Against the backdrop of the construction of China's five major urban clusters, this article utilizes data on the establishment of branch offices in different locations by listed companies to analyze the industrial shift in the Guangdong-Hong Kong-Macao Greater Bay Area, investment interaction in the Yangtze River Delta, the capital effect in the Beijing-Tianjin-Hebei region, the gradient absorption in the Central Yangtze River region, and the cross-regional absorption in the Chengdu-Chongqing dual-city economic circle. The findings provide significant insights into the economic radiation and siphoning phenomena in the construction of urban clusters in China.

Agricultural subsidies are crucial for stabilizing supply and price in fresh produce wholesale markets. In particular, fresh produce suffers the risk of yield uncertainty in the upstream origin market, which may cause supply and price fluctuations in the downstream wholesale market. By developing a game-theoretical framework, this paper analyzes the effectiveness of the transaction fee subsidy in wholesale markets under yield uncertainty. Our result shows that the subsidy policy can increase supply and reduce prices but may aggravate price fluctuations by inducing a larger supply scale in the wholesale market. The numerical analysis indicates that the subsidy policy performs a low efficiency in improving consumer surplus but high efficiency in social welfare.

"People's Forum · Academic Frontier" Yao Shujie: Core Characteristics and Historical Opportunities of China's Sustained Economic Development【Abstract】Over the past 40 years of China's reform and opening-up, despite experiencing multiple global and regional economic crises and significant historical events, it has managed to maintain continuous economic growth. It has transformed from a poor a...

We consider a budget hotel chain's revenue management problem of deciding how to dynamically allocate capacity to multiple segments of customers. Our work solves an industrial-sized problem faced by practitioners, with the reality of implementation motivating us to develop a tailored reinforcement learning approach. Our approach proceeds in two steps. First, a recommended average discount is computed with a reinforcement learning algorithm. Then, the recommended average discount is turned into a capacity allocation through a linear program. This approach overcomes the challenges of characterizing demand and estimating cancellations, and it facilitates hotel managers' acceptance of the revenue management system. We implement this approach in the hotel chain in a pilot study and assess its effectiveness using synthetic control methods. Our approach improves the key operational performance measure—revenue per available room—by 11.80%.