Journal of Data, Information and Management
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Published By Springer Science And Business Media LLC

2524-6356, 2524-6364

Author(s):  
Philipp Koncar ◽  
Tiago Santos ◽  
Markus Strohmaier ◽  
Denis Helic

AbstractMonitoring hygiene and motivation factors from Herzberg’s Two-Factor Theory is a popular way of understanding the influential aspects for employee satisfaction and motivation. The increased availability of employee feedback comprised in online employer reviews yields a promising data source to learn more about these influential factors and the theory itself. However, the application of the Two-Factor Theory to such reviews is yet missing. Thus, this article demonstrates how to apply this theory to more than 2 million online employer reviews. For that, review aspects as well as review ratings are leveraged to study factors that influence employee satisfaction with respect to the theory. Based on the gained insights, a prediction experiment is conducted to forecast employee satisfaction through the textual content of reviews. The presented approach identifies relevant aspects for satisfied and dissatisfied employees working in 43 different industries and 4 different countries. Overall, the results indicate that hygiene factors are most relevant for reviewers, while motivation factors are rather incidental. The prediction experiment achieves a mean balanced accuracy of 0.87, suggesting that review text is predictive for employee satisfaction. Further, the article adds useful input to the discussion of the Two-Factor Theory by providing comparative results across a plethora of different employers, industries and countries.


Author(s):  
Priyaa Thavasimani

AbstractData Management of Astronomy Data is often a laborious task and it is even more challenging for the extraordinary amounts of data expected from the world’s largest radio telescope, Square Kilometre Array. There are overt issues in transferring the voluminous data and the traditional data transfer methods are fragile especially for the data transfer between two continents. To address this, a new data transfer framework is proposed and the data transfer is achieved using two steps: international and local transfers. The efficiency of different end-to-end data transfer tools used in is evaluated on different dataset sizes. Further, a comparative study of two IRIS grid data transfer methods is made to understand each methods’ advantages and disadvantages. This study can be used as a reference for the development of future SKA’s data transfer operations.


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