Applied Stochastic Models in Business and Industry

1.2k papers and 12.3k indexed citations i.

About

The 1.2k papers published in Applied Stochastic Models in Business and Industry in the last decades have received a total of 12.3k indexed citations. Papers published in Applied Stochastic Models in Business and Industry usually cover Statistics and Probability (440 papers), Management Science and Operations Research (333 papers) and Statistics, Probability and Uncertainty (273 papers) specifically the topics of Statistical Distribution Estimation and Applications (268 papers), Reliability and Maintenance Optimization (214 papers) and Financial Risk and Volatility Modeling (163 papers). The most active scholars publishing in Applied Stochastic Models in Business and Industry are Min Xie, Steven L. Scott, Zhi‐Sheng Ye, Stan Lipovetsky, Michael Conklin, Jorge Navarro, Maxim Finkelstein, J.B. Heaton, J. H. Witte and Nick Polson.

In The Last Decade

Fields of papers published in Applied Stochastic Models in Business and Industry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Applied Stochastic Models in Business and Industry. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Applied Stochastic Models in Business and Industry.

Countries where authors publish in Applied Stochastic Models in Business and Industry

Since Specialization
Citations

This map shows the geographic impact of research published in Applied Stochastic Models in Business and Industry. 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 papers published in Applied Stochastic Models in Business and Industry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Applied Stochastic Models in Business and Industry more than expected).

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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2025