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Designing a data mining process for the financial services domain 为金融服务领域设计一个数据挖掘流程
Journal of Business Analytics Pub Date : 2022-07-07 DOI: 10.1080/2573234X.2022.2088412
V. Plotnikova, M. Dumas, Alexander Nolte, Fredrik P. Milani
{"title":"Designing a data mining process for the financial services domain","authors":"V. Plotnikova, M. Dumas, Alexander Nolte, Fredrik P. Milani","doi":"10.1080/2573234X.2022.2088412","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2088412","url":null,"abstract":"ABSTRACT The implementation of data mining projects in complex organisations requires well-defined processes. Standard data mining processes, such as CRISP-DM, have gained broad adoption over the past two decades. However, numerous studies demonstrated that organisations often do not apply CRISP-DM and related processes as-is, but rather adapt them to address industry-specific requirements. Accordingly, a number of sector-specific adaptations of standard data mining processes have been proposed. So far, however, no such adaptation has been suggested for the financial services sector. This paper addresses the gap by designing and evaluating a Financial Industry Process for Data Mining (FIN-DM). FIN-DM adapts and extends CRISP-DM to address regulatory compliance, governance, and risk management requirements inherent in the financial sector, and to embed quality assurance as an integral part of the data mining project life-cycle. The framework has been iteratively designed and validated with data mining and IT experts in a financial services organisation.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"60 1","pages":"140 - 166"},"PeriodicalIF":0.0,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74394433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-objective programming for designing sustainable biogas supply chain: a case study in North Dakota, USA 可持续沼气供应链设计的多目标规划——以美国北达科他州为例
Journal of Business Analytics Pub Date : 2022-07-03 DOI: 10.1080/2573234X.2022.2103040
Yuan Xu, Y. Park, O. Jadidi, John S. Loucks, Joseph G. Szmerekovsky
{"title":"Multi-objective programming for designing sustainable biogas supply chain: a case study in North Dakota, USA","authors":"Yuan Xu, Y. Park, O. Jadidi, John S. Loucks, Joseph G. Szmerekovsky","doi":"10.1080/2573234X.2022.2103040","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2103040","url":null,"abstract":"ABSTRACT This study considers the environmental and social impacts of an animal waste sourced biogas supply chain, along with economic factors for making tactical and strategic decisions. A multi-objective optimisation model is introduced to determine: 1) the best locations and capacities of biogas plants to treat cattle manure from dairy farms, and 2) the best transportation assignments from each farm to a subset of the opened biogas plants. This study formulates three objectives that include minimising total supply chain cost, carbon emissions, and social rejection. An augmented ε-constraint method is employed as a solution approach to solve the multi-objective problem. The results indicate the implementation of the proposed optimisation model has the potential to provide significant economic, environmental, and social benefits. In addition, the study finds that the allowed maximum transport distance contributes to the number and size of biogas plants used.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"64 1","pages":"188 - 200"},"PeriodicalIF":0.0,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75098384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Impact of mobility based network on COVID-19 spread 基于移动性的网络对COVID-19传播的影响
Journal of Business Analytics Pub Date : 2022-07-03 DOI: 10.1080/2573234X.2022.2088411
Arindam Ray, Wolfgang Jank, K. Dutta
{"title":"Impact of mobility based network on COVID-19 spread","authors":"Arindam Ray, Wolfgang Jank, K. Dutta","doi":"10.1080/2573234X.2022.2088411","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2088411","url":null,"abstract":"ABSTRACT COVID-19 has had a strong impact on this world. With the spreading of the virus and the implementation of various mitigation measures, the pandemic has indubitably upended our way of living. Research indicates that mobility is one of the key reasons of the spread. The purpose of this paper is to provide a suitable mobility measure based on intra-county and inter-county movements on the spreading of COVID-19 in the United States. Deviating from the extant research, which measures mobility by the average distance people travel, we operationalise mobility by the number of trips made. We further weigh them based on the current caseload, as the spread will not only depend on how many people are moving but also the proportion of infectious people within them. We also distinguish such trips based on their origin and destination, as that may help in taking appropriate policy decisions for intervention.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"35 1","pages":"179 - 187"},"PeriodicalIF":0.0,"publicationDate":"2022-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87644200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forecasting natural gas consumption in residential and commercial sectors in the US 预测美国住宅和商业部门的天然气消费量
Journal of Business Analytics Pub Date : 2022-04-18 DOI: 10.1080/2573234X.2022.2064777
Xingxing Zu, Xiaoyin Wang, Yunwei Cui
