Applied Stochastic Models in Business and Industry最新文献

{"title":"Digital Twins: A Revolution in Modeling and Simulation","authors":"Jean-Michel Poggi, Murat Caner Testik","doi":"10.1002/asmb.70006","DOIUrl":"https://doi.org/10.1002/asmb.70006","url":null,"abstract":"","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143612409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pareto Optimal Proxy Metrics","authors":"Alessandro Zito,&nbsp;Dylan Greaves,&nbsp;Jacopo Soriano,&nbsp;Lee Richardson","doi":"10.1002/asmb.70003","DOIUrl":"https://doi.org/10.1002/asmb.70003","url":null,"abstract":"<div>\u0000 \u0000 <p>North star metrics and online experimentation play a central role in how technology companies improve their products. In many practical settings, however, evaluating experiments based on the north star metric directly can be difficult. The two most significant issues are (1) low sensitivity of the north star metric and (2) differences between the short-term and long-term impact on it. A common solution is to rely on proxy metrics rather than the north star in experiment evaluation and launch decisions. Existing literature on proxy metrics concentrates mainly on the estimation of the long-term impact from short-term experimental data. In this article, instead, we focus on the trade-off between the estimation of the long-term impact and the sensitivity in the short term. In particular, we propose the Pareto optimal proxy metrics method, which simultaneously optimizes prediction accuracy and sensitivity. We also give a multi-objective optimization algorithm to solve our specific problem. We apply our methodology to experiments from a large industrial recommendation system, and found proxy metrics that are eight times more sensitive than the north star and consistently moved in the same direction, increasing the velocity and the quality of the decisions to launch new features.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143595236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?","authors":"Fabrizio Ruggeri,&nbsp;David Banks,&nbsp;William S. Cleveland,&nbsp;Nicholas I. Fisher,&nbsp;Marcos Escobar-Anel,&nbsp;Paolo Giudici,&nbsp;Emanuela Raffinetti,&nbsp;Roger W. Hoerl,&nbsp;Dennis K. J. Lin,&nbsp;Ron S. Kenett,&nbsp;Wai Keung Li,&nbsp;Philip L. H. Yu,&nbsp;Jean-Michel Poggi,&nbsp;Marco S. Reis,&nbsp;Gilbert Saporta,&nbsp;Piercesare Secchi,&nbsp;Rituparna Sen,&nbsp;Ansgar Steland,&nbsp;Zhanpan Zhang","doi":"10.1002/asmb.70004","DOIUrl":"https://doi.org/10.1002/asmb.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>The paper arises from the experience of <i>Applied Stochastic Models in Business and Industry</i> which has seen, over the years, more and more contributions related to Machine Learning rather than to what was intended as a stochastic model. The very notion of a stochastic model (e.g., a Gaussian process or a Dynamic Linear Model) can be subject to change: What is a Deep Neural Network if not a stochastic model? The paper presents the views, supported by examples, of distinguished researchers in the field of business and industrial statistics. They are discussing not only whether there is a future for traditional stochastic models in the era of Machine Learning and Artificial Intelligence, but also how these fields can interact and gain new life for their development.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143595155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redundancy Allocation Problem in k-Out-Of-n Systems With Dependent and Heterogeneous Components","authors":"Zohreh Zare,&nbsp;Somayeh Zarezadeh,&nbsp;Mahmood Kharrati-Kopaei","doi":"10.1002/asmb.2932","DOIUrl":"https://doi.org/10.1002/asmb.2932","url":null,"abstract":"<div>\u0000 \u0000 <p>The aim of this paper is to investigate the problem of one and two active redundant components allocation in a <i>k</i>-out-of-<i>n</i> system with dependent components. Here, some necessary and sufficient conditions are presented under which the redundancies are optimally allocated to the system components based on the usual stochastic order criterion. In addition, it is shown that, unlike the independence mode, a redundant component is not necessarily allocated to the weakest component. Further, in the case of the two redundant components, the weak (strong) redundant component is not necessarily allocated to the stronger (weaker) component of the system. Some algorithms are also presented for calculating the reliability of the considered system under the assumption of dependency between the main and redundant components. Using different copula functions for describing the dependencies between components, various examples are given to illustrate the optimal allocation of redundant components.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143533555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mean Distances and Dependence Structures for Lifetimes of Systems With Shared Components","authors":"Marco Capaldo,&nbsp;Antonio Di Crescenzo,&nbsp;Franco Pellerey","doi":"10.1002/asmb.70002","DOIUrl":"https://doi.org/10.1002/asmb.70002","url":null,"abstract":"<p>Distortion and copula functions represent powerful tools in the description of the reliability of some complex systems as functions of their components' reliability. On this aim, we study several pairs of reliability systems with one or more shared components, in the case when their lifetimes are independent and identically distributed or independent but not identically distributed. We focus on the dependence that arises from sharing components, often described by Marshall-Olkin copulas, making use of some distance measures related to the Gini's mean difference and its new recent generalizations. A special role is played by a new distortion function related to the ROC curve.