1. - the following data sources and scores are from the in depth analysis report on business model innovation and investment opportunities of China's blockchain instry published by foresight Instry Research Institute
< H2 > - original title: Analysis on the current situation and development trend of China's blockchain instry in 2019, widely applied and accelerating the construction of Digital China; Midstream blockchain application and technical services
application fields of downstream blockchain. The upstream hardware, technology and infrastructure mainly provide the necessary hardware, technology and infrastructure support for blockchain application. The hardware equipment includes mining machinery, ore pool, chip manufacturer, etc; General technologies include distributed storage, decentralized transaction, data service, distributed computing and other related technologies
the downstream application fields include the combination of application blockchain technology and existing instries, mainly including financial instry, logistics instry, right protection, medical health, instrial energy and many other fields. As an emerging technology, blockchain has many downstream application fields and great development potential
the application and service of midstream blockchain includes the construction of infrastructure platform and the provision of technical service support. The construction of infrastructure platform is divided into general infrastructure chain and vertical domain infrastructure chain; Technical service support includes technical support and service support. Similar to upstream technology, technical support is responsible for providing buyers with a series of technical support based on blockchain procts, such as blockchain security protection; Service support includes a series of services such as digital asset trading place, digital asset storage, media community, etc
analysis of instrial chain of blockchain instry
2. Blockchain platforms include Ethereum, Asch and other underlying application development platforms
Ethereum, an open source public blockchain platform with smart contract function, provides decentralized Ethereum virtual machine to process point-to-point contract through its special cryptocurrency ether (ETH)
arch, a decentralized application platform based on side chain technology. Asch is designed to lower the threshold of developers, such as using JavaScript as the application programming language and supporting relational database to store transaction data, which is believed to be very attractive to developers and small and medium-sized enterprises
extended data
in 2008, Nakamoto first proposed the concept of blockchain. In the following years, blockchain has become the core component of electronic currency bitcoin: public account book for all transactions
by using peer-to-peer network and distributed timestamp server, the blockchain database can be managed independently. The blockchain invented for bitcoin makes it the first digital currency to solve the problem of repeated consumption. Bitcoin's design is a source of inspiration for other applications
bitcoin is the absolute mainstream of digital currency, and digital currency is in full bloom. Bitcoin, litecoin, dogecoin, dashcoin are common. In addition to currency application, there are various derivative applications, such as Ethereum, Asch and other underlying application development platforms, as well as NXT, SIA, bitstocks, maidsafe, ripple and other instrial applications
3. Blockchain is a key project in the 13th five year plan for national informatization. It is parallel with artificial intelligence, big data, driverless and other projects. With the support of the government, blockchain technology has developed rapidly, and China's blockchain instry is expected to take the lead in the world. At present, the number of domestic blockchain related companies is increasing, of which fast online has been in the lead
4. Regulatory variables can be qualitative or quantitative. In the analysis of regulatory effect, the independent variable and regulatory variable should be transformed centrally. Brief model: y = ax + BM + CXM + E. The relationship between Y and X is characterized by regression coefficient a + cm, which is a linear function of M, and C measures the size of the moderating effect. If C is significant, it means that the regulatory effect of M is significant. 2. Analysis method of regulatory effect analysis method of significant variable: divided into four cases. When the independent variable is a category variable and the moderating variable is also a category variable, the analysis of variance of two factor interaction effect is used, and the interaction effect is the moderating effect; When the regulatory variable is a continuous variable, the independent variable uses the pseudo variable, centralizes the independent variable and the regulatory variable, and does the hierarchical regression analysis of y = ax + BM + CXM + e: 1. Do the regression of y to X and m, and get the determination coefficient R1 2. 