The_State_of_TechnologyProduct_ManagementJohn

The State of Technology

Product Management

John Milburn [email protected]

About Pragmatic Marketing

� Experts in technology product management and

product marketing

� Specialize in training and consulting

� Trained tens of thousands of people at

thousands of companies since 1993

Pragmatic Marketing Framework™ S

T R

A T

E G

Y E

X E

C U

T IO

The market-driven

model for managing

and marketing

technology products

Format for Tonight

� I’ll present 4 of today’s common problem areas for

Technology Product Management

� I’ll share some examples of companies (without their

names�..) that are experiencing them

� I’ll propose some approaches and conclusions

� We’ll open it up for discussion

� 4. For as long as I have material, -or- we run out of

time4..

Common Problem Areas

1. Project/Customer vs. Product/Market

2. “Solutions” vs. Products

3. Infrastructure Management vs. Product

Management

4. Waterfall Management with Agile Development

Project/Customer vs.

Product/Market

Only build solutions for

problems that are urgent,

pervasive and that the

market will pay to solve.

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�

Customers (n=1)

Michael Treacy & Fred Wiersema

Discipline of Market Leaders

Large “Big Data” firm recently acquired by an

Equity Investment Firm

Automobile/travel software company

Startup networking services provider

Federal hardware provider

RECOGNITION of

� Corporate trends and/or objectives

� Market differentiation may be your N=1 capabilities

It is very hard for a single PM to be both project/near

term revenue driven and product/strategic driven

Longer term value will be created with products

� The value of a project company are the people and the

contracts (Value “multiplier” is close to 1)

� The value of a product company is the repeatable revenue

streams (Value “multiplier” can be 10-20x)

“Solutions” vs.

Products

S T

R A

T E

G Y

E X

E C

U T

IO N

Market

Problems

S T

R A

T E

G Y

E X

E C

U T

IO N

What Market Problems does your “Solution”

solve?

Market

problems

Product

#1 Product #2

Product #3

Product #1 Product #3Product #2

Infrastructure

“Solution”

Solutions

Product

B u

sin e

ss P la

Product

P o

sitio n

in g

B u

y in

g P

ro ce

R e

q u

ire m

e n

M a

rk e

tin g

P la

Product

Business Plan Positioning Buying Process Requirements Marketing Plan

B u

sin e

ss P la

P o

sitio n

in g

B u

y in

g P

ro ce

R e

q u

ire m

e n

M a

rk e

tin g

P la

B u

sin e

ss P la

P o

sitio n

in g

B u

y in

g P

ro ce

R e

q u

ire m

e n

M a

rk e

tin g

P la

Infrastructure

Business Plan Positioning Buying Process Requirements Marketing Plan

$2B technology parts provider

International travel services provider

Solutions Management (aka Portfolio, Product Line) is

not a part time role

� Should not just be the Director of PM

� Should be defined by the Market, not the Technology

Solutions must be based on, and explicit about what

“Outside in” Market Problems they solve

Biggest issue is the “Governance Model” – who wins

when there is a conflict

Infrastructure

Management vs.

Product

Management

Solutions

Product

B u

sin e

ss P la

Product

P o

sitio n

in g

B u

y in

g P

ro ce

R e

q u

ire m

e n

M a

rk e

tin g

P la

Product

Business Plan Positioning Buying Process Requirements Marketing Plan

B u

sin e

ss P la

P o

sitio n

in g

B u

y in

g P

ro ce

R e

q u

ire m

e n

M a

rk e

tin g

P la

B u

sin e

ss P la

P o

sitio n

in g

B u

y in

g P

ro ce

R e

q u

ire m

e n

M a

rk e

tin g

P la

Infrastructure

Business Plan Positioning Buying Process Requirements Marketing Plan

Large Midwest healthcare software firm

� Director of Applications

� Director of Infrastructure

Large systems vendor

� Public Cloud offering

For infrastructure management, it may be better to

have only a Product Owner (a’la Agile), and not a

Product Manager

� Business Plan will always be negative; Marketing is minimal

� Someone needs to overlay Development and interface with

the other groups

Infrastructure funding justification should come from

the Solution ~or~ for Cost Savings/Internal Efficiency

One “process” does not fit all projects

Waterfall Management

with

Agile Development

Product

Roadmap Build / Test

System

Test

Business

Plan

Business

Gate

Waterfall Planning

LAUNCH

Release

Gate

Marketing

Plan Launch

Plan

Master Requirements List

Goals / Themes

Requirements Project

Plan

Design

Spec

Start

Gate

Market Requirements Document

Market Requirements Table

Product

Roadmap Build / Test

System

Test

Business

Plan

Business

Gate

Waterfall Planning - Accountability

LAUNCH

Release

Gate

Marketing

Plan Launch

Plan

Master Requirements List

Goals / Themes

Requirements Project

Plan

Design

Spec

Start

Gate

Market Requirements Document

Market Requirements Table

-- Product Manager

-- Development

-- Product Marketing Manager

Product

Roadmap

Business

Plan

Business

Gate

Agile Planning

Marketing

Plan

Launch

Plan

Product Backlog

Release Backlog

User Stories

Overall Project

Plan

Arch /Design

Start

Gate(s)

Release

Gate

LAUNCH

System

Test

Sprint Backlogs

Build(s) Sprint

Test(s) Sprint

Plan(s)

Demo(s)

Burnups /

Burndwns

Product

Roadmap

Business

Plan

Business

Gate

Agile Planning - Accountability

Marketing

Plan

Launch

Plan

Product Backlog

Release Backlog

User Stories

Overall Project

Plan

Arch /Design

Start

Gate(s)

Sprint Backlogs

Build(s) Sprint

Test(s) Sprint

Plan(s)

Demo(s) Release

Gate

LAUNCH

System

Test

-- Product Manager

-- Product Owner

-- Development

-- Product Marketing Manager

Burnups /

Burndwns

Innovation Competitive

Landscape

Technology

Assessment

Lead

Generation

Thought

Leadership

Referrals &

References

Launch

Plan

Use

Scenarios

Requirements

Status

Dashboard

Product

Roadmap

Presentations

& Demos

Event

Support

“Special”

Calls

Channel

Support

Channel

Training

Sales

Process

Collateral

Sales

Tools

BusinessMarket ProgramsPlanningStrategy SupportReadiness

S tr

a te

g ic Ta

ctica l

BusinessMarket ProgramsPlanningStrategy SupportReadiness

S tr

a te

g ic Ta

ctica l

Pragmatic Marketing Framework™

Marketing

Strategy

Technical

Innovation Competitive

Landscape

Technology

Assessment

Lead

Generation

Thought

Leadership

Referrals &

References

Launch

Plan

Use

Scenarios

Requirements

Status

Dashboard

Product

Roadmap

Presentations

& Demos

Event

Support

“Special”

Calls

Channel

Support

Channel

Training

Sales

Process

Collateral

Sales

Tools

BusinessMarket ProgramsPlanningStrategy SupportReadiness

S tr

a te

g ic Ta

ctica l

BusinessMarket ProgramsPlanningStrategy SupportReadiness

S tr

a te

g ic Ta

ctica l

Pragmatic Marketing Framework™

User

Acceptance?

Always

Available?

User Stories?

Use Cases?

UI Design?

Functional

Design?

Iteration

Planning

Management demands a Business Plan, even for Agile

projects

But, management must be willing to accept that

there are unknowns (else we pad #’s and just lie…)

It is healthy to kill an occasional project after it has

already been funded and started

Clarity and staffing of Roles (PM, PO, PMM) is

causing more of a void in Market Sensing activities

Thanks !

[email protected]

Unit VI Case Study

Headnote

In addition to knowing how to follow the bits of evidence, forensic detectives must know how to work with law enforcement.

IN SPRING OF 2003, several credit card associations and major credit card issuers began to notice increasing instances of fraud over a three-or four-month stretch. By looking at the patterns and types of fraud and tying that information back to common points, they believed they had identified one company (we'll call them Company A) as the source of the fraud. While the patterns of evidence pointed to Company A, it was still too circumstantial to call in law enforcement. Hard evidence was needed. So the associations and credit card issuers joined forces and contacted Ubizen (the author's company), which conducts cybercrime investigations. They also contacted Company A and asked them to cooperate with forensic examiners from Ubizen who would be sent to their site to investigate the possibility that a security breach had occurred within their production network environment. Company A officials said that they were not aware of any security breach, but they agreed to work with the investigators.

Company A is a software company that provides electronic payment software to numerous retail outlets, including restaurants, retail stores, and Internet companies. Company A's core business is its payment gateway service that processes credit card and check transactions. While the majority of Company A's transactions come from the Internet, wireless transactions are also common. The two different types of transactions are routed through two separate payment gateways, and together they often account for more than 200,000 electronic payment transactions daily.

The primary objective of the forensic investigations "was to determine the source and full extent of the breach. If sufficient evidence was found to prove that a crime had been committed, another objective would be to assist law enforcement in gathering additional evidence for prosecution.

Discovery. Before arriving at the company's site, the forensic team conducted an exhaustive discovery process. This advance work would enable the forensic team to hit the ground running when they went on to the company site.

Stolen data. The team conducted an in-depth analysis of the fraud patterns and found that the fraud resulted from duplicated credit cards used in "card-present transactions." These are seenarios where legitimate account numbers are fraudulently reproduced on unauthorized duplicate cards and used by criminals to purchase goods or services in person, often using matching falsified information.

For a criminal to duplicate a credit card with account information that will pass muster, he or she must have gotten access to the data contained in the magnetic stripe on the back of a card. A credit card magnetic stripe contains two separate tracks of information. Track 1 data contains information printed on the card, such as the cardholder's name, but this data is not a component of the transaction authorization-it merely verifies that the name on the card has not been changed. Track 2 contains more sensitive information, including the CVV code (the card verification value, a number string that is printed, not embossed, on a card), which helps verify that a transaction is authorized.

Sophisticated fraud could be perpetrated by skimming this information from individual cards. But the fraud pattern in this case made it likely that theft of data in large batches had occurred. In fact, the investigation revealed that full mag-stripe information had been taken from Company A's network.

Because mag-stripe information allows criminals to duplicate a credit card, the payment service industry stipulates that this type of information not be stored subsequent to authorization. The finding of theft at Company A raised questions about whether the mag-stripe information was being handled properly, according to the payment service industry's commonly accepted security standards. The fact that mag-stripe information was involved in this breach meant that the information was likely stored despite the standard against doing so.

Investigators needed to locate where on the customer's network this type of information resided. They could then identify the most likely avenues of intrusion through the network.

Lay of the land. To accomplish this, the forensic experts studied diagrams to learn the layout of Company A's computer network and determine whether it was vulnerable and which parts of the network were most likely to be exposed if a hacker had been able to penetrate the system. Frequently, the most likely targets are Internet-visible systems, such as Web servers and FTP servers, or weakly configured wireless network access points. The team found that, indeed, Company A's network -was not sufficiently hardened against an attack, making it likely that hackers could have penetrated the system and stolen the account information.

FBI assistance. Given these findings, the forensic team recognized that it was time for law enforcement to be brought into the process. This was a point sometimes overlooked by private firms: It was vital that the appropriate government agents be on the scene to help in the assembling of evidence that could lead to the capture and eventual prosecution of the attacker. In this case, because of the nature of the crime and the magnitude of the fraud, FBI agents were contacted.

In early June, FBI agents from the Atlanta field office -were the first to visit the site, although they were soon replaced by agents from the Chicago field office, who had much more extensive experience investigating cybercrimes. These agents had in fact worked with Ubizen investigators on previous investigations. Ubizen s forensic experts also visited the FBI field office to hold discussions over the specifics of the investigation, such as what forensic tools would be used to ensure the integrity of any data taken and how chain of custody would be maintained.

At the scene with the FBI agents, Ubizeris investigators began data collection; they first collected mirror images of Company A's payment gateway, which they shared with the FBI investigators. Together the two teams then interviewed Company A's staff for additional information on how the breach could have occurred, determining, for example, who in the organization had access to particular servers. Track 2 information had been compromised, so it was important to understand where in the network such data sat, which would indicate to the team what systems must have been touched by the attacker. This information could also help answer other questions, such as whether it could have been an inside job or whether the Internet was the avenue of attack.

After interviewing the staff and examining the organizations network diagram, several systems were identified that seemed likely avenues of attack based on their proximity to the Internet and lack of suitable security controls. The team investigated several servers where they suspected a significant point of exposure and found on one of the systems a number of files that had not been installed by Company A's administrators. These files included keystroke loggers and a common backdoor program called HackerDefender. This made it clear that the system had indeed been compromised, leading the team to rule out an inside job.

Footprints. FBI agents and the Ubizen team looked at files and audit logs to find the hacker's footprint and attack signature-that is, how the hacker broke in and what the hacker did once he or she had access. Without more in-depth analysis it would be impossible to determine how the intruder was first able to gain access to the systems.

However, based on the immediately visible footprint left behind by the intruder, it became clear that the server had become the staging point through which the intruder could continually gain access into other components of Company A's production network environment. Once the intruder had gained a foothold into the environment from the outside, he or she placed hacking tools and utilities within the systems, effectively exploiting the breach.

Live prey. When tracing the hacker's steps, the investigators looked closely at dates and time stamps to determine when the hacker last penetrated the company's network. They found files created by the hacker the day before the investigation began, proving that there was an ongoing breach, an important development since it could help the investigators to catch the attacker in the act.

Sewing up the breaches. The team first needed to repair the breach. Since the incidents of fraud associated with Company A were rapidly escalating-as many as hundreds per day-it was imperative to immediately lock out the hacker's access to private information.

The team began by purging from the organization's systems sensitive cardholder data that, under industry standards, should never have been stored on the systems. With that data removed, the exposure created by any future unauthorized access would be much less severe.

The team also took several of Company A's servers offline, replacing many of the compromised systems. They then enabled and configured logging and auditing functions to ensure that if unauthorized access were attempted again, the organization would be able to detect and respond to the unwanted activity.

All of the information collected on site was preserved, including hard drives from the compromised systems and logs from the intrusion detection system, the firewall, and the routers. The information was shipped back to Ubizeris labs for in-depth analysis and preservation for evidentiary purposes.

A number of different open-source tools were used to identify and salvage any other traces left behind by the intruder that might shed more light on the timeline of the attack or other systems that might be involved. The tools used included both Ubizen-proprietary and over-the-counter forensic tools such as Encase. Because these tools had been tested extensively in court, the FBI team could be sure that any evidence (such as copies of drives) provided by Ubizen would be admissible.

Setting the trap. With the loss of data stanched, investigators were ready to catch the hacker in the act. To accomplish this, the Ubizen team and the FBI set a trap with three components.

The first part was a packet sniffer, a laptop with a software program called EtherPeek that would watch traffic in and out of the affected servers. It allowed investigators to monitor any data the hacker was sending, such as individual keystrokes, the machines the intruder was attempting to access, and how he or she was attempting to do so. Also, the sniffer would capture firsthand evidence of files removed from the network that would, under normal circumstances, contain sensitive information or data that could be used for fraud.

Next, the files on those servers were loaded with dummy credit-card information to prevent additional fraud from occurring and to keep the hacker unaware that he or she had been noticed. The third part of the trap was the use of Tripwire, a program that monitors the integrity of files, which was configured to set off an alarm the moment any of the date and time-stamps of the files under observation were changed. That would allow the investigators to know exactly when the attacker hit so that they could catch the intruder in the act.

Underlying the trap was the fact that the investigators had determined precisely how the hacker would attack. The investigation had shown the particular backdoor the attacker was using and what port would be used in the compromise. But with a huge amount of traffic flowing back and forth across the network (this company also conducts e-commerce business), waiting for a Tripwire alarm was not necessarily going to allow the investigators to see the compromise as it happened. So, a Ubizen technician worked with the FBI's Quantico-based Data Analysis Team to create a signature that they could look for on the sniffer to see exactly when and where the hacker was attacking.

Hooked. The trap worked perfectly. When the hacker snuck in to begin copying what looked like credit-card information that Company A had backed up, he fell right into the ambush and was caught red handed. From this point, FBI agents took the evidence collected by the Ubizen and FBI teams and began the hunt for the suspect.