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143475533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Framework for Product Life Cycle Management Based Digital Twin Implementation in the Aerospace Industry","authors":"Busra Oksuz Gurdal,&nbsp;Ozlem Muge Testik","doi":"10.1002/asmb.70001","DOIUrl":"https://doi.org/10.1002/asmb.70001","url":null,"abstract":"<p>As an emerging technology, digital twin (DT) studies are gaining momentum in both academia and industry. Specifically, the aerospace industry can benefit significantly from the implementation of DT technology since its products and processes are complex, technically challenging, and costly. DTs enable a comprehensive technology integration capacity and holistic approach in the product life cycle. However, for simplification, implementations of DT to processes in the aerospace industry are often handled independently without integration with other related processes. In this study, we propose a methodological framework to integrate different processes throughout the essential parts of aircraft's life cycle. In pursuit of creating a DT of the system for managing the life cycle of aircraft, all aspects and processes have been thoroughly examined. Ten main components for the management of DTs are identified. Statistical and stochastic approaches for enhancing the analytical capabilities of DTs are discussed. Within the scope of Product Life Cycle Management and from the perspective of Systems Engineering, we advocate creating the DT of an aircraft by combining the DTs for each component through a digital thread.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 2","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling Task Durations Towards Automated, Big Data, Process Mining","authors":"Malcolm Faddy,&nbsp;Lingkai Yang,&nbsp;Sally McClean,&nbsp;Mark Donnelly,&nbsp;Kashaf Khan,&nbsp;Kevin Burke","doi":"10.1002/asmb.2933","DOIUrl":"https://doi.org/10.1002/asmb.2933","url":null,"abstract":"<p>Business processes are generally time-sensitive, impacting factors such as customer expectations, cost efficiencies, compliance requirements, supply chain constraints, and timely decision-making. Time analysis is therefore crucial for customer understanding and process congestion minimisation. Existing process mining methods mainly employ basic statistics, process discovery and data mining techniques. These approaches often lack a structured model or profile to characterise the data related to the duration of individual process tasks. Consequently, it can be difficult to comprehensively understand critical observations such as trends, peaks, and valleys of task durations. This paper proposes a parsimonious generic representation of task duration data that addresses these limitations. A mixture model comprising gamma, uniform and exponential distributions is proposed that allows for peaked components corresponding to durations terminating near a particular value (the peak) with, in addition, flatter components for durations terminating more randomly between the peaks. The modelling is validated using examples from patient billing and the telecom industry. In each scenario, the corresponding fitted models offer a good representation of the underlying process tasks. The model can therefore be used to improve knowledge of these tasks in terms of the mixture components and what they might represent, such as the root causes of task termination. The paper also considers information criteria more appropriate for large data sets where very small effects can appear “significant” using techniques developed for smaller data sets.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian Forecasting of Value-at-Risk and Expected Shortfall in Cryptocurrency Markets: A Nonlinear Semi-Parametric Framework","authors":"Cathy W. S. Chen,&nbsp;Po-Hui Chen,&nbsp;Ying-Lin Hsu","doi":"10.1002/asmb.2926","DOIUrl":"https://doi.org/10.1002/asmb.2926","url":null,"abstract":"<div>\u0000 \u0000 <p>Cryptocurrencies exhibit high volatility, emphasizing the importance of accurately measuring tail risk in their markets. This research incorporates a threshold-switching mechanism into Taylor's ES-CAViaR models that unveil features such as asymmetry and jump phenomena. These enhancements effectively capture the diverse tail risks of cryptocurrencies while enabling the simultaneous forecasting of both Value-at-Risk (VaR) and Expected Shortfall (ES). The proposed models incorporate two types of functions to address the VaR and ES nexus with the option to use the rolling standard deviation of returns as a short-term volatility proxy as a regressor. We estimate the parameters and forecast tail risk within a Bayesian framework. Taking the two largest cryptocurrencies by market capitalization, Bitcoin and Ethereum, we assess the one-step-ahead forecasting performance over a four-year out-of-sample period using a rolling window approach. The comparative results from backtests and five scoring functions among eight competing models support the conclusion that models with a threshold mechanism capture the tail risk of cryptocurrencies more accurately than other risk models.