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企业信息技术接受的影响因素模型与实证研究:以智慧消防技术为例

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消防工作是城市发展的基础保障。随着全国经济社会发展,高层建筑、大型商场等人员密集场所不断增多,消防安全监管的覆盖面越来越广、压力越来越大。高层建筑密集、消防基础设施不到位,火灾隐患多,单纯依靠人工巡检和传统方式监管,难以满足安全需求。

智慧消防将依托物联网、云计算、大数据、移动网等信息技术,与传统消防业务加大融合力度,构建一个立体式、覆盖全社会的火灾防控体系,这对于加大、加强消防部门的监督、管理手段和力度,提高各单位火灾预防能力,最大限度地保障社会和人民群众生命财产的安全具有十分重要和现实的意义。总体上来看,多数企业用户对于智慧消防的理解和参与程度不尽相同,导致目前关于智慧消防的认识还未统一,在具体执行层面相互之间也还没有达成共识,智慧消防在全社会的应用范围还处于初级和探索环节。

本文在相关文献综述的基础上,分别基于技术-组织-环境(TOE)框架和说服模型,通过回归分析对影响智慧消防技术接受意愿和购买行为的因素进行了理论分析和实证检验。相关结论可以为政府相关部门、社会企业等主体的日常决策提供参考和借鉴。

本文的研究结论主要有以下几点:(1)TOE框架对于分析企业是否采用智慧消防技术进而实现消防安全工作信息化、智能化升级具有一定的解释力,该框架下技术、组织和环境三个层面共计6个影响因素会对企业智慧消防技术的采用产生显著的正向作用,分别是技术维度的有用性、易用性、兼容性,组织维度的配套资源和风险偏好,以及环境维度的模仿压力。(2)技术的先进性、高管态度、政府压力没有通过显著性检验。(3)基于说服模型,本研究探索了影响企业购买智慧消防技术的考虑要素,企业的曝光率、知名度,营销团队的素养和专业话能力作为说服者特征,显著影响购买行为;企业接受智慧消防技术,自身经营状况作为说服对象特征,影响其的购买意愿;说服过程中提高技术的实用性证明有明显的促进购买效果。(4)本研究发现智慧消防企业规模并不足以显著影响购买行为,说服情境特征如说服场景和时间点也没有明显的作用。

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  • 2020

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农村银行业金融机构资产规模对盈利能力的影响研究

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近几年,随着国家对“三农”问题的不断重视,相关部门先后下发了金融业支持新农村建设的相关政策,推动了以农信社、村镇银行、农村合作银行等为代表的农村银行业金融机构的发展,各地区农村银行业金融机构迎来了快速发展的时期。但是迅速发展过程中发现部分地区农村银行业金融机构盈利水平并没有出现等比例的增长甚至是下降。

本文从资产规模的角度,对农村银行业金融机构的盈利能力是否存在一个最适资产规模进行分析和检验。结合既有文献的研究成果以及笔者多年从事县域农村银行业金融机构股权投资的相关检验,本文梳理出资产规模、治理结构(国企持股比例、员工持股比例)、业务管理(存贷比、成本收入比、贷款集中度、个人贷款占比、个人存款占比)和环境因素(地区经济、居民储蓄、区域人口)等会对县域农村银行业金融机构盈利能力产生影响的内外部因素,构建了农村银行业金融机构资产规模与盈利能力之间的实证模型,并基于46家县域农村银行业金融机构2013-2017年面板数据,利用非线性固定效应回归模型检验了农村银行业金融机构最优规模。

研究发现,(1)样本农村银行业金融机构的最优规模在64亿元左右,有16家处于最优规模以下。(2)居民储蓄水平的提升有助于农村银行业金融机构提高盈利能力,但同等规模条件下,居民储蓄低地区的农村银行业金融机构盈利能力更强。(3)以成本收入比为表征的农村银行业金融机构业务管理水平限制了其盈利能力提升。

