Data Analytics for Decision Making towards Business Excellence (eng)

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 of the book looks into better understanding of marketing metrics/ strategy/ theory and practice using 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; digitalizationin retailing; consumer behaviour and marketing in omni-channel retail environments. In Part B, 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/ macroeconomic variables/ FOREX/ cryptocurrency price; deep learning for finance and insurance applications. 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.

Bhaskar Basu is Professor of Information Systems at Xavier Institute of Management, XIM University, Bhubaneswar. He obtained his PhD from Indian Institute of Technology (IIT), Kharagpur, India, and is a University Gold Medallist from Jadavpur University, Kolkata, India. He also has a Post Graduate Diploma in Business Management (equivalent to MBA) from Indian Institute of Management (IIM), Calcutta. His research interests are in the areas of knowledge management, AI applications in business and sports management. His research work has been published in journals like VINE Journal of Information and Knowledge Management Systems, Journal of Modeling in Management, Journal of Innovation & Knowledge etc. He has also edited a book titled “Organizational Learning-Perspectives and Practices” (2006) and co-edited “Sports Management in an Uncertain Environment” (2023).

Jitendra Kumar Jha is Associate Professor in the Department of Industrial and Systems Engineering at IIT Kharagpur. He obtained his PhD from IIT Kanpur. He has received several scholarships and awards from DRPG IIT Kanpur, North American wing of BITSAA (alumni association of institutions of Birla Institute of Technology and Sciences), SJ Jindal Trust New Delhi, IIT Kharagpur. His main areas of teaching and research include operations research, statistical decision modeling, facility planning, supply chain and logistics planning, and inventory control. His publications have appeared in the reputed journals like Journal of the Operational Research Society, Journal of Manufacturing Systems, Applied Mathematical Modelling, Computers & Industrial Engineering, International Journal of Production Research, and other leading journals of Industrial Engineering. He is serving as an editorial board member of International Journal of Industrial Engineering: Theory, Applications and Practice.

Indrajit Mukherjee is Professor at Shailesh J. Mehta School of Management, IIT Bombay. He obtained his PhD from the Department of Industrial Engineering and Management, IIT Kharagpur. His Master's degree in Quality, Reliability & Operations Research is from Indian Statistical Institute (ISI), Kolkata, India. His research contributions have been published in the European Journal of Operational Research, Journal of Manufacturing Systems, Quality and Reliability Management, Quality Engineering, Computers & Industrial Engineering, to name some. His primary research interest is in multivariate quality control, quality management, applied operations research, and sourcing in the supply chain.

Raghu Nandan Sengupta is Professor, Department of Industrial & Management Engineering, IIT Kanpur. He obtained his PhD from IIM Calcutta and post doctoral fellowship from Princeton University, USA. His research interests are in areas of sequential estimation, statistical and mathematical reliability theory, risk analysis, optimization techniques in finance, meta heuristic techniques, reliability based optimization, robust optimization. His research work has been published in European Journal of Operational Research, Computational Statistics & Data Analysis, Communication in Statistics, Journal of Applied Statistics, Metrika, Statistics, Marketing Intelligence and Planning, Journal of Marketing Theory and Practice, Annals of Operations Research. He has also edited two books titled (i) Decision Sciences: Theory and Practice, (2016); and (ii) Studies in Quantitative Decision Making (2022), the latter being published by Springer.