Jurisprudence on Legal Liability for Intellectual Property Protection in Virtual Reality Content Production

In the science and technology continues to innovate, deeply integrated into economic and social development today, virtual reality technology has made important breakthroughs, has become an important innovation direction of science and technology. Virtual reality (VR) technology is a simulation technology to create and experience the virtual world, in cooperation with the computer, virtual reality technology can create interactive three-dimensional dynamic scene, by entering the human behavior simulation system, can provide users with immersive experience [1-5]. Capital investment and entrepreneurial teams prefer virtual reality technology in the process of industrial development due to its relatively low requirements in all aspects and relatively mature research and development [6-9]. This leads to a large number of content projects using virtual reality technology to copy and imitate content projects emerge after a certain content project becomes popular, and the products become homogenized, which seriously affects the innovative development of the industry [10-13]. Entrepreneurs are reluctant to invest resources in content development and tend to do application platform and equipment production, which is easy to cause deformed development of the industrial structure and is not conducive to the benign development of the virtual reality industry [14-15]. In addition, at the present stage, China’s intellectual property protection is not enough universalization of law, the people’s legal awareness is not strong and the law enforcement agencies are not strict in law enforcement, etc., and it is difficult for intellectual property rights owners to safeguard their legitimate rights and interests through the law [16-19]. Therefore, the launching of the intellectual property strategy of virtual reality industry should be actively promoted, so as to provide specialized and systematic doctrinal support for the comprehensive and in-depth construction of a strong intellectual property country.

Literature [20] shows that the rise of meta-universes allows virtual worlds to interact with users through creative expression, inevitably leading to infringement of existing trademark and copyright protected works, and that there is a strong need to extend existing trademark and copyright laws to seek intellectual property protection for virtual goods and services within meta-universes in order to avoid commercial litigation. Literature [21] describes virtual assets within the meta-universe and examines copyright and trademark infringement liability for virtually generated content, proposing possible stakeholder-oriented solutions to clear judicial hurdles for intellectual property protection of virtually produced content in the meta-universe. Literature [22] describes the characteristics of acquiring intellectual property rights in modern virtual reality technologies, based on which it proposes relevant intellectual property protection measures for virtual reality content production, such as applying for precautionary IP protection and methods of selling and controlling content production using blockchain technology for intellectual property protection. Literature [23] establishes the legal status and scope of virtual reality production content, and in general the copyright of the intellectual property subject should be attributed to the creator, but taking into account the subject circle of complex objects in the field of virtual and augmented reality technology, the legal relationship between the object of content and the subject of intellectual property rights should be determined by the diversity of the object. Literature [24] points out that virtual reality technology is essentially a series of computer programs, and the use of virtual reality technology, including but not limited to various types of images, music and other works composed of programs, has a complex intellectual property rights behavior, thus emphasizing the definition of the control of related technologies into the legislation, and the realization of intellectual property rights protection through the protection of advanced technologies. Literature [25] studied the link between blockchain technology and virtual reality technology, and the use of cohesive applications to combine the two can achieve privacy protection and intellectual property protection during the transfer of virtual property to the physical world.

This paper analyzes and organizes the development status of virtual assets, intellectual property protection, and economic growth by systematically collecting domestic and international related literature, working reports, books and other information on virtual assets, intellectual property protection, and economic growth. The panel data of 31 provinces from 2008 to 2023 are collected as samples, time effect and individual effect are introduced, and the development of virtual industry is measured by total virtual market income and per capita virtual market income, so as to establish a panel regression model to empirically analyze the direct and indirect influence mechanisms of intellectual property rights protection on the development of virtual industry under the virtual economy, and to discuss the the responsibility of intellectual property protection laws on virtual reality productions.

2

Research on intellectual property rights of virtual reality productions

Virtual reality technology is rapidly progressing, and the productions it produces are highly valued for their assetization value. Compared with developed countries such as the U.S. and the U.K., the development of China’s virtual industry is still in the primary stage, and its legal definition and ownership issues are still unclear, resulting in the development of the virtual industry facing many dilemmas. Clarifying the above basic issues is crucial for the orderly development of the virtual economy and the benign operation of the virtual industry.

