munchee-the-sec-and-utility-tokens

.pdf

School

University of Ottawa *

*We aren’t endorsed by this school

Course

ADM3755

Subject

Business

Date

Feb 20, 2024

Type

pdf

Pages

15

Uploaded by rickthesizzler2631 on coursehero.com

Munchee, the SEC, and Utility Tokens Author: John V. Eagan Pub. Date: 2019 Product: SAGE Business Cases DOI: https://dx.doi.org/10.4135/9781526467843 Keywords: utility, security and classification, security, Securities and Exchange Commission, ethers, coining, restaurants Disciplines: Business & Management, Entrepreneurship, Strategic Management, Entrepreneurial Finance, Business Law Access Date: January 4, 2023 Publishing Company: SAGE Publications: SAGE Business Cases Originals City: London Online ISBN: 9781526467843 © 2019 SAGE Publications: SAGE Business Cases Originals All Rights Reserved.
1. 2. Abstract Munchee, Inc. is a company that created a peer-to-peer food review platform based on blockchain technology. Food reviewers were to be compensated with tokens that could be used at restaurants. In July 2017 the Security and Exchange Commission (SEC) released guidance on initial coin offerings (ICOs) that indicated that some tokens issued in an ICO may be clas- sified as a security. In their white paper, Munchee argued that their tokens were utility tokens and not a security under the Howey test. Munchee launched a token offering in October 2017. The SEC contacted Munchee and Munchee ceased their ICO and returned investor funds. The SEC issued a cease-and-desist order that indicated that Munchee had violated securities laws in their token offering. The primary issue in this case is how students can craft a token to satisfy the “utility token” exception to classifying a blockchain token as a security. Case Learning Outcomes By the end of this case study, students should be able to: understand the application of the Howey test by the Security and Exchange Commission (SEC) to cryptographic tokens; and understand the issues raised by the “utility token” exception to classification of a token as a security. The Resources tab includes a glossary of technical terms. Background Munchee, Inc., a Delaware-licensed corporation based in San Francisco, was founded in 2015 to build the Munchee network, a food review platform. Munchee described itself in a public announcement in BitcoinTalk as “Yelp meets Instagram.” Munchee is addressing the USD 54.8 billion marketspace of people eating out. The primary competition in the food review business at the time of the Munchee initial coin offering (ICO) was Yelp, founded in 2004. Yelp, a USD 3.2 billion company with USD 704 million in annual revenue, had 135 million cumulative reviews as of August 2017. Foursquare, Google Places, Michelin Guide, OpenTable, SAGE © John Vincent Eagan 2019 SAGE Business Cases Page 2 of 15 Munchee, the SEC, and Utility Tokens
and Zagat also provide online food reviews, but these other sites were nowhere near as large as Yelp. As the eleventh most visited site on the web, according to SEMrush, industry analysis often grouped Yelp with Facebook, TripAdvisor, Foursquare, Yellow Pages, and MapQuest. Existing restaurant reviews focus on the entire dining experience, not only on the food itself. Munchee pro- vides visual search results on dishes, rather than on restaurants, along with prices, reviews, and dish ratings. Munchee uses a machine learning algorithm to discover user preferences and suitable reviewers for peer re- view. On the Munchee platform, food lovers and photographers take pictures and videos of their food and then review the food on Munchee and other social media. Customers search by dish or cuisine with side-by-side information about price, reviews, and dish ratings. Customers pin the results to try the restaurant in person, and can click the order button to have food delivered. In 2017, Munchee customer retention tactics included: following other users and being followed, in-app gamification, accumulating points, and obtaining rewards. The two problems with centralized food reviews that Munchee seeks to address are: (a) manipulation to se- cure advertising; and (b) the predisposition of people with negative reviews to post more than others. The Munchee white paper cited the study by Luca and Zervas (2015) that found 16% of the reviews in Boston were filtered by Yelp in 2014 to attempt to reduce review manipulation. At the same time, Yelp itself has been sued for review manipulation. In one example the Ninth Circuit Court in 2014 ruled that Yelp could lower a business rating based on whether the business advertised on Yelp. The judge wrote that, “[a]s Yelp has the right to charge for legitimate advertising services, the threat of economic harm that Yelp leveraged is, at most, hard bargaining” ( Levitt v. Yelp, Inc. , 2014). Yelp denied the practice, stating that it used an automated system to determine ratings from reviews. Munchee sought to address this problem, real or perceived, by creating a decentralized peer review process for creating food review posts. A peer review can approve or flag a post. A flag may indicate spam or inap- propriate content. An approval shows that all required fields are correctly listed and includes a check-in at the restaurant and a user-generated photo. Users must review the validity of other posts to earn permission to create their own post and garner tokens (the MUN token, discussed below). Users only earn tokens upon successful review of their post by other users. This peer review process was projected to take seven to ten days. Machine learning would elect suitable reviewers based on location, food preference, and related crite- ria. A smart contract would keep an audit trail of submissions and a second smart contract would keep the MUN token record. SAGE © John Vincent Eagan 2019 SAGE Business Cases Page 3 of 15 Munchee, the SEC, and Utility Tokens
