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Archive for the ‘IP Valuation Models – Pricing Intangible Assets’ Category


The Digital Age Gave Rise to New Definitions – New Benchmarks were born on the World Wide Web for the Intangible Asset of Firm’s Reputation: Pay a Premium for buying e-Reputation

Curator: Aviva Lev–Ari, PhD, RN

 

Direct reputation, feedback reputation and signaling effects are present; and shows that better sellers are always more likely to brand stretch. The comparative statics with respect to the initial reputation level, however, are not obvious. … a higher reputation firm can earn a higher direct reputation effect premium. But a higher reputation firm also has more to lose. The trade-off between using one’s reputation and protecting it can go both ways.

Luıs M B Cabral, New York University and CEPR, 2005

 

 

Part 1:   A Digital Business Defined and the Intangible Asset of Firm’s Reputation

  1.  Claiming Distinction
  2.  Recognition Bestowed
  3.  The Technology
  4.  The Sphere of Influence
  5.  The Industrial Benefactors in Potential
  6.  The Actors at Play – Experts, Authors, Writers – Life Sciences & Medicine as it applies to HEALTH CARE
  7.  1st Level Connection on LinkedIn = +7,100 and Endorsements = +1,500
  8.  The DIGITAL REPUTATION of our Venture – Twitter for the Professional and for Institutions
  9.  Growth in Twitter Followers and in Global Reach: Who are the NEW Followers? they are OUR COMPETITION   and   other Media Establishments – that is the definition of Trend Setter, Opinion Leader and Source for Emulation
  10.  Business Aspects of the Brick & Mortar World render OBSOLETE

Part 2:   Business Perspectives on Reputation

Part 3:   Economics Perspectives on Reputation

 

 

Part 1:   A Digital Business Defined and the Intangible Asset of Firm’s Reputation

This curation attempts to teach-by-example the new reality of the Intangible Asset of Firm’s Reputation when the business is 100% in the cloud, 100% electronic in nature (paperless), the customers are the Global Universe and the organization is 100% Global and 100% virtual.

 

A Case in Point: Intellectual Property Production Process of Health Care Digital Content using electronic Media Channels

 

Optimal Testimonial of e-Product Quality and Reputation for an Open Access Online Scientific Journal pharmaceuticalintelligence.com 

 

 1.   Claiming Distinction

Executive Summary

WHAT ARE LPBI Group’s NEEDS in June 2019: Aviva’s BOLD VISION on June 11, 2019

 

2.   Recognition Bestowed 

Our Books are here

  • On 8/17/2018, Dr. Lev-Ari, PhD, RN was contacted by the President elect of the Massachusetts Academy of Sciences (MAS), Prof. Katya Ravid of Boston University, School of Medicine, to join MAS in the role of Liaison to the Biotechnology and eScientific Publishing industries for the term of August 2018-July 2021. In the MAS, Dr. Lev-Ari serve as Board member, Fellow, and Advisor to the Governing Board.

http://www.maacadsci.org

MAS FELLOWS 

GOVERNING BOARD

ACTIVITIES

BUNDLED BY AMAZON.COM INTO A SIX-VOLUME SERIES FOR $515

https://lnkd.in/e6WkMgF

Sixteen Volumes ARE ON AMAZON.COM, average book length – 2,400 pages

https://lnkd.in/ekWGNqA

3.   The Technology

Curation Methodology – Digital Communication Technology to mitigate Published Information Explosion and Obsolescence in Medicine and Life Sciences

Detailed Technology Description

LPBI’s Pipeline Map: A Positioning Perspectives – An Outlook to the Future from the Present

 

4.   The Sphere of Influence 

LPBI Group’s Social Media Presence

JOURNAL Statistics on 2/24/2019

  • LPBI Platform is been used by GLOBAL Communities of Scientists for interactive dialogue of SCIENCE – Four case studies are presented in the link, below

Electronic Scientific AGORA: Comment Exchanges by Global Scientists on Articles published in the Open Access Journal @pharmaceuticalintelligence.com – Four Case Studies

