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What is the technology adoption curve? Is it relevant to DSS?

The technology adoption curve (TAC) is a theory about how individuals and organizations behave in implementing innovative technologies. A quick examination of the framework shows some similarities to the product life cycle curve discussed in business marketing courses. The theory is however more sophisticated than a life cycle or a diffusion model. The underlying model of technology adoption identifies 5 types of adopters of technology with very different interests and buying characteristics. The companies and individuals that are first to adopt a new technology are called innovators. The second type is known as the early adopters. The third type is called early majority, then the late majority adopters and, finally, the laggards.

The technology adoption curve is a traditional bell curve with exponential growth in the beginning and a slowdown in adoptions occurring during the late majority period. When new technology is introduced, it is usually hard to get, expensive and imperfect. Over time, the technology's availability, costs and features improve to the point where a large population of users can benefit from adopting the technology. The innovators are technically oriented users and “visionary”. The laggards are practical and conservative. The early adopters are seeking a competitive advantage. Productivity issues and conformity influence the early and late majority adopters. Some technology innovations reach a “dead end” early in the adoption cycle. These immature or premature innovations never become “killer applications” like the VisiCalc spreadsheet.

To summarize: Innovators are enthusiasts who like technology for its own sake. Early Adopters have the vision to adopt an emerging technology and apply it to an opportunity that is important to them. Early Majority adopters are pragmatists who do not like to take the risks of pioneering, but are ready to see the advantages of tested technologies. They are the beginning of a mass market for the new technology. Late Majority adopters are also pragmatists and this group represents about one-third of available customers. This group dislikes “discontinuous innovations” and believes in tradition rather than progress. The late majority buy high-technology products reluctantly and do not expect to like them. Traditionalists (or laggards) don't really like technology. This group performs a “reality testing” service for the rest of us by pointing out the discrepancies between the day-to-day reality of a technology product and the claims made for it.

This model, TAC, is relevant to understanding the adoption of various decision support technologies. Model-driven DSS are probably at the late majority stage, but Web technologies have reinvigorated that type of DSS and changed its adoption curve. Data warehousing and OLAP are probably still in the hands of the early majority. Customer Relationship Management (CRM) may be at a dead end. Communications- Driven DSS are being adopted quickly. Knowledge-driven DSS are probably still in the early adoption stage. Document-driven DSS are evolving with the Web technologies. Some DSS have been dead ends.

Don Norman is credited with first explaining the technology adoption curve model. See an example of applying the curve to microprocessor technology at http://www.startribune.com/digage/curve.htm. Moore's model of technology adoption prescribes that a company can not expect to target a mass market directly with a technology innovation. Rather, the company must first target the early adopters. So what do you think? Does the technology adoption curve hold for innovative decision support applications? Will data visualization tools follow this curve? What about OLAP or data warehouses? Simulation models and optimization? Or Web-based DSS?

Reference

Moore, G. A., Crossing the Chasm, HarperBusiness, New York, 1991.

The above response is from Power, D., What is the technology adoption curve? Is it relevant to DSS? DSS News, Vol. 2, No. 13, June 17, 2001.

Last update: 2005-08-06 17:50
Author: Daniel Power

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