Gerald Häubl

4.7k total citations · 2 hit papers
86 papers, 3.2k citations indexed

About

Gerald Häubl is a scholar working on Marketing, General Decision Sciences and Sociology and Political Science. According to data from OpenAlex, Gerald Häubl has authored 86 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Marketing, 19 papers in General Decision Sciences and 16 papers in Sociology and Political Science. Recurrent topics in Gerald Häubl's work include Consumer Market Behavior and Pricing (35 papers), Decision-Making and Behavioral Economics (19 papers) and Consumer Behavior in Brand Consumption and Identification (18 papers). Gerald Häubl is often cited by papers focused on Consumer Market Behavior and Pricing (35 papers), Decision-Making and Behavioral Economics (19 papers) and Consumer Behavior in Brand Consumption and Identification (18 papers). Gerald Häubl collaborates with scholars based in Canada, United States and Netherlands. Gerald Häubl's co-authors include Valerie Trifts, Kyle B. Murray, Andreas Herrmann, Christian Hildebrand, Benedict G. C. Dellaert, Terry Elrod, Peter T. L. Popkowski Leszczyc, Tobias Schlager, Jan R. Landwehr and Anouk Bergner and has published in prestigious journals such as Journal of Personality and Social Psychology, PLoS ONE and Journal of Marketing.

In The Last Decade

Gerald Häubl

83 papers receiving 2.8k citations

Hit Papers

Consumer Decision Making in Online Shopping Environments:... 2000 2026 2008 2017 2000 2023 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Gerald Häubl Canada 24 1.7k 1.3k 793 415 287 86 3.2k
Gerald L. Lohse United States 23 1.0k 0.6× 1.3k 1.0× 1.0k 1.3× 520 1.3× 199 0.7× 39 3.4k
Olivier Toubia United States 26 1.1k 0.6× 1.3k 0.9× 536 0.7× 285 0.7× 383 1.3× 70 2.9k
Martin Spann Germany 31 1.7k 1.0× 1.3k 1.0× 614 0.8× 392 0.9× 652 2.3× 140 3.5k
Oded Netzer United States 28 1.5k 0.9× 1.4k 1.1× 243 0.3× 394 0.9× 317 1.1× 65 3.3k
Nicholas H. Lurie United States 17 1.2k 0.7× 1.4k 1.1× 622 0.8× 410 1.0× 177 0.6× 39 2.3k
Sanjoy Ghose United States 23 1.5k 0.9× 1.0k 0.8× 670 0.8× 518 1.2× 220 0.8× 61 2.5k
Berend Wierenga Netherlands 30 1.1k 0.7× 862 0.6× 403 0.5× 527 1.3× 430 1.5× 108 2.9k
Gerrit van Bruggen Netherlands 23 1.4k 0.8× 1.1k 0.8× 525 0.7× 770 1.9× 307 1.1× 48 2.9k
Baohong Sun United States 25 1.7k 1.0× 669 0.5× 263 0.3× 450 1.1× 476 1.7× 57 2.7k
Yili Hong United States 27 1.6k 0.9× 2.2k 1.7× 781 1.0× 391 0.9× 319 1.1× 150 3.6k

Countries citing papers authored by Gerald Häubl

Since Specialization
Citations

This map shows the geographic impact of Gerald Häubl'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 Gerald Häubl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gerald Häubl more than expected).

Fields of papers citing papers by Gerald Häubl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gerald Häubl. 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 Gerald Häubl. The network helps show where Gerald Häubl may publish in the future.

