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Weitersagen:


Herausgeber: 
  • Vinod Sharma
  • Chandan Maheshkar
  • Jeanne Poulose
  • Analytics Enabled Decision Making 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Mai 2023  
    Genre:  Wirtschaft / Recht 
    ISBN:  9789811996573 
    EAN-Code: 
    9789811996573 
    Verlag:  Springer Nature Singapore 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 216 mm / B 153 mm / D 23 mm 
    Gewicht:  533 gr 
    Seiten:  324 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      



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