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- Genre: Doctoral Dissertation
- Creators: Gu, Bin
Description现今的理论研究及实践表明，供应链上各个企业进行协调运作的基础是节点企业间有效信息进行高效传递。但供应链上下游企业在合作过程中通常存在信息不完全对称现象、牛鞭效应等问题，供应链中信息传递的实时性及真实性受到较大影响，这也是导致供应链管理整体效率不高的原因之一。因此，供应链伙伴间信息共享问题已是国内外学者普遍关注的焦点。本文旨在针对目前我国家居供应链企业间信息沟通不畅、信息共享不充分的问题及其理论研究的不足，来开展针对影响家居供应链企业间信息共享因素的实证研究。本文基于家居供应链这一特殊的行业供应链，建立基于家居供应链企业间信息共享关键影响因素理论模型，通过实证方法来寻找影响供应链企业间信息共享的关键因素及其具体影响程度。
在已有文献的基础上，本文提出信任、共同愿景、信息技术能力、渠道权力结构与信息共享间影响关系的概念模型，并对长三角及珠三角地区家居供应链经销商企业进行问卷调查研究。最后在回收的 164 份有效问卷基础上通过数据分析来验证假设。研究结果显示：(1)不论是家居工厂与经销商间还是家居卖场与经销商间，信任对共享信息的内容和质量都有显著正向影响。(2)家居工厂与经销商间的共同愿景对彼此间信息共享内容有显著正向影响作用，但对信息共享质量作用不明显。而家居卖场与经销商间的共同愿景对信息共享的内容和质量都有正向影响作用。(3)经销商的信息技术能力对双方间信息共享的内容和质量都有显著影响，同时，还能促进家居工厂与经销商之间的信任，间接影响双方的信息共享程度。(4) 家居卖场与经销商间的渠道权力对双方间的信任程度有显著影响，而对双方间的信息共享没有直接影响。
本研究主要研究贡献在于：发现影响家居供应链信息共享的关键因素，弥补了现有文献对中国供应链企业信息共享影响因素研究的不足，特别聚焦于家居供应链；从供应链上下游整体角度出发，探讨了中国情境下信任、共同愿景、信息技术能力和渠道权力结构与信息共享之间的作用机理。
在已有文献的基础上，本文提出信任、共同愿景、信息技术能力、渠道权力结构与信息共享间影响关系的概念模型，并对长三角及珠三角地区家居供应链经销商企业进行问卷调查研究。最后在回收的 164 份有效问卷基础上通过数据分析来验证假设。研究结果显示：(1)不论是家居工厂与经销商间还是家居卖场与经销商间，信任对共享信息的内容和质量都有显著正向影响。(2)家居工厂与经销商间的共同愿景对彼此间信息共享内容有显著正向影响作用，但对信息共享质量作用不明显。而家居卖场与经销商间的共同愿景对信息共享的内容和质量都有正向影响作用。(3)经销商的信息技术能力对双方间信息共享的内容和质量都有显著影响，同时，还能促进家居工厂与经销商之间的信任，间接影响双方的信息共享程度。(4) 家居卖场与经销商间的渠道权力对双方间的信任程度有显著影响，而对双方间的信息共享没有直接影响。
本研究主要研究贡献在于：发现影响家居供应链信息共享的关键因素，弥补了现有文献对中国供应链企业信息共享影响因素研究的不足，特别聚焦于家居供应链；从供应链上下游整体角度出发，探讨了中国情境下信任、共同愿景、信息技术能力和渠道权力结构与信息共享之间的作用机理。
ContributorsYang, Yu (Author) / Gu, Bin (Thesis advisor) / Chen, Xinlei (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2019
Description中国商品期货市场经历30年发展，已初备协调资源分配、对冲经营风险的功能。但受产业自身和期货市场发展的制约，各期货品种市场有效性参差不齐。随着我国经济从增量阶段过渡到存量阶段，期货作为企业的价格管理和风险控制工具的重要性日益凸显，因此研究我国商品期货市场有效性具有非常好的现实意义。
本文开创性的从期货的基本功能——资源配置的角度出发，提出有效市场是指其期货价格能够对本行业社会资源起到合理的调配作用的市场。在内容安排上，本文首先总结了现有国际成熟期货品种的特点并找出能够反映期货对资源配置能力的四个指标假说，分别为期现回归性、利润波动性、库存波动性以及现金流变化，然后通过数学模型证明指标数据和品种成熟度的关联，最后应用该套指标对我国商品市场有效性进行检验。数学方法上，本文先采用Bai-Perron内生多重结构突变模型对时间序列进行突变点检验，然后对断点时间序列分别进行多元回归，并在剔除季节性和周期性后，通过平稳性检验、ARCH效应检验结果来确定相应的Garch模型，并用Garch模型来描述时间序列的波动性。
通过数学验证，我们认为期现回归性、利润波动性、库存波动性以及现金流变化这四个指标可以作为反映期货成熟度的检验指标，用该套方法对国内部分活跃品种检验后发现大连豆粕期货已经具备成熟品种的特征，本文认为豆粕期货市场是有效的；PTA、玉米淀粉期货的四个检验指标在近年来表现出时间序列优化的特点，但因时间较短尚不稳定，可以认为是接近成熟的品种；而螺纹钢和铝期货在多数指标上表现不佳，表明他们对社会资源配置能力较差，因此本文认为螺纹钢和铝期货市场是活跃但非有效的。通过进一步分析，本文认为品种的期现回归性差是制约其资源配置能力发挥的关键因素，而交易标的不明确、
仓单制作难度大、产业参与度低以及期货设计中的其他限制因素又是导致期现回归性差的重要原因。
