With the continued growth of the tourism industry, increasing attention has been devoted in recent years to how tourist cities should formulate appropriate tourism policies. As a well-known cruise destination in Alaska, Juneau faces the critical challenge of balancing the economic growth generated by tourism with the visitor carrying capacity of the local area, which has become a key concern for local policymakers. This paper develops a GDP growth accounting model based on data on tourism consumption, tax revenue, and government investment. By formulating the maximization of tourism-driven GDP growth as the objective function, the model identifies the optimal number of visitors and the corresponding tax policy for the region, thereby providing concrete policy recommendations for local government decision-making. A sensitivity analysis with respect to the visitor-capacity limit further shows that relaxing the maximum visitor capacity increases both the feasible visitor scale and the upper bound of GDP gains, while the optimal tax policy remains relatively stable in the low-capacity region. These findings provide a quantitative basis for sustainable cruise-tourism management in Juneau and other small port destinations with similar structural characteristics.

Show more

With socioeconomic development and population growth, demand rises steadily. Against the backdrop of global collaborative and intelligent supply chain development, issues like frequent bullwhip effect, low automated operation efficiency and scattered warehouse goods restrict overall supply chain performance and corporate core competitiveness, calling for targeted optimization. This study focuses on the field of supply chain management, aiming to mitigate the bullwhip effect, improve the efficiency of automated operations and enhance the density of goods storage. This study adopts the literature research method and case analysis method to verify the feasibility of optimization strategies. The study shows that promoting multi-enterprise cooperation can mitigate the bullwhip effect and reduce manual workload; constructing a three-dimensional best-selling index model with the entropy method to formulate storage location scheduling can enhance storage density. This study can provide references for supply chain management practices and help enterprises boost their core competitiveness in the supply chain.

Show more

This study examines whether companies can manage market expectations by voluntarily making substantial documents on Artificial Intelligence (AI) governance public. Using Meta’s July 18, 2023 release of Llama 2 and its accompanying governance materials (including the Responsible Use Guide and System Card) as the focal event, the study applies an event-study framework and a GARCH(1,1) model to examine abnormal returns and volatility dynamics., conducted an event study to estimate abnormal returns, using the Generalized Autoregressive Conditional Heteroskedasticity (garch) model (1,1), using the volatility comparison and the pseudo event. Variation in the variance of test conditions. The results show a delay in market assimilation. On launch day, the outstanding return is low, but the following trading day shows a significant outstanding return (+ 1.24%). In addition, post-disclosure specific volatility decreased by approximately 39.7% in one week, with a significantly negative GARCH event coefficient, which reduced perceived causal risk. Overall, proactive and detailed disclosure of AI compliance serves as a reliable signal to stabilize prices and reduce risk premiums. This study provides important insights into how positive disclosure of the AI regulatory framework affects market dynamics, especially in high-tech sectors. Focus on Meta's July 18, 2023 disclosure and review subsequent market responses, including exceptional returns and low volatility.

Show more

In the post-financial crisis era, global trade protectionism rises, and the cost of domestic production factors increases. The traditional operation and management mode of "OEM + agency" of small and medium-sized foreign trade enterprises in China can no longer adapt to the new market environment. These enterprises urgently need to transform and upgrade. This study takes Hangzhou Hexun Industrial Co., Ltd. as the research sample. It uses literature research method, PEST macro environment analysis method, SWOT matrix analysis method and case analysis method. The study sorts out four core problems of the traditional operation and management mode of small and medium-sized foreign trade enterprises in China. It analyzes the macro environment and industrial characteristics of China's foreign trade industry in the new trade environment. Combined with the internal resources and capabilities of Hangzhou Hexun, the study puts forward an innovative operation and management model for small and medium-sized foreign trade enterprises. This model takes "customer demand as the core and six dimensions as support". In addition, the study discusses the implementation path, applicable conditions and industry universality of the model. It provides theoretical reference and practical path for small and medium-sized foreign trade enterprises in China to break through development bottlenecks and improve core competitiveness.

Show more