Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.
More on Web3 & Crypto
Shan Vernekar
3 years ago
How the Ethereum blockchain's transactions are carried out
Overview
Ethereum blockchain is a network of nodes that validate transactions. Any network node can be queried for blockchain data for free. To write data as a transition requires processing and writing to each network node's storage. Fee is paid in ether and is also called as gas.
We'll examine how user-initiated transactions flow across the network and into the blockchain.
Flow of transactions
A user wishes to move some ether from one external account to another. He utilizes a cryptocurrency wallet for this (like Metamask), which is a browser extension.
The user enters the desired transfer amount and the external account's address. He has the option to choose the transaction cost he is ready to pay.
Wallet makes use of this data, signs it with the user's private key, and writes it to an Ethereum node. Services such as Infura offer APIs that enable writing data to nodes. One of these services is used by Metamask. An example transaction is shown below. Notice the “to” address and value fields.
var rawTxn = {
nonce: web3.toHex(txnCount),
gasPrice: web3.toHex(100000000000),
gasLimit: web3.toHex(140000),
to: '0x633296baebc20f33ac2e1c1b105d7cd1f6a0718b',
value: web3.toHex(0),
data: '0xcc9ab24952616d6100000000000000000000000000000000000000000000000000000000'
};The transaction is written to the target Ethereum node's local TRANSACTION POOL. It informed surrounding nodes of the new transaction, and those nodes reciprocated. Eventually, this transaction is received by and written to each node's local TRANSACTION pool.
The miner who finds the following block first adds pending transactions (with a higher gas cost) from the nearby TRANSACTION POOL to the block.
The transactions written to the new block are verified by other network nodes.
A block is added to the main blockchain after there is consensus and it is determined to be genuine. The local blockchain is updated with the new node by additional nodes as well.
Block mining begins again next.
The image above shows how transactions go via the network and what's needed to submit them to the main block chain.
References
ethereum.org/transactions How Ethereum transactions function, their data structure, and how to send them via app. ethereum.org
William Brucee
3 years ago
This person is probably Satoshi Nakamoto.
Who founded bitcoin is the biggest mystery in technology today, not how it works.
On October 31, 2008, Satoshi Nakamoto posted a whitepaper to a cryptography email list. Still confused by the mastermind who changed monetary history.
Journalists and bloggers have tried in vain to uncover bitcoin's creator. Some candidates self-nominated. We're still looking for the mystery's perpetrator because none of them have provided proof.
One person. I'm confident he invented bitcoin. Let's assess Satoshi Nakamoto before I reveal my pick. Or what he wants us to know.
Satoshi's P2P Foundation biography says he was born in 1975. He doesn't sound or look Japanese. First, he wrote the whitepaper and subsequent articles in flawless English. His sleeping habits are unusual for a Japanese person.
Stefan Thomas, a Bitcoin Forum member, displayed Satoshi's posting timestamps. Satoshi Nakamoto didn't publish between 2 and 8 p.m., Japanese time. Satoshi's identity may not be real.
Why would he disguise himself?
There is a legitimate explanation for this
Phil Zimmermann created PGP to give dissidents an open channel of communication, like Pretty Good Privacy. US government seized this technology after realizing its potential. Police investigate PGP and Zimmermann.
This technology let only two people speak privately. Bitcoin technology makes it possible to send money for free without a bank or other intermediary, removing it from government control.
How much do we know about the person who invented bitcoin?
Here's what we know about Satoshi Nakamoto now that I've covered my doubts about his personality.
Satoshi Nakamoto first appeared with a whitepaper on metzdowd.com. On Halloween 2008, he presented a nine-page paper on a new peer-to-peer electronic monetary system.
Using the nickname satoshi, he created the bitcointalk forum. He kept developing bitcoin and created bitcoin.org. Satoshi mined the genesis block on January 3, 2009.
Satoshi Nakamoto worked with programmers in 2010 to change bitcoin's protocol. He engaged with the bitcoin community. Then he gave Gavin Andresen the keys and codes and transferred community domains. By 2010, he'd abandoned the project.
The bitcoin creator posted his goodbye on April 23, 2011. Mike Hearn asked Satoshi if he planned to rejoin the group.
“I’ve moved on to other things. It’s in good hands with Gavin and everyone.”
