Young-Won Ha

3.7k citations
10 papers · 2.5k · 2 hit papers · h-index 8

Impact in

    • Decision-Making and Behavioral Economics
  • Marketing top 1%
    • Consumer Behavior in Brand Consumption and Identification
    • Consumer Market Behavior and Pricing

Papers in

Young-Won Ha

10 papers receiving 2.2k citations

Young-Won Ha's Hit Papers

Confirmation, disconfirmation, and information in hypothesis testing. 1987 · 1.4k citations
1.4k0+13+26Years since publication4008001.2k

Peers

Young-Won Ha
Comparison fields: 5 of 121
  • General Decision Sciences 595
  • Marketing 683
  • Applied Psychology 233
  • History and Philosophy of Science 155
  • Family Practice 63
Replace Joshua Klayman with:
Joshua Klayman United States
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Andreas Glöckner Germany
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Philip M. Fernbach United States
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Citations per year

Countries citing papers authored by Young-Won Ha

Since Specialization
Citations

This map shows the geographic impact of Young-Won Ha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Young-Won Ha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Young-Won Ha more than expected).

Fields of papers citing papers by Young-Won Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Young-Won Ha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Young-Won Ha. The network helps show where Young-Won Ha may publish in the future.

Co-authors

The 5 scholars most cited alongside Young-Won Ha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Young-Won Ha Line = papers co-authored together Young-Won Ha links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Confirmation, disconfirmation, and information in hypothesis testing.
Hit paper breakdown →
19871367
2
Consumer Learning: Advertising and the Ambiguity of Product Experience
Hit paper breakdown →
1986707
3 1989188
4 1989121
5 198795
6 198934
7 201415
8 202112
9 20145
10
When the Attraction Effect Disappears: the Differential Impact of Adding Common Versus Unique Features on Consumer Choice
20042

About Young-Won Ha

Young-Won Ha is a scholar working on General Decision Sciences, Marketing, Cognitive Neuroscience, History and Philosophy of Science and Artificial Intelligence, having authored 10 papers that have together received 2.5k indexed citations. Recurring topics across this work include Decision-Making and Behavioral Economics (6 papers), Psychology of Moral and Emotional Judgment (3 papers), Consumer Behavior in Brand Consumption and Identification (3 papers), Experimental Behavioral Economics Studies (2 papers), Philosophy and History of Science (2 papers), Economic and Environmental Valuation (2 papers), Advanced Text Analysis Techniques (1 paper) and Cultural Differences and Values (1 paper). The work is most often cited by research in General Decision Sciences (595 citations), Marketing (683 citations), Applied Psychology (233 citations), History and Philosophy of Science (155 citations) and Family Practice (63 citations). Young-Won Ha has collaborated with scholars based in United States, South Korea and Canada. Frequent co-authors include Joshua Klayman, Stephen J. Hoch, Myung‐Soo Jo, Emine Sarigöllü and Sehoon Park. Their work appears in journals such as Journal of Experimental Psychology Learning Memory and Cognition, Psychological Review, Journal of Consumer Research, Marketing Letters and Current Psychology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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