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End user productivity is a specific classification that focuses on the final end user of computing technology. A considerable amount of work has been associated with end user productivity. Deleon & McLean (1992) identify six major categories of information system success: system quality, information quality, use, user satisfaction, individual impact, and organizational impact. Seddon (1997), in his extension of Deleon and McLean's work, further defined the categories and added several more variables.
Each of the categories identified can also be used as surrogate interpretations of productivity, based on how you define the term "output" in the productivity equation. Common variables have included: user satisfaction, response time, system reliability, usefulness, timeliness, frequency of use, satisfaction, decision quality, and effectiveness just to name a few. Shayo, Guthrie & Igbaria (1999) present a good overview of the variables used.
In reviewing these different studies it can be observed that a separate classification can be made based on the degree of interdependence between the studies' dependent variable (whatever it may be defined as) and the hardware component of the technology. An example is the relationship between response time and processor speed.
The first category would include relationships that have a weak interdependence, such as studies on frequency of use, decision quality, and usefulness. These dependant variables, it can be argued, have a low correlation with hardware characteristics. The second category would include those relationships that have a strong interdependence, such as response time, system reliability, and timeliness. It is obvious that there is a large, if not direct, correlation between these variables and the associated hardware on which they depend. This study looks at the second of these categories. It is intended to isolate and measure the impact that simply changing the processor can have on end user productivity.
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