Nakamoto Satoshi
The man who broke the banking system vanished. Why?
Satoshi's wallets held 1,000,000 BTC. In December 2017, when the price peaked, he had over US$19 billion. Nakamoto had the 44th-highest net worth then. He's never cashed a bitcoin.
This data suggests something happened to bitcoin's creator. I think Hal Finney is Satoshi Nakamoto .
Hal Finney had ALS and died in 2014. I suppose he created the future of money, then he died, leaving us with only rumors about his identity.
Hal Finney, who was he?
Hal Finney graduated from Caltech in 1979. Student peers voted him the smartest. He took a doctoral-level gravitational field theory course as a freshman. Finney's intelligence meets the first requirement for becoming Satoshi Nakamoto.
Students remember Finney holding an Ayn Rand book. If he'd read this, he may have developed libertarian views.
His beliefs led him to a small group of freethinking programmers. In the 1990s, he joined Cypherpunks. This action promoted the use of strong cryptography and privacy-enhancing technologies for social and political change. Finney helped them achieve a crypto-anarchist perspective as self-proclaimed privacy defenders.
Zimmermann knew Finney well.
Hal replied to a Cypherpunk message about Phil Zimmermann and PGP. He contacted Phil and became PGP Corporation's first member, retiring in 2011. Satoshi Nakamoto quit bitcoin in 2011.
Finney improved the new PGP protocol, but he had to do so secretly. He knew about Phil's PGP issues. I understand why he wanted to hide his identity while creating bitcoin.
Why did he pretend to be from Japan?
His envisioned persona was spot-on. He resided near scientist Dorian Prentice Satoshi Nakamoto. Finney could've assumed Nakamoto's identity to hide his. Temple City has 36,000 people, so what are the chances they both lived there? A cryptographic genius with the same name as Bitcoin's creator: coincidence?
Things went differently, I think.
I think Hal Finney sent himself Satoshis messages. I know it's odd. If you want to conceal your involvement, do as follows. He faked messages and transferred the first bitcoins to himself to test the transaction mechanism, so he never returned their money.
Hal Finney created the first reusable proof-of-work system. The bitcoin protocol. In the 1990s, Finney was intrigued by digital money. He invented CRypto cASH in 1993.
Legacy
Hal Finney's contributions should not be forgotten. Even if I'm wrong and he's not Satoshi Nakamoto, we shouldn't forget his bitcoin contribution. He helped us achieve a better future.
Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 2)
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? But it turns out that there is a clever solution.
Polynomials
Polynomials are a special class of algebraic expressions of the form:
- x+5
- x^4
- x^3+3x^2+3x+1
- 628x^{271}+318x^{270}+530x^{269}+…+69x+381
i.e. they are a sum of any (finite!) number of terms of the form cx^k
There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: polynomials are a single mathematical object that can contain an unbounded amount of information (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.
Furthermore, a single equation between polynomials can represent an unbounded number of equations between numbers. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:
- A(0)+B(0)=C(0)
- A(1)+B(1)=C(1)
- A(2)+B(2)=C(2)
- A(3)+B(3)=C(3)
And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:
- 12+1=13
- 10+8=18
- 15+8=23
- 15+13=28
You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:
- A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
- B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
- C(x)=5x+13
Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.
Comparing a polynomial to itself
You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you also check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)
As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.
Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).
Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F actually satisfies this condition by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:
H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}
Where Z(x) = (x-0)*(x-1)*…*(x-98).
You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!
Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.
see part 3
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Sam Hickmann
3 years ago
The Jordan 6 Rings Reintroduce Classic Bulls
The Jordan 6 Rings return in Bulls colors, a deviation from previous releases. The signature red color is used on the midsole and heel, as well as the chenille patch and pull tab. The rest of the latter fixture is black, matching the outsole and adjacent Jumpman logos. Finally, white completes the look, from the leather mudguard to the lace unit. Here's a closer look at the Jordan 6 Rings. Sizes should be available soon on Nike.com and select retailers. Also, official photos of the Air Jordan 1 Denim have surfaced.
Jordan 6 Rings
Release Date: 2022
Color: N/A
Mens: $130
Style Code: 322992-126
Navdeep Yadav
3 years ago
31 startup company models (with examples)
Many people find the internet's various business models bewildering.
