Journal of Business Analytics最新文献

Exploring the relationship between YouTube video optimisation practices and video rankings for online marketing: a machine learning approach 探索 YouTube 视频优化实践与网络营销视频排名之间的关系：一种机器学习方法

Journal of Business Analytics Pub Date : 2023-12-12 DOI: 10.1080/2573234x.2023.2292536

Marina E. Johnson, Ross A. Malaga

引用次数: 0

The era of business analytics: identifying and ranking the differences between business intelligence and data science from practitioners’ perspective using the Delphi method 商业分析时代：用德尔菲法从从业人员的角度识别商业智能和数据科学之间的差异并对其进行排序

Journal of Business Analytics Pub Date : 2023-11-21 DOI: 10.1080/2573234x.2023.2285483

M. Al-Debei

引用次数: 0

Intelligent decision support system using nested ensemble approach for customer churn in the hotel industry 基于嵌套集成方法的酒店行业客户流失智能决策支持系统

Journal of Business Analytics Pub Date : 2023-11-10 DOI: 10.1080/2573234x.2023.2281317

Leila Taherkhani, Amir Daneshvar, Hossein Amoozad Khalili, Mohammad Reza Sanaei

{"title":"Intelligent decision support system using nested ensemble approach for customer churn in the hotel industry","authors":"Leila Taherkhani, Amir Daneshvar, Hossein Amoozad Khalili, Mohammad Reza Sanaei","doi":"10.1080/2573234x.2023.2281317","DOIUrl":"https://doi.org/10.1080/2573234x.2023.2281317","url":null,"abstract":"ABSTRACTSince customer retention costs much less than attracting new customer, the problem of customer churn is a major challenge in various fields of work and particularly Hotel Industry. In this research, a solution based on an intelligent decision support system using text mining and nested ensemble techniques is presented, which combines the advantages of stacking and voting methods. In the proposed system, after the text mining of the data collected from the hotels of Kish Island, the effective feature selection is done using the gravity search algorithm. In the first level of nested ensemble technique method, stacking deep learning methods are used. Voting is used in the MetaClassifier section, which includes Random Forest, Xgboost and Naïve Bayes methods. The results of the implementation and comparison of the proposed system, show that the performance of the proposed system has increased the accuracy by 0.04 compared to the best existing method.KEYWORDS: Customer churndecision support systemnested ensembleensemble learning Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":" 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135141888","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

Introducing technological disruption: how breaking media attention on corporate events impacts online sentiment 引入技术颠覆:媒体对企业事件的突发关注如何影响网络情绪

Journal of Business Analytics Pub Date : 2023-10-31 DOI: 10.1080/2573234x.2023.2274088

Dane Vanderkooi, Atefeh Mashatan, Ozgur Turetken

{"title":"Introducing technological disruption: how breaking media attention on corporate events impacts online sentiment","authors":"Dane Vanderkooi, Atefeh Mashatan, Ozgur Turetken","doi":"10.1080/2573234x.2023.2274088","DOIUrl":"https://doi.org/10.1080/2573234x.2023.2274088","url":null,"abstract":"One modern strategy to anticipate consumer reaction to new products and services involves looking towards social media sites to explore consumer opinions. A rich body of literature on social media marketing suggests that an effective way to leverage social media platforms is the empirical analysis of electronic word-of-mouth (eWOM), particularly through sentiment analysis (SA). We propose a novel method for innovators to leverage social media by exploring how breaking media attention on notable corporate events impacts the general public sentiment surrounding a pre-introduced, potentially disruptive innovation (PPDI). Twitter conversations surrounding Facebook’s pre-introduced payment system called Libra, a permissioned blockchain-based cryptocurrency, were analysed as a case study. The analysis suggests that breaking media attention leads to a significant change in sentiment polarity. An event with a preannouncement leads to an emotional momentum effect whereby sentiment polarity accumulates across an anticipation period. Implications for how managers may leverage these insights are discussed.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"75 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135809508","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

An adaptive and enhanced framework for daily stock market prediction using feature selection and ensemble learning algorithms 使用特征选择和集成学习算法的自适应和增强的每日股票市场预测框架

Journal of Business Analytics Pub Date : 2023-10-05 DOI: 10.1080/2573234x.2023.2263522

