scholarly journals A Study on the Relationship between Public Derivative Big Data and Industrial Policymaking: Taking Bike Sharing as an Example

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Huilin Song
Keyword(s):  
Big Data ◽  
Industrial Policy ◽  
Second Keyword ◽  
Short Text ◽  
Bike Sharing ◽  
Enhancement Method ◽  
Short Text Clustering ◽  
Topic Clustering ◽  
The Relationship ◽  
Smart Government

Smart government is an important part of the smart world. The use of big data analysis technology can effectively improve the government’s ability of fine management. Taking China’s bike-sharing industry as the research object, we study the relationship between public-derived big data and industrial policy. First, a feature-enhanced short text clustering method is proposed to perform topic clustering on publicly derived big data. Second, keyword extraction based on word frequency is used to quantify the text of industrial policy. Finally, time is taken as the main line to analyze the co-occurrence of clustering topics and keywords. The results show that (1) the feature enhancement method we proposed can effectively improve the clustering effect. (2) There is a great correlation between the industrial policy and the information mined by Weibo, but there is an obvious lag. Rational use of public-derived big data will effectively help the industrial policy to be released in a better and faster way.

scholarly journals Impacts of COVID-19 pandemic on user behaviors and environmental benefits of bike sharing: A big-data analysis

2021 ◽  
Vol 285 ◽  
pp. 116429
Author(s):  
Wen-Long Shang ◽  
Jinyu Chen ◽  
Huibo Bi ◽  
Yi Sui ◽  
Yanyan Chen ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Environmental Benefits ◽  
User Behaviors ◽  
Bike Sharing

Dave Snowden on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 12-17 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Theory And Practice ◽  
Content Type ◽  
Face To Face ◽  
The Relationship ◽  
A Company ◽  
Practical Implications ◽  
Scientific Officer

Purpose Dave Snowden has been an important voice in knowledge management over the years. As the founder and chief scientific officer of Cognitive Edge, a company focused on the development of the theory and practice of social complexity, he offers informative views on the relationship between big data/analytics and KM. Design/methodology/approach A face-to-face interview was held with Dave Snowden in May 2015 in Auckland, New Zealand. Findings According to Snowden, analytics in the form of algorithms are imperfect and can only to a small extent capture the reasoning and analytical capabilities of people. For this reason, while big data/analytics can be useful, they are limited and must be used in conjunction with human knowledge and reasoning. Practical implications Snowden offers his views on big data/analytics and how they can be used effectively in real world situations in combination with human reasoning and input, for example in fields from resource management to individual health care. Originality/value Snowden is an innovative thinker. He combines knowledge and experience from many fields and offers original views and understanding of big data/analytics, knowledge and management.

scholarly journals How Do Instant Messages Reduce Psychological Withdrawal Behaviors?—Mediation of Engagement and Moderation of Self-Control

2021 ◽  
Vol 18 (6) ◽  
pp. 2983
Author(s):  
Xia Jiang ◽  
Jing Du ◽  
Tianfei Yang ◽  
Yujing Liu
Keyword(s):  
Instant Messaging ◽  
Cognitive Engagement ◽  
Time Instant ◽  
Self Control ◽  
Emotional Engagement ◽  
Short Text ◽  
Mediating Role ◽  
Withdrawal Behaviors ◽  
The Relationship

Enabling people to send and receive short text-based messages in real-time, instant messaging (IM) is a communication technology that allows instantaneous information exchanges. The development of technology makes IM communication widely adopted in the workplace, which brings a series of changes for modern contemporary working life. Based on the conservation of resource theory (COR), this paper explores the mechanism of workplace IM communication on employees’ psychological withdrawal, and investigates the mediating role of work engagement in the relationship and the moderating role of self-control. Using the experience sampling method (ESM), a 10-consecutive workdays daily study was conducted among 66 employees. By data analysis of 632 observations using SPSS and HLM, results found that: (1) IM demands had a positive relation with emotion and cognitive engagement. (2) Emotion and cognitive engagement were negatively correlated with psychological withdrawal. (3) Emotion and cognitive engagement mediated the relations of IM demands and psychological withdrawal. (4) Self-control moderated the relationship between emotional engagement and psychological withdrawal.

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