And from a manufacturing/engineering point-of-view (which I am neither), I guess it's really hard to solve this problem.
You have some unpredictable 1/100 or 1/1000 defect that occurs long after production and sale.
Just how do you go about isolating the cause, and testing a solution? Make 5 changes, and put through a production batch of 1000 units, and then do accelerated testing? If 5 fail from one batch, and 2 from the rest, is there even enough statistical power to confirm that you've come across a solution? And you just burned through 5000 units.
Sounds like fun trying to solve this kind of problem.
Anecdotally confirming. When shopping around for the past 10 years, I've usually bought used PCs and used parts, both desktops and laptops, but after deciding to try out a Mac in early 2012, buying used just didn't seem to be worth the discount.
It doesn't seem to be so bad right now, but part of this may be due to my insistence on getting at least 4GB of RAM for a MacBook Air, which was hard to find on the used market.
I recall some years ago (7?), some other mac having some characteristic issue that could almost always be fixed with a little time in the oven.
Having a kitchen with an oven and living in a student area where Apple products were popular, I sensed a business opportunity.
I put up an ad on some local classifieds with a lowball price for these units (but not much different than what the broken ones would sell for on Ebay, minus the hassle). I quickly learned that, after investing in a premium product, people would rather hold onto their brick rather than turn it into at least some cash. I never even got a chance to try out the procedure, people would counter-offer with ridiculous prices for, what is for them, a brick.
The sunk cost fallacy at work.
edit: I think I even offered pickup and some data recovery/security as a part of the offer, no takers.
Yep, this is the kind of thing I want too. A few scenarios (assuming that one person is living in a particular place):
I want the thermostat (with knowledge of outside temperature and winds) to know that my HVAC can increase the temperature by, say, 1C every 30 minutes.
Based on what it knows about my location and biometrics, it can drop to the minimum to prevent the pipes from freezing or other problems when I'm gone, and know when my classes/work ends and commute time to turn on the system at just the right time to be pleasant for my arrival. Maybe detect/realize that I'm in a, or will be in a, traffic jam, and hold off accordingly.
Integrate it with my alarm clock to cool the bedroom by a few C overnight, but warm the place up so I'm not chilled when I get out from under the blankets.
Detect that I've gotten out of bed in the middle of the night, and start blasting heat into the bathroom.
I see this as an ongoing model/strategy for grocery stores and other retailers: Taking the Amazon approach where they're just distributors, and you pay for the shelf space, and a fee per transaction.
The manufacturer/distributor sets the price and the grocer could care less whether any sells at all, as long as they find a way to keep getting foot traffic.
I'll bet they'll never attribute the value to Youtube that comes from being able to better target ads off-Youtube based on your Youtube views. Youtube might lose on paper, but generate more value in total for Google than direct costs.
Google also gets a whole pile of AV to do speech-to-text and other analysis on (before any additional compression) that no other firm gets a chance to do.
Perhaps the used prices are propped up by a high number of units dying.