2.1

The nature of rights in virtual reality productions

The right to property is a civil right directly embodied in a certain property interest, including the right to property, claims, inheritance and the property right part of intellectual property rights, and has the distinctive characteristics of value and disposability, and the opposite of the right to property is the right of person. Therefore, whether the right corresponding to the virtual reality production object belongs to the property right mainly lies in whether it possesses the value and disposability that the property right has. On the one hand, the most important characteristic of virtual reality productions that distinguishes them from native data is de-identification, so the personality right and privacy right characteristic of native data rights can be excluded when discussing the legal attributes of the rights of virtual reality productions. The object of native data is usually user information and cannot be sold because it is strictly protected by the right of privacy and personality right, but the virtual reality productions can be independent of the native data after in-depth processing, and no longer have the identifiable characteristics, so they usually become tradable objects. With the explosive growth of the data industry, the assetization value of virtual reality artifacts is also expanding. On the other hand, Chinese law stipulates that personal rights are exclusively owned by the individual right holder and cannot be transferred, while property rights are not subject to restrictions. As an incorporeal object, the right holder can usually dispose of virtual reality products without disclosing state secrets or infringing on other people’s privacy. Therefore, the right to virtual reality productions belongs to the category of property rights. The right of virtual reality production belongs to intellectual property rights for the following reasons: First, according to the property law, the object corresponding to the right of property is object, usually tangible objects and abstract objects such as stocks and bonds. The object of the right of virtual reality production object is virtual reality production object, which belongs to intangible object, with distinctive non-material characteristics, which is the fundamental characteristic different from the right of property. Secondly, the virtual reality production object itself does not constitute the debt relationship, only when the right person and the specific obligor around the virtual reality production object and the formation of various rights and obligations (such as: the virtual reality production object transfer, rent and other debt relationship) constitute the debt relationship. Therefore, the right to produce virtual reality objects does not belong to the debt. Third, although the virtual reality production belongs to a new type of property, but due to the virtual reality production processor in the process of cleaning, desensitization, polymerization, processing to make it has the de-identification, therefore belongs to the intellectual labor results, the virtual reality production corresponding to the rights should also belong to the intellectual property rights.

2.2

Macro policy analysis of the development of virtual reality productions

The vigorous development of virtual reality products cannot be separated from the top-level design and policy implementation of the state. In recent years, people’s congresses and governments at all levels have introduced a series of laws and regulations centering on virtual reality products, and the status of data as a key production factor has been further clarified, which provides policy guidance for the development of the virtual reality products industry. Virtual reality production objects are products of the development of information networks, which is a typical manifestation of the development of the digital economy. Its development history, as shown in Figure 1, has roughly gone through the following stages, with each stage presenting its own characteristics.

3

Regression model of the impact of intellectual property protection on the development of virtual industries

3.1

Panel data model

Panel data contains different cross-section unit data sets, the same cross-section unit set contains different repeated observations, in these different cross-section at the same time to select different sample observations constitute the sample data is panel data. Parallel panel data integrates the information of time data and cross-section data in two dimensions, compared with the previous single time series data or cross-section data, parallel panel data can be constructed closer to the reality of the more accurate data model, so as to carry out a more in-depth analysis of the problem, which has occupied an important position in the field of modern econometrics.

When regression analysis is performed on two-dimensional panel data, the panel regression model can be classified into three categories based on whether the constant term, coefficient term and intercept term in the regression model change over time. Fixed effects panel regression models: 1 $Y_{i} = α_{i} + β X_{i} + U_{i}$ $${Y_i} = {\alpha _i} + \beta {X_i} + {U_i}$$

Random effects panel regression model: 2 $Y_{i} = α_{i} + β_{i} X_{i} + U_{i}$ $${Y_i} = {\alpha _i} + {\beta _i}{X_i} + {U_i}$$

From the basic regression formula of the random effects panel regression model, it can be seen that the constant term α_i, the intercept term U_i and the coefficient term β_i of the random effects model are not fixed and will change over time, so the random effects model is called the variable coefficient regression model by some people. In addition, the random effects regression model can generally be solved by the generalized least squares method (i.e., the GLS method), and thus it is also called the GLS regression model.

Mixed effects panel regression model: 3 $Y_{i} = α + β X_{i} + U_{i}$ $${Y_i} = \alpha + \beta {X_i} + {U_i}$$

As the name suggests, a mixed effects regression model is a hybrid form of a random regression model and a fixed regression model. As can be seen from its basic regression formula, the constant term α and coefficient term β of the mixed-effects model are fixed and do not change over time, but its intercept term U_i is not fixed and changes over time. The mixed effects regression model is also known as the LS regression model because it can generally be solved by the mixed least squares method (i.e., the LS method).

