This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, ...This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. first, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.展开更多
Public data serves as a fundamental pillar in the advancement of the digital economy.Its importance for unlocking the value associated with information asymmetry has attracted substantial attention in both practice an...Public data serves as a fundamental pillar in the advancement of the digital economy.Its importance for unlocking the value associated with information asymmetry has attracted substantial attention in both practice and theory.We leverage a quasi-natural experiment from China’s local public data openness platforms.Employing data for Ashare listed firms from 2009 to 2021,we use a time-varying difference-in-differences model to systematically examine how public data openness affects corporate stock price crash risk.The results demonstrate that public data openness significantly reduces the accumulation of corporate stock price crash risk.This effect is primarily attributed to lower production of inappropriate information and enhanced information disclosure quality.Further analysis indicates that a supportive institutional environment amplifies the risk-reducing effect of public data openness.This effect is particularly pronounced in firms with strained government-market relationships,non-state ownership,and minimal agency conflicts.These insights highlight the potential that public data openness has for improving information efficiency and facilitating a transition toward digital governance.展开更多
Data represent a crucial production factor and information source for firms’production scheduling and risk management.Exploiting China’s staggered establishment of public data open platforms(PDOPs),I sample Chinese ...Data represent a crucial production factor and information source for firms’production scheduling and risk management.Exploiting China’s staggered establishment of public data open platforms(PDOPs),I sample Chinese A-share listed firms(2010–2022)and apply a staggered difference-in-differences model to investigate how data sharing impacts firm-level supply chain risk.Supply chain risk decreases significantly following PDOP establishment.Data sharing via PDOPs alleviates the“bullwhip effect”and promotes supply chain diversification,mitigating supply chain risks.In more complex firms,those with more advanced digital innovation,as well as non-state-owned firms,data sharing plays a greater role in alleviating supply chain risks.These findings increase awareness of the significance of data resources and offer practical guidance for enterprises’supply chain risk management.展开更多
基金This work was funded by National Natural Science Foundation of China(grant numbers. 51478189 and 51308220)%Natural Science Foundation of Guangdong(grant number 2014A03031326)%Fundamental Research Funds for the Central Universities(grant number 2015ZZ0022)
文摘This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. first, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.
基金supported by the Key R&D Program(Soft Science Project)of Shandong Province,China(Grant No.2024RKY0301).
文摘Public data serves as a fundamental pillar in the advancement of the digital economy.Its importance for unlocking the value associated with information asymmetry has attracted substantial attention in both practice and theory.We leverage a quasi-natural experiment from China’s local public data openness platforms.Employing data for Ashare listed firms from 2009 to 2021,we use a time-varying difference-in-differences model to systematically examine how public data openness affects corporate stock price crash risk.The results demonstrate that public data openness significantly reduces the accumulation of corporate stock price crash risk.This effect is primarily attributed to lower production of inappropriate information and enhanced information disclosure quality.Further analysis indicates that a supportive institutional environment amplifies the risk-reducing effect of public data openness.This effect is particularly pronounced in firms with strained government-market relationships,non-state ownership,and minimal agency conflicts.These insights highlight the potential that public data openness has for improving information efficiency and facilitating a transition toward digital governance.
文摘Data represent a crucial production factor and information source for firms’production scheduling and risk management.Exploiting China’s staggered establishment of public data open platforms(PDOPs),I sample Chinese A-share listed firms(2010–2022)and apply a staggered difference-in-differences model to investigate how data sharing impacts firm-level supply chain risk.Supply chain risk decreases significantly following PDOP establishment.Data sharing via PDOPs alleviates the“bullwhip effect”and promotes supply chain diversification,mitigating supply chain risks.In more complex firms,those with more advanced digital innovation,as well as non-state-owned firms,data sharing plays a greater role in alleviating supply chain risks.These findings increase awareness of the significance of data resources and offer practical guidance for enterprises’supply chain risk management.
