Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 17, No. 2, 2024 298 Information Transparency and Corporate Value Among the Selected Guang Dong Province High-Tech Enterprises: A Proposed Investment Guide Ying Zhang Department of Management, Adamson University, Manila, 10000, Philippines Abstract: As Guangdong is one of the leading provinces in the Chinese economy, its high-tech enterprises have become a key driving force for innovation and economic growth. However, these enterprises often face challenges in value evaluation by investors and other stakeholders due to their inherent complexity. In response to this issue, this study collected data through a questionnaire survey to explore the interrelationships among information transparency, investor confidence, and the value of high-tech enterprises in Guangdong Province. This study applied quantitative research methods, including descriptive statistics, correlation analysis, regression analysis, and moderating effect analysis, to conduct an in-depth research of the data. The results indicate that information transparency positively impacts both corporate value and investor confidence. Moreover, investor confidence plays a moderating role in the relationship between information transparency and corporate value. Based on the results, this study proposes a specific investment guide for investors in high-tech enterprises in Guangdong Province. Keywords: Corporate Value, Information Transparency, Investor Confidence, High-tech Enterprises, Guangdong Province. 1. Introduction 1.1. Background of the Study In the context of globalization and innovation-driven economy, technological innovation has stood out as the core engine for sustained economic growth. High-tech enterprises, as the main force carrying this engine, are undoubtedly the key force driving national economic growth. In Guangdong Province, China, the development of high-tech enterprises has shown a particularly strong momentum, injecting a strong impetus for local and national economic stability and prosperity. According to the latest data released by the Guangdong Provincial Science and Technology Department, the Guangdong high-tech enterprises’ revenue in 2023 amounted to US$1.7 trillion, and the number of enterprises exceeded 75,000, accounting for 70% of the province's manufacturing sector. Moreover, Guangdong Province is home to one-sixth of the total number of high-tech enterprises in China, which is the eighth consecutive year of the country's leading position. These remarkable figures not only highlight the great contribution of high-tech enterprises in promoting the transformation and upgrading of Guangdong's manufacturing industry, but also indicate that the future of Guangdong's manufacturing industry will further rely on the innovation ability and technological advantages of these enterprises. However, in such a dynamic and opportunistic market environment, high-tech enterprises also face many challenges. Due to rapid technological updating, huge research and development (R&D) investment and increasingly fierce market competition, the operating and financial conditions of these enterprises are often characterized by complexity and volatility. This also makes the information transparency problem of high-tech enterprises gradually surfaced, which brings more uncertainty and risk to investors. It is therefore evident that for high-tech enterprises in the province of Guangdong, the urgent necessity exists to address the issue of improving information transparency. Previous studies have shown that information transparency affects corporate value by influencing investor confidence. This interplay makes all three work together to a large extent to determine the performance and position of firms in the market. A study by Li et al. (2019) found a positive relationship between corporate value and accounting information transparency, with the findings aligning with the tenets of the life cycle theory. More recently, Naveed et al. (2021) investigate how transparency of information influences investors' perception of financial well-being. Their results suggest that not only does transparency enhance the confidence of investors, but also positively affects their risk tolerance towards the firm. However, it is worth emphasizing that information transparency is an ever-changing process and its impact on corporate value may vary over time, by region and by industry. The above studies may not be sufficient to consider the potential impact of regional and industry differences on information transparency. High-tech firms, in particular, face challenges and opportunities in information transparency that are quite different from those of traditional firms due to their unique technological characteristics and market environment. In light of the aforementioned considerations, this paper focuses its analysis on high-tech enterprises in the province of Guangdong, deeply explores the intrinsic connection between information transparency and corporate value, and devotes itself to revealing the correlation mechanism between the two, with a view to providing investors with a practical investment guide to help them better understand and assess the true value of high-tech enterprises. This will not only help to protect the interests of investors, but also further promote the healthy development and value enhancement of enterprises. 