Matching Items (6)
Filtering by
- All Subjects: Social Media
- Member of: Theses and Dissertations
Description
Social media offers a powerful platform for the independent digital content producer community to develop, disperse, and maintain their brands. In terms of information systems research, the broad majority of the work has not examined hedonic consumption on Social Media Sites (SMS). The focus has mostly been on the organizational perspectives and utilitarian gains from these services. Unlike through traditional commerce channels, including e-commerce retailers, consumption enhancing hedonic utility is experienced differently in the context of a social media site; consequently, the dynamic of the decision-making process shifts when it is made in a social context. Previous research assumed a limited influence of a small, immediate group of peers. But the rules change when the network of peers expands exponentially. The assertion is that, while there are individual differences in the level of susceptibility to influence coming from others, these are not the most important pieces of the analysis--unlike research centered completely on influence. Rather, the context of the consumption can play an important role in the way social influence factors affect consumer behavior on Social Media Sites. Over the course of three studies, this dissertation will examine factors that influence consumer decision-making and the brand personalities created and interpreted in these SMS. Study one examines the role of different types of peer influence on consumer decision-making on Facebook. Study two observes the impact of different types of producer message posts with the different types of influence on decision-making on Twitter. Study three will conclude this work with an exploratory empirical investigation of actual twitter postings of a set of musicians. These studies contribute to the body of IS literature by evaluating the specific behavioral changes related to consumption in the context of digital social media: (a) the power of social influencers in contrast to personal preferences on SMS, (b) the effect on consumers of producer message types and content on SMS at both the profile level and the individual message level.
ContributorsSopha, Matthew (Author) / Santanam, Raghu T (Thesis advisor) / Goul, Kenneth M (Committee member) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2013
Description
When preparing for and responding to disasters, humanitarian organizations must run effective and efficient supply chains to deliver the resources needed by the affected population. The management of humanitarian supply chains include coordinating the flows of goods, finances, and information. This dissertation examines how humanitarian organizations can improve the distribution of information, which is critical for the planning and coordination of the other two flows. Specifically, I study the diffusion of information on social media platforms since such platforms have emerged as useful communication tools for humanitarian organizations during times of crisis.
In the first chapter, I identify several factors that affect how quickly information spreads on social media platforms. I utilized Twitter data from Hurricane Sandy, and the results indicate that the timing of information release and the influence of the content’s author determine information diffusion speed. The second chapter of this dissertation builds directly on the first study by also evaluating the rate at which social media content diffuses. A piece of content does not diffuse in isolation but, rather, coexists with other content on the same social media platform. After analyzing Twitter data from four distinct crises, the results indicate that other content’s diffusion often dampens a specific post’s diffusion speed. This is important for humanitarian organizations to recognize and carries implications for how they can coordinate with other organizations to avoid inhibiting the propagation of each other’s social media content. Finally, a user’s followers on social media platforms represent the user’s direct audience. The larger the user’s follower base, the more easily the same user can extensively broadcast information. Therefore, I study what drives the growth of humanitarian organizations’ follower bases during times of normalcy and emergency using Twitter data from one week before and one week after the 2016 Ecuador earthquake.
In the first chapter, I identify several factors that affect how quickly information spreads on social media platforms. I utilized Twitter data from Hurricane Sandy, and the results indicate that the timing of information release and the influence of the content’s author determine information diffusion speed. The second chapter of this dissertation builds directly on the first study by also evaluating the rate at which social media content diffuses. A piece of content does not diffuse in isolation but, rather, coexists with other content on the same social media platform. After analyzing Twitter data from four distinct crises, the results indicate that other content’s diffusion often dampens a specific post’s diffusion speed. This is important for humanitarian organizations to recognize and carries implications for how they can coordinate with other organizations to avoid inhibiting the propagation of each other’s social media content. Finally, a user’s followers on social media platforms represent the user’s direct audience. The larger the user’s follower base, the more easily the same user can extensively broadcast information. Therefore, I study what drives the growth of humanitarian organizations’ follower bases during times of normalcy and emergency using Twitter data from one week before and one week after the 2016 Ecuador earthquake.