本文开创性的从期货的基本功能——资源配置的角度出发，提出有效市场是指其期货价格能够对本行业社会资源起到合理的调配作用的市场。在内容安排上，本文首先总结了现有国际成熟期货品种的特点并找出能够反映期货对资源配置能力的四个指标假说，分别为期现回归性、利润波动性、库存波动性以及现金流变化，然后通过数学模型证明指标数据和品种成熟度的关联，最后应用该套指标对我国商品市场有效性进行检验。数学方法上，本文先采用Bai-Perron内生多重结构突变模型对时间序列进行突变点检验，然后对断点时间序列分别进行多元回归，并在剔除季节性和周期性后，通过平稳性检验、ARCH效应检验结果来确定相应的Garch模型，并用Garch模型来描述时间序列的波动性。
通过数学验证，我们认为期现回归性、利润波动性、库存波动性以及现金流变化这四个指标可以作为反映期货成熟度的检验指标，用该套方法对国内部分活跃品种检验后发现大连豆粕期货已经具备成熟品种的特征，本文认为豆粕期货市场是有效的；PTA、玉米淀粉期货的四个检验指标在近年来表现出时间序列优化的特点，但因时间较短尚不稳定，可以认为是接近成熟的品种；而螺纹钢和铝期货在多数指标上表现不佳，表明他们对社会资源配置能力较差，因此本文认为螺纹钢和铝期货市场是活跃但非有效的。通过进一步分析，本文认为品种的期现回归性差是制约其资源配置能力发挥的关键因素，而交易标的不明确、
仓单制作难度大、产业参与度低以及期货设计中的其他限制因素又是导致期现回归性差的重要原因。
ContributorsWang, Ping (Author) / Gu, Bin (Thesis advisor) / Li, Feng (Thesis advisor) / Yan, Hong (Committee member) / Arizona State University (Publisher)
Created2019
Description本文采用2010年1月1日至2017年12月31日在香港主板IPO上市的共574家公司作为研究样本，系统采集包括与发行人、承销商、投资人、发行热度、市场每日交易数据等相关的数据近100项，对超额配售选择权在香港IPO中的实际效用进行实证研究，研究发现：1）超额配售选择的确可以起到提高发行价格，降低IPO抑价率的作用，但是同时也是破发的主要原因。2）由超额配售选择权赋予承销商稳价行为中，市场买入量越大，最大回撤越大，市场下跌风险越大同时超额配售选择权还导致了最大回撤日的推后，增大了稳价结束后的市场风险，而这很有可能是由于承销商追求更高利益造成的。3）没有证据显示，超额配售选择权会降低承销商的佣金比例，但是，超额配售选择权却为承销商带来非常高的额外收益，而这个收益与市场下跌幅度和承销商从市场购买股份的比例直接相关。
其中，本文首次对最大回撤率、最大回撤日与承销商市场买入量之间的关系进行实证研究，揭示了承销商市场买入量与承销商收益正相关，与最大回撤率负相关，与最大回撤日正相关的关系，可能是增加市场下跌风险的因素。这与现有理论中及监管机构的预期中，“超额配售选择权具有向上稳定价格的作用”是有一定偏差的。
根据研究结果，本文首先建议发行人要客观对待超额配售选择权提升发行价格的作用，以免引起破发。其次建议市场投资人要客观认识超额配售选择权的作用，不要由于超额配售选择权的存在给与发行过高的认同价格。再次建议发行人要能够认识到超额配售选择权是承销商零成本获得的一个有固定收益保障的看空期权，是承销商在承销IPO时的收益之一，而股价下跌幅度与承销商的收益正相关。因此要对承销商的稳价行为进行一定管控，同时可以因为超额配售选择权的存在而要求更低的承销佣金比例。最后建议承销商要维护市场公平，爱护自己的声誉，尽可能避免因超额配售选择权的使用对市场造成不应有的干扰。
其中，本文首次对最大回撤率、最大回撤日与承销商市场买入量之间的关系进行实证研究，揭示了承销商市场买入量与承销商收益正相关，与最大回撤率负相关，与最大回撤日正相关的关系，可能是增加市场下跌风险的因素。这与现有理论中及监管机构的预期中，“超额配售选择权具有向上稳定价格的作用”是有一定偏差的。
根据研究结果，本文首先建议发行人要客观对待超额配售选择权提升发行价格的作用，以免引起破发。其次建议市场投资人要客观认识超额配售选择权的作用，不要由于超额配售选择权的存在给与发行过高的认同价格。再次建议发行人要能够认识到超额配售选择权是承销商零成本获得的一个有固定收益保障的看空期权，是承销商在承销IPO时的收益之一，而股价下跌幅度与承销商的收益正相关。因此要对承销商的稳价行为进行一定管控，同时可以因为超额配售选择权的存在而要求更低的承销佣金比例。最后建议承销商要维护市场公平，爱护自己的声誉，尽可能避免因超额配售选择权的使用对市场造成不应有的干扰。
