In social commerce, a platform that integrates social and transactional functions, the information cocoon has been identified as an impactful problem affected by personal and technical factors and has attracted the attention of many researchers. Therefore, this paper will conduct a systematic literature review to explore the causes of information cocoons, their various effects, and proposed measures, providing a comprehensive framework for scholars and business leaders to understand information cocoons. Specifically, the information cocoon comes from confirmation bias, in which people only pursue information consistent with their cognition, and personalised recommendation systems will positively mediate this causal relationship. Besides, the formation of information cocoons will have three effects, which are consumption cocoons, user fatigue, and group polarisation. To mitigate these negative effects, scholars believe that potential solutions are to improve individuals' information filtering ability and optimise personalised recommendation algorithms. All in all, this paper analyses the whole process of 'causes-consequences-interventions' of information cocoons in social commerce for the first time, providing comprehensive theoretical guidance for the economic development of social platforms.

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Against the backdrop of carbon peaking and carbon neutrality goals, closed-loop supply chains serve as a critical pathway to realize a circular economy. Nevertheless, the collaborative operation mechanism between eco-friendly material application and recycling technologies remains unclear. This paper conducts an analysis taking Apple Inc. as the research case. Combined with green design theory, the study finds that the adoption of materials such as recycled aluminum streamlines processes at the source, forms positive feedback with disassembly technologies, and achieves the organic integration of carbon emission reduction and supply chain resilience improvement. The research verifies that the integrated operation of the two is constrained by high costs and technical adaptability issues, yet it can balance economic and environmental benefits. The findings provide practical references for the green transformation and upgrading of manufacturing industries.

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This paper takes listed companies in China's new energy vehicle industry chain as the research subject and constructs an experimental model for predicting industry capital market prosperity. Compared to existing research mainly focusing on predicting the direction of individual stock prices, identifying fluctuations in clean energy assets, and optimizing deep learning models, research on the overall capital market scenario of the new energy vehicle industry chain is still relatively limited. Research is conducted on representative companies in the three sub industries of vehicle, battery, and lithium resources to establish an equal weight index for the new energy vehicle industry. The industry index returns over the next 20 trading days are divided into three categories: Growth, Neutral, and Decline. The experiment used yfinance to obtain daily trading data from January 2018 to April 2026. In terms of models, this article compares the predictive performance of Majority Baseline, Logistic Regression, Random Forest, and LSTM. The results showed that logistic regression performed the best under the current feature system, indicating that there is a certain degree of predictability in changes in industry prosperity, but complex models were not significantly better than simple interpretable models.

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Young investors can use risk management strategies to build long-term wealth in the stock market. Compared to previous age, young investors have more opportunities to enter financial markets today, such as mobile trading apps, online brokerage platforms, and social media, which all make investing more accessible. However, the younger age of access can create risks because of emotional trading, overconfidence, fear of missing out, and poor decision-making. This article argues that young investors should not treat the stock market as a shortcut to wealth, but as a long-term financial planning tool. Key strategies for youth to help reduce unnecessary losses, including financial literacy, understanding personal risk tolerance, diversification, long-term investing, and disciplined investing habits. While also explains that young investors may have more time to recover from market downturns, and age alone does not justify risk-taking. Overall, successful investing requires knowledge, patience, emotional control, and a balanced approach to risk. This paper provides suggestions for young investors' investment strategies.

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