3.2

Impact of variable selection

What are the effects of variable misselection on estimation? And how does variable selection improve the predictive accuracy of the dependent variable? For simplicity, assume the standard deviation of the error term is σ = 1.

Let $X = (X_{1}, X_{2})$ $$X = \left( {{X_1},{X_2}} \right)$$, $β = {(β_{1}^{'}, β_{2}^{'})}^{'}$ $$\beta = {\left( {{{\beta _1^\prime}},{{\beta _2^\prime}}} \right)^\prime }$$, where X₁ is a n × s-dimensional matrix, X₂ is a n × (k − s)-dimensional matrix, β₁ is a s-dimensional vector, and β₂ is an k − s-dimensional vector, the full model is written in the following form: 4 $y = X_{1} β_{1} + X_{2} β_{2} + ε$ $$y = {X_1}{\beta _1} + {X_2}{\beta _2} + \varepsilon$$

And the alternative model is: 5 $y = X_{1} β_{1} + ε$ $$y = {X_1}{\beta _1} + \varepsilon$$

For the full model (4), the least squares estimate of the regression coefficient β₁ is: 6 $\hat{β} = ({\hat{β}}_{1}', {\hat{β}}_{2}')' = {(X' X)}^{- 1} X' Y$ $$\hat{\beta }=\left( {{{\hat{\beta }}}_{1}}^\prime ,{{{\hat{\beta }}}_{2}}^\prime \right)^\prime ={{\left( X^\prime X \right)}^{-1}}X^\prime Y$$

For the alternative model (5), the least squares estimate of the regression coefficient β₁ is: 7 ${\tilde{β}}_{1} = {(X_{1}' X_{1})}^{- 1} X_{1}' Y$ $${\widetilde \beta _1} = {\left( {{X_1}^\prime {X_1}} \right)^{ - 1}}{X_1}^\prime Y$$

If the full model is correct, then there are $E (\hat{β}) = β$ $$E(\widehat \beta ) = \beta$$, $V a r (\hat{β}) = {(X' X)}^{- 1}$ $$Var(\widehat \beta ) = {\left( {X^\prime X} \right)^{ - 1}}$$, $E ({\tilde{β}}_{1}) = β_{1} + {(X_{1}' X_{1})}^{- 1} X_{2}' β_{2}$ $$E\left( {{{\widetilde \beta }_1}} \right) = {\beta _1} + {\left( {{X_1}^\prime {X_1}} \right)^{ - 1}}{X_2}^\prime {\beta _2}$$, $V a r ({\tilde{β}}_{1}) = {(X_{1}' X_{1})}^{- 1}$ $$Var\left( {{{\widetilde \beta }_1}} \right) = {\left( {{X_1}^\prime {X_1}} \right)^{ - 1}}$$. From the above, it is clear that as long as β₂ ≠ 0, $\tilde{β}$ $$\widetilde \beta$$ is a biased estimation, its variance cannot be used as a measure of β estimation accuracy, and a more reasonable criterion can be measured by the mean-square error $M S E ({\tilde{β}}_{1}) = E {({\tilde{β}}_{1} - β_{1})}^{'} ({\tilde{β}}_{1} - β_{1})$ $$MSE\left( {{{\widetilde \beta }_1}} \right) = E{\left( {{{\widetilde \beta }_1} - {\beta _1}} \right)^\prime }\left( {{{\widetilde \beta }_1} - {\beta _1}} \right)$$ which can be calculated: 8 $M S E ({\tilde{β}}_{1}) = {(X_{1}' X_{1})}^{- 1} + {(X_{1}' X_{1})}^{- 1} X_{2}' β_{2} β_{2}' X_{2} {(X_{1}' X_{1})}^{- 1}$ $$MSE\left( {{{\widetilde \beta }_1}} \right) = {\left( {{X_1}^\prime {X_1}} \right)^{ - 1}} + {\left( {{X_1}^\prime {X_1}} \right)^{ - 1}}{X_2}^\prime {\beta _2}{\beta _2}^\prime {X_2}{\left( {{X_1}^\prime {X_1}} \right)^{ - 1}}$$

