The music industry ＆ its consumers： A potential divorce through technology and shifting market linkages？

A large market exists of online users who desire online video and music content. However, recent developments have shown that some industries, such as music and videos are not fully utilising the market benefits that disruptive technologies can bring to organisations despite the change of value drivers. According to Christensen et al （2004）, and based on RPV theory, organisations may decide not to pursue disruptive innovative ideas for a variety of reasons, such as their values are set in another direction, processes do not support the new technology and resources may become under-utilised or even obsolete. Trying to pursue partly aggressive strategies, partly defence or avoidance strategies, it is suggested that the music industry has missed to reengineer its business so far. At the same time, music consumers have found various peer-to-peer models to execute their own avoidance strategies, i.e., avoiding to buy music but to share it. Various consumption platforms for music, such as, pandora, hulu or spotify, emerged, which themselves show significant innovative power. As scholars＇ research tested, innovation has two beams, technology and market linkages. While the technological part is inevitably developing further, the music industry erects legal barriers to bloc those sites by applying the presently unclear DRM, since the new ways of music consumption threaten their established ways of content distribution. At the same time, barriers are placed that those consumers being online specialists find ways to circumvent them. The proposition is that by the salient marketing concept of CRM such behaviour increases the pressure on incumbents since risking market linkages with their customers. This paper will contrast technology and market linkages, discussing how online innovations may alter the status quo of the music industry, especially its record business. Research provides evidence that technological implications are supporting a sustainable shift of consumers＇ behaviour and the ways, by which consumers are able to overcome the legal and technological barriers for accessing P2P sites despite industrial prevention. It is suggested that there is further significance this paper addresses, since what affects the music industry today, will likely have an impact on the movie, games, software and other industries in the near future： Disruption of existing resources, processes and values and threatening market linkages by redefined ways of content distribution.

Does More Trading Lead to Better Market Linkage?Evidence from the Commodity Futures Markets

In this study,we use eight pairs of commodity futures data to investigate the impact of the recently launched nighttime trading session by Chinese futures exchanges.We conduct a thorough empirical analysis on the cross-market information transmission mechanisms between China and the U.S.We apply various econometric analyses including the co-integration analysis,the forecast error variance decomposition analysis,and the volatility spillover analysis with a bivariate GARCH model.Findings in this study indicate that,after the launching of nighttime-trading hours in China,the price discovery function of the Chinese futures market is noticeably improved,and that the Chinese market began to dominate the U.S.market in the bidirectional volatility spillover process.Thus,the introduction of the nighttime-trading hours appears to be an effective step toward China’s long-term goal of establishing pricing power in key commodities on the global financial market.

Research on the Dynamic Volatility Relationship between Chinese and U.S. Stock Markets Based on the DCC-GARCH Model under the Background of the COVID-19 Pandemic

This study utilizes the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model to investigate the dynamic relationship between Chinese and U.S. stock markets amid the COVID-19 pandemic. Initially, a univariate GARCH model is developed to derive residual sequences, which are then used to estimate the DCC model parameters. The research reveals a significant rise in the interconnection between the Chinese and U.S. stock markets during the pandemic. The S&P 500 index displayed higher sensitivity and greater volatility in response to the pandemic, whereas the CSI 300 index showed superior resilience and stability. Analysis and model estimation suggest that the market’s dependence on historical data has intensified and its sensitivity to recent shocks has heightened. Predictions from the model indicate increased market volatility during the pandemic. While the model is proficient in capturing market trends, there remains potential for enhancing the accuracy of specific volatility predictions. The study proposes recommendations for policymakers and investors, highlighting the importance of improved cooperation in international financial market regulation and investor education.