Intense Market Competition Research Articles

Financial Statement Analysis of BYD Company Limited

This paper takes BYD as an example to analyze its financial indicators and conduct a comprehensive DuPont analysis for the period from 2019 to 2023. The analysis reveals that the company achieved significant financial growth during this period. Both operating revenue and net profit showed an upward trend, with particularly strong growth momentum in 2022 and 2023, as net profit increased substantially. The gross profit margin and net profit margin also improved, indicating enhanced operational efficiency and effective cost control. At the same time, BYD's continuous increase in R&D investment has driven technological innovation and product upgrades. The total assets have continued to grow, reflecting the company's business expansion and strengthened capabilities. The cash flow position remains healthy, with net operating cash flow steadily increasing, providing stable financial support for the company. However, BYD faces challenges such as intensified market competition and fluctuations in raw material prices, which necessitate ongoing optimization of business strategies and operational models to maintain its leading position and competitiveness. Overall, BYD has performed outstandingly in the new energy vehicle sector, with promising prospects for future development.

Sunwoda's Financial Analysis Based on The Harvard Analytical Framework

In order to comply with the strategy of sustainable development, China hopes to further accelerate the rapid development of the new energy vehicle industry and supporting industries. Power battery is the core component of new energy vehicles, and the selection of sunwoda in the battery industry for financial analysis can provide a useful reference for the same type of enterprises.This paper selects sunwoda as an analysis case, applies the Harvard analytical framework to sunwoda's financial analysis, and conducts in-depth discussion and analysis of sunwoda's financial status and existing problems. The analysis found that sunwoda is currently in the growth period,adopting a growth-oriented development strategy to gradually expand the scale of the enterprise, with many projects underconstruction and rapid growth in scale. However, behind the seemingly perfect financial data, there are problems such as low profitability, intensified market competition,and insufficient future development capabilities.In view of these problems,corresponding improvement suggestions are put forward,hoping to help the development of sunwoda.

Can improving the business environment narrow the within-firm pay gap? Evidence from data on 233 Chinese cities

This paper investigates the impact of the business environment (BE) on the within-firm pay gap (WFPG) by using data on listed firms from 233 cities in China. The main finding is that a better BE reduces the WFPG between management and regular employees. After a series of endogeneity treatments and robustness tests, this conclusion remains unchanged. The results of mechanism analysis suggest that intensifying market competition and the alleviating agency problems are two important channels for this effect. Heterogeneity tests indicate a stronger effect for non-state owned enterprises, firms with worse governance, and firms in noncompetitive industries. Additional analysis indicates that human resources, the innovation environment, and financial services are the main factors through which the BE affects the WFPG. This paper provides empirical insights for practical application.

Application of K-Nearest Neighbor Algorithm for Consumer Behaviour Identification and Product Personalisation Based on Big Data Analysis

The rapid digital transformation has fundamentally altered the retail industry, presenting challenges such as shifting consumer behavior and intensified market competition. This research explores the application of the K-Nearest Neighbor (KNN) algorithm for identifying consumer behavior and developing product personalization systems based on big data insights. Utilizing a dataset comprising 10,000 transaction records from January to December 2023 and 5,302 product types, we implemented the KNN algorithm to predict consumer purchases. The data was processed into 89,908 distinct transaction records. Our evaluation, using 5-fold cross-validation, demonstrated that the optimal performance of the KNN model was achieved with 𝑘=10, yielding a precision of 0.8319, recall of 0.8311, and an F1-score of 0.8312. These findings highlight the effectiveness of KNN in enhancing consumer satisfaction through precise product recommendations. This study provides strategic insights for modern retailers aiming to leverage AI and big data to remain competitive and meet evolving consumer expectations.

Influence of Strategic Planning on Banking Performance via Differentiation Strategy

Effective strategic planning plays a crucial role in enhancing the performance of banking businesses. This research aims to analyze the impact of strategic planning on banking business performance through the implementation of differentiation strategy. Utilizing a quantitative approach, primary data was collected through surveys distributed to senior managers from several banks operating in various markets. Multiple linear regression analysis was employed to evaluate the relationship between strategic planning, strategic differentiation, and business performance. The research findings indicate that strategic planning significantly influences strategic differentiation in the context of the banking industry. Additionally, strategic differentiation also positively contributes to banking business performance. The implications of these findings are that banks implementing effective strategic planning tend to adopt better differentiation strategies, thereby enhancing their performance in facing intense market competition. This study provides valuable contributions to understanding the relationship between strategic planning, strategic differentiation, and business performance in the banking context. The results offer guidance for banks to improve their strategic planning practices and implement effective differentiation strategies to strengthen their competitive position in the market. Future research could explore additional factors influencing this relationship and broaden the industry scope to validate these findings more comprehensively.