The above derivation shows that choosing the wrong model can result in biased parameter estimates. In addition, it can be shown that if $V a r ({\hat{β}}_{2}) - β_{2} β_{2}^{'}$ $$Var\left( {{{\widehat \beta }_2}} \right) - {\beta _2}{\beta _2}^\prime$$ is a semi-positive definite matrix, then $V a r ({\hat{β}}_{1}) - M S E ({\tilde{β}}_{1})$ $$Var\left( {{{\widehat \beta }_1}} \right) - MSE\left( {{{\widetilde \beta }_1}} \right)$$ is also semi-positive definite, indicating that fewer variables can lead to an improvement in estimation accuracy, and therefore, if the variable $(β_{2} \approx 0)$ $$\left( {{\beta _2} \approx 0} \right)$$, which has a very small effect, is present in the model, and we are able to remove it using the relevant method, the resulting estimates will not only be less biased, but also have improved accuracy.

3.3

Methodology for variable selection

Hypothesis testing includes forward selection method, backward elimination method, step-by-step regression method, etc. The basic idea is to determine whether to add or remove certain variables through step-by-step hypothesis testing results, and then select the significant variables. The following is a brief introduction to the forward selection method as an example, for more details, please refer to “Linear Statistical Modeling - Linear Regression and ANOVA”.

Forward selection method is to introduce independent variables one by one, from less to more, until there are no independent variables that can be selected into the independent variables, requiring each time the introduction of the variable on the dependent variable is the largest among the remaining variables, and through the hypothesis test, the specific steps are as follows:

Step 1: Build a one-way linear regression model for each of the k independent variables x₁, x₂, ⋯, x_k with the dependent variable y: 9 $y = β_{0} + x_{i} β_{1} + ε, i = 1, 2, \dots k$ $$y = {\beta _0} + {x_i}{\beta _1} + \varepsilon ,i = 1,2, \cdots k$$

The value of the F-test statistic for the corresponding regression coefficient for each independent variable is then calculated and noted as $F_{1}^{(1)}, F_{2}^{(1)}, \dots, F_{k}^{(1)}$ $$F_1^{(1)},F_2^{(1)}, \cdots ,F_k^{(1)}$$. Also noted as $F_{i_{1}}^{(1)} = \max {F_{1}^{(1)}, F_{2}^{(1)}, \dots, F_{k}^{(1)}}$ $$F_{{i_1}}^{(1)} = \max \left\{ {F_1^{(1)},F_2^{(1)}, \cdots ,F_k^{(1)}} \right\}$$. For a given significance level α, the critical value $F_{α}^{(1)}$ $$F_\alpha ^{(1)}$$ is known and if $F_{i_{1}}^{(1)} \geq F_{α}^{(1)}$ $$F_{{i_1}}^{(1)} \geq F_\alpha ^{(1)}$$, the variable $x_{i_{1}}$ $${x_{{i_1}}}$$ is introduced into the linear regression model, otherwise variable selection is terminated.

Step 2: Build a binary linear regression model for dependent variable y and a subset of independent variables ${x_{i_{1}}, x_{1}}, \dots, {x_{i_{1}}, x_{i_{1} - 1}}, {x_{i_{1}}, x_{i_{1} + 1}}, \dots, {x_{i_{1}}, x_{k}}$ $$\left\{ {{x_{{i_1}}},{x_1}} \right\}, \cdots ,\left\{ {{x_{{i_1}}},{x_{{i_1} - 1}}} \right\},\left\{ {{x_{{i_1}}},{x_{{i_1} + 1}}} \right\}, \cdots ,\left\{ {{x_{{i_1}}},{x_k}} \right\}$$, of which there are k − 1. Then calculate the value of the F test statistic for the corresponding regression coefficients of variable $x_{j} (j \neq i_{1})$ $${x_j}\left( {j \ne {i_1}} \right)$$, denoted as $F_{j}^{(2)} (j \neq i_{1})$ $$F_j^{(2)}\left( {j \ne {i_1}} \right)$$, alternatively: 10 $F_{i_{2}}^{(2)} = \max {F_{1}^{(2)}, \dots, F_{i_{1} - 1}^{(2)}, F_{i_{1} + 1}^{(2)}, \dots, F_{k - 1}^{(2)}}$ $$F_{{i_2}}^{(2)} = \max \left\{ {F_1^{(2)}, \cdots ,F_{{i_1} - 1}^{(2)},F_{{i_1} + 1}^{(2)}, \cdots ,F_{k - 1}^{(2)}} \right\}$$

For a given significance level α, the critical value $F_{α}^{(2)}$ $$F_\alpha ^{(2)}$$ is known and if $F_{i_{2}}^{(2)} \geq F_{α}^{(2)}$ $$F_{{i_2}}^{(2)} \geq F_\alpha ^{(2)}$$, variable $x_{i_{2}}$ $${x_{{i_2}}}$$ is introduced into the linear regression model, otherwise variable selection is terminated.

