Krishnadas Nanath

503 total citations
21 papers, 320 citations indexed

About

Krishnadas Nanath is a scholar working on Information Systems, Information Systems and Management and Artificial Intelligence. According to data from OpenAlex, Krishnadas Nanath has authored 21 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 5 papers in Information Systems and Management and 5 papers in Artificial Intelligence. Recurrent topics in Krishnadas Nanath's work include Green IT and Sustainability (4 papers), Technology Adoption and User Behaviour (4 papers) and Environmental Sustainability in Business (4 papers). Krishnadas Nanath is often cited by papers focused on Green IT and Sustainability (4 papers), Technology Adoption and User Behaviour (4 papers) and Environmental Sustainability in Business (4 papers). Krishnadas Nanath collaborates with scholars based in United Arab Emirates, India and United States. Krishnadas Nanath's co-authors include Radhakrishna G. Pillai, Sajjad Ali, Janakiraman Moorthy, Jayanthi Ranjan, Pulak Ghosh, Nazrul Islam, Sreejith Balasubramanian and Vinaya Shukla and has published in prestigious journals such as Technological Forecasting and Social Change, Behaviour and Information Technology and International Journal of Sustainability in Higher Education.

In The Last Decade

Krishnadas Nanath

20 papers receiving 290 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Krishnadas Nanath United Arab Emirates 11 75 63 61 49 40 21 320
Kristijan Mirkovski Australia 10 42 0.6× 89 1.4× 44 0.7× 100 2.0× 89 2.2× 26 325
Sarika Sharma India 11 42 0.6× 28 0.4× 58 1.0× 61 1.2× 21 0.5× 47 384
Kamal Kant Hiran Denmark 8 41 0.5× 46 0.7× 77 1.3× 33 0.7× 43 1.1× 29 293
Savita K. Sugathan Malaysia 11 37 0.5× 78 1.2× 98 1.6× 37 0.8× 79 2.0× 59 449
Carsten Hahn Germany 8 86 1.1× 51 0.8× 17 0.3× 63 1.3× 19 0.5× 29 323
Luis Hernan Contreras Pinochet Brazil 8 56 0.7× 37 0.6× 42 0.7× 75 1.5× 62 1.6× 72 305
Adnan Aktepe Türkiye 9 45 0.6× 27 0.4× 38 0.6× 51 1.0× 40 1.0× 33 368
Kyung Jin South Korea 10 95 1.3× 50 0.8× 145 2.4× 110 2.2× 67 1.7× 31 422
Laura Rocca Italy 8 104 1.4× 160 2.5× 134 2.2× 42 0.9× 48 1.2× 23 437

Countries citing papers authored by Krishnadas Nanath

Since Specialization
Citations

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

Fields of papers citing papers by Krishnadas Nanath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Krishnadas Nanath

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

All Works

20 of 20 papers shown
1.
Nanath, Krishnadas, et al.. (2023). An investigation of crowdsourcing methods in enhancing the machine learning approach for detecting online recruitment fraud. International Journal of Information Management Data Insights. 3(1). 100167–100167. 12 indexed citations
2.
Nanath, Krishnadas, et al.. (2022). Developing a mental health index using a machine learning approach: Assessing the impact of mobility and lockdown during the COVID-19 pandemic. Technological Forecasting and Social Change. 178. 121560–121560. 28 indexed citations
3.
Nanath, Krishnadas, et al.. (2022). Examination of fake news from a viral perspective: an interplay of emotions, resonance, and sentiments. Journal of Systems and Information Technology. 24(2). 131–155. 18 indexed citations
4.
Nanath, Krishnadas, et al.. (2021). Industry-academia outreach: a study of student perception. International Journal of Technology Enhanced Learning. 13(4). 390–390.
5.
Nanath, Krishnadas, et al.. (2021). Towards a framework for sustaining Green IT initiatives: an empirical investigation. Information Technology and Management. 22(3). 193–206. 3 indexed citations
6.
Nanath, Krishnadas, et al.. (2021). The role of communication medium in increasing e-waste recycling awareness among higher educational institutions. International Journal of Sustainability in Higher Education. 22(4). 833–853. 13 indexed citations
7.
Nanath, Krishnadas, et al.. (2021). Decision-making system for higher education university selection: comparison of priorities pre- and post-COVID-19. Journal of Applied Research in Higher Education. 14(1). 347–365. 24 indexed citations
8.
Nanath, Krishnadas, et al.. (2021). Leveraging Twitter data to analyze the virality of Covid-19 tweets: a text mining approach. Behaviour and Information Technology. 42(2). 196–214. 26 indexed citations
9.
Nanath, Krishnadas, et al.. (2021). Exploring Cybersecurity Ecosystem in the Middle East: Towards an SME Recommender System. Journal of Cyber Security and Mobility. 10 indexed citations
10.
Nanath, Krishnadas, et al.. (2020). Individual and organizational factors affecting the implementation of Green IT: A case study of an Indian business school. The Electronic Journal of Information Systems in Developing Countries. 87(3). 7 indexed citations
11.
Nanath, Krishnadas, et al.. (2020). Predicting a Hit Song with Machine Learning: Is there an apriori secret formula?. 111–116. 13 indexed citations
12.
Nanath, Krishnadas, et al.. (2019). Towards a Model For Performance Evaluation of Cloud Machines. 420–425. 1 indexed citations
13.
Nanath, Krishnadas, et al.. (2017). Adoption of Cloud Computing in UAE. International Journal of Information Systems in the Service Sector. 9(4). 1–20. 4 indexed citations
14.
Nanath, Krishnadas, et al.. (2016). The Influence of Green IS Practices on Competitive Advantage: Mediation Role of Green Innovation Performance. Information Systems Management. 34(1). 3–19. 77 indexed citations
15.
Nanath, Krishnadas, et al.. (2015). Cloud performance evaluation using fuzzy logic. 3. 1–8. 1 indexed citations
16.
Moorthy, Janakiraman, et al.. (2015). Big Data: Prospects and Challenges. Vikalpa The Journal for Decision Makers. 40(1). 74–96. 52 indexed citations
17.
Nanath, Krishnadas & Radhakrishna G. Pillai. (2013). A Model for Cost-Benefit Analysis of Cloud Computing. Journal of international technology and information management. 22(3). 19 indexed citations
18.
Nanath, Krishnadas, et al.. (2012). A Sustainability Model of Green IT Initiatives. International Conference on Information Systems. 7 indexed citations
19.
Nanath, Krishnadas. (2011). LifeSpring Hospitals: a social innovation in Indian healthcare. Emerald Emerging Markets Case Studies. 1(1). 1–14. 2 indexed citations
20.
Nanath, Krishnadas. (2011). GOONJ: the power of cloth. Emerald Emerging Markets Case Studies. 1(4). 1–12. 2 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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