{"title":"Forecasting natural gas consumption in residential and commercial sectors in the US","authors":"Xingxing Zu, Xiaoyin Wang, Yunwei Cui","doi":"10.1080/2573234X.2022.2064777","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2064777","url":null,"abstract":"ABSTRACT The paper proposes a parallel forecasting approach for weekly natural gas consumption in the US residential and commercial sectors, which models scrape data and ratio data separately and then combines the outputs to generate the forecasts. To improve forecasting accuracy, both semi-parametric and nonparametric models, including dynamic linear regression model and dynamic semi-parametric model, are adopted to model the effects of weather variables, and time series techniques are employed to address the serial correlation exhibited by the data. An algorithm focusing on forecasting accuracy is proposed to select the smoothing parameter for serially correlated data. The proposed model is empirically tested using data in the New England area from 2013 to 2018 and benchmarked against some deep learning approaches including Deep Neural Network, Long Short-Term Memory Neural Network, and Gated Recurrent Unit Neural Network methods. Overall, the results show that the proposed approach performs well in generating accurate forecasts.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"19 1","pages":"77 - 94"},"PeriodicalIF":0.0,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75259846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Artificial intelligence in energy industry: forecasting electricity consumption through cohort intelligence & adaptive neural fuzzy inference system 能源工业中的人工智能:通过队列智能和自适应神经模糊推理系统预测用电量
Journal of Business Analytics Pub Date : 2022-03-10 DOI: 10.1080/2573234X.2022.2046514
Salih Tutun, Ali Tosyali, H. Sangrody, Mohammad Khasawneh, Marina Johnson, Abdullah Albizri, A. Harfouche
{"title":"Artificial intelligence in energy industry: forecasting electricity consumption through cohort intelligence & adaptive neural fuzzy inference system","authors":"Salih Tutun, Ali Tosyali, H. Sangrody, Mohammad Khasawneh, Marina Johnson, Abdullah Albizri, A. Harfouche","doi":"10.1080/2573234X.2022.2046514","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2046514","url":null,"abstract":"ABSTRACT Demand forecasting is critical for energy systems, as energy is difficult to store and should only be supplied as needed. Researchers attempted to improve forecasts of energy consumption. However, they assume independent factors increase at a constant growth rate, which is unrealistic. Existing methods are designed to determine annual consumption, whereas energy-planning organizations rely on short- or medium-term consumption values. Therefore, we propose a new forecasting framework that introduces new models and scenarios. We apply a cohort intelligence-based adaptive neuro-fuzzy inference system (CI-ANFIS) with a subtractive clustering and grid partition approach to forecast net electricity consumption. One challenge in accurately predicting electricity consumption for specific projection intervals is missing values for factors independent of those known for existing net consumption. Then, we utilize a regression equation scenario approach. We test our framework using a real-world energy consumption dataset and show that our proposed framework outperforms the existing methods.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"42 1","pages":"59 - 76"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78712967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Winning one-day international cricket matches: a cross-team perspective 赢得为期一天的国际板球比赛:跨团队视角
Journal of Business Analytics Pub Date : 2022-02-20 DOI: 10.1080/2573234X.2022.2041370
Subrat Sarangi, R. Singh
{"title":"Winning one-day international cricket matches: a cross-team perspective","authors":"Subrat Sarangi, R. Singh","doi":"10.1080/2573234X.2022.2041370","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2041370","url":null,"abstract":"ABSTRACT The study analyses the predictors of a win for four international cricket teams in the one-day international cricket format. A binary logistic regression is used to determine the relationship between the independent variables, i.e., fours and sixes scored, bowling economy, extras conceded, fielding dismissals, the number of debutants from each side, umpire’s nationality, pitch condition, and season of play vis-à-vis odds of a win. The study found that the number of fielding dismissals and bowler economy significantly influence the odds of winning for all four teams. Further, the nationality of the umpire did not affect any team, while other variables influenced the fortunes of different teams differently. Proposed models in the paper can be used by team management and coaches in devising match strategy and player selection for higher win outcomes based on a combination of historical trend data for specific variables and actual data for the others.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"102 1","pages":"39 - 58"},"PeriodicalIF":0.0,"publicationDate":"2022-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82841488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Business analytics and big data research in information systems 信息系统中的商业分析和大数据研究
Journal of Business Analytics Pub Date : 2022-01-02 DOI: 10.1080/2573234X.2022.2069426
Christian Janiesch, Barbara Dinter, Patrick Mikalef, Olgerta Tona
{"title":"Business analytics and big data research in information systems","authors":"Christian Janiesch, Barbara Dinter, Patrick Mikalef, Olgerta Tona","doi":"10.1080/2573234X.2022.2069426","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2069426","url":null,"abstract":"ABSTRACT Business analytics and big data have been at the center of interest for researchers and practitioners for almost a decade now. The methods and processes that comprise business analytics, combined with the rich information that can be extracted from big data have enabled organizations to generate rich insight which is critical to decision making. The scientific inquiry in this interdisciplinary domain has had a long and successful history at the European Conference on Information Systems (ECIS). We provide a synthesis of prominent themes that have appeared during the past decade within the “Business Analytics and Big Data” track of ECIS. Based on the synthesis, we provide a narrative of how the field has evolved, as well as where we see future research efforts being focused. Specifically, we identify three areas that are likely to attract considerable research interest in the years to come. Within each of these three areas, we describe several key challenges that need to be addressed. We conclude with an overview of the six articles included in this special issue, and a description of how they contribute to our understanding of this domain.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"34 1","pages":"1 - 7"},"PeriodicalIF":0.0,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90930919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