They contacted a law enforcement computer-crime liaison group in the Eastern European country where it was determined that the hacker was located. Ultimately, the hacker-a college-age male-was arrested and extradited, and the evidence gathered against him will be used when the case comes to trial.

Aftermath. While Company A breathed a sigh of relief when the hacker was caught, the work of the Ubizen investigative team wasn't over yet. Their mission was not only to help identify the hacker but also to determine the full extent of the breach and figure out precisely how many credit cards had been compromised, and when.

Targets. The complete analysis showed that there were in fact several intruders who took advantage of the backdoor the original hacker left, and they seemed to be unaware of each other's presence. Altogether these attackers maintained some level of access into Company A for more than six months, two months longer than the previously recognized fraud dates. The team was also able to identify other machines on the network that had been compromised. These included the organizations two database servers, the mail server, two file and print servers, and each of the Internet-visible systems.

Recommendations. The final step was to provide recommendations to Company A on how to bolster its security against future attacks. These included the obvious suggestion of adapting to industry best practices.

MasterCard and VISA have led the industry in establishing guidelines to secure customer credit card data. MasterCard's Site Data Protection Service (SDP) and Visas Cardholder Information Security Program (CISP) are industry mandates with serious financial penalties for noncompliance. These programs define a standard of due care for deploying security compliance programs, ensuring that online merchants and payment service providers are adequately protected against hacker intrusions and account data compromises. The investigative team determined that Company A was far from fulfilling these requirements and outlined exactly what measures the company needed to take to be fully compliant.

A key suggestion was for Company A to conduct regular vulnerability scanning internally or to outsource the scans to an expert. This inexpensive automated process proactively identifies vulnerabilities to find out if and where a computer system can be exploited or is vulnerable.

Finally, the team provided a set of recommendations above and beyond the established credit card industry standards. The team advised Company A to either add an internal IT team dedicated solely to security or to consider outsourcing key elements of its security program to a managed security services provider. The amount of data generated by security devices is overwhelming, and it can only be properly monitored by a dedicated team whose sole function is to oversee the network data.

Since the attackers had access to stored credit card data, the team also urged Company A not to retain credit card data longer than needed. As this case made clear, storing this type of sensitive information opens up a high risk of exposure.

This case illustrates how private cybercrime investigators and law enforcement can collaborate to both protect the bottom line and stem crime. That's good news for long-beleaguered online businesses, and bad news for online fraudsters.

Sidebar

Forensic detectives can often quickly identify the most likely targets of a hacker attack on a given network.

Sidebar

Two Teams are Better Than One

Cybercrime investigations are Often initiated by the victimized company not through a call to the police, but through a call to a private firm that specializes in computer forensics examinations. These private-sector teams will then call law enforcement into the process as soon as they confirm that illegal activity is occurring.

Cooperation between law enforcement and private-sector investigators is still a fairly new idea, however. Several years ago, when the author's company first started conducting forensics investigations, it was often met with distrust by both their private sector clients, who feared bad publicity or losing control of company data, and law enforcement agents, who were reluctant to share information with third-party vendors. However, this reluctance is diminishing as law enforcement becomes more accustomed to working with third-party cyberforensics experts and as clients see that the process can work. Companies like Ubizen work under strict conditions and with detailed nondisclosure agreements, which protects clients and helps allay fears.

Although they need to work together, it is important to understand that ultimately the two groups of investigators have different goals. The private-sector team has the ultimate goal of understanding the full extent of the compromise and helping the client find and close the vulnerability that led to the breach-in other words, to protect its reputation and profits. Law enforcement is focused on the illegal activity and in collecting any evidence that will lead to the attacker and help in a prosecution.

The two groups also work differently due to the nature of their responsibilities. A private forensic firm is doing paid work for a client and will devote a team to getting the work done in a short time frame. For example, this case took Ubizen two days on site and another two weeks to complete the analysis and write a report. By contrast, law enforcement agents typically are juggling multiple cases or responsibilities and may take longer to complete an investigation or may have difficulty devoting sufficient resources to a specific case.

While the goals are different, the groundwork serves both objectives. For that reason, the analysis completed by the private-sector team is often useful to law enforcement, saving them time and giving them a head start in understanding all the technical details of an investigation so that they can make a case for protection.

AuthorAffiliation

Bryan Sartin is director of technology for Ubizen, where he is responsible for all customer-facing issues regarding the technology of its managed security solution offerings.

Unit VI Case Study

What problem was identified? What steps were taken to solve the problem?

 Various stages of the investigation were focused on different goals. Briefly list and describe what these were as the investigation progressed and what strategies were employed.

 Identifying and catching the criminal was not the only purpose for this investigation—what else needed to be done, and how was it to be accomplished?

 What type(s) of cybercrime was/were involved in this article? Does the identified offender fit the characteristics for this type of cybercrime?

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10:40 – 10:55 a.m. Break Session 2 10:55 – 11:45 a.m.

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Leadership mistakes you don’t have to make What teams really need from their leaders

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Document de travail (Working Paper)

"Crowdfunding: tapping the right crowd"

Belleflamme, Paul ; Lambert, Thomas ; Schwienbacher, Armin

Abstract

The basic idea of crowdfunding is to raise external finance from a large audience (the “crowd”), where each individual provides a very small amount, instead of soliciting a small group of sophisticated investors. The paper develops a model that associates crowdfunding with pre-ordering and price discrimination, and studies the conditions under which crowdfunding is preferred to traditional forms of external funding. Compared to traditional funding, crowdfunding has the advantage of offering an enhanced experience to some consumers and, thereby, of allowing the entrepreneur to practice menu pricing and extract a larger share of the consumer surplus; the disadvantage is that the entrepreneur is constrained in his/her choice of prices by the amount of capital that he/she needs to raise: the larger this amount, the more prices have to be twisted so as to attract a large number of “crowdfunders” who pre-order, and the less profitable the menu pricing scheme.

Référence bibliographique

Belleflamme, Paul ; Lambert, Thomas ; Schwienbacher, Armin. Crowdfunding: tapping the right crowd. CORE Discussion Paper; 2011/32. (2011).

http://hdl.handle.net/2078.1/78971

2011/32

■

Crowdfunding: tapping the right crowd

Paul Belleflamme, Thomas Lambert and Armin Schwienbacher

Center for Operations Research and Econometrics

Voie du Roman Pays, 34

B-1348 Louvain-la-Neuve Belgium

http://www.uclouvain.be/core

D I S C U S S I O N P A P E R

CORE DISCUSSION PAPER 2011/32

Crowdfunding: tapping the right crowd

Paul BELLEFLAMME 1, Thomas LAMBERT2

and Armin SCHWIENBACHER 3

June 2011

Abstract The basic idea of crowdfunding is to raise external finance from a large audience (the “crowd”), where each individual provides a very small amount, instead of soliciting a small group of sophisticated investors. The paper develops a model that associates crowdfunding with pre-ordering and price discrimination, and studies the conditions under which crowdfunding is preferred to traditional forms of external funding. Compared to traditional funding, crowdfunding has the advantage of offering an enhanced experience to some consumers and, thereby, of allowing the entrepreneur to practice menu pricing and extract a larger share of the consumer surplus; the disadvantage is that the entrepreneur is constrained in his/her choice of prices by the amount of capital that he/she needs to raise: the larger this amount, the more prices have to be twisted so as to attract a large number of “crowdfunders” who pre-order, and the less profitable the menu pricing scheme. Keywords: crowdfunding, pre-ordering, menu pricing.

JEL Classification: G32, L11, L13, L15, L21, L31

1 Université catholique de Louvain, CORE and Louvain School of Management, B-1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]. Other affiliation: CESifo. This author is also member of ECORE, the association between CORE and ECARES. 2 Université catholique de Louvain, Louvain School of Management, B-1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]. 3 Université Lille Nord de France – SKEMA Business School (Université Lille 2, Faculté de Finance, Banque et Comptabilité, F-59020 Lille Cedex, France. E-mail: [email protected]. Other affiliation as research fellow: University of Amsterdam Business School. The authors are grateful to seminar and conference participants in Antwerp, Bologna, Copenhagen, Groningen, Lille, Louvain- la-Neuve, Montpellier, Paris, Prague, and Porto for their helpful comments on a previous version.

This paper presents research results of the Belgian Program on Interuniversity Poles of Attraction initiated by the Belgian State, Prime Minister's Office, Science Policy Programming. The scientific responsibility is assumed by the authors.

1 Introduction

It is well recognized that new ventures face difficulties in attracting external finance at their very initial stage, be it through bank loans or equity capital (see, e.g., Berger and Udell, 1995, Cassar, 2004, and Cosh et al., 2009). While business angels and venture capital funds fill gaps for larger amounts, the smallest amounts are provided by entrepreneurs themselves and friends & family. Still, many ventures remain unfunded, partially because of a lack of sufficient value that can be pledged to investors, partially because of unsuccessful attempts to convince investors (Hellmann, 2007; Casamatta and Haritchabalet, 2010). To circumvent these problems, creative founders have recently made use of a new source of finance–so-called crowdfunding–by tapping the “crowd” instead of specialized investors.

The concept of crowdfunding finds its root in the broader concept of crowdsourcing, which refers to using the crowd to obtain ideas, feedback and solutions in order to develop corporate activities (Howe, 2008; Klee- mann et al., 2008). In the case of crowdfunding, the objective is to collect money for investment; this is generally done by using social networks, in particular through the Internet (Twitter, Facebook, LinkedIn and different other specialized blogs). In other words, instead of raising the money from a very small group of sophisticated investors, the idea of crowdfunding is to obtain it from a large audience (the “crowd”), where each individual will pro- vide a very small amount. This can take the form of equity purchase, loan, donation or pre-ordering of the product to be produced. The amounts that have been targeted through crowdfunding have continuously increased, with Trampoline Systems targeting more than £1 million for the financing of the commercialization stage of their new software. Recently, TikTok+LunaTik raised $941,718 from 13,512 individuals in the form of product pre-ordering of its multi-touch watch kit.

In this paper, we develop a model that associates crowdfunding with pre- ordering and price discrimination, and we study the conditions under which crowdfunding is preferred to traditional forms of external funding (bank loan or equity investor). In this framework, the funding is needed to finance up-front fixed costs of production. Since the remaining consumers will pay a different price, crowdfunding that takes the form of pre-ordering gives the opportunity to price discriminate between the first group (those who pre- order and thus constitute the investing crowd) and the second group (the

other consumers who wait that production takes place before purchasing directly). However, an entrepreneur is generally unable to identify these consumers. The entrepreneur must then use some self-selecting device so as to induce high-paying consumers to reveal themselves. In this sense, crowdfunding appears as a form of menu pricing.

The trade-off we explore in the model is thus the following: compared to traditional funding, crowdfunding has the advantage of offering an enhanced experience to some consumers and, thereby, of allowing the entrepreneur to practice second-degree price discrimination and extract a larger share of the consumer surplus; the disadvantage is that the entrepreneur is constrained in his/her choice of prices by the amount of capital that he/she needs to raise initially to fund production: the larger this amount, the more prices have to be twisted so as to attract a large number of “crowdfunders”, and the less profitable the menu pricing scheme.

The model highlights the importance of community-based experience for crowdfunding to be a viable alternative to traditional funding. If the entrepreneur is not able to create such benefits, no consumer will find it worthwhile to pre-order the good, unless a discount is offered. However, crowdfunding then becomes less profitable compared to traditional funding. Also, the analysis shows that crowdfunding is the most profitable option only for lower levels of finance. Indeed, crowdfunding yields higher profits only for small amounts where the entrepreneur faces no (or limited) constraints in his/her price setting between the two types of consumers while still securing enough up-front financing. As the amount required becomes larger, the entrepreneur is forced to distort more the prices so that more consumers are willing to pre-order and thus the entrepreneur can collect up-front more money. This in turn reduces the gains from price discrimination. Our results are robust to the possibility that the entrepreneur may take the money collected from the crowdfunding initiative and run away with it.

Another important result is that crowdfunders eventually pay more than other, regular consumers. This outcome is consistent with findings from different case studies where community benefits are important. Indeed, our model shows that through price-discrimination, individuals with the highest willingness-to-pay become crowdfunders. As they are willing to pay the most and additionally enjoy non-monetary community benefits, it turns out that they end up paying more than consumers waiting for the product to

reach the market. The remaining of this paper is structured as follows. The next section

offers a definition of crowdfunding, discusses crowdfunding practices and provides a survey of related literature. Section 3 presents the theoretical model and discusses its results and implications. Finally, Section 4 concludes with suggested topics for future research.1

2 Crowdfunding as a distinct form of entrepreneurial

finance

Our objective in this section is twofold. First, we aim at providing a general definition of crowdfunding. Second, we discuss how crowdfunding differs from other sources of entrepreneurial finance. To this end, we present se- lected crowdfunding initiatives and then provide a review of the related literature.

2.1 A definition

As mentioned, the concept of crowdfunding can be seen as part of the broader concept of crowdsourcing, which refers to using the “crowd” to obtain ideas, feedback and solutions in order to develop corporate activi- ties. The term “crowdsourcing” has been first used by Jeff Howe and Mark Robinson in the June 2006 issue of Wired Magazine, an American magazine for high technology (Howe, 2008). Kleemann et al. (2008) point out that “crowdsourcing takes place when a profit oriented firm outsources specific tasks essential for the making or sale of its product to the general public (the crowd) in the form of an open call over the internet, with the intention of animating individuals to make a [voluntary] contribution to the firm’s production process for free or for significantly less than that contribution is worth to the firm.” Although this definition of crowdsourcing is a useful starting point, several caveats and clarifications need to be made in order to transpose it to crowdfunding.

Raising funds by tapping a general public (the crowd) is the most impor- tant element of crowdfunding. This means that consumers can volunteer to

1Section 5 is an appendix containing the details of the mathematical developments and

the proofs of the propositions.

provide input to the development of the product, in this case in form of fi- nancial help. How the interaction with the crowd takes place may, however, differ from crowdsourcing. For instance, platforms have recently emerged to facilitate the interaction between entrepreneurial initiatives and poten- tial crowdfunders. Entrepreneurs can post their project on the platform and benefit from the platform’s visibility to reach potential investors. A platform of this sort, Kickstarter, has successfully intermediated more than 7,000 projects already.2

Yet, while the use of the Internet to make an “open call” may be very efficient for crowdsourcing in general, it can become more problematic for crowdfunding, especially if it involves the offering of equity to the crowd. Indeed, making a general solicitation for equity offering is limited to publicly listed equity. In many countries, there is also a limit as to how many private investors a company can have (see Larralde and Schwienbacher, 2010, for an extended discussion). This creates important legal limitations to crowd- funding initiatives, given that the input of the crowd is capital and not an idea or time. Therefore, most initiatives do not offer shares but provide other types of rewards such as a product or membership.

Besides, while the Web 2.0 has been a critical ingredient in the devel- opment of crowdfunding practices, it also differs from open-source practices (Brabham, 2008; Fershtman and Gandal, 2011). An important distinction is that in the case of open-source, the resource belongs to the community, which can then exploit it on an individual basis (there is no restriction on who can use it); in the case of crowdfunding (and also crowdsourcing), it ultimately belongs to the firm, which will be the only one to use it. This distinction with open-source practices becomes even more obvious when re- lated to crowdfunding, since capital cannot be shared. Unlike an idea or a software code, capital is not a public good in the economic sense that assumes non-rivalness and non-excludability.

Based on this discussion and in the spirit of Kleemann et al. (2008), we offer the following, refined definition:

Definition 1 Crowdfunding involves an open call, mostly through the In- ternet, for the provision of financial resources either in form of donation or

2These platforms share some similarities with online lending markets (Everett, 2008;

Freedman and Jin, 2010); while the latter more prominently target social entrepreneurship,

crowdfunding platforms have a broader scope of entrepreneurial initiatives.

in exchange for the future product or some form of reward and/or voting rights.

As mentioned above, the promised reward can be monetary or non- monetary (such as recognition). This definition encompasses many forms of crowdfunding practices and has been discussed as such. However, in this pa- per, we focus on crowdfunding initiatives that take the form of pre-ordering of products. The following sections are restricted to the latter form.

