Global manufacturing has extended the supply chain not only in span of networks and dispersion of geographical locations but also more importantly, it also transcends vast organizational boundaries among webs of long supply chains. Naturally, the information and computation technology (ICT) systems supporting these entities serve well on their own merits independently; however, the sharing of information among them in a responsive and agile and secure fashion is limited. The advent of cloud computing provides a distinct possibility to enhance sharing of information, to better apply modern analytic tools and to improve managing the controlled access as well as security. This paper is prepared to address the architectural issues of the data, analytics, and organizational layers.

Issue Section:
Special Section Articles
Keywords:
Control, Production systems optimization, Automation
Topics:
Cloud computing, Design, Supply chains, Security, Manufacturing

References

1.
Assunção
,
M. D.
,
Calheiros
,
R. N.
,
Bianchi
,
S.
,
Netto
,
M. A. S.
, and
Buyya
,
R.
,
2015
, “
Big Data Computing and Clouds: Trends and Future Directions
,”
J. Parallel Distrib. Comput.
,
79–80
, pp.
3
–
15
.10.1016/j.jpdc.2014.08.003
Google Scholar
Crossref
Search ADS
 
2.
Hardy
,
Q.
,
2014
, “
What Cars Did for Today’s World, Data May Do for Tomorrow’s
,” Bits, Blog, Accessed Sept. 24, 2014, http://mobile.nytimes.com/blogs/bits/2014/08/10/g-e-creates-a-data-lake-for-new-industrial-ecosystem/
3.
Manyika
,
J.
,
Chui
,
M.
,
Bughin
,
J.
,
Dobbs
,
R.
,
Bisson
,
P.
, and
Marrs
,
A.
,
2013
,
Disruptive Technologies: Advances That Will Transform Life, Business, and the Global Economy
,
McKinsey Global Institute
, pp.
1
–
176
.
4.
Manyika
,
J.
,
Chui
,
M.
,
Brown
,
B.
,
Bughin
,
J.
,
Dobbs
,
R.
,
Roxburgh
,
C.
, and
Byers
,
A. H.
,
2011
,
Big Data: The Next Frontier for Innovation, Competition, and Productivity
,
McKinsey Global Institute
, pp.
1
–
156
.
5.
Paul
,
A.
,
2014
,
The Information Paradigm Shift: Redefine Your Competitive Advantage
,
Hewlett-Packard Company
,
Dover, DE
, p.
16
.
6.
Shaw
,
J.
,
2014
, “
Why 'Big Data' Is a Big Deal
,”
Harvard Magazine
, Mar.–Apr., pp.
30
–
75
.
7.
Böhm
,
M.
,
Koleva
,
G.
,
Leimeister
,
S.
,
Riedl
,
C.
, and
Krcmar
,
H.
,
2010
, “
Towards a Generic Value Network for Cloud Computing
,”
Economics of Grids, Clouds, Systems, and Services
,
J.
Altmann
, and
O. F.
Rana
, eds.,
Springer
,
Berlin, Germany
.10.1007/978-3-642-15681-6_10
8.
Fung
,
V. K.
,
Fung
,
W. K.
, and
Wind
,
Y. J. R.
,
2007
,
Competing in a Flat World: Building Enterprises for a Borderless World
,
Pearson Prentice Hall
,
Upper Saddle River, NJ
.
9.
Magretta
,
J.
,
1998
, “
Fast, Global, and Entrepreneurial: Supply Chain Management, Hong Kong Style: An Interview With Victor Fung
,”
Harv. Bus. Rev.
,
76
(
5
), pp.
102
–
114
.10.1225/2020
Google Scholar
PubMed
 
10.
Sirkin
,
H. L.
,
Zinser
,
M.
, and
Rose
,
J.
,
2013
,
The U.S. as One of the Developed World's Lowest-Cost Manufacturers
,
Chicago, IL
, pp. 1–18.
11.
Porter
,
E.
,
2014
,
Globalization Is in Retreat? Not So Fast
,
The New York Times
,
New York
.
12.
Lee
,
H. L.
,
2004
, “
The Triple-A Supply Chain
,”
Harv. Bus. Rev.
,
82
(
10
), pp.
102
–
112
.10.1108/01443571211195727
Google Scholar
PubMed
 
