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Citation

Thesis Title
Forecasting the Decline of Superseded Technologies: A comparison of alternative methods to forecast the decline phase of technologies

Read article at Massey Research Online:

Technology commonly declines rapidly on arrival of an innovative substitute shortening the economic life of a firm's technological assets, and undermining a firm's return on capital. Mr MacRae's investigation found pro-innovation bias, with research focused on innovation growth rather than existing asset decline. He addressed this bias through investigating three well-established forecasting approaches: statistical models, analogous data models from historic examples, and the judgment of expert forecasters when applied to decline. The average of all historic decline data was as accurate a forecast as the best statistical models, even a straight-line drawn through the last few data points provided a better forecast than the statistical models. A panel of experts also bettered the statistical models. While the literature says people forecast such declines poorly; it seems, on average, that this is not the case. Mr MacRae's research results provide the first simple guidelines for forecasting existing technology decline.

Supervisors
Professor Malcolm Wright
Dr Kesten Green
Dr Ravi Balasubramanian