ContributorsXie, Hui (Author) / Gu, Bin (Thesis advisor) / Yan, Hong (Thesis advisor) / Jiang, Zhan (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation presents the development of structural health monitoring and prognostic health management methodologies for complex structures and systems in the field of mechanical engineering. To overcome various challenges historically associated with complex structures and systems such as complicated sensing mechanisms, noisy information, and large-size datasets, a hybrid monitoring framework comprising of solid mechanics concepts and data mining technologies is developed. In such a framework, the solid mechanics simulations provide additional intuitions to data mining techniques reducing the dependence of accuracy on the training set, while the data mining approaches fuse and interpret information from the targeted system enabling the capability for real-time monitoring with efficient computation.
In the case of structural health monitoring, ultrasonic guided waves are utilized for damage identification and localization in complex composite structures. Signal processing and data mining techniques are integrated into the damage localization framework, and the converted wave modes, which are induced by the thickness variation due to the presence of delamination, are used as damage indicators. This framework has been validated through experiments and has shown sufficient accuracy in locating delamination in X-COR sandwich composites without the need of baseline information. Besides the localization of internal damage, the Gaussian process machine learning technique is integrated with finite element method as an online-offline prediction model to predict crack propagation with overloads under biaxial loading conditions; such a probabilistic prognosis model, with limited number of training examples, has shown increased accuracy over state-of-the-art techniques in predicting crack retardation behaviors induced by overloads. In the case of system level management, a monitoring framework built using a multivariate Gaussian model as basis is developed to evaluate the anomalous condition of commercial aircrafts. This method has been validated using commercial airline data and has shown high sensitivity to variations in aircraft dynamics and pilot operations. Moreover, this framework was also tested on simulated aircraft faults and its feasibility for real-time monitoring was demonstrated with sufficient computation efficiency.
This research is expected to serve as a practical addition to the existing literature while possessing the potential to be adopted in realistic engineering applications.