Step 3: Consider a subset of independent variables ${x_{i_{1}}, x_{i_{2}}, x_{j}} (j \neq i_{1}, i_{2})$ $$\left\{ {{x_{{i_1}}},{x_{{i_2}}},{x_j}} \right\}\left( {j \ne {i_1},{i_2}} \right)$$ with the regression model of dependent variable y and repeat step 2 until, as tested by F, there are no independent variables that can be introduced, completing the variable selection.

4

Mechanisms of intellectual property laws affecting virtual reality productions

4.1

Virtual production assets study

4.1.1

The growing size of the virtual economy

The development of the virtual economy is based on virtual assets as a carrier, the scale of virtual assets is closely related to the development of the virtual economy, the larger the scale of virtual assets, the more the development of the virtual economy is alive, therefore, the scale of virtual assets can be shown by the status of the development of the virtual economy as shown in Figure 2. According to the White Paper on Virtual Economy published by the China Institute of Information and Communication Research in 2023, the overall scale of China’s virtual economy has been increasing, from 2.6 trillion yuan in 2005 to 28 trillion yuan in 2018, and then reaching the broken 50 trillion yuan for the first time in 2023, and the overall scale of the virtual economy has shown a rising trend. In addition, the virtual economy’s share of GDP has continued to increase, reaching 41.7% of GDP in 2023, surpassing the secondary industry’s share of GDP (the secondary industry’s share of GDP was 39.9% in 2023).

4.1.2

Continuous optimization of the structure of the virtual economy

Since entering the stage of high-quality development, the structure of China’s virtual economy is shown in Figure 3.In 2023, the scale of China’s virtual industrialization will be 9.3 trillion yuan, and the scale of industrial virtualization will be 41 trillion yuan.Compared with 2017, the proportion of virtual industrialization in the virtual economy has risen from 7% to 7.7%, and the proportion of industrial virtualization in the virtual economy has risen from 23.2% to 34.1%, and the proportion of virtual industrialization has continued to rise , the proportion of industrial virtualization continues to rise, and the virtual economy has deepened the degree of virtualization transformation for traditional industries.

4.1.3

Act on Intellectual Property Protection of Virtual Assets

The protection of virtual intellectual property rights is an important economic and legal topic, and with the advent of the virtualization era, the protection of virtual intellectual property rights is crucial to promoting innovation, facilitating industrial development and maintaining fair competition. The national ministerial policies for the intellectual property system are shown in Table 1.

Table 1.

The policy of the virtual intellectual property system

Policy document	Release date	Release unit	Relevant content
Outline of the construction of intellectual property powers	2021/9/22	CPC central committee	We will accelerate the legislation of new intellectual property rights in new areas such as virtual reality, artificial intelligence and gene technology
“Fourteen five” national intellectual property protection and application planning	2021/10/9	The state council	We will improve the protection system for new industries such as virtual reality, artificial intelligence and genetic technology
A report on the work of the people’s court	2021/10/21	Supreme people’s court	Properly hearing data confirmation, trading, service, privacy protection, etc
The national intellectual property administration protection work plan in 2022	2022/1/20	State intellectual property bureau	We will actively respond to new requirements for intellectual property protection in new areas such as virtual reality and artificial intelligence The rules of intellectual property protection of the data.
Notification of the pilot area of the data intellectual property work	22/11/17	State intellectual property bureau	Determine the pilot area of data intellectual property in Beijing, Shanghai, jiangsu, zhejiang, fujian, shandong, guangdong and shenzhen
Opinions about the role of data based systems to better use data elements	2022/12/2	CPC central committee	Explore the establishment of data property rights system and study data property registration
Notification of the initial case of the initial intellectual property pledge financing and insurance	2023/1/12	The national intellectual property bureau of China’s bank of China	To explore the new model of intellectual property ownership and the number of intellectual property
Opinions on strengthening the protection of intellectual property	2023/2/20	National development and reform commission Supreme people’s court	To promote the research on the relevant system of data intellectual property protection
Guidelines for promoting annual development of intellectual property	2023/3/23	State intellectual property bureau	Explore the construction of data intellectual property protection system and registration system

