With the increasing executive-employee pay disparity in recent years, research on executive compensation has grown exponentially. This paper reviews all articles on executive compensation published between 2000 and 2022 in the six accounting journals with the highest impact index in South Korea and China (five journals in China), and evaluates and analyzes the research in both countries. The analysis results are organized as follows: First, the research on executive compensation started earlier in South Korea than in China; second, the focus of the research on executive compensation differs between the two countries; then, the study on the determinants of executive compensation varies between the two countries; forth, the proxies for firm performance are mostly the same in the two countries; and finally, most of the studies in the two countries assert that executive compensation has a positive impact on firm performance. Based on the above research, this paper confirms that the agency theory, which has been widely validated in Western countries, is also valid in Asian countries. In addition, it provides an essential reference for future research on executive compensation in Asian countries.

This paper improves the expected return variable and the corresponding trend factor documented by Han, Zhou, and Zhu (2016) and reveals the incremental predictability of this novel expected return measure on stock returns in the Chinese stock market. Portfolio analyses and firm-level cross-sectional regressions indicate a significantly positive relation between the improved expected return and future returns. These results are robust to the short-, intermediate-, and long-term price trends and other derived expected returns. Our improved trend factor also outperforms all trend factors constructed by other expected returns. Additionally, we observe that lottery demand, capital states, return synchronicity, investor sentiment and information uncertainty can help explain the superior performance of the improved expected return measure in the Chinese stock market.

This paper presents an innovative Comprehensive Growth Dynamic Model (CGDM). CGDM is designed to simulate the temporal evolution of an event, incorporating economic and social factors. CGDM is a regression of logistic regression, power law regression, and Gaussian perturbation term. CGDM is comprised of logistic regression, power law regression, and Gaussian perturbation term. CGDM can effectively forecast the temporal evolution of an event, incorporating economic and social factors. The illicit trade in wildlife has a deleterious impact on the ecological environment. In this paper, we employ CGDM to forecast the trajectory of illegal wildlife trade from 2024 to 2034 in China. The mean square error is utilized as the loss function. The model illuminates the future trajectory of illegal wildlife trade, with a minimum point occurring in 2027 and a maximum point occurring in 2029. The stability of contemporary society can be inferred. CGDM's robust and generalizable nature is also evident.

This paper improves the expected return variable and the corresponding trend factor documented by Han, Zhou, and Zhu (2016) and reveals the incremental predictability of this novel expected return measure on stock returns in the Chinese stock market. Portfolio analyses and ffrm-level cross-sectional regressions indicate a signiffcantly positive relation between the improved expected return and future returns. These results are robust to the short-, intermediate-, and long-term price trends and other derived expected returns. Our improved trend factor also outperforms all trend factors constructed by other expected returns. Additionally, we observe that lottery demand, capital states, return synchronicity, investor sentiment and information uncertainty can help explain the superior performance of the improved expected return measure in the Chinese stock market.

This article offers an in-depth exploration of the significance of research philosophy in the realm of management studies. It conducts a critical review of research philosophy, encompassing ontological, epistemological, and axiological dimensions, shedding light on their implications for management research. Traditional ontological perspectives, including realism, idealism, and pragmatism, are analyzed along with their influence on the field. Moreover, contemporary ontological debates are discussed, emphasizing their relevance to management research. The article also delves into the role of epistemology in shaping research methodologies, examining positivism, interpretivism, and critical realism as prominent frameworks. Emerging epistemological trends are explored, highlighting their impact on management research. Throughout the review, novel insights are presented, providing a foundation for future theoretical and empirical development. Researchers are encouraged to embrace ethical pragmatism, dynamic reflexivity, and epistemological pluralism, which can lead to more comprehensive and adaptable theories. The article concludes by calling for continued exploration and innovation in research philosophy to shape the future of management research. It emphasizes the dynamic nature of research philosophy and its potential to drive positive change in the management field. [译]本文深入探讨了研究哲学在管理研究领域中的重要性。文章对研究哲学进行了批判性综述，涵盖了本体论、认识论和价值论三个维度，并揭示了它们对管理研究的启示。文章分析了包括实在论、唯心主义和实用主义在内的传统本体论观点及其对该领域的影响，并讨论了当代本体论辩论，强调了它们与管理研究的关联性。此外，文章还深入探讨了认识论在塑造研究方法论方面的作用，审视了实证主义、解释主义和批判实在论等突出框架。文章还探讨了新兴的认识论趋势，强调了它们对管理研究的影响。在综述过程中，文章提出了新颖的观点，为未来的理论和实证研究奠定了基础。文章鼓励研究者采纳伦理实用主义、动态反思性和认识论的多元主义，这有助于形成更全面和更具适应性的理论。文章最后呼吁继续探索和创新研究哲学，以塑造管理研究的未来。它强调了研究哲学的动态性质及其在管理领域推动积极变革的潜力。

