Carlos Tam

3.1k total citations · 3 hit papers
27 papers, 2.3k citations indexed

About

Carlos Tam is a scholar working on Information Systems and Management, Sociology and Political Science and Organizational Behavior and Human Resource Management. According to data from OpenAlex, Carlos Tam has authored 27 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Information Systems and Management, 16 papers in Sociology and Political Science and 9 papers in Organizational Behavior and Human Resource Management. Recurrent topics in Carlos Tam's work include Technology Adoption and User Behaviour (17 papers), Digital Marketing and Social Media (16 papers) and Customer Service Quality and Loyalty (9 papers). Carlos Tam is often cited by papers focused on Technology Adoption and User Behaviour (17 papers), Digital Marketing and Social Media (16 papers) and Customer Service Quality and Loyalty (9 papers). Carlos Tam collaborates with scholars based in Portugal, Brazil and United States. Carlos Tam's co-authors include Tiago Oliveira, Jo�ão Varaj�ão, Fernando de Oliveira Santini, Frederico Cruz‐Jesus, Viswanath Venkatesh, Diego Costa Pinto, Ricardo Martins, Manuela Aparício and Ana Alice Baptista and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Tourism Management.

In The Last Decade

Carlos Tam

26 papers receiving 2.2k citations

Hit Papers

Exploring the influential factors of continuance intentio... 2016 2026 2019 2022 2018 2016 2019 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Carlos Tam Portugal 18 1.4k 1.2k 591 409 290 27 2.3k
Zoran Kalinić Serbia 18 1.4k 1.0× 1.2k 1.0× 809 1.4× 358 0.9× 170 0.6× 34 2.3k
Younghoon Chang South Korea 23 1.2k 0.8× 1.3k 1.1× 502 0.8× 407 1.0× 242 0.8× 64 2.2k
Shuiqing Yang China 23 1.5k 1.1× 1.4k 1.2× 623 1.1× 472 1.2× 183 0.6× 38 2.4k
Frank K. Y. Chan Hong Kong 14 1.1k 0.8× 1.0k 0.9× 293 0.5× 323 0.8× 366 1.3× 24 2.3k
Gonçalo Baptista Portugal 5 1.5k 1.1× 1.1k 1.0× 563 1.0× 320 0.8× 159 0.5× 7 2.1k
Veljko Marinković Serbia 19 1.2k 0.8× 1.1k 0.9× 827 1.4× 499 1.2× 128 0.4× 53 2.2k
Jiunn-Woei Lian Taiwan 16 1.1k 0.8× 757 0.6× 535 0.9× 184 0.4× 321 1.1× 24 1.9k
Pushp P. Patil United Kingdom 8 1.0k 0.7× 1.1k 1.0× 468 0.8× 228 0.6× 167 0.6× 8 2.0k
Said S. Al‐Gahtani Saudi Arabia 13 1.4k 1.0× 815 0.7× 332 0.6× 314 0.8× 232 0.8× 19 2.2k
Wei‐Tsong Wang Taiwan 21 977 0.7× 934 0.8× 466 0.8× 467 1.1× 182 0.6× 67 2.2k

Countries citing papers authored by Carlos Tam

Since Specialization
Citations

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

Fields of papers citing papers by Carlos Tam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Tam

This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Tam. A scholar is included among the top collaborators of Carlos Tam 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 Carlos Tam. Carlos Tam 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.
Varaj�ão, Jo�ão, et al.. (2025). CrEISPS - A framework of criteria for evaluating success in information systems projects. Procedia Computer Science. 256. 1821–1835. 1 indexed citations
2.
Tam, Carlos, et al.. (2025). Success with Agile Project Management: Looking back and into the future. Journal of Systems and Software. 226. 112428–112428.
3.
Cruz‐Jesus, Frederico, et al.. (2025). Assessing micro-mobility net benefits at the individual level: Evidence for two European countries. Transportation Research Part F Traffic Psychology and Behaviour. 111. 95–111. 2 indexed citations
4.
Tam, Carlos, et al.. (2024). What helps Agile remote teams to be successful in developing software? Empirical evidence. Information and Software Technology. 177. 107593–107593. 3 indexed citations
5.
Tam, Carlos, et al.. (2024). Understanding the Motivations for Continuance Usage of Mobile Apps. Journal of Computer Information Systems. 65(4). 474–488. 5 indexed citations
6.
Tam, Carlos, et al.. (2024). Agile software development projects–Unveiling the human-related critical success factors. Information and Software Technology. 170. 107432–107432. 20 indexed citations
7.
Tam, Carlos, et al.. (2023). What Influences People’s Adoption of Cognitive Cybersecurity?. International Journal of Human-Computer Interaction. 40(23). 8295–8312. 3 indexed citations
8.
Tam, Carlos, et al.. (2022). Understanding the determinants of users’ continuance intention to buy low-cost airline flights online. Journal of Hospitality and Tourism Technology. 13(2). 264–280. 18 indexed citations
9.
Tam, Carlos, et al.. (2022). What influences the purchase intention of online travel consumers?. Tourism and Hospitality Research. 24(2). 304–320. 7 indexed citations
10.
Oliveira, Tiago, et al.. (2022). Continuance Intention of Mobile Payment: TTF Model with Trust in an African Context. Information Systems Frontiers. 51 indexed citations
11.
Oliveira, Tiago, et al.. (2021). Understanding the factors of mobile payment continuance intention: empirical test in an African context. Heliyon. 7(8). e07807–e07807. 72 indexed citations
12.
Oliveira, Tiago, et al.. (2020). Dataset for understanding why people share their travel experiences on social media: Structural equation model analysis. SHILAP Revista de lepidopterología. 30. 105447–105447. 17 indexed citations
13.
Tam, Carlos, et al.. (2020). The factors influencing the success of on-going agile software development projects. International Journal of Project Management. 38(3). 165–176. 167 indexed citations
14.
Oliveira, Tiago, et al.. (2020). Evaluating collaborative consumption platforms from a consumer perspective. Journal of Cleaner Production. 273. 123018–123018. 27 indexed citations
15.
Tam, Carlos, et al.. (2019). The individual performance outcome behind e-commerce. Internet Research. 30(2). 439–462. 61 indexed citations
16.
Oliveira, Tiago, et al.. (2019). Why do people share their travel experiences on social media?. Tourism Management. 78. 104041–104041. 243 indexed citations breakdown →
17.
Tam, Carlos & Tiago Oliveira. (2018). Does culture influence m-banking use and individual performance?. Information & Management. 56(3). 356–363. 76 indexed citations
18.
Oliveira, Tiago, et al.. (2018). Wearable technology: What explains continuance intention in smartwatches?. Journal of Retailing and Consumer Services. 43. 157–169. 186 indexed citations
19.
Tam, Carlos, et al.. (2018). Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers. 22(1). 243–257. 401 indexed citations breakdown →
20.
Tam, Carlos & Tiago Oliveira. (2017). Literature review of mobile banking and individual performance. International Journal of Bank Marketing. 35(7). 1044–1067. 142 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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