Pub Date : 2024-07-14DOI: 10.1016/j.cjar.2024.100375
Yanxi Li, Duo Wang, Delin Meng, Yunge Hu
In this study, we examine the peer effect on climate risk information disclosure by analyzing A-share listed companies in China. We find that industry peers influence target firms’ climate risk information disclosure through active (passive) imitation resulting from cost–benefit considerations (institutional pressures). Leader companies are more likely to be emulated by within-industry follower companies and target firms prefer to learn from similar within-industry firms. Executive overconfidence and performance pressure negatively affect target firms’ willingness to emulate their peers. Finally, the peer effect of climate risk information disclosure demonstrates a regional aspect. Our findings have implications for reasonable climate risk information disclosure at the micro level and effective regulation to move toward achieving carbon peak/neutrality at the macro level.
在本研究中,我们通过分析中国 A 股上市公司,研究了同行效应对气候风险信息披露的影响。我们发现,行业同行会通过成本收益考虑(制度压力)导致的主动(被动)模仿来影响目标公司的气候风险信息披露。领先企业更容易被行业内的追随者企业效仿,而目标企业则更愿意向行业内的同类企业学习。高管过度自信和业绩压力会对目标企业效仿同行的意愿产生负面影响。最后,气候风险信息披露的同行效应体现了区域性。我们的研究结果对微观层面上合理的气候风险信息披露和宏观层面上实现碳峰值/中性的有效监管具有启示意义。
{"title":"Peer effect on climate risk information disclosure","authors":"Yanxi Li, Duo Wang, Delin Meng, Yunge Hu","doi":"10.1016/j.cjar.2024.100375","DOIUrl":"10.1016/j.cjar.2024.100375","url":null,"abstract":"<div><p>In this study, we examine the peer effect on climate risk information disclosure by analyzing A-share listed companies in China. We find that industry peers influence target firms’ climate risk information disclosure through active (passive) imitation resulting from cost–benefit considerations (institutional pressures). Leader companies are more likely to be emulated by within-industry follower companies and target firms prefer to learn from similar within-industry firms. Executive overconfidence and performance pressure negatively affect target firms’ willingness to emulate their peers. Finally, the peer effect of climate risk information disclosure demonstrates a regional aspect. Our findings have implications for reasonable climate risk information disclosure at the micro level and effective regulation to move toward achieving carbon peak/neutrality at the macro level.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100375"},"PeriodicalIF":1.9,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000339/pdfft?md5=13834dff435e5c04c3a4bdd2de4d5536&pid=1-s2.0-S1755309124000339-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141709601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1016/j.cjar.2024.100374
Xinwu Li, Zixi Ling, Zhe Li, Liyi Zhu
The application of big data technology to global tax management is becoming increasingly widespread. China has been implementing increasingly mature technologies for tax governance using big data systems in recent years. By collecting data through web scraping on the earliest implementation times of big data tax administration in various provinces of China, we explore the relationship between big data tax administration and corporate bank credit in emerging markets. Our results show that big data tax administration enhances firms’ ability to obtain bank loans. Mechanism tests indicate that big data tax administration improves the quality of corporate information disclosure, facilitating access to bank credit loans. We find that big data tax administration improves the corporate financing environment, enhancing the efficiency of resource allocation in the credit market.
