Assessing the rate of change in the enterprise database system market over time using DEA

How do you measure the rate of change in a product category? Simple measures such as product life cycles do not necessarily measure performance change over time. Similarly, extrapolating a single performance criterion does not account for design tradeoffs. This paper builds upon previous work of using data envelopment analysis (DEA) to measure incremental innovation in technology by applying it to the online transaction processing market. A variable returns to scale DEA model is utilized to determine an annual rate of change in benchmarks based on data provided by the Transaction Processing Performance Council. This rate of change may then be used to forecast possible future performance trendsetters of the TPC. The underlying model of a database system used for this study was based upon price to performance, the DEA technique demonstrated here allows for much more complex models to be examined