In 2020, the “Proposal on Accelerating the Construction of Data Intellectual Property Protection System” declared by the Intellectual Property Development Research Center of the State Intellectual Property Office (SIPO) won the Outstanding Strategic Information Award. This is the first time that the concept of “data intellectual property” has appeared in an official government document. In September 2021, the State Council issued the Outline for the Construction of a Strong Intellectual Property Rights State (2021-2035), which explicitly proposed to “study and construct rules for the protection of intellectual property rights of data”, which is the first step from theoretical exploration to institutional innovation. Subsequently, the State Intellectual Property Office formulated the “14th Five-Year Plan for the Protection and Utilization of National Intellectual Property Rights”, setting up a column on data intellectual property rights protection, and deploying it in terms of constructing protection rules, promoting the utilization of data resources and security protection. In March 2022, the State Intellectual Property Office (SIPO) issued the Annual Working Guidelines for Promoting High-Quality Development of Intellectual Property Rights (2022), which made new requirements in formulating a new intellectual property protection system, and made it clear that it was necessary to promote the application of intellectual property rights and to promote the development of big data and artificial intelligence with incentive mechanisms. In addition the Guidelines also require the prevention of a series of risks that may be caused by the new industry, to avoid the misuse of big data as well as the leakage of personal privacy.2022 On November 30, 2022, in order to promote the effective implementation of the local pilot work of data intellectual property rights, the State Intellectual Property Office (SIPO) has organized a data intellectual property rights pilot conference, and eight regions, including Beijing, Shanghai and other regions, have been registered as pilot regions for data intellectual property rights to carry out the pilot work.

In addition to pilot regulations, governments at all levels have taken a series of measures to strengthen enforcement of virtual intellectual property rights. The Government and law enforcement agencies have achieved certain results by strengthening their efforts to combat intellectual property rights violations. For example, in combating online piracy, the National Copyright Administration of China has launched several “Sword Net Actions” to focus on and combat copyright infringement of virtual works. In terms of the application of innovative technology, the NCCA has actively utilized innovative technological means to enhance the level of protection of virtual intellectual property rights. For example, through virtual watermarking technology, encryption technology, and intelligent monitoring technology, virtual content can be traced and anti-counterfeiting, thus enhancing the ability of copyright protection. In addition, artificial intelligence technology has been widely used in the field of copyright protection, which can automatically monitor, identify, and deal with infringements. In terms of industry self-regulation and cooperation mechanisms, self-regulation and cooperation have been carried out in the virtual industry to strengthen the protection of virtual intellectual property rights. Industry associations, Internet platforms, and content providers are among the main bodies that have actively promoted the establishment and operation of self-regulatory mechanisms to strengthen protection measures for virtual intellectual property rights. In addition, a good cooperation mechanism has been formed between the government and enterprises to jointly combat infringement and promote the protection of virtual intellectual property rights.

4.2

Empirical analysis of the impact of intellectual property protection on the development of virtual industry

4.2.1

Descriptive statistics of variable samples

In this paper, panel data from 31 provinces in China from 2008-2023 is selected. Tibet is excluded because there is some missing data in intellectual property protection, industrial aggregation, and virtual resources. The total virtual market revenue and the number of voluntarily registered works in each region are from the website of the National Copyright Administration (NCA), and the number of invention patents authorized, national GDP, regional GDP, urban per capita consumption expenditure, and regional population are from the website of the National Bureau of Statistics (NBS), etc.

The model of the direct impact of the core explanatory variable IPR protection on the development of the virtual industry of the explanatory variable is established, using a panel regression model, taking into account the time effect and individual effect. The total virtual market revenue (WHSR) and per capita virtual market revenue (JWH) are used to measure the development of the virtual industry respectively, so the model is constructed as follows: $\begin{array}{l} W H S R_{i t} = β_{10} + β_{11} Z S C Q_{i t} + \sum C_{1 k} {Control}_{k_{i} i t} + u_{i} + ϕ_{t} + ε_{i t} \\ J W H_{i t} = β_{20} + β_{21} Z S C Q_{i t} + \sum C_{2 k} {Control}_{k_{i} i t} + u_{i} + ϕ_{t} + ε_{i t} \end{array}$ $$\begin{array}{l} WHSR_{i t}=\beta_{10}+\beta_{11} Z S C Q_{i t}+\sum C_{1 k} \ \hbox{Control}_{k_i i t}+u_i+\phi_t+\varepsilon_{i t} \\ J W H_{i t}=\beta_{20}+\beta_{21} Z S C Q_{i t}+\sum C_{2 k} \hbox{Control}_{k_i i t}+u_i+\phi_t+\varepsilon_{i t} \end{array}$$