{"title":"Does big data tax administration expand bank credit loans?","authors":"Xinwu Li, Zixi Ling, Zhe Li, Liyi Zhu","doi":"10.1016/j.cjar.2024.100374","DOIUrl":"10.1016/j.cjar.2024.100374","url":null,"abstract":"<div><p>The application of big data technology to global tax management is becoming increasingly widespread. China has been implementing increasingly mature technologies for tax governance using big data systems in recent years. By collecting data through web scraping on the earliest implementation times of big data tax administration in various provinces of China, we explore the relationship between big data tax administration and corporate bank credit in emerging markets. Our results show that big data tax administration enhances firms’ ability to obtain bank loans. Mechanism tests indicate that big data tax administration improves the quality of corporate information disclosure, facilitating access to bank credit loans. We find that big data tax administration improves the corporate financing environment, enhancing the efficiency of resource allocation in the credit market.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100374"},"PeriodicalIF":1.9,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000327/pdfft?md5=f0a99d0033b1a89f76fa724dfa33c5c1&pid=1-s2.0-S1755309124000327-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141703477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1016/j.cjar.2024.100371
Tong Lu , Lijun Ruan , Yanyan Wang , Lisheng Yu
{"title":"Corrigendum to “Real effects of greenhouse gas disclosures” [China Journal of Accounting Research, 17(2), (2024) 100360]","authors":"Tong Lu , Lijun Ruan , Yanyan Wang , Lisheng Yu","doi":"10.1016/j.cjar.2024.100371","DOIUrl":"10.1016/j.cjar.2024.100371","url":null,"abstract":"","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100371"},"PeriodicalIF":1.9,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000297/pdfft?md5=27b73a147f46b683b2bb0fbeea1e5095&pid=1-s2.0-S1755309124000297-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141962027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-19DOI: 10.1016/j.cjar.2024.100373
Lei Zhu , Qianwen Zheng , Yubin Li
To improve the usefulness of audit opinions, on 23 March 2021, the China Securities Regulatory Commission mandated that auditors disclose overall quantitative materiality of consolidated financial statements in special explanations of modified audit opinions. This paper selects Chinese A-share companies issued with modified audit opinions for the period of 2020–2022 as the research sample and analyzes the assessment of materiality in audit practice and the informativeness of audit materiality. Our findings are as follows. (1) The most commonly used bases for materiality by auditors are profit and income, with considerable differences in the percentages applied to the different bases and variations even within the same base. (2) The higher the materiality amount, the poorer the audit quality. This negative correlation is mainly observed in scenarios where the audited companies engage in downward earnings management and where the competency of audit firms or auditors is relatively low. (3) Companies that disclose quantitative materiality in the special explanations of modified audit opinions have a lower earnings response coefficient than companies that do not disclose audit materiality. This research sheds light on the “black box” of the audit process and verifies the information value of audit materiality. The conclusions are of significant value to auditing standard-setters, investors and regulators.
{"title":"Is audit materiality informative? Evidence from China","authors":"Lei Zhu , Qianwen Zheng , Yubin Li","doi":"10.1016/j.cjar.2024.100373","DOIUrl":"10.1016/j.cjar.2024.100373","url":null,"abstract":"<div><p>To improve the usefulness of audit opinions, on 23 March 2021, the China Securities Regulatory Commission mandated that auditors disclose overall quantitative materiality of consolidated financial statements in special explanations of modified audit opinions. This paper selects Chinese A-share companies issued with modified audit opinions for the period of 2020–2022 as the research sample and analyzes the assessment of materiality in audit practice and the informativeness of audit materiality. Our findings are as follows. (1) The most commonly used bases for materiality by auditors are profit and income, with considerable differences in the percentages applied to the different bases and variations even within the same base. (2) The higher the materiality amount, the poorer the audit quality. This negative correlation is mainly observed in scenarios where the audited companies engage in downward earnings management and where the competency of audit firms or auditors is relatively low. (3) Companies that disclose quantitative materiality in the special explanations of modified audit opinions have a lower earnings response coefficient than companies that do not disclose audit materiality. This research sheds light on the “black box” of the audit process and verifies the information value of audit materiality. The conclusions are of significant value to auditing standard-setters, investors and regulators.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100373"},"PeriodicalIF":1.9,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000315/pdfft?md5=9839298c039c85ddd4fd1c3b87950d85&pid=1-s2.0-S1755309124000315-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-13DOI: 10.1016/j.cjar.2024.100372
The deep integration of artificial intelligence (AI) into enterprises presents both opportunities and challenges, making it a focal point of current research. This study explores the impact of AI on corporate risk-taking, using data spanning 2010–2019 from A-share listed companies in China. Our findings suggest that AI significantly heightens companies’ level of risk-taking. Furthermore, financing constraints can amplify the relationship between AI and risk-taking, enhancing their sensitivity correlation. AI also significantly improves firms’ investment efficiency and mitigates their underinvestment issues. Finally, mediation tests indicate that AI enhances risk-taking by diminishing firms’ risk perception. Overall, we offer valuable insights into and references for accelerating the deep integration of AI into enterprises.
