Journal of Business Analytics最新文献_第3页

From star rating to sentiment rating: using textual content of online reviews to develop more effective reputation systems for peer-to-peer accommodation platforms 从星级评价到情感评价:利用在线评论的文本内容，为点对点住宿平台开发更有效的信誉系统

Journal of Business Analytics Pub Date : 2022-09-13 DOI: 10.1080/2573234X.2022.2122880

H. Zolbanin, Donald Wynn

{"title":"From star rating to sentiment rating: using textual content of online reviews to develop more effective reputation systems for peer-to-peer accommodation platforms","authors":"H. Zolbanin, Donald Wynn","doi":"10.1080/2573234X.2022.2122880","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2122880","url":null,"abstract":"ABSTRACT Star ratings on P2P accommodation platforms are highly positive. Such biases have led many users to utilise selective processing strategies to evaluate the textual content of online reviews. However, when many reviews are available for a product or a service, these strategies would be suboptimal at best, posing several challenges to the users of peer-to-peer (P2P) accommodation platforms. To enable the guests to perform more informed evaluations and overcome the challenges that the skewed distribution of star ratings creates for decision-making, we employ content analysis tools to derive an aggregated sentiment score for each listing. Using this score, we define a new measure, called “sentiment rating”, that compares a listing with other similar listings based on their textual reviews. Our choice-based conjoint experiment suggests that unlike users’ initial perception about the function of star rating as the most salient factor in evaluating P2P listings, users actually attribute more importance to sentiment ratings of P2P accommodations. Therefore, a text-based summary of online reviews would indeed help users in evaluating alternatives on a P2P platform and in decision making. We argue that a text-based quantitative summary of user reviews could be a useful supplements to (or substitutes for) star ratings on P2P accommodation platforms and even online retailing websites.","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91264882","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

Analysis of employee perception of employer brand: a comparative study across business cycles using structural topic modelling 员工对雇主品牌的认知分析:使用结构主题模型的跨商业周期比较研究

Journal of Business Analytics Pub Date : 2022-08-02 DOI: 10.1080/2573234X.2022.2104663

G. Karkhanis, Suresh Udhavdas Chandnani, Swapnajit Chakraborti

{"title":"Analysis of employee perception of employer brand: a comparative study across business cycles using structural topic modelling","authors":"G. Karkhanis, Suresh Udhavdas Chandnani, Swapnajit Chakraborti","doi":"10.1080/2573234X.2022.2104663","DOIUrl":"https://doi.org/10.1080/2573234X.2022.2104663","url":null,"abstract":"ABSTRACT Employer branding is an important measure to attract prospective employees and to motivate, engage, and retain their current employees. Employer branding is instrumental for the employer to position the organisation in the minds of current and potential employees by using a combination of economic, psychological, and functional benefits. In the current research the authors implement a set of natural language processing techniques (structural topic modelling) on the employee reviews posted on Glassdoor.com (an online platform where the employees can post reviews about their current and previous employers). The study has thematically structured the 35,075 reviews from 8 Information Technology companies, spanning 5 years from 2015 to 2019. The study compares the employer branding parameters and has identified the prominent dimensions across the expansionary (2015–2017) and contractionary (2017–2019) phases of business cycles. A significant difference in topical proportions were found across the business cycles, suggesting different priorities for different dimensions of the employer brand during expansionary and contractionary phases. The findings would serve as guidance for HR managers to understand the trends in the employee perceptions in the context of changing macro-environment situations and accordingly recalibrate their existing strategies for talent attraction and retention","PeriodicalId":36417,"journal":{"name":"Journal of Business Analytics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84371052","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

Algorithmic enhancements to identify predictable components from users’ data and a framework to detect misinformation in social media 增强算法，从用户数据中识别可预测的组件，并建立框架，检测社交媒体中的错误信息

Journal of Business Analytics Pub Date : 2022-07-18 DOI: 10.1080/2573234X.2022.2100834

G. Dixit, A. Kushwaha

引用次数: 0

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

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

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

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

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":null,"pages":null},"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

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":null,"pages":null},"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