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Artificial intelligence (AI) is currently one of the most prominent fields in the technology industry, with China and the US being two global centers for AI research and development. However, the two countries differ in their development levels of the AI industry. In particular, the emergence of ChatGPT in 2022 has sparked extensive discussions regarding the capabilities and competitiveness of Chinese AI companies. This study analyzes over 120 000 AI invention patents approved in the past five years in both China and the US. Firstly, it constructs a multidimensional index based on AI patent features to identify the top 10 AI companies in both countries. Further, the analysis reveals significant differences in patent technology and research networks between these two groups. Chinese leading companies have notably fewer AI patents, less patent citation, and lower conversion rates. The patents of leading Chinese companies are mainly concentrated on application-level technologies such as image recognition and speech recognition, and have not yet formed distinctive AI technology clusters. In contrast, American leading companies have generated more influential AI patents, particularly forming multiple technology clusters in the foundational and core technology layers of the AI industry. In terms of academic research, Chinese leading companies primarily collaborate with domestic research institutions, while American leading companies demonstrate stronger collaboration with Chinese institutions, as well as among domestic companies. This comparative analysis reveals prominent differences in technological capabilities and collaboration strategies of leading AI companies in China and in the US, and provides managerial insights and three policy suggestions for better developing China's AI industry. [ABSTRACT FROM AUTHOR]

To measure the systemic risk contribution of the financial institutes in China more accurately and to avoid financial risk events, a new method named CoES model is proposed based on the mean value of tail loss. Compared to the traditional CoVaR model, this method pays more attention to the mean value of tail loss than the expected loss on one single quantile, which could provide more accurate information for the supervision when capturing the systemic risk of financial system. The new method is utilized to measure the systemic risk contributions of 21 financial institutions in China from 2007 to 2016. The empirical results show that: 1) the CoVaR model may underestimate the systemic risk of financial institutes; 2) the banking industry brings the largest systemic risk contribution to the whole financial system, followed by insurance, real estate and diversified financial industry; 3) among banking industry, the systemic risk contributions of Industrial and Commercial Bank of China and Bank of China are the largest, which should be the key regulatory objects; 4) compared with the banking and real estate industry, the insurance industry and the diversified financial industry own higher VaR value and their systemic risk contributions are relatively lower, so the regulators could pay more attention to their own risk management. [ABSTRACT FROM AUTHOR]

Business intelligence systems has become an important tool to solve complex problems and improve management efficiency for retailers. Based on the demand for practices and existed information platform within dominated information provider, we design and propose a novel framework of the big data and business intelligence system, i.e.. HDBI system, which can integrate with other more than 20 retail information systems and apply to cross-regional retailers with multi-formats. Further, we explore and discuss some design methods and key techniques. The practical application shows the effectiveness and advancements of HDBI. [ABSTRACT FROM AUTHOR]

One of the most difficult problems in operation management for retailers is the circulation safety management of limited shelf life commodities. Based on the circulation characteristics and management difficulties of limited shelf life commodities, we propose a brand new circulation safety management framework, entitled "shelf-life code bar traceability system, SCBTS", which could integrate other systems seamlessly to achieve automation management in production, circulation and sales. Meanwhile, we discuss the detailed process design, integrated solutions, and application value. The practical application shows that SCBTS can improve the efficiency of management for commodity with limited shelf life. [ABSTRACT FROM AUTHOR]

The estimation of China's future food grains demand is an important reference for designing food security measures. In recent years, the urbanization level has been accelerated, the aging problem has been serious and the universal two-child policy has been just implemented, so China has been in a critical period of demographic transition. Furthermore, the changes of population size and structure have a direct impact on food grains demand. Based on China's recommended nutrient intake, considering the age structure, sex structure and urban and rural structure of population, the paper uses the standard person consumption coefficient method to estimate the food grains demand (which includes grain ration and feed grain) for 2020-2050 years in three fertility scenarios, which are two-child fertility policy for couples where either the husband or the wife is from a single-child family, universal two-child policy and the birth limit be canceled policy. The results show that: under the universal two-child policy, China's food grains demand will peak at 2030, about 392.631 million tons, which is 100.610 million tons lower than that calculated with the per capital method; with the rise of urbanization rate, the food grains will increase about 4.067 million tons, 11.425 million tons and 15.538 million tons in 2020, 2030 and 2050 respectively; the demographic transition for fertility policy adjustment is not the main impacting factor of China's food security during 2020 to 2050. It is suggested that effective measures should be taken to guide and encourage bearing and rearing better children, to cancel the birth limit in a proper time, and to minimize the loss and waste of food grains. [ABSTRACT FROM AUTHOR]

Structural changes often occur in air passengers due to some external factors such as airport expansion, policy orientation and economic development; model uncertainty is a common long-standing issue in forecasting. To address these issues, a novel time-varying Jackknife model averaging method (TVJMA) (Sun et al, 2020, 2012) is employed to predict air passengers of the Top 5 airports in China. Based on nonparametric estimation, the optimal time-varying weights for various candidate models with time-varying parameters in candidate models are obtained by minimizing the local Jackknife criterion at every time point t. TVJMA method allows the weights and parameters to change over time. Empirical results show that the TVJMA method used in this paper is significantly superior to other benchmark models, including Hansen and Racine's (2012) Jackknife model averaging method (JMA), autoregression model (AR), autoregression integrated moving average model (ARIMA), seasonal autoregression integrated moving average model (SARIMA), and time-varying parameter model (TVP). Furthermore, the predictive effect of TVJMA is robust to different test sets and prediction steps. Overall, TVJMA method effectively reduces the predictive risk caused by structural changes and model uncertainty, and thus produces accurate and stable forecasts of air passengers. [ABSTRACT FROM AUTHOR]

Based on the traditional two-sided market theory and the characteristics of P2P lending platforms, this paper proposes a two-stage game model to analyse different business models, especially profit models of P2P lending platforms. With the purpose of showing the continuous operating condition and developing direction of P2P lending platforms under the financial environment in China, this paper takes China's new policies about P2P into consideration, takes account of impact of policy and finds the following results: 1) under the scenario in which P2P platform charges "subscription fee + transaction fee" or "subscription fee only", network externalities reduces the P2P platforms' profit when lenders are multihoming; 2) adopting the profit model of "subscription fee + transaction fee" makes a higher profit than the profit model of "subscription fee only"; 3) the prohibition in existing policies of P2P lending platforms on principal guaranteed model will protect the interests of lenders. Finally, this paper puts forward policy suggestions of the P2P lending platforms in China. [ABSTRACT FROM AUTHOR]

This paper considers that business model innovation is an iterative design process of the adjustments. A comprehensive feedback analysis model named PNMP-CET@I is proposed based on the iceberg theory and CET@I methodology for business model studies. PNMP-CET@I model takes into account several kinds of environmental factors and then optimizes the existing business model via an integrated analysis. The integrated analysis results show that the business model of Ant Finance is superior to the traditional financial business model. Some new ideas and management inspiration to the development of internet financial enterprises and traditional financial enterprises are presented. [ABSTRACT FROM AUTHOR]