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.
First-mover advantages
19882.5k citationsDavid B. Montgomery et al.profile →
First-mover (dis)advantages: retrospective and link with the resource-based view
1998670 citationsDavid B. Montgomery et al.profile →
Citations per year, relative to David B. Montgomery David B. Montgomery (= 1×)
peers
Curtis M. Grimm
Countries citing papers authored by David B. Montgomery
Since
Specialization
Citations
This map shows the geographic impact of David B. Montgomery'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 David B. Montgomery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David B. Montgomery more than expected).
Fields of papers citing papers by David B. Montgomery
This network shows the impact of papers produced by David B. Montgomery. 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 David B. Montgomery. The network helps show where David B. Montgomery may publish in the future.
Co-authorship network of co-authors of David B. Montgomery
This figure shows the co-authorship network connecting the top 25 collaborators of David B. Montgomery.
A scholar is included among the top collaborators of David B. Montgomery 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 David B. Montgomery. David B. Montgomery is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Urbany, Joel E., David B. Montgomery, & Marian Chapman Moore. (2001). Competitive reactions and modes of comtetitive reasonings : downplaying the unpredictable?. Marketing Science Institute eBooks.1 indexed citations
3.
Montgomery, David B. & George S. Yip. (2000). The Challenge of Global Customer Management. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 9(4). 22.45 indexed citations
4.
Hausman, Warren H., David B. Montgomery, & Aleda V. Roth. (2000). Exploring the Impact of Marketing and Manufacturing Strategies, Conflict, and Morale on Business Performance. RePEc: Research Papers in Economics.1 indexed citations
5.
Montgomery, David B. & George S. Day. (1999). Fundamental Issues and Directions for Marketing. Journal of Marketing.9 indexed citations
6.
Montgomery, David B., George S. Yip, & Belén Villalonga. (1999). Demand for and use of global account management. OpenGrey (Institut de l'Information Scientifique et Technique).13 indexed citations
7.
Clark, Bruce H. & David B. Montgomery. (1996). Perceiving competitive reactions : the value of accuracy (and paranoia) : working paper. Marketing Science Institute eBooks.1 indexed citations
8.
Montgomery, David B.. (1988). On Negative Binomial Distribution: Comment. Journal of Business and Economic Statistics. 6(2). 163–164.1 indexed citations
9.
Montgomery, David B.. (1985). Conjoint Calibration of the Customer/Competitor Interface in Industrial Markets. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University).10 indexed citations
10.
Montgomery, David B. & George S. Day. (1985). Experience Curves: Evidence, Empirical Issues, and Applications. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University).14 indexed citations
11.
Day, George S. & David B. Montgomery. (1983). Diagnosing the Experience Curve. Journal of Marketing. 47(2). 44–58.60 indexed citations
12.
Montgomery, David B., et al.. (1980). Proceedings of the First ORSA/TIMS Special Interest Conference on Market Measurement and Analysis. Marketing Science Institute eBooks.5 indexed citations
13.
Seaman, Bruce A., et al.. (1976). ¥FTROFF : a basic program for trade-off analysis. Marketing Science Institute eBooks.2 indexed citations
14.
Montgomery, David B. & Charles B. Weinberg. (1974). Modeling marketing phenomena : a managerial perspective. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 2. 17.11 indexed citations
15.
Montgomery, David B., et al.. (1972). FORAC MOD I : a computer program for forecast evaluation statistics. Journal of Marketing Research. 9(2). 200.5 indexed citations
16.
Montgomery, David B. & Adrian B. Ryans. (1971). Stochastic models of consumer choice behavior. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University).8 indexed citations
17.
Montgomery, David B.. (1970). Developing a Balanced Marketing Information System. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 3.4 indexed citations
18.
Montgomery, David B. & Glen L. Urban. (1970). Applications of management sciences in marketing. Prentice Hall eBooks.2 indexed citations
19.
Montgomery, David B.. (1968). Stochastic Consumer Models: Some Comparative Results. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 71(7).4 indexed citations
20.
Montgomery, David B. & C. T. Yang. (1958). Orbits of highest dimension. Transactions of the American Mathematical Society. 87(2). 284–293.17 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.