Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Development and Validation of TQM Implementation Constructs
19961.4k citationsMatthew A. Waller et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
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Countries citing papers authored by Matthew A. Waller
Since
Specialization
Citations
This map shows the geographic impact of Matthew A. Waller'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 Matthew A. Waller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew A. Waller more than expected).
Fields of papers citing papers by Matthew A. Waller
This network shows the impact of papers produced by Matthew A. Waller. 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 Matthew A. Waller. The network helps show where Matthew A. Waller may publish in the future.
Co-authorship network of co-authors of Matthew A. Waller
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew A. Waller.
A scholar is included among the top collaborators of Matthew A. Waller 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 Matthew A. Waller. Matthew A. Waller is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Fawcett, Stanley E. & Matthew A. Waller. (2013). Moving the Needle: Making a Contribution When the Easy Questions Have Been Answered. SSRN Electronic Journal.1 indexed citations
Fawcett, Stanley E. & Matthew A. Waller. (2011). Making Sense Out of Chaos: Why Theory is Relevant to Supply Chain Research. SSRN Electronic Journal.3 indexed citations
Hardgrave, Bill C., et al.. (2008). Measuring the Impact of RFID on Out of Stocks at Wal-Mart. MIS Quarterly Executive. 7(4). 4–523.35 indexed citations
14.
Waller, Matthew A.. (2008). Building theory in business logistics through reviews of the literature : special issue. The International Journal of Logistics Management. 19(2).1 indexed citations
15.
Waller, Matthew A., Andrea Heintz Tangari, & Brent D. Williams. (2008). Case pack quantity's effect on retail market share. International Journal of Physical Distribution & Logistics Management. 38(6). 436–451.30 indexed citations
16.
Rutner, Stephen M., Matthew A. Waller, & John T. Mentzer. (2004). A PRACTICAL LOOK AT RFID. Supply chain management review.24 indexed citations
17.
Waller, Matthew A. & Robert A. Novack. (1995). USING POLICY CAPTURING TO IDENTIFY THE EFFECTS OF EXTERNAL CONSISTENCY ON LOGISTICS MANAGERS' PERFORMANCE. Transportation Journal. 34(3). 45–53.2 indexed citations
18.
Waller, Matthew A. & Robert A. Novack. (1995). THE EFFECTS OF JUDGMENTAL STRUCTURE, COMPLEXITY, AND CONSISTENCY ON MANAGERIAL PERFORMANCE.. Journal of Business Logistics.2 indexed citations
19.
Dunn, Steven C., et al.. (1994). LATENT VARIABLES IN BUSINESS LOGISTICS RESEARCH: SCALE DEVELOPMENT AND VALIDATION /. Journal of Business Logistics.365 indexed citations
20.
Waller, Matthew A., et al.. (1993). A NOTE ON RESEARCH METHODOLOGY IN BUSINESS LOGISTICS.. Logistics and transportation review.15 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.