Maja Trstenjak
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- Digital Transformation in Industry 15
- Manufacturing Process and Optimization 5
- Flexible and Reconfigurable Manufacturing Systems 4
- Engineering Technology and Methodologies 2
- Management Information Systems top 10%
- Big Data and Business Intelligence 3
- Quality and Supply Management 3
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- Technology Assessment and Management 6
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- Sustainable Supply Chain Management 3
Maja Trstenjak
21 papers receiving 246 citations
Peers
Comparison fields: 5 of 62
- Industrial and Manufacturing Engineering 167
- Management Information Systems 57
- Management of Technology and Innovation 25
- Safety, Risk, Reliability and Quality 31
- Strategy and Management 42
Countries citing papers authored by Maja Trstenjak
This map shows the geographic impact of Maja Trstenjak'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 Maja Trstenjak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maja Trstenjak more than expected).
Fields of papers citing papers by Maja Trstenjak
This network shows the impact of papers produced by Maja Trstenjak. 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 Maja Trstenjak. The network helps show where Maja Trstenjak may publish in the future.
Co-authorship network
The 9 scholars most cited alongside Maja Trstenjak, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 15 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2023 | 15 | |
| 5 | 2023 | 9 | |
| 6 | 2023 | 8 | |
| 7 | 2023 | 4 | |
| 8 | 2022 | 17 | |
| 9 | 2022 | 17 | |
| 10 | 2020 | 2 | |
| 11 | 2020 | 3 | |
| 12 | 2020 | 25 | |
| 13 | 2020 | 31 | |
| 14 | 2019 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2019 | 5 | |
| 17 | Lean Philosophy in the Digitalization Process | 2018 | 1 |
| 18 | 2017 | 82 | |
| 19 | Industry 4.0 readiness factor calculation - problem structuring | 2017 | 3 |
| 20 | New machines selection tools using analytic hierarchy process | 2015 | 3 |
About Maja Trstenjak
Maja Trstenjak is a scholar working on Industrial and Manufacturing Engineering, Management Information Systems and Safety, Risk, Reliability and Quality, having authored 21 papers that have together received 256 indexed citations. Recurring topics across this work include Digital Transformation in Industry (15 papers), Technology Assessment and Management (6 papers), Manufacturing Process and Optimization (5 papers), Flexible and Reconfigurable Manufacturing Systems (4 papers), Big Data and Business Intelligence (3 papers), Quality and Supply Management (3 papers), Sustainable Supply Chain Management (3 papers) and Engineering Technology and Methodologies (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (167 citations), Management Information Systems (57 citations) and Management of Technology and Innovation (25 citations). Maja Trstenjak has collaborated with scholars based in Croatia and Czechia. Frequent co-authors include Tihomir Opetuk, Hrvoje Cajner, Goran Đukić, Danijel Pavković, Andrea Benešová, Mihael Cipek, Josef Basl, Dragutin Lisjak and H. Kober. Their work appears in journals such as Sustainability, Applied Sciences, Future Internet, Tehnicki vjesnik - Technical Gazette and Sensors.
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.