ig data analytics in healthcare

: are end-users ready?

Abstract

This dissertation aims to understand if end-users are aware of big data analytics, and given this, if the perceived value of healthcare products that use big data techniques is sufficient to surpass their concerns for sharing personal data. Additionally, it is tested whether they are interested in purchasing such products. In order to address this topic, the theoretical foundations are based on the Theory of Reasoned Model, which studies human’s decision-making process. Based on the data from a questionnaire directed to end-users, a Chi-square test studies if it exists an association between the different variables and Simple Linear Regressions evaluate the strength of the associations. The results obtained from both type of tests prove that a higher perception of value from health products that require the use of big data technologies (PV) is positively correlated with a superior willingness to share personal data (WTS), as well as a higher willingness to buy (WTB), a positive word of mouth for both sharing data (WoM_sd) and purchasing such devices (WoM_d). Finally, three Multiple Regression models are created. The first model explains WTB as a positive influence of PV, WTS, WoM_d and WoM_sd. The second regression tests the WoM_d dimension as a result of PV, WTB and WTS. The third model shows that WoM_sd is explained by PV, WTB and WTS. These three models are in line with the previous conclusions obtained from both the Chi-Square test and the Simple Linear Regressions.

Date of Award	2014
Original language	English
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Paulo Amaral (Supervisor)