In the case of structural health monitoring, ultrasonic guided waves are utilized for damage identification and localization in complex composite structures. Signal processing and data mining techniques are integrated into the damage localization framework, and the converted wave modes, which are induced by the thickness variation due to the presence of delamination, are used as damage indicators. This framework has been validated through experiments and has shown sufficient accuracy in locating delamination in X-COR sandwich composites without the need of baseline information. Besides the localization of internal damage, the Gaussian process machine learning technique is integrated with finite element method as an online-offline prediction model to predict crack propagation with overloads under biaxial loading conditions; such a probabilistic prognosis model, with limited number of training examples, has shown increased accuracy over state-of-the-art techniques in predicting crack retardation behaviors induced by overloads. In the case of system level management, a monitoring framework built using a multivariate Gaussian model as basis is developed to evaluate the anomalous condition of commercial aircrafts. This method has been validated using commercial airline data and has shown high sensitivity to variations in aircraft dynamics and pilot operations. Moreover, this framework was also tested on simulated aircraft faults and its feasibility for real-time monitoring was demonstrated with sufficient computation efficiency.
This research is expected to serve as a practical addition to the existing literature while possessing the potential to be adopted in realistic engineering applications.
ContributorsLi, Guoyi (Ph.D.) (Author) / Chattopadhyay, Aditi (Thesis advisor) / Mignolet, Marc (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Yekani Fard, Masoud (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2019
Description中医药是中华文明的瑰宝，中药材是中医药文化和产业的核心。随着近年来国家相关政策出台，中药材产业的发展备受瞩目。由于中药材产业链条长，层级多，各层级间信息不对称，因而中药材市场普遍具有“假”、“乱”、“杂”的问题。
A公司的中药材全产业链服务商模式，通过对上游各主要专营商的整合，形成一定的平台综合集采能力，并开始得到下游医药厂家、药店认可，在市场逐步形成品牌号召力。本文实证研究A公司商业模式的转型对中药材市场价格的影响，进而分析中药材全产业链服务商模式在中药材行业健康发展中所发挥的积极作用。研究结果表明，上下游产销结合的中药材全产业链服务商模式，只有在形成一定收购规模，对市场价格产生一定影响的时候，才能充分释放药材质量的信号，润滑药材交易市场，提高收购价格，增加市场波动率，发挥价格发现作用。由于中药材市场的信息不对称程度较高，如果产销结合模式仍处于初级开创阶段，产销结合模式释放的药材质量信号则不足以全面改善信息不对称的状况。
A公司的中药材全产业链服务商模式，通过对上游各主要专营商的整合，形成一定的平台综合集采能力，并开始得到下游医药厂家、药店认可，在市场逐步形成品牌号召力。本文实证研究A公司商业模式的转型对中药材市场价格的影响，进而分析中药材全产业链服务商模式在中药材行业健康发展中所发挥的积极作用。研究结果表明，上下游产销结合的中药材全产业链服务商模式，只有在形成一定收购规模，对市场价格产生一定影响的时候，才能充分释放药材质量的信号，润滑药材交易市场，提高收购价格，增加市场波动率，发挥价格发现作用。由于中药材市场的信息不对称程度较高，如果产销结合模式仍处于初级开创阶段，产销结合模式释放的药材质量信号则不足以全面改善信息不对称的状况。
ContributorsYin, Xiaowei (Author) / Shen, Wei (Thesis advisor) / Yan, Hong (Thesis advisor) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2019
Description本论文研究的目的是针对银行卡跨境支付行为，根据不同的跨境支付渠道，结合资金清算的不同模式下的资金清算效率进行研究，并对现有清算系统内，运用理论和模型，对如何提高银行卡跨境资金清算进行阐述分析，力图在现有跨境资金清算金融设施的基础上，对银行卡跨境资金清算的流动性管理、头寸控制、增加清算周期等因素进行研究分析，进而尝试提出清算机制和流程的优化设计，以促进跨境资金提高周转效率，节约社会交易成本和持卡人资金成本。
