With an accelerating increase of business benefits produced from big data analytics (if used appropriately and intelligently by businesses in the private and public sectors), this study focused on empirically identify...With an accelerating increase of business benefits produced from big data analytics (if used appropriately and intelligently by businesses in the private and public sectors), this study focused on empirically identifying the big data analytics (BDA) attributes. These attributes were classified into four groups (i.e., value innovation, social impact, precision, and completeness of BDA quality) and were found to influence the decision-making performance and business performance outcomes. A structural equation modeling analysis using 382 responses from a BDA related to practitioners indicated that the attributes of representativeness, predictability, interpretability, and innovativeness as related to value innovation greatly enhanced the decision-making confidence and effectiveness of decision makers who make decisions using big data. In addition, individuality, collectivity, and willfulness, which are related to social impact, also greatly improved the decision-making confidence and effectiveness of the same decision makers. This shows that the value innovation and social impact, which have received relatively less attention in previous studies, are the crucial attributes for BDA quality as they influence the decision-making performance. Comprehensiveness, factuality, and realism, which are linked to completeness, also have similar results. Furthermore, the higher the decision-making confidence of the decision makers who used big data was, the higher the financial performance of their companies. In addition, high decision-making confidence using big data was found to improve the nonfinancial performance metrics such as customer satisfaction and quality levels as well as product development capabilities. High decision-making effectiveness with big data was also shown to improve the nonfinancial performance metrics.展开更多
In this study,the impact of business and financial information integration(BFⅡ)on the voluntary management earnings forecasts(VMEFs)of listed firms in China between 2008 and 2018 is investigated.Drawing on litigation...In this study,the impact of business and financial information integration(BFⅡ)on the voluntary management earnings forecasts(VMEFs)of listed firms in China between 2008 and 2018 is investigated.Drawing on litigation cost and ability signaling theories,we find that the adoption of BFⅡencourages top managers to disclose VMEFs.BFⅡfirms are identified through the textual analysis of management discussion and analysis(MD&A)reports,and the empirical results indicate that BFⅡfirms have a higher probability and frequency of issuing VMEFs than non-BFⅡfirms.The results remain robust after we identify causality by applying a propensity score matching and difference-in-differences(PSM-DID)test and use an alternate measure of BFⅡ.Further tests show that BFⅡfirms issue more accurate VMEFs and are able to issue them at an earlier stage.We also find that the positive relationship between BFⅡand VMEFs is weakened if the media expresses concern about the uncertainty of BFⅡadoption.展开更多
文摘With an accelerating increase of business benefits produced from big data analytics (if used appropriately and intelligently by businesses in the private and public sectors), this study focused on empirically identifying the big data analytics (BDA) attributes. These attributes were classified into four groups (i.e., value innovation, social impact, precision, and completeness of BDA quality) and were found to influence the decision-making performance and business performance outcomes. A structural equation modeling analysis using 382 responses from a BDA related to practitioners indicated that the attributes of representativeness, predictability, interpretability, and innovativeness as related to value innovation greatly enhanced the decision-making confidence and effectiveness of decision makers who make decisions using big data. In addition, individuality, collectivity, and willfulness, which are related to social impact, also greatly improved the decision-making confidence and effectiveness of the same decision makers. This shows that the value innovation and social impact, which have received relatively less attention in previous studies, are the crucial attributes for BDA quality as they influence the decision-making performance. Comprehensiveness, factuality, and realism, which are linked to completeness, also have similar results. Furthermore, the higher the decision-making confidence of the decision makers who used big data was, the higher the financial performance of their companies. In addition, high decision-making confidence using big data was found to improve the nonfinancial performance metrics such as customer satisfaction and quality levels as well as product development capabilities. High decision-making effectiveness with big data was also shown to improve the nonfinancial performance metrics.
基金financial support from the National Natural Science Foundation of China(Grant No.71902210)the Youth Research Fund of the Ministry of Education for Humanities and Social Sciences(Grant No.19YJC630092)+2 种基金the Program for Innovation Research in Central University of Finance and Economics(Grant No.CUFE 20190111)Social Science Foundation of Guangdong Province of China(Grant No.GD19CGL05)Graduate Research and Innovation Fund Project of Central University of Finance and Economics(Grant No.20182Y006)
文摘In this study,the impact of business and financial information integration(BFⅡ)on the voluntary management earnings forecasts(VMEFs)of listed firms in China between 2008 and 2018 is investigated.Drawing on litigation cost and ability signaling theories,we find that the adoption of BFⅡencourages top managers to disclose VMEFs.BFⅡfirms are identified through the textual analysis of management discussion and analysis(MD&A)reports,and the empirical results indicate that BFⅡfirms have a higher probability and frequency of issuing VMEFs than non-BFⅡfirms.The results remain robust after we identify causality by applying a propensity score matching and difference-in-differences(PSM-DID)test and use an alternate measure of BFⅡ.Further tests show that BFⅡfirms issue more accurate VMEFs and are able to issue them at an earlier stage.We also find that the positive relationship between BFⅡand VMEFs is weakened if the media expresses concern about the uncertainty of BFⅡadoption.