Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Understanding anthropomorphism in service provision: a meta-analysis of physical robots, chatbots, and other AI
2021683 citationsMarkus Blut, Nancy V. Wünderlich et al.Journal of the Academy of Marketing Scienceprofile →
Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage
2019365 citationsMarkus Blut, Cheng WangJournal of the Academy of Marketing Scienceprofile →
Impulse buying: a meta-analytic review
2019334 citationsGopalkrishnan R. Iyer, Markus Blut et al.Journal of the Academy of Marketing Scienceprofile →
Meta-Analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT): Challenging its Validity and Charting A Research Agenda in the Red Ocean
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2022158 citationsMarkus Blut, Alain Yee‐Loong Chong et al.Durham Research Online (Durham University)profile →
Influencer marketing effectiveness: A meta-analytic review
202433 citationsMarkus Blut, Zach W. Y. Lee et al.Journal of the Academy of Marketing Scienceprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Markus Blut'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 Markus Blut with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Blut more than expected).
This network shows the impact of papers produced by Markus Blut. 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 Markus Blut. The network helps show where Markus Blut may publish in the future.
Co-authorship network of co-authors of Markus Blut
This figure shows the co-authorship network connecting the top 25 collaborators of Markus Blut.
A scholar is included among the top collaborators of Markus Blut 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 Markus Blut. Markus Blut is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Blut, Markus, et al.. (2024). Influencer marketing effectiveness: A meta-analytic review. Journal of the Academy of Marketing Science. 53(1). 52–78.33 indexed citations breakdown →
Blut, Markus, et al.. (2022). Meta-Analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT): Challenging its Validity and Charting A Research Agenda in the Red Ocean
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\n. Durham Research Online (Durham University).158 indexed citations breakdown →
Evanschitzky, Heiner, Boris Bartikowski, Tim Baines, et al.. (2020). Digital Disruption in Retailing and Beyond. RePEc: Research Papers in Economics. 4(4). 187–204.13 indexed citations
10.
Iyer, Gopalkrishnan R., Markus Blut, Sarah Xiao, & Dhruv Grewal. (2019). Impulse buying: a meta-analytic review. Journal of the Academy of Marketing Science. 48(3). 384–404.334 indexed citations breakdown →
Blut, Markus, Nancy V. Wünderlich, & Christian Brock. (2018). Innovative Technologies in Branded-Service Encounters: How Robot Characteristics Affect Brand Trust and Experience. Journal of the Association for Information Systems.6 indexed citations
14.
Brock, Christian, et al.. (2017). Developing a Conceptualization of Mobile Service Quality. Journal of the Association for Information Systems.8 indexed citations
15.
Paluch, Stefanie, et al.. (2015). ACCEPTANCE OF SOCIAL MEDIA BY ORGANIZATIONAL USERS - TESTING THE IMPACT OF SYSTEM DESIGN FEATURES. RWTH Publications (RWTH Aachen).2 indexed citations
Blut, Markus, Heiner Evanschitzky, Verena Vogel, & Dieter Ahlert. (2007). Switching Barriers in the Four-Stage Loyalty Model. Advances in consumer research. 34(34). 726–734.47 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.