Curator and Editor-in-Chief: Journal and BioMed e-Series, Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2018/04/10/electronic-scientific-agora-comment-exchanges-by-global-scientists-on-articles-published-in-the-open-access-journal-pharmaceuticalintelligence-com-four-case-studies/

 

5.   The Industrial Benefactors in Potential

Opportunities Map in the Acquisition Arena

Dynamic Contents for LPBI Group’s PowerPoint Presentation

Potential Use of LPBI IP as Value Price Driver by Potential Acquirer: Assumptions per Asset Class 

 

6.   The Actors at Play – Experts, Authors, Writers – Life Sciences & Medicine as it applies to HEALTH CARE

Founder’s Role in the Development of Venture’s Factors of Content Production – Biographical Notes by Aviva Lev-Ari, PhD, RN, LPBI Group

Top Authors by Number of eReaders Views

Top Articles by Number of e-Readers for All Days ending 2019-02-17

FIT Members Contribute to Opportunities Map

FINAL IMPROVEMENT TEAM (FIT): Definition of Active, Lapsing of Active Status, COMPs Formulas

FIT members – Who works on WHAT?

Summer 2019 Plan – Research Associates Tasks

 

7.   1st Level Connection on LinkedIn = +7,100 and Endorsements = +1,500

Connections First Level on LinkedIn: 500 CEOs, 200 Big Pharma Professionals, 7,000 in Total: LPBI Group Founder – Aviva Lev-Ari, PhD, RN

 

8.   The DIGITAL REPUTATION of our Venture – Twitter for the Professional and for Institutions

Mostly HONORED to be followed by [from an Excerpt of 117 Followers of the Twitter Account @AVIVA1950 from the List of 359 Followers] by the Number of their Followers on 2/24/2019

LPBI Group is mostly HONORED to be followed by [from an Excerpt of 136 Followers of the Twitter Account @pharma_BI from the List of 505 Followers] by the Number of their Followers on 3/20/2019

Excerpt of 136 Followers of @pharma_BI (from the List of 505 Followers) by the Number of their Followers on 3/20/2019

Excerpt of 117 Followers of @AVIVA1950 (from the List of 359 Followers) by the Number of their Followers

REACH – Two Handles on Twitter.com @AVIVA1950 @pharma_BI

9.   Growth in Twitter Followers and in Global Reach: Who are the NEW Followers: OUR COMPETITION and other Media Establishments – that is the definition of Trend Setter, Opinion Leader and Source for Emulation

@4openjournalFollows you

Follow

4open is a multi- & inter-disciplinary, online, peer-reviewed, open access journal publishing across a broad range of subjects in the STEM domain.

@roll_clausFollows you

Follow

Publishing Editor at 

@EDPSciences

@PubtextoPFollows you

Following

Pubtexto is an International online publishing organization that publishes Scientific literature through its different open access Journals.

@alexanderlabrieFollows you

Following

CEO 

@sphereinc

@BjoernBruecherFollows you

Following

THEODOR-BILLROTH-ACADEMY® 

(link: http://linkedin.com/in/bruecher)

linkedin.com/in/bruecher // 

(link: http://4open-sciences.org)

4open-sciences.org – Editor-in-Chief // Science Profile – 

(link: http://researchgate.net/profile/Bjoern)

researchgate.net/profile/Bjoern

@MPDexpertFollows you

Follow

translate research into life-changing Global manufactured Medical Products – drugs, devices, biotech, combination; anything requiring FDA approval#MedProdDev

@P_A_MORGONFollows you

Following

Life science expert & investor_travel, wine & golf amateur_Proud father of 2 girls_My Tweets are only mine 

@INmuneBioFollows you

Follow

INmune Bio, Inc. is developing therapies that harness patient’s #immunesystem to treat #cancer. Our focus is on #NKcells and #myeloid derived suppressor cells.

