2,017 research outputs found
The Role of Regulatory Foci and Information Seeking Behavior on Self-Disclosure on Social Media
This paper aims to explore the role of Regulatory Foci and Information Seeking Behavior on Self-Disclosure on social media platforms. This research used quantitative research methodology, a self -administrated survey was conducted among generation Y college students. Participants answers were recorded using Google forms and the results were analyzed using structural equation modeling. The Results showed that there was a significant relationship between the Regularity Foci and the Self disclosure. Moreover, the results showed that there was a mediating effect of the Information seeking behavior between Regularity Foci and Self disclosure. The limitation of this study is the sample size (150) and generalizability of the results
Systematic Review on Privacy Categorization
In the modern digital world users need to make privacy and security choices
that have far-reaching consequences. Researchers are increasingly studying
people's decisions when facing with privacy and security trade-offs, the
pressing and time consuming disincentives that influence those decisions, and
methods to mitigate them. This work aims to present a systematic review of the
literature on privacy categorization, which has been defined in terms of
profile, profiling, segmentation, clustering and personae. Privacy
categorization involves the possibility to classify users according to specific
prerequisites, such as their ability to manage privacy issues, or in terms of
which type of and how many personal information they decide or do not decide to
disclose. Privacy categorization has been defined and used for different
purposes. The systematic review focuses on three main research questions that
investigate the study contexts, i.e. the motivations and research questions,
that propose privacy categorisations; the methodologies and results of privacy
categorisations; the evolution of privacy categorisations over time. Ultimately
it tries to provide an answer whether privacy categorization as a research
attempt is still meaningful and may have a future
A machine learning approach to the digitalization of bank customers: evidence from random and causal forests
Understanding the digital jump of bank customers is key to design strategies to bring on
board and keep online users, as well as to explain the increasing competition from new providers of financial services (such as BigTech and FinTech). This paper employs a machine
learning approach to examine the digitalization process of bank customers using a comprehensive consumer finance survey. By employing a set of algorithms (random forests, conditional inference trees and causal forests) this paper identities the features predicting bank
customers’ digitalization process, illustrates the sequence of consumers’ decision-making
actions and explores the existence of causal relationships in the digitalization process. Random forests are found to provide the highest performance–they accurately predict 88.41%
of bank customers’ online banking adoption and usage decisions. We find that the adoption
of digital banking services begins with information-based services (e.g., checking account
balance), conditional on the awareness of the range of online services by customers, and
then is followed by transactional services (e.g., online/mobile money transfer). The diversification of the use of online channels is explained by the consciousness about the range of
services available and the safety perception. A certain degree of complementarity between
bank and non-bank digital channels is also found. The treatment effect estimations of the
causal forest algorithms confirm causality of the identified explanatory factors. These results
suggest that banks should address the digital transformation of their customers by segmenting them according to their revealed preferences and offering them personalized digital services. Additionally, policymakers should promote financial digitalization, designing policies
oriented towards making consumers aware of the range of online services available.FUNCAS Foundation
PGC2018 - 099415 - B - 100 MICINN/FEDER/UEJunta de Andalucia
P18RT-3571
P12.SEJ.246
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