关键词:农村银行业金融机构;盈利能力;资产规模;影响因素; 非线性固定效应回归模型

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  • 2020

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我国建筑行业上市公司IPO业绩效应研究

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中国建筑行业经历百年发展,在一定程度上已趋于稳定并缓慢增长阶段,其中多数建筑企业已形成了自己的经营业务圈,经营能力与竞争格局稳固。2015年,我国建筑业开始出现产能过剩,整个建筑行业景气程度开始呈现下行趋势。在此背景下,传统建筑企业需要调整发展战略、谋求转型升级、提高核心竞争力并试图寻找新的盈利增长点以应对市场下行和产业过剩带来的不利影响。其中,一些建筑企业试图通过资本市场上市等途径推动产业升级和转型发展。但是,结合现有理论文献与实践经验,公司上市后易出现“业绩变脸”现象,主要来源于公司选择市场走高和本身业绩最优时择时上市、为满足上市条件或获取更高估值在上市前会计操纵、管理层与股东代理冲突导致管理层机会主义增加、内部治理效率低下等方面,这种“业绩变脸”现象不仅不利于企业自身发展与投资者利益保护,同时不利于资本市场的资源有效配置。

本文基于我国建筑行业发展现状与上市公司“业绩变脸”的相关研究文献,立足于我国建筑行业企业公司IPO业绩效应,探究其发生的原因与经济后果。本文使用文献回顾、理论分析、现状研究、实证研究与案例分析相结合的方法,选取截至目前A股建筑业上市公司全样本,采用实证研究方法检验这些公司在IPO前后的经营业绩指标变化,即检验IPO业绩效应的存在性。在此基础上,本文结合宏观经济运行、资本市场情绪、公司盈余管理、公司产权性质等层面因素,探究建筑行业上市公司IPO业绩效应的来源和主导因素,并对IPO后不同年度区间内的业绩变化进行统计分析,最终证实宏观经济增长、社会固定资产投资增速、资本市场估值与流动性、公司上市前的盈余管理、产权性质对IPO业绩效应均有显著影响。最后,本文以龙元建设为例,通过结构化和非结构化实地访谈等方式进行案例研究,进而探究IPO对建筑行业上市公司业绩影响的具体路径与机制。

本文的研究将对IPO业绩变脸相关文献进行了一定程度的补充,在实践中,本文结论将对建筑行业企业IPO时应怎样应对宏观经济与资本市场变化、怎样利用金融中介、怎样提升公司的股东与管理层在IPO过程中的主动性提出建议,为建筑企业实现上市转型提出引导性意见。

关键词:建筑业,IPO业绩效应,盈余操纵,经济后果

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  • 2020

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中国多元化公司整体或分拆上市的适用性研究

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多元化公司整体上市和分拆上市的理论与实践在国际市场已经较为成熟,而对于中国A股来说,分拆上市一直受制于政策;2019年以来,随着科创板的开启及A股将迎来的改革,多元化公司分拆上市也将迎来重要机遇。

多年来,学术界对于多元化公司在资本市场方面的研究主要聚焦于估值比较、相关影响因素以及整体上市和者分拆上市的法律、财务、风险等方面。而本文在已有理论基础上,从股权集中度、新兴行业、跨市场上市(A+H)三个方面研究中国多元化公司的整体或者分拆上市的行为选择,研究发现:大股东持股比例更高的公司更倾向于整体上市,新兴行业或者创新性的子公司更可能被分拆上市,跨多个股票市场上市的公司更倾向分拆上市子公司,这与委托代理理论和信息不对称理论的预测一致。

为了让研究更加全面并具实用性,本文加入了对中国平安集团和温氏集团的案例分析,还针对中介投行和研究人员的特定人群进行分析式调研,结果均较好支持了研究结论,使得本文的研究兼具理论创新和实际指导价值。