13.
Gattorna
,
J.
,
2010
,
Dynamic Supply Chains: Delivering Value Through People
, 2 ed.,
FT Press
,
New York
.
14.
Radke
,
A. M.
,
2012
, “
An Inventory Planning Methodology Based on the Value of Inventory in High-Mix Low-Volume Production
,” Ph.D. thesis, Industrial Engineering and Logistics Management Department, Hong Kong University of Science & Technology.
15.
Cavinato
,
J. L.
,
Flynn
,
A. E.
, and
Kauffman
,
R. G.
,
2006
,
The Supply Management Handbook
, 7 ed.,
McGraw-Hill
,
New York
.
16.
Monczka
,
R. M.
,
Handfield
,
R. B.
,
Giunipero
,
L. C.
, and
Patterson
,
J. L.
,
2011
,
Purchasing and Supply Chain Management
, 5 ed.,
Cengage Learning
,
Cincinnati, OH
.
17.
Burt
,
D.
,
Dobler
,
D.
, and
Starling
,
S.
,
2002
,
World Class Supply Management: The Key to Supply Chain Management
, 7 ed.,
McGraw-Hill/Irwin
,
Boston, MA
.
18.
Johnson
,
P. F.
,
Leenders
,
M.
, and
Flynn
,
A.
,
2010
,
Purchasing and Supply Management
, 14 ed.,
The Mcgraw-Hill/Irwin Series Operations and Decisions Sciences, McGraw-Hill/Irwin
,
Boston, MA
.
19.
Payne
,
J.
, and
Dorn
,
W. R.
,
2011
,
Managing Indirect Spend: Enhancing Profitability Through Strategic Sourcing
,
Wiley
,
Hoboken, NJ
.10.1002/9781118386828
20.
Kaufmann
,
L.
, and
Hedderich
,
F.
,
2005
, “
A Novel Framework for International Sourcing Applied to the Emerging Chinese Supply Market
,”
Perspektiven des Supply Management: Konzepte und Anwendungen
,
M.
Eßig
, ed.,
Springer
,
Berlin, Germany
, Chap. 6.
21.
Bahrami
,
B.
, and
Jordan
,
E.
,
2013
, “
Utilizing Enterprise Resource Planning in Decision-Making Processes
,”
Innovation and Future of Enterprise Information Systems
,
F.
Piazolo
, and
M.
Felderer
, eds.,
Springer
,
Berlin, Germany
, Chap. 13.10.1007/978-3-642-37021-2_13
22.
Ajayi
,
N.
,
2013
, “
The Role of Information System in Supply Chain Information Management
,”
International Conference on Information Society (i-Society 2013)
, Toronto, ON, June 24–26, pp.
138
–
146
.
23.
Jula
,
A.
,
Sundararajan
,
E.
, and
Sundararajan
,
Z.
,
2014
, “
Cloud Computing Service Composition: A Systematic Literature Review
,”
Expert Syst. Appl.
,
41
(
8
), pp.
3809
–
3824
.10.1016/j.eswa.2013.12.017
Google Scholar
Crossref
Search ADS
 
24.
Hsu
,
P.-F.
,
Ray
,
S.
, and
Li-Hsieh
,
Y.-Y.
,
2014
, “
Examining Cloud Computing Adoption Intention, Pricing Mechanism, and Deployment Model
,”
Int. J. Inf. Manage.
,
34
(
4
), pp.
474
–
488
.10.1016/j.ijinfomgt.2014.04.006
Google Scholar
Crossref
Search ADS
 
25.
Ooi
,
K.-B.
,
Chong
,
A. Y.-L.
, and
Tan
,
B.-I.
,
2011
, “
Application of Web 2.0 in Supply Chain Management: A Brief Overview
,”
Trends Appl. Sci. Res.
,
6
(
4
), pp.
394
–
399
.10.3923/tasr.2011.394.399
Google Scholar
Crossref
Search ADS
 
26.
Matzer
,
M.
,
2014
, “
Der deutsche Cloudmarkt wächst, doch die Fertigungsindustrie hinkt hinterher
,”
VDI Nachrichten
,
VDI Verlag
,
Düsseldorf, Germany
, p.
10
.
27.
Cegielski
,
C. G.
,
Jones-Farmer
,
L. A.
,
Wu
,
Y.
, and
Hazen
,
B. T.
,
2012
, “
Adoption of Cloud Computing Technologies in Supply Chains: An Organizational Information Processing Theory Approach
,”
Int. J. Logist. Manage.
,
23
(
2
), pp.
184
–
211
.10.1108/09574091211265350
Google Scholar
Crossref
Search ADS
 
28.
Wu
,
Y.
,
Cegielski
,
C. G.
,
Hazen
,
B. T.
, and
Hall
,
D. J.
,
2013
, “
Cloud Computing in Support of Supply Chain Information System Infrastructure: Understanding When to Go to the Cloud
,”
J. Supply Chain Manage.
,
49
(
3
), pp.
25
–
41
.10.1111/j.1745-493x.2012.03287.x
Google Scholar
Crossref
Search ADS
 
29.
Oliveira
,
T.
,
Thomas
,
M.
, and
Espadanal
,
M.
,
2014
, “
Assessing the Determinants of Cloud Computing Adoption: An Analysis of the Manufacturing and Services Sectors
,”
Inf. Manage.
,
51
(
5
), pp.
497
–
510
.10.1016/j.im.2014.03.006
Google Scholar
Crossref
Search ADS
 
