Commercialization Options for a set of Wireless Patents

CCOOMMMMEERRCCIIAALLIIZZAATTIIOONN OOPPTTIIOONNSS FFOORR AA SSEETT OOFF
WWIIRREELLEESSSS PPAATTEENNTTSS
Department of Management Studies, IISc
Shanmukha Sreenivas P , M.MGT II Year
Project Advisor : Prof. Mary Mathew
Industry Supervisor: Mr. Mihir Mahajan

CCoonntteennttss
Problem Statement
Objectives
Literature Review
Methodology
Results
Conclusions
Bibliography
2

PPrroobblleemm SSttaatteemmeenntt
To compare a given set of patents to class similar
benchmark patents of the world and suggest
commercialization options for a selected set of
patents.
3

4
OObbjjeeccttiivveess
1) To compare the given set of wireless patents with the
identified sample of wireless world patents.
2) To identify a benchmark sample of wireless patents in
the world, given the patent classes of the given set of
wireless patents.
3) To evolve an elimination model to select a sample of
patents with higher commercial potential.
4) Suggest commercialization options for the selected
set of patents.

LLiitteerraattuurree RReevviieeww
5
Variable Insights Author
No of US classes Breadth, Extent of core technology diffusion Shapiro (2003)
No of IPC classes Breadth, Extent of core technology diffusion Shapiro (2003)
No of Inventors
Degree of inventor collaboration, Opposition
Survivability
Reitzig (2003), Gibbs
(2008)
No of family members Patent value and Market size Gambardella et al. (2008)
Patent Grant Lag Degree of Technology Complexity, Patent Value Popp (2003), Retzig (2003)
Age Probability of Patent trade, Patent Value Serrano (2008)
Backward citations count Quantitative indicator of prior art, Market size
Reitzig (2003), Lemley
(2013)
Forward citations count Patent Value, Probability of patent trade Serrano (2008)
No of claims Patent Value Ughetto (2011)
No of words in first claim Scope of Claim, Patent Quality Osenga (2012)
No of elements in first
claim Scope of Claim, Patent Quality Osenga (2012)

7
Set of 175 Wireless
communication patents
Demographic analysis
Patent Bucketing exercise
(3 methods)
Three search techniques
for potential licensees
World benchmark patents
obtained for each bucket.
(n5 = 135)
Selected set
of patents
(n4 = 135)
Demographic comparison of
benchmark and given set of
patents
Discriminant analysis to identify
patents similar to benchmark
Commercialization strategy
Shortlist of frequently
appearing companies
Sampling of world
patents from above
companies
(n2 = 252);(n3 = 252)
Cont…
25 Buckets
Patents of high potential
List of potential licensees
for each Bucket

8
Given set of patents
Cont…
Sample of world patents
from above
(n2 = 252);(n3= 252) (n1 = 175)
Comparison of 2 random samples
& given set of patents

DDaattaa SSeettss
Given Set of Patents (n1= 175)
Two samples of patents from short listed
companies of random world sample (n2= 252,
n3= 252)
Patents from the given set considered after
bucketing (n4= 135)
World benchmark patents obtained for each
bucket (n5= 135)
 Ocean Tomo auctioned patents (n6= 10)
Extracted from – Innography(2013) ; Relecura(2013) )

11..11 PPaatteenntt DDeemmooggrraapphhiicc AAnnaallyyssiiss
USP class wise analysis of given data set
Status of the applications (awarded v/s filed)
Patents by inventor type ( academic v/s non-academic)
Patent class by key inventors
Analysis of families
Descriptive statistics on :
Patent lag and Age
Number of Citations – forward and backward
Number of Foreign Filings
Number of Inventors
Number of words and elements in the first claim

11..22 PPaatteenntt BBuucckkeettiinngg EExxeerrcciissee
Identified 5 broad categories.
The above 5 categories further into 25 buckets.
11

