Business Analytics (BA) is an evolving phenomenon that showcases the increasing importance of using huge volumes of data to generate value for businesses. Advances in BA have offered great opportunities for organisations to improve, innovate, and develop existing or new processes, products, and services. BA is the process of transforming data into actionable insight by using statistical and mathematical analysis, descriptive, prescriptive, and predictive models, machine learning, information systems and network science methods, among others, along with a variety of data, expert knowledge, and fact-based management to support better and faster decision-making.

BA and Business Intelligence (BI) generate capabilities for companies to compete in the market effectively and has become one of the main functional areas in most companies. BA tools are used in diverse ways, for example, to identify consumer behaviour patterns and market trends, to derive valuable insights on the performance of stocks, to find information on the attrition rate of employees, to analyse and solve healthcare problems, to offer insight into inventory management and supply chain management, to analyse data from social networks, and to infer traffic behaviour and develop traffic management policy, among others.

BA and BI have become one of the most popular research areas in academic circles, as well as in the industry, driven by the increasing demand in the business world. This book aims to become a stimulus for innovative business solutions covering a wide range of aspects of business analytics, such as management science, information technology, descriptive, prescriptive, and predictive models, machine learning, network science, mathematical and statistical techniques. The book will encompass a valuable collection of chapters exploring and discussing computational frameworks, practices, and applications of BA that can assist industries and relevant stakeholders in decision-making and problem-solving exercises, with a view to driving competitive advantage.


section Section I|85 pages

Operations and Supply Chain Analytics

chapter Chapter 2|13 pages

AI and ML in Supply Chain Decision Making A Pragmatic Discussion

ByArvind Shroff

chapter Chapter 4|15 pages

Role of Artificial Intelligence in Supply Chain Management

ByPratibha Garg, Neha Gupta, Mohini Agarwal

chapter Chapter 5|9 pages

Impact of Blockchain in Creating a Sustainable Supply Chain

ByPiyusha Nayyar, Pratibha Garg

chapter Chapter 6|15 pages

Exploring Adoption of Blockchain Technology for Sustainable Supply Chain Management

BySalaj, Subhrata Das, Mohini Agarwal

section Section II|63 pages

Data Mining, Computational Framework, and Practices

chapter Chapter 7|32 pages

Mathematical Model of Consensus and its Adaptation to Achievement Consensus in Social Groups

ByIosif Z. Aronov, Olga V. Maksimova

chapter Chapter 8|14 pages

Data to Data Science A Phenomenal Journey

ByMohammad Haider Syed, Sidhu, Kamal Upreti

section Section III|108 pages

Business Intelligence and Analytics Applications

chapter Chapter 10|17 pages

HR ANALYTICS Galvanizing the Organizations with the Prowess of Technology

ByRuchi Jain, Ruchi Khandelwal

chapter Chapter 11|17 pages

Marketing Analytics Concept, Applications, Opportunities, and Challenges Ahead

ByManita Matharu

chapter Chapter 12|16 pages

Effect of Social Media Usage on Anxiety During a Pandemic An Analytical Study on Young Adults

ByAmit Dangi, Vijay Singh, Neha Gupta

chapter Chapter 13|15 pages

An Exploratory Study of Understanding Consumer Buying Behaviour Towards Green Cosmetics Products in the Indian Market

ByMd Sohail, Richa Srivastava, Srikant Guptal

chapter Chapter 14|19 pages

Analytical Study of Factors Affecting the Adoption of Blockchain by Fintech Companies

ByPooja Mathur, Sony Thakural