@sallyeavesFollows you

Following

Innovating #tech #education #business CEO CTO Advisor & Prof. #blockchain #AI 

@OxfordSBS

@Forbes

 #FinTech #speaker #SDGs #STEM #techforgood #sustainability

@sciencetracker2Follows you

You will hear more recent and cool scientific news here. Besides, some health and tech news. Follow us in

(link: http://facebook.com/sciencetracker2)

facebook.com/sciencetracker2

13.8K Following

24.6K Followers

Followed by Stanford Tweets, Biotech Week Boston, and 23 others you follow

@sgruenwaldFollows you

Following

MD, PhD, scientist, futurist, entrepreneur, managing director of 

(link: http://www.genautica.com)

genautica.com, co-founder 

(link: http://www.diagnomics.com)

diagnomics.com

(link: http://www.scoop.it/t/amazing-science)

scoop.it/t/amazing-scie…user

 

10.  Business Aspects of the Brick & Mortar World render OBSOLETE

Financial Valuation of Three Health Care Intellectual Property (IP) Content Asset Classes

Global Market Penetration Forecast for each Volume in the 16 Volume BioMed e-Series

2013-2019, On the Medical & Scientific Bookshelf in Kindle Store: eReader Behaviors: Browsing, Page Downloads and Buying e-Books – LPBI Group’s BioMed e-Series, Royalties Payment Analysis 

 

Part 2: BUSINESS PERSPECTIVES on Reputation

 

Warren Buffett on reputation: the economic value of values, integrity and corporate culture

Warren Buffett understands that reputation and integrity have economic value. Research that shows that a good reputation is worth real money — in fact, some research indicates that a good reputation might replace a line of credit at the bank. In his book Berkshire Beyond Buffett: The Enduring Value of Values, Lawrence Cunningham argues that one of Berkshire Hathaway’s greatest assets is reputation.

https://www.finn.agency/fr/warren-buffett-reputation-berkshire-hathaway

 

The Value of Reputation

Thomas Pfeiffer1,2,4,*, Lily Tran5, Coco Krumme5 and David G Rand1,3,* 1 Program for Evolutionary Dynamics, FAS, 2 School of Applied Sciences and Engineering, and 3 Department of Psychology, Harvard University, Cambridge MA 02138, USA 4 New Zealand Institute for Advanced Study, Massey University, Auckland 0745, New Zealand 5 MIT Media Laboratory, Cambridge MA 02139, USA

 

Reputation plays a central role in human societies.

Empirical and theoretical work indicates that a good reputation is valuable in that it increases one’s expected payoff in the future. Here, we explore a game that couples a repeated Prisoner’s Dilemma (PD), in which participants can earn and can benefit from a good reputation, with a market in which reputation can be bought and sold. This game allows us to investigate how the trading of reputation affects cooperation in the PD, and how participants assess the value of having a good reputation. We find that depending on how the game is set up, trading can have a positive or a negative effect on the overall frequency of cooperation. Moreover, we show that the more valuable a good reputation is in the PD, the higher the price at which it is traded in the market. Our findings have important implications for the use of reputation systems in practice.

Keywords: evolution of cooperation; reciprocal altruism; indirect reciprocity; reputation

http://decisionlab.harvard.edu/_content/research/papers/Krumme_Pfieffer_Tran_and_Rand_Value_of_Reputation.pdf

 

The Impact of Reputation on Market Value by Simon Cole

One of the most familiar, but least understood, intangible assets is a firm’s reputation.

Simon Cole is the founding partner of the corporate reputation and branding consultancy Reputation Dividend (www. reputationdividend.com).

http://www.reputationdividend.com/files/4713/4822/1479/Reputation_Dividend_WEC_133_Cole.pdf

 

Part 3:   ECONOMICS PERSPECTIVES on Reputation

 

The Economics of Trust and Reputation: A Primer

Luıs M B Cabral New York University and CEPR, June 2005, lecture series at the University of Zurich

lcabral@stern.nyu.edu

https://pdfs.semanticscholar.org/24e5/2f3bd22d4bfa86902e5ae07d57039480004f.pdf

 

Notes on the literature

Important note: The notes in this section are essentially limited to the ideas discussed in the present version of these lectures notes. They cannot therefore be considered a survey of the literature. There are dozens of articles on the economics of reputation which I do not include here. In a future version of the text, I hope to provide a more complete set of notes on the literature. The notes below follow the order with which topics are presented.

