The primary goal of this study is to predict the next logical and practical approach in the use of advanced Decision Support Systems (DSS) and Artificial Intelligence to find and evaluate markets for prospective products. In addition to determining these markets, DSS will then be used to predict the success of the market and other product lines that can be brought to those markets, making companies more successful in the structuring of marketing models and product lines.
[keywords] Decision support system; artificial intelligence; marketing; DSS; marketing model; 1ST; IS; global marketing
Information Systems Technology (1ST) is becoming a more prominent part of global marketing. With the aid of 1ST, companies can become competitive in all phases of customer relations (Ives and Learmonth, 1984). The use of information technology for finding markets is expanding, enabling companies to keep up with prospective markets in today's dynamic economy. 1ST accomplishes this feat by helping marketing departments determine targets for their products and charting the most effective way to cover the largest market in the shortest amount of time. They also enable marketing to establish trends so that new products coming to market can be quickly evaluated and decisions made on the best placement for these products.
Information Systems (IS) today are designed with reusability in mind. They span multiple markets, enabling companies that design products to sell them to several different companies interested in gaining an edge with respect to the marketing of their products (Bakos, 1991). IS includes Advanced Decision Support Systems (DSS) that are able to assist businesses in making decisions about a market without the need for investing costly resources testing that market with product. The DSS can test and even predict the way in which a particular market will respond to certain products without the need to release those products into the market. IS scientists use databases with prediction models, and in some cases Artificial Intelligence (AI), to model the healthiest market for a particular product or to create models for a particular market of interest (MaLec, 2002).
Evaluation of Current Systems
The following is a concise evaluation of Decision Support Systems and their history. Some discussion of these systems and how they are used today for the furthering of marketing decisions is also presented. When a clear understanding of the current technology has been presented, it will be possible to continue to the next section, which will delineate the future of DSS and AI.
History of Decision Support Systems (DSS)
The history of DSS arguably began in 1965; some of the earliest beginnings of DSS are represented in Table 1 (Power, 2003).
Other milestones that helped along the way include the creation of tools like Lotus 123(TM) and Microsoft(TM) Excel(TM), both of which enabled people to crunch numbers and view them in a presentation manner not available before the 1980s. Tremendous hardware advancements and the reduction in computer size also contributed to DSS development. IS moved from being luxury that only very large organizations (such as the Department of Defense or I. B. M.) could afford to be an operation with a budget footprint that most businesses could handle.
One of the most prevalent technologies today is the relational database system. With the appropriate data, relational database systems are able to predict the best potential markets for prospective products. Unfortunately, the appropriate data is not always available, and new product lines are not able to take advantage of such systems. Therefore, relational systems often lack the ability to predict the best markets. More promising and relatively successful technologies are Expert Systems, Fuzzy Logic, and Artificial Neural Networks (ANN).
Expert Systems. …