A 2020 perspective on "How to derive causal insights for digital commerce in China? A research commentary on computational social science methods"

A 2020 perspective on "How to derive causal insights for digital commerce in China? A research commentary on computational social science methods"

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 (...

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Bibliographic Details
Main Author: PHANG, David C. W.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2020
Subjects:
Causal inference
Computational social science (CSS)
Cyber-physical sensing
Data analytics
Machine learning
Wearable devices
Asian Studies
Databases and Information Systems
E-Commerce
Online Access:https://ink.library.smu.edu.sg/sis_research/5970
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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