1.2. Statement of the Problem Based on the research background, this paper proposed several key questions to explore the information transparency of high-tech enterprises in Guangdong Province and its 299 relationship with corporate value and investor confidence. Specifically, this study seeks answers to the following questions: (1) Is there a significant relationship between information transparency and the corporate value? (2) Is there a significant relationship between information transparency and the investor confidence? (3) Is there a moderating effect of investor confidence on both information transparency and corporate value? (4) Based on the above research results, what is the proposed investment guide for investors? 1.3. Hypotheses The following null hypotheses had been tested based on the statement of the problems: H01: There is no significant relationship between the information transparency and the corporate value. H02: There is no significant relationship between the information transparency and the investor confidence. H03: There is no moderating effect of investor confidence on both information transparency and corporate value. 1.4. Related Literature Research results show that many scholars have already explored information transparency and its resulting economic impacts from multiple perspectives. Studies have found that information transparency was of great significance for corporate governance, digital transformation, protection of investor interests, and promotion of the healthy development of enterprises and the fulfillment of social responsibility (Sun et al. 2024; Gao et al. 2019; Liu & Gao 2021; Huang et al. 2019). In addition, synthesizing all the above studies reveals that the creation of corporate value is a complex and multivariate process involving multiple dimensions, which includes many elements such as the transformation of the digital economy, managerial traits, and the market environment (Li 2021; He et al. 2019; Ren 2021; Wang et al. 2021). As an important indicator of market sentiment, investor confidence has been widely studied and recognized as an important factor affecting market volatility. In recent years, several scholars have thoroughly explored the relationship between investor confidence and market volatility from different perspectives. Their studies showed that investor confidence had a significant impact on a number of dimensions, including corporate value, the quality of information disclosure, the impact of policy changes, and stock returns (Wang et al. 2022; Zhang et al. 2021; Qin et al. 2020). Furthermore, previous studies also revealed an intricate interaction between information transparency, investor confidence, and corporate value (Li et al. 2019; Truong, 2022; Ramadan, 2020;). There is a robust correlation between information transparency, investor confidence and corporate value. Information transparency affects corporate value by influencing investor confidence, which in turn plays a key mediating role (Naveed et al. 2021; Wang et al. 2019; Liu, 2019). This interaction makes all three of them work together to a large extent to determine the performance and position of firms in the market. However, it should be underlined that information transparency is a changing process and at different times and regions and for various industries, its effect on corporate value can be different. The researches above may be a little inadequate in considering possible influences of regional and industry differences on information transparency. In this regard, high-tech enterprises face a completely different set of challenges and opportunities regarding information transparency compared to traditional enterprises, because of the differing nature of their technological characteristics and market environment. In addition, the previous research in information transparency, investor confidence, and corporate value mostly adopted the second-hand data, while this study directly collected data through questionnaire surveys, which can more objectively reflect the relevant situation. Based on this, this research chose high-tech enterprises in Guangdong Province as the research samples to deeply analyze the role and actual effects of information transparency in the specific regional and industry background. 1.5. Conceptual Framework This study takes high-tech enterprises in Guangdong Province as the research object, and deeply explores the intrinsic relationship between information transparency, investor confidence, and corporate value, aiming to provide scientific investment guidance for investors. The conceptual framework shown in Figure 1 is constructed based on the statement of the problem and research hypotheses. Figure 1. Author’s Conceptual Framework 2. Methods 2.1. Research Design In order to answer those questions above, this study used of quantitative research methods, specifically covering descriptive statistics, correlation analysis, regression analysis and moderating effect analysis. In terms of data collection, this study relied on questionnaires to extensively collect investors' evaluation of the information transparency of high- tech enterprises in the province of Guangdong, their investment confidence in the companies, and their comprehensive assessment of the value of the enterprises, which covers a variety of dimensions such as the financial performance and market value of the enterprises. 2.2. Data Management In quantitative research, data can be categorized as independent, moderating and dependent variables based on their role. 2.2.1. Independent Variables - Information Transparency In this study, the independent variable is information transparency which is further subdivided into: Transparency of Governance Information. It involves the extent to which the decision-making process, policies and behaviors of the firm's management are made public. Transparency of Organizational Information. It includes 300 the transparency of a firm's organizational structure, shareholding structure, management hierarchy, and internal operations. Transparency of Accounting Information. It refers to the openness and understandability of an enterprise's financial reports, accounting policies and audit information. 