This article summarizes 31 startup e-books.
1. Using the freemium business model (free plus premium),
The freemium business model offers basic software, games, or services for free and charges for enhancements.
Examples include Slack, iCloud, and Google Drive
Provide a rudimentary, free version of your product or service to users.
Google Drive and Dropbox offer 15GB and 2GB of free space but charge for more.
Freemium business model details (Click here)
2. The Business Model of Subscription
Subscription business models sell a product or service for recurring monthly or yearly revenue.
Examples: Tinder, Netflix, Shopify, etc
It's the next step to Freemium if a customer wants to pay monthly for premium features.
Subscription Business Model (Click here)
3. A market-based business strategy
It's an e-commerce site or app where third-party sellers sell products or services.
Examples are Amazon and Fiverr.
On Amazon's marketplace, a third-party vendor sells a product.
Freelancers on Fiverr offer specialized skills like graphic design.
Marketplace's business concept is explained.
4. Business plans using aggregates
In the aggregator business model, the service is branded.
Uber, Airbnb, and other examples
Marketplace and Aggregator business models differ.
Amazon and Fiverr link merchants and customers and take a 10-20% revenue split.
Uber and Airbnb-style aggregator Join these businesses and provide their products.
5. The pay-as-you-go concept of business
This is a consumption-based pricing system. Cloud companies use it.
Example: Amazon Web Service and Google Cloud Platform (GCP) (AWS)
AWS, an Amazon subsidiary, offers over 200 pay-as-you-go cloud services.
“In short, the more you use the more you pay”
When it's difficult to divide clients into pricing levels, pay-as-you is employed.
6. The business model known as fee-for-service (FFS)
FFS charges fixed and variable fees for each successful payment.
For instance, PayU, Paypal, and Stripe
Stripe charges 2.9% + 30 per payment.
These firms offer a payment gateway to take consumer payments and deposit them to a business account.
Fintech business model
7. EdTech business strategy
In edtech, you generate money by selling material or teaching as a service.
edtech business models
Freemium When course content is free but certification isn't, e.g. Coursera
FREE TRIAL SkillShare offers free trials followed by monthly or annual subscriptions.
Self-serving marketplace approach where you pick what to learn.
Ad-revenue model The company makes money by showing adverts to its huge user base.
Lock-in business strategy
Lock in prevents customers from switching to a competitor's brand or offering.
It uses switching costs or effort to transmit (soft lock-in), improved brand experience, or incentives.
Apple, SAP, and other examples
Apple offers an iPhone and then locks you in with extra hardware (Watch, Airpod) and platform services (Apple Store, Apple Music, cloud, etc.).
9. Business Model for API Licensing
APIs let third-party apps communicate with your service.
Uber and Airbnb use Google Maps APIs for app navigation.
Examples are Google Map APIs (Map), Sendgrid (Email), and Twilio (SMS).
Business models for APIs
Free: The simplest API-driven business model that enables unrestricted API access for app developers. Google Translate and Facebook are two examples.
Developer Pays: Under this arrangement, service providers such as AWS, Twilio, Github, Stripe, and others must be paid by application developers.
The developer receives payment: These are the compensated content producers or developers who distribute the APIs utilizing their work. For example, Amazon affiliate programs
10. Open-source enterprise
Open-source software can be inspected, modified, and improved by anybody.
For instance, use Firefox, Java, or Android.
Google paid Mozilla $435,702 million to be their primary search engine in 2018.
Open-source software profits in six ways.
Paid assistance The Project Manager can charge for customization because he is quite knowledgeable about the codebase.
A full database solution is available as a Software as a Service (MongoDB Atlas), but there is a fee for the monitoring tool.
Open-core design R studio is a better GUI substitute for open-source applications.
sponsors of GitHub Sponsorships benefit the developers in full.
demands for paid features Earn Money By Developing Open Source Add-Ons for Current Products
Open-source business model
11. The business model for data
If the software or algorithm collects client data to improve or monetize the system.
Open AI GPT3 gets smarter with use.
Foursquare allows users to exchange check-in locations.
Later, they compiled large datasets to enable retailers like Starbucks launch new outlets.
12. Business Model Using Blockchain
Blockchain is a distributed ledger technology that allows firms to deploy smart contracts without a central authority.
