{"product_id":"9789819575442","title":"Decision Sciences for Quality and Productivity Improvement Towards Operational and Business Excellence","description":"\u003ch1\u003eDecision Sciences for Quality and Productivity Improvement\u003c\/h1\u003e\u003ch2\u003eTowards Operational and Business Excellence\u003c\/h2\u003e\u003ch3\u003eIndrajit Mukherjee | Raghu Nandan Sengupta | Bhaskar Basu | Jitendra Kumar Jha\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eBusiness \u0026amp; Economics \/ Production \u0026amp; Operations Management\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\u003cp\u003eThis edited volume explores decision science theory-based approaches for enhancing the quality and productivity of products and processes, particularly in the fields of manufacturing, services, healthcare, banking, environment, agriculture, education, digital technology, and information technology. The decision science theories are drawn from various areas of management science, economics, operations research, statistical methods, machine learning, data mining, artificial intelligence, behavioural decision making and cognitive psychology. The book offers a unique platform to address various real-life problems and scenarios related to quality and productivity improvement, as well as operations excellence. The new concepts, varied solution methods, diverse research implications, industry case studies, comparative analysis of relevant approaches, in-depth literature review, and future research scopes discussed in the articles will certainly provide food for thought to researchers, decision-makers, and practitioners working in the domain of quality, productivity, and operations excellence. These theme-based book chapters demonstrate the immense potential of decision science theories to develop novel ideas that can support scientific decision-making, thereby improving the operations, quality, and productivity of any organisation.\u003c\/p\u003e\u003c\/div\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-IN\"\u003eIndrajit Mukherjee \u003c\/span\u003e\u003c\/strong\u003e\u003cspan lang=\"EN-IN\"\u003eis Professor at Shailesh J. Mehta School of Management, IIT Bombay. He did his Ph.D. from the Department of Industrial Engineering and Management, Indian Institute of Technology, Kharagpur. He did his Master's degree in Quality, Reliability \u0026amp; Operations Research from Indian Statistical Institute, Kolkata, India. He has authored and co-authored several research papers published in refereed and reputed journals. His research contributions are published in the\u003cem\u003e European Journal of Operational Research\u003c\/em\u003e, \u003cem style=\"mso-bidi-font-style: normal;\"\u003eAnnals of Operations Research,\u003c\/em\u003e \u003cem\u003eJournal of Manufacturing Systems\u003c\/em\u003e, \u003cem\u003eQuality and Reliability Management\u003c\/em\u003e, \u003cem\u003eQuality Engineering\u003c\/em\u003e, \u003cem\u003eComputers \u0026amp; Industrial Engineering\u003c\/em\u003e. His primary research interest is in multivariate quality control, quality management, applied operations research, and sourcing in the supply chain.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-IN\"\u003eRaghu Nandan Sengupta\u003c\/span\u003e\u003c\/strong\u003e\u003cspan lang=\"EN-IN\"\u003e is Professor, Department of Industrial \u0026amp; Management Engineering, Indian Institute of Technology Kanpur. He obtained his PhD from Indian Institute of Management Calcutta and PDF 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 \u003cem\u003eEJOR\u003c\/em\u003e, \u003cem\u003eQF\u003c\/em\u003e, \u003cem\u003eCSDA\u003c\/em\u003e, \u003cem\u003eCommunication in Statistics\u003c\/em\u003e, \u003cem\u003eJournal of Applied Statistics\u003c\/em\u003e, \u003cem\u003eMetrika\u003c\/em\u003e, \u003cem\u003eStatistics, Marketing Intelligence and Planning\u003c\/em\u003e, \u003cem\u003eJournal of Marketing Theory and Practice\u003c\/em\u003e, \u003cem\u003eAnnals of Operations Research\u003c\/em\u003e. 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.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-IN\"\u003eBhaskar Basu\u003c\/span\u003e\u003c\/strong\u003e\u003cspan lang=\"EN-IN\"\u003e is Professor of Information Systems at Xavier Institute of Management, XIM University, Bhubaneswar. He obtained his PhD from Indian Institute of Technology, Kharagpur (India) and is a University Gold Medallist (Jadavpur University, India). He also has a Post Graduate Diploma in Business Management (equivalent to MBA) from Indian Institute of Management, 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, \u003cem\u003eJournal of Modeling in Management\u003c\/em\u003e, IJITDM etc. He has also edited a book titled “Organizational Learning-Perspectives and Practices” (2006) and another one on sports management (co-edited) with Springer (2023).\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003e\u003cspan lang=\"EN-IN\"\u003eJitendra Kumar Jha \u003c\/span\u003e\u003c\/strong\u003e\u003cspan lang=\"EN-IN\"\u003eis working as a 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, BITSAA of NorthAmerica, 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. He has published\/presented more than sixty papers in international journals and conferences, and his publications have appeared in the reputed journals like \u003cem\u003eJournal of the Operational Research Society\u003c\/em\u003e, \u003cem\u003eJournal of Manufacturing Systems\u003c\/em\u003e, \u003cem\u003eApplied Mathematical Modelling\u003c\/em\u003e, \u003cem\u003eComputers \u0026amp; Industrial Engineering\u003c\/em\u003e, \u003cem\u003eInternational Journal of Production Research\u003c\/em\u003e, and other leading journals of Industrial Engineering. He is serving as an editorial board member of \u003cem\u003eInternational Journal of Industrial Engineering: Theory, Applications and Practice\u003c\/em\u003e.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e24 September 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Singapore\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9789819575442\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e282\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Singapore","offers":[{"title":"Default Title","offer_id":45938033950860,"sku":"9789819575442","price":179.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9789819575442.jpg?v=1781088177","url":"https:\/\/lateknightbooks.com\/products\/9789819575442","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}