11..33 SSeeaarrcchh tteecchhnniiqquueess eemmppllooyyeedd oonn
bbuucckkeettss
Search Techniques:
IPC classification based search
Forward and Backward citations based search (Two - level)
Keyword based search
Outcome:
List of potential licensees for each bucket
Shortlist of frequently appearing companies (14)
12

22..11 MMooddeell ttoo sshhoorrttlliisstt ppaatteennttss wwiitthh
ccoommmmeerrcciiaall ppootteennttiiaall -- LLDDAA
Classification method
D= v1X1+v2X2+v3X3+v4X4+…+c
D= Discriminate function
v=Discriminant coefficient or weight for that variable
X=Variable considered
c=Constant
Patents of the given set (n4) having a greater extent of
similarity with the benchmark patents (n5) are considered
for further analysis.
13

22..22 PPoossiittiioonniinngg ooff sshhoorrttlliisstteedd ppaatteennttss
oonn IInnnnoovvaattiioonn cchhaaiinn && WWiirreelleessss cchhaaiinn
Concept / Device based
Basic R&D / Applied R&D / NPD
Academic / Industry based inventors
Device value chain
Network value chain
Infrastructure value chain
Application value chain
Content value chain
14
}Wireless Value Chain

DDeemmooggrraapphhiicc AAnnaallyyssiiss ooff GGiivveenn SSeett ((nn11 ==117755))
16

DDeemmooggrraapphhiicc AAnnaallyyssiiss……11
17
No. of patents/patent applications filed in each USP class
Patent filings w.r.t Filing Year and Publication Year
Based on data extracted from Innography

DDeemmooggrraapphhiicc AAnnaallyyssiiss……22
Jurisdictional Spread and Family analysis
18
Publication_Country
No of
Applications
CA 1
CN 35
DE 7
EP 6
JP 33
KR 23
US 175
WO 89
Total 369
No. of Filings No. of applications
1 68
2 61
3 19
4 16
5 10
8 1
Total 175
Based on data extracted from Innography
Few country filings are not included in Innography

PPaatteenntt bbuucckkeettss iiddeennttiiffiieedd ::
19
Category-Buckets No. of patents
Telecommunications Software 34
Digital Image Processing 5
Quality of Service 7
Security 13
Data Management 5
Other 4
Communication 60
Massive MIMO 16
Modulation 2
Space Time Coding 7
Energy Optimization & Error
9
detection
Cognitive Radios 8
Multi hop Communication 4
Other 14
Networking 64
Location Discovery 7
Node authentication 7
Internetwork Load balancing 3
Quality of Experience
4
determination
Device handoff 3
Scheduling in adhoc networks 5
Optical Networks 5
Packet Management 9
Sensor Management 4
Resource – Network Management 8
Other 9
Hardware-Medical Devices 7
OTHER 10

o Search techniques applied onn bbuucckkeettss iiddeennttiiffiieedd……11
20
Ex: Massive MIMO
IPC Classification based search
Forward & Backward citations based
search Keyword based search
Airgo Networks Inc. Alcatel-lucent Alcatel-lucent
Atheros Communications, Inc. Deere & Company Broadcom Corporation
Broadcom Corporation Ems Technologies, Inc.
Electronics And Telecommunications Research
Institute
Electronics And Telecommunications Research
Institute Fujitsu Limited Fujitsu Limited
Fujitsu Limited General Telecommunications Institute Huawei Technologies Co., Ltd.
Hitachi, Ltd. Google Inc. Intel Corporation
Intel Corporation Htc Corporation Interdigital, Inc.
Interdigital, Inc. Ikanos Communications, Inc. Koninklijke Philips Electronics Nv
Lg Corp. Intel Corporation Lg Corp.
Marvell Technology Group Ltd. Kathrein-werke Kg Mimos, Berhad
Nippon Telegraph & Telephone Corp. Microsoft Corporation Nec Corporation
Panasonic Corporation Motorola Solutions Inc Nippon Telegraph & Telephone Corp.
Qualcomm, Inc. Nokia Corporation Nokia Corporation
Sony Corporation Qualcomm, Inc. Panasonic Corporation
Sharp Corporation Rockwell Collins, Inc. Qualcomm, Inc.
Samsung Electronics Co., Ltd. Samsung Electronics Co., Ltd. Samsung Electronics Co., Ltd.
Telefonaktiebolaget Lm Ericsson Toshiba Corporation Sony Corporation
Toshiba Corporation Unwired Planet Inc Telefonaktiebolaget Lm Ericsson
Wionics Res Xr Communications, Llc Zte Corporation

