Factors Influencing the Development and Adoption of Knowledge Based Decision Support Systems for Small, Owner-Operated Rural Businesses DON KERR School of Management, Griffith University, Kessels Road, Nathan, QLD, 4111 Australia (E-mail: d.kerr@mailbox.gu.edu.au) Abstract. This paper provides an analysis of existing literature and practical problems associated with the adoption of a developed knowledge-based decision support system (KBDSS) within small rural businesses. The rural small businesses selected for this study were individual farms within the Australian dairy industry and the developed KBDSS was called DairyPro. The object was to determine the factors that could help with future KBDSS development and improve adoption rates. These factors were tested against DairyPro to determine their effectiveness. This analysis indicates that system developers need to have a good working knowledge of the target industry and to understand the types of decisions that are made by managers in order to develop systems that will be used. A review of the literature also suggests that adoption rates can be influenced by cultural, political, educational and age factors as well as individual characteristics of information technology itself. Small business managers needed more ownership in the process of KBDSS development. The author suggests that the factors affecting KBDSS adoption by dairy farmers can be equally applicable to other small, owner-operated rural businesses. This approach advocates the use of domain experts to provide esti- mates of expected production levels rather than that of the traditional approach of using the results from mathematical or simulation models to make these estimates. Keywords: decision support, knowledge based systems, small business 1. Introduction In Australia, and many other countries, the majority of rural businesses are owner-operated. According to Kilpatrick (1999), 99.6% of Austra- lian farm businesses are family owned. This data suggest that many agricultural decision support systems (DSS) are developed for use by family owned, small businesses. Cox (1996) and Newman et al. (1999) suggest that most agricultural DSS have been based on research models that have the primary aim of discovering and understanding relation- ships between data, or applied models used as decision or policy making tools. Many of these systems have not had widespread acceptance by Artificial Intelligence Review 22: 127–147, 2004. Ó 2004 Kluwer Academic Publishers. Printed in the Netherlands. 127