ASMBI -《商業(yè)和工業(yè)中的應(yīng)用隨機(jī)模型》(前身為《應(yīng)用隨機(jī)模型和數(shù)據(jù)分析》)于1985年首次出版，發(fā)表了關(guān)于隨機(jī)模型、數(shù)據(jù)分析及其在商業(yè)、金融、保險(xiǎn)、管理和生產(chǎn)等方面的應(yīng)用的論文。2007年ASMBI成為國(guó)際商業(yè)和工業(yè)統(tǒng)計(jì)學(xué)會(huì)的官方期刊()。主要目標(biāo)是發(fā)表論文，包括技術(shù)和實(shí)踐方面的，提出解決現(xiàn)實(shí)問題的新結(jié)果，或在這方面有很大潛力。數(shù)學(xué)的嚴(yán)謹(jǐn)性、創(chuàng)新的隨機(jī)模型和完善的應(yīng)用程序是經(jīng)過非常有選擇性的評(píng)審過程后發(fā)表論文的關(guān)鍵因素。《華爾街日?qǐng)?bào)》是非常開放的新思想,如科學(xué)數(shù)據(jù)和大數(shù)據(jù)所帶來的問題在工程業(yè)務(wù)和行業(yè)或不確定性量化,以及傳統(tǒng)的,如可靠性、質(zhì)量控制、實(shí)驗(yàn)設(shè)計(jì)、管理流程、供應(yīng)鏈和庫存,保險(xiǎn)、計(jì)量經(jīng)濟(jì)學(xué)、金融建模(提供了論文相關(guān)的問題)。該雜志還對(duì)研究商業(yè)和工業(yè)決策對(duì)環(huán)境、醫(yī)療保健和社會(huì)生活的影響的論文感興趣。當(dāng)與可靠的應(yīng)用程序和創(chuàng)新的模型相結(jié)合時(shí)，最先進(jìn)的計(jì)算方法也非常受歡迎。

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 (). 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.