o Search techniques applied onn bbuucckkeettss iiddeennttiiffiieedd……22
Potential licensees for the portfolio
21
Potential licensees - Massive MIMO
Airgo Networks Inc.
Atheros Communications, Inc.
Deere & Company
Ems Technologies, Inc.
Ikanos Communications, Inc.
Kathrein-werke Kg
Marvell Technology Group Ltd.
Mimos, Berhad
Rockwell Collins, Inc.
Unwired Planet Inc
Wionics Res
Xr Communications, Llc
Apple
Broadcom
Cisco Systems
Fujitsu Limited
Huawei
Koninklijke Philips Electronics
LG Electronics
Motorola Mobility (acquired by
Google)
NEC corporation
Nokia corporation
Qualcomm
Research in Motion (Blackberry)
Samsung Electronics
ZTE corporation

Patent Demographic ccoommppaarriissoonnss --
nn11 ((GGiivveenn SSeett)) vv//ss nn22 && nn33 ((WWoorrlldd SSaammpplleess))
22

PPaatteenntt DDeemmooggrraapphhiiccss nn11 vv//ss nn22 && nn33
23
Mean of Given
Set(1)
Mean of World
Set-I(2)
Mean of World Set-
II(3) F statistic
t12
statistic
t13
statistic
t23
statistic
No of IPC
classes 1.57 3.29 2.98 21.934** -6.54** -6.25** 1.14
No of
Inventors 1.67 2.88 2.79 32.75** -7.95** -7.68** 0.558
No of family
members 1.96 5.52988 4.438247 53.29** 10.343** -8.872** 1.553
Patent Grant
Lag 1128.46 1507.12 1582.15 10.58** 3.872** -5.122** -0.95
Backward
Citations
Count
6.31 29.27 20.75 29.889** -7.81** -6.085** 2.744*
Forward
Citations
Count
0.57 2.69 3.02 17.551** -5.377** -6.266** -0.71
No of words
in first claim 209.5 158.5 171.89 7.27** 3.6223* 2.49* -1.566
No of claims 22.01 22.12 21.33 0.269 -0.09 0.59 0.615
No of
elements in
first claim
4.3571 4.4936 4.6107 0.23 0.387 0.626 0.402
No of US
classes 2.53 2.92 3.04 2.167 -1.62 -1.962 -0.493
Significance level: * for 0.05, ** for 0.01

Discrimination of given set ( nn44) and world
benchmark (nn55) to identify commercially
potential patents in the given set

DDaattaa iinnppuutt ttoo tthhee LLDDAA mmooddeell
25
from given set
No. of world
benchmark
patents
considered
Telecommunications Software 30 30
Digital Image Processing 5 5
Quality of Service 7 7
Security 13 13
Data Management 5 5
Similarly, we extracted data for all the remaining buckets

VVaarriiaabblleess cchhoosseenn ffoorr aannaallyyssiiss -- LLDDAA
26
Forward Citations
Count
V01
Backward Citations
Count
V02
No of US classes V03
No of IPC classes V04
No of Inventors V05
No of family members V06
Patent Grant Lag V07
No of claims V08
Strength V09
Age V10
No of words in first
V11
claim
No of elements in first
claim
V12
{1, if patent belongs to given set
0, if patent belongs to benchmark set
The class variable =

