Not All Great Technology Changes the World

In 1986, I was a 19-year-old college student who spent way too much time in the student center arcade at the University of Alabama. One of my favorite games was Super Mario Brothers, and I probably fed enough quarters into it to pay my tuition for a semester.

So imagine how thrilled I was when I learned that Nintendo, the company that made Super Mario Brothers, was releasing a system that would allow someone to play what was remarkably similar to the arcade version right in their own home. While it would be several years before this poor college student would get his hands on one, plenty of like-minded people essentially lined up to give Nintendo their money for this ground-breaking technology.

Contrast this with the 2024 release of the Apple Vision Pro, which was just as unique, maybe even more so, than the Nintendo Entertainment System (NES). The Vision Pro was more than just another virtual reality headset. It introduced a new approach to spatial computing, blending digital content with the physical world in ways few consumers had experienced before. And yet, while the Vision Pro has not been considered a failure, it has not achieved the widespread consumer adoption many observers expected.

So why did one innovation immediately capture the imagination of consumers while the other has struggled to find a similar audience?

Communication scholar Everett Rogers, in his landmark book Diffusion of Innovations (Rogers, 2003), uses the NES as a case study to explain how new technologies spread through society. Rather than attributing the NES’s success solely to better technology or good timing, Rogers argues that consumers adopted Nintendo because it aligned closely with five perceived characteristics that influence whether an innovation succeeds.

Rogers’ analysis resonated with me because I lived through it. I remember the excitement surrounding the NES, the anticipation of new games, and the cultural phenomenon that Nintendo quickly became. Reading his explanation made me realize that my enthusiasm wasn’t driven solely by the technology itself, but by the way I perceived it. More surprisingly, his framework also offers a compelling explanation for why Apple’s Vision Pro has struggled to generate the same level of consumer enthusiasm.

Rogers (2003) argues that consumers evaluate innovations through five perceived attributes: relative advantage (is it better than what I have now?), compatibility (does it fit my life?), complexity (is it easy to understand and use?), trialability (can I try it before committing?), and observability (do I see other people benefiting from it?).

The NES fit very nicely into all five. For people like me, Nintendo wasn’t introducing the idea of home video games. Atari, ColecoVision, and Odyssey had already made that concept familiar. Nintendo simply promised a dramatically better version of something we already understood and wanted. It was ridiculously easy to use – a five-minute hookup to the TV, pop in a cartridge, turn it on and start playing. Every toy store, department store and video rental store seemed to have one set up as a demo. As soon as you saw one, you wanted one, because you knew the days of dropping quarters into slots would be over.

Now contrast that with the Apple Vision Pro. The Vision Pro’s relative advantage is technologically impressive, but much harder for the average consumer to translate into everyday value. As a result, there’s a certain amount of trepidation on the part of many about using it, and even those who do, find it difficult to master. The only place to really try one is in an Apple store, and it’s really hard for many to see how much better their life would be if they had one.

Whether Rogers’ theory fully explains the different adoption patterns of these two technologies, however, is less clear. Subsequent research (van Rijnsoever et al., 2009) has suggested that Rogers’ five attributes should not be viewed in isolation, but instead often work together. Consumers rarely evaluate an innovation on a single characteristic; rather, perceptions of usefulness, compatibility, complexity, trialability, and observability influence one another. That was certainly the case with the NES. If it had been technologically superior to the Atari but the size of an arcade cabinet and took hours to set up, its adoption would almost certainly have been slower. Likewise, if Nintendo had never placed demonstration units in toy and department stores, requiring customers to purchase the console sight unseen, it is difficult to imagine it becoming the cultural phenomenon it did. For products like the NES—and, arguably, the Apple Vision Pro—the combined effect of all five attributes appears more important than any single one.

The Vision Pro, however, may have been at a disadvantage from the very beginning. A 2019 study looked at social media discussions surrounding the Oculus Rift and HTC Vive, two virtual reality headsets that were dominating the market at the time, but hadn’t found widespread consumer acceptance. The researchers found that many posters questioned the lack of applications, limitations of the technology, limited opportunities to experience them before purchasing, and price (Laurell et al., 2019). These were some of the same questions that many have raised about the Vision Pro, especially the cost, which was more than $3,500 at its launch (the Rift was $400 and the Vive was $600). It immediately positioned it as a luxury purchase outside the budget of most middle class households. My first thought when Apple announced the price was that many families would have to choose between buying one and paying for something far more practical, such as their children’s braces. Whether that comparison was entirely fair is beside the point—it illustrates how quickly consumers evaluate an innovation in terms of perceived value. Those findings suggest that many of the barriers consumers identified several years before Apple’s headset appeared align closely with Rogers’ attributes of relative advantage, trialability, and compatibility.

But could there be other plausible reasons for the Vision Pro’s lack of widespread adoption? Possibly. The field of research surrounding the adoption of virtual reality is extensive. A review of 158 studies found many potential explanations, including the Technology Acceptance Model (two main beliefs shape choice – perceived ease of use and perceived usefulness), Unified Theory of Acceptance and Use of Technology (four main beliefs shape choice – performance expectancy, effort expectancy, social influence and facilitating concerns) and the Theory of Planned Behavior (behavior is guided by intentions, which are shaped by three core factors: attitudes, subjective norms and perceived behavioral control), among others (Fares et al., 2024). The authors concluded that while Rogers’ theory is a good place to start, the actual reasons why virtual reality has had a hard time gaining traction with consumers is more nuanced. To me, these theories seem less like competing explanations than different ways of describing the same decision-making process. I just don’t believe that any virtual reality system—whether the Rift, Vive, Vision Pro, or another competitor—has yet convinced most consumers that it provides enough everyday value to justify its cost.

That’s where the NES shone. Among my friends, no one ever questioned whether buying one was a good idea, and it remained popular long after Nintendo released successor systems. Today, working vintage units can still sell for more than their original retail price on eBay. And while I bought other systems, both for myself and later for my son, I never sold my NES. It’s still in a box in my attic, waiting for me to pull it out and hook it up to my TV. And I’m still saving quarters.

Fares, O. H., Aversa, J., Lee, S. H., & Jacobson, J. (2024). Virtual reality: A review and a new framework for integrated adoption. International Journal of Consumer Studies, 48(3), Article e13040. https://doi.org/10.1111/ijcs.13040

Laurell, C., Sandström, C., Berthold, A., & Larsson, D. (2019). Exploring barriers to adoption of virtual reality through social media analytics and machine learning. Journal of Business Research, 100, 469–474. https://doi.org/10.1016/j.jbusres.2018.10.007

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

van Rijnsoever, F. J., van Hameren, D., Walraven, P.F.G., & van Dijk, J. P.  (2009). Interdependent technology attributes and the diffusion of consumer electronics. Telematics and Informatics, 26(3), 229–240. https://doi.org/10.1016/j.tele.2008.05.001