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The Use of Big Data and Its Effects in a Diffusion Forecasting Model for Korean Reverse Mortgage Subscribers

Title
The Use of Big Data and Its Effects in a Diffusion Forecasting Model for Korean Reverse Mortgage Subscribers
Authors
Yang, JinahMin, DaikiKim, Jeenyoung
Ewha Authors
민대기
SCOPUS Author ID
민대기scopus
Issue Date
2020
Journal Title
SUSTAINABILITY
ISSN
2071-1050JCR Link
Citation
SUSTAINABILITY vol. 12, no. 3
Keywords
generalized bass modelbig dataexogenous variablessales predictionKorean reverse mortgage
Publisher
MDPI
Indexed
SCIE; SSCI; SCOPUS WOS
Document Type
Article
Abstract
In recent years, big data has been widely used to understand consumers' behavior and opinions. With this paper, we consider the use of big data and its effects in the problem of projecting the number of reverse mortgage subscribers in Korea. We analyzed web-news, blog post, and search traffic volumes associated with Korean reverse mortgages and integrated them into a Generalized Bass Model (GBM) as a part of the exogenous variables representing marketing effort. We particularly consider web-news volume as a proxy for marketer-generated content (MGC) and blog post and search traffic volumes as proxies for user-generated content (UGC). Empirical analysis provides some interesting findings: First, the GBM by incorporating big data is helpful for forecasting the sales of Korean reverse mortgages, and second, the UGC as an exogenous variable is more useful for predicting sales volume than the MGC. The UGC can explain consumers' interest relatively well. Additional sensitivity analysis supports that the UGC is important for increasing sales volume. Finally, prediction performance is different between blog posts and search traffic volumes.
DOI
10.3390/su12030979
Appears in Collections:
경영대학 > 경영학전공 > Journal papers
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