commerce industry, we propose a recommendation-based social spectrum sharing mechanism, where secondary users collaboratively recommend "good" channels to each other and access accordingly. We devise an adaptive channel recommendation algorithm based on Markov decision process, which achieves a good system communication performance. We then propose an imitation-based social spectrum sharing mechanism, where each secondary user estimates its expected throughput based on local observations, and imitates another neighboring user’s channel selection if neighbor’s estimated throughput is higher. We show that the mechanism can converge to an imitation equilibrium. When the number of users is large, the convergent imitation equilibrium corresponds to a Nash equilibrium, which is a mutually satisfactory spectrum sharing solution. / For the individual intelligence, secondary users share the spectrum competitively based on strategic interactions. To formulate the competitive spectrum sharing with spatial reuse, we propose a framework of spatial spectrum access game on general directed interference graphs. We investigate the impact of the underlying interference graph structure on the existence of a Nash equilibrium. We also design a distributed learning algorithm based on local observations that can converge to an approximate Nash equilibrium for any spatial spectrum access games. We then apply the game theoretic approach for modeling the distributed channel selection problem among the APs and distributed AP association problem among the secondary users in database-assisted white-space AP networks. We show that both the distributed AP channel selection game and the distributed AP association game are potential games. We then design distributed algorithms for achieving Nash equilibria by utilizing the finite improvement property of potential game. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Chen, Xu. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 180-188). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Overview --- p.1 / Chapter 1.2 --- Thesis Outline --- p.5 / Chapter I --- Social Intelligence For Distributed Spectrum Sharing --- p.7 / Chapter 2 --- Recommendation-based Social Spectrum Sharing --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- System Model --- p.12 / Chapter 2.3 --- Introduction To Channel Recommendation --- p.13 / Chapter 2.3.1 --- Review of Static Channel Recommendation --- p.14 / Chapter 2.3.2 --- Motivations For Adaptive Channel Recommendation --- p.16 / Chapter 2.4 --- Adaptive Channel Recommendation With Channel Homogeneity --- p.18 / Chapter 2.4.1 --- MDP Formulation For Adaptive Channel Recommendation --- p.19 / Chapter 2.4.2 --- Existence of Optimal Stationary Policy --- p.21 / Chapter 2.5 --- Model Reference Adaptive Search For Optimal Spectrum Access Policy --- p.22 / Chapter 2.5.1 --- Model Reference Adaptive Search Method --- p.23 / Chapter 2.5.2 --- Model Reference Adaptive Search For Optimal Spectrum Access Policy --- p.24 / Chapter 2.5.3 --- Convergence of Model Reference Adaptive Search --- p.29 / Chapter 2.6 --- Adaptive Channel Recommendation With Channel Heterogeneity --- p.30 / Chapter 2.7 --- Numerical Results --- p.33 / Chapter 2.7.1 --- Simulation Setup --- p.33 / Chapter 2.7.2 --- Homogeneous Channel Recommendation --- p.34 / Chapter 2.7.3 --- Heterogenous Channel Recommendation --- p.35 / Chapter 2.8 --- Chapter Summary --- p.38 / Chapter 2.9 --- Appendix --- p.39 / Chapter 2.9.1 --- Proof of Lemma 2.1 --- p.39 / Chapter 2.9.2 --- Derivation of Transition Probability --- p.40 / Chapter 2.9.3 --- Proof of Theorem 2.1 --- p.41 / Chapter 2.9.4 --- Proof of Theorem 2.2 --- p.42 / Chapter 2.9.5 --- Proof of Theorem 2.3 --- p.47 / Chapter 2.9.6 --- Proof of Theorem 2.4 --- p.50 / Chapter 3 --- Imitation-based Social Spectrum Sharing --- p.52 / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Spectrum Sharing System Model --- p.55 / Chapter 3.3 --- Imitative Spectrum Access Mechanism --- p.58 / Chapter 3.3.1 --- Expected Throughput Estimation --- p.59 / Chapter 3.3.2 --- Information Sharing Graph --- p.63 / Chapter 3.3.3 --- Imitative Spectrum Access --- p.63 / Chapter 3.4 --- Convergence of Imitative Spectrum Access --- p.65 / Chapter 3.4.1 --- Cluster-based Representation of Information Sharing Graph --- p.65 / Chapter 3.4.2 --- Dynamics of Imitative Spectrum Access --- p.67 / Chapter 3.4.3 --- Convergence of Imitative Spectrum Access --- p.71 / Chapter 3.5 --- Imitative Spectrum Access with Innovation --- p.73 / Chapter 3.6 --- Imitative Spectrum Access With User Heterogeneity --- p.75 / Chapter 3.7 --- Simulation Results --- p.77 / Chapter 3.7.1 --- Large User Population --- p.78 / Chapter 3.7.2 --- Small User Population --- p.82 / Chapter 3.7.3 --- Markovian Channel Environment --- p.85 / Chapter 3.7.4 --- Imitative Spectrum Access With User Heterogeneity --- p.88 / Chapter 3.8 --- Chapter Summary --- p.88 / Chapter 3.9 --- Appendix --- p.89 / Chapter 3.9.1 --- Proof of Theorem 3.1 --- p.89 / Chapter 3.9.2 --- Proof of Theorem 3.2 --- p.91 / Chapter II --- Individual Intelligence For Distributed Spectrum Sharing --- p.93 / Chapter 4 --- Spatial Spectrum Access Game --- p.94 / Chapter 4.1 --- Introduction --- p.94 / Chapter 4.2 --- System Model --- p.97 / Chapter 4.3 --- Spatial Spectrum Access Game --- p.101 / Chapter 4.4 --- Existence of Nash Equilibria --- p.102 / Chapter 4.4.1 --- Existence of Pure Nash Equilibria on Directed Interference Graphs --- p.103 / Chapter 4.4.2 --- Existence of Pure Nash Equilibria on Undirected Interference Graphs --- p.108 / Chapter 4.5 --- Distributed Learning For Spatial Spectrum Access --- p.113 / Chapter 4.5.1 --- Expected Throughput Estimation --- p.114 / Chapter 4.5.2 --- Distributed Learning Algorithm --- p.115 / Chapter 4.5.3 --- Convergence of Distributed Learning Algorithm --- p.117 / Chapter 4.6 --- Numerical Results --- p.121 / Chapter 4.7 --- Chapter Summary --- p.126 / Chapter 4.8 --- Appendix --- p.127 / Chapter 4.8.1 --- Proof of Theorem 4.2 --- p.127 / Chapter 4.8.2 --- Proof of Theorem 4.3 --- p.129 / Chapter 4.8.3 --- Proof of Lemma 4.4 --- p.131 / Chapter 4.8.4 --- Proof of Lemma 4.5 --- p.133 / Chapter 4.8.5 --- Proof of Theorem 4.5 --- p.136 / Chapter 4.8.6 --- Proof of Theorem 4.6 --- p.139 / Chapter 5 --- Distributed AP Channel Selection Game --- p.141 / Chapter 5.1 --- Introduction --- p.141 / Chapter 5.2 --- Distributed AP Channel Selection --- p.144 / Chapter 5.2.1 --- Problem Formulation --- p.144 / Chapter 5.2.2 --- Distributed AP Channel Selection Game --- p.146 / Chapter 5.3 --- Distributed AP Channel Selection Algorithms --- p.149 / Chapter 5.3.1 --- Distributed AP Channel Selection Algorithm With Information Exchange --- p.149 / Chapter 5.3.2 --- Distributed AP Channel Selection Algorithm Without Information Exchange --- p.151 / Chapter 5.4 --- Numerical Results --- p.157 / Chapter 5.4.1 --- Distributed AP Channel Selection With Information Exchange --- p.157 / Chapter 5.4.2 --- Distributed AP Channel Selection Without Information Exchange --- p.159 / Chapter 5.5 --- Chapter Summary --- p.161 / Chapter 5.6 --- Appendix --- p.162 / Chapter 5.6.1 --- Proof of Theorem 5.2 --- p.162 / Chapter 6 --- Distributed AP Association Game --- p.165 / Chapter 6.1 --- Introduction --- p.165 / Chapter 6.2 --- Distributed AP Association --- p.166 / Chapter 6.2.1 --- Channel Contention Within an AP --- p.167 / Chapter 6.2.2 --- Distributed AP Association Game --- p.168 / Chapter 6.2.3 --- Distributed AP Association Algorithm --- p.170 / Chapter 6.3 --- Numerical Results --- p.172 / Chapter 6.4 --- Chapter Summary --- p.175 / Chapter 7 --- Conclusions and Future Work --- p.176 / Bibliography --- p.180

Advanced technologies, a world-wide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex cost-to-go functions (i.e. the storage content value curves). The multi-stage problem of multi-storage power system scheduling is thus decomposed into many smaller one-stage subproblems with evolved cost-to-go functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multi-storage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, non-convex and non-smooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.

Advanced technologies, a world-wide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex cost-to-go functions (i.e. the storage content value curves). The multi-stage problem of multi-storage power system scheduling is thus decomposed into many smaller one-stage subproblems with evolved cost-to-go functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multi-storage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, non-convex and non-smooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.

Advanced technologies, a world-wide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex cost-to-go functions (i.e. the storage content value curves). The multi-stage problem of multi-storage power system scheduling is thus decomposed into many smaller one-stage subproblems with evolved cost-to-go functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multi-storage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, non-convex and non-smooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.

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