Janghyeok Yoon

Janghyeok Yoon


Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 November 2012 in R&D Management
Verified
Journal Article
Closed access
PDF file
SCSungchul Choi
Sungchul Choi
HKHongbin Kim
Hongbin Kim
JYJanghyeok Yoon
Janghyeok Yoon
KKKwangsoo Kim
Kwangsoo Kim
JLJae Yeol Lee
Jae Yeol Lee


1 July 2020 in Computers & Industrial Engineering
Verified
Journal Article
Closed access
JCJaewoong Choi
Jaewoong Choi
BJByeongki Jeong
Byeongki Jeong
JYJanghyeok Yoon
Janghyeok Yoon
BCByoung-Youl Coh
Byoung-Youl Coh
JLJae-Min Lee
Jae-Min Lee

6 December 2017 in IEEE Access
Verified
Journal Article
Open access
NKNamuk Ko
Namuk Ko
BJByeongki Jeong
Byeongki Jeong
SCSungchul Choi
Sungchul Choi
JYJanghyeok Yoon
Janghyeok Yoon
As an emerging voice of the customer (VOC) containing feedback such as opinions and expectations about products, social media data have the potential used for product improvement and new product development. However, most prior studies have focused on determining customer concerns, while neglecting to incorporate them into a systematic approach to identify product opportunities. In response, this paper suggests an approach to identify product opportunities from customer reviews in social media. This approach employs topic modeling to identify the product topics discussed by customers from large-scale review posts related to a given product. A keygraph is then constructed based on the co-occurrences among the topics contained in each post. The chance discovery theory is then applied to generate new product opportunities from the chance nodes obtained from the keygraph. Our approach contributes to the systematic ideation process for product opportunity analysis based on large-scale and real-time VOC.

25 March 2017 in Sustainability
Verified
Journal Article
Open access
PDF file
BJByeongki Jeong
Byeongki Jeong
JYJanghyeok Yoon
Janghyeok Yoon
Augmented reality has recently achieved a rapid growth through its applications in various industries, including education and entertainment. Despite the growing attraction of augmented reality, trend analyses in this emerging technology have relied on qualitative literature review, failing to provide comprehensive competitive intelligence analysis using objective data. Therefore, tracing industrial competition trends in augmented reality will provide technology experts with a better understanding of evolving competition trends and insights for further technology and sustainable business planning. In this paper, we apply a topic modeling approach to 3595 patents related to augmented reality technology to identify technology subjects and their knowledge stocks, thereby analyzing industrial competitive intelligence in light of technology subject and firm levels. As a result, we were able to obtain some findings from an inventional viewpoint: technological development of augmented reality will soon enter a mature stage, technologies of infrastructural requirements have been a focal subject since 2001, and several software firms and camera manufacturing firms have dominated the recent development of augmented reality.

1 July 2021 in Technological Forecasting and Social Change
Verified
Journal Article
Closed access
JLJiho Lee
Jiho Lee
NKNamuk Ko
Namuk Ko
JYJanghyeok Yoon
Janghyeok Yoon
CSChangho Son
Changho Son