Examples include Alchemy, Solana, and Ethereum.
Business models using blockchain
Economy of tokens or utility When a business uses a token business model, it issues some kind of token as one of the ways to compensate token holders or miners. For instance, Solana and Ethereum
Bitcoin Cash P2P Business Model Peer-to-peer (P2P) blockchain technology permits direct communication between end users. as in IPFS
Enterprise Blockchain as a Service (Baas) BaaS focuses on offering ecosystem services similar to those offered by Amazon (AWS) and Microsoft (Azure) in the web 3 sector. Example: Ethereum Blockchain as a Service with Bitcoin (EBaaS).
Blockchain-Based Aggregators With AWS for blockchain, you can use that service by making an API call to your preferred blockchain. As an illustration, Alchemy offers nodes for many blockchains.
13. The free-enterprise model
In the freeterprise business model, free professional accounts are led into the funnel by the free product and later become B2B/enterprise accounts.
For instance, Slack and Zoom
Freeterprise companies flourish through collaboration.
Start with a free professional account to build an enterprise.
14. Business plan for razor blades
It's employed in hardware where one piece is sold at a loss and profits are made through refills or add-ons.
Gillet razor & blades, coffee machine & beans, HP printer & cartridge, etc.
Sony sells the Playstation console at a loss but makes up for it by selling games and charging for online services.
Advantages of the Razor-Razorblade Method
lowers the risk a customer will try a product. enables buyers to test the goods and services without having to pay a high initial investment.
The product's ongoing revenue stream has the potential to generate sales that much outweigh the original investments.
Razor blade business model
15. The business model of direct-to-consumer (D2C)
In D2C, the company sells directly to the end consumer through its website using a third-party logistic partner.
Examples include GymShark and Kylie Cosmetics.
D2C brands can only expand via websites, marketplaces (Amazon, eBay), etc.
D2C benefits
Lower reliance on middlemen = greater profitability
You now have access to more precise demographic and geographic customer data.
Additional space for product testing
Increased customisation throughout your entire product line-Inventory Less
16. Business model: White Label vs. Private Label
Private label/White label products are made by a contract or third-party manufacturer.
Most amazon electronics are made in china and white-labeled.
Amazon supplements and electronics.
Contract manufacturers handle everything after brands select product quantities on design labels.
17. The franchise model
The franchisee uses the franchisor's trademark, branding, and business strategy (company).
For instance, KFC, Domino's, etc.
Subway, Domino, Burger King, etc. use this business strategy.
Many people pick a franchise because opening a restaurant is risky.
18. Ad-based business model
Social media and search engine giants exploit search and interest data to deliver adverts.
Google, Meta, TikTok, and Snapchat are some examples.
Users don't pay for the service or product given, e.g. Google users don't pay for searches.
In exchange, they collected data and hyper-personalized adverts to maximize revenue.
19. Business plan for octopuses
Each business unit functions separately but is connected to the main body.
Instance: Oyo
OYO is Asia's Airbnb, operating hotels, co-working, co-living, and vacation houses.
20, Transactional business model, number
Sales to customers produce revenue.
E-commerce sites and online purchases employ SSL.
Goli is an ex-GymShark.
21. The peer-to-peer (P2P) business model
In P2P, two people buy and sell goods and services without a third party or platform.
Consider OLX.
22. P2P lending as a manner of operation
In P2P lending, one private individual (P2P Lender) lends/invests or borrows money from another (P2P Borrower).
Instance: Kabbage
Social lending lets people lend and borrow money directly from each other without an intermediary financial institution.
23. A business model for brokers
Brokerages charge a commission or fee for their services.
Examples include eBay, Coinbase, and Robinhood.
Brokerage businesses are common in Real estate, finance, and online and operate on this model.
Buy/sell similar models Examples include financial brokers, insurance brokers, and others who match purchase and sell transactions and charge a commission.
These brokers charge an advertiser a fee based on the date, place, size, or type of an advertisement. This is known as the classified-advertiser model. For instance, Craiglist
24. Drop shipping as an industry
Dropshipping allows stores to sell things without holding physical inventories.
When a customer orders, use a third-party supplier and logistic partners.
Retailer product portfolio and customer experience Fulfiller The consumer places the order.