ContributorsYoo, Eunae (Author) / Rabinovich, Elliot (Thesis advisor) / Gu, Bin (Thesis advisor) / Rand, William (Committee member) / Fowler, John (Committee member) / Arizona State University (Publisher)
Created2018
Description
By collecting and analyzing more than two million tweets, U.S. House Representatives’ voting records in 111th and 113th Congress, and data from other resources I study several aspects of adoption and use of Twitter by Representatives. In the first chapter, I study the overall impact of Twitter use by Representatives on their political orientation and their political alignment with their constituents. The findings show that Representatives who adopted Twitter moved closer to their constituents in terms of political orientation.
By using supervised machine learning and text mining techniques, I shift the focus to synthesizing the actual content shared by Representatives on Twitter to evaluate their effects on Representatives’ political polarization in the second chapter. I found support for the effects of repeated expressions and peer influence in Representatives’ political polarization.
Last but not least, by employing a recently developed dynamic network model (separable temporal exponential-family random graph model), I study the effects of homophily on formation and dissolution of Representatives’ Twitter communications in the third chapter. The results signal the presence of demographic homophily and value homophily in Representatives’ Twitter communications networks.
These three studies altogether provide a comprehensive picture about the overall consequences and dynamics of use of online social networking platforms by Representatives.
By using supervised machine learning and text mining techniques, I shift the focus to synthesizing the actual content shared by Representatives on Twitter to evaluate their effects on Representatives’ political polarization in the second chapter. I found support for the effects of repeated expressions and peer influence in Representatives’ political polarization.