2.2 Examples

Different reasons may explain recent successes of entrepreneurs who have relied on crowdfunding. Also, there exist many ways to “crowdfund” a project. However, crowdfunding initiatives share some common character- istics, which we stress below in the light of selected cases.

In 2005, the South African singer Verity Price launched the “Lucky Packet Project”. To record her album without assistance of a record label, Verity Price needed to advance an up-front investment of ZAR400,000.3 To this end, she set up a website where she asked people to pre-purchase her album at ZAR200 before she recorded it. In return from their contributions, people were compensated with some form of non-monetary rewards, such as their name credited on her website, the possibility to vote on which songs are recorded, and what artwork and photography are used. Also, 10% of sales would be transferred to charities. Verity Price managed to reach the threshold of ZAR400,000 with the contributions of 2061 individuals. Then, she used the money to record her album. Now, the album has been put on the market and is sold to everyone at ZAR100.

In the same vein, the LINCH three Project aims at making a documen- tary film about the artist David Lynch. The filmmakers ask to David Lynch’s fans to donate $50 each to fund the film project. The fans’ community are rewarded by having online access to exclusive content on the filmmaking process and by receiving limited edition of footage created by Lynch himself either into print, T-shirt, or bag. Once the money is raised, the documentary film will be produced and distributed via the regular distribution channels.4

3ZAR (South African Rands) 400,000 is approximately e35,000. 4Buyacredit.com’s initiative or the film “The Age of Stupid ” are other examples of

independent films for which financing is crowdfunded.

As exemplified by these two cases, crowdfunding seems more successful in the entertainment industry. However, entrepreneurial ventures in other industries have been financed in the same way and share similar characteris- tics. Initiatives have been undertaken in other industries such as journalism (Spot.Us ), beer (BeerBankroll ), software (Blender Foundation, Trampoline Systems ) and tourism (MediaNoMad ). For instance, by investing in the launch of the Lebanese restaurant mybar, people may enjoy financial and social benefits, such as voting rights, special privileges at mybar, and annual dividends. Also, members of MyFootballClub (who own the football club Ebbsfleet United in United Kingdom) are completely involved in the man- agement of the club through their voting right. The contribution of fans (a membership fee of £35) allowed them to complete the takeover of the club and form a community with real decision power.

To sum up, these cases highlight three recurrent characteristics. First, crowdfunding initiatives often rely on advance purchase of a product, which is not yet on the market in its finished form. At the pre-ordering stage, the entrepreneur offers just a description and promise on what the final prod- uct will be, and also commits that the product will indeed be put on the market. Second, in most of the cases, consumers who pre-order the product pay more than the regular consumers, who wait that production takes place before purchasing directly. In the Verity Price’s experience, the regular con- sumers pay ZAR100 whereas the pre-ordering consumers pay ZAR200. The crowdfunders are therefore willing to pay more for the product. Third, the crowd must identify themselves as such. Crowdfunders must feel that they are being part of a community of privileged consumers. This community can take many forms, starting with receiving rewards up to direct involvement in the project. In the case of LINCH three Project, they gain access to ex- clusive footage of David Lynch. Hence, consumers may self-select into this community and entrepreneurs ensure that consumers enjoy such community benefits and trust in the project.

2.3 Related literature

As crowdfunding is a relatively new phenomenon, it is no surprise that the literature specifically devoted to crowdfunding is only nascent. It is however worthwhile making parallels with other sources of entrepreneurial finance. This allows us to better understand the specificities of crowdfunding as a

distinct form of finance. First, looking at crowdfunding from a pure financial perspective, connec-

tions can be made with bootstrap finance. This form of financing consists of using internal financing ways rather than traditional sources of external finance (e.g., bank loan, angel capital and venture capital). Several studies provide evidence of the different forms of internal sources used by boot- strapping entrepreneurs (see Bhidé, 1992, Winborg and Landstrom, 2001, and Ebben and Johnson, 2006, just to cite a few). Bhidé (1992) shows that even among the Inc. 500 companies in the US, most of them started by bootstrapping the company. Further financing methods for startups com- panies are analyzed, for instance, by Cosh et al. (2009), who examine a broader range of financing alternatives. None of these studies however con- sider the “crowd” as possible alternative (regardless of whether it constitutes potential consumers or simply profit-driven individuals).

A few studies have recently focused on crowdfunding more specifically. One is by Agrawal, Catalini and Goldfarb (2011) that examines the geo- graphic origin of consumers who invest on the SellaBand platform.5 The authors observe that “the average distance between artist-entrepreneurs and investors is about 3,000 miles, suggesting a reduced role for spatial proxim- ity.” However, they establish that distance still plays a role insofar as “local investors are more likely than distant ones to invest in the very early stages of a single round of financing and appear less responsive to decisions by other investors.”

The idea that investors may be responsive to other investors’ decisions is also present in Ward and Ramachandran (2010). The goal of this paper is to estimate the extent to which demand for crowdfunding projects is driven by peer effects. Like in our model, it is assumed that consumption cannot hap- pen until projects successfully complete their funding. What differs is the

5SellaBand is an online platform based in Amsterdam that enables musicians to raise

money to produce their album. SellaBand ’s business model is as follows. Artists can post

a number of songs (demos) on the platform; visitors to the site can then listen to the

music for free and choose the artists they want to invest in; artists seek to raise $50,000 by

selling “Parts” at $10 each; during the fundraising stage, money is held in an escrow until

the threshold of $50,000 is reached. The $50,000 will be used to fund the artist’s recording

project; finally investors (the “Believers”) are compensated by receiving 10% of revenue

from the album. SellaBand has been one of the first website of this kind; followers are,

e;g., MyMajorCompany in France, Akamusic in Belgium, and ArtistShare in the United

States.

link that the authors make between crowdfunding and information. While we assume that crowdfunding allows the firm to gain information about its consumers, they posit that crowdfunding allows consumers to refine their information about the quality of an experience good. In their model, crowd- funders may update their prior based on information from their investor social network. Analyzing also data from SellaBand, they find that crowd- funders are influenced by the success or failure of related projects and use the actions of other crowdfunders as a source of information in their funding decisions.

Finally, when crowdfunding is associated with pre-ordering and price discrimination, some strand of literature in the realm of industrial orga- nization provides useful insight. Nocke et al. (2011) have recently linked product pre-ordering to price discrimination, however in a context of infor- mation asymmetry.6 There, the true quality of the product is revealed later so that the firm faces consumers with different expected valuations for its forthcoming product. This induces consumers with highest expected valua- tion to pre-order before the quality is known. Advance-purchase then leads to price discounts, in contrast to our setting that abstracts from information asymmetry. Also, their setting does not induce any network effect like in our setting.

Such network effects and similar coordination issues among consumers are present in another strand of literature that can be related to our work, namely the literature on threshold (or discrete) public goods. These goods can be provided only after a sufficient amount of contributions is reached so as to cover their cost of provision (think, e.g., of a lighthouse or a bridge). The parallel with crowdfunding is clear as the entrepreneur also needs to collect private contributions before producing her good (which is private rather than public in the present case). When contributing, an individual exerts a positive externality on other individuals by raising the likelihood that the good (public or private) will be produced. Free-riding may then be observed. In our setting, as will be explained below, we treat this problem by requiring that consumers’ expectations (about the contribution behavior of other consumers) be fulfilled at equilibrium and by assuming that the entrepreneur is able to somehow coordinate consumers’ decisions so as to

6Other studies have shown that advance-purchase discounts may arise in environments

where production capacity is limited or the aggregate level of demand is uncertain (Gale

and Holmes, 1992, 1993; Dana, 1998, 1999, 2001).

avoid free-riding. This simplification allows us to focus on other important issues of crowdfunding. In contrast, the literature on threshold public goods explicitly addresses the possibility of free-riding and examines the design of optimal mechanisms for the provision of those goods when, for instance, each individual has private information about the cost or benefit associated with his or her participation in the provision of the good (Gradstein, 1994), or when permitting continuous rather than binary “all-or-nothing” contribu- tions (Cadby and Maynes, 1999), or under different rules of allocating excess contributions if the total amount collected exceeds the required threshold (Spencer et al., 2009).

3 Crowdfunding, pre-ordering and menu pricing

In this section, we focus on crowdfunding experiences where consumers are invited to pre-order the product. For the entrepreneur to be able to launch production, the amount collected through pre-ordering must cover the fixed cost of production. Since the remaining consumers will pay a different price, crowdfunding that takes the form of pre-ordering gives the opportunity to price discriminate between the first group (those who pre-order and thus constitute the investing “crowd”) and the second group (the other consumers who wait that production takes place before purchasing directly).

Since the consumers who pre-order are those with a high willingness to pay for the product, these will generally constitute the bulk of the “crowd”. However, an entrepreneur is generally unable to identify these consumers. The entrepreneur must then use some self-selecting device so as to induce high-paying consumers to reveal themselves. The sort of ‘community ex- perience’ that web-based crowdfunding offers may be a means by which the entrepreneur enhances the perceived quality of the product for the con- sumers who agree to pre-order it. In this sense, crowdfunding appears as a form of menu pricing (i.e., of second-degree price discrimination).

The trade-off we explore in our model is thus the following: compared to external funding, crowdfunding has the advantage of offering an enhanced experience to some consumers and, thereby, of allowing the entrepreneur to practice second-degree price discrimination and extract a larger share of the consumer surplus; the disadvantage is that the entrepreneur is constrained in the first period by the amount of capital that she needs to raise. The

larger this amount, the larger the number of consumers that have to be attracted to cover it, which eventually reduces the profitability of the menu pricing scheme.

In what follows, we first present our model; we then derive, in turn, the outcome under traditional sources of financing (such as debt) and under crowdfunding; finally, we derive the optimal funding choice.

3.1 Model

Suppose a unit mass of consumers identified by θ, with θ uniformly dis- tributed on [0, 1]. The parameter θ denotes a consumer’s taste for an in- crease in product’s quality. Consumers have unit demand (they buy one or zero unit of the product). All consumers have a reservation utility r > 0 for the product; any increase from the basic quality is valued in proportion to the taste parameter θ. Normalizing basic quality to zero, we have that if consumer θ buys one unit of product of increased quality s sold at price p, her net utility is r + θs−p.7 To ensure interior solutions at the pricing stage, we assume:

Assumption 1. r < s < 2r.

The product is marketed by a monopolist. In our simple model, we consider the quality of the product, s, as exogenous and known by the consumers before purchase.8 For simplicity, we set to zero the marginal cost of production. There is, however, a fixed cost of production K > 0. The timing of the game is as follows. In period zero, the entrepreneur chooses her funding mechanism—traditional funding or crowdfunding—with the following implications. If the entrepreneur chooses traditional funding, then, in period 1, it incurs the fixed cost K, which is financed through, e.g., a bank loan; in period 2, the entrepreneur sets a price p for her product, and consumers decide to buy or not.

On the other hand, if the entrepreneur chooses crowdfunding, then it is able to set a menu pricing scheme. In period 1, the entrepreneur sets

7This problem was initially examined by Mussa and Rosen (1978). We use here the

results of the extended analysis of Bhargava and Choudary (2001). 8A natural extension of this framework would be to assume that the quality of the

product is unknown to the consumers before purchase. As observed in some crowdfunding

experiences, the entrepreneur may then use web-based crowdfunding to reveal information

about the product and, thereby, alleviate the experience good problem. We discuss this

possibility in the concluding section.

p1, the price for consumers who pre-order the product; the total revenue collected through pre-orders is meant to cover the fixed cost of production. In period 2, the entrepreneur sets two prices: pc, the price to be paid by those consumers who have contributed to the financing of the venture (the so-called “crowdfunders”), and pr, the price to be paid by those consumers who have not (the so-called “regular consumers”).9 As for consumers, they choose in period 1 whether to pre-order or not; in period 2, they decide whether to purchase the product or not (as long as the product has been put on the market, i.e., if total contributions in period 1 are at least as large as K).

The key feature of crowdfunding from the point of view of the consumers is that the participation to the mechanism may provide consumers with an increase in the product quality. We have indeed observed in Section 2 that entrepreneurs resorting to crowdfunding use the Internet to maintain an in- teraction with their funders so as to provide them with so-called ‘community benefits’. Various forms of rewards are sometimes offered but it appears that these rewards are mostly symbolic and that crowdfunders essentially value the feeling of belonging to a group of ‘special’ or ‘privileged’ consumers. It is therefore important for the entrepreneur to attract a sufficient number of regular (i.e., ‘non-privileged’) consumers to whom crowdfunders can feel somehow ‘superior’. Denoting the number of regular consumers by nr and the minimal number of them by ρ (with ρ ≥ 0), we capture these findings in the model through the following assumption:

Assumption 2. Crowdfunders perceive the quality of the product to be equal to s + σ, with σ > 0 if nr ≥ ρ and σ = 0 otherwise.

Assumption 2 translates the idea that crowdfunders enjoy some addi- tional utility from the product compared to regular consumers as long as the number of those regular consumers is above some threshold. To elim- inate two sub-cases of very little interest, we put an upper bound on the parameters σ and ρ:

Assumption 3. σ < s (r + s) / (2r).

Assumption 4. ρ < r/ (2s). 9The entrepreneur is able to recognize consumers who pre-ordered in period 1 and

therefore to tell them apart from regular consumers; no personal arbitrage is thus possible

in period 2.

The entrepreneur maximizes the present discounted value of her profits over the two periods. Consumers maximize the present discounted value of their net utility over the two periods. We assume that the entrepreneur and the consumers have the same discount factor and we let 0 < δ ≤ 1 denote it.

Two comments are warranted on the pricing schedule, which is meant to be very general. First, contributors pay p1 + δpc in total, other consumers pay δpr. This framework encompasses several, more restrictive schemes, including full pre-payments (where contributors pay one single amount up- front, equal to p1 + δpc) as well as ex post price discrimination (where each type pays a different price). This means that we do not exogenously impose pc and pr to be identical, although the framework here allows for this. Sec- ond, by enabling the participating crowd to pay up-front only part of their contribution, we avoid any price setting in which the entrepreneur would raise funds well beyond what she really needs, namely K. Here, contribu- tors provide in period 1 merely what is needed for starting production, the rest being paid in period 2. As we will see, this implies that the first-period price charged to crowdfunders (p1) is not directly set by the entrepreneur but is rather indirectly determined by the interplay between the capital require- ment K and the number of crowdfunders (noted nc), which depends itself on the two second-period prices, pc and pr. These two prices are therefore the two actual choice variables of the entrepreneur.

We now consider the choice of prices under the two funding mechanisms. We then compare optimal profits in the two cases and address the choice of funding mechanism.

3.2 Traditional funding

The case of traditional funding is straightforward. In period 1, the en- trepreneur gathers funds and in period 2, she sets a uniform price p. All consumers perceive that the product has quality s. Hence, the indifferent consumer is such that r + θs−p ≥ 0, or θ ≥ (p−r) /s ≡ θ̂. As we assume a unit mass of consumers uniformly distributed on the unit interval, we have that the quantity demanded is equal to q (p) = 1 − θ̂ = 1 − (p−r) /s. From the first-order condition for profit-maximization, we easily find that the optimal price is p∗ = (r + s) /2. It follows that θ̂∗ = (s−r) /2s, which is positive according to Assumption 1. We can then compute the optimal

gross profit as p∗ (

1 − θ̂∗ )

= (r + s)2 / (4s). The net profit under traditional funding is thus equal to

πT =

{ δ

(r+s)2

4s −K for K < δ (r+s)

4s ,

0 otherwise. (1)

3.3 Crowdfunding

The crowdfunding case is more complex to analyze for two reasons. First, the entrepreneur tries to achieve a form of second-degree price discrimina- tion; profit is thus maximized under a set of incentive compatibility and participation constraints. Second, in period 1 consumers who contemplate pre-ordering the product must form expectations regarding the number of consumers who will do likewise: the larger this number, the lower the pre- ordering price as the fixed cost will be spread over more consumers, which generates a form of network effects. We look for a subgame-perfect equilib- rium of the game played by the entrepreneur and the consumers over the two periods.

