Hsia‐Ching Chang

645 total citations
31 papers, 386 citations indexed

About

Hsia‐Ching Chang is a scholar working on Information Systems and Management, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Hsia‐Ching Chang has authored 31 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Information Systems and Management, 12 papers in Information Systems and 8 papers in Management Science and Operations Research. Recurrent topics in Hsia‐Ching Chang's work include Technology Adoption and User Behaviour (9 papers), Digital Marketing and Social Media (7 papers) and Data Quality and Management (5 papers). Hsia‐Ching Chang is often cited by papers focused on Technology Adoption and User Behaviour (9 papers), Digital Marketing and Social Media (7 papers) and Data Quality and Management (5 papers). Hsia‐Ching Chang collaborates with scholars based in United States, Taiwan and Nigeria. Hsia‐Ching Chang's co-authors include Chen‐Ya Wang, Victor R. Prybutok, Suliman Hawamdeh, Seng‐Cho T. Chou, Jeonghyun Kim, Jiangping Chen, Jie Yang, Susan Squires, Abebe Rorissa and Yuan Zhang and has published in prestigious journals such as Computers in Human Behavior, Journal of Knowledge Management and Journal of Marketing Communications.

In The Last Decade

Hsia‐Ching Chang

26 papers receiving 363 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hsia‐Ching Chang United States	9	129	96	86	69	62	31	386
Spyros Angelopoulos United Kingdom	12	154 1.2×	62 0.6×	53 0.6×	79 1.1×	78 1.3×	38	461
Hsuanwei Michelle Chen United States	7	197 1.5×	73 0.8×	111 1.3×	106 1.5×	45 0.7×	16	399
Maria R. Lee Taiwan	9	138 1.1×	68 0.7×	129 1.5×	109 1.6×	57 0.9×	26	494
Christian Kittl Austria	6	90 0.7×	76 0.8×	85 1.0×	27 0.4×	78 1.3×	17	416
Rohit Valecha United States	13	289 2.2×	129 1.3×	119 1.4×	41 0.6×	139 2.2×	39	607
Luke Tredinnick United Kingdom	10	150 1.2×	127 1.3×	112 1.3×	55 0.8×	68 1.1×	45	454
Brian Whitworth New Zealand	14	140 1.1×	150 1.6×	103 1.2×	74 1.1×	75 1.2×	45	503
Tom Seymour United States	7	192 1.5×	79 0.8×	65 0.8×	62 0.9×	74 1.2×	13	463
Lianren Wu China	8	170 1.3×	61 0.6×	58 0.7×	162 2.3×	67 1.1×	25	445

Countries citing papers authored by Hsia‐Ching Chang

Since Specialization

Citations

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

Fields of papers citing papers by Hsia‐Ching Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsia‐Ching Chang. 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 Hsia‐Ching Chang. The network helps show where Hsia‐Ching Chang may publish in the future.

Co-authorship network of co-authors of Hsia‐Ching Chang

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

All Works

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20 of 20 papers shown

Chang, Hsia‐Ching, et al.. (2025). Investigating the symbiotic relationship between artificial intelligence and blockchain to promote zero-trust cybersecurity in an evolving information ecosystem. Information Discovery and Delivery.

Chang, Hsia‐Ching, et al.. (2023). A Scoping Review of Collaborative Information Behavior.

Prybutok, Victor R., et al.. (2022). How do morning and friendly ads influence mobile advertising? A mediation perspective using appraisal theory. Journal of Marketing Communications. 29(5). 510–532. 7 indexed citations

Hawamdeh, Suliman, et al.. (2020). Open access in the age of a pandemic. Proceedings of the Association for Information Science and Technology. 57(1). e295–e295. 4 indexed citations

Zhang, Yuan & Hsia‐Ching Chang. (2018). Selfies of Twitter Data Stream through the Lens of Information Theory: A Comparative Case Study of Tweet-trails with Healthcare Hashtags. Proceedings of the ... Annual Hawaii International Conference on System Sciences.

Chang, Hsia‐Ching, et al.. (2018). The current state of data governance in higher education. Proceedings of the Association for Information Science and Technology. 55(1). 198–206. 16 indexed citations

Wang, Chen‐Ya, Yi-Chun Lin, Hsia‐Ching Chang, & Seng‐Cho T. Chou. (2017). Consumer Sentiment in Tweets and Coupon Information-Sharing Behavior. RePEc: Research Papers in Economics. 7(3). 1–19. 1 indexed citations

Chang, Hsia‐Ching, et al.. (2017). Security and Privacy Issues with Smart Thermostats – A First Look. University of North Texas Digital Library (University of North Texas). 1 indexed citations

Chang, Hsia‐Ching, Susan Squires, & Chen‐Ya Wang. (2016). Using Trace Ethnography to Compare Perceived Cyber-Threats of IT to Non-IT Professionals. Americas Conference on Information Systems. 2 indexed citations

10.

Chang, Hsia‐Ching. (2016). Discovering Hashtag Trails with Cross-Platform Hashtag Search Engines: A State-of-Art Analysis. 3 indexed citations

11.

Chang, Hsia‐Ching. (2016). The Synergy of Scientometric Analysis and Knowledge Mapping with Topic Models: Modelling the Development Trajectories of Information Security and Cyber-Security Research. Journal of Information & Knowledge Management. 15(4). 1650044–1650044. 7 indexed citations

12.

Wang, Chen‐Ya, et al.. (2013). Acceptance and Willingness to Pay for Mobile TV Apps. Pacific Asia Conference on Information Systems. 260. 6 indexed citations

13.

Ho, Kevin, Hsia‐Ching Chang, & Wei‐Bin Lee. (2013). Effect of Noise on Gradient Systems. International Journal of Computer Theory and Engineering. 841–845.

14.

Chang, Hsia‐Ching, et al.. (2012). Trends in Twitter Hashtag Applications: Design Features for Value-Added Dimensions to Future Library Catalogues. Library trends. 61(1). 248–258. 24 indexed citations

15.

Wang, Chen‐Ya, Seng‐Cho T. Chou, & Hsia‐Ching Chang. (2010). Exploring An Individual’s Intention to Use Blogs: The Roles of Social, Motivational and Individual Factors. Pacific Asia Conference on Information Systems. 161. 11 indexed citations

16.

Chang, Hsia‐Ching. (2010). A new perspective on Twitter hashtag use: Diffusion of innovation theory. Proceedings of the American Society for Information Science and Technology. 47(1). 1–4. 166 indexed citations

17.

Wang, Chen‐Ya, Seng‐Cho T. Chou, & Hsia‐Ching Chang. (2009). THE MODERATING ROLE OF UTILITARIAN/HEDONIC USER MOTIVATION ON USER BEHAVIOUR TOWARDS WEB 2.0 APPLICATIONS. European Conference on Information Systems. 1430–1441. 3 indexed citations

18.

Wang, Chen‐Ya, Seng‐Cho T. Chou, & Hsia‐Ching Chang. (2009). Emotion and Motivation: Understanding User Behavior of Web 2.0 Application. 1. 1341–1346. 9 indexed citations

19.

Chang, Hsia‐Ching. (2009). Emotion barometer of reading. 3371–3376. 2 indexed citations

20.

Wang, Chen‐Ya, Seng‐Cho T. Chou, & Hsia‐Ching Chang. (2009). Examining the impacts of perceived value and perceived quality on users' intention to join web 2.0 communities. 329–334.

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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