Jöerg Evermann

2.8k citations
77 papers · 2.1k · 2 hit papers · h-index 22

Impact in

Papers in

Jöerg Evermann

72 papers receiving 2.0k citations

Jöerg Evermann's Hit Papers

Predicting process behaviour using deep learning 2017 · 313 citations
3130+4+8Years since publication100200300

Peers

Jöerg Evermann
Comparison fields: 5 of 123
  • Management Information Systems 797
  • Information Systems and Management 263
  • Management Science and Operations Research 370
  • Information Systems 631
  • Software 90
Replace Sandeep Purao with:
Sandeep Purao United States
Atish P. Sinha United States
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Bill C. Hardgrave United States
Markus Helfert Ireland
J. Alberto Espinosa United States
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Citations per field
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Citations per year

Countries citing papers authored by Jöerg Evermann

Since Specialization
Citations

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

Fields of papers citing papers by Jöerg Evermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jöerg Evermann, 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 Jöerg Evermann Line = papers co-authored together Jöerg Evermann links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Critical Examination of Common Beliefs About Partial Least Squares Path Modeling
Hit paper breakdown →
2013347
2
Predicting process behaviour using deep learning
Hit paper breakdown →
2017313
3 2016193
4 2005102
5 200179
6 201878
7 201776
8 200560
9 201752
10 202342
11 200542
12 201539
13 200838
14 201437
15 202336
16 200731
17 200629
18 201628
19 200927
20
Testing Models or Fitting Models? Identifying Model Misspecification in PLS
201025

About Jöerg Evermann

Jöerg Evermann is a scholar working on Management Information Systems, Information Systems, Artificial Intelligence, Information Systems and Management and Management Science and Operations Research, having authored 77 papers that have together received 2.1k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (25 papers), Service-Oriented Architecture and Web Services (24 papers), Business Process Modeling and Analysis (23 papers), Technology Adoption and User Behaviour (13 papers), Information Systems Theories and Implementation (9 papers), Data Quality and Management (9 papers), Big Data and Business Intelligence (8 papers) and Advanced Text Analysis Techniques (8 papers). The work is most often cited by research in Management Information Systems (797 citations), Information Systems and Management (263 citations), Management Science and Operations Research (370 citations), Information Systems (631 citations) and Software (90 citations). Jöerg Evermann has collaborated with scholars based in Canada, New Zealand and United States. Frequent co-authors include Mikko Rönkkö, Peter Fettke, Mary Tate, Yair Wand, Jana-Rebecca Rehse, Nijat Mehdiyev, Roman Lukyanenko, Guy G. Gable, Jeffrey Parsons and Jennifer Jewer. Their work appears in journals such as Journal of the Association for Information Systems, Requirements Engineering, European Journal of Marketing, Information Systems and Journal of Database Management.

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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