Love Ekenberg
Impact in
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- Multi-Criteria Decision Making
- Complex Systems and Decision Making
- General Decision Sciences top 5%
Papers in
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- Bayesian Modeling and Causal Inference 40
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- Multi-Criteria Decision Making 43
- Co-authors
- Mats Danielson (95 shared papers)Karin Hansson (25 shared papers)Aron Larsson (35 shared papers)F.F. Tusubira (11 shared papers)Magnus Boman (5 shared papers)Henrik Hansson (6 shared papers)J. Linnerooth‐Bayer (4 shared papers)Nadejda Komendantova (16 shared papers)
In The Last Decade
Love Ekenberg
147 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 118
- Management Science and Operations Research 601
- General Decision Sciences 68
- Business and International Management 30
- Communication 98
- Artificial Intelligence 433
Countries citing papers authored by Love Ekenberg
This map shows the geographic impact of Love Ekenberg'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 Love Ekenberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Love Ekenberg more than expected).
Fields of papers citing papers by Love Ekenberg
This network shows the impact of papers produced by Love Ekenberg. 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 Love Ekenberg. The network helps show where Love Ekenberg may publish in the future.
Co-authors
The 25 scholars most cited alongside Love Ekenberg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 171 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 119 | |
| 2 | Exploring the e-Learning State of Art | 2008 | 90 |
| 3 | 2007 | 88 | |
| 4 | 2014 | 81 | |
| 5 | 1998 | 62 | |
| 6 | 2016 | 56 | |
| 7 | 2001 | 43 | |
| 8 | 2006 | 43 | |
| 9 | The DecideIT Decision Tool | 2003 | 39 |
| 10 | 2011 | 39 | |
| 11 | 2015 | 36 | |
| 12 | 2007 | 34 | |
| 13 | 1997 | 33 | |
| 14 | 2001 | 33 | |
| 15 | 2014 | 31 | |
| 16 | 2019 | 30 | |
| 17 | 2007 | 23 | |
| 18 | 1996 | 21 | |
| 19 | 2005 | 21 | |
| 20 | 1995 | 21 |
About Love Ekenberg
Love Ekenberg is a scholar working on Artificial Intelligence, Management Science and Operations Research, Political Science and International Relations, Media Technology and Computational Theory and Mathematics, having authored 171 papers that have together received 1.6k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (43 papers), Bayesian Modeling and Causal Inference (40 papers), E-Government and Public Services (18 papers), ICT Impact and Policies (14 papers), Social Media and Politics (13 papers), Rough Sets and Fuzzy Logic (13 papers), Fuzzy Systems and Optimization (10 papers) and Innovation and Socioeconomic Development (8 papers). The work is most often cited by research in Management Science and Operations Research (601 citations), General Decision Sciences (68 citations), Business and International Management (30 citations), Communication (98 citations) and Artificial Intelligence (433 citations). Love Ekenberg has collaborated with scholars based in Sweden, Austria and Portugal. Frequent co-authors include Mats Danielson, Karin Hansson, Aron Larsson, F.F. Tusubira, Magnus Boman, Henrik Hansson, J. Linnerooth‐Bayer, Nadejda Komendantova, Ying He and Paul Cunningham. Their work appears in journals such as Knowledge-Based Systems, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Sustainability, Group Decision and Negotiation and International Journal of Approximate Reasoning.
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.