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Gauging the Success of Is

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Gauging the Success of IS

 Reginald R. Blanding

Embry-Riddle Aeronautical University

Mgmt. 424 Aug 2017

                                   Prof. Robert A. Miller


In recent times surrounding the devastating economic turmoil in the world, there are organizations that continues to increase their spending on Information Technology(IT) By increasing the budgets with in this sector they are looking for a return on these investments. Information Technology dynamics in this world has had an influence Environmental, Organization, and Human factors; that may make it kind of difficult and a little hard to measure the success of Information Systems(IS).

        It’s very surprising how many different tools, and techniques have come to be in existence in such a short operational duration of Information Systems, with the many practical uses of IS with in organizations like knowledge management systems, e-commerce, decision support systems, computer-mediated communications, and many others. The normal limits and zones have been shuffled around trying to assess the many variety of practical ways Information System is used in every up and running organization that researchers may have established different models for success (DeLeon, W.H. (1992). A lot of the systems and models are focused on emphasizing a need for a more consistent success metric.

This paper should give you a better knowledge of the way to measure Information Systems role in the different industries, sectors, organizations and other firms where it may be used. Numerous models based on the systems dating back to the 1970s-80s until today has been shown in this paper including the DeLone and McLean (D&M) model of IS success (1992). A actual example of the IS success management used in the company Bissell Homecare in Walker gives a clear example to detail.

                                           Single Measurement Approach

Research of the effectiveness of Information Systems was in its infancy in the 70’s and 80’s. A good amount of the studies that were performed at that time was focused on a single variable of successes of IS to describe the whole system. The researchers gave a basis for the development of more effective models, to including DeLeon & McLean. In various forms, studies of IS effectiveness using one of the following single variable approaches continue to this day.

2.1 System Quality: Essentially (hardware and software), this is the measure of System Quality is meant to describe how well the processing system did its job. This measure is mostly technical and objective depicts the passing of the design of engineering of information systems at that time.

2.2 Information Quality: The quality of the content of information systems. It is often pragmatically defined as: "The fitness for use of the information provided." Although this pragmatic definition is usable for most everyday purposes, specialists often use more complex models for information quality.

2.3 Information Use:  Researchers have put out an idea of how much people will use the system described how good the system really was. For these researchers, in what quantities and how people used the systems was the most important. The system used for measuring Information Systems effectiveness was defined, however, it had multiple opinions as to what type of use weather voluntary, or involuntary, actual use or reported use, etc.… (Trice, A.W. 2011), spoke of how utilization is measured by effectively using the correct reference theory, and how both the independent and dependent variables in studying Information System effectiveness.

2.4 User Satisfaction: Computer user satisfaction (and closely related concepts such as System Satisfaction, User Satisfaction, Computer System Satisfaction, End User Computing Satisfaction) is the attitude of a user to the computer system (s)he employs in the context of his/her work environments. User satisfaction surveys continue to be an important measure of success for many systems; there is ongoing research into the different affects of a user’s overall satisfaction, including that of cognitive style described later in this paper.

2.5 Individual Impact: The individual impact of an Information System is difficult to define due to the measure ultimately will relie on the amount in production for the user, which can be affected by an infinite number of factors. The research will measure the change in Information Systems and how it affects an increase in productivity, speed of a user, and decision effectiveness. Empirical studies have shown the effectiveness of an IS by having individuals place a dollar value on the information, Hilton & Swiernga (1982).

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