Bootstrap models. The bootstrap mechanism for trust is based on a general result known as the folk theorem (known as such because of its uncertain origins). For a fairly general statement of the theorem (and its proof) see Fudenberg and Makin (1986). One of the main areas of application of the folk theorem has been the problem of (tacit or explicit) collusion in oligopoly. This is a typical problem of trust (or lack thereof): all firms would prefer prices to be high and output to be low; but each firm, individually, has an incentive to drop price and increase output. Friedman (1971) presents one of the earliest formal applications of the folk theorem to oligopoly collusion. He considers the case when firms set prices and history is perfectly observable. Both of the extensions presented in Section 2.2 were first developed with oligopoly collusion applications in mind. The case of trust with noisy signals (2.2.1) was first developed by Green and Porter (1984). A long series of papers have been written on this topic, including the influential work by Abreu, Pearce and Stacchetti (1990). Rotemberg and Saloner (1986) proposed a model of oligopoly collusion with fluctuating market demand. In this case, the intuition presented in Section 2.2.2 implies that firms collude on a lower price during periods of higher demand. This suggests that prices are counter-cyclical in markets where firms collude. Rotemberg and Saloner (1986) present supporting evidence from the cement industry. A number of papers have built on Rotemberg and Saloner’s analysis. Kandori (1992) shows that the i.i.d. assumption simplifies the analysis but is not crucial. Harrington (19??) considers a richer demand model and looks at how prices vary along the business cycle. The basic idea of repetition as a form of ensuring seller trustworthiness is developed in Klein and Leffler (1981). See also Telser (1980) and Shapiro (1983). When considering the problem of free entry, Klein and Leffler (1981) propose advertising as a solution, whereas Shapiro (1983) suggests low intro25 ductory prices. Section ?? is based on my own research notes. The general analysis of selfreinforcing agreements when there is an outside option of the kind considered here may be found in Ray (2002). Watson (1999, 2002) also considers models where the level of trust stars at a low level and gradually increases.

Bayesian models. The seminal contributions to the study of Bayesian models of reputation are Kreps and Wilson (1982) and Milgrom and Roberts (1982). The model in Section 3.2.1 includes elements from these papers as well as from Diamond (1989). H¨olmstrom (1982/1999) makes the point that separation leads to reduced incentives to invest in reputation. The issue of reputation with separation and changing types is treated in detail in the forthcoming book by Mailath and Samuelson (2006). In Section 3.3, I presented a series of models that deal with name as carriers of reputations. The part on changing names (Section 3.3.1) reflects elements from a variety of models, though, to the best of my knowledge, no study exists that models the process of secret, costless name changes in an infinite period adverse selection context. The study of markets for names follows the work by Tadelis (1999) and Mailath and Samuelson (2001). All of these papers are based on the Bayesian updating paradigm. Kreps (1990) presents an argument for trading reputations in a bootstrap type of model. The analysis of brand stretching (Section 3.3.3) is adapted from Cabral (2000). The paper considers a more general framework where the direct reputation, feedback reputation and signalling effects are present; and shows that better sellers are always more likely to brand stretch. The comparative statics with respect to the initial reputation level, however, are not obvious. As we saw above, a higher reputation firm can earn a higher direct reputation effect premium. But a higher reputation firm also has more to lose. The trade-off between using one’s reputation and protecting it can go both ways. For other papers on brand stretching and umbrella branding see Choi (1998), Anderson (2002).

