1 00:00:02,040 --> 00:00:07,000 Speaker 1: Welcome to brain Stuff from how Stuff Works, Hey, brain Stuff, 2 00:00:07,080 --> 00:00:10,680 Speaker 1: Lauren Vogel bomb here. Why do restaurants use tipping? Is 3 00:00:10,680 --> 00:00:13,480 Speaker 1: it a reward for good service? Studies show that tips 4 00:00:13,560 --> 00:00:16,000 Speaker 1: don't go up or down significantly based on the quality 5 00:00:16,000 --> 00:00:21,120 Speaker 1: of service. Does tipping attract and retain better wait staff? Not? Really? 6 00:00:21,800 --> 00:00:23,520 Speaker 1: Is it a bribe so the waiter won't spit in 7 00:00:23,560 --> 00:00:26,119 Speaker 1: your soup the next time you come? Probably depends on 8 00:00:26,120 --> 00:00:29,520 Speaker 1: the waiter. In most countries, a service charge is included 9 00:00:29,520 --> 00:00:32,600 Speaker 1: in the bill. However, in America, instead of an upfront 10 00:00:32,680 --> 00:00:36,000 Speaker 1: service charge, diner's hand over fifteen or more of the 11 00:00:36,040 --> 00:00:38,520 Speaker 1: price of the meal to the server at their own discretion. 12 00:00:38,960 --> 00:00:42,440 Speaker 1: It's not required, but it is customary. But this seemingly 13 00:00:42,479 --> 00:00:46,920 Speaker 1: generous practice has some unpleasant hidden costs for starters. The 14 00:00:46,960 --> 00:00:50,040 Speaker 1: existence of tipping allows restaurants to pay servers a federal 15 00:00:50,159 --> 00:00:53,120 Speaker 1: minimum wage of two dollars and thirteen cents an hour, 16 00:00:53,760 --> 00:00:57,520 Speaker 1: so waiters in most states basically live and die by tips. 17 00:00:58,080 --> 00:01:00,480 Speaker 1: The result is that tipped workers are twice is likely 18 00:01:00,520 --> 00:01:02,920 Speaker 1: to live in poverty and depend on food stamps as 19 00:01:02,960 --> 00:01:07,920 Speaker 1: other workers. Then there's the opposite problem. In stronger restaurant markets, 20 00:01:07,920 --> 00:01:10,800 Speaker 1: like big cities, the existence of tipping means that waiters 21 00:01:10,800 --> 00:01:13,400 Speaker 1: in busy restaurants end up making a lot more money 22 00:01:13,400 --> 00:01:16,120 Speaker 1: than neque cooks and dishwashers, who get paid a fixed 23 00:01:16,120 --> 00:01:19,479 Speaker 1: hourly wage while working just as hard. Add to all 24 00:01:19,520 --> 00:01:22,199 Speaker 1: that mess the fact that America's tipping system is rooted 25 00:01:22,240 --> 00:01:25,720 Speaker 1: in racist hiring practices that emerged after the Emancipation when 26 00:01:25,720 --> 00:01:29,040 Speaker 1: white business owners were trying to avoid paying new black employees, 27 00:01:29,400 --> 00:01:33,920 Speaker 1: and tipping comes out looking decidedly ugly. So when does 28 00:01:33,920 --> 00:01:36,600 Speaker 1: it make sense to abandon tipping in favor of raising 29 00:01:36,640 --> 00:01:40,000 Speaker 1: restaurant prices so that all staff is paid fairly or 30 00:01:40,120 --> 00:01:44,120 Speaker 1: would customers bulk get that? Sarah Clifton is a mathematics 31 00:01:44,120 --> 00:01:47,280 Speaker 1: professor at the University of Illinois who specializes in modeling 32 00:01:47,319 --> 00:01:51,280 Speaker 1: complex social behaviors. In a recent paper, she created mathematical 33 00:01:51,360 --> 00:01:55,520 Speaker 1: models of two hypothetical competing restaurants, one with conventional tipping 34 00:01:55,560 --> 00:01:59,240 Speaker 1: and one without. The paper was published in the February 35 00:01:59,680 --> 00:02:02,920 Speaker 1: issue of Chaos, a journal from the American Institute of Physics. 