This work explored the changes in production decision-making trends of Chinese steel enterprises under the influence of the carbon border adjustment mechanism. First, using evolutionary game theory, the interactive mechanism of complex production strategies among steel enterprises considering the carbon border adjustment mechanism was studied, including the impact of government subsidy coefficients, additional profits and carbon tax prices on enterprise decisionmaking.Second, the influence of key parameters on the dynamic evolutionary process was analysed. On this basis, the empirical simulation method was used to verify the game model and the main conclusions. Finally, the sensitivity analysis of the selected parameters was determined using Matlab software. The results showed that additional profits from green investment, government subsidy coefficients, input-output values and carbon tax prices had a higher impact on the evolution of enterprise production strategies. The results of this study provide a decision-making basis for the selection of future production methods for steel enterprises.

Under contemporary market conditions in China, the stock index has been volatile and highly reflect trends in the coronavirus pandemic, but rare scientific research has been conducted to model the nonlinear relations between the two variables. Added, on the advent that covid-related news in one time period impacts the stock market in another period, time delay can be an equally good predictor of the stock index but rarely investigated. This study utilizes high-frequency data from January 2020 to the first week of July 2022 to model the nonlinear relationship between the stock index, new covid cases and time delay under polynomial regression environment. The empirical results show that time delay and new covid cases, when modelled in a polynomial environment with optimal degree and delay, do present better representation (up to 16-fold) of the nonlinear relationship such predictors have with stock index for China. The representative delay model is used to project for up to 17 weeks for future trends in the stock index. From the findings, the prowess of the time delay polynomial regression is heavily dependent on instability in covid-related time trends and that researchers and decision-makers should consider modeling to cover for the unsteadiness in coronavirus cases.

Secular declines in U.S. Treasury yields are concentrated in three-day windows around FOMC announcement dates. Cumulative yield changes during these short windows explain the secular decline in yields. This factor contains essential information on excess bond returns and outperforms well-known proxies for interest rate trends in prediction regressions. We estimate a dynamic term structure model to explain these empirical facts. The model suggests that the secular declines in Treasury yields over the past three decades were primarily due to reductions in expected interest rates, mostly during the FOMC announcement windows.

The U.S. stock market has long been the most popular venue for both foreign companies and global investors. The recent cross-border regulation tensions between the U.S. and China, however, have exposed many U.S.-listed China Concepts Stocks (CCS) to substantial de-listing risks, forcing them to pursue dual listings on the Hong Kong Stock Exchange (HKEX). In this paper, we quantify the economic value of dual-listing, using the SEC’s adoption of the ffnal amendments implementing mandates of the Holding Foreign Companies Accountable Act (HFCAA) on December 2, 2021 as a natural experiment. We estimate that CCS with pre-shock dual-listing status on average have 14.88% higher returns, or USD 8 billion in market capitalization, than their peers listed only on the U.S. exchanges during a three-month period after the shock. Our ffndings survive a set of robustness checks, including parallel trends test, alternative treatment and control groups based on the qualiffed but not yet dual-listed CCS, and various sub-sample and placebo analyses. In addition to stock returns, dual-listed CCS are also less adversely affected in trading volume, volatility, and liquidity. Our ffndings highlight the large economic impact of the escalating political U.S.-China tensions on the global ffnancial markets.

The improvement of production efficiency and the change of business model brought about by the deep integration of the digital economy and the real economy have become an important driving force for industrial transformation and upgrading. This paper explains the necessity of digital transformation of manufacturing, the trends, paths and six technologies of financial digital transformation. In the digital era, relying on data, scenarios, and algorithms to explore the essential logic of business, make predictions and decisions based on business insights, and put forward higher requirements for financial empowerment business. As an important way for enterprise management transformation and upgrading, the core goal of financial digital transformation is to take "data-driven" as the main line, promote transformation based on the two principles of industry-finance integration and in-depth scenarios, and build "value-creating" finance, that is, based on the integrated application of digital technology, so that finance can expand the functions of supporting strategy, assisting decision-making, empowering business, preventing and controlling risks, lean management, operational excellence, quality and efficiency, compliance supervision and other functions on the basis of basic transaction accounting functions, and promote and even lead the value creation functions of enterprises. The article points out that the manufacturing industry should take enhancing competitiveness as the direction, financial management as the center, and improving quality and efficiency as the goal to accelerate digital transformation. Introduced Midea Group's financial digital transformation practices and results. It is proposed that enterprises should vigorously promote the deep integration of big data, Internet, cloud computing, Internet of Things, artificial intelligence, blockchain and the real economy, accelerate the digital transformation of finance, and inject new impetus into the high-quality development of enterprises.