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Analytics enabled decision making

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analytics enabled decision making/ edited by Vinod Sharma, Chandan Maheshkar, Jeanne Poulose.
其他作者:	Sharma, Vinod.
出版者:	Singapore :Springer Nature Singapore : : 2023.,
面頁冊數:	1 online resource (xxxiii, 288 p.) :ill. (some col.), digital ;24 cm.
內容註:	Chapter 1 Next generation smart manufacturing and service systems using big data analytics -- Chapter 2 Elements of decision making under uncertainty -- Chapter 3 Data, Inference, and Marketing Decisions -- Chapter 4 Competitor and competition Analysis through analytics -- Chapter 5 Influence of big data analytics on business intelligence -- Chapter 6 Improved price alignment to perceived value of product/service using data analytics -- Chapter 7 Changing the landscape of retailing using pricing analytics -- Chapter 8 Enhancing efficiency and effectiveness in supply chain management through Business Intelligence -- Chapter 9 Quantifying thoughts and feelings about a company from big data to improve brand strength -- Chapter 10 Enabling achievement of organisational/corporate goals through HR analytics -- Chapter 11 Workforce Analytics facilitates Human Resource Demand Forecasting -- Chapter 12 Ascertainment of Employee Competencies and measurement with greater precision using T&D Analytics -- Chapter 13 Analytics to Measure Employees' Behavioural Traits and predict employee performance -- Chapter 14 Using predictive analytics alongside psychometric assessments and other measures to identify the candidates with the right performance and behavioural criteria -- Chapter 15 Designing competitive yet cost effective compensation packages using analytics to reduce attrition -- Chapter 16 Mitigating Compliance Failure Risk using Analytics (gender equal pay, overtime payments, appropriate number of each category of employees) -- Chapter 17 Predictive analytics to aid employee alignment with the culture of the organisation -- Chapter 18 Analysing the impact of Employees' Satisfaction and Frustration on their and organizations' performance -- Chapter 19 Assessing and Controlling Political Behaviour of Groups in Organizations -- Chapter 20 Measuring Organizational/Industrial Citizenship Behaviour -- Chapter 21 Psychological Framework and Methodology for Analysing Decision Risk -- Chapter 22 Analysing Challenging Behaviours of Two Individuals with Intellectual Differences/Disability -- Chapter 23 Measuring the effectiveness of data analytics in higher education to improve student outcomes -- Chapter 24 Building an industry 4.0 analytics platform with a proven example and proof of concept -- Chapter 25 Gaining competitive advantage through business analytics.
Contained By:	Springer Nature eBook
標題:	Decision making - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-19-9658-0
ISBN:	9789811996580

Analytics enabled decision making
Analytics enabled decision making[electronic resource] /edited by Vinod Sharma, Chandan Maheshkar, Jeanne Poulose. - Singapore :Springer Nature Singapore :2023. - 1 online resource (xxxiii, 288 p.) :ill. (some col.), digital ;24 cm.

Chapter 1 Next generation smart manufacturing and service systems using big data analytics -- Chapter 2 Elements of decision making under uncertainty -- Chapter 3 Data, Inference, and Marketing Decisions -- Chapter 4 Competitor and competition Analysis through analytics -- Chapter 5 Influence of big data analytics on business intelligence -- Chapter 6 Improved price alignment to perceived value of product/service using data analytics -- Chapter 7 Changing the landscape of retailing using pricing analytics -- Chapter 8 Enhancing efficiency and effectiveness in supply chain management through Business Intelligence -- Chapter 9 Quantifying thoughts and feelings about a company from big data to improve brand strength -- Chapter 10 Enabling achievement of organisational/corporate goals through HR analytics -- Chapter 11 Workforce Analytics facilitates Human Resource Demand Forecasting -- Chapter 12 Ascertainment of Employee Competencies and measurement with greater precision using T&D Analytics -- Chapter 13 Analytics to Measure Employees' Behavioural Traits and predict employee performance -- Chapter 14 Using predictive analytics alongside psychometric assessments and other measures to identify the candidates with the right performance and behavioural criteria -- Chapter 15 Designing competitive yet cost effective compensation packages using analytics to reduce attrition -- Chapter 16 Mitigating Compliance Failure Risk using Analytics (gender equal pay, overtime payments, appropriate number of each category of employees) -- Chapter 17 Predictive analytics to aid employee alignment with the culture of the organisation -- Chapter 18 Analysing the impact of Employees' Satisfaction and Frustration on their and organizations' performance -- Chapter 19 Assessing and Controlling Political Behaviour of Groups in Organizations -- Chapter 20 Measuring Organizational/Industrial Citizenship Behaviour -- Chapter 21 Psychological Framework and Methodology for Analysing Decision Risk -- Chapter 22 Analysing Challenging Behaviours of Two Individuals with Intellectual Differences/Disability -- Chapter 23 Measuring the effectiveness of data analytics in higher education to improve student outcomes -- Chapter 24 Building an industry 4.0 analytics platform with a proven example and proof of concept -- Chapter 25 Gaining competitive advantage through business analytics.

Analytics is changing the landscape of businesses across sectors globally. This has led to the stimulation of interest of scholars and practitioners worldwide in this domain. The emergence of 'big data', has fanned the usages of machine learning techniques and the acceptance of 'Analytics Enabled Decision Making'. This book provides a holistic theoretical perspective combined with the application of such theories by drawing on the experiences of industry professionals and academicians from around the world. The book discusses several paradigms including pattern mining, clustering, classification, and data analysis to name a few. The main objective of this book is to offer insight into the process of decision-making that is accelerated and made more precise with the help of analytics. Dr Vinod Sharma is an Associate Professor with Symbiosis Centre for Management and Human Resource Development, Symbiosis International University, Pune. He has over 22 years of experience including both academia and industry, at different levels of management, preparing him to be an effective researcher and instructor. He specialized in Marketing Strategy, Marketing Research & Analytics, and Consumer Behaviour. He has authored over 65 papers in national and international journals and he has also been involved in many consultation research projects, conducted various research workshops, and conducted training programs in association with MSME and FIEO on various subjects of management. Dr Chandan Maheshkar is a Senior Consultant, East Nimar Society for Education India. He has served several management institutes in Central India including the University of Indore, India, in various academic roles. He obtained his MBA and PhD from DAVV, Indore. In 2014, the University of Indore awarded him a Golden Jubilee Research Scholarship on the occasion of completion of its successful 50 years. Business education, HRD, cross-culture business, and organizational behavior are his core areas of research interests. Dr Jeanne Poulose is an Associate Professor with School of Business and Management, CHRIST (Deemed to be University), Delhi NCR, India. She obtained a PhD and MPhil in Management and an MBA with a specialization in Finance and Human Resources. She has around 22 years of Industry-Academia experience in the retail, banking, and educational sectors through leadership and teaching roles in organizations like ICICI Bank, GlobalNxt University, St. Joseph's Degree & PG College, etc. She teaches HR Analytics, Agile HR, Organizational Behaviour, and Workforce Planning and Employee Selection.

ISBN: 9789811996580

Standard No.: 10.1007/978-981-19-9658-0doiSubjects--Topical Terms:

752376
Decision making
--Data processing.

LC Class. No.: HD30.23

Dewey Class. No.: 658.4030285

Analytics enabled decision making
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