TY - JOUR
T1 - A 2020 Perspective on "How to Derive Causal Insights for Digital Commerce in China? A Research Commentary on Computational Social Science Methods"
AU - Phang, David C. W.
AU - Wang, Kanliang
AU - Wang, Qiuhong
AU - Kauffman, Robert J.
AU - Naldi, Maurizio
PY - 2020
Y1 - 2020
N2 - Cyber-physical data from wearable and other data-sensing devices have been rapidly changing the landscape of opportunity for the conduct of computational social science (CSS) studies. We now have the opportunity to include in our research wearable healthcare data sensors, global positioning system (GPS) data, as well as a range of other digital data via mobile phones and other kinds of easily deployed sensors. The result is a dramatic new set of measurement opportunities for management scientists, marketing research staff, and policy analysts, who can now apply a range of approaches to such data capture and analysis, including machine learning of patterns, and causal inference methods for relevant policy analytics conclusions.
AB - Cyber-physical data from wearable and other data-sensing devices have been rapidly changing the landscape of opportunity for the conduct of computational social science (CSS) studies. We now have the opportunity to include in our research wearable healthcare data sensors, global positioning system (GPS) data, as well as a range of other digital data via mobile phones and other kinds of easily deployed sensors. The result is a dramatic new set of measurement opportunities for management scientists, marketing research staff, and policy analysts, who can now apply a range of approaches to such data capture and analysis, including machine learning of patterns, and causal inference methods for relevant policy analytics conclusions.
KW - Causal inference
KW - Computational social science (CSS)
KW - Cyber-physical sensing
KW - Data analytics
KW - Machine learning
KW - Wearable devices
KW - Causal inference
KW - Computational social science (CSS)
KW - Cyber-physical sensing
KW - Data analytics
KW - Machine learning
KW - Wearable devices
UR - https://sfx-45cbs.hosted.exlibrisgroup.com/45cbs?url_ver=Z39.88-2004&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&ctx_enc=info:ofi/enc:UTF-8&ctx_ver=Z39.88-2004&rfr_id=info:sid/sfxit.com:azlist&sfx.ignore_date_threshold=1&rft.object_id=111030117704000
U2 - 10.1016/j.elerap.2020.100975
DO - 10.1016/j.elerap.2020.100975
M3 - Comment/debate
VL - 41
JO - Electronic Commerce Research and Applications
JF - Electronic Commerce Research and Applications
SN - 1567-4223
IS - May-June
M1 - 100975
ER -