Comparison ooff mmeeaannss bbeettwweeeenn tthhee ttwwoo ggrroouuppss
27
Mean of Given
Set(1)
Mean of Benchmark
Set(2)
t12 statistic
Forward Citations
Count 0.6 5.8 -10.79**
Backward Citations
Count 5.95 19.26 4.59**
No of IPC classes 1.52 1.94 -2.98*
No of Inventors 1.64 3.23 -8.12**
No of family members 1.61 2.93 6.086**
Patent Grant Lag 708.86 848.32 -2.602*
No of claims 22.33 32.83 6.733**
Strength 31.07 75.07 -19.31**
Age 1307.28 1736.07 7.822**
No of words in first
claim 142.25 139.58 0.247
No of elements in
first claim 4.14 4.17 0.119
No of US classes 2.3 2.73 -1.33
Significance level: * for 0.05, ** for 0.01

BBooxx PPlloott ooff tthhee ssttrreennggtthh vvaarriiaabbllee
High Strength
-Given set patents
Low Strength
benchmark patents
Box Plot of the Strength variable for the two sets 28

29
LLiinneeaarr DDiissccrriimmiinnaanntt AAnnaallyyssiiss
1. Classification Results without strength variable
2. Classification Results with outliers
removed without strength variable
Membership misfit of benchmark patents = 28.1 % Membership misfit of benchmark patents = 25.5 %

30
LLDDAA ffuunnccttiioonn
3. Classification Results with strength variable
Is_given_set
Predicted
Group
Membership
0 1 Total
Cross-validated
Results
Count 0 111 24 135
1 10 125 135
% 0 82.4 17.6 100.0
1 7.4 92.6 100.0
Membership misfit of benchmark patents = 17.6 %
87.5% (236/270) of cross validated grouped
cases are correctly classified

GGooooddnneessss ooff ffiitt ooff tthhee mmooddeell
31
Function Eigenvalue
% of
Variance
Cumulative
%
Canonical
Correlation
1 1.606 100.0 100.0 .785
Test of
Function(s)
Wilks'
Lambda Chi-square df Sig.
1 .384 253.302 9 .000
62 % of the variability is
explained
Model is significant
Fairly good
discrimination is
achieved between
the two groups

SShhoorrttlliisstteedd PPaatteennttss
S.No Publication No
Forward
Citations
Count
Backward
Citations
Count
No of
US
classes
No of
IPC
classes
No of
Inventors
No of
family
members
Patent
Grant
Lag
No of
claims
Patent
Granted Strength Age Bucket
P1 US8266256 6 19 7 1 1 4 1148 10 1 85 1403
Sensor
mngmnt
P2 US20100217345 4 0 2 2 2 2 547 20 0 55 1547 Health
P3 US20100226491 3 5 3 3 2 1 549 20 0 55 1535 Health
P4 US20100271994 3 5 1 1 1 0 552 20 0 55 1489 node auth
P5 US20120014424 2 3 1 1 2 0 553 33 0 65 1042 MIMO
P6 US20110003612 1 13 1 1 2 0 553 33 0 55 1420 node auth
P7 US20120068845 1 0 1 1 1 1 566 29 0 65 992 QoS
P8 US8126486 0 26 10 8 2 1 1278 18 1 55 1727 MIMO
P9 US8327367 0 39 9 5 3 3 1370 12 1 55 1539
Sensor
mngmnt
P10 US8193941 0 26 5 2 2 2 1126 28 1 65 1477 Health
The last three patents are the additional ones that are obtained using model 3 32

CCoommppaarraattiivvee AAnnaallyyssiiss wwiitthh ssoolldd
ppaatteennttss
Shortlisted patents of given set – 10
Ocean Tomo Auctioned Patents – 10
Sample of benchmark patents – 10
Sample of patents from given set – 10
33

