TY - JOUR
T1 - Customer data taxonomy
T2 - A multidimensional scaling approach
AU - Córdova-Lavado, Hafid Joseph
AU - Libaque-Saenz, Christian Fernando
PY - 2024
Y1 - 2024
N2 - Privacy concerns have led customer-centric companies to adopt fair information practices to protect their customers’ private information. This situation forces organizations to understand how their consumers perceive their private data when they are disclosed or are already known by the company. This study aims to establish a classification of private data based on customer perceptions to allow companies to address rising privacy concerns. This study developed a two-dimensional map of the positioning of various pieces of information according to customer perceptions. A total of 157 observations were collected online, and multidimensional scaling was used as an analysis technique. The dimensions that explain the resulting classification or spatial map were the degree of exposure customers feel when their data are known and the likelihood that a specific piece of information can identify a particular person.
AB - Privacy concerns have led customer-centric companies to adopt fair information practices to protect their customers’ private information. This situation forces organizations to understand how their consumers perceive their private data when they are disclosed or are already known by the company. This study aims to establish a classification of private data based on customer perceptions to allow companies to address rising privacy concerns. This study developed a two-dimensional map of the positioning of various pieces of information according to customer perceptions. A total of 157 observations were collected online, and multidimensional scaling was used as an analysis technique. The dimensions that explain the resulting classification or spatial map were the degree of exposure customers feel when their data are known and the likelihood that a specific piece of information can identify a particular person.
KW - Pronóstico del precio del cobre
KW - Aprendizaje profundo
KW - Pronóstico multi-horizonte
KW - Redes neuronales recurrentes
KW - Series temporales
KW - Copper price forecasting
KW - Deep learning
KW - Multi-step forecasting
KW - Recurrent neural networks
KW - Time series
U2 - 10.48009/2_iis_2024_102
DO - 10.48009/2_iis_2024_102
M3 - Article in a journal
SN - 1529-7314
VL - 25
SP - 9
EP - 23
JO - Issues in Information Systems
JF - Issues in Information Systems
IS - 2
ER -