Jack C. Hayya

3.1k citations
73 papers · 2.4k indexed · h-index 28

Jack C. Hayya

72 papers receiving 2.3k citations

Peers

Jack C. Hayya
Comparison fields: 5 of 117
  • Management Information Systems 1.7k
  • Industrial and Manufacturing Engineering 714
  • Strategy and Management 909
  • Management Science and Operations Research 505
  • Statistics, Probability and Uncertainty 191
Replace Charles S. Tapiero with:
Charles S. Tapiero United States
Hua Ke China
Amiya K. Chakravarty United States
Jeremy F. Shapiro United States
Abdul Raouf Canada
G. Hadley United States
Amy Hing‐Ling Lau United States
Apostolos Burnetas Greece
Fariborz Y. Partovi United States
Jean‐Marie Proth France
Jack C. Hayya relative to Charles S. Tapiero United States Charles S. Tapiero's profile →
Citations per field
00.5×3.5×
Charles S. Tapiero · 1×
Citations per year

Countries citing papers authored by Jack C. Hayya

Since Specialization
Citations

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

Fields of papers citing papers by Jack C. Hayya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack C. Hayya. 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 Jack C. Hayya. The network helps show where Jack C. Hayya may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jack C. Hayya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jack C. Hayya Line = papers co-authored together Jack C. Hayya links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20117
2 200646
3 200627
4 2005126
5 20051
6 20042
7
Supply Chain Information Technology Metrics
20031
8 200127
9 200111
10 199315
11 199348
12 19921
13 199280
14 1991108
15 199152
16 199014
17
ON THE DISTRIBUTION OF DEMAND DURING LEAD TIME.
19822
18 1982111
19 1975149
20 19744

About Jack C. Hayya

Jack C. Hayya is a scholar working on Management Information Systems, Industrial and Manufacturing Engineering and Management Science and Operations Research, having authored 73 papers that have together received 2.4k indexed citations. Recurring topics across this work include Supply Chain and Inventory Management (47 papers), Scheduling and Optimization Algorithms (17 papers), Advanced Queuing Theory Analysis (16 papers), Sustainable Supply Chain Management (11 papers), Business Process Modeling and Analysis (8 papers), Advanced Statistical Process Monitoring (8 papers), Forecasting Techniques and Applications (8 papers) and Simulation Techniques and Applications (6 papers). The work is most often cited by research in Management Information Systems (1.7k citations), Industrial and Manufacturing Engineering (714 citations) and Strategy and Management (909 citations). Jack C. Hayya has collaborated with scholars based in United States, Latvia and Canada. Frequent co-authors include Terry P. Harrison, Dean C. Chatfield, J. Keith Ord, Jae‐Dong Hong, Ranga V. Ramasesh, Chao‐Hsien Chu, Uttarayan Bagchi, John J. Kanet, Donald B. Armstrong and Susan H. Xu. Their work appears in journals such as International Journal of Production Economics, International Journal of Production Research, European Journal of Operational Research, Decision Sciences and Management Science.

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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