34
CCoommppaarraattiivvee AAnnaallyyssiiss
(days)

35
SSuuggggeesstteedd ppoossiittiioonniinngg iinn ––
WWiirreelleessss VVaalluuee CChhaaiinn
ffoorr tthhee sshhoorrttlliisstteedd ppaatteennttss
ooff ggiivveenn sseett
P9P9
P8P8
P1P1 P2P2
P3P3
P9P9
P4P4
P5P5
P7P7
P6P6 P7P7
P8P8
P1P010
Source : “Value network dynamics in 3G–4G wireless communications: A systems thinking approach to strategic value assessment” Pagani, 2008

SSuuggggeesstteedd ppoossiittiioonniinngg iinn ––
IInnnnoovvaattiioonn VVaalluuee CChhaaiinn ffoorr tthhee sshhoorrttlliisstteedd ppaatteennttss ooff ggiivveenn sseett
P3P3 P2P2
P4P4 P5P5 P6P6 P7 P7
P8P8 P9P9
P1P010
P1P1
36 Source : Innovation Value Chain , Hansen (2007)

f Rationale foorr ccoommmmeerrcciiaalliizzaattiioonn
ooppttiioonnss
Commercialization options available are :
 New product development investments:
Valid if the patent is a concept suitable to enter the device development
stage.
 License the patent/s : Valid if a potential licensee keen to work further
on the patent and based on a mutually agreed royalty model.
 Sell out of the patent/s: Selling a patent may not be substantial unless the
product has been on the market for a long time. The patent buyer
usually won't want to spend a lot for an unproven product that might not
generate a big profits.
 Initiate a startup: Valid if the patent is at that stage where it can be
manifested into a service or product for a customer and revenues are in
sight within 6 months. It should also have a willing entrepreneur keen to
take it out.
 Cross Licensing: Usually, this type of agreement happens between two
parties in order to avoid litigation or to settle an infringement
dispute. Very often, the patents that each party owns covers different
essential aspects of a given commercial product.
Source: Shapiro, Carl, “Navigating the Patent Thicket: Cross Licenses, Patent Pools, and Standard Setting )”,2010 37



c Suggested coommmmeerrcciiaalliizzaattiioonn ooppttiioonnss ffoorr
tthhee sshhoorrttlliisstteedd PPaatteennttss//PPaatteenntt AApppplliiccaattiioonnss
38
Publication No
Patent
Granted
Device
based
Concept
based
Academic
Inventor
Industrial
Inventor
Suggested
positioning in -
Wireless Value
Chain
Suggested
positioning in -
Innovation Value
Chain
Suggested
– Bucket
Suggested -
Commercialization
Route
US8266256 • • • Infrastructure Applied R&D
Sensor
mgmt Technology Licensing
US20100217345 • • Infrastructure
Development &
Design Health NPD
US20100226491 • • Device
Development &
Design Health NPD
US20100271994 • • Infrastructure Applied R&D Node Auth Technology Licensing
US20120014424 • • Infrastructure Applied R&D MIMO Technology Licensing
US20110003612 • • Infrastructure Applied R&D Node Auth Technology Licensing
US20120068845 • •
Network &
Infrastructure
Development &
Design QoS NPD
US8126486 • • • Infrastructure Applied R&D MIMO Technology Licensing
US8327367 • • •
Network &
Infrastructure Applied R&D
Sensor
mgmt Technology Licensing
US8193941 • • • Infrastructure
Development &
Design Health NPD
Snoring Treatment

CCoonncclluussiioonnss
Objectives
1) To compare the given set of wireless
patents with the identified sample of
world wireless patents.
2) To identify a benchmark sample of
wireless patents in the world, given
the patent classes of the given set of
wireless patents.
3) To evolve an elimination model to
select a sample of patents with higher
commercial potential.
4) Suggest commercialization options
for the selected set of patents.
Results
1) Analyzed the gap between the given set of
wireless patents with the identified sample
of world wireless patents based on Patent
Latent Variables.
2) Identified benchmark patents of 14
companies shortlisted on applying search
techniques on the buckets identified.
3) Used Linear Discriminant Analysis to
identify the patents with higher commercial
potential.
4) Positioned the shortlisted patents on the
Wireless Value Chain and on the Innovation
Value Chain and suggested
commercialization options.
39