人工智能(AI)与企业的深度融合既带来了机遇,也带来了挑战,因此成为当前研究的一个焦点。本研究利用中国 A 股上市公司 2010-2019 年的数据,探讨了人工智能对企业风险承担的影响。我们的研究结果表明,人工智能大大提高了企业的风险承担水平。此外,融资约束会放大人工智能与风险承担之间的关系,增强二者的敏感相关性。人工智能还能明显提高企业的投资效率,缓解投资不足问题。最后,中介测试表明,人工智能通过降低企业的风险意识来增强风险承担能力。总之,我们为加速人工智能与企业的深度融合提供了宝贵的见解和参考。
{"title":"Artificial intelligence and corporate risk-taking: Evidence from China","authors":"","doi":"10.1016/j.cjar.2024.100372","DOIUrl":"10.1016/j.cjar.2024.100372","url":null,"abstract":"<div><p>The deep integration of artificial intelligence (AI) into enterprises presents both opportunities and challenges, making it a focal point of current research. This study explores the impact of AI on corporate risk-taking, using data spanning 2010–2019 from A-share listed companies in China. Our findings suggest that AI significantly heightens companies’ level of risk-taking. Furthermore, financing constraints can amplify the relationship between AI and risk-taking, enhancing their sensitivity correlation. AI also significantly improves firms’ investment efficiency and mitigates their underinvestment issues. Finally, mediation tests indicate that AI enhances risk-taking by diminishing firms’ risk perception. Overall, we offer valuable insights into and references for accelerating the deep integration of AI into enterprises.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100372"},"PeriodicalIF":1.9,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000303/pdfft?md5=0229d4a6f38a056adb4df35c0e533ead&pid=1-s2.0-S1755309124000303-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141396173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-13DOI: 10.1016/j.cjar.2024.100370
In this study, we take a machine learning-based approach to measure institutional investor attention to corporate social responsibility (CSR) issues when communicating with firms during site visits. We find that institutional investors can effectively enhance CSR performance through CSR-related communication. This effect remains robust to various checks and is more pronounced for non-state-owned enterprises and firms with lower levels of institutional ownership and in periods following the issuance of Green Investment Guidelines. We also identify information asymmetry and financing constraints as the two mechanisms underlying this effect. Overall, our findings highlight the importance of private interactions between management and institutional investors in promoting CSR.
{"title":"Does investor communication improve corporate social responsibility? A machine learning-based textual analysis","authors":"","doi":"10.1016/j.cjar.2024.100370","DOIUrl":"10.1016/j.cjar.2024.100370","url":null,"abstract":"<div><p>In this study, we take a machine learning-based approach to measure institutional investor attention to corporate social responsibility (CSR) issues when communicating with firms during site visits. We find that institutional investors can effectively enhance CSR performance through CSR-related communication. This effect remains robust to various checks and is more pronounced for non-state-owned enterprises and firms with lower levels of institutional ownership and in periods following the issuance of Green Investment Guidelines. We also identify information asymmetry and financing constraints as the two mechanisms underlying this effect. Overall, our findings highlight the importance of private interactions between management and institutional investors in promoting CSR.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100370"},"PeriodicalIF":1.9,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000285/pdfft?md5=3bb57adbb0b07505bee4dc75c751fae2&pid=1-s2.0-S1755309124000285-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141400448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-25DOI: 10.1016/j.cjar.2024.100362
Yani Sun , Yuezhe Shen , Qingmei Tan
This study investigates whether and how customer firms’ environmental, social and governance (ESG) performance impacts suppliers’ green innovation quality using a sample of Chinese A-share listed companies from 2009 to 2022. We find that customers’ ESG performance facilitates suppliers’ green innovation quality through green learning and corporate competition. Additional tests indicate that customers with stickier customer–supplier relationships and a more central position in the supply chain network than peers enhance suppliers’ green innovation quality. After categorizing whether customers engage in greenwashing, we determine that those adherence to green principles, genuinely promote suppliers’ green innovation quality. Finally, we find the above effect ultimately enhances suppliers’ environmental performance. This study provides valuable insights for supply chain companies into collaboratively achieving sustainable development.
