William H. Money

34 papers receiving 939 citations

Hit Papers

Big Data: Issues and Challenges Moving Forward20132026201720212013100200300400500

Peers

William H. Money
Comparison fields: 5 of 109
  • Management Information Systems 369
  • Information Systems 302
  • Information Systems and Management 267
  • Management Science and Operations Research 189
  • Artificial Intelligence 158
Replace Vijay Khatri with:
Vijay Khatri United States
Atish P. Sinha United States
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William H. Money relative to Vijay Khatri United States Vijay Khatri's profile →
Citations per field
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Citations per year

Countries citing papers authored by William H. Money

Since Specialization
Citations

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

Fields of papers citing papers by William H. Money

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William H. Money. 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 William H. Money. The network helps show where William H. Money may publish in the future.

Co-authorship network of co-authors of William H. Money

This figure shows the co-authorship network connecting the top 25 collaborators of William H. Money. A scholar is included among the top collaborators of William H. Money 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 William H. Money. William H. Money 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
Integration of Information Systems: Robotic Process Automation
0
4 10
5 1
6 37
7
Cloud Computing: Implications for Information Systems Development Service Providers and Practitioners
1
8 7
9 6
10 4
11 4
12 14
13
Big Data: Issues and Challenges Moving Forwardbreakdown →
571
14 36
15
Online social networking: a task-person-technology fit perspective
11
16 67
17
An assessment of the impact of the fit among computer self-efficacy, task characteristics and systems characteristics on performance and information systems utilization
1
18
Decision support and information system tools for effective team project planning
1
19 18
20 12

About William H. Money

William H. Money is a scholar working on Information Systems and Management, Management Information Systems and Health Informatics, having authored 35 papers that have together received 1.0k indexed citations. Recurring topics across this work include Big Data and Business Intelligence (8 papers), Technology Adoption and User Behaviour (7 papers) and Cloud Computing and Resource Management (5 papers). The work is most often cited by research in Management Information Systems (369 citations), Information Systems and Management (267 citations) and Management Science and Operations Research (189 citations). William H. Money has collaborated with scholars based in United States, Finland and United Kingdom. Frequent co-authors include Stephen H. Kaisler, Frank Armour, J. Alberto Espinosa, Frank T. Anbari, John R. Schermerhorn, Myron D. Fottler, John K. Wong, Brendan D. Bannister, Chester A. Schriesheim and John W. Wong. Their work appears in journals such as Academy of Management Review, Computers & Education and Journal of Management Information Systems.

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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