Combining machine-based and econometrics methods for policy analytics insights
Computational Social Science (CSS) has become a mainstream approach in the empirical study of policy analytics issues in various domains of e-commerce research. This article is intended to represent recent advances that have been made for the discovery of new policy-related insights in business, con...
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sg-smu-ink.sis_research-47312024-05-31T14:52:28Z Combining machine-based and econometrics methods for policy analytics insights KAUFFMAN, Robert J. KIM, Kwansoo LEE, Sang-Yong Tom HOANG, Ai Phuong REN, Jing Computational Social Science (CSS) has become a mainstream approach in the empirical study of policy analytics issues in various domains of e-commerce research. This article is intended to represent recent advances that have been made for the discovery of new policy-related insights in business, consumer, and social settings. The approach discussed is fusion analytics, which combines machine-based methods from Computer Science (CS) and explanatory empiricism involving advanced Econometrics and Statistics. It explores several efforts to conduct research inquiry in different functional areas of Electronic Commerce and Information Systems (IS), with applications that represent different functional areas of business, as well as individual consumer, social and public issues. Recent developments and shifts in the scientific study of technology-related phenomena and Social Science issues in the presence of historically-large datasets prompt new forms of research inquiry. They include blended approaches to research methodology and more interest in the production of research results that have direct application to industry contexts. This article showcases the methods shifts and several contemporary applications. They discuss (1) feedback effects in mobile phone-based stock trading; (2) sustainability of top-rank chart popularity of music tracks; (3) household TV viewing patterns; and (4) household sampling and purchases of video-on-demand (VoD) services. The range of applicability of the ideas goes beyond the scope of these illustrations, to include issues in public services, healthcare, product and service deployment, public opinion and elections, electronic auctions, and travel and tourism services. In fact, the coverage is as broad as for-profit and for-non-profit, private and public, and governmental and non-governmental institutions. 2017-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/3729 info:doi/10.1016/j.elerap.2017.04.004 https://ink.library.smu.edu.sg/context/sis_research/article/4731/viewcontent/1_s20_S1567422317300145_main.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Causality Computational Social Science Data analytics Econometrics E-commerce Empirical research Fintech Fusion analytics Music popularity Stock trading Policy analytics TV viewing Video-on-demand (VoD) Databases and Information Systems E-Commerce Strategic Management Policy |
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Causality Computational Social Science Data analytics Econometrics E-commerce Empirical research Fintech Fusion analytics Music popularity Stock trading Policy analytics TV viewing Video-on-demand (VoD) Databases and Information Systems E-Commerce Strategic Management Policy KAUFFMAN, Robert J. KIM, Kwansoo LEE, Sang-Yong Tom HOANG, Ai Phuong REN, Jing Combining machine-based and econometrics methods for policy analytics insights |
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Computational Social Science (CSS) has become a mainstream approach in the empirical study of policy analytics issues in various domains of e-commerce research. This article is intended to represent recent advances that have been made for the discovery of new policy-related insights in business, consumer, and social settings. The approach discussed is fusion analytics, which combines machine-based methods from Computer Science (CS) and explanatory empiricism involving advanced Econometrics and Statistics. It explores several efforts to conduct research inquiry in different functional areas of Electronic Commerce and Information Systems (IS), with applications that represent different functional areas of business, as well as individual consumer, social and public issues. Recent developments and shifts in the scientific study of technology-related phenomena and Social Science issues in the presence of historically-large datasets prompt new forms of research inquiry. They include blended approaches to research methodology and more interest in the production of research results that have direct application to industry contexts. This article showcases the methods shifts and several contemporary applications. They discuss (1) feedback effects in mobile phone-based stock trading; (2) sustainability of top-rank chart popularity of music tracks; (3) household TV viewing patterns; and (4) household sampling and purchases of video-on-demand (VoD) services. The range of applicability of the ideas goes beyond the scope of these illustrations, to include issues in public services, healthcare, product and service deployment, public opinion and elections, electronic auctions, and travel and tourism services. In fact, the coverage is as broad as for-profit and for-non-profit, private and public, and governmental and non-governmental institutions. |
format |
text |
author |
KAUFFMAN, Robert J. KIM, Kwansoo LEE, Sang-Yong Tom HOANG, Ai Phuong REN, Jing |
author_facet |
KAUFFMAN, Robert J. KIM, Kwansoo LEE, Sang-Yong Tom HOANG, Ai Phuong REN, Jing |
author_sort |
KAUFFMAN, Robert J. |
title |
Combining machine-based and econometrics methods for policy analytics insights |
title_short |
Combining machine-based and econometrics methods for policy analytics insights |
title_full |
Combining machine-based and econometrics methods for policy analytics insights |
title_fullStr |
Combining machine-based and econometrics methods for policy analytics insights |
title_full_unstemmed |
Combining machine-based and econometrics methods for policy analytics insights |
title_sort |
combining machine-based and econometrics methods for policy analytics insights |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2017 |
url |
https://ink.library.smu.edu.sg/sis_research/3729 https://ink.library.smu.edu.sg/context/sis_research/article/4731/viewcontent/1_s20_S1567422317300145_main.pdf |
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