Data Science and Digital Collaborations
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ItemA Communication Model that Bridges Knowledge Delivery between Data Miners and Domain Users( 2018-01-03)Findings generated from data mining sometimes are not interesting to the domain users. The problem is that data miners and the domain users do not speak the same language, so human subjectivity towards the domain users’ own fields of knowledge affects the understanding of knowledge generated from data mining. This paper proposes a communication model based on the reference services model in the field of library science in order to bridge the communications between data miners and domain users. The creation of a data liaison specialist role in the data mining team aims at understanding the subjectivity as well as the thinking process of both parties in order to translate knowledge between the two fields and deliver findings to domain users. Through five steps-”data interview, pre-mid evaluation, post-mid evaluation, knowledge delivery, and follow up-”the data liaison specialist can achieve effective knowledge synthesis and delivery to the domain users.
ItemTopic Analysis through Streamgraph via Shiny Application: A Social Collaborative Approach( 2018-01-03)With the increasing complexity and volume of data, the transformation from streaming information into actionable knowledge becomes more and more challenging and requires a synthesis of computational and substantive approaches. In this view, the collaboration between developers and substantive experts is essential for obtaining meaningful and strategic insights. Despite the large number of various platforms and software to develop a customized tool, the main challenge is developing social organizational forms for communication. In this paper, we explore a new method of organization workflow, namely a social collaboration via the rizzoma platform. In particular, we introduce our on-going project for developing a research-driven visualization portal that is responsive to the need of specific research in strategic studies.
ItemThe Effect of Enterprise Crowdsourcing Systems on Employees’ Innovative Behavior and Job Performance( 2018-01-03)Employees are main sources of innovative ideas via their insights of companies’ products, processes, customers, and competitors. Enterprise crowdsourcing systems (ECSs) are used to collect, refine, and realize ideas. However, only a small percent of employees submit ideas - about 7.7% at Pfizer, 2% at HCL Technologies, and 3% at Polaris Industries. Why employee’s participation is low? More specifically, what are the factors that can lead employees to use ECS actively to submit and share their innovative ideas for improving their job performance? In this research, we used a multi-actor dyadic survey to survey 183 employees and their managers and conducted data analysis to understand the impact of ECS factors on employees’ job performance. The findings of this study can help organizations refine their ECSs and innovation initiatives.