In the above equation, i and t represent different provinces and years, respectively, WHCY represents virtual industry development, ZSCQ represents intellectual property protection, u_i represents individual fixed effects, ϕ_t represents time fixed effects, ε_it represents random error term, Control represents control variables, and k is used to denote different control variables, and the specific control variables include the consumption level represented by using XF, the resource level represented by using WHZY to represent, the level of capital resources using GDP, the level of human resources using RK, the level of virtual technology using CX, and the level of virtual industry agglomeration using JJ. The overall descriptive statistical characteristics of virtual industry development, intellectual property protection, and related variables are shown in Table 2 for panel data consisting of 500 samples.

Table 2.

Variable sample descriptive statistics

VARIABLES	N	mean	sd	min	max
WHSR	500	7.021e+06	3.121e+07	0	5.014e+08
JWH	500	2312	6933	2	87495
ZSCQ	500	27846	109294	1	1.012e+06
CX	500	4727	8859	5	60234
XF	500	16018	7842	5365	48795
WHZY	500	9815	8229	2	556
GDP	500	16928	18365	2180	108493
RK	500	4421	2894	288	13284
JJ	500	1.014	0.987	1	9278

4.2.2

Analysis of empirical results

The regression results of intellectual property protection on the development of virtual industry are shown in Table 3, model (1) and (2) are used to measure the virtual market development by the total virtual market income, and model (3) and (4) are used to measure the virtual market development by the per capita virtual market income. Only total virtual market income and intellectual property protection are regressed in model (1), at which time the coefficient of intellectual property protection is 115.132 and is significant at the 1% level, indicating that one unit of change in intellectual property protection can have a 115.132-unit impact on the development of the virtual industry after eliminating the individual effect and the time effect. The model adjusted R² is 0.345, and the whole passes the F test at 1% significance level, indicating that the impact of intellectual property protection on the development of virtual industry exists significantly. Model (2) added consumption level XF, cultural resources WHZY, capital resources GDP, human resources RK as control variables, the coefficient of the impact of intellectual property protection on the development of virtual industry becomes smaller to 50.268, and the impact of intellectual property protection on the development of virtual industry is significant at 1% significance level. R² increases to 0.533 after model adjustment, indicating that the addition of industry aggregation variables makes the model fit increase dramatically, and the model still passes the F-test at 1% significance level in the whole. In model (3), only the per capita virtual market income and intellectual property protection are regressed, at this time, the coefficient of intellectual property protection is 0.053, and it is significant at 1% level, which indicates that after eliminating the individual effect and the time effect, the change of one unit of intellectual property protection can have an impact of 0.053 units on the development of virtual industry. The model adjusted R² is 0.552, and the whole passes the F-test at 1% significance level, indicating that the impact of intellectual property protection on the development of virtual industry exists significantly. Model (2) adds consumption level XF, cultural resources WHZY, capital resources GDP, human resources RK, virtual technology resources CX, virtual industry aggregation level JJ as control variables, the coefficient of the impact of intellectual property protection on the development of the virtual industry becomes 0.022, and the impact of intellectual property protection on the development of the virtual industry is significant at 1% significance level. The R² increases to 0.796 after model adjustment, indicating that the addition of industry aggregation variable makes the model fit increase dramatically, and the model still passes the F-test at 1% significance level in the whole. In summary, whether using the total virtual market income or per capita virtual market income to measure the degree of virtual industry development, intellectual property protection has a positive and positive impact on virtual industry development.

Table 3.