2. The regression of y to x, m and XM yielded R2 2. If R2 2 was significantly higher than R1 2, the regulatory effect was significant. Or, XM regression coefficient test, if significant, the regulatory effect is significant; When the independent variable is a continuous variable, the regulating variable is a category variable, grouping regression: grouping according to the value of M, doing y to x regression. If the difference of regression coefficient is significant, the regulation effect is significant. When the regulation variable is a continuous variable, the hierarchical regression analysis of y = ax + BM + CXM + e is done as above. There are two ways to analyze the moderating effect of latent variables: one is that the moderating variable is the category variable and the independent variable is the latent variable; The second is that both regulatory variables and independent variables are latent variables. When the moderator is a class variable, group structural equation analysis is performed. The method is to limit the regression coefficients of the two groups of structural equations to be equal, and get one χ 2 and the corresponding degrees of freedom. Then remove this restriction, re estimate the model, and get another one χ 2 and the corresponding degrees of freedom. ahead χ 2 minus the following χ 2 get a new one χ 2, the degree of freedom is the difference between the two models. If χ If the test result is statistically significant, the moderating effect is significant; When regulatory variables and independent variables are latent variables, there are many different analysis methods. The most convenient one is the unconstrained model proposed by marsh, Wen and Hau. 3. The definition of intermediary variable is the influence of independent variable x on dependent variable y. if x influences y by influencing variable m, then M is called intermediary variable. Y=cX+e1, M=aX+ e2 , Y= c′X+bM+e3 Where C is the total effect of X on y, AB is the mediating effect through M, and C 'is the direct effect. When there is only one mediating variable, there is C = C ′ + AB between the effects, and the mediating effect is measured by C-C ′ = ab. 4. Mediating effect analysis method mediating effect is indirect effect, regardless of whether the variables involve latent variables, structural equation model can be used to analyze mediating effect. The first step is to test system C. if C is not significant and the correlation between Y and X is not significant, stop the mediating effect analysis, and if it is significant, proceed to the second step; The second step is to test a and B once. If they are all significant, then test C ′, C ′, and the mediating effect is significant. If C ′ is not significant, then the complete mediating effect is significant; If at least one of a and B is not significant, do Sobel test, significant mediating effect is significant, not significant mediating effect is not significant. The statistic of Sobel test is Z = ^ A ^ B / SAB, in which ^ A and ^ B are estimates of a and B respectively, SAB = ^ a2sb2 + b2sa2, SA and Sb are standard errors of ^ A and ^ B respectively. 5. Comparison between moderator and mediator moderator m moderator m research purpose when does x affect y or when does x have a greater impact? How does x affect the moderating effect, interaction effect, mediating effect of y-related concepts When the influence of X on y is considered, the influence of strong x on y is strong and stable. The typical model is y = am + BM + CXM + e, M = ax + E2, y = C ′ x + BM + E3. The position of m in the model is x, M is in front of Y, M can be in front of X, the function of m after X and before y affects the direction (positive or negative) and strength of the relationship between Y and X. x influences the relationship between Y, m and X, X and X through it The correlation between M and X, y can be significant or not (the latter is ideal) the correlation between M and X, y is significant effect regression coefficient C regression coefficient proct AB effect estimate ^ C ^ A ^ B effect test whether C is equal to zero, AB is equal to zero test strategy do hierarchical regression analysis, test the significance of partial regression coefficient C (t test); 6. SPSS operation method of mediating effect and moderating effect. First, descriptive statistics, including M SD and internal consistency reliability (a) are used. Second, all variables are correlated, including statistical variables and hypothetical x, y, y, Third, regression analysis To choose linear regression in regression, we should first centralize the independent variable and m, that is, subtract their respective mean. 1. Now, we input m (regulatory variable or intermediary variable), y dependent variable, and demographic variable related to any of the independent variable, dependent variable, and M regulatory variable into independent. 2. Then press next to input x independent variable (intermediary variable so far). 3 In order to do the adjustment variable analysis, it is necessary to input the opportunity of X and m in the next for further regression. The test mainly depends on whether f is significant
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6. First, whether blockchain technology service providers provide successful cases; Second, the scale and strength of the technical team is the most important factor to ensure the progress and stability of the project. We can take a look at Heshu blockchain technology laboratory
7. The laikelib blockchain technology developed by Shanghai Heshu software is easy to access.
8. As a blockchain technology R & D enterprise, Shanghai Heshu Software Co., Ltd. is aiming at the blockchain technology instry, and deeply excavates the frontier technology of blockchain to build an Internet innovation ecosystem based on blockchain in an all-round way. It aims to strengthen the ability of big data collection and analysis through the R & D and application of blockchain technology, and provide reasonable and legal technical development and application guidance for different enterprises and indivial users. Let indivial users get Internet Dividends with effective behavior records, let enterprise users rece operating costs and improve the accuracy of market delivery.