Last but not least, by employing a recently developed dynamic network model (separable temporal exponential-family random graph model), I study the effects of homophily on formation and dissolution of Representatives’ Twitter communications in the third chapter. The results signal the presence of demographic homophily and value homophily in Representatives’ Twitter communications networks.
These three studies altogether provide a comprehensive picture about the overall consequences and dynamics of use of online social networking platforms by Representatives.
ContributorsMosuavi, Seyedreza (Author) / Gu, Bin (Thesis advisor) / Vinzé, Ajay S. (Committee member) / Shi, Zhan (Michael) (Committee member) / Arizona State University (Publisher)
Created2016
Description区块链技术应用（DApp）最早出现在数字货币交易上，也有部分DApp涉及游戏、音乐、教育、出行等场景，但是由于前几年DApp还属于新生事物，多数社会大众对其了解程度不高，加之多数DApp开发和优化的水平有限，用户体验较差，因此并没有良好的市场表现。
尽管如此， 2017年11月一款叫CryptoKitties的区块链游戏正式上线，并且在短时间之内引爆了整个区块链，游戏交易量在1个月内暴涨至1.7万。随后风险资本不断进入区块链行业，并且催生出一大批区块链DApp出来，涉及的应用场景进一步拓展到游戏、赌博、社交、金融、市场、保险、健康等领域。如何设计一套有效的治理机制，从而实现用户留存高、项目前景好，成为多数区块链DApp最为关注的问题。
本文选择CryptoKitties、Mycryptohero、Steemit和NeoWorld这四款区块链DApp作为案例研究对象，通过归纳总结发现这四款DApp都将游戏性、通证经济、社群生态和网络效应作为共同的治理方式。基于这四方面，本文对四款DApp的异同进行了跨案例比较，发现NeoWorld要比其他三款DApp在治理手段上更加丰富和合理。最后，利用136份NeoWorld玩家调查问卷数据，对游戏性、通证经济、社群生态和网络效应对其治理绩效的影响进行了实证检验，结果发现除了社群生态之外，其他三个因素都能提升NeoWorld的治理绩效。
本研究的最大创新是选择在区块链场景应用中具有代表性的4个DApp项目作为案例研究对象，通过归纳总结发现各自在治理手段上的共同之处（影响因素），并根据问卷调查数据对不同影响因素对特定Dapp治理绩效的影响程度进行实证检验，丰富了平台治理相关研究成果，也为社会各界深化认识DApp治理方式和成效，推动DApp行业生态健康有序发展提供参考和借鉴。
关键词：通证经济；社群生态；网络效应；跨案例研究；回归分析
尽管如此， 2017年11月一款叫CryptoKitties的区块链游戏正式上线，并且在短时间之内引爆了整个区块链，游戏交易量在1个月内暴涨至1.7万。随后风险资本不断进入区块链行业，并且催生出一大批区块链DApp出来，涉及的应用场景进一步拓展到游戏、赌博、社交、金融、市场、保险、健康等领域。如何设计一套有效的治理机制，从而实现用户留存高、项目前景好，成为多数区块链DApp最为关注的问题。
本文选择CryptoKitties、Mycryptohero、Steemit和NeoWorld这四款区块链DApp作为案例研究对象，通过归纳总结发现这四款DApp都将游戏性、通证经济、社群生态和网络效应作为共同的治理方式。基于这四方面，本文对四款DApp的异同进行了跨案例比较，发现NeoWorld要比其他三款DApp在治理手段上更加丰富和合理。最后，利用136份NeoWorld玩家调查问卷数据，对游戏性、通证经济、社群生态和网络效应对其治理绩效的影响进行了实证检验，结果发现除了社群生态之外，其他三个因素都能提升NeoWorld的治理绩效。
本研究的最大创新是选择在区块链场景应用中具有代表性的4个DApp项目作为案例研究对象，通过归纳总结发现各自在治理手段上的共同之处（影响因素），并根据问卷调查数据对不同影响因素对特定Dapp治理绩效的影响程度进行实证检验，丰富了平台治理相关研究成果，也为社会各界深化认识DApp治理方式和成效，推动DApp行业生态健康有序发展提供参考和借鉴。
关键词：通证经济；社群生态；网络效应；跨案例研究；回归分析
ContributorsHe, Xin (Author) / Shao, Benjamin (Thesis advisor) / Hu, Jie (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2020