30.
Subramanian
,
N.
,
Abdulrahman
,
M. D.
, and
Zhou
,
X.
,
2014
, “
Integration of Logistics and Cloud Computing Service Providers: Cost and Green Benefits in the Chinese Context
,”
Transp. Res.
, Part E,
70
, pp.
86
–
98
.10.1016/j.tre.2014.06.015
31.
Gerhardter
,
A.
, and
Ortner
,
W.
,
2013
, “
Flexibility and Improved Resource Utilization Through Cloud Based ERP Systems: Critical Success Factors of SaaS Solutions in SME
,”
Innovation and Future of Enterprise Information Systems
,
F.
Piazolo
, and
M.
Felderer
, eds.,
Springer
,
Berlin, Germany
, Chap. 14.10.1007/978-3-642-37021-2_14
32.
Hansel
,
S.
,
2014
, “
Broker für die Cloud
,”
VDI Nachrichten
,
VDI Verlag
,
Düsseldorf, Germany
, p.
10
.
33.
Buyya
,
R.
,
Vecchiola
,
C.
, and
Selvi
,
S. T.
,
2013
, “
Cloud Computing Architecture
,”
Mastering Cloud Computing
,
R.
Buyya
,
C.
Vecchiola
, and
S. T.
Selvi
, eds.,
Morgan Kaufmann
,
Boston, MA
, Chap. 4.10.1016/B978-0-12-411454-8.00004-8
34.
Chang
,
V.
,
Walters
,
R. J.
, and
Wills
,
G.
,
2013
, “
The Development That Leads to the Cloud Computing Business Framework
,”
Int. J. Inf. Manage.
,
33
(
3
), pp.
524
–
538
.10.1016/j.ijinfomgt.2013.01.005
Google Scholar
Crossref
Search ADS
 
35.
Hill
,
R.
,
Hirsch
,
L.
,
Lake
,
P.
, and
Moshiri
,
S.
2012
, “
Developing a Cloud Roadmap
,”
Guide to Cloud Computing
,
Springer
,
London, UK
, Chap. 11.10.1007/978-1-4471-4603-2_11
36.
Yang
,
N.
,
Li
,
D.
, and
Tong
,
Y.
,
2012
, “
A Cloud Computing-Based ERP System Under the Cloud Manufacturing Environment
,”
Int. J. Digital Content Technol. Appl.
,
6
(
23
), pp.
126
–
134
.10.4156/jdcta.vol6.issue23.15
Google Scholar
Crossref
Search ADS
 
37.
Mezgár
,
I.
, and
Rauschecker
,
U.
,
2014
, “
The Challenge of Networked Enterprises for Cloud Computing Interoperability
,”
Comput. Ind.
,
65
(
4
), pp.
657
–
674
.10.1016/j.compind.2014.01.017
Google Scholar
Crossref
Search ADS
 
38.
Lu
,
Y.
,
Xu
,
X.
, and
Xu
,
J.
,
2014
, “
Development of a Hybrid Manufacturing Cloud
,”
J. Manuf. Syst.
,
33
(
4
), pp.
551
–
566
.10.1016/j.jmsy.2014.05.003
Google Scholar
Crossref
Search ADS
 
39.
Schrödl
,
H.
,
2012
, “
Adoption of Cloud Computing in Supply Chain Management Solutions: A SCOR-Aligned Assessment
,”
Web Technologies and Applications
,
H.
Wang
, et al., eds.,
Springer
,
Berlin, Germany
.10.1007/978-3-642-29426-6_27
40.
Xu
,
X.
,
2012
, “
From Cloud Computing to Cloud Manufacturing
,”
Rob. Comput. Integr. Manuf.
,
28
(
1
), pp.
75
–
86
.10.1016/j.rcim.2011.07.002
Google Scholar
Crossref
Search ADS
 
41.
Nair
,
P. R.
,
2014
, “
Tackling Supply Chain Through Cloud Computing: Management Opportunities, Challenges and Successful Deployments
,”
ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of
CSI 2013
, Varun Beach, Visakhapatnam, Springer International Publishing.10.1007/978-3-319-03095-1_82
42.
Rossetti
,
M. D.
, and
Yaohua
,
C.
,
2012
, “
A Cloud Computing Architecture for Supply Chain Network Simulation
,”
2012 Winter Simulation Conference
(
WSC
), Berlin, Germany, Dec. 9–12, pp.
1
–
12
.10.1109/WSC.2012.6465196
43.
Li
,
Q.
, and
Xia
,
N.
,
2011
, “
The Utilization of Cloud Computing in Network Collaborative Commerce Chain
,”
4th International Conference on Business Intelligence and Financial Engineering
, Wuhan, China, Oct. 17–18, pp.
279
–
284
.10.1109/BIFE.2011.148
44.
Lackermair
,
G.
,
2011
, “
Hybrid Cloud Architectures for the Online Commerce
,”
Procedia Comput. Sci.
,
3
, pp.
550
–
555
.10.1016/j.procs.2010.12.091
Google Scholar
Crossref
Search ADS
 
45.
Moynihan
,
P.
, and
Wei
,
D.
,
2013
, “
Concurrent Intelligent Integration and Optimisation Engine for Supply Chains Management
,”
16th International Conference on Network-Based Information Systems 2013
, Gwangju, Korea, Sep. 4–6, pp.
577
–
582
.10.1109/NBiS.2013.96
46.
Leukel
,
J.
,
Kirn
,
S.
, and
Schlegel
,
T.
,
2011
, “
Supply Chain as a Service: A Cloud Perspective on Supply Chain Systems
,”
IEEE Syst. J.
,
5
(
1
), pp.
16
–
27
.10.1109/JSYST.2010.2100197
Google Scholar
Crossref
Search ADS
 