Mahmut Sami Sivri, Alp Ustundag

{"title":"An adaptive and enhanced framework for daily stock market prediction using feature selection and ensemble learning algorithms","authors":"Mahmut Sami Sivri, Alp Ustundag","doi":"10.1080/2573234x.2023.2263522","DOIUrl":"https://doi.org/10.1080/2573234x.2023.2263522","url":null,"abstract":"ABSTRACTEven a slight increase in accuracy when predicting the direction of stock movements can have a significant impact on the rate of returns. However, determining the most suitable variables, methods, and parameters to predict price changes is extremely challenging due to the multitude of variables influencing these changes. This paper presents an innovative prediction framework that combines ensemble learning and feature selection algorithms to effectively capture daily stock movements. The study focuses on predicting the change between the opening and closing prices of the subsequent day and employs a daily sliding window cross-validation methodology. The framework comprises fourteen variable groups encompassing a range of financial and operational indicators. Experimental findings indicate that a competitive performance was achieved for stocks within the Borsa Istanbul 30 index. Light Gradient Boosting Machines and Shapley Additive Explanations emerges as the optimal model combination and exhibits superior performance compared to a buy-and-hold strategy.KEYWORDS: Stock market predictionfeature selectionensemble learningmachine learningforecastingemerging markets Disclosure statementNo potential conflict of interest was reported by the author(s).Author contributionMahmut Sami Sivri constructed the idea for research, planned the methodology to reach the conclusion, took responsibility in execution of the experiments, data management and reporting, logical interpretation, presentation of the results, literature review and construction of the whole of the manuscript.Alp Ustundag organised and supervised the course of the project and taking the responsibility, reviewed the article before submission and provided personnel, environmental and financial support and tools and instruments that are vital for the project.Additional informationFundingThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135483292","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

When and how to adjust statistical forecasts in supply chains? Insight from causal machine learning 何时以及如何调整供应链中的统计预测?因果机器学习的洞察力

Journal of Business Analytics Pub Date : 2023-08-17 DOI: 10.1080/2573234x.2023.2248203

B. Wibowo

引用次数: 0

A Shapley-value Index for Market Basket Analysis: Weighting Shapley’s Value 市场篮子分析的沙普利价值指数:沙普利价值加权

Journal of Business Analytics Pub Date : 2023-07-23 DOI: 10.1080/2573234x.2023.2239877

Harrison Bohl, Jasmine Craig, E. Shellshear

引用次数: 1

Role of External Factors in Adoption of HR Analytics: Does Statistical Background, Gender and Age Matters? 外部因素在采用人力资源分析中的作用:统计背景、性别和年龄重要吗?

Journal of Business Analytics Pub Date : 2023-07-04 DOI: 10.1080/2573234x.2023.2231966

Ghulam Muhammad, Muddassir Siddiqui, Rizwana Rasheed, Heena Shabbir, Rabia Falak Sher

引用次数: 0

An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective 可持续和弹性案例研究的交互式分析方法:机器学习视角

Journal of Business Analytics Pub Date : 2023-04-26 DOI: 10.1080/2573234X.2023.2202691

S. M. Mousavi, Kiarash Sadeghi R., L. Lee

{"title":"An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective","authors":"S. M. Mousavi, Kiarash Sadeghi R., L. Lee","doi":"10.1080/2573234X.2023.2202691","DOIUrl":"https://doi.org/10.1080/2573234X.2023.2202691","url":null,"abstract":"ABSTRACT Sustainable development is a problem-solving method that simultaneously accounts for the economic, environmental, and social impacts of actions. Decision-makers have recently recognised the need for sustainable development. Multiobjective optimisation is the most reliable technique to solve multiple sustainable development goals. However, there needs to be more research examining the role of interactive methods in multiobjective optimisation problems. To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. To show the method’s applicability, this paper uses the proposed algorithm in three sustainable and resilient case studies. The selected cases are the river pollution problem, the urban transit network design problem, and the resilience problem. Moreover, the proposed algorithm is compared with two other algorithms for validation purposes. The results reveal that the proposed algorithm outperforms non-interactive algorithms by providing superior solutions.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":"5 1","pages":"276 - 293"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74491683","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

Data analytics management capability and strategies for interorganisational collaborations: a survey research 组织间合作的数据分析管理能力与策略:一项调查研究

Journal of Business Analytics Pub Date : 2023-04-23 DOI: 10.1080/2573234X.2023.2204159

Mohammad Daneshvar Kakhki, Utkarsh Shrivastava

引用次数: 0