Utilizing virtual arts in reforming market players' behavior to invest in sustainability projects

The study addresses how the expansion of the virtual arts market can influence private investors’ behavior toward financing sustainability projects. Framed by global sustainability milestones such as the 1992 Earth Summit and the UN’s 2015 Sustainable Development Goals, the paper highlights critical financing gaps and investor perceptions that often hinder green investment. It posits that immersive and interactive virtual arts experiences can reshape attitudes by educating investors on the financial and societal benefits of sustainable projects and by illustrating the risks of inaction. Focusing on China—given its rapid economic growth, environmental challenges, and flourishing virtual arts ecosystem—the research aims to fill a gap in understanding the linkage between virtual arts market size and private sustainable investment, with a particular emphasis on private actors’ motivations and behavior.

The paper reviews four strands of literature. (1) Virtual arts and sustainability: Prior work shows virtual reality and augmented reality can promote sustainable behaviors, raise environmental awareness, and engage individuals across domains such as eco-feedback, simulations, storytelling, tourism, and architecture. (2) Sustainable investment: Studies emphasize sustainable finance’s roles in addressing environmental challenges, supporting growth, improving long-run performance and resilience, and spurring innovation and low-carbon transitions, while noting developing economies’ capital access constraints. (3) Private sustainable investment: Research examines private investors’ motivations, barriers, ESG considerations, policy and institutional influences, social norms, and corporate practices that shape investment decisions. (4) Sustainable development in China: Scholarship covers sustainable urbanization, renewable energy policy, the Belt and Road Initiative’s impacts, and persistent environmental challenges. The identified gap concerns the underexplored influence of virtual arts on private sustainable investment in China and the broader intersection of virtual arts and sustainable finance.

The study employs annual Chinese data from 1985–2021 to examine how virtual arts market size (VAM) affects private investment in green projects (PIGP). All series are transformed to logarithms. The dependent variable is private investment in green projects (PIGP). Key explanatory variable is the virtual arts market size (VAM). Controls include renewable deployment (RD), economic size (GDP), financial development (FD), social inclusion (SI), and privatization (PR/PRI). Data sources include the China Statistical Yearbook (National Bureau of Statistics of China), China Data Center, China Statistical Database (CNKI), and China Information Network (CNInfo). A correlation matrix indicates no severe multicollinearity among variables. The empirical framework is an Autoregressive Distributed Lag (ARDL) model allowing mixed integration orders I(0)/I(1) and potential endogeneity. The analysis sequence is: (1) Augmented Dickey–Fuller (ADF) tests to assess stationarity; (2) bounds testing for cointegration; (3) estimation of short-run dynamics via an Error Correction Model (ECM) and long-run coefficients via ARDL; (4) diagnostic checks (LM test for misspecification, Ramsey RESET for functional form, ARCH for heteroscedasticity/serial correlation); (5) Granger causality tests to evaluate directionality between VAM and PIGP; (6) robustness checks using green electricity generation (from BP) as an alternative dependent variable, re-estimating short- and long-run effects for VAM and privatization. Reported equation forms include a log-linear specification for PIGP with VAM and controls, an ECM for short-run dynamics including the lagged error-correction term, and an ARDL form for long-run relationships. Stationarity results show some variables stationary at levels and others after first differencing, supporting ARDL use. Bounds testing supports a long-run cointegrating relationship.

• Virtual arts market expansion: A 1% increase in VAM is associated with approximately a 0.46% short-term increase and a 0.38% long-term increase in private sustainable investment (PIGP) in China. Long-run ARDL coefficient for Ln(VAM) ≈ 0.384 (p ≈ 0.028); short-run ECM coefficient for D(Ln(VAM)) ≈ 0.466 (p ≈ 0.002). - Social inclusion (SI): Short-run ≈ 0.26% increase in PIGP per 1% SI increase; long-run coefficient ≈ 0.439 (p ≈ 0.001), indicating sustained positive effects. - Financial development (FD): Positive and significant effects in both the short and long run; long-run coefficient ≈ 0.219 (p ≈ 0.025). - Economic size (GDP): Short-run ≈ 0.05% and long-run ≈ 0.07% increases in PIGP per 1% GDP increase; long-run coefficient ≈ 0.074 (p ≈ 0.007). - Renewable deployment (RD): Positive effects; long-run coefficient ≈ 0.392 (p ≈ 0.004). - Privatization (PR/PRI): Short-run ≈ 0.35% and long-run ≈ 0.23% increases in PIGP per 1% PR increase; long-run coefficient ≈ 0.239 (p ≈ 0.017). - Error-correction term: ECM(-1) ≈ −0.662 (p ≈ 0.000) indicates meaningful adjustment toward long-run equilibrium. - Diagnostics: LM p ≈ 0.633; Ramsey RESET p ≈ 0.004; ARCH p ≈ 0.944, reported as supporting model reliability. - Granger causality: Evidence of bi-directional causality between VAM and PIGP (F ≈ 9.747, p ≈ 0.054 for VAM→PIGP; F ≈ 8.923, p ≈ 0.001 for PIGP→VAM). - Robustness: Using green electricity generation as the dependent variable yields consistent direction and significance: long-run Ln(VAM) ≈ 0.423 (p ≈ 0.023), Ln(PR) ≈ 0.215 (p ≈ 0.011); short-run D(Ln(VAM)) ≈ 0.296 (p ≈ 0.001), D(Ln(PR)) ≈ 0.194 (p ≈ 0.053).

Findings directly address the research question by demonstrating that growth in the virtual arts market is linked to higher private sustainable investment in both the short and long run. This aligns with the proposed transmission channels: virtual arts expand visibility of sustainability opportunities, convey persuasive and informational content through immersive experiences, shape pro-sustainability investor attitudes, and create networking effects that connect investors with projects. The positive roles of social inclusion, financial development, GDP, renewable deployment, and privatization further contextualize the enabling environment required for private capital to flow into sustainable initiatives. The bidirectional Granger results suggest feedback between sustainable investment activity and the virtual arts market, implying that as green investment expands, it may also stimulate virtual arts content and platforms related to sustainability. Overall, the results are relevant for sustainable finance and cultural-technology policy, suggesting that virtual arts can be leveraged as part of broader strategies to mobilize private capital for sustainability in China.

The study contributes empirical evidence that expansion of the virtual arts market correlates with increased private sustainable investment in China, with elasticities of about 0.46% in the short term and 0.38% in the long term for a 1% rise in VAM. It identifies complementary drivers—social inclusion, financial development, GDP growth, renewable deployment, and privatization—that also enhance private green investment. Policy recommendations include: integrating sustainability education across curricula; establishing digital platforms and marketplaces for sustainable virtual arts; leveraging big data for investor insights; developing efficient green financing markets and instruments (e.g., green bonds, impact investing vehicles) tailored to the virtual arts sector; and fostering cross-sector collaborations among virtual arts organizations, educational institutions, technology firms, and financial intermediaries. Future research directions proposed include examining electronic exhibitions and sustainable tourism as channels influencing private investors, and conducting survey-based studies with experts in sustainable virtual arts and green investments to deepen micro-level behavioral insights.

The analysis focuses on China and uses aggregate annual time-series data from 1985–2021, which may limit generalizability beyond this context. The study does not directly examine channels such as electronic exhibitions or sustainable tourism, and it lacks survey-based evidence from investors or experts; these are identified as avenues for future research.