47.
Wu
,
D.
, Greer, M. J., Rosen, D. W., and Schaefer, D.,
2013
, “
Cloud Manufacturing: Drivers, Current Status, and Future Trends
,”
ASME
Paper No. MSEC2013-1106. 10.1115/MSEC2013-1106
48.
Adamson
,
G.
,
Wang
,
L.
, and
Holm
,
M.
,
2013
, “
The State of the Art of Cloud Manufacturing and Future Trends
,”
ASME
Paper No. MSEC2013-1123. 10.1115/MSEC2013-1123
49.
Helgoson
,
M.
,
Wang
,
L.
,
Karlsson
,
R.
,
Givehchi
,
M.
, and
Tedeborg
,
M.
,
2014
, “
Concept for Function Block Enabled Process Planning Towards Multi-Site Cloud Collaboration
,”
ASME
Paper No. MSEC2014-4027. 10.1115/MSEC2014-4027
50.
Hu
,
C.
,
Xu
,
C.
,
Cao
,
X.
, and
Zhang
,
P.
,
2013
, “
Study on the Multi-Granularity Virtualization of Manufacturing Resources
,”
ASME
Paper No. MSC2013-1174.10.1115/MSEC2013-1174
51.
Wang
,
X. V.
, and
Xu
,
X. W.
,
2013
, “
Virtualize Manufacturing Capabilities in the Cloud: Requirements and Architecture
,”
ASME
Paper No. MSEC2013-1046. 10.1115/MSEC2013-1046
52.
Liu
,
X.
,
Li
,
Y.
,
Wang
,
W.
, and
Wang
,
L.
,
2014
, “
A Feature Based Method for Product-Oriented Representation to Manufacturing Resources in Cloud Manufacturing
,”
ASME
Paper No. MSEC2014-4031. 10.1115/MSEC2014-4031
53.
Helo
,
P.
,
Suorsaa
,
M.
,
Haoa
,
Y.
, and
Anussornnitisarn
,
P.
,
2014
, “
Toward a Cloud-Based Manufacturing Execution System for Distributed Manufacturing
,”
Comput. Ind.
,
65
(
4
), pp.
646
–
656
.10.1016/j.compind.2014.01.015
Google Scholar
Crossref
Search ADS
 
54.
Rauschecker
,
U.
,
Stöhr
,
M.
, and
Schel
,
D.
,
2013
, “
Requirements and Concept for a Manufacturing Service Management and Execution Platform for Customizable Products
,”
ASME
Paper No. MSEC2013-1021. 10.1115/MSEC2013-1021
55.
Wang
,
L.
,
Gao
,
R.
, and
Ragai
,
I.
,
2014
, “
An Integrated Cyber-Physical System for Cloud Manufacturing
,”
ASME
Paper No. MSEC2014-4171. 10.1115/MSEC2014-4171
56.
Yang
,
Y.
,
Gao
,
R. X.
,
Fan
,
Z.
,
Wang
,
J.
, and
Wang
,
L.
,
2014
, “
Cloud-Based Prognosis: Perspective and Challenge
,”
ASME
Paper No. MSEC2014-4155. 10.1115/MSEC2014-4155
57.
Wang
,
L.
,
2013
, “
Machine Availability Monitoring and Machining Process Planning Towards Cloud Manufacturing
,”
CIRP J. Manuf. Sci. Technol.
,
6
(
4
), pp.
263
–
273
.10.1016/j.cirpj.2013.07.001
Google Scholar
Crossref
Search ADS
 
58.
Wang
,
L.
,
Wanga
,
X. V.
,
Gaob
,
L.
, and
Vánczac
,
J.
,
2014
, “
A Cloud-Based Approach for WEEE Remanufacturing
,”
CIRP Ann.: Manuf. Technol.
,
63
(
1
), pp.
409
–
412
.10.1016/j.cirp.2014.03.114
Google Scholar
Crossref
Search ADS
 
59.
Yip
,
A. L. K.
,
Corney
,
J. R.
,
Jagadeesan
,
A. P.
, and
Qin
,
Y.
,
2013
, “
A Product Configurator for Cloud Manufacturing
,”
ASME
Paper No. MSEC2013-1250. 10.1115/MSEC2013-1250
60.
Wu
,
D.
,
Rosen
,
D. W.
,
Wang
,
L.
, and
Schaefer
,
D.
,
2015
, “
Cloud-Based Design and Manufacturing: A New Paradigm in Digital Manufacturing and Design Innovation
,”
Comput.-Aided Design
,
59
, pp.
1
–
14
.10.1016/j.cad.2014.07.006
Google Scholar
Crossref
Search ADS
 
61.
Ren
,
L.
,
Zhang
,
L.
,
Zhao
,
C.
, and
Chai
,
X.
,
2013
, “
Cloud Manufacturing Platform: Operating Paradigm, Functional Requirements, and Architecture Design
,”
ASME
Paper No. MSEC2013-1185. 10.1115/MSEC2013-1185
62.
Lückmann
,
R.
,
2014
, “
Die Buchhaltung im Handgepäck
,”
VDI Nachrichten
,
VDI Verlag
,
Düsseldorf, Germany
, p.
12
.
63.
Hammerschmidt
,
C.
,
2014
, “
Kapitäne der Fernstraße im Netz von Big Data
,”
VDI Nachrichten
,
VDI Verlag
,
Düsseldorf, Germany
, p.
14
.
64.
Ren
,
L.
,
Zhang
,
L.
,
Hou
,
B.
,
Wu
,
Q.
, and
Teng
,
D.
,
2014
, “
Intelligent User Interface in Cloud Manufacturing
,”
ASME
Paper No. MSEC2014-4099. 10.1115/MSEC2014-4099
65.
Chen
,
C. L. P.
, and
Zhang
,
C.-Y.
,
2014
, “
Data-Intensive Applications, Challenges, Techniques and Technologies: A Survey on Big Data
,”
Inf. Sci.
,
275
(
10
), pp.
314
–
347
.10.1016/j.ins.2014.01.015
Google Scholar
Crossref
Search ADS
 