41
BBiibblliiooggrraapphhyy……1
 Aronoff, R. (2013). Use it or lose it: monetize patents while others still need them. Intellectual Asset
Management2, 57, 39–45.
 Bekkers, R., & Nuvolari, A. (2011) .Economics of information systems and policies, 1001–1015.
 Berkowitz, L. (1993). Getting the most from your patents. Research Technology Management, Volume 32, Issue 2,
pp. 26.
 Bessen, J. (2008). The value of U.S. patents by owner and patent characteristics. Research Policy, 37(5), 932–945.
doi:10.1016/j.respol.2008.02.005
 Bessen, J., & Maskin, E. (2009). Sequential innovation, patents and imitation , 40(4), 611–635.
 Bilir, L. K. (2011). Patent Laws , Product Lifecycle Lengths , and the Global Sourcing Decisions of U.S.
Multinationals.
 Calderini, M., Caviggioli, F., Franzoni, C., & Ughetto, E. (2011). Study on the quality of the patent system in
Europe Tender MARKT / 2009 / 11 / D Contract Notice in the Official Journal of the European March 2011
Disclaims :, (March), 1–194.
 Chesbrough, H. (2006). Open Innovation : A New Paradigm for Understanding Industrial Innovation.
 Cohen, W. M., Goto, A., Nagata, A., Nelson, R. R., & Walsh, J. P. (2002).R & D spillovers, patents and the
incentives to innovate in Japan and the United States, 31, 1349–1367.
 Cotropia, C. A., Lemley, M., & Neukom, W. H. (2012). Do Applicant Patent citations matter? , 600 W 168, 1–
44.
 CTIA. (2012) Wireless & Wireline Industry Comparison Report Mid-Year 2012.
http://files.ctia.org/pdf/CTIA_Survey_MY_2012_Graphics-_final.pdf
 Dahlman, E., Furuskär, A., Jading, Y., Lindström, M., & Parkvall, S. (2008). Key features of the LTE radio
interface, 77–80.
 Ewing, T., & Feldman, R. (2012). The Giants Among Us. Stanford Technology Law Review, (expected).
 Wanetick, D. (2012). Strategies for Negotiating Licenses, 1–16.
 Wirtz, B. W. (2001). Reconfiguration of Value Chains in Converging Media and Communications Markets, 34,
489–506.

