In theory, companies base decisions on whether or not to buy a new technology on an objective assessment of its merits and demerits. In practice, however, it doesn’t always work that way. Random events and ‘copy-cat’ behaviours among competitors play a significant role in the spread of innovation.
New products and technologies often fail to depose inferior ‘incumbents’. (The classic example is the Dvorak keyboard, which, despite being more efficient, lost out to the original QWERTY model in the 1930s.) New products and technologies of equal strengths often go on to win unequal shares of the market.
The dynamics of competition are complex. They can, however, be partly explained by ‘path dependence’, the theory that early events shape the diffusion or adoption and acceptance of innovative products.
Recent research sheds new light on path dependence in the business-to-business environment. Based on a quantitative study of two comparable and contemporaneous technologies, it lays bare the influence of random or chance events and of ‘social learning’ in the spread of innovation.
The study focuses on the diffusion of the DC-10 and L-1011, two wide-bodied jets introduced in the 1970s by McDonnell Douglas and Lockheed respectively. The airplanes were both developed to serve the growing market for long-haul, smaller-capacity aircraft and were so technologically similar they were referred to as ‘twins’ by the media. Their long-term commercial performance, however, was very different.
Early design flaws in the DC-10 caused fatal accidents. The airplane was temporarily grounded by the Federal Aviation Administration and, unsurprisingly, lambasted in the press. Nonetheless, after the initial years of competition, it consistently outsold its rival, usually by a factor of two. While the DC-10 went on to be the base for future models, the L-1011 was discontinued.
One of the key differences between the two planes was the timing of their entry into the market. Initial production of the L-1011 was delayed due to the receivership of Rolls Royce, its engine supplier. The DC-10, on the other hand, was luckier. It ‘got there’ earlier, achieved an early sales lead and, despite its design faults, was able to adapt more quickly, benefitting from economies of scale as its market grew. Its success, however, was not solely a function of ‘first-mover’ advantage.
The research finds that ‘social information processing’ was a big factor in the history of both aircraft and underlay their respective successes and failures. When updating their fleets, airlines were influenced by the choices of other companies — particularly those of a similar size and with a similar market and routes. In their rush to obtain the competitive advantage offered by the new technology, they seemed to ‘listen’ more to social sources than their own judgement of technical merits. If a ‘proximate’ competitor had adopted a technology, an inference seemed to be made that they had done so on the basis of positive information about its design.
The results of the research contradict classical models that suggest the best technologies are ‘revealed and chosen’ through ‘organizational search’. They help explain why the link between the quality of an innovation and its commercial success can be weak. “Diffusion processes,” say the researchers, “do not reliably spread the best innovations.”
The research has implications for both the producers and consumers of innovative technologies. The success or failure of a new technology dates from the period immediately after its launch. Once an innovation has the lead, ‘social information processing’ accelerates its spread.
Manufacturers can benefit from social information processing by:
Companies faced with the strategic decision of whether or not to invest in a new technology, meanwhile, need to think carefully before acting on the ‘cues’ provided by others. Social information processing is a flawed mechanism that can result in the amplification of small initial differences that have little or no impact on a company and can lead to the wrong product choice.
The risks of over-reliance on ‘social learning’ — and of being saddled with an inferior technology — vary with circumstances. Decision-makers will need to be particularly cautious in markets where the degree of uncertainty is high and competitive pressure intense.
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