66.
Chen
,
M.
,
Mao
,
S.
,
Zhang
,
Y.
, and
Leung
,
V. C.
,
2014
,
Big Data: Related Technologies, Challenges and Future Prospects
(Springer Briefs in Computer Science),
S.
Zdonik
, et al., eds.,
Springer
,
Heidelberg, Germany
.10.1007/978-3-319-06245-7
67.
Committee on the Analysis of Massive Data, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Their Applications, Division on Engineering and Physical Sciences, and National Research Council,
2013
,
Frontiers in Massive Data Analysis
,
The National Academic Press
,
Washington, DC
.
68.
Loshin
,
D.
,
2013
, “
Big Data Tools and Techniques
,”
Big Data Analytics
,
D.
Loshin
, ed.,
Morgan Kaufmann
,
Boston, MA
, Chap. 7.10.1016/B978-0-12-417319-4.00007-7
69.
Smith
,
G. S.
,
2013
,
Straight to the Top: CIO Leadership in a Mobile, Social, and Cloud-Based World
, 2 ed.,
Wiley
,
Hoboken, NJ
.10.1002/9781118634226
70.
Sanders
,
N. R.
,
2014
,
Big Data Driven Supply Chain Management: A Framework for Implementing Analytics and Turning Information Into Intelligence
,
Pearson Education
,
Upper Saddle River, NJ
.
71.
Supply Chain Council
,
2014
, “
Supply Chain Operations Reference (SCOR) Model: Overview
,” Supply Chain Council, Cypress, TX, p.
24
.
72.
Chao
,
C.-H.
,
2013
, “
The Framework of Information Processing Network for Supply Chain Innovation in Big Data Era
,”
The 3rd International Workshop on Intelligent Data Analysis and Management
,
L.
Uden
,
L. S. L.
Wang
,
T.-P.
Hong
,
H.-C.
Yang
, and
I.-H.
Ting
, eds.,
Springer, Dordrecht
,
The Netherlands
, Chap. 9.10.1007/978-94-007-7293-9_9
73.
van Rijmenam
,
M.
,
2014
,
Think Bigger: Developing a Successful Big Data Strategy for Your Company
,
AMACOM
,
New York
.
74.
Howard
,
J.
,
Zwemer
,
M.
, and
Loukides
,
M.
,
2012
,
Designing Great Data Products
,
O'Reilly Media
,
Sebastopol, CA
.
75.
Demirkan
,
H.
, and
Delen
,
D.
,
2013
, “
Leveraging the Capabilities of Service-Oriented Decision Support Systems: Putting Analytics and Big Data in Cloud
,”
Decis. Support Syst.
,
55
(
1
), pp.
412
–
421
.10.1016/j.dss.2012.05.048
Google Scholar
Crossref
Search ADS
 
76.
Krishnan
,
K.
,
2013
, “
Data-Driven Architecture for Big Data
,”
Data Warehousing in the Age of Big Data
,
K.
Krishnan
, ed.,
Morgan Kaufmann
,
Boston, MA
, Chap. 11.10.1016/B978-0-12-405891-0.00011-8
77.
Chan
,
C. P.
,
2014
, “
Hitachi Leads by Example in Big-Data Analytics
,”
The Edge Singapore
,
Edge Business Publishing
,
Singapore, Singapore
.
78.
IBM
,
2014
,
Five Best Practices for Maximizing Big Data ROI
,
IBM
, p.
5
.
79.
Strickland
,
J.
,
2014
, “
How Server Virtualization Works
,” Accessed Sept. 21, 2014, http://computer.howstuffworks.com/server-virtualization.htm
80.
Fitzgerald
,
M.
,
2014
, “
The Four Traps of Predictive Analytics
,” Big Idea: Data and Analytics, Accessed Aug. 25, 2014, http://sloanreview.mit.edu/article/the-four-traps-of-predictive-analytics/
81.
Kwon
,
O.
,
Lee
,
N.
, and
Shin
,
B.
,
2014
, “
Data Quality Management, Data Usage Experience and Acquisition Intention of Big Data Analytics
,”
Int. J. Inf. Manage.
,
34
(
3
), pp.
387
–
394
.10.1016/j.ijinfomgt.2014.02.002
Google Scholar
Crossref
Search ADS
 
82.
Kambatla
,
K.
,
Kolliasb
,
G.
,
Kumarc
,
V.
, and
Gramaa
,
A.
,
2014
, “
Trends in Big Data Analytics
,”
J. Parallel Distrib. Comput.
,
74
(
7
), pp.
2561
–
2573
.10.1016/j.jpdc.2014.01.003
Google Scholar
Crossref
Search ADS
 
