William J. Tastle

675 total citations
32 papers, 413 citations indexed

About

William J. Tastle is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, William J. Tastle has authored 32 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Management Science and Operations Research, 8 papers in Artificial Intelligence and 5 papers in Computational Theory and Mathematics. Recurrent topics in William J. Tastle's work include Multi-Criteria Decision Making (8 papers), Rough Sets and Fuzzy Logic (5 papers) and Teaching and Learning Programming (3 papers). William J. Tastle is often cited by papers focused on Multi-Criteria Decision Making (8 papers), Rough Sets and Fuzzy Logic (5 papers) and Teaching and Learning Programming (3 papers). William J. Tastle collaborates with scholars based in United States, Iceland and Switzerland. William J. Tastle's co-authors include Mark J. Wierman, Massimo Buscema, Uldarico Rex Dumdum, Eileen P. Kelly, Barbara Russell, Amjad Abdullat, Jeffry Babb, John N. Mordeson and Terry D. Clark and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the Association for Information Systems and Behavior Research Methods.

In The Last Decade

William J. Tastle

29 papers receiving 369 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
William J. Tastle United States	11	65	58	54	53	51	32	413
Rafael A. González Colombia	10	73 1.1×	75 1.3×	81 1.5×	123 2.3×	61 1.2×	46	604
Antonia Ferrer-Sapena Spain	12	43 0.7×	59 1.0×	21 0.4×	52 1.0×	159 3.1×	76	446
Lee T. Ostrom United States	8	31 0.5×	79 1.4×	70 1.3×	15 0.3×	47 0.9×	19	491
Carlos Olmeda‐Gómez Spain	11	19 0.3×	46 0.8×	29 0.5×	51 1.0×	131 2.6×	46	565
Abdel‐Salam G. Abdel‐Salam Qatar	15	56 0.9×	30 0.5×	60 1.1×	40 0.8×	27 0.5×	70	647
Ryan J. Baxter United States	11	47 0.7×	65 1.1×	26 0.5×	25 0.5×	52 1.0×	33	567
Hanns de la Fuente‐Mella Chile	12	45 0.7×	30 0.5×	54 1.0×	34 0.6×	34 0.7×	73	442
Carmen López-Illescas Spain	10	26 0.4×	31 0.5×	28 0.5×	31 0.6×	101 2.0×	23	506
Javier López Gijón Spain	6	75 1.2×	39 0.7×	16 0.3×	67 1.3×	48 0.9×	25	324
Zehra Taşkın Türkiye	12	32 0.5×	30 0.5×	26 0.5×	72 1.4×	94 1.8×	35	386

Countries citing papers authored by William J. Tastle

Since Specialization

Citations

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

Fields of papers citing papers by William J. Tastle

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William J. Tastle

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Babb, Jeffry, et al.. (2016). Use of Failure in IS Development Statistics: Lessons for IS Curriculum Design. Information Systems Education Journal. 14(5). 44–61. 1 indexed citations

Buscema, Massimo & William J. Tastle. (2015). Artificial Neural Network What-If Theory. International Journal of Information Systems and Social Change. 6(4). 52–81. 3 indexed citations

Buscema, Massimo & William J. Tastle. (2012). Intelligent Data Mining in Law Enforcement Analytics. DIAL (Catholic University of Leuven). 8 indexed citations

Russell, Barbara, et al.. (2010). A Study of the Programming Languages Used in Information Systems and in Computer Science Curricula.. Information Systems Education Journal. 8(56). 3 indexed citations

Tastle, William J., Amjad Abdullat, & Mark J. Wierman. (2010). A New Approach in Requirements Elicitation Analysis. Journal of Emerging Technologies in Web Intelligence. 2(3). 1 indexed citations

Tastle, William J.. (2009). Measuring Faculty Instructional Performance. Information Systems Education Journal. 26(20). 93–7. 1 indexed citations

Tastle, William J., et al.. (2009). Emerging trends in information technology departments of major Icelandic corporations. International Journal of Commerce and Management. 19(3). 195–207.

Tastle, William J., et al.. (2007). Assessing Team Performance in Information Systems Projects. Digital Collections - Ithaca College Library (Ithaca College). 24. 4 indexed citations

Tastle, William J. & Mark J. Wierman. (2007). Using Consensus to Measure Weighted Targeted Agreement. 31–35. 10 indexed citations

10.

Tastle, William J., et al.. (2006). A New Tool in IS Management: Geographic Information Systems. Information Systems Education Journal. 4(12). 3 indexed citations

11.

Tastle, William J. & Mark J. Wierman. (2006). An information theoretic measure for the evaluation of ordinal scale data. Behavior Research Methods. 38(3). 487–494. 36 indexed citations

12.

Wierman, Mark J. & William J. Tastle. (2006). Placing the Dissonance Measure in the Context of Generalized Information Theory. 253–256. 4 indexed citations

13.

Tastle, William J. & Mark J. Wierman. (2006). Consensus and dissention: A measure of ordinal dispersion. International Journal of Approximate Reasoning. 45(3). 531–545. 171 indexed citations

14.

Tastle, William J., et al.. (2005). A new measure to analyze student performance using the likert scale. Digital Collections - Ithaca College Library (Ithaca College). 29(1-2). 19–21. 19 indexed citations

15.

Tastle, William J., Mark J. Wierman, & Uldarico Rex Dumdum. (2005). RANKING ORDINAL SCALES USING THE CONSENSUS MEASURE. SHILAP Revista de lepidopterología. 31 indexed citations

16.

Tastle, William J. & Mark J. Wierman. (2005). Consensus and Dissention: A New Measure of Agreement. 385–388. 15 indexed citations

17.

Kelly, Eileen P. & William J. Tastle. (2004). E-government and the judicial system: online access to case information. Electronic Government an International Journal. 1(2). 166–166. 14 indexed citations

18.

Tastle, William J., et al.. (2003). Analysis and Design: Assessing Actual and Desired Course Content. Journal of the Association for Information Systems. 14(1). 77–90. 5 indexed citations

19.

Tastle, William J. & Uldarico Rex Dumdum. (1998). Globalization Issues in Information Systems Education: Toward a Collaborative Multischool Systems Analysis Experience. Journal of the Association for Information Systems. 9(3). 19–23. 2 indexed citations

20.

Tastle, William J.. (1996). INTRODUCTION TO THE SPECIAL ISSUE ON THE GENERAL SYSTEMS PROBLEM SOLVER. International Journal of General Systems. 24(1-2). 1–3. 1 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.

Explore authors with similar magnitude of impact