3.3.1 Consumer choices

Suppose that each consumer expects that a mass nec of consumers will choose to pre-order and pay the price p1 set by the entrepreneur in period 1. We adopt the fulfilled-expectations approach: consumers base their decision on their expectation on the mass of contributors, and attention is restricted on equilibria in which these expectations turn out to be correct (i.e., are ratio- nal; see Katz and Shapiro, 1985). Two cases have to be distinguished. First, if nec = 0, then it is optimal for each consumer not to contribute.

10 As the initial expectation is realized, we have a fulfilled expectations equilibrium. Naturally, crowdfunding is doomed to failure under such equilibrium. As some successful crowdfunding experiences exist in reality, it seems natural to assume that entrepreneurs can find some ways to coordinate consumers so that this ‘bad’ equilibrium is not selected.11

The second case is the case of interest. For any nec > 0, the entrepreneur can set p1 such as p1nec ≥ K. As there is no need to gather more capital

10This is so because each consumer is infinitesimal and thus cannot on his own make

sure that the product will be put on the market. 11Another reason to select the ‘good’ equilibrium is that it clearly Pareto-dominates the

‘bad’ equilibrium.

than needed, we have p1 = K/nec. So, if consumers expect a positive mass of contributors, they can be sure that the good will be produced.12 They also realize that the lower their expectation, the larger the value of p1, i.e., the contribution that will be asked by the entrepreneur.

To decide whether to pre-order or not, consumer θ compares his ex- pected utility in the two options. Let us consider for the moment that the entrepreneur attracts a sufficient number of regular consumers at equilib- rium: nr ≥ ρ. (Naturally, we will have to check below if this condition is actually met.) If the consumer pre-orders, he pays p1 = K/nec today and gets tomorrow a product of enhanced quality (s + σ). We can thus express the expected utility of a crowdfunder as

Uec = − K

nec + δ (r + θ (s + σ) −pc) .

If the consumer decides not to pre-order, he does not pay anything today and he gets tomorrow a product of quality s at price pr. Hence, his expected utility as regular consumer is

Uer = δ (r + θs−pr) .

So, for a consumer to contribute, we must have

Uec ≥ U e r ⇔ δ (θσ + pr −pc) ≥

nec

⇔ θ ≥ K

δσnec − pr −pc σ

≡ θ̄ (nec) .

All consumers with a value of θ larger than θ̄ (nec) prefer to pre-order. We observe logically that the mass of crowdfunders increases as (i) the expected number of contributors (nec) increases, (ii) the capital requirement (K) de- creases, (iii) the enhancement in quality (σ) resulting from pre-ordering increases, (iv) the difference between the price for regular consumers and for crowdfunders (pr −pc) increases.

To ease the exposition, we define ∆ ≡ pr−pc; that is, ∆ is the difference between the second period prices for regular consumers and crowdfunders. For a given expected mass of crowdfunders nec, the actual mass of crowd- funders is equal to nc = 1 − θ̄ (nec). We require fulfilled expectations at

12Provided that the entrepreneur does not find it profitable to run away with the contri-

butions at the start of period 2. We consider this issue in Subsection 3.5. For the moment,

we assume that the entrepreneur is able to credibly commit that she will not run away.

equilibrium: nc = nec. We must thus solve

nc = 1 + ∆ σ −

δσnc .

This equation is represented in Figure 1: solutions are the intersection between the 45◦ line (nc) and the function 1 + ∆σ −

K δσnc

, which is increasing and concave in nc. Figure 1 depicts the latter function for different values of ∆. We observe that an intersection exists as long as

∆ ≥ σ (

2 √ K/ (δσ) − 1

) ≡ ∆. (2)

To understand the meaning of this condition, let us describe what happens when it is violated. For ∆ < ∆, the price charged to crowdfunders is not sufficiently smaller than the price charged to regular consumers, so that a large value of nec is needed to convince consumers to pre-order the prod- uct; indeed, the larger the expected number of crowdfunders, the lower the price p1 each crowdfunder has to pay in period 1, which increases the at- tractiveness of pre-ordering, other things being equal. Yet, the number of consumers who actually decide to pre-order always remains smaller than the expected number, meaning that expectations cannot be fulfilled (i.e., there is no solution to the above equation). Note that the threshold ∆ logically increases with K: the higher the capital requirement, the more difficult it becomes for expectations to be fulfilled. Note also that at ∆ = ∆, there is a unique solution, which is easily computed as nc =

√ K/ (δσ). This value

is strictly lower than unity as long as K < δσ, which we assume for the moment.13 For ∆ > ∆, there are two intersections. As we expect the mass of crowdfunders to increase with ∆, we select the largest value of nc, which is computed as

nc = 1

2σ

( σ + ∆ +

√ (σ + ∆)2 − (σ + ∆)2

) . (3)

As shown in Figure 1, this value is strictly smaller than unity for ∆ < K/δ.

3.3.2 Optimal prices

Suppose for now that nc < 1. We have then that nc consumers pre-order the product at price p1 and buy it in period 2 at price pc. As for the

13For K ≥ δσ, the fulfilled-expectations equilibrium is such that all consumers become crowdfunders. This implies that there can be no regular consumers and that σ inevitably

falls to zero. This possibility is examined under Case 2b below.

K /(!")

! = !

! = K /"

Figure 1: Fulfilled expectations equilibrium

other consumers, they buy the product as long as r + θs − pr ≥ 0, or θ ≥ (pr −r) /s ≡ θ̂. If 0 < (pr −r) /s < 1 − n, the number of regular consumers is equal to nr = 1 − n − (pr −r) /s. As long as nr > ρ, the entrepreneur’s profit can be written as

π = p1nc −K︸︷︷︸ =0

+δpcnc + δprnr

= δpr

( 1 −

pr −r s

) −δ∆

1 2σ

( σ + ∆ +

√ (σ + ∆)2 − (σ + ∆)2

) ,

where the second line is obtained by substituting expression (3) for nc, and ∆ for pr −pc. It is equivalent to maximize π over pr and pc, or over pr and ∆; we choose the latter option.

It is easily found that the first-order condition with respect to pr yields the optimal value p∗r = (r + s) /2, which implies that θ̂ = (p

∗ r −r) /s =

(s−r) /2s. The derivative of profit with respect to ∆ is

dπ

d∆ = −

2σ

[ σ + 2∆ +

√ (σ + ∆)2 − (σ + ∆)2 + ∆(σ+∆)√

(σ+∆)2−(σ+∆)2

] . (4)

It is clear that the bracketed term is strictly positive for positive values

of ∆. Hence, any interior solution must be such that ∆ < 0 (i.e., that pr < pc, meaning that crowdfunders pay more than other consumers in period 2). Because of the constraint imposed by (2), this is only possible if ∆ is negative, which is equivalent to K < (δσ) /4. We therefore have to distinguish between two cases (we sketch the results here and refer the reader to the appendix for the detailed computations).

Case 1: K < (δσ) /4. In this case, we solve dπ/d∆ = 0 for ∆ and find:

∆∗ = 4K −δσ

2δ .

We verify that K < (δσ) /4 implies that ∆∗ < 0, i.e. that p∗c > p ∗ r: crowd-

funders pay more than other consumers in period 2 (we will return to this below). We also compute that the number of crowdfunders is given by n∗c = 1/2. Hence, at (p

∗ r, ∆

∗), consumers split into three groups: those with θ ∈ [0, (s−r) /2s] do not consume, those with θ ∈ [(s−r) /2s, 1/2] buy in period 2, and those with θ ∈ [1/2, 1] pre-order in period 1. We compute the equilibrium number of regular consumers as n∗r = 1/2 − (s−r) /2s = r/2s. From Assumption 4, we have that n∗r > ρ, which implies that σ > 0 as initially assumed. We then compute the optimal profit as

π = δ (r + s)2

4s + δσ

4 −K. (5)

In the present case, the capital requirement imposes no constraint what- soever on the entrepreneur. To see this, let us first compute the total price paid by crowdfunders. It is equal to p1 + δpc = δ2 (r + s + σ). Next, we observe that this is exactly the price that the entrepreneur would set if it was only selling in period 1 a product of quality (s + σ) to be delivered in period 2. Indeed, the indifferent consumer would be identified by θ0 such that −p + δ (r + θ0 (s + σ)) = 0, which is equivalent to θ0 = 1s+σ

( 1 δ p−r

) .

The entrepreneur would then maximize π = δ (p (1 −θ0)). It is easy to check that the optimal price is indeed p = 1

2 δ (r + s + σ).

Case 2: K ≥ (δσ) /4. Here, ∆ ≥ 0 under condition (2). Then, expres- sion (4) is clearly negative, meaning that the optimal choice is the lowest admissible value of ∆, i.e., ∆ = ∆ > 0. The intuition goes as follows: the higher capital requirement, combined to the fulfilled expectations require- ment, forces the entrepreneur to give a discount to crowdfunders (pc < pr)

but the entrepreneur prefers to keep this discount as small as possible. The number of crowdfunders is then given by

nc = 1 2

+ ∆ 2σ

= √ K/ (δσ) ≥

1 2 .

We see thus that the entrepreneur has to attract a larger number of crowd- funders than in the previous, unconstrained, case; this number grows with K (and remains smaller than unity as long as K < δσ).

As the number of crowdfunders grows, it is not clear whether the en- trepreneur still finds it optimal to attract a sufficient number of regular consumers in period 2. It does so as long as 1 − nc − (p∗r −r) /s ≥ ρ. As p∗r = (r + s) /2, the latter condition is equivalent to

K ≤ δσ ( r + s

2s −ρ )2 ≡ K1 (σ,ρ) .

It can be checked that Assumptions 1 and 4 ensure that K1 (σ,ρ) is com- prised between (δσ) /4 and δσ; it is also clear that K1 increases with σ and decreases with ρ. There are thus two subcases to consider.

Case 2a: (δσ) /4 ≤ K ≤ K1 (σ,ρ) . Here, as nr ≥ ρ, we have that σ > 0 for crowdfunders and we can compute the equilibrium value of pc as p∗c = p

∗ r − ∆ = (r + s) /2 − 2σ

√ K/ (δσ) + σ (which is positive under

Assumption 3). The equilibrium profit is then equal to

π = δ (r + s)2

4s + √ δσK − 2K. (6)

Case 2b: K > K1 (σ,ρ) . In this case, given nc and p ∗ r, the number of

regular consumers is too low for crowdfunders to enjoy any additional utility through ‘community benefits’. The entrepreneur faces then the following alternative: she either adjusts pr so as to keep nr above ρ and, thereby, σ > 0, or she accepts nr < ρ, σ = 0 and maximizes a different objective function. We show in the appendix that the latter option is equivalent, in terms of equilibrium profits, to traditional funding. As for the former option, the entrepreneur sets the price pr such that nr = ρ, which is equivalent to

pr = r + s−s (√

K/ (δσ) + ρ ) .

The price for crowdfunders is then computed as pc = pr − ∆ = r + s + σ − sρ−(s + 2σ)

√ K/ (δσ). It seems reasonable to exclude negative prices. We

have thus that this option is feasible as long as pc ≥ 0, which is equivalent to

K ≤ δσ ( r + s + σ −sρ

s + 2σ

)2 ≡ K2 (σ,ρ) .

We show in the appendix that Assumption 3 implies that K2 (σ,ρ) > K1 (σ,ρ). Hence, for K1 (σ,ρ) < K ≤ K2 (σ,ρ), the option of setting pr so that nr = ρ yields the following profit:

π = δ ( r + s−s

(√ K/ (δσ) + ρ

))(√ K/ (δσ) + ρ

) + √ δσK − 2K. (7)

We will show below that the latter function decreases with K. At K = K2, we have pc = 0, pr > 0 and nr = ρ > 0; it follows that the entrepreneur still earns positive profits in this extreme case. The question remains, however, whether this option is more profitable than traditional funding or not. We will examine this issue in the next section but before, we collect our results and perform some comparative statics exercises.

Summary. Combining expressions (5) to (7), we can express equilibrium profits in the crowdfunding case as

πC =

 

δ (r+s)2

4s + δσ

4 −K for K < δσ

4 ,

δ (r+s)2

4s + √ δσK − 2K for δσ

4 ≤ K ≤ K1,

( r + s−sρ−s

√ K δσ

)(√ K δσ

+ ρ )

+ √ δσK − 2K

for K1 < K ≤ K2. (8)

We show in the appendix that each segment of this profit function is a decreasing function of K and an increasing function of σ; moreover, the third segment is a decreasing function of ρ. We record these results in the following proposition.

Proposition 1 The equilibrium profit under crowdfunding decreases with the capital requirement (K) and with the minimal number of regular con- sumers required to generate community benefits (ρ); it increases with the magnitude of community benefits (σ).

The intuition behind these comparative static results is clear. The capital requirement has a twofold negative impact on profit: on the one hand, it makes production more expensive and on the other hand, it reduces the possibility to implement the optimal menu pricing scheme. An increase in

the minimal number of regular consumers required to generate community benefits also constraints price discrimination and thereby negatively affects profits. Indeed, when ρ increases, communuty benefits cannot be shared as broadly as before. Finally, if crowdfunders have a higher valuation for the community benefits, their willingness to pay increases and the entrepreneur is able to increase her margins.

3.4 Choice of funding method

Comparing expressions (8) and (1), we observe first that for small values of K (K ≤ (δσ) /4), crowdfunding clearly yields larger profits than traditional funding. The intuition is obvious: in this region of parameters, crowdfunding allows the entrepreneur to optimally price discriminate between the high- valuation crowdfunders and the remaining consumers. As the ‘enhanced quality’ σ comes at no cost for the entrepreneur, menu pricing performs better than the uniform pricing that prevails under traditional funding.

For larger values of K, however, the entrepreneur is constrained to im- plement corner solutions under crowdfunding. Here, σ is no longer a sort of ‘manna from heaven’ for the entrepreneur: several requirements constrain the prices that the entrepreneur can choose, which inevitably reduces her profits. The first constraining requirements are the network effects among crowdfunders and the imposition of fulfilled expectations. Nevertheless, crowdfunding still dominates for values of K comprised between (δσ) /4 and K1 (σ,ρ): πC −πT =

√ δσK −K, which is positive as K ≤ K1 (σ,ρ) < δσ.

Yet, an additional constraint bites for K1 (σ,ρ) < K ≤ K2 (σ,ρ), namely the minimal number of regular consumers necessary to generate the commu- nity benefits for crowdfunders (combined with the non-negativity of prices). We show in the appendix that the profit under crowdfunding may fall under the profit under traditional funding when the capital requirement becomes large enough. More precisely, we find that for K1 (σ,ρ) < K ≤ K2 (σ,ρ), πC −πT if and only if K ≤ K3 (σ,ρ), with

K3 (σ,ρ) ≡ δσ ( s(r+s+σ−2sρ)+

√ σs(4sρ(r−sρ)+σs+s2−r2) 2s(s+σ)

)2 .

We show in the appendix that K3 (σ,ρ) > K1 (σ,ρ) and that, for given values of the other parameters, there exists a value σ̂ such that K2 (σ,ρ) > K3 (σ,ρ) for σ < σ̂ and K2 (σ,ρ) < K3 (σ,ρ) for σ > σ̂. Moreover, it is intuitive that the three thresholds increase with σ and decrease with ρ.

! (r +s) 2

!T = 0

!C = !T

K3(!,")

K2(!,")

Crowdfunding

Traditional funding

No activity

s(r +s) 2r

Figure 2: Choice of funding method

We collect our results in the following proposition and we depict them in Figure 2.

Proposition 2 In situations where an entrepreneur can use crowdfunding and pre-sales to induce self-selection of high paying consumers, crowdfund- ing is preferred over traditional funding if the capital requirement is below some threshold value (i.e., K ≤ min{K2 (σ,ρ) ,K3 (σ,ρ)}). This condition becomes less stringent as community benefits become more important, either because their magnitude (σ) increases or because they are generated more easily (ρ decreases).