Co-authorship network of co-authors of Gerald Häubl

This figure shows the co-authorship network connecting the top 25 collaborators of Gerald Häubl. A scholar is included among the top collaborators of Gerald Häubl based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gerald Häubl. Gerald Häubl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Aka, Ada, Daniel M. Bartels, Stefan Bucher, et al.. (2025). A timeline of cognitive costs in decision-making. Trends in Cognitive Sciences. 29(9). 827–839. 2 indexed citations
2.
Zeithammer, Robert, et al.. (2024). Strange case of Dr. Bidder and Mr. Entrant: Consumer preference inconsistencies in costly price offers. International Journal of Research in Marketing. 42(2). 255–274.
3.
Greiner, Russell, et al.. (2021). Using survival prediction techniques to learn consumer-specific reservation price distributions. PLoS ONE. 16(4). e0249182–e0249182. 5 indexed citations
4.
Donkers, Bas, et al.. (2020). Preference Dynamics in Sequential Consumer Choice with Defaults. Journal of Marketing Research. 57(6). 1096–1112. 15 indexed citations
5.
Bergner, Anouk, Christian Hildebrand, & Gerald Häubl. (2019). Machine Talk: How Conversational Chatbots Promote Brand Intimacy and Influence Consumer Choice. Alexandria (UniSG) (University of St.Gallen). 2 indexed citations
6.
Schlager, Tobias, Christian Hildebrand, Gerald Häubl, & Andreas Herrmann. (2015). The Gamification of Buying. ACR Asia-Pacific Advances. 1 indexed citations
7.
Häubl, Gerald, et al.. (2015). The Dynamics of Success: How Experiencing Success Versus Failure Influences Subsequent Motivation. ACR North American Advances. 1 indexed citations
8.
Hildebrand, Christian, Gerald Häubl, Andreas Herrmann, & Jan R. Landwehr. (2013). Conformity and the Crowd. Harvard business review. 91(7). 23–24. 16 indexed citations
9.
Trudel, Remi, et al.. (2012). Helping Consumers Get Out of Debt Faster: How Debt Repayment Strategies Affect Motivation to Repay Debt. ACR North American Advances. 1 indexed citations
10.
Murray, Kyle B. & Gerald Häubl. (2012). Why Dominant Companies Are Vulnerable. Alexandria (UniSG) (University of St.Gallen). 53(2). 12–14. 6 indexed citations
11.
Murray, Kyle B. & Gerald Häubl. (2011). Freedom of choice, ease of use, and the formation of interface preferences. MIS Quarterly. 35(4). 955–976. 31 indexed citations
12.
Häubl, Gerald, et al.. (2010). Numeric Fluency and Preference. ACR North American Advances. 8 indexed citations
13.
Häubl, Gerald, et al.. (2008). Self-Determination and the Relinquishment of Decision Control: Why Are Consumers Reluctant to Delegate Their Decisions to Surrogates?. ACR North American Advances. 1 indexed citations
14.
Häubl, Gerald, et al.. (2007). The Opposing Effects of Personalized Recommendations on Objective and Subjective Decision Outcomes. ACR North American Advances. 2 indexed citations
15.
Zhu, Tingshao, et al.. (2005). Goal-directed site-independent recommendations from passive observations. Alexandria (UniSG) (University of St.Gallen). 549–556. 1 indexed citations
16.
Zhu, Tingshao, et al.. (2005). Using learned browsing behavior models to recommend relevant web pages. Alexandria (UniSG) (University of St.Gallen). 1589–1591. 2 indexed citations
17.
Häubl, Gerald, Benedict G. C. Dellaert, Kyle B. Murray, & Valerie Trifts. (2004). Buyer behavior in personalized shopping environments: insights from the institute for online consumer studies. Data Archiving and Networked Services (DANS). 207–229. 2 indexed citations
18.
Murray, Kyle B. & Gerald Häubl. (2002). The Fiction of No Friction: A User Skills Approach to Cognitive Lock-In. Alexandria (UniSG) (University of St.Gallen). 29(1). 11–18. 21 indexed citations
19.
Elrod, Terry & Gerald Häubl. (2002). An Extended Random Coefficients Model, with Application to Metric Conjoint Analysis. SSRN Electronic Journal. 4 indexed citations
20.
Häubl, Gerald. (1999). Consumer Decision Making in Online Environments. Alexandria (UniSG) (University of St.Gallen). 294(1). 379–388. 8 indexed citations

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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