Ah-Lian Kor

62 papers receiving 428 citations

Peers

Ah-Lian Kor
Comparison fields: 5 of 86
  • Computer Networks and Communications 85
  • Information Systems 72
  • Artificial Intelligence 72
  • Electrical and Electronic Engineering 68
  • Strategy and Management 47
Replace Dhavalkumar Thakker with:
Dhavalkumar Thakker United Kingdom
Egīls Ginters Latvia
Chintan Amrit Netherlands
Justyna Żywiołek Poland
Amr Adel Australia
Jaime Campos Sweden
Balbir Barn United Kingdom
Raman Kumar Goyal India
Ip‐Shing Fan United Kingdom
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Citations per field
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Dhavalkumar Thakker · 1×
Citations per year

Countries citing papers authored by Ah-Lian Kor

Since Specialization
Citations

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

Fields of papers citing papers by Ah-Lian Kor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ah-Lian Kor. 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 Ah-Lian Kor. The network helps show where Ah-Lian Kor may publish in the future.

Co-authorship network of co-authors of Ah-Lian Kor

This figure shows the co-authorship network connecting the top 25 collaborators of Ah-Lian Kor. A scholar is included among the top collaborators of Ah-Lian Kor 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 Ah-Lian Kor. Ah-Lian Kor 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
#WorkIndexed citations
1 1
2 1
3 0
4 1
5 1
6 2
7 36
8 5
9 3
10 24
11 1
12 4
13 1
14 1
15 64
16
A Conceptual Model of the Factors Affecting Saudi Citizens' Use of Social Media to Communicate with the Government
1
17 2
18
Factors affecting citizens' use of social media to communicate with the government: a proposed model
23
19 18
20
A Value Oriented Conceptual Model for Innovation in Local Government
2

About Ah-Lian Kor

Ah-Lian Kor is a scholar working on Signal Processing, Computer Networks and Communications and Information Systems and Management, having authored 64 papers that have together received 459 indexed citations. Recurring topics across this work include Green IT and Sustainability (14 papers), IoT and Edge/Fog Computing (10 papers) and Cloud Computing and Resource Management (10 papers). The work is most often cited by research in Business and International Management (9 citations), Management of Technology and Innovation (30 citations) and Computer Networks and Communications (85 citations). Ah-Lian Kor has collaborated with scholars based in United Kingdom, Malaysia and Italy. Frequent co-authors include Colin Pattinson, Karl Andersson, Mohammad Shahadat Hossain, Éric Rondeau, Vyacheslav Kharchenko, Jean‐Philippe Georges, Muthu Ramachandran, Amin Hosseinian‐Far, Reemiah Muneer Alotaibi and Tony Elliman. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

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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