Applied Stochastic Models in Business and Industry

Aims & Scope

ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production.

In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org).

The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so.

Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process.

The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems).

The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life.

State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.5
2024	1.30

Journal Rank

Year	Value
2024	13142

Journal Citation Indicator

Year	Value
2024	306

SJR (SCImago Journal Rank)

Year	Value
2024	0.428

Quartile

Year	Value
2024	Q2

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Decision Sciences and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Stochastic modelling and analysis of degradation for highly reliable products

  Citation: 577

  Authors: Zhi‐Sheng, Min

• Deep learning for finance: deep portfolios

  Citation: 467

  Authors: J. B., N. G., J. H.

• Analysis of regression in game theory approach

  Citation: 448

  Authors: Stan, Michael

• Applications of Hilbert–Huang transform to non‐stationary financial time series analysis

  Citation: 421

  Authors: Norden E., Man‐Li, Wendong, Steven R., Samuel S. P.

• A tutorial on <i>ν</i>‐support vector machines

  Citation: 388

  Authors: Pai‐Hsuen, Chih‐Jen, Bernhard

• A modern Bayesian look at the multi‐armed bandit

  Citation: 224

  Authors: Steven L.

• The COM‐Poisson model for count data: a survey of methods and applications

  Citation: 144

  Authors: Kimberly F., Sharad, Galit

• REBUS‐PLS: A response‐based procedure for detecting unit segments in PLS path modelling

  Citation: 135

  Authors: V., L., S., M.

• Stochastic ordering properties for systems with dependent identically distributed components

  Citation: 114

  Authors: Jorge, Yolanda, Miguel A., Alfonso

• Managing uncertainty in call centres using Poisson mixtures

  Citation: 113

  Authors: Geurt, Ger

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