One important implication of Proposition 1 is that the level of addi- tional benefits accruing to the pre-ordering crowd (i.e., σ) must be suffi- ciently large. If the crowd does not enjoy any of such benefits or utility, crowdfunding does not yield any benefits over traditional funding for the entrepreneur. The parameter σ can be seen as additional utility or bene- fits from a community-based experience. Then, the lack of a community would result in a value of σ equal to zero. An important implication is the need for the entrepreneur to identify and target this community. While con- sumers with a high willingness to pay for the product may self-select into the community, the entrepreneur still needs to ensure that the “crowd” can

generate these additional benefits. The following managerial lesson can thus be drawn from our analysis: entrepreneurs who cannot identify or create a community around their products so that this community enjoys additional benefits, will hardly ever opt for crowdfunding. Indeed, we observe on Figure 2 that as σ decreases, the range of values of K for which crowdfunding is preferred narrows down.

The previous finding is consistent with many observed crowdfunding ini- tiatives. Indeed, while some offer monetary rewards, an important other form of reward is recognition or credits offered to crowdfunders. The im- portance of non-monetary benefits for crowdfunders is further stressed by the observation that at equilibrium, crowdfunders always end up paying a larger total price than regular consumers. To see this, we compute the dif- ference (p∗1 + δp

∗ c) −δp∗r in the three regimes. We find that this difference is

equal to δσ/2 for K < δσ/4, and to δσ (

1 − √ K/ (δσ)

) for K ≥ δσ/4. As

crowdfunding is not feasible for K > δσ, we check that (p∗1 + δp ∗ c) > δp

∗ r for

all admissible values of the parameters. This result is not surprising insofar as crowdfunders are high-valuation consumers and that their willingness to pay is further enhanced by the community benefits.

3.5 Take the money and run

In the previous analysis, we have abstracted away the possibility that the entrepreneur could “take the money and run” at the start of period 2, i.e., to collect p1 from the crowdfunders without incurring the fixed cost and thus, without producing the product. That is, we implicitly assumed that the en- trepreneur had some form of commitment at her disposal to guarantee her second-period activity. Absent such commitment device, consumers would only be convinced that production will take place if it is indeed in the en- trepreneur’s best interest; otherwise, no consumer would agree to pre-order the product and crowdfunding would fail. The entrepreneur’s net profit when producing must then be at least as large as the total amount that is collected at the end of period 1, i.e., K. We show in the appendix that

πC ≥ K ⇔ K ≤ K4 (σ,ρ)

with14

K4 (σ,ρ) ≡

 

δσ

( (r+s(1−2ρ)+σ)+

√ −12sσρ2+4σ(3r+2s)ρ+(r+s+σ)2

2(s+3σ)

)2 for 0 < σ ≤ σ1,

δσ 36

( 1 +

√ 1 + 3 (r+s)

σs

)2 for σ1 ≤ σ ≤

s(r+s) 2r

σ1 ≡ s(r+s)2

(r+s−2sρ)(3r+s−6sρ).

As depicted on Figure 3, K4 (σ,ρ) lies below the minimum of K2 (σ,ρ) and K3 (σ,ρ) for sufficiently large values of σ and sufficiently large values of K.15 This implies that when consumers may fear that the entrepreneur could take the money and run, crowdfunding becomes harder to implement: there exists indeed a region of parameters (characterized by high values of σ and K) where consumers will not agree to pre-order the product as they rightfully anticipate that the entrepreneur will not put the product on the market. For these parameters, traditional funding appears as the only option (assuming, of course, that banks are better equipped than crowdfunders to prevent the entrepreneur’s default). We record this result in the following proposition.

Proposition 3 When the entrepreneur has no credible way to commit that she will not run away with the money collected in period 1, crowdfunding is less likely to be preferred to traditional funding.

4 Concluding remarks

This paper sheds light on crowdfunding practices of entrepreneurial activ- ities. It stresses the need for building a community that ultimately enjoys additional private benefits from their participation to make crowdfunding a viable alternative to investor- or creditor-based funding such as through banks, business angels or even venture capital. In setting up the initiative, the entrepreneur potentially faces the following trade-off. Crowdfunding al- lows for price discrimination if pre-ordering is used. The capacity to opti- mally implement price-discrimination between pre-ordering consumers (the

14The second branch of K4 only obtains for sufficiently small values of ρ. 15Logically, K4 (σ,ρ) (where πC = K) intersects with K3 (σ,ρ) (where πC = πT ) at

K = δ (r + s) 2 / (8s), which is the value of K such that πT = K. Above this threshold,

we have that for any σ, K4 (σ,ρ) < K3 (σ,ρ).

! (r +s) 2

!T = 0

!C = !T

K3(!,")

K2(!,")

Crowdfunding

Traditional funding

No activity

s(r +s) 2r

K4(!,")

!C = K

Figure 3: Funding method if the entrepreneur can take the money and run

crowdfunders) and other consumers may however be constrained by the amount of capital that the entrepreneur needs to raise to cover the up-front (fixed) costs. Whenever this amount exceeds some threshold, the distortion in the price discrimination becomes excessive, in which case the profitability of the crowdfunding initiative is reduced and the entrepreneur may be better off approaching a single, larger investor (a bank or a large equity investor) who can cover the full costs on its own.

To our knowledge, this is the very first study offering a theoretical anal- ysis of crowdfunding. It also highlights new follow-up research questions on the topic. For instance, an interesting avenue for future research is to incorporate the fact that the crowdfunders can at times also participate in strategic decisions or even have voting rights. In this case, control rights and voting power become an additional benefit for the participating crowd. Crowdfunding through pre-ordering will have a very different effect on in- formation and voting results than if the crowd purchases equity in the en- trepreneurial firm. Also, outcomes of votes can provide valuable insights into the optimal design of products if the voting community is representative for the overall population of end-consumers.

Future works may further explore information motivations of entrepreneurs. Indeed, while the primary goal of crowdfunding is certainly to raise money, it may also help firms in testing, promoting and marketing their products,

in gaining a better knowledge of their consumers’ tastes, or in creating new products or services altogether. In this sense, crowdfunding can be used as a promotion device, as a means to support mass customization or user-based innovation, or as a way for the producer to gain a better knowledge of the preferences of its consumer. Crowdfunding seems thus to have implications that go beyond the financial sphere of an organization: it also affects the flow of information between the organization and its customers.

In any case, a strong advantage of this form of financing is the attention that the entrepreneur may attract on his/her project or company. This can become a vital asset for many of them, especially for artists or entrepreneurs in need to present their talent and product to the crowd (as potential cus- tomers). In other cases, it is a unique way to validate original ideas in front of a specifically targeted audience. This may in turn provide insights into market potential of the product or service offered. From this perspective, crowdfunding may be viewed as a broader concept than purely raising funds: it is a way to develop corporate activities through the process of fundraising.

Also, several platforms have emerged recently, such as IndieGoGo, Kick- starter, Sandawe, SellaBand, MyMajorCompany and Artistshare. These platforms intermediate between entrepreneurs and potential crowdfunders. Therefore, a distinction can be made between direct and indirect fundraising because at times entrepreneurs make use of such crowdfunding platforms in- stead of seeking direct contact with the crowd. These platforms share some similarities with online lending markets (Everett, 2008; Freedman and Jin, 2010); while the latter more prominently target social entrepreneurship, crowdfunding platforms have a broader scope of entrepreneurial initiatives. Our understanding of the role played by platforms is still limited; it is worth investigating the extent to which platforms increase the chances of success of crowdfunding initiatives or solve asymmetric information issues. As an example, for crowdfunders, platforms may facilitate in learning the quality of the product through the possible interaction between crowdfunders (e.g., via other crowdfunder comments on a forum) or by observing the contribu- tions of other crowdfunders. More research could be done along the line of peer effects as it relates to crowdfunding platforms, as suggested by Ward and Ramachandran (2010).

From a more general perspective, crowdfunding practices raise questions with respect to corporate governance and investor protection issues if most

individuals only invest tiny amounts. Crowdfunders are most likely to be offered very little investor protection. This may lead to corporate gover- nance issues, which in turn may entail reputation concerns if some cases of fraud or bad governance are uncovered. Crowdfunders have very little scope to intervene to protect their interests as stakeholders. Moreover, the fact that their investment is small is likely to create a lack of incentive to inter- vene. Therefore, trust-building is an essential ingredient for any successful crowdfunding initiative. It is also not a surprise that many of the observed crowdfunded initiatives are either project-based or based on donations. In many cases, the financial return seems to be of secondary concern for those who provide funds. This suggests that crowdfunders care about social rep- utation or enjoy private benefits from participating in the success of the initiative (Glaeser and Shleifer, 2001; Ghatak and Mueller, 2011).

5 Appendix

We give here the details of the mathematical developments that we sketched in the text.

5.1 Optimal prices under crowdfunding

Case 1. If K < (δσ) /4, then there may exist a value of ∆ ≥ ∆ that solves dπ/d∆ = 0, or

σ + 2∆ + √

(σ + ∆)2 − (σ + ∆)2 + ∆(σ+∆)√ (σ+∆)2−(σ+∆)2

= 0 ⇔

√ (σ + ∆)2 − (σ + ∆)2 =

(σ + ∆)2

σ + 2∆ − (σ + ∆) (9)

As long as the RHS is positive, we can take the square of the two sides of the equality:

(σ + ∆)2 − (σ + ∆)2 = (σ + ∆)4

(σ + 2∆)2 + (σ + ∆)2 − 2

(σ + ∆) (σ + ∆)2

σ + 2∆ ,

which, after simplification, yields

∆∗ = 1

2σ

[ (σ + ∆)2 −σ2

] =

1 2δ

(4K −δσ) .

We still need to check whether condition (2) is satisfied:

1 2σ

[ (σ + ∆)2 −σ2

] > ∆ ⇔ 2σ∆ + ∆2 > 2σ∆,

which is true. We also need to check that the RHS of expression (9) is positive, as we assumed it. We compute

(σ + ∆)2

σ + 2∆ > (σ + ∆) ⇔

4σK/δ 4K/δ

> 4K + δσ

2δ ⇔ 2δσ > 4K + δσ ⇔ K < δσ/4

which is true. To proceed, we compute

σ + ∆∗ = 1

2σ

[ (σ + ∆)2 + σ2

] ,√

(σ + ∆∗)2 − (σ + ∆)2 = 1

2σ

[ σ2 − (σ + ∆)2

] .

It follows that

n∗ = 1

2σ

( 1

2σ

[ (σ + ∆)2 + σ2

] +

1 2σ

[ σ2 − (σ + ∆)2

]) =

1 2 .

Recall that we need

pr −r s

< 1 −n ⇔ s−r s

< 1 2 ⇔ s < 2r,

which is guaranteed by Assumption 1. We can now compute the optimal profit:

π = δ (r + s)2

4s −δ∆∗

1 2σδ

(δ (σ + ∆∗) −δ∆∗)

= δ (r + s)2

4s + δσ

4 −K.

Case 2. We first have to establish under which condition there is a suffi- cient number of regular consumers. We need 1 − nc − (p∗r −r) /s ≥ ρ. As nc =

√ K/ (δσ) and p∗r = (r + s) /2, the condition can be rewritten as

1 − √ K

δσ − s−r

2s ≥ ρ ⇔ K ≤ δσ

( r + s

2s −ρ )2 ≡ K1 (σ,ρ) .

We compute

K1 (σ,ρ) − δσ

4 =

σδ (r + 2s− 2sρ) (r − 2sρ) 4s2

> 0,

δσ −K1 (σ,ρ) = σδ (r + 3s− 2sρ) (s + 2sρ−r)

4s2 > 0,

which are both positive because of Assumptions 1 (s > r) and 4 (ρ < r/ (2s)).

Case 2a: (δσ) /4 ≤ K ≤ K1 (σ,ρ) . We need to show that p∗c = p∗r − ∆ = (r + s) /2 − 2σ

√ K/ (δσ) + σ ≥ 0. This condition is equivalent to

K ≤ δσ ( r + s + 2σ

4σ

)2 ≡ K5 (σ,ρ) .

We have K5 (σ,ρ) > K1 (σ,ρ) if and only if

r + s + 2σ 4σ

> r + s

2s −ρ ⇔ ρ > −

s (r + s) − 2rσ 4sσ

≡ ρ̃.

Assumption 3, i.e., σ < s (r + s) / (2r), implies that ρ̃ < 0 and hence, that the inequality is satisfied, meaning that p∗c > 0 when K ≤ K1 (σ,ρ).

Case 2b: K > K1 (σ,ρ) . We showed in the text that pc ≥ 0 as long as

K ≤ δσ ( r + s + σ −sρ

s + 2σ

)2 ≡ K2 (σ,ρ) .

We have that K2 (σ,ρ) > K1 (σ,ρ) is equivalent to

r + s + σ −sρ s + 2σ

> r + s

2s −ρ ⇔

s (r + s) − 2rσ + 4sσρ 2s (s + 2σ)

> 0,

which is true under Assumption 3 as 2rσ < s (r + s). We also need to show that when the entrepreneur accepts nr < ρ (which

implies σ = 0), she achieves the same profit as under traditional funding. Suppose first that the entrepreneur decides to attract no regular consumer whatsoever. She can do so by setting p > r + s. In that case, a consumer decides to pre-order the product (which is the only option) if

− K

nec + δ (r + θs−pc) ≥ 0 ⇔ θ ≥

δsnec − r −pc s

As we require fulfilled expectations, we must have

nc = 1 − K

δsnc + r −pc s

Solving the latter equation and keeping the largest root, we have

n = δ (r + s−pc) +

√ δ2 (r + s−pc)2 − 4δsK 2δs

which is valid as long as pc ≤ r + s− 2 √ sK/δ.

The entrepreneur choose pc to maximize

π = pc δ (r + s−pc) +

√ δ2 (r + s−pc)2 − 4δsK 2δs

Solving for the first-oder condition, we find the optimal price as

pc = r + s

2 −

2s δ (r + s)

and we check that it is indeed no larger than r + s− 2 √ sK/δ as required.

We can then compute the number of consumers as n = (r + s) / (2s) and the optimal profit as:

π = δ ( r + s

2 −

2s δ (r + s)

) r + s

2s = δ

(r + s)2

4s −K = πT .

Alternatively, the entrepreneur could still attract some regular consumers (but less than ρ). To do so, she must set pr < r + s. A consumer would then choose to pre-order the product if

− K

nec + δ (r + θs−pc) ≥ δ (r + θs−pr) ⇔

nec ≤ δ (pr −pc) ,

which is clearly impossible if pc ≥ pr. Suppose then pc < pr. The latter condition can we rewritten as

nec ≥ K

δ (pr −pc) .

Expectations are no longer an issue in the present case. Taking nc = K/(δ (pr −pc)), we express the entrepreneur’s profit as

π = δpc K

δ (pr −pc) +δpr

( 1 −

δ (pr −pc) − pr −r s

) = δpr

( 1 −

pr −r s

) −K,

which is exactly the same profit function as under traditional funding; this completes our proof.

5.2 Proof of Proposition 1

We have that profits under crowdfunding are equal to πC1 for K < δσ4 , to πC2 for δσ4 ≤ K ≤ K1, and to πC3 for K1 < K ≤ K2, with

πC1 = δ (r+s)2

4s + δσ

4 −K,

πC2 = δ (r+s)2

4s + √ δσK − 2K,

πC3 = δ ( r + s−sρ−s

√ K δσ

)(√ K δσ

+ ρ )

+ √ δσK − 2K.

It is obvious that πC1 increases with σ and decreases with K. As for πC2, it clearly increases with σ while its derivative with respect to K is equal to

∂πC2 ∂K

= √ δσ

1 2 √ K − 2.

The latter expression is negative if K > δσ/16, which is the case here. Regarding πC3, we first compute:

∂πC3 ∂K

= (r + s + σ − 2sρ)

√ σδK − 2 (s + 2σ) K

2σK .

The latter expression is negative if and only if

K > δσ

( r + s + σ − 2sρ

2 (s + 2σ)

)2 ≡ K6 (σ,ρ) .