Impact and Prospects of Prepared Meals on the Catering Market

The increasing pace of modern life has catalyzed the rise of the prepared meals industry, reshaping consumer behaviors and market dynamics in the global catering sector. This study examines the impact of prepared meals on the catering market, focusing on consumer behavior, market dynamics, technological innovations, and sustainability issues. The prepared meals industry has seen exponential growth, driven by consumer demands for convenience, health, and environmentally friendly options. Technological advancements in food preservation, distribution, and packaging have played a pivotal role in improving product quality and safety while extending market reach. Financial analyses of key industry players like Tyson Foods, Inc., Nissin Foods Holdings Co., Ltd., and Nestl S.A. reveal varied strategies for capitalizing on this growth, highlighting significant contributions to their overall business performance. The sector faces challenges including environmental sustainability, health and nutritional scrutiny, and intense market competition. Strategic responses to these challenges, such as investing in sustainable practices, focusing on health and nutrition, leveraging new technologies, and enhancing consumer engagement, are essential for future success. This research provides critical insights into the evolution of the prepared meals market, offering a comprehensive overview that could guide stakeholders in navigating this dynamic landscape.

Assessing the potential of collaborative innovation strategies to drive green development: Threshold effect of market competition

Environmental management literature suggests that elevating the total factor productivity (TFP) of the renewable energy (RE) industry is pivotal for achieving green development. With intensifying market competition in the RE sector, collaborative innovation (COI) has emerged as a crucial strategic choice for enterprises to address developmental bottlenecks. To assess the potential of COI in driving green development, we leveraged data from 114 Chinese RE enterprises from 2011 to 2022. The research findings indicate: (1) COI significantly enhances the TFP of RE enterprises; this enhancement primarily stems from the positive influence of COI on innovation capabilities. (2) The positive effects of COI on TFP manifest only when market competition surpasses a certain threshold level. (3) COI significantly impacts the TFP of small and medium-sized RE enterprises in the growth stage.

Do error-tolerance and correction mechanisms enhance the performance of state-owned enterprises in China?

This study investigates the impact of error-tolerance and correction mechanisms (ETCM) on the performance of state-owned enterprises (SOEs). We conduct difference-in-differences (DID) estimations and find that the implementation of this policy significantly improves SOEs' performance. Mechanism analysis shows that the ETCM can strengthen the innovation capacity and improve internal governance of SOEs. Heterogeneity analysis shows that our results are more pronounced in SOEs with lower levels of corporate management, lower risk preferences of managers, higher intense external market competition, non-Industrial corporate and eastern regions. We also find that the ETCM improves SOEs' total factor productivity (TFP). Overall, this study provides perspectives and evidence from ETCM for deepening the reform of SOEs.

A Study of Hong Kong's Insurance Industry Based on the New Development Pattern Model

Against the backdrop of global economic changes and China's economic restructuring, the potential of Hong Kong's insurance industry as an investment channel is gaining increasing attention. This thesis aims to explore the opportunities and challenges of Hong Kong's insurance industry under the new development pattern. Through a combination of quantitative and qualitative analyses, it examines the historical data and future trends of Hong Kong's insurance market and conducts a study based on first-hand information obtained through data surveys and expert interviews, exploring the specific impacts of the new development pattern on the insurance industry, and incorporating the development of the Greater Bay Area into the research framework. Hong Kong's insurance industry harbours a wealth of investment opportunities in terms of expanding market size, product diversification, and policy support, but it also faces challenges such as intensifying market competition and international uncertainty. The study recommends that investors should focus on long-term trends to optimise their investment strategies and address market risks.

