Big data and business analytics: A research agenda for realizing business value

2020 ◽  
Vol 57 (1) ◽  
pp. 103237 ◽  
Author(s):  
Patrick Mikalef ◽  
Ilias O. Pappas ◽  
John Krogstie ◽  
Paul A. Pavlou
Keyword(s):  
Big Data ◽  
Research Agenda ◽  
Business Value ◽  
Business Analytics

scholarly journals Business value of big data analytics: A systems-theoretic approach and empirical test

2020 ◽  
Vol 57 (1) ◽  
pp. 103124 ◽  
Author(s):  
John Qi Dong ◽  
Chia-Han Yang
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Empirical Test ◽  
Big Data Analytics ◽  
Business Value ◽  
Theoretic Approach

A Big Data Conceptual Model to Improve Quality of Business Analytics

2020 ◽  
pp. 20-37
Author(s):  
Grace Park ◽  
Lawrence Chung ◽  
Haan Johng ◽  
Vijayan Sugumaran ◽  
Sooyong Park ◽  
...  
Keyword(s):  
Big Data ◽  
Conceptual Model ◽  
Improve Quality ◽  
Business Analytics

scholarly journals BIG DATA BUSINESS ANALYTICS AS A STRATEGIC ASSET FOR HEALTH CARE INDUSTRY

2019 ◽  
Vol 01 (02) ◽  
pp. 12-20 ◽  
Author(s):  
Smys S ◽  
Vijesh joe C
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Industry ◽  
Customer Relationship ◽  
Business Strategies ◽  
Business Analytics ◽  
Care Industry ◽  
Strategic Assets

The big data includes the enormous flow of data from variety of applications that does not fit into the traditional data base. They deal with the storing, managing and manipulating of the data acquired from various sources at an alarming rate to gather valuable insights from it. The big data analytics is used provide with the new and better ideas that pave way to the improvising of the business strategies with its broader, deeper insights and frictionless actions that leads to an accurate and reliable systems. The paper proposes the big data analytics for the improving the strategic assets in the health care industry by providing with the better services for the patients, gaining the satisfaction of the patients and enhancing the customer relationship.

Architecture of modern platforms for big data analytics

2021 ◽  
pp. 67-74
Author(s):  
Liudmyla Zubyk ◽  
Yaroslav Zubyk
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Business Processes ◽  
Service Providers ◽  
Big Data Analytics ◽  
Business Value ◽  
Third Party ◽  
Unstructured Data ◽  
Business Decision ◽  
World Industry

Big data is one of modern tools that have impacted the world industry a lot of. It also plays an important role in determining the ways in which businesses and organizations formulate their strategies and policies. However, very limited academic researches has been conducted into forecasting based on big data due to the difficulties in capturing, collecting, handling, and modeling of unstructured data, which is normally characterized by it’s confidential. We define big data in the context of ecosystem for future forecasting in business decision-making. It can be difficult for a single organization to possess all of the necessary capabilities to derive strategic business value from their findings. That’s why different organizations will build, and operate their own analytics ecosystems or tap into existing ones. An analytics ecosystem comprising a symbiosis of data, applications, platforms, talent, partnerships, and third-party service providers lets organizations be more agile and adapt to changing demands. Organizations participating in analytics ecosystems can examine, learn from, and influence not only their own business processes, but those of their partners. Architectures of popular platforms for forecasting based on big data are presented in this issue.

A structured literature review on Big Data for customer relationship management (CRM): toward a future agenda in international marketing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pasquale Del Vecchio ◽  
Gioconda Mele ◽  
Evangelia Siachou ◽  
Gloria Schito
Keyword(s):  
Big Data ◽  
Customer Relationship Management ◽  
Research Agenda ◽  
International Marketing ◽  
Relationship Management ◽  
Customer Relationship ◽  
Future Research ◽  
Content Type ◽  
Future Research Agenda ◽  
Structured Literature Review

PurposeThis paper aims to advance the international marketing debate by presenting the results of a structured literature review (SLR) focusing on Big Data implementation in customer relationship management (CRM) strategizing. It outlines past and present literature and frames a future research agenda.Design/methodology/approachThe research analyzes papers published in journals from 2013 to 2020, deriving significant insights about Big Data applications in CRM. A sample of 48 articles indexed at Scopus was preliminarily submitted for bibliometric analysis. Finally, 46 papers were analyzed with content and a bibliometric analysis to identify areas of thematic specializations.FindingsThe paper presents a conceptual multilevel framework demonstrating areas of specialization emerging from the literature. The framework is built around four coordinated sequences of actions relevant to “why,” “what,” “who” and “how” Big Data is implemented in CRM strategies, thus supporting the conception and implementation of an internationalization marketing strategy.Research limitations/implicationsImplications for the development of the future research agenda on international marketing arise from the comprehension of Big Data in CRM strategy.Originality/valueThe paper provides a comprehensive SLR of the articles dealing with models and processes of Big Data for CRM from an international marketing perspective. Despite these issues' relevance and the increasing literature focused on them, research in this area is still fragmented and underexplored, requiring more systematic and holistic studies.

THE RELATIONSHIP OF SOCIOTECHNICAL AND TECHNOLOGICAL ASPECTS OF THE INTRODUCTION AND APPLICATION OF BUSINESS INTELLIGENCE SYSTEMS

2021 ◽  
Vol 5 (12) ◽  
pp. 30-35
Author(s):  
Edward N. Ozhiganov ◽  
◽  
Alexander A. Chursin ◽  
Alexey D. Linkov ◽  
◽  
...  
Keyword(s):  
Big Data ◽  
Business Intelligence ◽  
New Technologies ◽  
Business Analytics ◽  
Scientific Publications ◽  
Business Decisions ◽  
Business Decision ◽  
Business Intelligence Systems ◽  
Demand Fluctuations ◽  
New Research

This article describes a relation between sociotechnical and technological factors involved in launching and implementing Business Intelligence systems. Advanced BI systems include business analytics, data mining, data visualization, data tools and infrastructure, and advanced IT solutions to support business decisions based on big data. Various industries and businesses handle large amounts of data to adapt to changing markets and demand fluctuations, push new technologies, and repair ineffective strategies, etc. With an upsurge in data sizes, more and more new research papers are published today to describe BI implemen-tation, use and results. However, today most studies and scientific publications focus on Business Intelligence technological challenges, while sociotechnical aspects – that is processes involved in business decision mak-ing based on big data – are studied in much rarer cases.

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