Naomi Haefner

1.1k total citations · 1 hit paper
8 papers, 618 citations indexed

About

Naomi Haefner is a scholar working on Strategy and Management, Management Information Systems and Sociology and Political Science. According to data from OpenAlex, Naomi Haefner has authored 8 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Strategy and Management, 4 papers in Management Information Systems and 2 papers in Sociology and Political Science. Recurrent topics in Naomi Haefner's work include Big Data and Business Intelligence (4 papers), Innovation and Knowledge Management (3 papers) and Digital Transformation in Industry (2 papers). Naomi Haefner is often cited by papers focused on Big Data and Business Intelligence (4 papers), Innovation and Knowledge Management (3 papers) and Digital Transformation in Industry (2 papers). Naomi Haefner collaborates with scholars based in Switzerland, United States and Finland. Naomi Haefner's co-authors include Oliver Gassmann, Vinit Parida, Joakim Wincent, Maximilian Palmié, Stephan Winterhalter, Marco Zeschky, Jörg Goldhahn, Alexander Schuhmacher, Phanish Puranam and Timothy D. Golden and has published in prestigious journals such as Entrepreneurship Theory and Practice, Technological Forecasting and Social Change and Drug Discovery Today.

In The Last Decade

Naomi Haefner

8 papers receiving 580 citations

Hit Papers

Artificial intelligence a... 2020 2026 2022 2024 2020 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Naomi Haefner Switzerland 5 167 143 122 110 102 8 618
Albrecht Fritzsche Germany 11 142 0.9× 149 1.0× 106 0.9× 64 0.6× 86 0.8× 42 647
Serge-Lopez Wamba-Taguimdje France 4 107 0.6× 210 1.5× 87 0.7× 88 0.8× 138 1.4× 7 674
Anwar Al-Gasaymeh Jordan 13 189 1.1× 198 1.4× 155 1.3× 54 0.5× 164 1.6× 27 802
Christian Dremel Switzerland 12 209 1.3× 320 2.2× 93 0.8× 109 1.0× 83 0.8× 33 751
Nadja Damij Slovenia 10 104 0.6× 167 1.2× 51 0.4× 80 0.7× 76 0.7× 37 512
Maarit Tihinen Finland 9 141 0.8× 146 1.0× 82 0.7× 41 0.4× 72 0.7× 25 695
Manal Yunis Lebanon 12 286 1.7× 161 1.1× 196 1.6× 60 0.5× 51 0.5× 27 815
Mounir El Khatib United Arab Emirates 15 195 1.2× 291 2.0× 109 0.9× 103 0.9× 213 2.1× 68 968
Alberto Pezzi Italy 7 254 1.5× 107 0.7× 94 0.8× 50 0.5× 41 0.4× 26 552
Muhammad Saleem Sumbal Hong Kong 15 265 1.6× 160 1.1× 47 0.4× 80 0.7× 109 1.1× 40 619

Countries citing papers authored by Naomi Haefner

Since Specialization
Citations

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

Fields of papers citing papers by Naomi Haefner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naomi Haefner

This figure shows the co-authorship network connecting the top 25 collaborators of Naomi Haefner. A scholar is included among the top collaborators of Naomi Haefner 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 Naomi Haefner. Naomi Haefner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Haefner, Naomi, Vinit Parida, Oliver Gassmann, & Joakim Wincent. (2023). Implementing and scaling artificial intelligence: A review, framework, and research agenda. Technological Forecasting and Social Change. 197. 122878–122878. 44 indexed citations
2.
Schuhmacher, Alexander, et al.. (2022). The dominant logic of Big Tech in healthcare and pharma. Drug Discovery Today. 28(2). 103457–103457. 11 indexed citations
3.
Haefner, Naomi, et al.. (2021). With(Out) a Little Help From My Friends? Reconciling Incongruous Findings on Stakeholder Management, Innovation, and Firm Performance. Entrepreneurship Theory and Practice. 47(1). 142–171. 19 indexed citations
4.
Haefner, Naomi, Joakim Wincent, Vinit Parida, & Oliver Gassmann. (2020). Artificial intelligence and innovation management: A review, framework, and research agenda✰. Technological Forecasting and Social Change. 162. 120392–120392. 504 indexed citations breakdown →
5.
Burkhard, Barbara, Naomi Haefner, Richard A. Bettis, et al.. (2020). The Nexus Between Artificial Intelligence and the Behavioral Theory of the Firm. Academy of Management Proceedings. 2020(1). 19063–19063. 2 indexed citations
6.
Palmié, Maximilian, Naomi Haefner, & Timothy D. Golden. (2018). Clarifying CSE on Job Performance: The Roles of Innovative Work Behavior & Transformational Leaders. Academy of Management Proceedings. 2018(1). 16964–16964. 1 indexed citations
7.
Haefner, Naomi & Maximilian Palmié. (2017). “With(out) a Little Help From My Friends? Stakeholder Management, Innovation Strategy, and Long-Term Firm Performance”. Alexandria (UniSG) (University of St.Gallen). 1 indexed citations
8.
Palmié, Maximilian, et al.. (2015). Coordination mechanisms for international innovation in SMEs: effects on time-to-market and R&D task complexity as a moderator. Small Business Economics. 46(2). 273–294. 36 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.

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