In-game win probability models for Canadian football 加拿大足球游戏中的获胜概率模型
Journal of Business Analytics Pub Date : 2021-12-18 DOI: 10.1080/2573234X.2021.2015252
S. Hill
{"title":"In-game win probability models for Canadian football","authors":"S. Hill","doi":"10.1080/2573234X.2021.2015252","DOIUrl":"https://doi.org/10.1080/2573234X.2021.2015252","url":null,"abstract":"ABSTRACT This article presents in-game win probability models for Canadian football. Play-by-play and wagering data for games from the Canadian Football League for the 2015 to 2019 seasons is used to create logistic regression and gradient boosting models. Models with and without the effect of pregame spread and total (over/under) data are presented and discussed. The resulting win probability models are well-calibrated and can be used to support in-game decision-making, review coaching decisions, estimate the magnitude of team “comebacks”, and potentially identify in-game wagering opportunities. An R Shiny application is provided to allow for estimation of in-game win probability for user-provided game state inputs. Opportunities for future work are identified and described.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"3 1","pages":"164 - 178"},"PeriodicalIF":0.0,"publicationDate":"2021-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82034173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data 检测业务流程中的临时变通方法——一种基于深度学习的分析事件日志数据的方法
Journal of Business Analytics Pub Date : 2021-12-07 DOI: 10.1080/2573234X.2021.1978337
Sven Weinzierl, Verena Wolf, Tobias Pauli, D. Beverungen, Martin Matzner
{"title":"Detecting temporal workarounds in business processes – A deep-learning-based method for analysing event log data","authors":"Sven Weinzierl, Verena Wolf, Tobias Pauli, D. Beverungen, Martin Matzner","doi":"10.1080/2573234X.2021.1978337","DOIUrl":"https://doi.org/10.1080/2573234X.2021.1978337","url":null,"abstract":"ABSTRACT Business process management distinguishes the actual “as-is” and a prescribed “to-be” state of a process. In practice, many different causes trigger a process’s drifting away from its to-be state. For instance, employees may “workaround” the proposed systems to increase their effectiveness or efficiency in day-to-day work. So far, ethnography or critical incident techniques are used to identify how and why workarounds emerge. We design a deep-learning-based method that helps detect different workaround types in event logs. Our method tracks indications of potential workarounds in the early stages of their emergence among deviating behaviour. Our evaluation based on four real-life event logs reveals that our method performs well and works best for business processes with fewer variations and a higher number of different activities. The proposed method is one of the first information technology artefacts to bridge the boundaries between the complementing research disciplines of organisational routines and business processes management.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"1 1","pages":"76 - 100"},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79830638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Optimal trimming proportion in regression analysis for non-normal distributions 非正态分布回归分析中的最优修剪比例
Journal of Business Analytics Pub Date : 2021-11-29 DOI: 10.1080/2573234X.2021.2007803
Amit Mitra, Pankush Kalgotra
{"title":"Optimal trimming proportion in regression analysis for non-normal distributions","authors":"Amit Mitra, Pankush Kalgotra","doi":"10.1080/2573234X.2021.2007803","DOIUrl":"https://doi.org/10.1080/2573234X.2021.2007803","url":null,"abstract":"ABSTRACT Regression analysis is a widely used modelling tool in business decision making. However, proper application of this methodology requires that certain assumptions, associated with the model, be satisfied. The assumption we focus on is the normality of the response variable, which is directly related to the assumption of normality of the error component. In a variety of fields in business, such as finance, marketing, information systems, operations, and healthcare, the selected dependent variable does not inherently have a normal distribution. In the regression context, where the model parameters and independent variables are assumed to be constant, the distribution of the random error component thus influences the distribution of the dependent variable. Here, we study the impact of symmetric and asymmetric error distributions on the performance of the estimated model parameters. To create robust estimates, through a process of trimming the response variable, we study the effectiveness of the trimmed estimators with respect to the ordinary least squares estimator (OLS) via a simulation procedure. Accordingly, to minimise the ratio of the mean squared error of the trimmed estimator to that of the OLS, a recommendation is developed for the optimal trimming proportion.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"53 1","pages":"152 - 163"},"PeriodicalIF":0.0,"publicationDate":"2021-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89816712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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