Jia Liu

Hong Kong University of Science & Technology (HKUST) - HKUST Business School

Clear Water Bay

Hong Kong

SCHOLARLY PAPERS

4

DOWNLOADS

304

SSRN CITATIONS

4

CROSSREF CITATIONS

0

Scholarly Papers (4)

1.

A Semantic Approach for Estimating Consumer Content Preferences from Online Search Queries

Columbia Business School Research Paper No. 16-2
Number of pages: 59 Posted: 19 Dec 2015 Last Revised: 17 Apr 2019
Jia Liu and Olivier Toubia
Hong Kong University of Science & Technology (HKUST) - HKUST Business School and Columbia Business School - Marketing
Downloads 245 (129,832)
Citation 4

Abstract:

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search engine optimization, search engine marketing, search queries, content preferences, semantic relationships, topic modeling

2.

Understanding Consumer Dynamic Decision Making Under Competing Loyalty Programs

Number of pages: 60 Posted: 04 Sep 2019
Jia Liu and Asim Ansari
Hong Kong University of Science & Technology (HKUST) - HKUST Business School and Columbia Business School - Marketing
Downloads 33 (470,459)

Abstract:

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Loyalty Programs, Promotions, Competition, Bounded Rationality, Approximate Dynamic Programming, Experiments

3.

Content-Based Model of Web Search Behavior: An Application to TV Show Search

Number of pages: 66 Posted: 07 May 2019
Hong Kong University of Science & Technology (HKUST) - HKUST Business School, Columbia Business School - Marketing and Microsoft Corporation - Microsoft Research, New York City
Downloads 26 (506,065)

Abstract:

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marketing, search, interpretable machine learning, recommendation systems, Poisson factorization, variational inference, big data

4.

How do Consumers Form Online Search Queries? The Importance of Activation Probabilities between Queries and Results

Columbia Business School Research Paper No. 15-91
Posted: 18 Oct 2015 Last Revised: 04 Sep 2019
Jia Liu and Olivier Toubia
Hong Kong University of Science & Technology (HKUST) - HKUST Business School and Columbia Business School - Marketing

Abstract:

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online search queries, consumer search, content preferences, digital marketing