We consider here values of K > K1 (σ,ρ). Let us show that Assumption 4, i.e., ρ < r/ (2s), makes sure that K1 (σ,ρ) > K6 (σ,ρ). The latter condition is equivalent to

r + s 2s −ρ−

r + s + σ − 2sρ 2 (s + 2σ)

= 1 2 σ

2 (r − 2sρ) + s s (s + 2σ)

> 0.

Second, we have

∂πC3 ∂σ

= 2sK − (r − 2sρ + s−σ)

√ σδK

2σ2 .

If σ > r − 2sρ + s, then the latter expression is clearly positive. Otherwise, it is positive as long as

K > δσ

( r − 2sρ + s−σ

)2 ≡ K7 (σ,ρ) .

We show again that K1 (σ,ρ) > K7 (σ,ρ), which is equivalent to

r + s 2s −ρ−

r − 2sρ + s−σ 2s

= σ

2s > 0.

Finally, we compute

∂πC3 ∂ρ

= δ

( r + s− 2sρ− 2s

√ K

σδ

) .

This expression is negative for

K > δσ

( r + s− 2sρ

)2 = K1 (σ,ρ) ,

which completes the proof.

5.3 Proof of Proposition 2

We first derive the value of K such that π3C = πT .

( r + s−sρ−s

√ K

δσ

)(√ K

δσ + ρ

) + √ δσK − 2K = δ

(r + s)2

4s −K ⇔

−(s + σ) K+(r + s + σ − 2sρ) √ δσ √ K+δσ (r + s−sρ) ρ−δσ

(r + s)2

4s = 0.

This second-degree polynomial in √ K has real roots as long as

(r + s + σ − 2sρ)2 δσ + 4 (s + σ) ( δσ (r + s−sρ) ρ−δσ (r+s)

) =

σ2δ s

( 4sρ (r −sρ) + sσ + s2 −r2

) > 0,

which is satisfied under Assumptions 1 and 4. The roots are then given by

√ K =

√ δσ s (r + s + σ − 2sρ) ±

√ σs (4sρ (r −sρ) + σs + s2 −r2)

2s (s + σ) .

Some lines of computations establish that both roots are positive and that δσ (r + s−sρ) ρ < δσ (r+s)

4s under our assumptions. It follows that πC3 > πT

if and only if

δσ

( s(r+s+σ−2sρ)−

√ σs(4sρ(r−sρ)+σs+s2−r2) 2s(s+σ)

)2 < K

< δσ

( s(r+s+σ−2sρ)+

√ σs(4sρ(r−sρ)+σs+s2−r2) 2s(s+σ)

)2 = K3 (σ,ρ) .

We establish now that K1 (σ,ρ) lies between these two bounds. First, the upper bound (i.e., K3) being larger than K1 (σ,ρ) is equivalent to

s(r+s(1−2ρ)+σ)+ √ σs(4sρ(r−sρ)+σs+s2−r2)

2s(s+σ) >

r + s 2s −ρ ⇔√

σs (4sρ (r −sρ) + σs + s2 −r2) > σ (r − 2sρ) ⇔

σ (s−r + 2sρ) (r − 2sρ + s) (s + σ) > 0,

which is satisfied under Assumptions 1 (s > r) and 4 (ρ < r/ (2s)). As for the lower bound being smaller than K1 (σ,ρ), this is so if

s(r+s(1−2ρ)+σ)− √ σs(4sρ(r−sρ)+σs+s2−r2)

2s(s+σ) <

r + s 2s −ρ ⇔√

σs (4sρ (r −sρ) + σs + s2 −r2) > −σ (r − 2sρ) ,

which is clearly satisfied under Assumption 4. We can thus state that when K > K1 (σ,ρ),

πC > πT ⇔ K ≤ δσ ( s(r+s+σ−2sρ)+

√ σs(4sρ(r−sρ)+σs+s2−r2) 2s(s+σ)

)2 = K3 (σ,δ) .

We show next that for given values of the other parameters, there exists a value σ̂ such that K2 (σ,ρ) > K3 (σ,ρ) for σ < σ̂ and K2 (σ,ρ) < K3 (σ,ρ) for σ > σ̂. For δσ > 0, we have

K2 (σ,ρ)−K3 (σ,ρ) ∝ r+s+σ−sρs+2σ − s(r+s(1−2ρ)+σ)+

√ σs(−4s2ρ2+4rsρ+s2−r2+σs) 2s(s+σ)

The latter expression tends to (r + s) / (2s) when σ tends to zero, and to −1/2 when σ tends to infinity. As both K2 and K3 are increasing functions of σ, there exists a value of σ below which K2 > K3 and above which K3 > K2. Numerical simulations suggest that this cutoff value of σ is smaller than s (r + s) / (2r), i.e., the upper bound we have assumed for σ.

5.4 Proof of Proposition 3

Recall that profits under crowdfunding are equal to πC1 for K < δσ4 , to πC2 for δσ

4 ≤ K ≤ K1, and to πC3 for K1 < K ≤ K2, with

πC1 = δ (r+s)2

4s + δσ

4 −K,

πC2 = δ (r+s)2

4s + √ δσK − 2K,

πC3 = δ ( r + s−sρ−s

√ K δσ

)(√ K δσ

+ ρ )

+ √ δσK − 2K.

We need to check under which conditions πC ≥ K. We first have that πC1 ≥ K if and only if

δ (r+s)2

4s + δσ

4 > 2K ⇐⇒ K < 1

( δ

(r+s)2

4s + δσ

) .

The latter threshold is larger than δσ 4

provided that

1 2

( δ

(r+s)2

4s + δσ

) − δσ

4 = δ

( (r + s)2 −σs

) > 0.

The latter condition is satisfied because of Assumptions 1 and 3; we have indeed that s (r + s) / (2r) < (r + s)2 /s. It follows that in the space of parameters that we consider, πC1 > K.

Next, we find that πC2 ≥ K if and only if

−3K + √ δσ √ K + δ (r+s)

4s > 0.

This polynomial has one negative and one positive real root; as the polyno- mial is positive for K = 0, we have that the condition for πC2 ≥ K is

√ K ≤ 1

(√ δσ +

√ δσ + 3δ (r+s)

) or equivalently

K ≤ δσ 36

( 1 +

√ 1 + 3 (r+s)

σs

)2 ≡ K8 (σ,ρ) .

Is the latter condition more or less stringent than K ≤ K1 (σ,ρ)? We compute

K1 > K8 ⇔ r+s2s −ρ > 1 6

( 1 +

√ 1 + 3 (r+s)

σs

) ⇔ σ > s(r+s)

(3r+s−6sρ)(r+s−2sρ) = σ1 (ρ) .

Whether σ1 (ρ) is above or below s (r + s) / (2r) depends on the value of ρ. It can be checked that σ1 (ρ) increases with ρ and σ1 (0) =

s(r+s) 3r+s

< s(r+s)

while σ1 ( r 2s

) = (r+s)

s >

s(r+s) 2r

. The exact cutoff value is 0 < ρ̂ < r 2s

, with

ρ̂ = 3r + 2s−

√ 6r2 + 6rs + s2

6s .

Finally, we find that πC3 ≥ K if and only if

( r + s−sρ−s

√ K

δσ

)(√ K

δσ + ρ

) + √ δσK ≥ 3K.

Developing this inequality, we find that it is equivalent to

K < δσ

( (r+s(1−2ρ)+σ)+

√ −12sσρ2+4σ(3r+2s)ρ+(r+s+σ)2

2(s+3σ)

)2 = K9 (σ,ρ) .

Unsurprisingly, we find that K9 > K1 for σ < σ1 (ρ). We have thus that K8 (σ,ρ) and K9 (σ,ρ) constitute the two branches of K4 (σ,ρ) as described in the text.

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autonomy and educational performance: within-country evidence. 2010/83. Dunia LOPEZ-PINTADO. Influence networks. 2010/84. Per AGRELL and Axel GAUTIER. A theory of soft capture. 2010/85. Per AGRELL and Roman KASPERZEC. Dynamic joint investments in supply chains under

information asymmetry. 2010/86. Thierry BRECHET and Pierre M. PICARD. The economics of airport noise: how to manage

markets for noise licenses. 2010/87. Eve RAMAEKERS. Fair allocation of indivisible goods among two agents. 2011/1. Yu. NESTEROV. Random gradient-free minimization of convex functions. 2011/2. Olivier DEVOLDER, François GLINEUR and Yu. NESTEROV. First-order methods of

smooth convex optimization with inexact oracle. 2011/3. Luc BAUWENS, Gary KOOP, Dimitris KOROBILIS and Jeroen V.K. ROMBOUTS. A

comparison of forecasting procedures for macroeconomic series: the contribution of structural break models.

2011/4. Taoufik BOUEZMARNI and Sébastien VAN BELLEGEM. Nonparametric Beta kernel estimator for long memory time series.

2011/5. Filippo L. CALCIANO. The complementarity foundations of industrial organization. 2011/6. Vincent BODART, Bertrand CANDELON and Jean-François CARPANTIER. Real exchanges

rates in commodity producing countries: a reappraisal. 2011/7. Georg KIRCHSTEIGER, Marco MANTOVANI, Ana MAULEON and Vincent

VANNETELBOSCH. Myopic or farsighted? An experiment on network formation. 2011/8. Florian MAYNERIS and Sandra PONCET. Export performance of Chinese domestic firms: the

role of foreign export spillovers. 2011/9. Hiroshi UNO. Nested potentials and robust equilibria. 2011/10. Evgeny ZHELOBODKO, Sergey KOKOVIN, Mathieu PARENTI and Jacques-François

THISSE. Monopolistic competition in general equilibrium: beyond the CES. 2011/11. Luc BAUWENS, Christian HAFNER and Diane PIERRET. Multivariate volatility modeling of

electricity futures. 2011/12. Jacques-François THISSE. Geographical economics: a historical perspective. 2011/13. Luc BAUWENS, Arnaud DUFAYS and Jeroen V.K. ROMBOUTS. Marginal likelihood for

Markov-switching and change-point GARCH models. 2011/14. Gilles GRANDJEAN. Risk-sharing networks and farsighted stability. 2011/15. Pedro CANTOS-SANCHEZ, Rafael MONER-COLONQUES, José J. SEMPERE-MONERRIS

and Oscar ALVAREZ-SANJAIME. Vertical integration and exclusivities in maritime freight transport.

2011/16. Géraldine STRACK, Bernard FORTZ, Fouad RIANE and Mathieu VAN VYVE. Comparison of heuristic procedures for an integrated model for production and distribution planning in an environment of shared resources.

2011/17. Juan A. MAÑEZ, Rafael MONER-COLONQUES, José J. SEMPERE-MONERRIS and Amparo URBANO Price differentials among brands in retail distribution: product quality and service quality.

Recent titles CORE Discussion Papers - continued

2011/18. Pierre M. PICARD and Bruno VAN POTTELSBERGHE DE LA POTTERIE. Patent office

governance and patent system quality. 2011/19. Emmanuelle AURIOL and Pierre M. PICARD. A theory of BOT concession contracts. 2011/20. Fred SCHROYEN. Attitudes towards income risk in the presence of quantity constraints. 2011/21. Dimitris KOROBILIS. Hierarchical shrinkage priors for dynamic regressions with many

predictors. 2011/22. Dimitris KOROBILIS. VAR forecasting using Bayesian variable selection. 2011/23. Marc FLEURBAEY and Stéphane ZUBER. Inequality aversion and separability in social risk

evaluation. 2011/24. Helmuth CREMER and Pierre PESTIEAU. Social long term care insurance and redistribution. 2011/25. Natali HRITONENKO and Yuri YATSENKO. Sustainable growth and modernization under

environmental hazard and adaptation. 2011/26. Marc FLEURBAEY and Erik SCHOKKAERT. Equity in health and health care. 2011/27. David DE LA CROIX and Axel GOSSERIES. The natalist bias of pollution control. 2011/28. Olivier DURAND-LASSERVE, Axel PIERRU and Yves SMEERS. Effects of the uncertainty

about global economic recovery on energy transition and CO2 price. 2011/29. Ana MAULEON, Elena MOLIS, Vincent J. VANNETELBOSCH and Wouter VERGOTE.

Absolutely stable roommate problems. 2011/30. Nicolas GILLIS and François GLINEUR. Accelerated multiplicative updates and hierarchical

als algorithms for nonnegative matrix factorization. 2011/31. Nguyen Thang DAO and Julio DAVILA. Implementing steady state efficiency in overlapping

generations economies with environmental externalities. 2011/32. Paul BELLEFLAMME, Thomas LAMBERT and Armin SCHWIENBACHER. Crowdfunding:

tapping the right crowd.

Books P. VAN HENTENRYCKE and L. WOLSEY (eds.) (2007), Integration of AI and OR techniques in constraint

programming for combinatorial optimization problems. Berlin, Springer. P-P. COMBES, Th. MAYER and J-F. THISSE (eds.) (2008), Economic geography: the integration of

regions and nations. Princeton, Princeton University Press. J. HINDRIKS (ed.) (2008), Au-delà de Copernic: de la confusion au consensus ? Brussels, Academic and

Scientific Publishers. J-M. HURIOT and J-F. THISSE (eds) (2009), Economics of cities. Cambridge, Cambridge University Press. P. BELLEFLAMME and M. PEITZ (eds) (2010), Industrial organization: markets and strategies. Cambridge

University Press. M. JUNGER, Th. LIEBLING, D. NADDEF, G. NEMHAUSER, W. PULLEYBLANK, G. REINELT, G.

RINALDI and L. WOLSEY (eds) (2010), 50 years of integer programming, 1958-2008: from the early years to the state-of-the-art. Berlin Springer.

G. DURANTON, Ph. MARTIN, Th. MAYER and F. MAYNERIS (eds) (2010), The economics of clusters – Lessons from the French experience. Oxford University Press.

J. HINDRIKS and I. VAN DE CLOOT (eds) (2011), Notre pension en heritage. Itinera Institute.

CORE Lecture Series D. BIENSTOCK (2001), Potential function methods for approximately solving linear programming

problems: theory and practice. R. AMIR (2002), Supermodularity and complementarity in economics. R. WEISMANTEL (2006), Lectures on mixed nonlinear programming.

