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.
Why do so many digital transformations fail? A bibliometric analysis and future research agenda
Countries citing papers authored by Markus Helfert
Since
Specialization
Citations
This map shows the geographic impact of Markus Helfert'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 Helfert with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Helfert more than expected).
This network shows the impact of papers produced by Markus Helfert. 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 Helfert. The network helps show where Markus Helfert may publish in the future.
Co-authorship network of co-authors of Markus Helfert
This figure shows the co-authorship network connecting the top 25 collaborators of Markus Helfert.
A scholar is included among the top collaborators of Markus Helfert 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 Helfert. Markus Helfert is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
McDonnell, Peter J., et al.. (2017). Barriers to benefit from integration of building information with live data from IOT devices during the facility management phase.3 indexed citations
11.
Helfert, Markus, et al.. (2017). Identifying Emerging Challenges for ICT industry in Ireland: Multiple Case Study Analysis of Data Privacy Breaches. Journal of the Association for Information Systems.1 indexed citations
12.
Helfert, Markus, et al.. (2016). Data quality for web log data using a Hadoop environment.1 indexed citations
13.
Parsons, Jeffrey, et al.. (2016). Breakthroughs and emerging insights from ongoing design science projects: Research-in-progress papers and poster presentations from the 11th international conference on design science research in information systems and technology (DESRIST) 2016. St. John, Newfoundland, Canada, May 23-25. 100.2 indexed citations
14.
Bezbradica, Marija, et al.. (2016). Types of IT architectures in smart cities – a review from a business model and enterprise architecture perspective. Arrow@dit (Dublin Institute of Technology).7 indexed citations
15.
Donnellan, Brian, et al.. (2014). SYSTEMATIC PROBLEM FORMULATION IN ACTION DESIGN RESEARCH: THE CASE OF SMART CITIES. Journal of the Association for Information Systems.3 indexed citations
16.
Ge, Mouzhi, Markus Helfert, & Dietmar Jannach. (2011). INFORMATION QUALITY ASSESSMENT: VALIDATING MEASUREMENT DIMENSIONS AND PROCESSES. Journal of the Association for Information Systems. 75.17 indexed citations
17.
Yao, Juan, et al.. (2010). InfoGuard: A Process-Centric Rule-Based Approach for Managing Information Quality.. ERCIM news/ERCIM news online edition. 2010. 55–56.1 indexed citations
18.
Donnellan, Brian & Markus Helfert. (2010). Applying Design Science to IT Management: The IT-Capability Maturity Framework. Journal of the Association for Information Systems. 227.4 indexed citations
19.
Helfert, Markus, et al.. (2010). AN APPROACH TO MONITORING DATA QUALTIY - PRODUCT ORIENTED APPROACH -. Journal of the Association for Information Systems. 362.1 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.