论文将对相关银行卡跨境支付、清算基本流程、涉及的相关系统进行说明，并对全球和世界主要国家的银行卡市场进行介绍，结合我国银行卡跨境业务的现状、跨境支付清算涉及的主要环节、清算系统，通过不同层次、不同模型的分类比对，提出提高银行卡跨境支付资金清算的关键节点，并加以聚焦、深入测算、推导。研究的最终目的是期望通过对以上的分析，能够对银行卡资金清算参与主体对清算模式的选择、流动性节约、头寸管理等有所帮助，让清算主体能籍此对支付通道、清算模式、账户管理等选择上有所参考，促进卡组织（支付系统）籍此提高清算效率，从而降低整体交易和资金成本，提高支付行业整体资金资源的使用效率。
论文将对相关银行卡跨境支付、清算基本流程、涉及的相关系统进行说明，并对全球和世界主要国家的银行卡市场进行介绍，结合我国银行卡跨境业务的现状、跨境支付清算涉及的主要环节、清算系统，通过不同层次、不同模型的分类比对，提出提高银行卡跨境支付资金清算的关键节点，并加以聚焦、深入测算、推导。研究的最终目的是期望通过对以上的分析，能够对银行卡资金清算参与主体对清算模式的选择、流动性节约、头寸管理等有所帮助，让清算主体能籍此对支付通道、清算模式、账户管理等选择上有所参考，促进卡组织（支付系统）籍此提高清算效率，从而降低整体交易和资金成本，提高支付行业整体资金资源的使用效率。
ContributorsZhao, Jinxing (Author) / Gu, Bin (Thesis advisor) / Zhang, Anmin (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2019
Description随着中国经济过去30多年的高速发展，出现了一大批的高收入人群，他们更注重生活的品质，如追求自然、简约、低调的休闲生活方式，更看重健康生活、自身的身心修养，和提高自身修养的内涵式生活，以及注重子女的内涵气质教育。
同时，具有很强烈地获得心理认同的需求，参加各种以消费和交往为媒介和主体活动的社群或“社交圈子”，在心理和情感上自我获得与其在财富、生活方式以及生活品位等诸方面都类似的群体间的身份认同感和归属感；更看着与其社会阶层相匹配的身份地位、社交人脉、兴趣爱好等。
因此，从运营的角度来看，如何增加上述这些高净值人群对高净值社群的归属感，进而提高其对高净值社群的忠诚度，是高净值社群进一步可持续经营和发展的基石。本研究以上海嘉庭俱乐部为例，在对问卷调查的基础上，通过实证研究，探讨影响高净值社群归属感与忠诚度的关键因素，高净值社群中会员的归属感与忠诚度的关系，会员生活型态的差异使得归属感与忠诚度的影响关系呈现显著的不同。
实证研究表明，“时尚流行”会员较为理性，其更注重休闲风尚；而“优雅休闲与享受尊荣”的会员则偏感性，其相当注重心灵感受与宁静舒适的感觉，强调全家共享以及纯封闭式的会员享受，能够更多地认识到与个人品味和品位相同的人，如对生活品质的追求、价值观、子女教育等；内心更开放、所接受教育程度更高的家庭，在嘉庭会感受到的归属感意识更高、其忠诚度也更高。
同时，具有很强烈地获得心理认同的需求，参加各种以消费和交往为媒介和主体活动的社群或“社交圈子”，在心理和情感上自我获得与其在财富、生活方式以及生活品位等诸方面都类似的群体间的身份认同感和归属感；更看着与其社会阶层相匹配的身份地位、社交人脉、兴趣爱好等。
因此，从运营的角度来看，如何增加上述这些高净值人群对高净值社群的归属感，进而提高其对高净值社群的忠诚度，是高净值社群进一步可持续经营和发展的基石。本研究以上海嘉庭俱乐部为例，在对问卷调查的基础上，通过实证研究，探讨影响高净值社群归属感与忠诚度的关键因素，高净值社群中会员的归属感与忠诚度的关系，会员生活型态的差异使得归属感与忠诚度的影响关系呈现显著的不同。
实证研究表明，“时尚流行”会员较为理性，其更注重休闲风尚；而“优雅休闲与享受尊荣”的会员则偏感性，其相当注重心灵感受与宁静舒适的感觉，强调全家共享以及纯封闭式的会员享受，能够更多地认识到与个人品味和品位相同的人，如对生活品质的追求、价值观、子女教育等；内心更开放、所接受教育程度更高的家庭，在嘉庭会感受到的归属感意识更高、其忠诚度也更高。
ContributorsLi, Hailin (Author) / Gu, Bin (Thesis advisor) / Chen, Xinlei (Thesis advisor) / Chang, Chun (Committee member) / Arizona State University (Publisher)
Created2019
Description
This investigation focuses on the development of uncertainty modeling methods applicable to both the structural and thermal models of heated structures as part of an effort to enable the design under uncertainty of hypersonic vehicles. The maximum entropy-based nonparametric stochastic modeling approach is used within the context of coupled structural-thermal Reduced Order Models (ROMs). Not only does this strategy allow for a computationally efficient generation of samples of the structural and thermal responses but the maximum entropy approach allows to introduce both aleatoric and some epistemic uncertainty into the system.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
ContributorsSong, Pengchao (Author) / Mignolet, Marc P (Thesis advisor) / Smarslok, Benjamin (Committee member) / Chattopadhyay, Aditi (Committee member) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2019
Description
A new type of electronics was envisioned, namely edible electronics. Edible electronics are made by Food and Drug Administration (FDA) certified edible materials which can be eaten and digested by human body. Different from implantable electronics, test or treatment using edible electronics doesn’t require operations and perioperative complications.