Semantic Web-Based Prediction Method for Goodwill Impairment in Listed Companies Using Mamba

In the context of globalization and intense market competition, mergers and acquisitions (M&A) have become a common strategy for enterprises to expand and transform. However, goodwill issues in M&A are increasingly concerning. Traditional goodwill impairment prediction models face drawbacks like reliance on precise predictions, large datasets, complexity, poor interpretability, high computational costs, and data acquisition difficulties. This paper proposes a prediction model based on an improved Mamba algorithm. By processing financial data from listed companies in the CSMAR database, the model constructs lagged and rolling statistical features to reflect performance trends. The Mamba algorithm dynamically adjusts input parameters through a Selective State-Space Model (SSM), capturing dependencies in long-sequence data and improving prediction accuracy and timeliness. Experimental results show the Mamba algorithm excels in handling long-sequence data, offering valuable guidance for financial management and risk control.

Biomass supply chain coordination considering government subsidies and corporate social responsibility

PurposeThe purpose of this paper is to investigate the impact of various decision-making approaches and government subsidies on supply chain performance, aiming to enhance the profits of disposal firms and retailers as well as to improve social welfare.Design/methodology/approachIn this paper, a two-echelon biomass supply chain composed of a disposal firm and a retailer is developed. Firstly, considering the effects of government subsidies, we analyze biofuels prices, corporate social responsibility levels, social welfare and supply chain profitability under centralized and decentralized decision-making scenarios, respectively. Furthermore, we assess how subsidies influence pricing, market participation, profitability and social welfare. Secondly, we propose a revenue sharing–cost sharing contract to enhance the profits of the disposal firm and retailer. Thirdly, we extend the supply chain to a disposal firm and two retailers and explore the impact of competition intensity on corporate decision-making behavior. Finally, numerical analysis is conducted by taking one biomass energy firm as an example to support the results.FindingsOur research finds that (1) Equilibrium strategies under the centralized decision-making scenario are greater than those under the decentralized decision-making scenario. Centralized decision-making can increase market demand and consumer surplus. (2) Government subsidies can promote corporate social responsibility levels, despite causing a slight increase in retail price for biofuels. When market competition intensifies, companies usually reduce their investment in CSR, and this trend is particularly pronounced in the absence of subsidies. (3) In both the decentralized and the centralized decision-making scenarios, increasing conversion rates and the CSR coefficient can significantly increase the overall profitability and social welfare.Research limitations/implicationsA three-echelon biomass supply chain involving collection station, disposal firm and retailer can be studied in the future.Originality/valueBy examining the effects of subsidies on CSR engagement and market outcomes, our study contributes valuable insights into policy design for promoting sustainable practices in biomass industries.

A knowledge graph-enabled multi-domain mapping approach supporting product rapid design: A case study of new energy vehicles

In the context of mass personalization, the dynamic and erratic nature of customer requirements (CRs) is increasingly pronounced. Amidst intensifying market competition, enterprises are compelled to swiftly adjust their products to satisfy the ever-changing CRs. However, the complicated design processes often result in prolonged product update and iteration cycles. Thus, it is urgent for enterprises to promote product rapid design, in which, it is essential to map CRs to functional requirements (FRs), then to design parameters (DPs). Traditional mapping methods are time-consuming and labor-intensive, struggle to keep pace with the ever-changing CRs. Moreover, enhancing the efficiency of design knowledge management and reuse is imperative for achieving product rapid design. Considering the strengths of knowledge graphs (KGs) in knowledge management and mining, we establish a multi-domain product design KG (MPDKG) including a CR domain, a FR domain, and a DP domain, and facilitate the mapping process by constructing mapping relations between domains. Firstly, CR entities in the CR domain are extracted through a triple-task cascaded CRs identification model from online reviews and complaints. Secondly, FR entities are identified from product functional lists and instructions, and the Sentence-Bert model is employed to establish the mapping relations between CR entities and FR entities. Subsequently, a corpus comprising product design knowledge is constructed and a cross-domain joint entity relation extraction model is developed to extract DP entities and construct their mapping relations with FR entities. Lastly, the multi-domain mapping of BYD Qin is implemented as a case study to elucidate the practical utility and effectiveness of the proposed methodology.