2.2.2. Moderating Variable - Investor Confidence In this study, the moderating variable is investor confidence, which consists of: Company Development Confidence. It refers to investors' confidence in the firm's future growth potential and market outlook. Stock Holding Confidence. It refers to investors' willingness and confidence in holding shares of a firm. 2.2.3. Dependent Variable - Corporate Value This study will approach from the perspective of investors, comprehensively considering the two core elements of corporate financial performance and market value through a questionnaire survey. In addition, as this study used a questionnaire survey to assess value, the term "corporate value" used herein (except in the context of related research) refers to investors' perceptions of that value, which consists of: Financial performance. This research measures financial performance through sales revenue, net profit, earnings per share, dividends per share and ROE. For example, respondents use a four-point scale to gauge how quickly a company's sales revenue has increased during the past fiscal years, where 1 represents worse and 4 represents better. Market value. This research used stock price, total market value, price to earnings ratio, price to book ratio, and market competitive position to measure the market value of high-tech enterprises. For example, respondents measure the growth rate of a company's sales profit margin over the past three years using a four point scale, where 1 represents worse and 4 represents better. Based on this, this study set a significance level of 0.05 to assess the significance of the statistical analysis results. All statistical analyses had been conducted in SPSS 24.0 software to ensure standardization of the analysis process and accuracy of the results. 2.3. Sampling Design This study's focus is on high-tech companies in Guangdong Province that are listed on the Chinese A-share stock exchange. To guarantee data availability and research feasibility, the Guangdong Provincial Department of Science and Technology's list of high-tech companies for three years in a row in 2021–2023 was chosen as the study's sample pool. After screening, this study further selected the top 5 companies with P/E ratios from these enterprises as the research sample. This study mainly adopts the questionnaire method as the data collection tool. The respondents to this questionnaire are investors of enterprises, and the minimum share of company stocks held by investors is set at 100. Given that individual investors face more severe challenges in terms of information asymmetry, in contrast to institutional investors who have professional investment decision-making teams. Therefore, the investment advice in this paper is mainly for individual investors, so the respondents of this paper will be specific to individual investors of these companies. In the questionnaire design section, this study will utilize the Likert scale to quantify investors' views and attitudes towards information transparency, investor confidence, and corporate value of Guangdong Province's high-tech companies. The Likert scale usually contains 4 or 7 levels, and this study can adopt a 4-level scale. In order to collect the survey data, this study distributed electronic questionnaires to the Stock Bar websites and stock investor WeChat groups of five high-tech enterprises through the Internet platform "Questionnaire Star". The expected goal of the study is to collect about 60 valid questionnaires for each company. To assess the completion rate, a trial survey was conducted in advance, and based on this, the actual total number of questionnaires distributed by each company was determined. the following is the distribution of the number of respondents in these companies. Table 1. Distribution of Respondents According to Company Company Frequency Percent Company A 56 18.9 Company B 60 20.3 Company C 60 20.3 Company D 59 19.9 Company E 61 20.6 Total 296 100 Table 1 lists the five high-tech enterprises studied in this article and their corresponding number of respondents (i.e. stock investors), as well as the percentage of these numbers among the total respondents. 3. Results 3.1. Reliability & Validity Reliability test results show that the Cronbach's Alpha coefficients of each latent variable are between 0.8910 and 0.8919, with all coefficients exceeding 0.89, indicating high reliability of these latent variables. Moreover, the total scale's internal consistency was high, and there was a good connection between the questionnaire's questions, as indicated by the Cronbach's Alpha value of 0.954. Therefore, this questionnaire can be considered a highly reliable tool for measuring these latent variables. As to validity test, according to the KMO and Bartlett's Test results shown the KMO coefficient is 0.945, the chi square value of Bartlett's Test is 7346.592, the degree of freedom is 595, and the significance level (Sig.) is less than 0.05. so, the data are suitable for factor analysis. Through further in-depth analysis with SPSS software, it can be concluded from the exploratory factor analysis that the total variance of the 7 factors extracted from the questionnaire can be explained is 73.579%, that is, the factor interpretation ability is good and the original data information can be completely retained. At the same time, the variance percentage of the first factor is 39.092%, which is less than 40%, indicating that there is no serious common method bias in the data. Besides, all questions fall in the corresponding dimension, indicating that the questionnaire has good structural validity, and the data obtained from the questionnaire can be used for further analysis. 