Bibliography

Abreu, Dilip, David Pearce and Ennio Stacchetti (1990), “Toward a Theory of Discounted Repeated Games with Imperfect Monitoring,” Econometrica 58, 1041–1064. Andersson, Fredrik (2002), “Pooling reputations,” International Journal of Industrial Organization 20, 715–730. Bernhein, B. Douglas and Michael D. Whinston (1990), “Multimarket Contact and Collusive Behavior,” Rand Journal of Economics 21, 1–26. Cabral, Lu´ıs M B (2000), “Stretching Firm and Brand Reputation,” Rand Journal of Economics 31, 658-673. Choi, J.P. (1998), “Brand Extension and Informational Leverage,” Review of Economic Studies 65, 655–69. Diamond, Douglas W (1989), “Reputation Acquisition in Debt Markets,” Journal of Political Economy 97, 828–862. Ely, Jeffrey C., and Juuso Valim ¨ aki ¨ (2003), “Bad Reputation,” The Quarterly Journal of Economics 118, 785–814. Fishman, A., and R. Rob (2005), “Is Bigger Better? Customer Base Expansion through Word of Mouth Reputation,” forthcoming in Journal of Political Economy. Friedman, James (1971), “A Noncooperative Equilibrium for Supergames,” Review of Economic Studies 28, 1–12. Fudenberg, Drew and Eric Maskin (1986), “The Folk Theorem in Repeated Games with Discounting or with Imperfect Public Information,” Econometrica 54, 533–556. Green, Ed and Robert Porter (1984), “Noncooperative Collusion Under Imperfect Price Information,” Econometrica 52, 87–100. Holmstrom, Bengt ¨ (1999), “Managerial Incentive Problems: A Dynamic Perspective,” Review of Economic Studies 66, 169–182. (Originally (1982) in Essays in Honor of Professor Lars Wahlback.) Kandori, Michihiro (1992), “Repeated Games Played by Overlapping Generations of Players,” Review of Economic Studies 59, 81–92. Klein, B, and K Leffler (1981), “The Role of Market Forces in Assuring Contractual Performance,” Journal of Political Economy 89, 615–641. 27 Kreps, David (1990), “Corporate Culture and Economic Theory,” in J Alt and K Shepsle (Eds), Perspectives on Positive Political Economy, Cambridge: Cambridge University Press, 90–143. Kreps, David M., Paul Milgrom, John Roberts and Robert Wilson (1982), “Rational Cooperation in the Finitely Repeated Prisoners’ Dilemma,” Journal of Economic Theory 27, 245–252. Kreps, David M., and Robert Wilson (1982), “Reputation and Imperfect Information,” Journal of Economic Theory 27, 253–279. Mailath, George J, and Larry Samuelson (2001), “Who Wants a Good Reputation?,” Review of Economic Studies 68, 415–441. Mailath, George J, and Larry Samuelson (1998), “Your Reputation Is Who You’re Not, Not Who You’d Like To Be,” University of Pennsylvania and University of Wisconsin. Mailath, George J, and Larry Samuelson (2006), Repeated Games and Reputations: Long-Run Relationships, Oxford: Oxford University Press. Milgrom, Paul, and John Roberts (1982), “Predation, Reputation, and Entry Deterrence,” Journal of Economic Theory 27, 280–312. Phelan, Christopher (2001), “Public Trust and Government Betrayal,” forthcoming in Journal of Economic Theory. Ray, Debraj (2002), “The Time Structure of Self-Enforcing Agreements,” Econometrica 70, 547–582. Rotemberg, Julio, and Garth Saloner (1986), “A Supergame-Theoretic Model of Price Wars During Booms,” American Economic Review 76, 390–407. Shapiro, Carl (1983), “Premiums for High Quality Products as Rents to Reputation,” Quarterly Journal of Economics 98, 659–680. Tadelis, S. (1999), “What’s in a Name? Reputation as a Tradeable Asset,” American Economic Review 89, 548–563. Tadelis, Steven (2002), “The Market for Reputations as an Incentive Mechanism,” Journal of Political Economy 92, 854–882. Telser, L G (1980), “A Theory of Self-enforcing Agreements,” Journal of Business 53, 27–44. Tirole, Jean (1996), “A Theory of Collective Reputations (with applications to the persistence of corruption and to firm quality),” Review of Economic Studies 63, 1–22. 28 Watson, Joel (1999), “Starting Small and Renegotiation,” Journal of Economic Theory 85, 52–90. Watson, Joel (2002), “Starting Small and Commitment,” Games and Economic Behavior 38, 176–199. Wernerfelt, Birger (1988), “Umbrella Branding as a Signal of New Product Quality: An Example of Signalling by Posting a Bond,” Rand Journal of Economics 19, 458–466.

https://pdfs.semanticscholar.org/24e5/2f3bd22d4bfa86902e5ae07d57039480004f.pdf

 

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In-House Development of an intellectual property value calculator (IP-V-Cal) for Valuation of INTANGIBLE products: Intellectual property (IP) assets of Digital Printed Products (DPP) – Online Journal(s), e-Books and a Corpus of Real Time generated eProceedings of the Top Biotech Global Conferences

Author: Aviva Lev-Ari, PhD, RN

1. All the points I made, below in my e-mail 4AM on 6/28/2019, see below – to match Intangible Assets in Document #2, 4/19/2019 in Inbox of each FIT member.

