Business Intelligence and Analytics: From Big Data to Big Impact

By Hsinchun Chen, Roger H. L. Chiang, Veda C. Storey. MIS Q., 2012

6,028 citations recorded by the source corpus.

Subfields: Information Systems, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f117c6f12d067bd66dad40996b3931c069daa2da

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In Information Systems

In Management Information Systems

In Management Science and Operations Research

Citations in the corpus

Deep learning in business analytics and operations research: Models, applications and managerial implications (2018, neutral): “Business analytics refers to the art and science of converting (big) data into business insights for faster and more accurate managerial decision-making ( Baesens et al., 2016; Chen et al., 2012 ).”
Internet of Things (IoT) and the Energy Sector (2020, methodology): “Advanced computing and analytic methods are needed to manage the Big data [102,103].”
How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management (2015, positive): “In addition to innovative data processing and analytical technologies, BDA also embraces business-centric practices and methodologies that can be applied to various high-impact applications such as e-commerce, market intelligence, e-government, health care, and security [13].”
Understanding the Factors Affecting the Organizational Adoption of Big Data (2018, background): “Chen, Chiang, and Storey [7] listed the top journals, conferences, and industry magazines that cover topics relevant to BI&A.”
The impact of big data on world-class sustainable manufacturing (2015, background): “The majority of studies so far have endeavored to understand the different dimensions of the concept and to capture the potential benefits to OM/SCM [3, 7].”
Big data analytics in supply chain management between 2010 and 2016: Insights to industries (2018, methodology): “To this end, a business intelligence and analytics tool proposed the use of big data to assist Chief Financial Officer (CFO) to improved data accuracy, provide greater value and make better decisions (Chen et al., 2012).”
The impact of big data analytics on firms’ high value business performance (2016, background): “Business intelligence and analytics and the related field of big data analytics (BDA) have become increasingly important in both the academic and the business communities over the past years (Chen et al. 2012).”
Big Data and supply chain management: a review and bibliometric analysis (2016, background): “Researchers (Chen et al. 2012; Wamba et al. 2015; Dubey et al. 2016; Wang et al. 2016; Song et al. 2016) have endeavoured to explore different dimensions of Big Data and capture the potential benefits to supply chain management (SCM).”
Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation (2018, background): “New application domains of machine learning—such as personalized medicine (Collins and Varmus, 2015), business intelligence (Chen et al., 2012), and smart urbanism (Kitchin, 2014)—emerged, which come with vast amounts of data.”
Algorithmic bias: review, synthesis, and future research directions (2021, background): “Firms are increasingly adopting data analytics, big data technologies, and artificial intelligence (AI) to transform and improve their key operations and organisational decision making (Chen et al., 2012; Mikalef et al., 2018).”
Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities (2020, background): “Firms that invest in developing their BDACs are shown to be better positioned in identifying inefficiencies in their internal and external operations [83].”
Creating Strategic Business Value from Big Data Analytics: A Research Framework (2018, background): “Today’s BDA has evolved from the early era of business intelligence 1.0 characterized by structured content, OLAP, dashboards, data mining, and statistical analysis, to 2.0 characterized by unstructured online content, opinion mining, web analytics and intelligence, social media analytics, and socia”