3.2. Descriptive Statistics 3.2.1. Descriptive Statistics on Information Transparency The following is a detailed evaluation of the information transparency level of 5 high-tech enterprises by investors in 301 various dimensions. Table 2. Descriptive Statistics on Information Transparency as to 5 Company Company Information Transparency Mean Overall Mean Interpretation Company A Transparency of Governance Information 2.76 2.65 Transparent Transparency of Organizational Information 2.59 Transparency of Accounting Information 2.59 Company B Transparency of Governance Information 2.81 2.75 Transparent Transparency of Organizational Information 2.76 Transparency of Accounting Information 2.68 Company C Transparency of Governance Information 2.43 2.49 Non-transparent Transparency of Organizational Information 2.52 Transparency of Accounting Information 2.54 Company D Transparency of Governance Information 2.38 2.48 Non-transparent Transparency of Organizational Information 2.44 Transparency of Accounting Information 2.62 Company E Transparency of Governance Information 2.43 2.51 Transparent Transparency of Organizational Information 2.43 Transparency of Accounting Information 2.68 Legend: Very Transparent (4) =3.26-4.00; Transparent (3) =2.51-3.25; Non-transparent (2) =1.76-2.50; Very Non-transparent (1) =1.0- 1.75 Table 2 presents descriptive statistical data of five high- tech enterprises on three key indicators of information transparency. The respondents had different evaluations of the information transparency of these five companies. Company A and Company B had high evaluations in various dimensions, demonstrating good transparency; however, Company D has shown weaker performance, especially in terms of governance and transparency of organizational information. This indicates that although most companies have performed well in terms of transparency, there is still room for improvement, and special attention should be paid to and measures must be taken to improve investors' perception of their transparency. 3.2.2. Descriptive Statistics on Corporate Value The following is a detailed evaluation of the corporate value performance of 5 high-tech enterprises by investors in 2 dimensions. Table 3. Descriptive Statistics on Corporate Value as to 5 Company Company Corporate Value Mean Overall Mean Interpretation Company A Financial Performance 2.81 2.68 Increase Market Value 2.56 Company B Financial Performance 2.67 2.73 Increase Market Value 2.78 Company C Financial Performance 2.39 2.46 Increase Market Value 2.53 Company D Financial Performance 2.42 2.5 Decrease Market Value 2.58 Company E Financial Performance 2.6 2.53 Increase Market Value 2.47 Legend: Significantly Increase (4) =3.26-4.00; Increase (3) =2.51-3.25; Decrease (2) =1.76-2.50; Significantly Decrease (1) =1.0-1.75 The data results in Table 3 indicate that there are differences in the value perception of different companies in the minds of investors. Company A and B perform more prominently in investor evaluations, while enterprises C and D have relatively lower evaluations. These data can help investors and corporate management understand the value perception of different companies in the minds of investors, and provide reference for investment decisions. 3.2.3. Descriptive Statistics on Investor Confidence The following were the evaluation results of investors' confidence performance in 2 dimensions for 5 high-tech enterprises. According to the data in table 4, investors generally hold a positive attitude towards the development and shareholding confidence of high-tech enterprises in Guangdong Province. Among them, Company B and Company C have received high praise in certain aspects, while Company D needs to work harder to enhance investor confidence. 302 Table 4. Descriptive Statistics on Investor Confidence as to 5 Company Company Investor Confidence Mean Overall Mean Interpretation Company A Company Development Confidence 2.64 2.58 Confident Stock holding Confidence 2.52 Company B Company Development Confidence 2.9 2.87 Confident Stock holding Confidence 2.84 Company C Company Development Confidence 2.52 2.6 Confident Stock holding Confidence 2.68 Company D Company Development Confidence 2.49 2.47 Unconfident Stock holding Confidence 2.45 Company E Company Development Confidence 2.53 2.54 Confident Stock holding Confidence 2.54 Legend: Very Confident (4) =3.26-4.00; Confident (3) =2.51-3.25; Unconfident (2) =1.76-2.50; Very Unconfident (1) =1.0-1.75 3.3. Correlation Analysis 3.3.1. Correlation Between Information Transparency and Investor Confidence Table 5 shows the correlation analysis results between variables based on 296 samples. The correlation coefficients between each variable are listed in the table, and significant correlations at the 0.01 level (two tailed) are marked with "* *". The findings of the research indicate that the two aspects of corporate value (financial performance and market value) and all aspects of information transparency (including governance, organization, and accounting) have a positive link. This indicates that there is a close relationship between the improvement of information transparency and the enhancement of investors' perception of investors' perception of corporate value. Especially, there is a substantial correlation (.686**) between overall corporate value (CV) and overall information transparency (IT), which supports the idea that there is a significant