MUN Token As seen above, the proposed MUN tokens were projected to be a component on the Munchee peer review process. The MUN open-source cryptographic token was to be a native cryptocurrency of the Munchee net- work. MUN was an ERC20 digital token issued on the Ethereum blockchain. The MUN was projected to be of fixed supply, fractionally divisible, and non-inflationary, transferable, and tradable on cryptocurrency ex- changes within thirty days of the ICO. Only a portion of the MUN token was projected to become liquid in the immediate term. The MUN token would be issued to Munchee, the restaurants, and users through an Ethereum smart contract. The MUN token would enable peer-to-peer transactions in the Munchee ecosystem. Munchee and restau- rants would make advertising payments to each other. Users would make in-app purchases from Munchee and receive rewards from Munchee. Restaurants would receive token payments for food and services from users and pay token rewards to users. There were further token incentives for content creators within this process. In each seven- to ten-day period the top 20% of users (in terms of review volume) would be rewarded additional MUN tokens. High-quality content contributors (top 20%) would also be rewarded with extra MUN tokens. Top reviewers were to be de- termined based on the accepted reviews, total number of likes, and pins in a period. Users could also earn MUN tokens for new users that joined and contributed to the platform though a referral process. The MUN tokens for these various payments were retrieved from Munchee’s company reserve of MUN. In this model Munchee argued that end users would benefit from peer review over false review sources and in tokens for activity in the mobile app, which could be redeemed for products and services at partner business- es or restaurants. Restaurants would benefit from the reduced fees to credit card agencies and knowing that their advertising dollars were going towards real reviews. The Munchee ecosystem would also be monetized through in-app advertising and 10–15% commissions on food delivery. Figure 1 , from the Munchee white paper (Munchee, 2014), shows a model of how the ecosystem would serve to increase the value of MUN. SAGE © John Vincent Eagan 2019 SAGE Business Cases Page 4 of 15 Munchee, the SEC, and Utility Tokens
Figure 1. MUN Value Model Source : Munchee (2014). Munchee proposed to use a proof-of-stake consensus algorithm for MUN as opposed to the proof-of-work consensus algorithm used by the Bitcoin network. Ethereum was moving to a proof-of-stake consensus algo- rithm in late 2017 as well. However, Munchee had not completely worked out the Munchee network consen- sus mechanism at the time of the token offering. There were no other firms offering a “blockchain-based food review incentivized platform” at the time of the Munchee token offering (Munchee, n.d.). SAGE © John Vincent Eagan 2019 SAGE Business Cases Page 5 of 15 Munchee, the SEC, and Utility Tokens
Munchee Roadmap Munchee did not have a fully working product at the time of their 2017 token offering, but the Munchee team had issued a white paper on October 16, 2017. Munchee first distributed its closed beta app in the fourth quar- ter of 2016, the iOS app in the second quarter of 2017 and an Android app in the fourth quarter of 2017. The Munchee white paper reported 3,500 Instagram followers and 16,000 Facebook followers in October 2017. The two-year roadmap for Munchee is presented in Table 1 . Table 1. Munchee Roadmap Quarter Planned feature completion or launch date 2017 Q4 Cryptotoken planning and issuance Cryptotoken pre-sale and sale event (ultimately canceled) 2018 Q2 Improve Munchee mobile app Backend, UX/UI, and restaurant database 2018 Q3 Begin development of Ethereum Smart contract for integration of MUN token in Munchee app Launch user acquisition and marketing campaigns 2018 Q4 Start of development of Smart contract to record reviews on Ethereum network Begin setting up in-app wallets for end-users 2019 Q1 Third-party security audits Food delivery partnership agreements 2019 Q2 Release a new website just for restaurant owners/managers Build web-based wallets for restaurants to facilitate advertisement SAGE © John Vincent Eagan 2019 SAGE Business Cases Page 6 of 15 Munchee, the SEC, and Utility Tokens
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help