Solar power, as an important part of renewable energy, has become one of the main choices for countries around the world in their energy strategic layout due to its cleanliness, renewability, and distributed attributes. In the context of the booming photovoltaic industry, China has emerged a large number of excellent photovoltaic companies, driving the whole industry to reduce costs and increase efficiency, making many contributions to the grid parity of photovoltaic power generation. In the development lifecycle of the photovoltaic industry, various companies choose different competitive strategies to deal with industry cyclical changes and external uncertainty based on their core competitiveness and market opportunities. Vertical integration is one of the strategic paths chosen by many photovoltaic companies. Therefore, it is an important issue to explore the impact of vertical integration on the development of Chinese photovoltaic companies.Based on the data of China's A-share listed photovoltaic companies from 2018 to 2022, this paper uses panel fixed effect model to empirically test the impact of vertical integration on corporate valuation, explores its influencing mechanism, and further analyzes the moderating effect of enterprise heterogeneity factors. The research in this paper shows that: (1) under other conditions unchanged, vertical integration significantly improves the valuation level of enterprises, and this positive impact will not change with the measurement method of enterprise valuation level. This is because the higher the vertical integration degree of enterprises, the stronger their ability to respond to external uncertainty. The more enterprises can obtain capital market preferences, the higher the enterprise valuation will be. This also means that the higher the vertical integration degree of photovoltaic enterprises, the higher their market share is, and they are more able to avoid the impact of external uncertainty, thus obtaining a higher valuation level in the secondary market. (2) The intermediary effect test shows that the channel for vertical integration of photovoltaic enterprises to affect enterprise valuation levels is to increase their market share. (3) Further heterogeneity analysis shows that enterprise profitability and enterprise size positively regulate the impact of vertical integration on enterprise valuation, while enterprise management shareholding ratio and enterprise operating cost ratio will weaken the positive promotion effect of vertical integration. The research conclusions of this paper provide micro-empirical evidence for how photovoltaic companies can improve their enterprise valuation, and also provide some management references for other unlisted companies in the same industry. Keywords: Photovoltaic enterprises; Vertical integration; Corporate valuation; Fixed effect model

With the continuous development of the Chinese capital market over the past thirty years, the securities analyst industry has experienced a process of transformation from a reckless period to a golden time. One of the most important signals is that securities analysts are increasingly conducting research report providing long-term earnings forecasts for the company. However, current research on analysts is limited to their short-term forecasting behavior, and there is little on analysts' long-term earnings forecasts. Therefore, this article takes the research on analysts' long-term forecast reports issued by analysts on A-share listed companies, and conducts an empirical study on the analysts' forecasts accuracy and its influencing factors. First, the author combed the research literature related to analyst forecasts and selected variables from three dimensions, including company characteristics (financial indicators and non-financial indicators), analyst characteristics and affiliated institution characteristics; secondly, considering the high-dimensionality of the influencing factors, this paper uses the method of combining machine learning and traditional regression to conduct empirical research; finally, the research tested the heterogeneity of influencing factors from two perspectives, including time and industry.The results of this article show that the long-term profit forecasts of analysts in China have advantages over traditional statistical models. More than 60% of analysts provide profit forecasts that are better than statistical models. Afterwards, when examining the factors that affected the accuracy of analysts’ forecasts, it found that although analyst and institutional characteristics affected analysts’ predictions to a certain extent, company characteristics are the most important variables among them all. As the time goes by, the influence of non-financial factors on forecast accuracy gradually decreasing, but analyst characteristics continue to strengthen. In addition, cyclical industries are more difficult to predict than companies in non-cyclical industries, and the difficulty of prediction will not be reduced with the analyst efforts. This research can help analysts optimizing their forecasting behavior and prompts investors to understand analysts' reports more deeply, which makes them using analyst forecast data to make investment decisions in a rationally ways, and it can also help to promote the securities pricing efficiency and development of Chinese capital market.

Over the past two decades, propelled by urbanization, domestic investment and construction of commercial complexes have rapidly accelerated. This has led to a dramatic expansion of these complexes with swift operational iterations and related data changes. The impact of changing domestic and international financial policies, along with political environments, has seen e-commerce gradually seize the middle and low-end retail markets. Additionally, the global spread of the COVID-19 pandemic in the last three years has resulted in a substantial slowdown in domestic economic growth. Despite this, there is still developmental potential, prompting unprecedented attention to corporate investment and commercial operations.However, acquiring basic operational data in commerce is challenging, with inconsistent measurement standards among enterprises, hindering accurate and systematic judgments of operational performance. The factors influencing the operational performance of commercial complexes in China remain inadequately researched.At this juncture, the scientific measurement of commercial complex operational performance is crucial for their healthy development. This study explores the relationship between enterprise investment behavior, operational management behavior, and commercial complex operational performance. It measures influencing factors using resource configuration theory to control uncontrollable environmental factors, such as urban hierarchy, surrounding population, per capita GDP, surrounding commercial inventory and increment, and location planning support. Dynamic capability theory is then applied to investigate the impact of variables like the number of leases, area, brands, lease cost income, marketing activity types, activity funds, and activity time on operational performance. A model is established to analyze operational performance, contrasting significant variables before and after the pandemic, identifying factors affecting operational performance in early-stage investment and later-stage management strategies. Post-pandemic adjustments are suggested to adapt to changing environmental conditions.In the empirical research section, this paper validates the theoretical model through data analysis, studying the volatility of operational performance based on factors influencing commercial complexes. Integrating theoretical backgrounds, it analyzes investment and management strategies for enterprises in different situations, emphasizing key indicators. This provides enterprises with better choices for future projects and empowers commercial complex managers for effective future management, enhancing operational performance. The study offers a theoretical basis and guidance for promoting the healthy development of the market.