relationship between the two and validates hypothesis 1. Table 5. Correlation Between Information Transparency and Corporate Value Variables ITG ITO ITA CVF CVM IT CV ITG 1 ITO .420** 1 ITA .385** .456** 1 CVF .460** .485** .483** 1 CVM .453** .478** .442** .509** 1 IT .766** .796** .787** .608** .584** 1 CV .525** .554** .532** .864** .873** .686** 1 ** Correlation is significant at the 0.01 level (2-tailed). (N=296) Abbreviation meaning of variables: ·ITG: Transparency of Governance Information ·ITO: Transparency of Organizational Information ·ITA: Transparency of Accounting Information ·CVF: Corporate Value - Financial Performance ·CVM: Corporate Value - Market Value ·IT: Information Transparency ·CV: Corporate Value Table 6. Correlation between Information Transparency and Investor Confidence Variables ITG ITO ITA ICD ICS IT IC ITG 1 ITO .420** 1 ITA .385** .456** 1 ICD .416** .503** .476** 1 ICS .445** .422** .452** .531** 1 IT .766** .796** .787** .594** .561** 1 IC .492** .528** .530** .869** .881** .660** 1 ** Correlation is significant at the 0.01 level (2-tailed). (N=296) Abbreviation meaning of variables: ·ITG: Transparency of Governance Information ·ITO: Transparency of Organizational Information ·ITA: Transparency of Accounting Information ·ICD: Investor Confidence-Company Development Confidence ·ICS: Investor Confidence-Stock holding Confidence ·IT: Information Transparency ·IC: Investor Confidence 303 3.3.2. Correlation Between Information Transparency and Investor Confidence Table 6 mainly shows the correlation between information transparency (IT) and investor confidence (IC), with significant correlations marked with "* *" at the 0.01 level (two tailed). According to table 6, All aspects of information transparency, including governance, organization, and accounting, are significantly and positively correlated with the two aspects of investor confidence (business development confidence and investor shareholding confidence). In addition, the correlation between overall information transparency (IT) and overall investor confidence (IC) is 0.660, indicating a strong correlation between the two and preliminarily testing hypothesis 2. 3.4. Regression Analysis 3.4.1. Regression Results Between Information Transparency and Corporate Value Table 7. Simple Regression Results Between Information Transparency and Corporate Value Model Unstandardized Coefficients B t Sig. F P-value Adj- R Square Remark Decision Model 1 Cons- 0.601 4.707 .000 261.46 .000 0.469 Significant Reject H01 IT 0.768 16.17 .000 a Dependent Variable: CV (N=296) As shown in table 7, the regression coefficient of information transparency was as high as 0.768, with a t-value of 16.17 and a very small Sig value (. 000, far below 0.05), showing that there is a a significant positive relationship between information transparency (IT) and the corporate value (CV) of high-tech companies in the province of Guangdong. Table 8. Multiple Regression Results Between Information Transparency and Financial Performance Model Unstandardized Coefficients B t Sig. VIF F P-value Adj- R Square Remark Model 2 Cons- 0.589 3.717 .000 57.1 36 .000 0.363 significant ITG 0.247 4.695 .000 1.288 ITO 0.259 4.728 .000 1.384 ITA 0.265 5.028 .000 1.339 a Dependent Variable: CVF (N=296) Table 8 presents in detail the linear regression analysis results. 0.247 is the regression coefficient for governance information transparency, accompanied by a significant t- value of 4.695 and Sig. value of 0.000, which clearly demonstrates the substantial beneficial boosting influence that governance information transparency has on corporate financial performance. Similarly, the transparency coefficient of organizational information is 0.259, with a t-value of 4.728 and a Sig. value of 0.000, indicating that financial performance is also considerably enhanced by organizational information transparency. Furthermore, the transparency coefficient of accounting information is 0.265, the t-value is 5.028, and the Sig. value remains at a significant level of 0.000, verifying the significant positive effect of transparency of accounting information on corporate financial performance. Table 9. Multiple Regression Results Between Information Transparency and Market Value Model Unstandardized Coefficients B t Sig. VIF F P-value Adj- R Square Remark Model 3 Cons- 0.614 3.676 .000 50.59 .000 0.335 significant ITG 0.262 4.715 .000 1.288 ITO 0.28 4.843 .000 1.384 ITA 0.224 4.027 .000 1.339 a Dependent Variable: CVM (N=296) Table 9 presents the statistical analysis data of polynomial regression results. Specifically, the transparency of governance information (ITG coefficient of 0.262, t-value of 4.715, Sig. value of. 000) indicates a significant positive impact of transparency of governance information on market value. The transparency of organizational information (ITO) coefficient is 0.28, with a t-value of 4.843 and a Sig. value of. 000, indicating a significant positive impact. The coefficient of transparency of accounting information (ITA) is 0.224, the t-value is 4.027, and the Sig. value is. 000, indicating that Market value is also considerably boosted by accounting information transparency. In summary, this study confirmed through multiple statistical analyses, including correlation analysis and regression analysis, that there is a significant and positive relationship between information transparency and corporate value of high-tech enterprises in the province of Guangdong - “reject H01”. 3.4.2. Regression Results Between Information Transparency and Investor Confidence Table 10 clearly shows the regression results between the two variables. The coefficient of Information Transparency is the key to this model. Its non-standardized coefficient is 0.769 (Sig.