My skills

Communication = Excellent

Teamwork = Excellent

Initiative = Excellent

Problem solving = Excellent

Flexibility = Excellent

Computer skills = Very good

Technical skills = Very good

-English = good ( writing- reading- speaking)

-Arabic = Excellent ( writing- reading- speaking)

ورقة1

Name of course	Offered by	Location	the period	Overview Course
1- Six Segma	(International Center for Strategic Management & Organizational Development) &University of California Irvine Extension	Irvine, CA	30 March to 7 April 2013	One successful business management strategy used by business enterprises is called six sigma. This strategy was developed and used originally by Motorola in the year 1986. Motorola is a renowned multinational telecommunications company. By the year 2010, this strategy was being used by many industry sectors. It is a high-performance approach that is data-driven. In this article, various Six Sigma goals are discussed. The Six Sigma strategy uses a number of quality management methods. Such methods include specific training used to create special infrastructures of certified individuals in the organization who are experts in these methods. These individuals are referred to as ‘belts’; yellow, green, black, or master black depending on their expertise. Such experts focus their attention on projects. This helps in getting things done in an organized, teamwork-based fashion and assures quality end products or services. One of the major goals of this strategy is quality control. The enterprise reviews quality of all factors involved in production. It places emphasis on elements like job management, controls, performance and integrity criteria. It also puts into place well managed and defined processes, as well as identification records. The Six Sigma Process also places a large emphasis competence, skills, knowledge, qualifications and experience of personnel. The aim is to identify, analyze and remove causes of errors and defects in the organization. By so doing, 6 Sigma delivers real improvements in terms of quality and revenue. As a result, the bottom line of the enterprise is affected positively. Another goal of this strategy is total quality management. This management philosophy aims at improving quality of processes and products continuously. It assumes that the quality of processes and products is the responsibility of any and every person involved in the consumption and creation of the service or products offered by an enterprise. It capitalizes on the involvement of customers, suppliers, workforce and management in order to exceed or meet the expectations of customers. The ultimate goal of Six Sigma lies in zero defects within the products or services offered by an organization. A sigma rating can be used to describe the maturity of manufacturing processes. This rating indicates the yield or percentage of products the particular process creates that are defect-free. Over 99.99 percent of the outputs are expected to be defect-free statistically when it comes to 6 Sigma, or more specifically, less than 3.4 defects per million opportunities. Defects are defined as any output that does not meet the specifications of customers. By having such high quality output, a process, and therefore, a company, can meet or exceed the requirements or specifications of its customers. Another Six Sigma Goal includes reducing variability in business and manufacturing processes. This is done by ensuring that each project carried out by the organization follows defined steps in a sequence. This shrinks the process variations dramatically. It also sets financial targets that are quantified such as profit increase or cost reduction. There are many other Six Sigma goals. The overall objective of this strategy is to expand a company's top line performance. This enables that company to drive the growth of its bottom line. The data-driven approach of analyzing the root causes of defects helps to deliver real improvements to the bottom line of the enterprise. Evidenced by the success attributed to those enterprises that have used it, it is clear that the techniques and tools the Six Sigma system provides are effective.
2- Financial Management	Chicago Analytics& Regent Park Institute Excellence in Education	Irvine, CA	1 day course ( 8th of July 2012)	What are the goals of Financial Management? The financial management has to take three important decision viz. (i) Investment decision i.e., where to invest fund and in what amount, (ii) Financing decision i.e., from where to raise funds and in what amount, and (iii) Dividend i.e., how much to pay dividend and how much to retain for future expansion. In order to make these decisions the management must have a clear understanding of the objective sought to be achieved. It is generally agreed that the financial objective of the firm should be maximization of owner's economic welfare. There are two widely discussed approaches or criterion of maximizing owners' welfare -(i) Profit maximization, and (ii) Wealth maximization. It should be noted here that objective is used in the sense of goal or goals or decision criterion for the three decisions involved. Profit Maximization: Maximization of profits is very often considered as the mainobjective of a business enterprise. The shareholders, the owners of the business, invest their funds in the business with the hope of getting higher dividend on their investment. Moreover, the profitability of the business is an indicator of the sound health of the organisation, because, it safeguards the economic interests of various social groups which are directly or indirectly connected with the company e.g. shareholders, creditors and employees. All these parties must get reasonable return for their contributions and it is possible only when company earns higher profits or sufficient profits to discharge the obligations to them. Wealth Maximization: The wealth maximization (also known as value maximization or Net Present Worth Maximization) is also universally accepted criterion for financial decision making. The value of an asset should be viewed in terms of benefits it can produce over the cost of capital investment. Prof. Era Solomon has defined the concept of wealth maximization as follows- "The gross present worth of a course of action is equal to the capitalized value of the flow of future expected benefits, discounted (or as capitalized) at a rate which reflects their certainty or uncertainty. Wealth or net amount of capital investment required to achieve the benefits being discussed. Any financial action which creates wealth or which has a net present worth above zero is a desirable one and should be undertaken. Any financial action which does not meet this test should be rejected. If two or more desirable courses of action are mutually exclusive (i.e., if only one can be undertaken) then the decision should be to do that which creates most wealth or shows the greatest amount of net present worth. In short, the operating objective for financial management is to maximize wealth or net present worth. Thus, the concept of wealth maximization is based on cash flows (inflows and outflows) generated by the decision. If inflows are greater than outflows, the decision is good because it maximizes the wealth of the owners.
3-Project Mahagment Mastery	uland stanford junior university	Irvine, CA	28th and 29th of April 2012	Project Management and Goal Setting Identifying actionable goals can be difficult if you don’t know what you want to achieve and if you don’t have a process in place. As engineers, we know that every successful project has a clearly defined project statement, scope, and process to deliver the intended results. The skills of project management, which we’ve developed delivering projects, can also be applied to defining and delivering our most important goals. Project management uses an easy five-step process to guide projects from concept through final delivery. This process is successful in delivering projects in the work place and you canuse it in delivering your projects as well. Applying the principals of project management, you can define and deliver your most important goals. The process includes these steps: Initiating. You initiate by defining your goal statement. Your goal statement includes all major deliverables, assumptions, objectives, constraints, stakeholders, and end date. Just like projects, the goal you’re aiming at may have more than one phase, so identify these and any major milestones as well. Planning. With the goal statement in mind, turn to planning the resources, the duration, how to overcome constraints, who you’ll need to work with, what alternatives do you need to consider and plan for, what risks are involved, and how each deliverable will be created. The planning may be specific if you know all of the possible parameters involved, or can be elaborated as more information becomes available. Executing. This step is simple: take action. Begin immediately executing your plan. Monitoring & Controlling. In projects we use quality control and assurance to ensure the project work is proceeding as planned. Measures of time, cost, and scope are typically used to identify if a project is on plan or not. Depending on the complexity or your goals, you may be concerned about these same quantitative parameters. Or you may be more interested in the qualitative factors associated with achieving your goals, such as the satisfaction that comes from working towards achieving what’s most important to you. Closing. Success isn’t achieved until the project is complete, whether in the work place or in our own lives. Your goal statement included deliverables, objectives and an end date. Closing out your goal requires that you meet these three elements. Project Management and Goal Setting Identifying actionable goals can be difficult if you don’t know what you want to achieve and if you don’t have a process in place. As engineers, we know that every successful project has a clearly defined project statement, scope, and process to deliver the intended results. The skills of project management, which we’ve developed delivering projects, can also be applied to defining and delivering our most important goals. Project management uses an easy five-step process to guide projects from concept through final delivery. This process is successful in delivering projects in the work place and you canuse it in delivering your projects as well. Applying the principals of project management, you can define and deliver your most important goals. The process includes these steps: Initiating. You initiate by defining your goal statement. Your goal statement includes all major deliverables, assumptions, objectives, constraints, stakeholders, and end date. Just like projects, the goal you’re aiming at may have more than one phase, so identify these and any major milestones as well. Planning. With the goal statement in mind, turn to planning the resources, the duration, how to overcome constraints, who you’ll need to work with, what alternatives do you need to consider and plan for, what risks are involved, and how each deliverable will be created. The planning may be specific if you know all of the possible parameters involved, or can be elaborated as more information becomes available. Executing. This step is simple: take action. Begin immediately executing your plan. Monitoring & Controlling. In projects we use quality control and assurance to ensure the project work is proceeding as planned. Measures of time, cost, and scope are typically used to identify if a project is on plan or not. Depending on the complexity or your goals, you may be concerned about these same quantitative parameters. Or you may be more interested in the qualitative factors associated with achieving your goals, such as the satisfaction that comes from working towards achieving what’s most important to you. Closing. Success isn’t achieved until the project is complete, whether in the work place or in our own lives. Your goal statement included deliverables, objectives and an end date. Closing out your goal requires that you meet these three elements.
4- Why Housing Development Cost So Much?	Housing Opportunities Made Easier & Housing Issues Forum	Camarillo, CA	15-Oct-13	Last year the federal government doled out nearly $2 billion in
				funding to public agencies across the country for the creation of
				affordable housing.
				That doesn’t include the millions of additional dollars that the
				states allocate to the projects in the form of set-aside property
				tax revenues and federal and state tax credits to firms that
				invest in the housing projects.
				place to live at a subsidized cost, the underlying goal behind all
				this funding is clearly well intentioned.
				But when it comes to how public agencies spend all that cash, it
				can leave a lot to be desired.
				A closer look at the affordable housing industry nationwide
				reveals a tangled web of rapidly rising construction costs,
				misspent funds, and in some cases, major fraud allegations
				against public officials and housing developers. And all that that
				ultimately means fewer housing units are being built to help
				house the nation’s poorest residents.
				So where are public officials going wrong?
				Here’s a rundown of the factors fueling the massive cost of
				creating affordable housing and what some agencies are doing
				to try to combat it.
				A new affordable housing philosophy
				In many cases these new developments are nothing like what
				many people think of when they think of public
				housing “projects.”
				Facing increasing city and state regulations and the hurdle of
				convincing often-less-than-welcoming residents, many public
				housing developers have added a host of sustainable building
				and design features to their housing projects — ranging from
				solar panels and expansive fitness centers to parks and
				amphitheaters.
				Nonprofit news site Voice of San Diego reported on the massive
				cost of affordable housing construction in a July special report
				titled “The Game: Building ‘Taj Mahals with Taxpayer Money.”
				“Far from the ugly concrete towers of the past, today’s
				affordable housing projects are often the best-designed, most
				beautiful buildings in their neighborhoods.”
				And this philosophy can be seen in other cities across the
				country, such as in New York City where a recent NY Times
				architecture review hailed the new Via Verde development as an
				architectural gem.
				“Unlike so many public-housing projects, Via Verde rethinks the
				mix of private and public spaces to encourage residents to
				spend time outside, in the fresh air. It breaks the mold of
				subsidized housing whereby clinics, low-income rentals and
				home ownership are all conceived, financed and regulated
				separately. Piecing them together, it takes the healthier, holistic
				tack. Healthy design comes down to fundamentals in this case:
				air, light, places to stroll, things to look at.
				Which is Via Verde’s other distinction: its premium on looks.”
				Supporters hail the changes as a massive improvement over the
				often poorly designed public housing projects of decades past.
				They point out that in many ways these buildings serve a variety
				of purposes beyond providing affordable housing, such as
				removing blight or adding important green space to dense
				urban areas
				But it comes at a cost.
				Many of these projects have hefty price tags, reaching into the
				tens of millions, to house only a few hundred families, if that.
				In San Diego, for example, construction costs have reached as
				$477,000 per unit, double what private developers spend to
				develop high-end apartments, according to the Voice of San
				Diego investigation.
				Some public officials argue that spending so much on single
				units misses the point of providing as much affordable housing
				as possible.
				In Glendale, Calif. where I used to work as a City Hall beat
				reporter, Mayor Ara Najarian often questioned the city’s policy
				of purchasing land to build pricey new housing, developments
				when he said the same ends could be met by rehabilitating
				existing apartment or condo units for low-income renters or
				buyers at a lower cost.
				“I think our obligation as a Housing Authority is to provide as
				much clean and safe housing to the public as possible. That
				doesn’t mean brand spanking new,” he said. “I think we are on
				the wrong track.”
				Because, Najarian and other critics say, at the end of the day,
				when projects costs are high, fewer units are built, and more
				people are left on mile-long waiting lists.
				Take the Via Verde development, as written about in the NY
				Times architecture review.
				“The complex, with 71 co-ops and 151 rental apartments, is
				harder to get into than some of the toughest colleges. Some 800
				families have applied for the co-ops alone.”
				Rising construction costs
				Expensive design plans, though, are only one of the factors
				fueling the major price tags to build these projects.
				In California, many in the public housing industry point to the
				state committee that hands out the tax credits that in most
				cases are needed to make the developments a reality.
				Voice of San Diego reported that many insiders have dubbed
				the business “The Game,” where the projects with the highest
				costs are often rewarded with the tax credits.
				“Developers spend months putting together applications that are
				often inches thick and that break down their projects to the
				finest detail. The trick is to score as high as possible on the
				committee’s points system, a process that during the last
				decade has become increasingly daunting and has resulted in
				escalating bills for taxpayers, who eventually foot the cost.”
				Housing officials themselves acknowledge that the process is
				growing out of control.
				Joel John Roberts, chief executive officer of Los Angeles
				nonprofit housing People Assisting the Homeless, took on the
				issue in a January 2011 blog post.
				He attributed the high costs to four main factors:
				1. Cost of land. You can’t simply strong-arm a land owner to
				lower their price despite the difficulty in selling in this economy.
				If public funding is used to build housing, the land has to be
				purchased at the going market rate.
				2. Cost of accessing public funding. No housing can be built and
				offered at affordable rent rates without public funding, from local,
				state, or federal funding sources. The application process is
				arduous, time-consuming, and political. The cost to put together
				a complicated housing development can be expensive. You
				almost need a PhD in finance, politics, and housing to be
				successful in public funding.
				3. Building and planning codes do not cater to affordable
				housing. A city in the Los Angeles region mandated that we
				provide two parking spaces per unit, even though we all knew
				that the building was designed for formerly homeless persons
				who would be lucky to have one car. That one requirement cost
				us more than a million dollars in building a garage larger than
				what was needed. Other codes mandate unit sizes that are
				larger than what could be used in affordable housing.
				4. Prevailing wage ordinance requirements. Most states
				mandate that if a development receives public funding, the
				developer must pay their construction workers prevailing
				wages. These wages are higher than minimum wage, and are
				geared toward insuring that low-income workers are paid high
				enough wages to prevent poverty. Builders believe this
				requirement increases construction costs by 10% to 50%.
				In turn, Roberts says that policy change is needed to ensure all
				housing dollars are spent effectively.
5- Young Professionals Leadership Summit	International Student Services Concordia University Irvine	Irvine, CA	Sep 25 To Oct 4 , 2013	I help a lot of leaders create individual development plans using some variation of this process. This time of year (January) is always especially busy.
				Although every leader I work with is unique, it seems like the development goals end up being somewhat common from year to year.
				To help you get a head start on your 2010 leadership development plan, here’s a list of development goals that may apply to you too. I’d recommend picking no more than one and really working at it for at least 6 months. Do not attempt to work on all 12, just because there are 12 months in a year. (-:
				For 2010, I’d like to improve my:
				1. Strategic thinking.
				Improve my ability to see the big picture and take a longer range, broader business perspective. Learn to step back from the day-to-day tactical details of my business and focus on the “why”, not just the “what” and “how”.
				2. Listening.
				Learn to pay attention and demonstrate to others that that I value what they have to say. Use active listening, open-ended questions, body language, and eliminate distractions that get in the way of my ability to listen.
				3. Coaching.
				Shift my leadership style away from always directing and telling and learn to guide and develop my direct reports. Work with each of my direct reports to create their own individual development plans.
				4. Financial acumen.
				Learn how to understand, interpret, and use “the numbers” to improve my business.
				5. Cross-functional knowledge and perspective.
				Learn about other aspects of the business other than my own functional silo.
				6. Industry, competitive, and customer knowledge.
				Improve my understanding of our industry and our competitors. Get closer to our customers and find out what they need and value.
				7. Leadership presence.
				Improve my ability to “command a room” and communicate in an authentic way that inspires others.
				8. Change leadership
				.
				Be more of a change catalyst, a champion of change. Learn to implement and sustain change in my organization.
				9. Remote management
				.
				Improve my ability to manage my remote direct reports and organization. Make better use of technology to plan, communicate, and collaborate virtually.
				10. Collaboration.
				Improve relationships with my peers. Be a better partner, understand their goals and needs, and learn to work together to help achieve each others goals.
				11. Talent management.
				Improve my ability to assess, hire, promote, and develop. Fill all open positions with nothing but “A” players and replace chronic underperformers. Develop a “virtual bench” for all key positions and a succession plan for my own position.
				12. Time management.
				Get a handle on where I’m wasting time and shift my focus to more value-added activities. Learn ways to work more efficiently and prioritize.
6- Finance	Chapman University	Orange, CA	26-Oct-13	What are your top three financial objectives?
				Most people, when asked that question, answer with general goals, such as achieving financial security.
				The fact is, many of us haven't thought much about which financial objectives really matter most. Instead, we muddle through our financial lives, spending to meet the day-to-day expenses that dominate our attention.
				That approach risks leaving your most important objectives unfulfilled.
				That's what this lesson is all about: helping you identify the financial goals that matter most to you and making sure they happen.
				That's not as easy as it sounds, since financial goals continually collide with one another. Paying for a child's braces may rob money that would otherwise go into his college fund, for example. And saving effectively for your kids' college can wipe out any hope of putting aside adequate money for your own retirement.
				That's why to get what you want most you must 1) decide which goals will take priority and 2) work toward the lesser goals only after the really important ones are well provided for.
				Fortunately, you have at least one ally in meeting your long-range goals: time. That's an advantage because of the power of compounding - the fact that even a small amount of money can earn interest, and that each year that interest gets applied to a growing sum of money.
				Suppose, for example, you put aside only the cost of a single candy bar - about 65 cents - each day. Invested in a tax-deferred account paying 5% a year compounded monthly, that string of savings would grow to $3,073 in just 10 years and to $16,470 in 30 years.
				For other examples of the way that money can grow over time, try CNNMoney.com's Savings Calculator.
				To put the power of compounding on your side, you have to start early. Suppose there are two siblings who both invest in Individual Retirement Accounts earning 8% a year.
				The sister starts at age 20, and for the next 10 years she stuffs $3,000 a year into her IRA. At age 30, though, she stops and never adds another penny.
				Her brother waits until age 30 to get started, but then dutifully salts away $3,000 a year for the rest of his life. Which sibling do you think will be better off?
				In this case, the early bird will always be ahead. The sister reaches age 65 with more than $642,000, while her brother will have a little under $518,000 - about 20% less.
				Of course, it's far better to start early AND keep it up. If both siblings started saving $3,000 a year in an IRA at 20, and kept it up until retirement, each would end up with nearly $1.2 million.
				The point is that to put time on your side, you need to decide early which of the many possible financial goals are really worth pursuing - and start working toward them.
				To get started, make a list of all the things that you'd need to feel secure, happy or fulfilled. These can range from the weighty (getting out of debt) to the luxurious (a Lamborghini). You don't need to prioritize them yet.
				But you should try to put down all of the money-related things that will really get your motor started. And if you have a spouse or significant other, do this exercise together! Here are some common goals you may want to consider:
				Accumulating enough savings to handle an emergency situation
				Buying a house
				Getting out of debt - and staying out
				Ensuring that your parents are comfortable and well taken care of in their old age
				Paying for your children's college education
				Amassing enough wealth to retire comfortably
				Once you have your list in hand, push on to the next section, where you'll determine which of these goals are most important to you.
				After you've clarified your priorities, what do you do with your new insight?
				Each time you spend more than pocket change on a purchase that doesn't help you attain one of your chief goals, ask yourself whether the outlay is really necessary.
				For example, let's say your highest priority is achieving financial independence. And let's say you've saved $4,000 to take the family on a vacation. If you take the trip, you'll be an additional $4,000 from kissing the time clock good-bye.
				(Further, actually, since $4,000 in savings would grow to nearly $20,000 invested for 20 years at a tax-deferred 8% - as CNNMoney.com's Savings Calculator would show.)
				Of course, if your family has been expecting the trip for months, you'd be unfair to tell them that it's off. Instead, from the beginning you should have earmarked the cash for your investment portfolio and either planned a low-ticket vacation or worked a deal with family members to take the trip later.
				OK, you say, but that choice isn't terribly difficult. You're more concerned about tougher decisions - choosing, for instance, among such priorities as health care, education and savings.
				All are important. How do you resolve conflicts among them? No single approach will work for everyone - but here are some guidelines that help.
				Is someone's health involved? If you believe that the ultimate purpose of money is to make life better, then you might decide that saving cash at the cost of your well-being - or that of a relative's - is a poor choice. For most people, someone's illness is the rainy day for which they've been saving. Most would agree there is no single financial goal more important than dealing with - and paying for -catastrophic illness.
				How many people will be affected by my choice? Will one of your goals make your own life better while another gives equivalent help to two of your children? You could decide that when more people derive roughly equal benefit from a goal, its priority rises.
				If two goals offer similar rewards, which causes the least harm? This method of selection is typically a last resort, but it can be useful when no other analysis helps you decide among options.
				Most people, for example, have to decide between the kids' tuition and their own retirement savings. Well, if you know that you won't be able to live adequately on the money you expect from your pension and Social Security, then retirement savings should be paramount. As for the child in college, he can take out a tuition loan.
				You can't put every nickel toward top priorities, of course - nor should you. Instead, you need to set aside part of your income for current pleasures, so long as you have enough cash left over to put toward your long-range goals.
				Also, remember that as the years go by, your priorities will change. You'll need to reexamine and rank your needs regularly in order to use your money most effectively.
				When you can save a dollar, you need to decide why you're putting it away. In addition, if you acquire the habit of quickly rating the urgency of every big purchase against the primary financial goals you've set for yourself, you'll eventually find that your spending is under control.
				Here are examples of plans you might draw up to meet three of the most common objectives: getting out of debt, paying for college, or financing your retirement.
				Getting out of debt
				If you struggle to meet credit-card payments every month, then face it: You probably need to shed or consolidate some of that debt.
				For example, suppose you owe $3,000 in outstanding credit-card debt at a 16% interest rate and a $10,000 car loan at 9%. To pay off both these obligations in a year, you'd need to pony up $1,147 a month.
				But if you are a homeowner with equity in your property, you could borrow $13,000 on a home-equity loan at the same 9% and retire those other bills. Then your cost to pay off the home-equity loan in a year would be slightly lower - $1,137 a month - because you're no longer paying high credit-card rates of interest.
				Moreover, because you can deduct the interest on most home-equity loans, you'd reduce your taxable income by $642 that year - a $212 saving for someone in the 33% federal tax bracket. In effect, the government would help pay off your expenses.
				Of course, this kind of strategy works only if you also stop charging new items on your credit cards.
				Paying for college
				Tuition, room and board at a private college can cost upward of $30,000 a year, and that bill is projected to reach about $80,000 by the time this year's crop of newborns enters college.
				Your children may qualify for financial aid either in the form of a scholarship or a loan, and many students work their way through college.
				But if you want to spare your kids the burden of graduating in debt, there are a couple of good savings vehicles available to you. Most states now offer so-called 529 Plans - contributions go into in pre-selected mutual funds, grow tax-free each year, and withdrawals to pay tuition are also tax free.
				You could also open a Coverdell Education Savings Account (previously called an Education IRA) that lets you put $2,000 a year, after taxes, into a bank account or other investments; earnings on that type of account are totally tax-free, provided the money is used for tuition when it's withdrawn.
				It's amazing how far these plans will get you. For example, if you started putting $2,000 a year today into a Coverdell account earning 8%, after 18 years you'd have more than $80,000.
				Financing a retirement
				A popular rule of thumb says that retirees need only 70% of their pre-retirement income to maintain their lifestyle, since they no longer have to pay for such costs as commuting or for work clothes.
				However, other costs go up in retirement, such as utility bills (if you're home all day), the price of hobbies and travel - and, of course, the cost of health care. In fact, some retirees find they need as much income in retirement as they spent while working.
				Unfortunately, traditional pensions pay only a fraction of your salary, and Social Security won't make up the difference. In addition, the younger you are, the less certain you can be about how much money you'll receive at age 67 from any of the retirement plans you have today.
				Why? Because Social Security benefits may be revised, and employers are free at any time to change their pension-plan formulas. (They can't do so retroactively - every retirement dollar that you've already qualified for is yours to keep.) Of course, Congress can change the laws governing retirement savings plans at any time.
				Moreover, the recent economic downturn has underscored the point that stocks can be extremely volatile in the short term, even if they remain among the most consistent performers over long periods. Thus, the stock portion of any retirement portfolio needs to take into account the possibility of sharp downturns.
				To make your retirement finances secure, you need to contribute to as many different plans as possible. If you have a 401(k), 403(b), or 457 program at work, put in as much money as you can.
				Most employers will match your contributions, giving you money for retirement that you won't get any other way. If you have no retirement plan at work, contribute to an IRA. Note that contributions to all of these plans are tax-deferred, so that you, Uncle Sam, and your boss together could be adding to your retirement stash.
7- Marketing your vision	Chapman University	Orange, CA	2-Nov-13	What's a Marketing Plan for a Startup?
				http://technori.com/2013/01/3070-7-step-startup-marketing-plan/
				The 5 Key Questions you need to answer to build your plan
				http://www.aspira.org/files/documents/entrepreneurship/session_07.pdf
				What you may not know about Visuals and Marketing
				http://www.wipo.int/export/sites/www/freepublications/en/intproperty/itc_p159/wipo_pub_itc_p159.pdf
				Making optimal use of visuals in your product positioning
				http://blog.kissmetrics.com/a-total-steal/
8- Product Management	OC Product Managers	Irvin, CA	16-Oct-13	You will find the information in the attached, its name (Product Management)
9- 2013 Integrated Marketing Forum	Integrated Marketing Forum	Tustin, CA	7-Nov-13	How to design and execute an effective content marketing strategy
				http://www.act-on.com/resources/whitepapers/6-best-practices-for-creating-a-content-marketing-strategy.pdf
				http://www.vendasta.com/reputation-monitoring/review-monitoring
				http://www.vendasta.com/reputation-monitoring/review-monitoring
10- Mind's Eye Marketing Workshop	california state long beach university	Laguna Beach, CA	12-Dec-13	Find focus & direction for your online marketing efforts in an
				unplugged workshop combining marketing-oriented brainstorming
				with a photography walk around the neighborhood. Learn secrets of
				using words & images to tell your story, focus & learn to navigate in
				the social media sea.