关键词: 中国多元化公司,整体上市,分拆上市,股权集中度,新兴行业,跨市场上市

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  • 2020

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从上市公司股权质押行为分析企业的潜在风险和公司治理

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我国上市公司股东采取股权质押贷款方式融资非常普遍,股权质押贷款总余额已经高达5.70万亿元,这些贷款背后隐藏着巨大的风险。上市公司大股东采用股权质押贷款的动机可能是对未来乐观行业预期的资金需求,或者是由于股权转让的限制而采取的变相套现转移风险。后者的动机里本身就包含着上市公司大股东对自身股价已经估值过高的判断。本文通过分析上市公司股权质押贷款风险 (即,上市公司当年股价估值程度与上市公司下一年股价崩盘风险之间的关系)会因为股权质押动机的不同而存在差异。只有在套现动机下,当年股价估值程度才会导致下一年显著的股价崩盘风险,而在融资动机下当年股价估值程度与下一年股价崩盘风险之间的关系则呈现负相关。鉴于目前大多数上市公司并不会披露大股东质押所得资金的具体去向,本文通过融资约束程度这个维度对上市公司大股东股权质押的动机进行识别。当上市公司所受融资约束较低时,当年股价高估程度程度越大,下一年股价崩盘风险越大(正相关),上市公司进行股权质押的动机更倾向于高位套现。在融资约束程度高的情况下,上市公司股权质押更倾向于融资,当年股价估值程度越大,下一年上市公司股价崩盘风险越小(负相关)。 在大股东控制权高的情况下,对于所受融资约束程度低的上市公司,独立董事不论是比例高或者低,独立董事制度对大股东的股票质押的行为 (套现动机)无影响。 对于所受融资约束程度高的上市公司,独立董事在占比高时,对通过股票质押来融资的行为有强化作用,可以表现出其治理影响力,在独董占比低的情况下则无法产生作用。

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  • 2020

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Research on critical indicators of Shanghai international financial center construction

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The city of Shanghai is set to become an international financial center (IFC) by 2020. To achieve this goal, it is imperative to clearly define the key characteristics of an

The city of Shanghai is set to become an international financial center (IFC) by 2020. To achieve this goal, it is imperative to clearly define the key characteristics of an IFC. In this study I draw from recent research on the ranking of IFCs to develop an index of these key characteristics that can be used to assess a city’s standings as an IFC. Based on a review of prior research, I first put together a comprehensive list of the indicators that have been used to evaluate IFCs, which includes six first-level indicators and 34 second-level indicators. I then collect information on all these indicators from public sources for the following eight cities each year from 2011 to 2013: London, New York, Paris, Hong Kong, Tokyo, Singapore, Beijing and Shanghai. Next, I conduct a principal component analysis (PCA) on my data, and obtain four primary factors that contain most information of the original 34 indicators. The first factor covers 18 of the original indicators and reflects a city’s level of development in general business environment. The second factor covers 10 of the original indicators and reflects a city’s level of development in financial markets. The third factor covers three of the original indicators and reflects a city’s level of economic vitality. The fourth factor covers three of the original indicators and reflects a city’s level of the costs of living. I further calculate the composite scores for the above eight cities along these four factors, and find that these eight cities can be classified into three tiers on the basis of their scores. The first tier consists of New York and London; the second tier consists of Singapore, Hong Kong, Paris and Tokyo; and the third tier consists of Shanghai and Beijing. I also find that Shanghai has been making progress in its scores along these four factors over the last three years, especially regarding financial market development, economic vitality, and cost of living. What Shanghai needs to focus on next is to improve its business environment so that it can move up to the second tier in IFC status.

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  • 2015

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A Case Study of Credit Risk Analysis and Modeling for SMEs -In an Internet Finance Setting

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In the last two years, China’s booming of Internet Finance Platform made significant impacts on three dimensions. Compared with the conventional market, Internet Finance is asserted to open a revolutionary

In the last two years, China’s booming of Internet Finance Platform made significant impacts on three dimensions. Compared with the conventional market, Internet Finance is asserted to open a revolutionary pathway of lending where by small and mid-sized companies may overcome the financing dilemma on credit accessibility and high cost. In other words, Internet Finance is hyped to be able to reduce information asymmetry, enhance allocation efficiency of resources, and promote product and process innovations for the financial institutions. However, the core essence of Internet Finance rests on risk assessment and control – a fundamental element applies to all forms of financing. Most current practice of internet finance on risk assessment and control remains unchanged from the mindset of traditional banking practices for small and medium sized firms. Hence, the same problems persisted and may only become even worse under the internet finance platform if no innovations take place.

