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- All Subjects: fraudulent detection
- Creators: Cao, Jianwei
- Creators: Chen, Pei-Yu
- Creators: Liang, Bing
Description
Due to the growing popularity of the Internet and smart mobile devices, massive data has been produced every day, particularly, more and more users’ online behavior and activities have been digitalized. Making a better usage of the massive data and a better understanding of the user behavior become at the very heart of industrial firms as well as the academia. However, due to the large size and unstructured format of user behavioral data, as well as the heterogeneous nature of individuals, it leveled up the difficulty to identify the SPECIFIC behavior that researchers are looking at, HOW to distinguish, and WHAT is resulting from the behavior. The difference in user behavior comes from different causes; in my dissertation, I am studying three circumstances of behavior that potentially bring in turbulent or detrimental effects, from precursory culture to preparatory strategy and delusory fraudulence. Meanwhile, I have access to the versatile toolkit of analysis: econometrics, quasi-experiment, together with machine learning techniques such as text mining, sentiment analysis, and predictive analytics etc. This study creatively leverages the power of the combined methodologies, and apply it beyond individual level data and network data. This dissertation makes a first step to discover user behavior in the newly boosting contexts. My study conceptualize theoretically and test empirically the effect of cultural values on rating and I find that an individualist cultural background are more likely to lead to deviation and more expression in review behaviors. I also find evidence of strategic behavior that users tend to leverage the reporting to increase the likelihood to maximize the benefits. Moreover, it proposes the features that moderate the preparation behavior. Finally, it introduces a unified and scalable framework for delusory behavior detection that meets the current needs to fully utilize multiple data sources.
ContributorsLi, Chunxiao (Author) / Gu, Bin (Thesis advisor) / Chen, Pei-Yu (Committee member) / Xiong, Hui (Committee member) / Arizona State University (Publisher)
Created2019
Description当前，民营企业已成为中国重要支撑力量，而未来5到10年，约有300多万家民营企业面临传承困境。但学术研究领域在传承整体框架、配套机制建设方面有完整论述、有成功案例的所见不多。首先，针对以上民营企业的传承现状，本文将研究、回答五个问题：1、成功传承的标准和要素是什么？2、传承模式有哪几种，每种模式配套的传承机制是什么，该如何建立？3、民营企业应选择何种传承模式，如何选择？4、民营企业的整套传承方案如何落地搭建？5、是否有普适性的、可借鉴的民营企业传承模型，包含哪些要素？
其次，本文主要使用文献研究、案例研究、实证分析，选取中、美、德、日四家不同传承阶段、不同传承模式的知名民营企业，对其传承情况进行深入研究。在此基础上，归纳总结出传承的关键要素，对前述五个问题进行系统解答。同时，本文创新性地结合理论研究、案例研究及企业实践，提出适合我国大部分民营企业的传承全周期管理框架。
最后，根据以上研究，本文总结出关于中国民营企业传承的八大结论及建议：1、本质：权力的交接和义务的传递；2、两大风险：继任风险（继任人的能力要求）、代理风险（继任人对企业核心理念的意愿/忠诚度）；3、降低风险的四大机制：领袖锻造、人才梯队、管控治理、激励机制；4、两大成功要素：“选领袖”和“建机制”；5、四大机制是并行推进、相辅相成的，要尽早构建、持续优化；6、三大模式：家族成员继承、内生培养经理人、外聘职业经理人；7、民营企业传承模型包含七大要素、五大步骤；8、民营企业在制定传承方案时，除了要注意传承模型中的要素，还要注意其他关键要素。
其次，本文主要使用文献研究、案例研究、实证分析，选取中、美、德、日四家不同传承阶段、不同传承模式的知名民营企业，对其传承情况进行深入研究。在此基础上，归纳总结出传承的关键要素，对前述五个问题进行系统解答。同时，本文创新性地结合理论研究、案例研究及企业实践，提出适合我国大部分民营企业的传承全周期管理框架。
最后，根据以上研究，本文总结出关于中国民营企业传承的八大结论及建议：1、本质：权力的交接和义务的传递；2、两大风险：继任风险（继任人的能力要求）、代理风险（继任人对企业核心理念的意愿/忠诚度）；3、降低风险的四大机制：领袖锻造、人才梯队、管控治理、激励机制；4、两大成功要素：“选领袖”和“建机制”；5、四大机制是并行推进、相辅相成的，要尽早构建、持续优化；6、三大模式：家族成员继承、内生培养经理人、外聘职业经理人；7、民营企业传承模型包含七大要素、五大步骤；8、民营企业在制定传承方案时，除了要注意传承模型中的要素，还要注意其他关键要素。
ContributorsCao, Jianwei (Author) / Huang, Xiaochuan (Thesis advisor) / Liang, Bing (Thesis advisor) / Cheng, Shijun (Committee member) / Arizona State University (Publisher)
Created2020