Small Business Acquisition of Computer Technology

This research investigated the selection process employed by small business firms in the acquisition of computer technology. The first decision that must be made by the small business owner or manager in relation to the acquisition of computer technology concerns the development of an in-house capability as opposed to contracting for computer support. Significant in the context of this decision are comparisons of cost, service time, and reliability. The second decision that must be made by the small business owner or manager in relation to the acquisition of computer technology concerns the decision rules for the in-house computer capability that will be developed. These decision rules are related to cost, performance, flexibility, ease of learning and ease of use, and expandability.

A sample of 104 owners and managers of small business was selected. The members of the research sample were grouped according to three business classifications--industrial, retail, and services. Overall selection procedures and decision rules relative to the acquisition of computer technology were identified. Additionally, differences in the selection procedures and decision rules were analyzed by comparing the responses to business classification.

The research found that small business owners and managers do not view outsourcing as a viable option for the acquisition of computer technology. The research also found that, in relation to trade-offs, sma

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amount of information to a decision-maker is a relatively short period of time. While some information is superior to no information, more information is not necessarily superior to less information. What is also significant about computer developed information is that it is typically high quality, as well as being massive and timely. The computer also has the capability of improving information. Such improvement may occur through a number of different processes, including the following: (1) the reorganization of data into formats which are either more easily understood, or which are more readily usable for specific applications; and (2) the manipulation of data, in order to determine what relevant relationships are present within a body of information or to remove extraneous data from a body of information. In the early 1970s, new approaches to decision analysis began to emerge. Two of these newer approaches have gained wide acceptance, and each of the approaches is heavily dependent upon use of the computer, if optimal effectiveness is to be attained. These two decision analysis techniques are probabilistic forecasting, and multi attribute analysis. Probabilistic forecasting permits a decision-m

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