(after reading Rick’s article we received a link to and after reading the link that I provided in this e-mail)

2. We Need Amnon to enter into an Excel spread sheet as Column #1 all the Contributing Factors to valuation in that 4AM e-mail

3. Columns #2,#3,#4 will be Gail, Amnon, Rick (Business Team)

4. Columns #5,#6 will be Dr. Williams, Prof. Feldman (our Board)

5. Columns #7,#8 #9,#10 will be Dr. Pearlman, Dr. Dror Nir, Dr. Saha, Dr. Irina (Scientists Team)

7. Each Column dedicated to each of out 10 alive and well Active FIT

Will be split into two columns

6. Column #11 will be Aviva’s 

8. First column of each of the 10 FIT members will be filled by each by a number between 50 to 100, representing the subjectively perceived contributing weight of the Factor mentioned in Column 1: list of factors contributing to Venture’s valuation

9. Second column of each of the 10 FIT members will list the member’s subjective perspective on Ranking the Factors in Column #1

10. To Column #1: each Business Team member (mentioned in 3, above), needs to contribute FIVE new factors taken from your discussion on Valuation add them with your initials to Column #1

11. Aviva will bring DATA from Article Scoring System already populating a database designed to quantify the 

11.1 Valuation of the Journal

11.2 Valuation of the BioMed e-Series: each book, each series, all 16 volumes

11.3 Author’s factor in pricing 11.1 and 11.2

 

12. Valuation of 70 eProceedings 

(60 by Aviva; 10 by Dr. Williams)

needs to be tied to a growth factor in LPBI Group’s INFLUENCE on Twitter

12.1 @pharma_BI

12.2 @AVIVA1950

12.3 Gail’s Twitter account

12.4 Dr. Williams’ Twitter account

12.5 Dr. Asha’s Twitter account

12.6 Dr. Irina’s Twitter account

Factors of INFLUENCE:

– Growth in #Followers on Twitter 

– Ratio #Tweets/#Likes

– Cumulative # of Followers’ Followers

13. LinkedIn

I discovered new features and I wish to conduct a Skype training session with narrow messaging to FIT members

Please contribute your thoughts, while 

 

– Amnon is building this Excel

– Irina will be designing DropBox for this Excel that TEN FIT members need to add a number 50 to 100, Ranking the relative importance of each factor for Venture Valuation

GREAT initiative by Business Team to focus on valuation, thank you.

Thank you all FIT members, get ready yo add your subjective numbers into the Valuation Excel.

Amnon, please share with me in a Skype session the draft of this Excel, before we deplore this instrument, place it in Dropbox and announce the window of one week when we collect 2×10 data points on each of the Factors in Column #1, 

Board members and Scientists: you are welcome to contribute Factors in Valuation of the Venture in Column #1, the longer this column, the greater the granularity. 

We can then focus only on factors that scored above the Mean or any cut off point we will agree upon.

Thank you all – it is exciting to get the entire Team, developing a custom tailor methodology for DIGITAL printed products, NO OFF THE SHELF MODEL WILL FIT US. 

Current valuation models that do NOT APPLY to our venture include the following:

“Book to market value” 

– we got Intangibles, Column #1

– LPBI Group’s Tangibles are royalties for books sold. 

(all data was reviewed by Dr. Williams, for Section #13 in Document #2, for the period, 4/2012 to 4/19/2019)

“VC investment dilution models” 

– we kept 100% of ownership 

– our shareholders are 12 FIT members: 

— >>>>>> 10 are active members 

– (Scientist Team: Formula in place) (Gail included)

– (Business Team: 10% of UPSIDE) (Gail included)

— >>>>>> Past commitments outstanding:

– to Dr. Larry and 

– to Adam Sonnenberg

– (Formula in place). 

