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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Ph.D. Thesis Defense Announcement
ENHANCING PUBLIC SECTOR ORGANIZATION KNOWLEDGE RETENTION WITH
SOCIAL NETWORK ANALYSIS, TEXT MINING AND MACHINE LEARNING
by
Yuzhi Guo
Advisor(s):
Dr. David Frost (CEE)
Committee Members:
Dr. Umit Catalyurek (CSE), Dr. Polo Chau (CSE), Dr. Tuo Zhao (ISyE), Dr. Wei Deng (Google)
Date & Time: 3pm May 7, 2020
Location: https://bluejeans.com/4043985879
Complete announcement, with abstract, is attached
The technical knowledge and expertise possessed by employees are considered amongst an organization’s greatest assets, but are also most vulnerable and can be easily impacted or lost. The loss of experienced employees and important knowledge can put an organization’s competency in great jeopardy. Thus, it is critical to address the challenge of proper knowledge transfer and retention proactively rather than reactively. Public sector organizations have their unique characteristics and are facing emerging HR challenges due to market changes. Most of the current knowledge retention approaches are either outdated and ineffective or developed without considering the features of public sector organizations. A study that overlaps computational and data science techniques with HR data management in light of these features is considered to be a strategic and systematic development that advances existing methods in knowledge retention and overcomes the emerging HR challenges faced by many large public organizations.
In the scope of this work, several data tools are studied for their applications to HR databases, with the objectives of enhancing perception on organization-wide attrition risk distribution, identifying critical knowledge at risk of being lost, and choosing the most suitable provider and recipient for a set of knowledge sharing programs. Moreover, an integrated computational system is developed for Georgia DOT. The system uses an existing HR database and provides modular tools to assist HR personnel strategically plan for a range of activities, aiming for increased level of knowledge transfer and lower employee turnover rate, among other benefits. The system is further evaluated by both user experience feedback, as well as a few “use cases” discussed with the end users.