=0.0014, below the significance level of 0.05), indicating that investor confidence is significantly affected by information transparency. 304 Table 10. Simple Regression Results Between Information Transparency and Investor Confidence Model Unstandardized Coefficients B t Sig. F P-value Adj- R Square Remark Decision Model 4 Cons- 0.633 4.614 .000 226.72 .000 0.433 Significant Reject H01 IT 0.769 15.057 .000 a Dependent Variable: IC (N=296) Table 11. Multiple Regression Results Between Information Transparency and Company Development Confidence Model Unstandardized Coefficients B t Sig. VIF F P-value Adj- R Square Remark Model5 Cons- 0.633 3.852 .000 53.986 .000 0.350 significant ITG 0.192 3.512 0.001 1.288 ITO 0.311 5.483 .000 1.384 ITA 0.268 4.9 .000 1.339 a Dependent Variable: ICD (N=296) As show in table 11, the coefficient of Information Transparency in Governance (ITG) is 0.192, indicating its positive role in boosting confidence in the firm's development. The significance of this impact is supported statistically (Sig.=0.001, below the significance level of 0.05). Meanwhile, the coefficient of transparency information in organizational (ITO) is 0.311, and its significance has been statistically verified (Sig.=. 000), with the highest among the three, indicating a significant impact of organizational information transparency on enhancing company development confidence. In addition, the coefficient of transparency of accounting information (ITA) is 0.268, which also indicates its positive promoting effect on company development confidence, and this effect is statistically significant (Sig.=. 000). Table 12. Multiple Regression Results Between Information Transparency and Stock Holding Confidence Model Unstandardized Coefficients B t Sig. VIF F P-value Adj- R Square Remark Model 6 Cons- 0.636 3.591 .000 45.151 .000 0.310 significant ITG 0.282 4.786 .000 1.288 ITO 0.206 3.373 0.001 1.384 ITA 0.277 4.707 .000 1.339 a Dependent Variable: ICS (N=296) Table 12 shows the coefficient of ITG is 0.282(sig.=.000), indicating that the transparency of governance information has a positive impact on ICS. Similarly, the coefficient of ITO is 0.206(sig.=.001), indicating that transparency of organizational information also has a favorable effect ICS, but the extent of the influence is slightly lower than ITG. In addition, the ITA coefficient is 0.277(sig.=.000), indicating that transparency in accounting information significantly and positive affects stock holding confidence in investors (ICS). In summary, this study explores the relationship between information transparency and investor confidence in high- tech enterprises in the province of Guangdong through various data analysis methods such as correlation and regression. The study's findings show that investor confidence and information transparency have a significant and positive relationship - “reject H02”. 3.5. Moderating Effect Analysis Moderation is an important methodological concept in social science research, which is a crucial means for researchers to explore the relationships between multiple variables (Fang Jie, Wen Zhonglin et al., 2015). If the relationship between the dependent variable and the independent variable (the magnitude and direction of the regression slope) changes with the change of the third variable, then the third variable is said to have a moderating effect between the independent variable and the dependent variable. At this time, the third variable is called the moderating variable. In order to improve the accuracy and stability of data analysis, researchers generally agree on the importance of centralization as a preprocessing step, one of which is to effectively alleviate the problem of multicollinearity (Dalal & Zickar, 2012; Jose, 2012). Therefore, in the analysis of moderation effects based on multiple regression, this study centered the independent variable and moderation variable by subtracting the sample mean from the variable, and then generated a product term. Finally, multiple regression analysis was conducted to analyze moderation effects (Wen Zhonglin, Liu Hongyun, Hou Jietai, 2012). Table 13. Results of Moderation Effect Analysis Based on Multiple Regression Model Unstandardized Coefficients B t Sig. VIF F P-value Adj- R Square Remark Model 7 Cons- 2.503 55.031 .000 104.793 .000 0.514 Reject H03 DIT 0.536 8.52 .000 1.913 DIC 0.247 4.749 .000 1.772 DIT*DIC 0.168 2.628 0.009 1.128 a Dependent Variable: CV (N=296) ·DIT=IT - IT(Mean) ·DIC=IC - IC(Mean) Table 13 presents in detail the regression analysis results of the relationship between Investor Confidence (DIC) and 305 Information Transparency (DIT) and Corporate Value (CV). Among them, both DIT and DIC have undergone past centralization processing to eliminate potential bias effects. Specifically, the non-standardized coefficient of DIT is 0.536, accompanied by a t-value of 8.52 and Sig. of. 000, which supports that corporate value is significantly enhanced by information transparency, consistent with previous research findings. Similarly, the non-standardized coefficient of DIC is 0.247, the t-value is 4.749, and Sig. is. 000, indicating that investor confidence itself is also an important factor in enhancing corporate value. Further exploration revealed that the non-standardized coefficient (0.168) and its significance (t=2.628, Sig.=0.009) of DIT * DIC clearly demonstrate that investor confidence has a positive moderating influence on the link between business value and information transparency, deepening our understanding of the complex mechanisms underlying the three factors. 