This dissertation bridges the food industry, material sciences, device fabrication, and biomedical engineering by demonstrating edible supercapacitors and electronic components and devices such as pH sensor.
Edible supercapacitors were fabricated using food materials from grocery store. 5 of them were connected in series to power a snake camera. Tests result showed that the current generated by supercapacitor have the ability to kill bacteria. Next more food, processed food and non-toxic level electronic materials were investigated. A “preferred food kit” was created for component fabrication based on the investigation. Some edible electronic components, such as wires, resistor, inductor, etc., were developed and characterized utilizing the preferred food kit. These components make it possible to fabricate edible electronic/device in the future work. Some edible electronic components were integrated into an edible electronic system/device. Then edible pH sensor was introduced and fabricated. This edible pH sensor can be swallowed and test pH of gastric fluid. PH can be read in a phone within seconds after the pH sensor was swallowed. As a side project, an edible double network gel electrolyte was synthesized for the edible supercapacitor.
This dissertation bridges the food industry, material sciences, device fabrication, and biomedical engineering by demonstrating edible supercapacitors and electronic components and devices such as pH sensor.
Edible supercapacitors were fabricated using food materials from grocery store. 5 of them were connected in series to power a snake camera. Tests result showed that the current generated by supercapacitor have the ability to kill bacteria. Next more food, processed food and non-toxic level electronic materials were investigated. A “preferred food kit” was created for component fabrication based on the investigation. Some edible electronic components, such as wires, resistor, inductor, etc., were developed and characterized utilizing the preferred food kit. These components make it possible to fabricate edible electronic/device in the future work. Some edible electronic components were integrated into an edible electronic system/device. Then edible pH sensor was introduced and fabricated. This edible pH sensor can be swallowed and test pH of gastric fluid. PH can be read in a phone within seconds after the pH sensor was swallowed. As a side project, an edible double network gel electrolyte was synthesized for the edible supercapacitor.
ContributorsXu, Wenwen (Author) / Jiang, Hanqing (Thesis advisor) / Dai, Lenore (Committee member) / Green, Matthew (Committee member) / Mu, Bin (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2019
Description
In this study I investigate the factors that may influence consumer preference and choice in China’s home interior decoration industry. With the fast development of information technology such as the internet in China, it becomes increasingly important to have a more precise understanding of consumer preference and choice in home interior decoration decisions so that companies in this industry can provide better services to meet customer needs. Using survey data from a sample of potential customers and a sample of existing customers of a large home interior decoration company, I find that (1) internet has become the mostly used channel by consumers to gather information about home interior decoration, (2) design style is the most influential factor in consumers’ choice of home interior decoration company, and (3) consumers are more likely to choose home interior decoration companies to provide full services when they are between 35 to 45 years old or above 55 years old, when it is the first time for them to purchase a real estate property, and when they are located in the Eastern region of China. Findings of this study can help home interior decoration companies better understand customer needs and preferences, facilitate changes in their marketing and sales strategies, and consequently strengthen their competitive advantage．
ContributorsYang, Jin (Author) / Shen, Wei (Thesis advisor) / Zhang, Anmin (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2015