The impact of intellectual property on the virtual industry

VARIABLES	(1) WHSR	(2) WHSR	(3) JWH	(4) JWH
ZSCQ	115.132***(6.53)	50.268***(2.85)	0.053***(15.47)	0.022***(5.04)
XF		1925.114***(2.74)		0.665***(5.36)
WHZY		-125117.725***(-4.08)		-9.485*(-2.03)
GDP		660.947***(5.63)		-0.292***(-5.68)
RK		392852.122***(5.68)		-1.008(-0.94)
CK				0.574***(7.96)
JJ				2512.5***(12.95)
Observations	500	500	500	500
R-squred	0.422	0.582	0.587	0.815
Adi R-squared	0.345	0.533	0.552	0.796
Province FE	YES	YES	YES	YES
Year FE	YES	YES	YES	YES
F test	2.58e-10	0	0	0
F	42.36	48.96	245.2	142.6

4.2.3

Empirical analysis of the indirect mechanism of the mediating effect

In this section, the number of invention patent authorizations is chosen to measure the mediating variable of virtual reality technology innovation. According to the previous analysis of the per capita virtual market revenue to measure the virtual industry development is more scientific and the fitting effect is also better, the following still refers to the previous way of selecting the explanatory variables, explanatory variables and control variables, and the data source is the same as above. Intellectual property protection through virtual technology innovation to promote the development of virtual industry mediation effect regression results shown in Table 4, model (6) reflects the total effect of intellectual property protection on the development of virtual industry under the condition of the total effect is significant, want to verify the mediation effect need to ensure that the model (7) in the protection of intellectual property rights on the virtual technological innovation of the impact of the model (8) in the virtual technological innovation of the virtual industry development of the impact of the model (7) is significant.

Table 4.

Empirical analysis of indirect mechanism of intermediary effect

VARIABLES	(5)JWH	(6)JWH	(7)CX	(8)JWH
ZSCQ	0.053***(15.47)	0.045***(9.36)	0.021***(9.85)	0.023***(5.28)
CX				0.822***(10.25)
XF		1.195***(8.69)	0.745***(9.82)	0.598***(4.35)
WHZY		-13.48**(-2.18)	2.458(0.74)	-15.268***(-2.78)
GDP		-0.063(-108)	0.414***(14.48)	-0.385***(-6.89)
RK		2.428*(1.89)	4.152***(5.63)	-0.986(-0.82)
Observations	500	500	500	500
R-squred	0.596	0.675	0.956	0.745
Province FE	YES	YES	YES	YES
Year FE	YES	YES	YES	YES
F test	0	0	0	0
R²_a	0.552	0.645	0.947	0.715
F	242.3	80.25	412.5	100.02

The coefficient of the impact of intellectual property protection on the development of virtual industry in model (6) is 0.045, and the impact on the development of virtual industry is significant at 1% significance level, indicating that the higher the degree of intellectual property protection, the higher the level of development of virtual industry. The impact coefficient of intellectual property protection on virtual technology innovation in model (7) is 0.021, and the impact on virtual technology innovation is significant at 1% significance level, indicating that the higher the degree of intellectual property protection, the higher the level of virtual technology innovation. Model (8) illustrates the impact of virtual technological innovation and intellectual property protection in one equation on the development of virtual industries. At this time, the impact coefficient of virtual technological innovation on the development of virtual industry is 0.023, and the impact on the development of virtual industry is significant at 1% significance level, which indicates that for every unit increase in the level of virtual technological innovation, the level of virtual industry development rises by 0.023 units, which means that virtual technological innovation accelerates the process of virtual industry development.

5

Conclusion

This paper tries to construct a panel regression model of intellectual property protection on the development of virtual industry under the virtual economy based on the consideration of individual effect and time effect, and uses the panel data of national GDP of 31 provinces, the number of invention patent authorization and other panel data from 2008 to 2023 to conduct empirical analysis, which indirectly reacts to the responsibility of the law of intellectual property protection in the virtual reality productions. The results show that with the continuous expansion and optimization of the virtual economy’s scale and structure. Intellectual property protection law is becoming increasingly important in the development of virtual display productions. Through the regression model, it can be seen that intellectual property protection has a significant impact on the development of virtual industries even at the 1% significance level of intellectual property protection. Intellectual property protection has a significant impact on virtual technology innovation, and virtual technology innovation can accelerate the process of industry development.

Lingua:: Inglese

Frequenza di pubblicazione:: 1 volte all'anno
Argomenti della rivista:: Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro

Feed RSS della rivista

Jurisprudence on Legal Liability for Intellectual Property Protection in Virtual Reality Content Production

Yinfeng Li

Pubblicato online: 24 mar 2025

Ricevuto: 21 ott 2024

Accettato: 15 feb 2025

DOI: https://doi.org/10.2478/amns-2025-0742

Parole chiavePanel data, Regression model, Mediation effect, Virtual industry

© 2025 Yinfeng Li, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Parole chiave
Panel data, Regression model, Mediation effect, Virtual industry