83.
Rajpurohit
,
A.
,
2014
, “
Exclusive Interview: Ajay Bhargava, TCS Shares the Big Data Mantra: Harness Data and Harvest Value
,” Accessed Sept. 23, 2014, http://www.kdnuggets.com/2014/09/interview-ajay-bhargava-tcs-big-data-mantra.html
84.
Lohr
,
S.
,
2014
, “
Future of Data Science
,” Bits, Blog, Accessed Sept. 23, 2014, http://mobile.nytimes.com/blogs/bits/2014/08/27/looking-to-the-future-of-data-science/
85.
Watts
,
D. J.
,
2014
, “
Scientific Thinking in Business
,”
MIT Technology Review
,
Jason Pontin
,
Cambridge, MA
.
86.
Bourguignat
,
C.
,
2014
, “
Interpretable Versus Powerful Predictive Models: Why We Need Them Both
,” Medium Blog, Accessed Sept. 23, 2014, https://medium.com/@chris_bour/interpretable-vs-powerful-predictive-models-why-we-need-them-both-990340074979
87.
Howard
,
J.
,
2012
, “
From Predictive Modelling to Optimization: The Next Frontier [Video, 35:12]
,” http://www.youtube.com/watch?v=vYrWTDxoeGg&feature=youtu.be
88.
Ransbotham
,
S.
,
2014
, “
Does Your Company Collect Data or Hoard It?
,” Big Idea: Data & Analytics, Blog, Accessed July 28, 2014, http://sloanreview.mit.edu/article/does-your-company-collect-data-or-hoard-it/
89.
Bollier
,
D.
,
2010
, “
The Promise and Peril of Big Data
,”
Communications and Society Program
,
C. M.
Firestone
, ed.,
The Aspen Institute
,
Washington, DC
, p.
56
.
90.
Coe
,
R.
,
2002
, “
It’s the Effect Size, Stupid—What Effect Size Is and Why It Is Important
,”
Annual Conference of the British Educational Research Association
, University of Exeter, Exeter, UK, pp.
1
–
18
.
91.
van Rijsbergen
,
C. J.
,
1979
, “
Evaluation
,”
Information Retrieval
, 2nd ed.,
Butterworth-Heinemann
,
Cambridge, UK
, Chap. 7.
92.
Asteriou
,
D.
, and
Hall
,
S. G.
,
2011
, “
Heteroskedasticity
,”
Applied Econometrics
,
Palgrave MacMillan
,
Basingstoke, UK
, Chap. 6.
93.
Rose
,
J.
, Barton, C., Souza, R., and Platt, J.,
2013
, “
The Trust Advantage: How to Win With Big Data
,” Accessed Sept. 21, 2014, https://www.bcgperspectives.com/content/articles/information_technology_strategy_consumer_products_trust_advantage_win_big_data/
94.
Stedman
,
C.
, and
Vaughan
,
J.
,
2013
, “
Orchestrating a Big Data Integration Strategy
,” TechTarget, Newton, MA, p.
9
.
95.
Barlow
,
M.
,
2013
,
Real-Time Big Data Analytics: Emerging Architecture
,
O'Reilly Media
,
Sebastopol, CA
.
97.
Katsov
,
I.
,
2013
, “
In-Stream Big Data Processing
,” Highly-Scalable, Blog, Accessed Oct. 1, 2014, http://highlyscalable.wordpress.com/2013/08/20/in-stream-big-data-processing/
98.
Cukier
,
K.
, and
Mayer-Schoenberger
,
V.
,
2013
, “
The Rise of Big Data: How It's Changing the Way We Think About the World
,”
Foreign Aff.
,
92
(
3
), pp.
28
–
40
.10.2469/dig.v43.n4.65
99.
Harris
,
D.
,
2014
, “
Google Has Open-Sourced a Tool for Inferring Cause From Correlations
,” GigaOM, Accessed Sept. 23, 2014, https://gigaom.com/2014/09/11/google-has-open-sourced-a-tool-for-inferring-cause-from-correlations/
100.
Ritter
,
D.
,
2014
, “
When to Act on a Correlation, and When Not To
,” Accessed Sept. 2014, http://blogs.hbr.org/2014/03/when-to-act-on-a-correlation-and-when-not-to/
101.
Santillana
,
M.
,
Zhang
,
D. W.
,
Althouse
,
B. M.
, and
Ayers
,
J. W.
,
2014
, “
What Can Digital Disease Detection Learn From (an External Revision to) Google Flu Trends?
,”
Am. J. Prev. Med.
,
47
(
3
), pp.
341
–
347
.10.1016/j.amepre.2014.05.020
Google Scholar
Crossref
Search ADS
PubMed
 
