That is HDt = (PDt. ADt. Apt. RDt). In general, the actual domain is only a small portion of the reachable domain. in turn, the reachable domain is only a small portion of potential domain, and only a small portion of the actual domain is observable. Note that HDt changes with time. There are many methods for helping us to upgrade or expand our habitual domains. (Cohen 2002) The Impacts of Information Technology on Decision Elements and Environment many studies have examined how a variety of information technology characteristics affected decision-making.
For example, O’Donnell and David reviewed 15 journals from 1987 through mid-1999, which identified 57 decision-making studies. Their literature review identified studies that provide empirical evidence about how information technology or features of information system can influence user decisions and how those features interact with other judgment and decision making variables such as: decision-making environment, problem-solving skills, and processing strategy.
One of the major ways that researchers have hypothesized that information technology or information system can influence decision-making is through variation in presentation format consisting of tables or graphs, multimedia presentations, hypertext systems, Geographical Information Systems (GIS), tree maps, and probability maps. However, a decision performance is a function of the decision elements, decision environment, and decision-making model utilized by a decision maker. For example, Payne et al.
13 described decision-making as a function of the context, the problem, and the person. Context variables recognize differences in the decision environment that could influence how a decision-maker interprets the elements and demands of the decision task. Problem variables include differences in decision attributes and differences in decision cues. Person variables represent differences in decision-making skills associated with different levels of task knowledge and problem-solving ability.
These variables interact each other to determine the strategy used for making a decision. In the rest of this section, we will discuss the impacts of IT on two dimensions of decision task, i. e. decision elements, and decision environment. (Seeley 1999) IT impacts on decision elements Let us take a look at an example. Suppose that you want to buy a new house in a new city. Because you do not know the housing market in the new city, it does not make sense for you to estimate the probability of buying a good house at a reasonable price.
You may ask some of your new colleagues or friends you can trust about the market for new houses in this city, or you can call a real estate broker to see what they have listed for sale. As you acquire more information, you become more familiar and more confident with the decision problem. When you reach a certain degree of confidence, you may decide to buy a house. In this decision problem, information input could come from many sources, including your spouse, family members and new colleagues or friends.
In addition, the broker who wants to sell you a house also plays an important role in the process of information input. The decision criteria in this problem include price, size of the house, the age of the house, location, convenience, neighborhood, interior design, appearance of the house, landscaping, home recreational facilities, etc. After you have identified a number of possible houses for consideration, i. e. alternatives, you may further narrow down the set of criteria that you are most interested in.
In the process, each time you talk to your friends or your broker, or take a tour of the available houses, you may change your preference and the conception about the market. As we can see in the above example, there are five basic elements involved in decision processes: decision alternatives, decision criteria, decision outcomes, decision preference, and decision information inputs. We briefly describe them as follows. (i) Alternatives are those choices that we can select or control in order to achieve our decision goals. (ii) Criteria are used for measuring the effectiveness or efficiency of the decision.
(iii) Decision outcomes are measurements in terms of the criteria, which can be deterministic, probabilistic, fuzzy, or unknown, (iv) Preferences over the possible decision outcomes determine which outcome would be more or less preferred than others. (v) Information inputs mean any message that is received by the decision maker, which may or may not affect the generation of alternatives, decision criteria, decision outcomes, and decision preferences with the aids of IT, these decision elements can be clarified and become more complete with less time and efforts.
For instance, in the example of buying a new house, you can browse websites on Internet to search any information about it. By doing so, you can take more criteria into consideration, which you did not know earlier, such as resale price, builder’s reputation, etc. Thus, the list of criteria to evaluate a new house will become more complete. Similarly, electronic photos of appearance of houses, and photos of interior design, etc. allows us to evaluate or screen alternatives, possible houses, without taking time to visit all possible houses.
IT also help decision makers clarify their preference structure by providing information such as pair wise comparison of decision outcomes acceptable or non-acceptable of some relevant criteria. A number of software for different decision models now can do this without much difficulty, eg AHP. The clearer picture of preference structure the decision makers have, the more satisfactory solution they would more likely to get. (Borenstein 1998)