Data Analytics for Decision Making towards Business Excellence

Introduction

This edited volume collates discussions on latest challenges, opportunities, trends and practices applicable to two major business sectors -- retail and financial services -- and chapters are segregated accordingly. It explores how these sectors are increasingly becoming data-intensive, and how ways of handling, manipulating, exploiting and evaluating data continues to change in this era of big data.

Part A: Retail Analytics

Topics being explored are: inventory, assortment, and promotion effectiveness; pricing strategies; brand/category switching and customer loyalty; customer profitability; customer engagement; cross-buying and up-buying; synergistic effects of online and offline channels and retail innovations; effectiveness of different type of distribution channels; customer experience; service excellence/failure/recovery; digitalization in retailing; consumer behaviour and marketing in omni-channel retail environments.

Part B: Financial Data Analytics

Topics of relevance include financial aspects of data analytics such as: behavioral data finance; Big data and credit risk; data analytics and financial econometrics; financial sentiment and news analysis; information and evidence in digital age; policy-making mechanisms and modelling approaches; stock market manipulation detection; stock market trading strategies using data analytics; high frequency/algorithmic trading with AI; financial forecasting including interest rate/old price/crude oil/macro-economic variables/FOREX/cryptocurrency price; deep learning for finance and insurance applications.

Conclusion

The book covers diverse and advanced concepts with practical examples to supplement and complement varied topics of interest within the domain. Thus students, researchers, and practitioners will undoubtedly find novel and new ideas for data analytics in the realm of two critical domain areas: retail and financial services.