On January 30, 2019, the China Securities Regulatory Commission issued the Implementation Opinions on the Establishment of the Science and Technology Innovation Board on the Shanghai Stock Exchange and the Pilot Registration-based System, announcing the establishment of a new Science and Technology Innovation Board(STAR). The STAR Market is an important measure in China's capital market reform, aiming to promote the transformation of China's economy from a stage of rapid growth to a stage of high-quality development. The companies listed on the Science and Technology Innovation Board are mainly scientific and technological innovation enterprises that are at the forefront of the world's science and technology, the main battlefield of the economy, and the major needs of the country, in line with the national strategy, breaking through key core technologies, and with high market recognition. Since its launch on July 22, 2019, to May, 15, 2023, there are 522 companies have been listed on the STAR Market, with a total market capitalization of more than RMB 7 trillion. The successful listing of these enterprises will provide strong support for the deep integration of China's high-tech industries and strategic emerging industries.This paper analyzes the influencing factors of IPO listing pricing on the STAR Market, and studies 1478 companies listed on the three listing platforms of the STAR Market, ChiNext and Hong Kong stocks. Through descriptive statistical analysis and multivariate regression model, the influencing factors of the 1st day and the 20th day were empirically studied. The results of the study will provide a pricing reference for ii listed companies in the future, and provide a reference for policymakers to meet the expectations of the new regulatory reforms. Through analysis of multiple factors includes but not limited as the NR,IPE, LEAD, ISCA, T10, AOL, BC, STL, RDI, CAGR, DTOR, these influencing factors have an important impact on the IPO of the STAR Market.

With the increasing aging population in China, the public's emphasis on health has been on the rise. Many innovative pharmaceutical companies have undertaken multiple rounds of financing, with some going public through IPOs. As a high-tech industry, it is essential to study the relationship between the level of corporate publicity and the financing process.This study collected information on the number of promotional articles, timing, and platforms of dozens of pharmaceutical companies that have already gone public through IPOs using Python. An analysis was conducted on the temporal variations of promotional articles for ten representative companies. It was found that the number of promotional articles experienced a significant increase in the month of IPO or the month before, and remained relatively high even after the IPO. Furthermore, the Pearson correlation coefficient method was used to analyze the correlation between the number of promotional articles and various stages of financing. The study found a positive correlation between the daily average number of promotional articles before IPO and the final financing amount. Additionally, a strong positive correlation was observed between the daily average number of promotional articles from 7 days before IPO to IPO day and the turnover rate on IPO day. Grey correlation analysis was also employed to analyze the impact of publicity on the financing amount of each ii financing round, revealing that the financing round and the Shanghai Composite Index had a significant influence. Finally, a multiple regression analysis was conducted to examine the relationship between the pre-IPO financing scale, IPO-day trading amount, and the level of corporate publicity. The regression results indicated that the pre-IPO financing scale was mainly influenced by the number of promotional articles in the 7 days preceding IPO, particularly for pharmaceutical companies listed on the A-share market. Moreover, a negative correlation was observed between the financing round and the financing amount, particularly among companies that experienced a decline in share price on the IPO day. However, the study found a weak association between the IPO-day trading amount and the level of corporate publicity, primarily observed among pharmaceutical companies listed on the A-share market.

This paper analyzes China's transformative changes over the past four decades through a microeconomic lens focused on enterprises. Market-oriented non-state-owned enterprises have emerged as a pivotal force driving China's economic development within this context. The article investigates the determinants of their development. Notably, more than half of market-oriented non-state-owned enterprises have entered the inheritance stage, necessitating the exploration of novel attributes for sustained growth.The study's research scope is defined across four dimensions, with a specific focus on approximately 4,000 market-oriented non-state-owned enterprises. It investigates the driving factors behind sustained performance growth at various stages of these enterprises, emphasizing five variables: "partnership governance, entrepreneurial spirit, development strategy, incentive mechanisms, and innovation capability." Employing a combination of "typical case studies" and "group validation" methods, the research examines the factors influencing sustained growth in these enterprises and their interrelationships. The goal is to construct a model for enterprise succession and development, ultimately offering recommendations to foster sustained growth. The research paper is structured into an introduction, literature review and theoretical foundation, typical case studies, empirical research on a group, and a conclusion. ii Key findings include: Partnership governance positively impacts partners' entrepreneurial spirit, promoting sustained performance growth. Trajectory-oriented development strategies, effective incentive mechanisms, and leading innovation capabilities have a positive moderating effect on entrepreneurial spirit, fostering sustained performance growth. During the innovation development phase, partnership governance significantly influences entrepreneurial spirit with a noteworthy environmental moderation effect. The paper recommends implementing a "Dual-Factor Improvement Model" that enhances both partnership governance systems and the selection and functioning mechanisms of entrepreneurial spirit partners. This approach aims to boost partners' entrepreneurial spirit and facilitate high-quality succession in market-oriented non-state-owned enterprises，，ultimately achieving sustained high-quality growth. In conclusion, this research contributes to a deeper understanding of sustained performance growth in enterprises. It offers valuable insights for the succession and development of market-oriented non-state-owned enterprises and innovation-driven entrepreneurship. This research holds significant value in advancing sustained high-quality development among market-oriented non-state-owned enterprises in China, optimizing resource allocation, and nurturing talented individuals.