• Title/Summary/Keyword: Commuting Mode Choice

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The Relationship Between Congestion Pricing and In-vehicle Crowding Level in Public Transport (혼잡통행료 징수와 대중교통 차내 혼잡수준의 관계)

  • YU, Sang-Gyun;BAE, Gi-Mok
    • Journal of Korean Society of Transportation
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    • v.34 no.6
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    • pp.510-522
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    • 2016
  • In studies involving public transport, social welfare improvement is simply explained by the increase in public transport demand. However, the increase in the demand for public transport is mostly observed by the change in the frequency of public transport service, and in-vehicle crowding in public transport has not been an object of concern. This study examines and tries to reveal the cause of the changes of the social welfare and in-vehicle crowding of the changing public transport from imposing congestion pricing. We observe that congestion pricing increases in-vehicle crowding in public transport. This predictable phenomenon is more exacerbated in case of not operating bus-only lane. It should be noted that in-vehicle crowding is more increased in suburban, but in First-best toll system it tends to get worse less than it in other congestion pricing systems. We identify that the change of in-vehicle crowding is affected by the change of proximity of the housing to workplace, the number of commuting trips, and unpredictable distortion effect of the congestion charge.

Development of Customer Sentiment Pattern Map for Webtoon Content Recommendation (웹툰 콘텐츠 추천을 위한 소비자 감성 패턴 맵 개발)

  • Lee, Junsik;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.67-88
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    • 2019
  • Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.