本研究以 2009 年至 2022 年中国 A 股上市公司为样本,探讨了客户企业的环境、社会和治理(ESG)绩效是否以及如何影响供应商的绿色创新质量。我们发现,客户的环境、社会和治理绩效通过绿色学习和企业竞争促进了供应商的绿色创新质量。其他测试表明,与同行相比,客户与供应商关系更紧密、在供应链网络中处于更核心地位的客户会提高供应商的绿色创新质量。在对客户是否进行绿色清洗进行分类后,我们确定那些坚持绿色原则的客户真正促进了供应商的绿色创新质量。最后,我们发现上述效应最终会提高供应商的环境绩效。本研究为供应链企业协同实现可持续发展提供了宝贵的启示。
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Pub Date : 2024-05-22DOI: 10.1016/j.cjar.2024.100363
This research contributes to understanding the spillover effect of customer digital transformation along the supply chain. We take a supply chain relationship perspective to explore the influence of customers’ digital transformation on suppliers’ audit fees and find a significant reduction in such fees when customers undergo digital transformation. An economic mechanism analysis reveals that this transformation reduces audit fees by lowering the risks and costs encountered by auditors. This is achieved by mitigating suppliers’ business risks and improving earnings quality. Heterogeneity analysis reveals that the impact of customers’ digital transformation on suppliers’ audit fees is more pronounced when the supply chain is geographically distant, suppliers with more specific investments and with high levels of market competition.
{"title":"Spillover effect of digital transformation along the supply chain: From the perspective of suppliers’ audit fees","authors":"","doi":"10.1016/j.cjar.2024.100363","DOIUrl":"10.1016/j.cjar.2024.100363","url":null,"abstract":"<div><p>This research contributes to understanding the spillover effect of customer digital transformation along the supply chain. We take a supply chain relationship perspective to explore the influence of customers’ digital transformation on suppliers’ audit fees and find a significant reduction in such fees when customers undergo digital transformation. An economic mechanism analysis reveals that this transformation reduces audit fees by lowering the risks and costs encountered by auditors. This is achieved by mitigating suppliers’ business risks and improving earnings quality. Heterogeneity analysis reveals that the impact of customers’ digital transformation on suppliers’ audit fees is more pronounced when the supply chain is geographically distant, suppliers with more specific investments and with high levels of market competition.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 3","pages":"Article 100363"},"PeriodicalIF":1.9,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000212/pdfft?md5=322dbc9f90606710ac9db364a64853cc&pid=1-s2.0-S1755309124000212-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141140919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-17DOI: 10.1016/j.cjar.2024.100360
Tong Lu , Lijun Ruan , Yanyan Wang , Lisheng Yu
This study investigates the valuation and real effects of the mandatory disclosure of greenhouse gas (GHG) emission costs from the perspective of “double materiality.” We consider a firm with a Cobb-Douglas production function that combines GHG-related and non-GHG-related investments to produce short-term and long-term returns. In particular, the GHG-related investment entails short-term and long-term social costs of GHG emissions, including corporate costs and negative externalities. We demonstrate how the mandatory disclosure of the long-term costs of GHG emissions affects capital market valuations and corporate investment decisions relative to a non-disclosure regime. The social welfare in an accounting regime hinges on three parameters: the persistence of the short-term investment return, the ratio of the productivity of GHG-related investment to that of non-GHG-related investment, and the social cost parameter for GHG emissions. Our findings suggest that disclosing the long-term costs of GHG emissions may be detrimental to social welfare. Specifically, the non-disclosure regime results in higher social welfare than the disclosure regime for high values of these parameters.
