Atjaunināt sīkdatņu piekrišanu

E-grāmata: Sharing Economy and Big Data Analytics

5.00/5 (1 ratings by Goodreads)
,
  • Formāts: EPUB+DRM
  • Izdošanas datums: 09-Jan-2020
  • Izdevniecība: ISTE Ltd and John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781119694991
Citas grāmatas par šo tēmu:
  • Formāts - EPUB+DRM
  • Cena: 165,30 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
  • Bibliotēkām
Sharing Economy and Big Data AnalyticsPalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 09-Jan-2020
  • Izdevniecība: ISTE Ltd and John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781119694991
Citas grāmatas par šo tēmu:

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

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.
Preface xi
Introduction xiii
Part 1 The Sharing Economy or the Emergence of a New Business Model
1(2)
Chapter 1 The Sharing Economy: A Concept Under Construction
3(1)
1.1 Introduction
3(2)
1.2 From simple sharing to the sharing economy
5(5)
1.2.1 The genesis of the sharing economy and the break with "consumer" society
5(3)
1.2.2 The sharing economy: which economy?
8(2)
1.3 The foundations of the sharing economy
10(1)
1.3.1 Peer-to-peer (P2P): a revolution in computer networks
10(3)
1.3.2 The gift: the abstract aspect of the sharing economy
13(5)
1.3.3 The service economy and the offer of use
18(6)
1.4 Conclusion
24(1)
Chapter 2 An Opportunity for the Business World
25(1)
2.1 Introduction
25(2)
2.2 Prosumption: a new sharing economy trend for the consumer
27(2)
2.3 Poverty: a target in the spotlight of the shared economy
29(2)
2.4 Controversies on economic opportunities of the sharing economy
31(6)
2.5 Conclusion
37(2)
Chapter 3 Risks and Issues of the Sharing Economy
39(1)
3.1 Introduction
39(1)
3.2 Uberization: a white grain or just a summer breeze?
40(3)
3.3 The sharing economy: a disruptive model
43(4)
3.4 Major issues of the sharing economy
47(3)
3.5 Conclusion
50(1)
Chapter 4 Digital Platforms and the Sharing Mechanism
51(1)
4.1 Introduction
51(1)
4.2 Digital platforms: "What growth!"
52(2)
4.3 Digital platforms or technology at the service of the economy
54(3)
4.4 From the sharing economy to the sharing platform economy
57(2)
4.5 Conclusion
59(2)
Part 2 Big Data Analytics at the Service of the Sharing Economy
61(2)
Chapter 5 Beyond the Word "Big": The Changes
63(1)
5.1 Introduction
63(1)
5.2 The 3 Vs and much more: volume, variety, velocity
64(5)
5.2.1 Volume
65(1)
5.2.2 The variety
66(1)
5.2.3 Velocity
67(1)
5.2.4 What else?
68(1)
5.3 The growth of computing and storage capacities
69(5)
5.3.1 Big Data versus Big Computing
70(1)
5.3.2 Big Data storage
71(2)
5.3.3 Updating Moore's Law
73(1)
5.4 Business context change in the era of Big Data
74(4)
5.4.1 The decision-making process and the dynamics of value creation
75(2)
5.4.2 The emergence of new data-driven business models
77(1)
5.5 Conclusion
78(3)
Chapter 6 The Art of Analytics
81(1)
6.1 Introduction
81(1)
6.2 From simple analysis to Big Data analytics
82(6)
6.2.1 Descriptive analysis: learning from past behavior to influence future outcomes
84(1)
6.2.2 Predictive analysis: analyzing data to predict future outcomes
84(1)
6.2.3 Prescriptive analysis: recommending one or more action plan(s)
85(2)
6.2.4 From descriptive analysis to prescriptive analysis: an example
87(1)
6.3 The process of Big Data analytics: from the data source to its analysis
88(9)
6.3.1 Definition of objectives and requirements
90(1)
6.3.2 Data collection
91(1)
6.3.3 Data preparation
92(2)
6.3.4 Exploration and interpretation
94(1)
6.3.5 Modeling
95(2)
6.3.6 Deployment
97(1)
6.4 Conclusion
97(2)
Chapter 7 Data and Platforms in the Sharing Context
99(1)
7.1 Introduction