The Influence of Brand Image, Product Innovation, and Marketing Content on Purchasing Decisions Honda Scoopy Motorbikes in Denpasar City

Changes in consumer preferences in the motorcycle industry demand companies to enchance their marketing strategies to meet the need for efficient transportation amidst intense market competition. Denpasar serves as a prominent commercial hub, facilitating the acquisition of information. This research carried out in Denpasar, a city divided into four districts, with the objective of evaluating the impact of brand image, product development, and marketing content on the purchasing decisions for Honda Scoopy scooters in the region. A quantitative, descriptive research approach was employed. The target population included motorcycle riders who did not currently own a Honda Scoopy. A purposive sampling method was utilized, resulting in a sample 100 respondents. Data were collected using a structured survey consisting of 18 questions designed to measure each variable. The responses from the 100 participants were analyzed using multiple regression analysis with SPSS Statistics 26. The results indicate that brand image substantial impacts on consumer decision-making. Marketing content also affects these decisions, while product innovation has a substantial and positive effect on purchasing choices. The coefficient of determination (R²) is 73.4%, suggesting that brand image, product innovation, and marketing content collectively explain 73.4% of the variance in purchasing decisions. Factors that are not included in the regression model have an impact on the remaining 26.6%. Therefore, can surmised that brand image, product development, and marketing content significantly impact purchasing decisions.

Analysis of Financial Performance of Yunnan Baiyao Group Co.

Yunnan Baiyao Group Co., Ltd. has been actively expanding its business territory and product lines, led by its diversification strategy, thus achieving remarkable financial results. The company has also used scientific asset management strategies to optimize the allocation of resources and enhance the efficiency of asset utilization, while efficient operations have provided solid support for its diversified growth. However, the implementation of a diversification strategy also introduces specific financial risks and challenges. Increasing financial pressure and intensifying market competition have gradually emerged, which require Yunnan Baiyao Group Co., Ltd. to continuously improve its financial structure and strengthen risk management to ensure the durability and profitability of its strategy. This article not only comprehensively analyzes the financial performance of Yunnan Baiyao Group Co., Ltd. in implementing its diversification strategy, but also deeply discusses the challenges faced by the group and its corresponding response strategies, which provides valuable reference and far-reaching insights for other enterprises in adopting similar strategies.

Research on Improvement of Employee Satisfaction Based on Career Management

As market competition intensifies, the demand for talent management among enterprises has escalated, with employee satisfaction increasingly emerging as a crucial driving force behind organizational success. Career management, as a pivotal component of human resource management, directly influences employees' professional growth and contentment by offering developmental pathways, training opportunities, and personalized guidance. However, numerous companies encounter challenges in implementing career management, often grappling with ambiguous paths, rigid mechanisms, and insufficient transparency. Therefore, investigating how career management can enhance employee satisfaction holds significant importance for the business sector. This study, grounded in a comprehensive analysis of the definition and elements of career management, explores its current practical applications within enterprises and proposes a series of specific measures aimed at elevating employee satisfaction. The objective is to assist organizations in effectively bolstering employee engagement and sense of belonging, thereby providing robust support for human resource management.

Influence of Strategic Planning on Banking Performance via Differentiation Strategy

Effective strategic planning plays a crucial role in enhancing the performance of banking businesses. This research aims to analyze the impact of strategic planning on banking business performance through the implementation of differentiation strategy. Utilizing a quantitative approach, primary data was collected through surveys distributed to senior managers from several banks operating in various markets. Multiple linear regression analysis was employed to evaluate the relationship between strategic planning, strategic differentiation, and business performance. The research findings indicate that strategic planning significantly influences strategic differentiation in the context of the banking industry. Additionally, strategic differentiation also positively contributes to banking business performance. The implications of these findings are that banks implementing effective strategic planning tend to adopt better differentiation strategies, thereby enhancing their performance in facing intense market competition. This study provides valuable contributions to understanding the relationship between strategic planning, strategic differentiation, and business performance in the banking context. The results offer guidance for banks to improve their strategic planning practices and implement effective differentiation strategies to strengthen their competitive position in the market. Future research could explore additional factors influencing this relationship and broaden the industry scope to validate these findings more comprehensively.

Analysis of the Effect Financial Ratios to Probability Default With the Risk as Moderation in Indonesian Building Construction Sub-Sector Companies

The construction and building sector are one of the important sectors for Indonesia development and economy, furthermore it is also being an indicator in assessing the economic development of a country. The development in the sector of construction and building, which is currently facing intense market competition, is encouraging many companies to improve their management fundamentals. A company's inability to anticipate changes can result the decreasing in business volume, which eventually has a negative impact on profits and caused bankruptcy. The aim of this research is to analyze the effect of GPM, NPM, CR, DER, TIE, and TATO by moderating risk on probability default (probability of bankruptcy) in the construction and building companies in Indonesia which registered on the IDX for the 2014-2023 period. The research method used in this research is a panel data model to estimate the coefficient model. The result shows that Total Assets Turnover (TATO) has a positive and significant effect on the probability of bankruptcy. Meanwhile, Gross Profit Margin (GPM), Net Profit Margin (NPM), Current Ratio (CR), Debt Equity Ratio (DER), and Times Interest Earned (TIE), does not have a significant effect on the probability default in the construction and building companies.

An FPGA-Based YOLOv5 Accelerator for Real-Time Industrial Vision Applications.

The You Only Look Once (YOLO) object detection network has garnered widespread adoption in various industries, owing to its superior inference speed and robust detection capabilities. This model has proven invaluable in automating production processes such as material processing, machining, and quality inspection. However, as market competition intensifies, there is a constant demand for higher detection speed and accuracy. Current FPGA accelerators based on 8-bit quantization have struggled to meet these increasingly stringent performance requirements. In response, we present a novel 4-bit quantization-based neural network accelerator for the YOLOv5 model, designed to enhance real-time processing capabilities while maintaining high detection accuracy. To achieve effective model compression, we introduce an optimized quantization scheme that reduces the bit-width of the entire YOLO network-including the first layer-to 4 bits, with only a 1.5% degradation in mean Average Precision (mAP). For the hardware implementation, we propose a unified Digital Signal Processor (DSP) packing scheme, coupled with a novel parity adder tree architecture that accommodates the proposed quantization strategies. This approach efficiently reduces on-chip DSP utilization by 50%, offering a significant improvement in performance and resource efficiency. Experimental results show that the industrial object detection system based on the proposed FPGA accelerator achieves a throughput of 808.6 GOPS and an efficiency of 0.49 GOPS/DSP for YOLOv5s on the ZCU102 board, which is 29% higher than a commercial FPGA accelerator design (Xilinx's Vitis AI).

Does local government debt management affect cross-border M&As? Evidence from China

The rapid expansion of government debt exacerbates systemic risks and tightens the credit transmission channels of monetary policy, posing a severe threat to the healthy development of firms. Existing literature mainly examines the impact of government debt on corporate financing behavior, innovation, and total output. Using data from a sample of Chinese A-share listed firms covering the period from 2001 to 2022, we investigate the impact of local government debt management on corporate cross-border mergers and acquisitions (M&As). Our analysis reveals that effective local government debt management promotes cross-border M&As by alleviating corporate financing constraints, intensifying market competition, and enhancing corporate risk-taking capacity. The findings offer fresh insights into achieving the dual objectives of risk prevention and stable growth through local government debt management and provide significant implications for boosting the high-quality development of the real economy.

The Effect of Market Structure on Sales of Coal Companies Listed on the Indonesia Stock Exchange (IDX) for the Period 2018 - 2022

The limited product diversification of the Indonesian coal mining industry underscores the imperative for the formulation of strategic business plans to navigate the intensifying market competition. This study aims to examine the market structure, the factors influencing sales, and the impact of market structure on the sales performance of coal mining companies in Indonesia. This study employs a quantitative method and utilizes a range of analytical techniques, including CR4, HHI, MES, CLR, PCM, and multiple linear regression. The CR4 and HHI analysis revealed that the market structure of coal mining companies in Indonesia is classified as a highly concentrated tight oligopoly. The MES analysis yielded the conclusion that new companies in the sector face significant barriers to market entry. The findings of the CLR analysis, which indicates that the coal mining sector is a capital-intensive industry, suggest that equity and capital factors are the primary contributors to the challenges faced by new companies attempting to enter the market. The results of the multiple linear regression analysis indicate that equity factors and production volume have a positive and significant effect on company sales. This finding is corroborated by the PCM analysis, which suggests that companies with low market share tend to set higher margins to obtain greater profits. Increasing investment levels may serve as a viable business strategy, particularly when supported by government policies aimed at fostering a secure and stable investment environment to enhance company equity and capital.