Cover image for Sharing Economy and Big Data Analytics

Sharing Economy and Big Data Analytics

Author Soraya Sedkaoui , Mounia Khelfaoui
Release Date: 2020/02/01
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Book Description

The different facets of the sharing economy offer numerous opportunities for businesses ? particularly those that can be distinguished by their creative ideas and their ability to easily connect buyers and senders of goods and services via digital platforms. At the beginning of the growth of this economy, the advanced digital technologies generated billions of bytes of data that constitute what we call Big Data.

This book underlines the facilitating role of Big Data analytics, explaining why and how data analysis algorithms can be integrated operationally, in order to extract value and to improve the practices of the sharing economy. It examines the reasons why these new techniques are necessary for businesses of this economy and proposes a series of useful applications that illustrate the use of data in the sharing ecosystem.

Table of Contents

  1. Cover
  2. Preface
  3. Introduction
    1. I.1. Why this book?
    2. I.2. The scope of this book
    3. I.3. The challenge of this book
    4. I.4. How to read this book
  4. PART 1: The Sharing Economy or the Emergence of a New Business Model
    1. 1 The Sharing Economy: A Concept Under Construction
      1. 1.1. Introduction
      2. 1.2. From simple sharing to the sharing economy
      3. 1.3. The foundations of the sharing economy
      4. 1.4. Conclusion
    2. 2 An Opportunity for the Business World
      1. 2.1. Introduction
      2. 2.2. Prosumption: a new sharing economy trend for the consumer
      3. 2.3. Poverty: a target in the spotlight of the shared economy
      4. 2.4. Controversies on economic opportunities of the sharing economy
      5. 2.5. Conclusion
    3. 3 Risks and Issues of the Sharing Economy
      1. 3.1. Introduction
      2. 3.2. Uberization: a white grain or just a summer breeze?
      3. 3.3. The sharing economy: a disruptive model
      4. 3.4. Major issues of the sharing economy
      5. 3.5. Conclusion
    4. 4 Digital Platforms and the Sharing Mechanism
      1. 4.1. Introduction
      2. 4.2. Digital platforms: “What growth!”
      3. 4.3. Digital platforms or technology at the service of the economy
      4. 4.4. From the sharing economy to the sharing platform economy
      5. 4.5. Conclusion
  5. PART 2: Big Data Analytics at the Service of the Sharing Economy
    1. 5 Beyond the Word “Big”: The Changes
      1. 5.1. Introduction
      2. 5.2. The 3 Vs and much more: volume, variety, velocity
      3. 5.3. The growth of computing and storage capacities
      4. 5.4. Business context change in the era of Big Data
      5. 5.5. Conclusion
    2. 6 The Art of Analytics
      1. 6.1. Introduction
      2. 6.2. From simple analysis to Big Data analytics
      3. 6.3. The process of Big Data analytics: from the data source to its analysis
      4. 6.4. Conclusion
    3. 7 Data and Platforms in the Sharing Context
      1. 7.1. Introduction
      2. 7.2. Pioneers in Big Data
      3. 7.3. Data, essential for sharing
      4. 7.4. Conclusion
    4. 8 Big Data Analytics Applied to the Sharing Economy
      1. 8.1. Introduction
      2. 8.2. Big Data and Machine Learning algorithms serving the sharing economy
      3. 8.3. Big Data technologies: the sharing economy companies’ toolbox
      4. 8.4. Big Data on the agenda of sharing economy companies
      5. 8.5. Conclusion
  6. PART 3: The Sharing Economy? Not Without Big Data Algorithms
    1. 9 Linear Regression
      1. 9.1. Introduction
      2. 9.2. Linear regression: an advanced analysis algorithm
      3. 9.3. Other regression methods
      4. 9.4. Building your first predictive model: a use case
      5. 9.5. Conclusion
    2. 10 Classification Algorithms
      1. 10.1. Introduction
      2. 10.2. A tour of classification algorithms
      3. 10.3. Modeling Airbnb prices with classification algorithms
      4. 10.4. Conclusion
    3. 11 Cluster Analysis
      1. 11.1. Introduction
      2. 11.2. Cluster analysis: general framework
      3. 11.3. Grouping similar objects using k-means
      4. 11.4. Hierarchical classification
      5. 11.5. Discovering hidden structures with clustering algorithms
      6. 11.6. Conclusion
  7. Conclusion
  8. References
  9. Index
  10. End User License Agreement
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