99(2)
7.2 Pioneers in Big Data
101(1)
7.2.1 Big Data on Walmart's shelves
101(1)
7.2.2 The Big Data behind Netflix's success story
102(1)
7.2.3 The Amazon version of Big Data
103(1)
7.2.4 Big data and social networks: the case of Facebook
104(1)
7.2.5 IBM and data analysis in the health sector
105(1)
7.3 Data, essential for sharing
106(10)
7.3.1 Data and platforms at the heart of the sharing economy
108(2)
7.3.2 The data of sharing economy companies
110(1)
7.3.3 Privacy and data security in a sharing economy
111(3)
7.3.4 Open Data and platform data sharing
114(2)
7.4 Conclusion
116(3)
Chapter 8 Big Data Analytics Applied to the Sharing Economy
119(1)
8.1 Introduction
119(2)
8.2 Big Data and Machine Learning algorithms serving the sharing economy
121(1)
8.2.1 Machine Learning algorithms
122(2)
8.2.2 Algorithmic applications in the sharing economy context
124(1)
8.3 Big Data technologies: the sharing economy companies' toolbox
125(2)
8.3.1 The appearance of a new concept and the creation of new technologies
127(3)
8.4 Big Data on the agenda of sharing economy companies
130(9)
8.4.1 Uber
131(1)
8.4.2 Airbnb
132(1)
8.4.3 BlaBlaCar
133(1)
8.4.4 Lyft
134(1)
8.4.5 Yelp
135(2)
8.4.6 Other cases
137(2)
8.5 Conclusion
139(2)
Part 3 The Sharing Economy? Not Without Big Data Algorithms
141(2)
Chapter 9 Linear Regression
143(1)
9.1 Introduction
143(1)
9.2 Linear regression: an advanced analysis algorithm
144(1)
9.2.1 How are regression problems identified?
145(1)
9.2.2 The linear regression model
146(2)
9.2.3 Minimizing modeling error
148(1)
9.3 Other regression methods
149(3)
9.3.1 Logistic regression
150(1)
9.3.2 Additional regression models: regularized regression
151(1)
9.4 Building your first predictive model: a use case
152(17)
9.4.1 What variables help set a rental price on Airbnb?
152(17)
9.5 Conclusion
169(2)
Chapter 10 Classification Algorithms
171(1)
10.1 Introduction
171(1)
10.2 A tour of classification algorithms
172(1)
10.2.1 Decision trees
172(3)
10.2.2 Naive Bayes
175(2)
10.2.3 Support Vector Machine (SVM)
177(2)
10.2.4 Other classification algorithms
179(4)
10.3 Modeling Airbnb prices with classification algorithms
183(1)
10.3.1 The work that's already been done: overview
184(1)
10.3.2 Models based on trees: decision tree versus Random Forest
185(5)
10.3.3 Price prediction with kNN
190(3)
10.4 Conclusion
193(2)
Chapter 11 Cluster Analysis
195(1)
11.1 Introduction
195(1)
11.2 Cluster analysis: general framework
196(4)
11.2.1 Cluster analysis applications
197(1)
11.2.2 The clustering algorithm and the similarity measure
198(2)
11.3 Grouping similar objects using k-means
200(1)
11.3.1 The k-means algorithm
201(2)
11.3.2 Determine the number of clusters
203(2)
11.4 Hierarchical classification
205(3)
11.4.1 The hierarchical model approach
206(1)
11.4.2 Dendrograms
207(1)
11.5 Discovering hidden structures with clustering algorithms
208(5)
11.5.1 Illustration of the classification of prices based on different characteristics using the k-means algorithm
209(1)
11.5.2 Identify the number of clusters k
210(3)
11.6 Conclusion
213(2)
Conclusion 215(2)
References 217(16)
Index 233
Soraya Sedkaoui is a Senior Lecturer at the University of Khemis Miliana, Algeria, as well as a data analyst and a strategic consultant. Her interests include Big Data, and the development of algorithms and models for business applications.





Mounia Khelfaoui is a Researcher and Maītre de conférences at the University of Khemis Miliana. Her research mainly focuses on sustainable development and all the relevant themes, with a focus on the social responsibility of organizations.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97811196949916e.html
Keywords: