MA v. Uber & Lyft Witness Tracker

	A	B	C	D	E	F	G	H	I	J
1	MA v. Uber & Lyft- Witness Tracker \| Maintained by Vidushi Dyall - Chamber of Progress
2	Witness				Key Arguments- ABC Test			Key Points that Each Side Gleaned from Witness Testimony
3	Called By	Name	Affiliation	Testimony Date	Drivers are free from the control of Uber/Lyft	Work is performed outside the usual course of the Uber/Lyft’s business	Work is done by someone who has their own, independent business or trade doing that kind of work	MA Key Points	Uber Key Points	Lyft Key Points
4	Plaintiff- Massachusetts Attorney General	Daniel Liestra Jones	Industrial Economics, Incorporated	5/13/2024		X		Designated as an expert in financial analysis; opined: U/L receive revenue primarily from driver service fees; key factors impacting revenue generation: driver supply, investment in driver incentives, demand for transportation, seasonality, improvements to platform; language used indicate U/L hold themselves out as a transportation company	Jones focused solely on U mobility segment & ignored delivery/freight which make up 56% total revenue; U charges fees riders, drivers, couriers, eaters, merchants, and restaurants for use of platform; Jones cherry picked 5 factors from the SEC 10-K out of 63- many were tech focused; ignored rider incentives when saying that driver incentives hold more weight	Driver incentives used to balance supply and demand because I can't tell drivers where to go since they don't have control over them; Lyft listed on NASDAQ- tech focused companies; no opinion that U/L don't talk about drivers as also being customers; agreed tech is important part of biz; a company can be in both the transportation industry while being a tech company
5	Plaintiff	David Weil	Brown University	5/14/2024		X		Designated as an expert in assessing/evaluating biz model of company; opined: U/L pursue profit by providing quality/affordable safe transportation to get customers, riders, from point A to B,using tech/real time info/algorithm refinements, to match drivers; keys of biz model: distinctive brands, decoupled pricing, rider pricing, driver pricing/driver earnings, managing cost of rides; platform companies that U/L are compared with have very different models	Drivers are the ones who decide to render services to riders; terms of service don't guarantee quality, safety or suitability of 3rd party providers; drivers may use U if they have job and for supplemental income; U provides drivers with services: payment processing, safety, matching, and dynamic pricing; U provides economic value to both rider and drivers and they should pay some value for that benefit.	Even taxis, who are considered independent contractors, can't set their rates- they are unilaterally set by regulators; U/L view riders/drivers as customers they need to incentivize; no need to create programs for employees (engineers, data scientists, lawyers); U/L is very similar to other marketplace companies (Airbnb/Etsy): U/L key to profitability is matching process & drivers are offering labor/property(cars); U/L are an economic intermediary like transportation broker; U/L can't tell drivers when/where/how much to work or to accept a task
6	Plaintiff	Ilana Bryant	Special Forces	5/16/2024	X			Designated as an expert in branding and advertising strategy; opined: based on ads reviewed the value proposition for U/L is: to provide comfortable, safe, and reliable rides; definition of a customer is someone who pays for a service	Offered no opinion on the value of U's tech/apps to their biz;. Bryant's team collectively interpreted ads but didn't conduct consumer research/surveys to corroborate interpretation; unaware if drivers also pay fees but agreed drivers are also value prop of U/L; matching algorithms and app interface also provide convenience, reliability, and safety	Excluded driver targeted ads in her analysis; of thousands of ads put out by U/L, couldn't say how many she didn't consider; both drivers and riders are target audiences of U/Lmarketing activities
7	Plaintiff	Kyle Tsyvaer	Driver	5/16/2024	X	X	X	Driver for Uber and Lyft for ~10 years; drives with U/L for ~20 hours a week per app; U/L make unilateral decisions on how much time given to accept ride, rider info provided, estimated payout, take rate; U/L determines terms of pay for partially completed rides or rides that take longer than estimated; drivers used to have more information on surge pricing	Tysvaer has started numerous businesses that he runs as sole proprietorships; he filed a PPP loan for his driving business, in the taxi industry, that was used to pay himself; never told to drive at a specific time or when to log onto app; can take time off without permission; chooses to maximize $ by chasing surges and working at night; switches between U/L for most lucrative opportunity	Tysvaer declines 75% of ride requests; switched his schedule from weekday mornings to weekend evenings; has taken long breaks before turning app back on with no adverse consequence; didn't need to inform anyone of taking break
8	Plaintiff	Christopher Hansen	Driver	5/16/2024	X	X	X	Driver for Lyft from 2019-2021; didn't know how many riders/drivers were in an area; sometimes needed to wait a long time for ride request; faced "swapping" when the accepted ride is automatically switched to another, which could be less lucrative		While working in MA, he was employed at Harvard University and now is employed at UMich; would have needed to request time off if testifying in personal; did not need to request any time off when driving; when a driver, drove on and off with breaks of up to months at a time before rejoining the app without issue
9	Plaintiff	Chris Arning	Creative Semiotics	5/17/2024	X			Tendered as an expert in semiotics; opined: U/L sway more towards the transportation section both in the way they talk about their goods/services and industry they're in; created “codes” for transport & marketplace tech companies that were used in analyzing at U/L ads	Failed to identify marketplace tech codes that could've also been interpreted in ads (didn't consider imagery of softball as nostalgic); even if U focused more ads on their tech/apps/matching it wouldn't change his classification	8 step analysis is a "modus operandi", not used by other semioticians; no 2 semioticians have arrived at different conclusions; analyzed ads containing unique typefaces and saturated colors but did not mark corresponding tech codes
10	Plaintiff	Lindsey Cameron	University of Pennsylvania	5/20/2024	X			Designated as an expert in organization control; opined: U/L exercise organizational control through gamification meant to keep drivers on apps (i.e enticing in-app sounds and rewards); other ways U/L exercise organizational control include: short timeframe to accept rides (confined choice), drivers don’t know how price is created (opaqueness), ride streaks (gamification), and drivers don't have many trip options (confined choice);	Cameron didn't analyze quantitative data in connection with case & the broad goal of qualitative analysis is to create new theories, not test them; qualitative research can’t be fully tested and “reliability” is not a term used by qualitative scholars who use qualitative methods; her conclusions can’t be replicated; drivers know there is a matching algorithm, upfront pricing, loyalty programs, incentives, rider ratings, reactivation, and geo tracking	Drivers express a sense of autonomy and Cameron didn't opine that they have a false consciousness; loyalty programs are aimed to increase more driving over a longer amount of time but there is still a high amount of churn; wasn’t able to say if in case of 100% driver refusal, whether U/L would still be exercising organization control
11	Lyft	Esin Arsan Karasabun	Lyft	5/21/2024	X	X		L has waitlist of drivers who apply to use the app; drivers see how much riders pay after ride is over; drivers supply their own phone and car without reimbursement from L; L decides the timing of launch; L controls matching process		Hundreds of L employees work exclusively on driver app; pain point survey of drivers define roadmap of new features; driver feedback led to increase time to accept ride and more ride/pay info; L provides drivers with various tools: queue feat, map overlays with raw data, location/radius filters, Ride Finder product, earning goal product
12	Lyft	Benjamin Chase	Driver	5/22/2024	X			L selects matches; couldn't see how many other drivers or riders were nearby; couldn't communicate with rider when request comes in; L determined price and couldn't negotiate; has website for other biz but not driving; sets prices in his other biz		Drove on and off for L; driving biz helped support his family and other biz; started driving between FT employment to fill gap; chose when he would drive and would take time off to support newborn and wife; only drove for couple months at a time; could log on after months of inactivity without issue; thought of L as platform used for business enabling him to connect with riders; used funds from driving for bills while working on growing other biz
13	Lyft	Tiouan Jehl	Lyft	5/22/2024		X		Excluded driver targeted ads in her analysis; of thousands of ads put out by U/L, couldn't say how many she didn't consider; both drivers and riders are target audiences of U/L marketing activities		Data scientist at L for dispatch and matching algorithm teams; mission of dispatch team is providing best platform for drivers and good experience for riders; mission of algorithm team is to increase driver utilization, not reduce earnings;uns exp on both drivers and riders
14	Lyft	Jeremy Bird	Lyft	5/22/2024		X		L could have introduced upfront pay and ride demand products sooner; announced earning commitment promising drivers at least 70% of far but doesn't include this in TOS or driver addendum; L uses a variable fee opposed to a fixed fee; L has never exited a market; MA accounts for 3% of rideshare volume		L’s mission is to create a marketplace that matches riders with a destination mind with drivers with a car and resources; focus this year is to increase driver earnings bc this is top request from customers; creating products that provide more info to drivers which increases utilization; rating has virtually no impact on drivers; median gross earnings in MA is $36 an hour; L national avg commision rate is 12% per ride; reclassification would lead to negative exp for riders in rural areas and for drivers; L is not equipped to make major tech changes needed for employment framework (create shifts, interview, hiring process), L would leave MA if reclassification occurs
15	Lyft	David Riege	Lyft	5/23/2014	X	X		Increased use of incentives means more revenue for L; began decoupled pricing in 2018; rider and driver pay used to be set by a rate card; under rate card, L has less flexibility to experiment with pay models; up front pay obscures payment logic; matching algorithm is optimized for profitability of L		Director of product management; driver earning team builds products dealing with base earnings and incentives; incentives make up less than 15% of driver earnings; L made changes with upfront model because drivers were hungry for more info to make decisions individually on which trips they wanted and which they did not; L charges fee for creating platform and features for drivers and riders- ie.matching services, payment processing
16	Lyft & Uber	Chris Stanton	Harvard Business School	5/24/2024	X			Relied on data set from Uber/Lyft; unaware of driver reward programs that aim to decrease amount of multi-apping; drivers cannot complete rides from different apps simultaneously; if multi-apping only took into account P2 & P3 time, drivers couldn't multi-app	Assignment was to analyze data (15M rides, 58K drivers) and the extent that drivers multi-app; concluded: drivers who use Uber/Lyft platforms routinely engage in multi-apping,drivers who engage in multi-apping do so regularly, and drivers who use Uber/Lyft the most are more likely to engage in multi-apping; of U drivers who multi-app: 38.6% of drivers multi-app at some point, 35.5% of drivers multi-app at same time (using app simultaneously), and of drivers that multi-apped, 91-92% did it using apps simultaneously; 45.9% of drivers who multi-app do so on least 80% of active days on the app; overall conclusion: robust multi-apping phenomenon, where most active users engage look for opportunities across platforms and choose how they engage with each platform.	Assignment was to analyze data (15M rides, 58K drivers) and the extent that drivers multi-app; concluded: drivers who use Uber/Lyft platforms routinely engage in multi-apping,drivers who engage in multi-apping do so regularly, and drivers who use Uber/Lyft the most are more likely to engage in multi-apping; of L drivers who multi-app: 48.3% of drivers multi-app at some point, 44.5% of drivers multi-app at same time (using app simultaneously), and of drivers that multi-apped, 92% did it using apps simultaneously; overall conclusion: robust multi-apping phenomenon, where most active users engage look for opportunities across platforms and choose how they engage with each platform.
17	Lyft	John Bonham	Driver	5/24/2024	X			Used to own carpentry biz where he set his prices and built rapport with customers; can't see how many drivers/riders are in area; L chooses rider matches; doesn't know if he is getting highest or lowest paying offer; no repeat customers		20 year retiree from carpentry; began driving for L to earn $ to go on family vacation; uses his earnings to travel; prefers driving in AM; doesn't seek out bonus zones and prefers using queue feature to keep him busy; doesn't care about tier/status in loyalty program; wouldn't drive for L if he had shifts " I like being my own boss, choosing my own hours"; chose to testify because he doesn't think reclassification is fair
18	Lyft	Deborah Jay	Jay Survey Strategics	5/24/2024	X		X	L had final say over survey questions; contact info on survey was L employee; some questions were open ended and others were closed; question on what drivers do while waiting for ride did not include option "waiting in car"		Conducted scientific survey with representative sample of people who use the Lyft driver app in MA; focal questions:. What, if anything, do drivers do when they are logging in but not on their way to pick up a rider or driving a ride?,Do drivers who use the Lyft driver platform use other gig economy platforms?, What if anything do drivers consider when using the Lyft driver platform?, The reasons why drivers use the Lyft driver platform?,How important, if at all, flexibility is to drivers who use the Lyft driver platform?; 513 randomly selected drivers out of survey universe were contacted; 666% drivers listen to radio/podcasts while logged onto app before accepting ride; 43% use at least 1 other gig work app
19	Lyft	Kevin Clark	Driver	5/28/2024	X		X	L provides training material to drivers; L needs to approve new car before using app; L gives drivers sticker and light display; can't set prices; riders don't pay drivers directly for service; drivers get paid on weekly basis from L via direct deposit		Clark is driving for L but is in between jobs and looking for full time employment; used to also drive for car service company but switched to only L because it was more lucrative and offered more flexibility; likes rating feature because he won't be paired with someone he rated poorly; doesn't care about L fees: “I see the ride and what I’m gonna get paid and I decide whether I’m gonna accept the ride.”; no interest in setting prices or negotiating because it would demand extra time and effort; views L as where he outsources services of his business (dispatch, payment processing)
20	Lyft	Mary Ellen McAllister	Driver	5/28/2024	X			Had to inform L when she got a new car; rating and cancellation score is important to her; no option to opt out of L tracking rating and cancellation; on Etsy, her customers can reach out to discuss custom work and she adjusts her pricing accordingly		Began driving because she quit her IT job and needed a mental break and loves driving; she describes herself as very "entrepreneurial" and has another business- making crafts that she sells on Etsy; no desire to set prices of rides because her "expertise is not there"; she stays away from bonus zones and congested areas; values the queue function; stopped driving because she got tired of it and reentered the IT workforce
21	Lyft	Paul Oyer	Stanford	5/28/2024	X			The ability to fire workers is a form of control; L can remove drivers permanently aka deactivation; in some cases drivers are deactivated for having low star ratings		Expert in labor economics; analyzed level of autonomy and control and flexibility of Lyft drivers relative to other types of work settings and likely effects on L, if using employment model; on any given day with at least 1 ride, 54% of drivers spent less than 2 hours driving; 90% spent less than 4 hours; vast majority spend less than 10 hours driving; 92% spend less than 20 hours a week driving; concluded there is no typical L driver or typical week of working; even high use drivers spent many weeks driving less than 10 hours or off the app completely; drivers make different choices in terms of when to drive and are idiosyncratic on when/how much they drive
22	Lyft	Daniel Friedman	Lyft	5/28/2024	X	X		L trademarks various phrases like "Your friend with a car" and "Riding is the new driving."		VP of marketplace growth; L views riders and drivers as customers and markets towards both groups differently; L spends more marketing $ on drivers; L markets the "what", not the "how" because it has limited time to get through to customers
23	Lyft	Catherine Tucker	MIT	5/29/2024	X	X		L uses decoupled pricing and variable commissions even though it doesn't cost L more to process payment or implement rating system on higher fare rides; the pricing algorithm maximizes profits; drivers are customers purchasing services but they don't know how much they are paying until after the ride is completed; rewards program are to increase driver retention and commitment which benefits L		Expert in platform economics and marketing; assignment was to describe differences between 2-sided platforms and traditional businesses, evaluate if L was a 2-sided platform or something else, and evaluate some features of L's platform that the AG was suggesting were indicative of control; Tucker concluded that L is a 2-sided platform with 2 distinct groups of users, main job of facilitating interactions between the groups, and creates value via network effects; rebut MA's expert separating U/L from other 2-sided platforms like Airbnb- all have the same defining traits; pricing is not a defining trait of a 2-sided marketplace-platforms take different approaches based on the type of interaction; U/L markets like other 2-sided platforms by focusing on industry context as opposed to underlying tech- Airbnb uses hotel language, Etsy uses craft language, Rover uses pet language
24	Uber	Chad Dobbs	Uber	5/29/2024		X		Take rate determined by U; fee not broken down by expense; many operating costs are fixed even though take rate is variable; customer support guidelines: say "independent driver" instead of "Uber driver" and cannot use Uber as verb or say drivers "get paid by Uber"; key metrics for spend are dependent on forecasted # of completed rides	Director of US city operations; tech company with 5K engineers, data scientists, product managers; division of teams to focus on drivers or riders; "tech IS the business"- algorithms for mobility, freight, eats; may refer to uber as transport in marketing because talking about tech can be confusing; no fleet of cars, planes, trains, buses; builds various features for drivers to use: Uber Pro, surge pricing, matching, payment processing, safety feats; operational expenses include data processing, support tech, and payment processing
25	Lyft	David Moyer	Driver	5/30/2024	X			He had to notify U/L when he got a new car to get it approved; was provided training material he was quizzed on; U/L limited how much he could use destination mode filter; didn't set prices for ride and needed to wait for payout		Drove 5-10 rides a week when fully employed as 30 hours when unemployed and looking for new job; used destination feature to allow him to drive along his commute; no longer drives because his new job and financial situation improved; proud of how he leveraged the app with his commute and to reduce carbon footprint; used both U/L platforms
26	Uber	Naser Zarrok	Driver	5/30/2024	X		X	Uber Quest feat motivated him to compete more rides; he takes advantage of surge to make more money; drives 6-7 days a week for 60+ hours a week; can only drive where U gives him a ride request	Used to be a limo driver and switched the company went down; started driving for U in 2014; is free to accept or decline rides; decides what rides he takes based on money and traffic; sees all relevant info when ride request comes in; works anytime he wants and on any day; doesn't want to be an employee; enjoys not being told where to go or what to do
27	Uber	On Amir	UC San Diego	5/30/2024		X		Ads target different parts of value proposition; a company can describe what value it provides to customers	Expert in marketing and rebuttal expert for Bryant and Arning; concluded that Bryant and Arning methodology is not reliable, testable, and is subjective; semiotics is not an accepted field; Uber is a 2 sided platform that markets to 2 audiences; most 2 sides marketplaces do not focus tech in ads, instead they focus on benefits to users
28	Uber	Jonathan Chabot	Driver	5/30/2024	X		X	Idle time or breaks are not compensated; he only gives rides where U provides request; completes 60-70 rides a week	Former driver for car service and bus driver; previously needed to rely on set schedule, had boss, and couldn't take time off or breaks; freedom is important to him; satisfied with earnings and believes he is compensated fairly
29	Uber	Edward Gannon	Driver	5/31/2024	X		X	Had to pass inspection and process was delayed bc of license/insurance issues; doesn't know why matches are made; can't communicate with rider when accepting request; U calculates and pays out earnings; can't see how many riders or drivers in an area	Began driving for U for supplemental income in addition to full time job worked evenings after work; had monetary goal he tracked in app for when he drove-time would vary; used UL on same day and at same time; liked having flexibility and didn't consider anyone at U as his boss; "it’s important to me… if I had lots of bills coming up, I could work more to do what I needed to do.”
30	Uber	Justin McCrary	Columbia Law School	5/31/2024	X	X		Data error: includes drivers from brazil with MA state code; relied on articles that were co-authored by advisors/former employees of U; was retained by U 9 times previously; some analysis did not consider P1 time (time spent logged on app before accepting ride)	Expert in labor economics and econometric methodology; 1 year data analysis: 6.3% of drivers work 1500+ hours (threshold for full time employees is around 2000 hours); 43% of drivers drive less than 50 days annually; 7% of drivers decline/cancel 90-100% of ride requests; concluded that wide variation of driving behavior is indicator that drivers exercise control; if U needed to factor in cost per worker for drivers, it would need to limit amount of drivers on platform
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100