				Workshop will occur rain or shine.
				Wear: Comfortable walking shoes and clothes suitable for a short
				neighborhood photo walk.
				Bring: Familiar point-and-shoot camera (ipads and Smartphones
				okay), fully charged, with enough memory for multiple photos.

11- Social Media Marketing Bootcamp Workshop to Attract New Customers	OGOING What's going on? Social Media Bootcamp	Irvine, CA	15-Nov-13	Confused about social media? Don't know where to start? Not sure if
				there is any value or ROI?
				What? oGoing invites you to an exclusive Social Media Marketing
				boot camp workshop for small businesses, non-profits, startups,
				SMBs or local organizations. This workshop is only limited to 10
				participants for maximum engagement and learning. oGoing founder
				Sanjay Dalal, who has trained over 750 business owners and
				professionals, will share tools and best practices that will accelerate
				your online presence, and boost your business with latest social
				media. He will help you become a social media expert in this crash
				course that is both insightful and hands-on! Learn the inside secrets
				(that only experts have) on how to rapidly attract, create, farm and
				expand customers through cutting-edge social media.
				"I definitely learned a lot and it got me motivated to have a larger
				presence online and oGoing!" - Paul Imhoff, Director, Newmark
				Knight Frank
				Why? While the social media market is exploding with dozens of
				leading websites such as Facebook, LinkedIn, Twitter, Google+,
				YouTube, Pinterest, Instagram and more, Ogoing remains focused
				on utilizing key tools that small business owners, entrepreneurs,
				startup founders, and professionals need in order to rapidly grow
				their social media presence. Majority of businesses do not have the
				time, knowledge, resources and money to boost their brand and
				obtain new leads using social media. This is where Ogoing helps!
				Think of Ogoing as the business matchmaker.
				Sanjay was awesome! Very informative presentation...not just useful for social media but great marketing tips as well. Julian Reyes,
				Director, The N.E.W. Program, Inc.
				Learn the importance of social media marketing today in growing
				your business now
				Leverage social and online media to promote your brand, products,
				services, news and events
				Increase the number of quality connections, contacts, followers and
				fans on major networks
				Connect with businesses and professionals using social media, and
				grow your business network
				Jumpstart your lead acquisition and sales using the latest promotion
				tools and best practices
				Facilitate five star customer feedback and recommendations, and
				improve customer loyalty
				Provide excellent customer service using social media, and make
				your customers happy
				Learn how to boost social presence on oGoing, Facebook, LinkedIn,
				Twitter, Google+, Blogs...
12- Financial Strategies	eMBA ALUMNI PROJECT	Costa Mesa, CA	6-Nov-13
				Long-term strategic goals

				I
				Profitable growth
				In order to achieve our long-term sales growth goal, we will stay
				focused in coming years on markets where we are already
				established: the Nordic region, many European countries, South
				Africa and Australia. In addition, we will establish a stronger local
				presence in selected markets such as North America, the UK, South
				America (Brazil) and Asia (Thailand and India).

				Performance

				Our efficiency improvement program was successfully finalised in
				2010. We have now reduced Saab’s cost base by SEK 1.5 billion
				over
				a three-year period. The market is constantly changing, which
				requires that we keep up with developments and in many cases that
				we stay on the forefront of change. This is why we continue to
				improve efficiencies in operations, focus on capital efficiency and
				generate strong cash flow.

				Portfolio

				To achieve our growth target, we have to invest partly in product
				innovation and partly in renewal and upgrades of existing products
				and systems. Investments in the portfolio will be prioritised in areas
				where we already have competitive technology and/or a competitive
				market position and our aim is to strengthen or retain our unique
				systems expertise.
				People

				Our employees are the foundation that enables us to implement our
				strategy and achieve our strategic and financial goals. Our market is
				changing, and successful changes require confidence in the future.
				We want to be an employer of choice for current and future
				employees who seek development opportunities and continuous
				change.

				Long-term financial goals

				Growth

				Over a business cycle, our organic sales growth will average 5 per
				cent per year. It is possible that growth will also be achieved through
				acquisitions if value-creating opportunities arise within our priority
				areas in the years ahead.
				Operating margin
				The operating margin after depreciation/amortisation (EBIT) will be at
				least 10 per cent.

				Equity/asset ratio

				The equity/assets ratio shall exceed 30 per cent.
				Dividend policy

				Saab’s long-term dividend objective is to distribute 20–40 per cent of
				net income over a business cycle to shareholders.
13- Crowd Funding and Recent Developments in Capital Raising	OC Tech Alliance	Newport Beach, CA		I attached a PDF of Crowd Funding
				Please look at the link
				http://books.google.com/books?hl=ar&lr=&id=hdLc_yaPz5YC&oi=fnd&pg=PP2&dq=goals+of++Capital+Raising&ots=pd1aAJPRcJ&sig=2w4u1S5_EOeN6qxTcNyFn80j6LQ#v=onepage&q=goals%20of%20%20Capital%20Raising&f=false
14- Leadership Development and Teambuilding	Skillpath Training Compumaster. HRC Professional business training since 1989	Anaheim. CA	2-Dec-13	Please look at attached pdf (Leadership)

http://www.greatleadershipbydan.com/2008/11/how-to-write-great-individual.html http://www.aspira.org/files/documents/entrepreneurship/session_07.pdf http://www.wipo.int/export/sites/www/freepublications/en/intproperty/itc_p159/wipo_pub_itc_p159.pdf http://blog.kissmetrics.com/a-total-steal/ http://www.act-on.com/resources/whitepapers/6-best-practices-for-creating-a-content-marketing-strategy.pdf http://www.vendasta.com/reputation-monitoring/review-monitoring http://books.google.com/books?hl=ar&lr=&id=hdLc_yaPz5YC&oi=fnd&pg=PP2&dq=goals+of++Capital+Raising&ots=pd1aAJPRcJ&sig=2w4u1S5_EOeN6qxTcNyFn80j6LQ http://www.greatleadershipbydan.com/2008/05/10-ways-to-be-more-strategic-leader.html http://www.greatleadershipbydan.com/2008/06/listening-tips-for-leaders.html http://www.greatleadershipbydan.com/2008/08/coaching-self-assessment-for-leaders.html http://www.greatleadershipbydan.com/2009/02/lipstick-on-pig-10-ways-to-improve-your.html http://www.amazon.com/Leading-Change-John-P-Kotter/dp/0875847471?ie=UTF8&tag=greatleadership-20&link_code=btl&camp=213689&creative=392969 http://www.amazon.com/Distance-Manager-Managing-Off-Site-Employees/dp/0071360654?ie=UTF8&tag=greatleadership-20&link_code=btl&camp=213689&creative=392969 http://cgi.money.cnn.com/tools/savingscalc/savingscalc.html http://technori.com/2013/01/3070-7-step-startup-marketing-plan/

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My Experiences

Number 1

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Number 2

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The second function tasks

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My evaluation from my manager, and it was every three months

From January 6, to March 2007 = 91%

From April to June 2007 = 93%

From July to September 2007 = 95%

From October to December 2007= 97%

From January to March 2008 =98%

From April to June 2008 = 99%

From July to September 2008 = 99%

From October to December 2008= 99%

From January to March 2009 =100%

From April to June 2009 = 100%

From July to September 2009 = 100%

From October to December 2009= 100%

From January to March 2010 =100%

My Education

The Bachelor

The university is (Umm Al- Qura University)

The City is ( Makkah )

The Country is (Kingdom of Saudi Arabia)

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The Master

California Lutheran University

Thousand Oaks , CA

Public Policy & Administration

This is the Transcript

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