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foreword Special Issue on New Frontiers in Reliability and Risk Analysis: A Tribute to Nozer Darabsha Singpurwalla","authors":"Subrata Kundu,&nbsp;Thomas Mazzuchi,&nbsp;Kimberly F. Sellers,&nbsp;Refik Soyer","doi":"10.1002/asmb.70000","DOIUrl":"https://doi.org/10.1002/asmb.70000","url":null,"abstract":"&lt;p&gt;Nozer D. Singpurwalla (1939–2022)&lt;/p&gt;&lt;p&gt;We are honored to be guest editors for this special issue of &lt;i&gt;Applied Stochastic Models in Business and Industry&lt;/i&gt; which is a tribute to Nozer D. Singpurwalla's scholarly work and achievements. The special issue contains seventeen papers. Four of these papers were based on presented talks at the 2-day conference entitled &lt;i&gt;New Frontiers in Reliability and Risk Analysis&lt;/i&gt;, held on October 13–14, 2023 at The George Washington University in Washington, DC. The conference, which was dedicated to Nozer, brought together leading experts and young researchers in the fields in which Nozer was a major contributor, that is reliability, risk analysis, and Bayesian statistics. The special issue includes contributions on these topics from Nozer's friends and colleagues as well as from other researchers.&lt;/p&gt;&lt;p&gt;The first article by Soyer and Spizzichino presents an overview of Nozer's work in reliability and risk analysis as well as his interests in foundational aspects of statistics, probability, and decision analysis. The paper by Li, Tierney, Hellmayr, and West deals with sequential Bayesian analysis of multivariate time series models with a focus on causal inference which were both areas of interest to Nozer.&lt;/p&gt;&lt;p&gt;The next two papers are on topics that attracted Nozer's attention due to their foundational implications. Sellers and Booker describe their collaborations with Nozer regarding the connections of fuzzy sets with probability and reliability theory. The authors further discuss subsequent advances in this space and the perceptions across disciplines (particularly among statisticians and data scientists) over the last 20 years. The article by Polson and Sokolov presents an introduction to the notions of negative probability, which was of interest to Nozer during his final years, and the authors give a version of Bayes rule for such probabilities.&lt;/p&gt;&lt;p&gt;The article by Arkadani, Asadi, and Soofi builds on earlier work by Nozer on the comparison of informativeness of failures versus survivals in life testing. The authors consider a comparison of the information on moments and the model parameters and develop information measures. Finkelstein and Cha present an overview of mixture failure rates (that Nozer often referred to as “predictive failure rate”) to model heterogeneity in reliability and discuss recent developments on the topic including the stochastic intensity paradox.&lt;/p&gt;&lt;p&gt;The articles by Limnios, and Palayangoda and Balakrishnan deal with gamma processes for degradation modeling. Nozer used the gamma process in his study of Bayesian life testing, and failure processes in dynamic and multiple failure mode environments. Limnios considers a gamma process for degradation under a random environment modeled by a Markov process and presents results for averaging and normal deviation. Palayangoda and Balakrishnan consider a complete likelihood for the gamma processes and develop inference using the EM","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IIoT and Digital Twin: A Systematic Literature Review and Looking Beyond the State","authors":"Thomas Bleistein,&nbsp;Moritz Paulus,&nbsp;Kiran Gani,&nbsp;Robert Becker,&nbsp;Dirk Werth","doi":"10.1002/asmb.2923","DOIUrl":"https://doi.org/10.1002/asmb.2923","url":null,"abstract":"<div>\u0000 \u0000 <p>The fourth industrial revolution has driven the emergence of Digital Twins (DTs) and Industrial Internet of Things (IIoT) in manufacturing. However, the use of different definition has led to varied interpretations and inconsistent understanding of DTs. Thus, by exploring the gap between theoretical frameworks and practical implementations of IIoT-based DTs in manufacturing, this paper aims to shed light on the DT phenomenon by considering the historical evolution and fundamental concepts of IIoT-based DTs. Therefore, a systematic literature review was conducted to assess the ambiguity concerning DTs, particularly in distinguishing architectures and types. Therefore, this paper identifies IIoT-based DTs in manufacturing by reviewing application-oriented literature. As a result of a subsequent classification, this paper proposes a hierarchical classification based on communication dynamics (i.e., Uni-directional and Bi-directional) and information processing (i.e., use or non-use of machine learning). Conclusively, this study proposes a comprehensive classification approach for IIoT-based DTs and thus contributes to a more consistent understanding of the DT phenomenon. Moreover, this paper discusses key findings, as well as implications for research and practice. Finally potential avenues for future research are derived and the limitations of this study are discussed.</p>\u0000 </div>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"41 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}