Vik Naidoo

16 papers receiving 503 citations

Vik Naidoo's Hit Papers

Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation 2020 · 257 citations
2570+2+4Years since publication50100150200250

Peers

Vik Naidoo
Comparison fields: 5 of 57
  • Marketing 126
  • Communication 84
  • Information Systems and Management 63
  • Applied Psychology 39
  • Artificial Intelligence 201
Replace Juliana Fernandes with:
Juliana Fernandes United States
Satyendra C. Pandey India
Caitlin McLaughlin Canada
Udo Gottlieb Australia
Sydney Chinchanachokchai United States
Gülen Sarial‐Abi Denmark
Zifei Fay Chen United States
Taeyeon Kim United States
Rachael K.F. Ip Hong Kong
Lucía Porcu Spain
Vik Naidoo relative to Juliana Fernandes United States Juliana Fernandes's profile →
Citations per field
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Juliana Fernandes · 1×
Citations per year

Countries citing papers authored by Vik Naidoo

Since Specialization
Citations

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

Fields of papers citing papers by Vik Naidoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Vik Naidoo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Vik Naidoo Line = papers co-authored together Vik Naidoo links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation
Hit paper breakdown →
2020257
2 200871
3 201648
4 200831
5 201728
6 201127
7 201416
8 202013
9 201612
10 20077
11 20207
12 20235
13 20222
14 20251
15 20251
16 20151
17 20250
18 20090
19 20240

About Vik Naidoo

Vik Naidoo is a scholar working on Political Science and International Relations, Sociology and Political Science, Communication, Marketing and Social Psychology, having authored 19 papers that have together received 527 indexed citations. Recurring topics across this work include Higher Education Governance and Development (6 papers), International Student and Expatriate Challenges (5 papers), Consumer Behavior in Brand Consumption and Identification (5 papers), AI in Service Interactions (3 papers), Digital Marketing and Social Media (3 papers), International Business and FDI (3 papers), Behavioral Health and Interventions (2 papers) and Customer Service Quality and Loyalty (2 papers). The work is most often cited by research in Marketing (126 citations), Communication (84 citations), Information Systems and Management (63 citations), Applied Psychology (39 citations) and Artificial Intelligence (201 citations). Vik Naidoo has collaborated with scholars based in Australia, New Zealand and Canada. Frequent co-authors include Rajat Roy, Terry Wu, Linda D. Hollebeek, Fazlul K. Rabbanee, Gopal Das, Jerome D. Donovan, Jaewoo Park, Hiroaki Ishii and Cheree Topple. Their work appears in journals such as Journal of Business Research, Journal of Studies in International Education, European Journal of Marketing, Journal of Marketing for HIGHER EDUCATION and Journal of Services Marketing.

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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