Journal of Business Analytics

Journal of Business Analytics is a quarterly peer-reviewed journal from Taylor & Francis that publishes research on how data and quantitative methods shape commercial and organisational decisions, and its 2025 Journal Impact Factor is 1.9.《商业分析杂志》（Journal of Business Analytics）由 Taylor & Francis 按季出版，刊载数据与定量方法如何影响商业及组织决策的研究，2025 年期刊影响因子为 1.9。

The first volume carried a 2018 cover date, and the run has since reached nine volumes, listed in two Emerging Sources Citation Index categories and placed in the third quartile of both.第 1 卷标注 2018 年，此后已出到第 9 卷，在两个新兴来源引文索引类目中均列第三分位。

Scope

• Analytics here means the whole chain from data capture to decision, and papers are expected to say which link of that chain they alter instead of reporting a model in isolation.这里的分析指从数据采集到决策的整条链条，论文需说明自己改变了链条的哪一段，而不是孤立地报告一个模型。
• Descriptive work arrives through dashboards, data storytelling and maturity assessments, including studies of how firms visualise performance and how analytics capability in an organisation is actually measured.描述性工作见于仪表盘、数据叙事与成熟度评估，包括企业如何呈现绩效以及如何度量分析能力的研究。
• Predictive studies form the largest block, covering demand and price forecasting, customer churn and employee attrition, share and electricity prices, and hybrid pipelines that pair statistical baselines with machine learning.预测性研究占比最大，涉及需求与价格预测、流失与离职模型、股价与电价预测，以及统计方法与机器学习混合的流程。
• Prescriptive analytics appears through optimisation, game-theoretic supply chain design, multi-criteria evaluation with fuzzy sets, and reinforcement learning applied to pricing and scarce capacity.规范性分析经优化建模、博弈论供应链设计、模糊集多准则评价，以及用于定价与稀缺容量分配的强化学习进入版面。
• Machine learning and deep learning carry much of the empirical load, from gradient boosted trees and long short-term memory networks to graph neural networks and federated learning over non-IID data.机器学习与深度学习承担多数实证工作，从梯度提升树与长短期记忆网络，到图神经网络与非独立同分布数据下的联邦学习。
• Text analytics reaches prospectuses, management discussion sections, open-ended survey answers and social media, with topic models, sentiment dictionaries and pretrained language models used side by side.文本分析覆盖招股说明书、管理层讨论、开放式问卷与社交媒体，主题模型、情感词典与预训练语言模型并列使用。
• Network and graph perspectives show up in studies of decentralised autonomous organisations, influencer identification, supply chain hypernetworks and the spread of information between platforms.网络与图视角见于去中心化自治组织治理、意见领袖识别、供应链超网络以及信息跨平台扩散的研究。
• Data governance, ownership and quality are treated as analytic questions in their own right, with separate papers on accountability, preprocessing validation and root-cause analysis of process data.数据治理、权属与质量被当作独立的分析问题，责任归属、预处理校验与流程数据的根因分析各有专文。
• Privacy and fairness enter through format-preserving data release, measured privacy-utility trade-offs, model bias in phishing detection and perceived fairness of algorithm-supported managerial decisions.隐私与公平经格式保持的数据发布、隐私与效用权衡的度量、钓鱼检测中的模型偏差，以及算法辅助管理决策的公平感进入议题。
• Generative artificial intelligence and large language models have become routine subjects, running from consistency checks in classification tasks to the ethics of anthropomorphised agents placed at work.生成式人工智能与大语言模型已成常规题目，从分类任务的一致性检验，到拟人化智能体进入工作场所的伦理讨论。
• Operations and supply chain papers test forecast adjustment with causal machine learning, newsvendor behaviour under digital word of mouth and resilience in rail equipment manufacturing networks.运营与供应链论文检验因果机器学习下的预测调整、数字口碑环境中的报童决策，以及轨道交通装备制造网络的韧性。
• Marketing and customer research spans recommender systems, in-store journey analytics, topic modelling on luxury fashion and the effect of analytics capability on new product development.营销与客户研究涵盖推荐系统、店内旅程分析、奢侈时装的主题建模，以及分析能力对新产品开发的作用。
• Finance, risk and fraud form a further strand, with tax compliance prediction, refund fraud analytics, insurance loss ratio forecasting and audit work reshaped by AI and blockchain.金融、风险与反欺诈构成另一条线索，涉及纳税遵从预测、退款欺诈分析、保险赔付率预测，以及人工智能与区块链下的审计转型。
• People analytics and organisational studies examine turnover and attrition prediction, employer brand perception and the conditions under which human resource analytics is taken up.人力分析与组织研究考察离职与人员损耗预测、雇主品牌感知，以及人力资源分析被采纳的条件。
• Health analytics applies the same toolkit to electronic health records, opioid prescribing after orthopaedic surgery and disparities in records of violent death.健康分析把同一套工具用于电子健康档案、骨科手术后的阿片类处方，以及暴力死亡记录中的群体差异。