Description随着计算机技术、互联网和云计算的高速发展，互联网＋、大数据、平台战略、长尾理论、生态圈、区块链等正在颠覆传统商业模式的运作逻辑，网络化、移动化、平台化趋势逐渐清晰。本文聚焦“互联网+”与会展平台相互融合背景下创新性数字化现代会展平台商业模式，以国内智慧会展行业领头企业——欧马腾为例，深入剖析“互联网+”赋予会展平台新的价值和成长空间，并以数据赋能为切入点，从基于大数据技术的项目监理实践、基于人工智能技术的智能营销、基于大数据的绿色生态平台建设为典型场景，系统阐述互联网会展平台成长和价值背后的重要推动作用。
研究结果发现：第一，互联网技术是欧马腾商业模式创新的重要技术保障，并为其提供了社群营销思维、大数据思维和去中心化理念，推动了欧马腾商业模式变革；第二，大数据技术是欧马腾盈利快速增长的有利支撑。这主要在于欧马腾采用大数据技术对客户售前、售中、售后进行动态跟踪，通过技术手段不断完善客户服务体系和风险控制体系，提升客户的服务体验，促使欧马腾的市场认可度逐渐上升，成为国内展览行业翘楚，品牌优势不断凸显；第三，大数据赋能欧马腾风险控制，近年来欧马腾成功的审图监理项目风险事件率为0背后的核心要素为大数据技术在审图监理项目中的应用，这充分体现了欧马腾数据赋能风险控制的成功典范；第四，人工智能赋能会展行业营销模式创新变革，欧马腾以“人工智能+”新会展生态圈为切入点，构建了智慧营销，助力其营销模式变革和商业模式转型；第五，绿色会展平台助力欧马腾价值发现创造，欧马腾的绿色平台建设能够增强现有客户再次使用的意愿，即提升欧马腾的客户黏性，从而发现和创造企业价值。
本文的研究对我国会展相关企业转型、资源整合、快速发展、可持续发展等具有重要的理论参考价值和实践借鉴。
关键词： 价值创造；数据赋能；互联网会展平台；绿色会展
研究结果发现：第一，互联网技术是欧马腾商业模式创新的重要技术保障，并为其提供了社群营销思维、大数据思维和去中心化理念，推动了欧马腾商业模式变革；第二，大数据技术是欧马腾盈利快速增长的有利支撑。这主要在于欧马腾采用大数据技术对客户售前、售中、售后进行动态跟踪，通过技术手段不断完善客户服务体系和风险控制体系，提升客户的服务体验，促使欧马腾的市场认可度逐渐上升，成为国内展览行业翘楚，品牌优势不断凸显；第三，大数据赋能欧马腾风险控制，近年来欧马腾成功的审图监理项目风险事件率为0背后的核心要素为大数据技术在审图监理项目中的应用，这充分体现了欧马腾数据赋能风险控制的成功典范；第四，人工智能赋能会展行业营销模式创新变革，欧马腾以“人工智能+”新会展生态圈为切入点，构建了智慧营销，助力其营销模式变革和商业模式转型；第五，绿色会展平台助力欧马腾价值发现创造，欧马腾的绿色平台建设能够增强现有客户再次使用的意愿，即提升欧马腾的客户黏性，从而发现和创造企业价值。
本文的研究对我国会展相关企业转型、资源整合、快速发展、可持续发展等具有重要的理论参考价值和实践借鉴。
关键词： 价值创造；数据赋能；互联网会展平台；绿色会展
ContributorsWang, Xiang (Author) / Gu, Bin (Thesis advisor) / Hu, Jie (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2020
Description随着科创板、注册制出台，企业间的竞争逐步从资源型竞争转向科技和技术的竞争，大量有知识、有文化、有理想、有技术的人才涌入社会，给科技发展、技术创新在政策、市场和人才层面提供了支撑、机遇和源动力，科技型创新企业大量涌现，形成趋势性上升行业。科技型创业企业多冠以“规模小、技术密集、高成长、高风险”的标签，在融资过程中困难重重，这些特点与风险投资（VC）“高风险、高回报”的特质不谋而合，VC机构还能给被投企业提供人才、信息、商业模式、政策法律咨询等增值服务，助力企业发展。引入VC走上市路径成为诸多科技型创业企业最优选择。
近些年VC行业在我国得到迅猛发展，IVC和CVC已成了助推我国科技型创业企业发展的主力军。由于IVC和CVC的组织架构、投资期限、资金来源、投资目标、投资经验、管理层薪资结构等方面存在着很大的不同。不同的投资模式势必会对被投企业的经营活动产生不同影响，本文基于总资产单位产出和投入为经济学逻辑，针对相关变量提出假设。
本文对我国中小板和创业板2013年以前上市的七个高新技术行业（5G通信、大数据、人工智能、软件服务、生物制药、新材料、医疗器械）共123家，以上市为起点的6年企业数据为基础。以IVC和CVC为自变量，以上市司龄、企业规模、行业控制、分红占净利润比为控制变量，以V/A、E/A、K/A和E/R为因变量，对IVC和CVC投入的科技型创业企业分别进行描述性统计、相关性分析和回归分析，验证IVC和CVC对被投企业的市场维度（V/A）、财务维度（E/A、E/R）、创新维度（K/A）的影响。试图从企业的角度出发，理清企业与VC的关系，为二级市场投资者提供一个投资决策视角。
ContributorsZhang, Mingpeng (Author) / Shen, Wei (Thesis advisor) / Jiang, Zhan (Thesis advisor) / Hu, Jie (Committee member) / Arizona State University (Publisher)
Created2021