Third-party Big Data Platforms And Voluntary Information Disclosure By Enterprise

The disclosure of customer identities by companies plays a crucial role in evaluating various aspects of the company’s operations,such as its business model,market position,and financial stability.Hence,investors and analysts have consistently exhibited a high demand for information related to a company’s customers.The disclosure rate of customer identity information by listed companies in China has been continuously decreasing since 2014,falling below 10% in 2021.This severe mismatch between the demand and supply of customer identity information warrants deep contemplation.In recent years,the volume of global data has experienced explosive growth.Third-party data platforms,based on big data technology,have significantly reduced the cost of information acquisition and processing for investors through methods such as information collection,cleaning,and analysis.As a result,an increasing number of investors,particularly individual ones,are relying on these platforms for investment decision-making.This trend has had a significant impact on the information demand-supply environment of China’s capital market.However,there is still relatively little discussion in the existing literature regarding this impact.Therefore,this study aims to address this gap by examining how these platforms affect the disclosure decisions of Chinese companies.This research has important practical implications and contributes to the academic literature on this topic.This study contends that the advent of third-party big data platforms which integrate mandatory disclosure information may alter the benefit and cost functions of firms’ disclosure of customer identity information,ultimately reducing their willingness to disclose information about major clients.On the one hand,these thirdparty platforms utilize big data to establish stakeholder information associations and provide information on operating risks,sensitive public opinion,judicial risks,and other factors.The disclosure of major customer identity information by firms may result in the risk of negative supply chain information.On the other hand,although third-party platforms have reduced the cost of information acquisition for investors,especially for small and medium-sized ones,these investors may struggle to understand the prevalent relationship-based transaction model in the Chinese capital market.Overreliance or misunderstandings of the platform’s information may lead investors to make ill-informed investment decisions,potentially causing negative publicity and stock price volatility for firms.Poor stock performance and negative publicity crises can potentially become reasons for shareholders to dismiss the current management team in a battle for control.Therefore,after the launch of big data platforms,management teams may be more inclined to refrain from disclosing customer identity information to reduce the cost of disclosure and the potential risk of job loss.To address these issues,this study aims to answer three key questions regarding the impact of thirdparty big data platforms on the disclosure decisions of corporate customer identity information:(1)Will the establishment of third-party big data platforms reduce firms’ willingness to disclose information about their major customers?(2)Which types of firms will experience the greatest reduction in disclosure?(3)Will firms increase voluntary disclosure in other areas to mitigate the rise in information asymmetry costs resulting from a reduction in the disclosure of major customer identity information?This study creates a supply chain database with data on the trading and risk relationships between Chinese listed companies and their top five customers,using customer identity information disclosed by A-share listed companies in the Shanghai and Shenzhen stock exchanges from 2009 to 2018,as well as customer risk information obtained through Python software crawling on third-party big data platforms.The study analyzes the impact of third-party big data platforms on the voluntary information disclosure behavior of Chinese firms,focusing on management’s proprietary costs in disclosing customer identity information,the costs incurred by investors in processing such information,and alternative disclosure mechanisms.The study considers prevalent relationship-based transaction characteristics in Chinese society and the high level of participation of individual investors in the capital market to reveal the pathways through which third-party big data platforms affect the voluntary information disclosure behavior of Chinese firms.This study finds that companies tend to decrease their disclosure of customer identity information following the introduction of third-party big data platforms.From the perspective of the heterogeneity of proprietary costs in disclosing customer identity information by management:(1)Firms that rely more heavily on relationship-based business models are more prone to reduce the disclosure of customer identity information;(2)Firms that engage in higher degrees of earnings management are more disposed to withholding the identities of their top five customers;(3)The greater the participation of individual investors in a company,the more likely it is to curb the disclosure of customer identity information.That is,a firm’s susceptibility to "retail trading" is an important factor in its considerations for adjusting customer disclosure policies;(4)If a company receives negative attention and criticism on social media,they may worry that investors will also become skeptical,leading to a negative impact on public opinion.As a result,they may choose to limit the disclosure of customer identity information.(5)Additionally,customers who are deemed high-risk could potentially spread risk to the supply chain,prompting companies to limit the disclosure of their identity information to minimize this risk.From the perspective of the heterogeneity of investors’ costs in handling customer identity information:(6)The third-party big data platforms are particularly effective in reducing integration costs for customer identity data that is harder to obtain and has lower levels of information transparency.Consequently,customers with these characteristics may be more reluctant to disclose their identity information once the platform becomes available.Subsequent research has utilized various machine learning prediction algorithms to confirm that warning information on the third-party big data platform,including customer risk,public opinion,and social security,has a significant influence on a company’s decision to disclose customer identity information.Finally,considering the ramifications of companies limiting the disclosure of customer identity information,the study found that:(7)Following the introduction of big data platforms,companies decreased their disclosure of "hard" customer identity information.However,they increased their disclosure of "soft" information in management discussion and analysis(MD&A)to convey a positive signal to external investors.Specifically,companies that limited their disclosure of customer identity information had a more positive tone in their MD&A texts and included more information regarding sales performance to offset the increased costs of information asymmetry resulting from reduced customer identity information disclosure.To summarize,third-party big data platforms have increased the cost of disclosing customer identity information for enterprises and reduced management’s willingness to disclose such information.This study contributes to the literature in the following ways:Firstly,it is the first to examine the impact of third-party big data platforms on management’s voluntary information disclosure decisions from the perspective of China’s institutional background.Existing research has primarily focused on how big data technology and alternative data can be used by professional investors to constrain management’s opportunistic behavior.In contrast,this study explores the impact of mandatory information disclosure integrated by third-party big data platforms and finds that as the integration cost of non-professional investors’ information reduces,management’s willingness to voluntarily disclose information also decreases.Additionally,the customer identity information is private information that investors can perceive,providing new ways for research on information processing costs.Secondly,by introducing the implementation of third-party big data platforms as an exogenous shock to the investor information environment,this study alleviates the endogeneity problem that exists when testing proprietary cost theory in existing research.Existing literature on this theory’s testing is mainly based on company crosssectional characteristics,the study enriches the relevant literature on the impact of proprietary costs on information disclosure.Thirdly,the study introduces novel ideas for utilizing unstructured and real-time text big data to predict micro-enterprise behavior,thereby promoting interdisciplinary research across artificial intelligence,machine learning,economics,and management.Finally,this study is of practical significance,especially considering the growing importance of information disclosure in the capital market amid China’s ongoing Registration System Reform.Nevertheless,there exists a substantial discrepancy between the demand and supply of customer identity information in the market.To address this issue,regulatory bodies should strengthen the disclosure requirements for enterprise supply chain information and enhance oversight of big data platforms’ public information processing to improve the overall reliability of the capital market information environment.