36 00:02:04,120 --> 00:02:07,480 Speaker 1: The key variable in Clifton's models is the average tipping rate. 37 00:02:07,800 --> 00:02:09,919 Speaker 1: Tipping rates have been creeping up of the past few 38 00:02:09,919 --> 00:02:14,000 Speaker 1: decades from ten percent to fift and now close in 39 00:02:14,080 --> 00:02:17,680 Speaker 1: major US restaurant markets. Clifton's models are designed to be 40 00:02:17,760 --> 00:02:20,600 Speaker 1: as simple as possible, with every player in the system 41 00:02:20,720 --> 00:02:24,360 Speaker 1: motivated purely by monetary gain, meaning that when cooks are 42 00:02:24,360 --> 00:02:26,920 Speaker 1: paid better, they're more likely to stay, meaning that food 43 00:02:27,000 --> 00:02:29,919 Speaker 1: quality goes up. When waiters are paid less, they're more 44 00:02:29,960 --> 00:02:34,040 Speaker 1: likely to leave, decreasing service quality, but eventually the waiters 45 00:02:34,080 --> 00:02:36,760 Speaker 1: would return if diners flooded the restaurant because of the 46 00:02:36,760 --> 00:02:40,239 Speaker 1: food quality, which would presumably mean more profit and higher 47 00:02:40,240 --> 00:02:43,640 Speaker 1: wages for all. What Clifton found was that when the 48 00:02:43,680 --> 00:02:46,760 Speaker 1: average tipping rate crosses a certain threshold call it the 49 00:02:46,800 --> 00:02:52,079 Speaker 1: tipping tipping point, restaurants will make more money by abandoning tipping. Unfortunately, 50 00:02:52,200 --> 00:02:55,760 Speaker 1: Clifton doesn't have enough real world data to calculate exactly 51 00:02:55,800 --> 00:03:00,799 Speaker 1: what that magic tipping point is. Dozens of end restaurants 52 00:03:00,800 --> 00:03:03,200 Speaker 1: across the United States, led by New York chef and 53 00:03:03,240 --> 00:03:07,400 Speaker 1: restaurant tour Danny Mayer, began experimenting with no tipping policies. 54 00:03:07,880 --> 00:03:11,000 Speaker 1: These trend setting restaurants either increased MANU prices by an 55 00:03:11,000 --> 00:03:14,200 Speaker 1: average of twelve to fifteen percent or included gratuity in 56 00:03:14,200 --> 00:03:17,400 Speaker 1: the final bill. That way, the restaurants could distribute the 57 00:03:17,440 --> 00:03:21,040 Speaker 1: earnings more fairly and pay everyone a fixed hourly wage, 58 00:03:21,600 --> 00:03:24,679 Speaker 1: but this plan was not popular with the public. Michael Lynn, 59 00:03:24,800 --> 00:03:28,000 Speaker 1: a professor of consumer behavior at the Cornell University School 60 00:03:28,040 --> 00:03:31,960 Speaker 1: of Hotel Administration who researches tipping, reported that online customer 61 00:03:32,040 --> 00:03:35,160 Speaker 1: reviews of no tipping restaurants went south when those no 62 00:03:35,280 --> 00:03:38,560 Speaker 1: tipping policies were instituted, and we're worse when tips were 63 00:03:38,640 --> 00:03:43,240 Speaker 1: replaced with service charges. Lynn said, people hate service charges, 64 00:03:43,520 --> 00:03:45,760 Speaker 1: and if I increase my menu prices, They're going to 65 00:03:45,800 --> 00:03:48,360 Speaker 1: think I'm more expensive, even if the combined bill is 66 00:03:48,400 --> 00:03:51,600 Speaker 1: no different. In other no tipping restaurants, it was the 67 00:03:51,640 --> 00:03:55,440 Speaker 1: waiters who revolted. At Bar Agricole in San Francisco, servers 68 00:03:55,440 --> 00:03:58,000 Speaker 1: were used to making twenty five dollars to forty dollars 69 00:03:58,000 --> 00:04:00,920 Speaker 1: an hour, including tips, while the hitchen staff was only 70 00:04:00,960 --> 00:04:04,160 Speaker 1: making thirteen to twenty dollars an hour. When owner Thad 71 00:04:04,200 --> 00:04:07,840 Speaker 1: Woggler decided to ditch tipping, his cooks and dishwashers were psyched, 72 00:04:07,960 --> 00:04:11,760 Speaker 1: but the serving staff kept leaving for more traditional restaurants, 73 00:04:11,800 --> 00:04:15,400 Speaker 1: so Waggler like lots of other pioneering restaurant owners switched 74 00:04:15,440 --> 00:04:19,520 Speaker 1: back to the normal tipping scheme. Clifton, our mathematician, feels 75 00:04:19,560 --> 00:04:22,919 Speaker 1: that these restaurateurs were simply ahead of their time. She said, 76 00:04:23,200 --> 00:04:26,000 Speaker 1: when restaurant owners get rid of tipping too early, as 77 00:04:26,040 --> 00:04:29,000 Speaker 1: we've been seeing with some really nice restaurants, they sometimes 78 00:04:29,000 --> 00:04:32,160 Speaker 1: have to reinstate it because it's not profitable that would 79 00:04:32,200 --> 00:04:36,279 Speaker 1: conform with what customers want. Her model indicates that casual 80 00:04:36,320 --> 00:04:39,359 Speaker 1: restaurants should actually make the move before fancy ones, because 81 00:04:39,400 --> 00:04:41,680 Speaker 1: the point at which the tipping rate becomes profitable would 82 00:04:41,720 --> 00:04:45,239 Speaker 1: be lower for them than in the high end places. However, 83 00:04:45,600 --> 00:04:49,120 Speaker 1: Joe's Crabshack, a decidedly not high end chain, tested the 84 00:04:49,160 --> 00:04:53,200 Speaker 1: waters in late when eighteen of its restaurants abandoned tipping. 85 00:04:53,839 --> 00:04:56,640 Speaker 1: Although customers were essentially paying the same exact total for 86 00:04:56,640 --> 00:04:59,880 Speaker 1: a meal as they were when tipping was allowed, said 87 00:04:59,880 --> 00:05:02,960 Speaker 1: they didn't like the no tipping policy. According to restaurant research, 88 00:05:03,480 --> 00:05:06,119 Speaker 1: customers said they didn't trust management to share the money, 89 00:05:06,279 --> 00:05:08,799 Speaker 1: and they felt it took away incentive for good service. 90 00:05:09,440 --> 00:05:11,600 Speaker 1: Joe's dropped the no tipping policy less than a year 91 00:05:11,640 --> 00:05:15,000 Speaker 1: after it started, after losing eight of its customers. During 92 00:05:15,040 --> 00:05:19,279 Speaker 1: the trial, so Americans themselves haven't reached the tipping tipping 93 00:05:19,320 --> 00:05:23,040 Speaker 1: point yet. In the meantime, restaurants will likely keep experimenting 94 00:05:23,040 --> 00:05:26,760 Speaker 1: with various tipping policies until they find one that keeps customers, waiters, 95 00:05:26,839 --> 00:05:35,120 Speaker 1: and kitchen staff all equally happy. Today's episode was written 96 00:05:35,120 --> 00:05:37,720 Speaker 1: by Dave Ruse and produced by Tyler Clang. For more 97 00:05:37,760 --> 00:05:40,040 Speaker 1: about the history and science of tipping, check out our 98 00:05:40,040 --> 00:05:42,800 Speaker 1: episode on the topic over on my other podcast, food Stuff, 99 00:05:43,120 --> 00:05:45,880 Speaker 1: And of course, for more on this and other depressing 100 00:05:45,920 --> 00:05:49,359 Speaker 1: but important topics, visit our home planet, how stuff works 101 00:05:49,480 --> 00:06:01,120 Speaker 1: dot com.