A nyone who has purchased a PC in the last 10 years knows the two basic results: the day after you buy a computer the price will drop, and as soon as you choose a computer a faster model will be released. While these factors may seem painful at the time, we are consoled by noting we will be able to buy faster, cheaper machines next year. But the real crux of the problem is how often should a you buy a new computer and what level of machine should you purchase? Technological change and investment requirements driven by Moore’s Law create the patterns we observe. Several writers [2, 3, 4, 6] have examined and attempted to measure these trends. As managers recognize, we all face the consequence of these trends when we purchase a computer [1]. Should we wait? Should we buy a faster PC? Should we buy the cheapest computer available? The problem with answering these questions is that it is exceedingly difficult to estimate the need or demand for computers. Even on a broader scale, researchers have found it challenging to identify the business impact of computers and IT spending. The productivity debate illustrates these problems [5]. A fundamental result of the performance and price changes is that organizations have to buy new PCs every few years. A conse-
[1]
R. Schaller,et al.
Moore's law: past, present and future
,
1997
.
[2]
Young Moo Kang,et al.
Computer hardware performance: production and cost function analyses
,
1989,
CACM.
[3]
Albert L. Lederer,et al.
The problems of rapid information technology change
,
1997,
SIGCPR '97.
[4]
Haim Mendelson,et al.
Economies of scale in computing: Grosch's law revisited
,
1987,
CACM.
[5]
H. Oosterbeek.
Returns from computer use: A simple test on the productivity interpretation
,
1997
.
[6]
Phillip Ein-Dor.
Grosch's law re-revisited: CPU power and the cost of computation
,
1985,
CACM.