102.
Koendjbiharie
,
S.
,
Koppius
,
O.
,
Vervest
,
P.
, and
van Heck
,
E.
,
2010
, “
Network Transparency and the Performance of Dynamic Business Networks
,”
4th IEEE International Conference on Digital Ecosystems and Technologies
(
DEST
), IEEE, Dubai, UAE, Apr. 13–16, pp.
197
–
202
.10.1109/DEST.2010.5610646
103.
Wagner
,
S. M.
, and
Bukó
,
C.
,
2005
, “
An Empirical Investigation of Knowledge-Sharing in Networks
,”
J. Supply Chain Manage.
,
41
(
4
), pp.
17
–
31
.10.1111/j.1745-493X.2005.04104003.x
Google Scholar
Crossref
Search ADS
 
104.
Hoffer
,
E.
,
2015
, “
The Context of Global Supply Chain Security
,”
Global Supply Chain Security
,
A. R.
Thomas
 and
S.
Vaduva
, eds.,
Springer
,
New York
, Chap. 1.10.1007/978-1-4939-2178-2_1
105.
Hintsa
,
J.
,
2010
, “
A Comprehensive Framework for Analysis and Design of Supply Chain Security Standards
,”
J. Transp. Secur.
,
3
(
2
), pp.
105
–
125
.10.1007/s12198-010-0042-3
Google Scholar
Crossref
Search ADS
 
106.
Urciuoli
,
L.
,
2010
, “
Supply Chain Security—Mitigation Measures and a Logistics Multi-Layered Framework
,”
J. Transp. Secur.
,
3
(
1
), pp.
1
–
28
.10.1007/s12198-009-0034-3
Google Scholar
Crossref
Search ADS
 
107.
Meixell
,
M. J.
, and
Norbis
,
M.
,
2011
, “
Assessing Security Risk in Global Supply Chains
,”
IEEE
International Technology Management Conference 2011
, San Jose, CA, June 27–30, pp.
510
–
515
.10.1109/ITMC.2011.5996020
108.
Roy
,
A.
,
Gupta
,
A. D.
, and
Deshmukh
,
S. G.
,
2012
, “
Information Security in Supply Chains: A Process Framework
,”
IEEE
International Conference on Industrial Engineering and Engineering Management
, Hong Kong, Dec. 10–13, pp.
1448
–
1452
.10.1109/IEEM.2012.6837986
109.
Salmela
,
H.
,
Toivonen
,
S.
, and
Scholliers
,
J.
,
2010
, “
Enhancing Supply Chain Security With Vulnerability Management and New Technology
,”
IET Intell. Transp. Syst.
,
4
(
4
), pp.
307
–
317
.10.1049/iet-its.2009.0124
Google Scholar
Crossref
Search ADS
 
110.
Zage
,
D.
,
Glass
,
K.
, and
Colbaugh
,
R.
,
2013
, “
Improving Supply Chain Security Using Big Data
,”
IEEE
International Conference on Intelligence and Security Informatics 2013
, Seattle, WA, June 4–7, pp.
254
–
259
.10.1109/ISI.2013.6578830
111.
Pearson
,
S.
,
2013
, “
Privacy, Security and Trust in Cloud Computing
,”
Privacy and Security for Cloud Computing
,
S.
Pearson
 and
G.
Yee
, eds.,
Springer
,
London, UK
, Chap. 1.10.1007/978-1-4471-4189-1_1
112.
Compagna
,
L.
,
El Khoury
,
P.
,
Krausová
,
A.
,
Massacci
,
F.
, and
Zannone
,
N.
,
2009
, “
How to Integrate Legal Requirements Into a Requirements Engineering Methodology for the Development of Security and Privacy Patterns
,”
Artif. Intell. Law
,
17
(
1
), pp.
1
–
30
.10.1007/s10506-008-9067-3
Google Scholar
Crossref
Search ADS
 
113.
Eken
,
H.
,
2013
, “
Security Threats and Solutions in Cloud Computing
,” World Congress on Internet Security (
WorldCIS
) 2013, London, Dec. 9–12, pp.
139
–
143
.10.1109/WorldCIS.2013.6751034
114.
Sabahi
,
F.
,
2011
, “
Cloud Computing Security Threats and Responses
,”
IEEE
3rd International Conference on Communication Software and Networks 2011
, Xi'an, China, May 27–29, pp.
245
–
249
.10.1109/ICCSN.2011.6014715
115.
Brodkin
,
J.
,
2008
, “
Gartner: Seven Cloud-Computing Security Risks
,” Accessed Mar. 21, 2015, http://www.infoworld.com/article/2652198/security/gartner--seven-cloud-computing-security-risks.html
116.
Schulzki-Haiddouti
,
C.
,
2015
, “
Europarat Will Big Data mit Datenschutz versöhnen
,”
VDI Nachrichten
,
VDI Verlag
,
Düsseldorf, Germany
, p.
10
.
117.
Behl
,
A.
, and
Behl
,
K.
,
2012
, “
An Analysis of Cloud Computing Security Issues
,” World Congress on Information and Communication Technologies (
WICT
) 2012, Trivandrum, India, Nov. 1–2, pp.
109
–
114
.10.1109/WICT.2012.6409059
118.
Durowoju
,
O.
,
2014
, “
Rationalising the Security Concern of Cloud Enabled E-Commerce in the Supply Chain Context
,”
E-Commerce Platform Acceptance
,
E.
Lacka
,
H. K.
Chan
, and
N.
Yip
, eds.,
Springer
,
Heidelberg
, Chap. 3.10.1007/978-3-319-06121-4_3
119.
Almorsy
,
M.
,
Grundy
,
J.
, and
Ibrahim
,
A. S.
,
2011
, “
Collaboration-Based Cloud Computing Security Management Framework
,”
IEEE International Conference on Cloud Computing
(
CLOUD
), 2011, Washington, DC, June 4–9, pp.
364
–
371
.10.1109/CLOUD.2011.9
120.
Villegas
,
D.
, Bobroff, N., Rodero, I., Delgado, J., Liu, Y., Devarakonda, A., Fong, L., Sadjadi, S. M., and Parashar, M.,
2012
, “
Cloud Federation in a Layered Service Model
,”
J. Comput. Syst. Sci.
,
78
(
5
), pp.
1330
–
1344
.10.1016/j.jcss.2011.12.017
Google Scholar
Crossref
Search ADS
 
