Chin‐Lung Hsu
- Sociology and Political Science top 0.2%
- Information Systems and Management top 0.02%
- Marketing top 0.5%
- Organizational Behavior and Human Resource Management top 1%
- Communication top 0.5%
- Topics
- Technology Adoption and User Behaviour (23 papers)Digital Marketing and Social Media (22 papers)Customer Service Quality and Loyalty (8 papers)
In The Last Decade
Chin‐Lung Hsu
25 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Sociology and Political Science 3.8k
- Information Systems and Management 3.6k
- Marketing 1.4k
- Organizational Behavior and Human Resource Management 921
- Communication 909
Countries citing papers authored by Chin‐Lung Hsu
This map shows the geographic impact of Chin‐Lung Hsu'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 Chin‐Lung Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chin‐Lung Hsu more than expected).
Fields of papers citing papers by Chin‐Lung Hsu
This network shows the impact of papers produced by Chin‐Lung Hsu. 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 Chin‐Lung Hsu. The network helps show where Chin‐Lung Hsu may publish in the future.
Co-authorship network of co-authors of Chin‐Lung Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Chin‐Lung Hsu. A scholar is included among the top collaborators of Chin‐Lung Hsu 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 Chin‐Lung Hsu. Chin‐Lung Hsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 42 | |
| 3 | 23 | |
| 4 | 79 | |
| 5 | 42 | |
| 6 | 5 | |
| 7 | 135 | |
| 8 | 74 | |
| 9 | 0 | |
| 10 | What drives purchase intention for paid mobile apps? – An expectation confirmation model with perceived valuebreakdown → | 491 |
| 11 | The effects of blogger recommendations on customers’ online shopping intentionsbreakdown → | 330 |
| 12 | 59 | |
| 13 | 15 | |
| 14 | 6 | |
| 15 | 22 | |
| 16 | Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivationbreakdown → | 1325 |
| 17 | 313 | |
| 18 | 217 | |
| 19 | 380 | |
| 20 | Why do people play on-line games? An extended TAM with social influences and flow experiencebreakdown → | 1484 |
About Chin‐Lung Hsu
Chin‐Lung Hsu is a scholar working on Information Systems and Management, Organizational Behavior and Human Resource Management and Communication, having authored 26 papers that have together received 5.9k indexed citations. Recurring topics across this work include Technology Adoption and User Behaviour (23 papers), Digital Marketing and Social Media (22 papers) and Customer Service Quality and Loyalty (8 papers). The work is most often cited by research in Information Systems and Management (3.6k citations), Marketing (1.4k citations) and Communication (909 citations). Chin‐Lung Hsu has collaborated with scholars based in Taiwan and China. Frequent co-authors include Judy Chuan‐Chuan Lin, Hsi‐Peng Lu, Hsi‐Peng Lu and Hsiu‐Sen Chiang. Their work appears in journals such as Computers in Human Behavior, Technological Forecasting and Social Change and Information & Management.
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.