3.6. Investment Guide for Investors Guangdong Province, with its rapid pace of innovation, government policy support, and enormous growth potential in the market, provides unique opportunities and challenges for investing in high-tech enterprises, especially in the local area. This investment guide is based on previous research findings, including statistical description and regression analysis results, focusing on core elements such as information transparency, investor confidence, financial performance, and market value, with the aim of assisting investors in making informed investment choices. 3.6.1. Evaluating Transparency Using Key Indicators and Standards Due to the inherent complexity and innovation cycle of the industry, information transparency is crucial in high-tech investment. Investors are advised to evaluate transparency from three aspects: A. Transparency of Governance Information In terms of sample company performance, the average score of governance transparency shows a certain weakness, such as the significantly lower average of Company D. Besides, it is worth noting that the regression analysis results show that governance transparency plays the most significant role in enhancing market value and boosting investor confidence in shareholding. This indicates that although some companies lack transparency in their governance, it remains a key factor in determining the overall performance of the company and investor perceptions. Therefore, when evaluating a company, investors are advised to pay attention to governance related indicators such as board composition, management stability, and transparency of decision-making processes, and strive to choose companies with higher governance transparency scores to ensure stable management practices. The following indicators are available for reference: (1) Board Structure. Evaluate the independence, diversity, and experienced composition of the company's board of directors to ensure management stability. (2) Management change situation. Review the frequency and transparency of management changes. Companies with stable management teams usually bring higher investor confidence. (3) Shareholder Meeting Minutes. High frequency and detailed shareholder meeting minutes can reflect the transparency of company decisions. B. Transparency of Organizational Information According to the regression analysis, investor confidence and corporate value are significantly enhanced by organizational transparency. Investors are advised to prioritize companies with transparent organizational structures, frequent updates on shareholder changes, and detailed disclosure of internal operations. Higher organizational transparency indicates operational stability and reduces investor uncertainty. Investors can pay attention to the following indicators: (1) Shareholder structure changes. Regularly updated shareholder structure changes indicate the transparency of the company and reduce investor uncertainty. (2) Internal operational disclosure. Pay attention to whether the company provides clear organizational charts, division of responsibilities between departments, and other information. Higher organizational transparency can enhance understanding of a company's operational capabilities, thereby boosting investment confidence. (3) Employee turnover rate. Employee stability is a measure of operational capability. Investors can evaluate employee turnover to assess the internal management efficiency of the company. C. Transparency of Accounting Information The regression analysis shows the strongest correlation between accounting transparency and financial performance. Investors are advised to pay attention to companies with high financial transparency, as accounting transparency has the strongest correlation with investor confidence. Investors are advised to closely monitor financial disclosures, with a focus on companies with high average scores in financial transparency (such as detailed revenue reports and consistent tracking of research and development expenditures). These indicators help investors measure a company's financial condition and make reliable investment decisions, including: (1) Accuracy and timeliness of financial statements. Such as R&D expenses, asset liability ratios, and revenue source breakdowns in annual financial reports. (2) Financial statement review. Ensure that the company's financial data has been audited by a third-party and has reliability and authority. (3) Frequency of financial statement disclosure. The high- tech industry has high volatility, and frequent financial updates help investors track the financial health of the enterprise. 3.6.2. Analyze Financial Performance and Market value Financial performance and market value are important factors in evaluating high-tech companies. The previous data results provide key performance indicators that investors are advised to pay attention to when analyzing these aspects. A. Financial performance indicators Strong financial performance is positively correlated with investor confidence. Key financial indicators such as revenue, profit, and return on equity (ROE) reveal a company's profitability and growth potential. High earnings per share and return on equity scores are consistent with strong investor confidence. Investors are advised to prioritize companies with high financial performance indicators to maximize their return potential. Indicators to consider: (1) Sales revenue. Continuous revenue growth is a sign of the company's market demand and customer base expansion. For high-tech companies, this growth is often related to innovation. (2) Net profit. A positive net profit margin reflects effective cost management and market competitiveness. 