Dropshipping advantages
Less money is needed (Low overhead-No Inventory or warehousing)
Simple to start (costs under $100)
flexible work environment
New product testing is simpler
25. Business Model for Space as a Service
It's centered on a shared economy that lets millennials live or work in communal areas without ownership or lease.
Consider WeWork and Airbnb.
WeWork helps businesses with real estate, legal compliance, maintenance, and repair.
26. The business model for third-party logistics (3PL)
In 3PL, a business outsources product delivery, warehousing, and fulfillment to an external logistics company.
Examples include Ship Bob, Amazon Fulfillment, and more.
3PL partners warehouse, fulfill, and return inbound and outbound items for a charge.
Inbound logistics involves bringing products from suppliers to your warehouse.
Outbound logistics refers to a company's production line, warehouse, and customer.
27. The last-mile delivery paradigm as a commercial strategy
Last-mile delivery is the collection of supply chain actions that reach the end client.
Examples include Rappi, Gojek, and Postmates.
Last-mile is tied to on-demand and has a nighttime peak.
28. The use of affiliate marketing
Affiliate marketing involves promoting other companies' products and charging commissions.
Examples include Hubspot, Amazon, and Skillshare.
Your favorite youtube channel probably uses these short amazon links to get 5% of sales.
Affiliate marketing's benefits
In exchange for a success fee or commission, it enables numerous independent marketers to promote on its behalf.
Ensure system transparency by giving the influencers a specific tracking link and an online dashboard to view their profits.
Learn about the newest bargains and have access to promotional materials.
29. The business model for virtual goods
This is an in-app purchase for an intangible product.
Examples include PubG, Roblox, Candy Crush, etc.
Consumables are like gaming cash that runs out. Non-consumable products provide a permanent advantage without repeated purchases.
30. Business Models for Cloud Kitchens
Ghost, Dark, Black Box, etc.
Delivery-only restaurant.
These restaurants don't provide dine-in, only delivery.
For instance, NextBite and Faasos
31. Crowdsourcing as a Business Model
Crowdsourcing = Using the crowd as a platform's source.
In crowdsourcing, you get support from people around the world without hiring them.
Crowdsourcing sites
Open-Source Software gives access to the software's source code so that developers can edit or enhance it. Examples include Firefox browsers and Linux operating systems.
Crowdfunding The oculus headgear would be an example of crowdfunding in essence, with no expectations.
Rajesh Gupta
3 years ago
Why Is It So Difficult to Give Up Smoking?
I started smoking in 2002 at IIT BHU. Most of us thought it was enjoyable at first. I didn't realize the cost later.
In 2005, during my final semester, I lost my father. Suddenly, I felt more accountable for my mother and myself.
I quit before starting my first job in Bangalore. I didn't see any smoking friends in my hometown for 2 months before moving to Bangalore.
For the next 5-6 years, I had no regimen and smoked only when drinking.
Due to personal concerns, I started smoking again after my 2011 marriage. Now smoking was a constant guilty pleasure.
I smoked 3-4 cigarettes a day, but never in front of my family or on weekends. I used to excuse this with pride! First office ritual: smoking. Even with guilt, I couldn't stop this time because of personal concerns.
After 8-9 years, in mid 2019, a personal development program solved all my problems. I felt complete in myself. After this, I just needed one cigarette each day.
The hardest thing was leaving this final cigarette behind, even though I didn't want it.
James Clear's Atomic Habits was published last year. I'd only read 2-3 non-tech books before reading this one in August 2021. I knew everything but couldn't use it.
In April 2022, I realized the compounding effect of a bad habit thanks to my subconscious mind. 1 cigarette per day (excluding weekends) equals 240 = 24 packs per year, which is a lot. No matter how much I did, it felt negative.
Then I applied the 2nd principle of this book, identifying the trigger. I tried to identify all the major triggers of smoking. I found social drinking is one of them & If I am able to control it during that time, I can easily control it in other situations as well. Going further whenever I drank, I was pre-determined to ignore the craving at any cost. Believe me, it was very hard initially but gradually this craving started fading away even with drinks.
I've been smoke-free for 3 months. Now I know a bad habit's effects. After realizing the power of habits, I'm developing other good habits which I ignored all my life.