42
 Gambardella, A., Harhoff, D., & Verspagen, B. (2008). The value of European patents, (2006), 69–84.
 Gans, J. S., & Stern, S. (2003). The product market and the market for “ideas”: commercialization strategies for
technology entrepreneurs, 32, 333–350.
 Gassmann, O., & Zedtwitz, M. Von. (1999). New concepts and trends in international R & D organizations.
 Gibbs, A. (2008). Explanation of PatentCafe ® Patent Factor Index TM Reports ( PFI ) The Practical Application of
Statistical Quality Scoring to Effective Patent Management PATENT QUALITY IMPACT FOLLOWING KSR V .
 Hall, B. H., Jaffe, A., & Trajtenberg, M. (2005). Market value and patent citations, 1–50.
 Harhoff, D., Scherer, F. M., & Vopel, K. (2003). Citations, family size, opposition and the value of patent rights.
Research Policy, 32(8), 1343–1363. doi:10.1016/S0048-7333(02)00124-5
 Hoydis, J. (2011). Massive MIMO : How many antennas do we need ?
 http://www.innography.com. Innography- Intellectual Property Business Intelligence Solution. Accessed on
January 10, 2013.
 http://www.relecura.com. Reclecura- Patent and Portfolio Analysis Platform. Accessed on April 30, 2013.
 http://www.uspto.gov. United States Patent and Trademark Office. Accessed on January 10, 2013.
 IBM Corp. 2011. IBM SPSS Statistics for Windows .(Version 20.0.) [Software] Armonk, NY: IBM Corp.
 Kayal, a. a., & Waters, R. C. (1999). An empirical evaluation of the technology cycle time indicator as a measure
of the pace of technological progress in superconductor technology. IEEE Transactions on Engineering
Management, 46(2), 127–131. doi:10.1109/17.759138
 Li, F., & Whalley, J. (2002). Deconstruction of the telecommunications industry : From value chains to value
networks, 26, 451–472.
 Maitland, C. F., Bauer, J. M., & Westerveld, R. (2002). The European market for mobile data : evolving value
chains and industry structures, 26, 485–504.
 Misek, P. (2011). Research in Motion (RIMM) (pp. 1–12). Retrieved from
http://ipcloseup.files.wordpress.com/2011/10/rimm.pdf
 Olla, P., & Patel, N. V. (2002). A value chain model for mobile data service providers, 26, 551–571.
 Osenga, K. (2012). The Shape of Things to Come : What We Can Learn From Patent Claim Length, 28(3).

43
 Pagani, M., & Fine, C. H. (2008). Value network dynamics in 3G–4G wireless communications: A systems
thinking approach to strategic value assessment. Journal of Business Research, 61(11), 1102–1112.
doi:10.1016/j.jbusres.2007.11.004
 Peppard, J., & Rylander, A. (2006). From Value Chain to Value Network: European Management Journal, 24(2-
3), 128–141. doi:10.1016/j.emj.2006.03.003
 Pham, A. (2011). Strategic Portfolio-based patent investment and management. Intellectual Asset Management,
45.
 R Development Core Team. 2013 R: A language and environment for statistical computing. (Version 3.0.1)
[Software] R Foundation for Statistical Computing, Vienna, Austria. Available from http://www.R-project.org.
 Reitzig, M. (2004). Improving patent valuations for management purposes—validating new indicators by
analyzing application rationales. Research Policy, 33(6-7), 939–957. doi:10.1016/j.respol.2004.02.004
 Sabat, H. K. (2002). The evolving mobile wireless value chain and market structure, 26, 505–535.
 Schankerman, M. (1985). “Estimates of the value of patent rights in European countries during the Post – 1950
period”. Economic Journal. Vol.97 . pp.1-25.
 Serrano, C. J., Holmes, T., Kortum, S., Aguirregabiria, V., Eckstein, Z., Ge, S., Leon, F. G. De, et al. (2013).
Estimating the Gains from Trade in the Market for Patent Rights This draft : January , 2013, 25–27.
 Shadunsky, A. (2012). Nokia Patent Portfolio Valuation. Retrieved February 4, 2013, from
http://seekingalpha.com/article/688381-nokia-patent-portfolio-valuation-range-too-great-to-make-nokia-a-compelling-
buy
 Shapiro, C. (2001). Antitrust Limits to Patent Settlements, (1998), 1–42.
 Somaya, D., Teece, D., & Wakeman, S. (2011). Innovation in Multi-Invention Contexts:, 53(4), 47–79.
 Sreekumaran, S., Mathew, M., & Nag, D. (2011). Technovation Dynamics between patent latent variables and
patent price. Technovation, 31(12), 648–654. doi:10.1016/j.technovation.2011.07.002
 Straathof, B., & Veldhuizen, S. Van. (2010). Market size, institutions, and the value of rights provided by patents.
 Talluri, S., Baker, R. C., & Sarkis, J. (1999). A framework for designing efficient value chain networks, 62.
 USPTO. 2012 U.S. Patent Statistics Report 2012. http://www.uspto.gov/web/offices/ac/ido/oeip/taf/us_stat.pdf

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