306 (3) Earnings per Share (EPS). EPS is crucial for evaluating shareholder value, especially in companies that prioritize growth. (4) Return on Equity (ROE). ROE represents the efficiency with which a company generates profits from shareholder investments. High ROE is a powerful indicator of financial health and effective management. B. Market Value Indicator Market value reflects investors' expectations for future growth, making it an important component of investment decisions. Stock price trend and price to earnings ratio are important indicators of market expectations. Investors are advised to pay attention to companies with positive market capitalization indicators to meet favorable growth expectations. Indicators to consider: (1) Stock price trend. A stable or upward trend in stock prices indicates positive investor sentiment and a perception of growth potential. (2) Price to earnings ratio. A higher P/E ratio typically indicates investors' expected growth, although it should be considered in conjunction with other indicators to ensure accuracy. (3) Market share and position. Companies with strong market influence are more resilient to competitive threats and economic fluctuations. (4) Total market value. A larger total market value usually reflects stability, while a smaller total market value may provide higher growth potential but increase risk. 3.6.3. Focus on the development potential and innovation capability of enterprises High tech enterprises face unique uncertainties in terms of technological progress and market changes. Therefore, it is particularly important to accurately assess a company's growth potential and innovation capabilities. The previous regression analysis results revealed that investor confidence plays a key moderating role between information transparency and company value. This confidence mainly stems from investors' trust in the development prospects of the enterprise and the stability of their shareholding, further highlighting investors' confidence in the potential for enterprise development and technological progress, as an important driving force for promoting corporate value growth. In the high-tech industry, due to the rapid innovation cycle, confidence in development and stability of shareholding are particularly important. Enterprises with stable innovation output are more conducive to achieving sustained growth. When evaluating the growth potential and innovation capability of a company, the following indicators need to be considered: (1) R&D intensity. Companies with higher R&D expenditures may be more likely to maintain competitiveness and innovation capabilities compared to those with higher revenues. Investors are advised to evaluate the consistency of a company's R&D investment as a signal of commitment to future growth. (2) Innovation achievements. Look for companies that regularly disclose technological breakthroughs, patents, or product releases. High innovation output often aligns with a company's long-term market positioning, demonstrating its innovation strength and market competitiveness. (3) Strategic planning. Evaluate the transparency of the company's future growth strategy. Companies that disclose their strategic goals and their implementation methods often have a clearer vision and plan for sustained growth. Investors are advised to pay attention to the strategic planning of these companies to assess their future growth potential and market competitiveness. (4) Shareholder communication strategy. As shown in the previous analysis, companies that regularly update shareholder information can enhance shareholder confidence, contribute to overall investment stability, and align with company goals. Therefore, investors are advised to prioritize companies with clear shareholder communication strategies, such as frequent updates and detailed disclosures of company initiatives during shareholder meetings, to ensure alignment with the company's vision and strategy. This communication strategy not only helps to boost investor confidence, but also promotes a good relationship between the company and investors, jointly driving the long-term development of the enterprise. 4. Conclusions Based on the study's results, this study found that the information transparency of high-tech companies in the province of Guangdong had a significant positive impact on the corporate value, with governance, organizational, and accounting transparency all contributing significantly to enhancing the value of enterprises. Focusing on high-tech companies in Guangdong, the study explored the significant positive impact of information transparency on investor confidence. Additionally, the study delved into the moderating effect of investor confidence in the relationship between information transparency and company value, with research results indicating that when investor confidence was higher, the effect of information transparency on corporate value was more pronounced. Consequently, the study proposes an investment guide for high-tech company investors in Guangdong, designed to optimize investment returns and minimize risks. While this study sheds light on the interplay between information transparency, investor confidence, and corporate value, it also opens avenues for future research to delve deeper into the interaction mechanisms between corporate transparency and investor confidence across different industries and regions. Additionally, as technology and financial markets evolve, future studies could investigate how fin-tech innovation or shifts in regulatory policies might affect transparency, investor confidence, and corporate value. 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