121.
Rajpurohit
,
A.
,
2014
, “
Exclusive Interview: Imran Siddiqi, SAP on Why the Business Needs Ambitious Big Data Use Cases
,” Accessed Sept. 23, 2014, http://www.kdnuggets.com/2014/09/interview-imran-siddiqi-sap-big-data-use-cases.html
122.
Hazen
,
B. T.
,
Booneb
,
C. A.
,
Ezellc
,
J. D.
, and
Jones-Farmer
,
L. A.
,
2014
, “
Data Quality for Data Science, Predictive Analytics, and Big Data in Supply Chain Management: An Introduction to the Problem and Suggestions for Research and Applications
,”
Int. J. Prod. Econ.
,
154
, pp.
72
–
80
.10.1016/j.ijpe.2014.04.018
Google Scholar
Crossref
Search ADS
 
123.
Brock
,
J.
,
Souza
,
R.
,
Dreischmeier
,
R.
, and
Platt
,
J.
,
2013
, “
Big Data’s Five Routes to Value: Opportunity Unlocked
,” BCG Perspectives, Accessed Sept. 21, 2014, https://www.bcgperspectives.com/content/articles/information_technology_strategy_digital_economy_opportunity_unlocked_big_data_five_routes_value/
124.
Bradsher
,
K.
, and
Mozur
,
P.
,
2014
,
Sealed Tight
,
The New York Times
,
New York
.
125.
Rajpurohit
,
A.
,
2014
, “
INFORMS The Business of Big Data 2014: Day 1 Highlights
,” Accessed Sept. 25, 2014, http://www.kdnuggets.com/2014/08/informs-business-big-data-2014-day1.html
126.
Ransbotham
,
S.
,
2014
, “
Data Analytics Makes the Transition From Novelty to Commodity
,” Big Idea: Data & Analytics, Blog, Accessed Aug. 25, 2014, http://sloanreview.mit.edu/article/data-analytics-makes-the-transition-from-novelty-to-commodity/
127.
Lipton
,
R. J.
,
2014
, “
Shifts in Algorithm Design
,” Gödel’s Lost Letter and P=NP, Blog, Accessed Oct. 3, 2014, http://rjlipton.wordpress.com/2014/07/21/shifts-in-algorithm-design/
128.
Borgs
,
C.
,
Brautbar
,
M.
,
Chayes
,
J.
, and
Teng
,
S.-H.
,
2014
, “
Multiscale Matrix Sampling and Sublinear-Time PageRank Computation
,”
Internet Math.
,
10
(
1–2
), pp.
20
–
48
.10.1080/15427951.2013.802752
Google Scholar
Crossref
Search ADS
 
129.
Svensson
,
M.
,
2009
, “
Contextual Metadata in Practice
,”
First International Conference on Advances in Multimedia 2009
, Colmar, July 20–25, pp.
12
–
17
.10.1109/MMEDIA.2009.10
130.
Dumbill
,
E.
,
2013
, “
Big Data Variety Means That Metadata Matters
,” Data Driven, Blog, Accessed Mar. 21, 2015, http://www.forbes.com/sites/edddumbill/2013/12/31/big-data-variety-means-that-metadata-matters/
131.
Patil
,
D. J.
,
2011
,
Building Data Science Teams: The Skills, Tools, and Perspectives Behind Great Data Science Groups
,
O’Reilly Media
,
Sebastopol, CA
.
132.
Harris
,
H. D.
,
Murphy
,
S. P.
, and
Vaisman
,
M.
,
2013
,
Analyzing the Analyzers: An Introspective Survey of Data Scientists and Their Work
,
O'Reilly Media
,
Sebastopol, CA
.
133.
Patil
,
D. J.
, and
Mason
,
H.
,
2015
,
Data Driven—Creating a Data Culture
,
O'Reilly Media
,
Sebastopol, CA
.
134.
Schönsleben
,
P.
, Radke, A. M., Plehn, J., Finke, G., and Hertz, P.,
2014
, “
Towards the Integrated Determination of a Strategic Production Concept, Distribution Concept, Service Concept, and Transport Concept for Manufacturers of Physical Products—A Generic Approach
,” E-Collection ETH Zurich, Accessed Mar. 21, 2015, http://e-collection.library.ethz.ch/eserv/eth:47687/eth-47687-01.pdf
Copyright © 2015 by ASME
You do not currently have access to this content.