– No UPSIDE, due to idle status since 2/6/2019, Exit period launch.

Thank you again.

Aviva Lev-Ari, PhD, RN

Editor-in-Chief, BioMed e-Series

http://PharmaceuticalIntelligence.com

Director & Founder

Leaders in Pharmaceutical Business Intelligence (LPBI) Group

On Jun 28, 2019, at 3:57 AM, Amnon Danzig <amnon.danzig@gmail.com> wrote:

This is a nice article that put in place Corporate Finance practices.

However, The Business Team currently is struggling in much more earlier stages of the valuation of the Group.

We have a long way to go before we are entering the valuation scene in numeric terms.

Aviva,

I must confess that in the last two weeks we (Rick, Gail and me) invested huge amount of work to disclose the real valuation of the Group.

It is a work-in-process.

Thank you for your patience.

Amnon

Amnon Danzig

Business Strategy 

https://lnkd.in/e-zTVz4

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Israel

http://pharmaceuticalintelligence.com 

e-Mailamnon.danzig@gmail.com

(M) +972-54-6998405

 www.amnondanzig.com

SkypeID: Amnon.Danzig  LinkedIn Profile Twitter Profile

On Fri, Jun 28, 2019 at 10:30 AM Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu> wrote:

What is Aviva’s take on LPBI Group Valuation?

https://bothsidesofthetable.com/do-you-really-even-need-vc-72013e985fab

  • Advantages of LPBI Group:
  1. We had low barrier to entry and 
  2. We had/have Zero labor cost
  3. We are virtual, therefore, no overhead expenses 
  4. Run rate at WordPress.com Business Premium Annual Fee $200 and LinkedIn Annual Business Premium $1000
  5. Our 1st CARDINAL factor of production [The Team] is the DEAPTH and very diverse EXPERTISE residing in the Scientist Team and in the Business TEAM
  6. Leadership expressed by new timely challenge selection – Directions into new domains
  7. Team ability to swarm around new domains (new timely challenge selection), Examples: 
  • 2015-2016 – 3D BioPrinting – Book: Series E, Volume 4
  • Volume 4: Medical 3D BioPrinting – The Revolution in Medicine, Technologies for Patient-centered Medicine: From R&D in Biologics to New Medical Devices. On Amazon.com since since 12/30/2017

https://www.amazon.com/dp/B078QVDV2W

  • 2016-2017 – Drug Discovery – JV with SBH Sciences, Dr. Raphael Nir

https://pharmaceuticalintelligence.com/drugdiscovery-lpbi-group/

  • 2019-2020 – AI + ML in Medicine – Book: Series B, Volume 2

https://pharmaceuticalintelligence.com/biomed-e-books/genomics-orientations-for-personalized-medicine/volume-two-genomics-methodologies-ngs-bioinformatics-simulations-and-the-genome-ontology/

  1. Our 2nd CARDINAL factor of Leadership is the FIDELITY of a CORE team of Scientists
  2. Aviva’s ability to multitask on several levels – FIVE persons in just One woman (nee: 1950): 
  • LPBI Group’s DAILY activity on Twitter, LinkedIn, Facebook
  • IN PERSON at +60 Conferences – yielded a Corpus of eProceedings N=70 [10 by Dr. Williams 
  • Curator of new content – Journal is LIVE at 

1,639,029 eReaders 

Content

5,642

Posts

686

Categories

10,083

Tags

  • Book Editor – multiple domains of knowledge: Series A, B, D, E
  • Full functions of Editor-in-Chief: 16 Titles, content acquisition, eTOCs designer
  • Relations builder with multiple Ecosystems: Israel, US, Europe – stay tune

4/19/2019 

@pharma_Bi # Followers = 505 

6/28/2019

@pharma_Bi # Followers = 519 RatioTweets to Likes: 25,000/3,086

4/19/2019 

@AVIVA1950 # Followers = 359

6/28/2019

@AVIVA1950 # Followers = 439 RatioTweets to Likes: 11,000/5,615

How can you use all of the above for your Valuation Modeling???

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