In this thesis, the author proposed and tested a credit risk assessment model using data analytics techniques through an in-depth cases study with actual transaction data. Specifically, based on the 30,000 observations collected from actual transactional data from small and medium size firms of China’s home furnishing industry. The preliminary results are promising in spite of the limitations. The thesis concludes with the findings of relevance to improve the current practices and suggests areas of future research.

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  • 2016

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The Probe of Forms of Incentive Mechanisms for Securities Companies

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As securities companies occupy an increasingly important position in the national economy, and the most valuable competitive advantage for whom is human resources; therefore, Security Industry practitioners pay close attention

As securities companies occupy an increasingly important position in the national economy, and the most valuable competitive advantage for whom is human resources; therefore, Security Industry practitioners pay close attention to the influences of securities companies' incentive mechanisms regarding to various business types.

This paper finds that asymmetry of information in business models is the motivation of the gaming for all participants, through analyzing the differences of various business models of securities brokerage services. Further, various incentive mechanisms under different circumstances result in diverse strategies of gaming. It varies development paths of securities companies. Therefore, the purpose of the paper is to theoretically deduce the most reasonable and optimal securities companies’ incentive mechanism.

This paper intends to identify the principle component factors influencing securities brokerage services via questionnaire investigations towards 75 branches under the same securities company and 13 different securities companies, respectively. In addition, based on historical data, the paper aim to explain rationales between adjustments of incentive mechanisms and market shares of securities brokerage services.Lastly, combining author’s personal experience of various incentive mechanisms and development tracks in four securities companies that hopefully presents valuable information and clues for deducing the optimal securities company incentive mechanism.

There are two critical agency relationships in securities brokerage services. One is between principals, securities companies, and agents which are directors of branches. The other is between principals, securities companies, and agents which are securities marketers or brokers. Because of such operational setup, information is highly asymmetrical between all parties. It brought prominent problems regarding agency relationship and motivation aspects.

Under the certain circumstances, implementation of Incomplete Contracting Theory with franchising models in securities companies is quite useful. Specifically, for the former relationship between securities companies and marketers, the motivation effects of sub-license franchising are better than bonus compensation structure. Fixed salaries without bonus have the worst stimulating effects in such business model. For the latter relationship between securities companies and directors of branches, the agents focus on long term residual value claim rights, since it coincides with agents’ appraisals, focusing on incremental market shares and profit drawings.

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Date Created
  • 2018

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A Qualitative Analysis of the Business Models of Shared Workspaces

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The emergence and fast growth of shared workspaces have attracted increasing attention from investors, practitioners, and researchers. Overall, this industry is still at an early stage of development and the

The emergence and fast growth of shared workspaces have attracted increasing attention from investors, practitioners, and researchers. Overall, this industry is still at an early stage of development and the business models of shared workspace providers are still evolving. To enhance the understanding of the different business models adopted by the leading shared workspace providers, I conduct an in-depth qualitative analysis of three current market leaders - Regus, WeWork, and UrWork – using the Business Model Canvas proposed by Osterwalder (2008). My analysis suggests that shared workspace providers creates value by offering three tiers of services: (1) satisfying users’ needs for physical office spaces, (2) helping them build an enterprise eco-system, and (3) facilitating the development of a user community. I further use the PEST model to analyze how the macro-environmental factors in China and U.S. may have contributed to the development of different shared workspace business models in these two countries. Based on the above analyses, I propose a list of factors that may be critical to investors’ valuations of shared workspace companies.

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Date Created
  • 2018

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Understanding, Analyzing and Predicting Online User Behavior

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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

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.

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Date Created
  • 2019