History

• Volume 1, number 1 appeared in 2018 as a new launch rather than a relaunch, since the title took a fresh ISSN block instead of continuing a predecessor's sequence of volumes.第 1 卷第 1 号于 2018 年面世，属于全新创办，刊物启用新的 ISSN 号段，未承接任何前身的卷次。
• That issue carried a nominal January 2018 date, while its papers went live online on 23 August 2018, an arrangement the publisher repeated through the early volumes.该期标注 2018 年 1 月，论文实际于 2018 年 8 月 23 日上线，出版社在早期各卷沿用这一安排。
• A one-page introduction by Sudha Ram and Dursun Delen opened the issue, followed by D. J. Power and colleagues asking what business analytics is, while the second issue of that volume carried Thomas Davenport's route from analytics to artificial intelligence.该期以（Sudha Ram）与（Dursun Delen）合写的一页导言开篇，随后是（D. J. Power）等人对商业分析定义的实证考察；同卷第 2 期另刊（Thomas Davenport）从分析走向人工智能的论述。
• Two issues a year, one dated January and one July, sufficed for the first five volumes, so the closing issue of volume 5 in 2022 was only the tenth on record.前五卷每年出两期，刊期分别落在 1 月与 7 月，到 2022 年第 5 卷收尾时累计只有十期。
• Volume 6 in 2023 was the first with four numbered issues, dated January, April, July and October, and the quarterly rhythm has held through volume 9 in 2026.2023 年第 6 卷首次编满四期，分别标注 1 月、4 月、7 月与 10 月，此后季度节奏延续到 2026 年第 9 卷。
• Each issue now holds four or five research items, and the 2025 Journal Citation Reports counted 26 citable articles for the year.如今每期收四到五篇研究文章，2025 年期刊引证报告统计的可引论文为 26 篇。
• Coverage in the Emerging Sources Citation Index brought a Journal Impact Factor of 1.7 in 2023, then 1.6 in 2024 and 1.9 in 2025.进入新兴来源引文索引后，2023 年影响因子为 1.7，2024 年为 1.6，2025 年回升至 1.9。
• The 2025 release ranks the title 178th of 266 in COMPUTER SCIENCE, INFORMATION SYSTEMS and 67th of 109 in OPERATIONS RESEARCH & MANAGEMENT SCIENCE, third quartile in both.2025 年榜单把该刊排在计算机信息系统类 266 种刊物的第 178 位与运筹管理科学类 109 种的第 67 位，两类均属第三分位。
• A five-year impact factor of 2.1 and a Journal Citation Indicator of 0.39 sit beside the current figure, with 272 citations in total and a cited half-life of 4.3 years.与当年数值并列的是 2.1 的五年影响因子与 0.39 的期刊引文指标，总被引 272 次，被引半衰期 4.3 年。
• Access follows a hybrid model, so subscription content and an open option coexist, and gold open access took 11.59 percent of the material counted in 2025.访问采用混合模式，订阅内容与开放获取选项并存，2025 年统计内容中金色开放获取占 11.59%。
• Corrections are published as free-standing items with their own identifiers, one in the first volume and another in volume 9, rather than folded quietly into the original papers.更正以独立条目发布并带有自己的标识符，第 1 卷与第 9 卷各有一条，原文不被悄然改写。
• The DOI stem 10.1080/2573234X has served every volume, a small marker of continuity across a run that changed its frequency but kept its publisher.全部卷次共用 10.1080/2573234X 这一 DOI 前缀，刊期改过而出版方未变，编号上的连续性由此可辨。

Editors

• Sudha Ram of the Eller College of Management at the University of Arizona is listed as a founding co-editor of the journal, a post she still holds.亚利桑那大学 Eller 管理学院的（Sudha Ram）被列为该刊创刊共同主编，这一职务延续至今。
• Dursun Delen, who holds the Spears and Patterson chairs in business analytics at Oklahoma State University, wrote the inaugural introduction with Ram and a companion review of research challenges in the same issue.俄克拉荷马州立大学的（Dursun Delen）持有该校商业分析讲席教授席位，与（Sudha Ram）合写创刊导言，并在同一期发表研究议题综述。
• Those two texts have worked as the journal's opening statement of intent, naming the questions the editors wanted the field to answer before regular papers began.这两篇文章构成刊物的开篇宣言，在常规论文之前先行列出编辑部希望领域回答的问题。
• Manuscripts reach the editorial office through the publisher's online submission system, and assessment draws on information systems and operations research reviewers, the two communities named by the journal's classification.稿件经出版社的在线投稿系统进入编辑部，审稿意见来自信息系统与运筹学两个群体，正是期刊引证报告为其设定的两个类目。
• Full research papers dominate each issue, with reviews appearing at a lower rate, among them a literature review on data science for innovation and a systematic review of AI-enabled decision-making in consumer goods.各期以完整研究论文为主，综述出现频率较低，其中有数据科学促进创新的文献综述，以及快速消费品行业人工智能决策的系统综述。
• Applied and case-based work sits beside formal modelling, from emergency gas leak management to growth hacking tools for small firms and a data mining process designed for financial services.应用与案例类研究与形式化建模并列，从燃气泄漏应急处置，到中小企业增长黑客工具，以及面向金融服务业的数据挖掘流程。
• A sports analytics strand recurs, with scouting report text used to project NBA performance, plus cricket match outcomes, home advantage in soccer and real-time point spreads in basketball.体育分析形成反复出现的线索，侦察报告文本用于预测球员进入 NBA 后的表现，另有板球赛果、足球主场优势与篮球实时让分的研究。
• Public sector and regulatory settings also appear, including big data adoption across the United Arab Emirates public sector and a supervised model for flagging non-compliant taxpayers in Tunisia.公共部门与监管场景同样进入版面，包括阿联酋的公共部门大数据采纳，以及突尼斯识别不遵从纳税人的监督学习模型。
• Both authors of that introduction came out of information systems departments, one in management information systems at Arizona and one in management science and information systems at Oklahoma State.创刊导言的两位作者都出自信息系统学科，一位在亚利桑那大学的管理信息系统系，另一位在俄克拉荷马州立大学的管理科学与信息系统系。
• Accepted papers receive a DOI and appear online before an issue is assembled, so a paper can be read and cited well ahead of its place in a printed volume.被录用的论文先取得 DOI 并在线上线，随后才编入具体期号，合订成卷并非发表的前提。