{"title":"Real effects of greenhouse gas disclosures","authors":"Tong Lu , Lijun Ruan , Yanyan Wang , Lisheng Yu","doi":"10.1016/j.cjar.2024.100360","DOIUrl":"10.1016/j.cjar.2024.100360","url":null,"abstract":"<div><p>This study investigates the valuation and real effects of the mandatory disclosure of greenhouse gas (GHG) emission costs from the perspective of “double materiality.” We consider a firm with a Cobb-Douglas production function that combines GHG-related and non-GHG-related investments to produce short-term and long-term returns. In particular, the GHG-related investment entails short-term and long-term social costs of GHG emissions, including corporate costs and negative externalities. We demonstrate how the mandatory disclosure of the long-term costs of GHG emissions affects capital market valuations and corporate investment decisions relative to a non-disclosure regime. The social welfare in an accounting regime hinges on three parameters: the persistence of the short-term investment return, the ratio of the productivity of GHG-related investment to that of non-GHG-related investment, and the social cost parameter for GHG emissions. Our findings suggest that disclosing the long-term costs of GHG emissions may be detrimental to social welfare. Specifically, the non-disclosure regime results in higher social welfare than the disclosure regime for high values of these parameters.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 2","pages":"Article 100360"},"PeriodicalIF":3.6,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000182/pdfft?md5=e61b9fb620d5cdc8b5cf20a771d90077&pid=1-s2.0-S1755309124000182-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141044740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.1016/j.cjar.2024.100361
Ashraf Khallaf , Yezen Kannan
We investigate how the accounting treatment of intangible assets on managers’ likelihood of issuing voluntary earnings guidance (MEF). We find that unrecognized intangibles (immediately expensed) are negatively associated with MEF issuance, while recognized intangibles (capitalized) show a positive association. These findings hold across various factors such as analysts’ coverage, industry type and for a subsample that excludes software firms permitted to capitalize software development costs under SFAS No. 86. In additional, we investigate the cross-sectional determinants of MEF issuance based on the characteristics of firm intangibility. We find a significant increase in the likelihood of MEF issuance for higher unrecognized intangibles with greater earnings uncertainty. This suggests that managers may prioritize delivering value-relevant information to market participants to alleviate uncertainty.
{"title":"Intangibles and management earnings forecasts","authors":"Ashraf Khallaf , Yezen Kannan","doi":"10.1016/j.cjar.2024.100361","DOIUrl":"10.1016/j.cjar.2024.100361","url":null,"abstract":"<div><p>We investigate how the accounting treatment of intangible assets on managers’ likelihood of issuing voluntary earnings guidance (MEF). We find that unrecognized intangibles (immediately expensed) are negatively associated with MEF issuance, while recognized intangibles (capitalized) show a positive association. These findings hold across various factors such as analysts’ coverage, industry type and for a subsample that excludes software firms permitted to capitalize software development costs under SFAS No. 86. In additional, we investigate the cross-sectional determinants of MEF issuance based on the characteristics of firm intangibility. We find a significant increase in the likelihood of MEF issuance for higher unrecognized intangibles with greater earnings uncertainty. This suggests that managers may prioritize delivering value-relevant information to market participants to alleviate uncertainty.</p></div>","PeriodicalId":45688,"journal":{"name":"China Journal of Accounting Research","volume":"17 2","pages":"Article 100361"},"PeriodicalIF":3.6,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755309124000194/pdfft?md5=109cc5806e97ce0cdf47666b038771f4&pid=1-s2.0-S1755309124000194-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141032298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}