Background

The unprecedented growth of Information Technology (IT) has inspired IT practitioners, researchers, developers, and innovators to seek new, more sophisticated, and more effective acceptance and usage methods (Agarwal and Prasad, 1998a; Moore and Benbasat, 1991; Taylor and Todd, 1995). Interest in the subject has been manifested in the abundance of R&D based projects undertaken to identify the factors that lead to successful adoption and use of IT in general and Decision Support Systems in particular (DSS) (Agarwal and Prasad, 1998a; Agarwal and Prasad, 1998b; Davis, 1989; Rose and Straub, 1998; Thompson and Rose, 1994). The last two decades have generated a multi-disciplinary research body that expands over the field of technology, Human Computer Interaction (HCI) and social psychology to shed light on user acceptance of technology (Agarwal and Prasad, 1998a; Agarwal and Prasad, 1998b; Davis, 1989; Rogers, 1995). Resulting from the research findings, many models have been developed to predict the relationship between user perception and technology acceptance and use. The Technology Acceptance Model (TAM), initially developed in 1986 by Fred Davis, has been used extensively and is respected in the industry (Davis, 1989; Moore and Benbasat, 1991; Taylor and Todd, 1995; Thompson, Higgins, and Howell, 1991).

Computing technology and information systems represent substantial investments for organizations; investments on which they hope to realize a return in areas such as making effective Strategic Decision Making (SDM) and improving efficiency. Simply acquiring the technology is insufficient. In order to obtain the anticipated benefits, it must be used in context of its end users. The most expensive shortcoming of DSS is that it is not typically used in making effective strategic decisions. However, if all the different variables that could affect this usage were considered in their specific environment, then CEO and other users would be more likely to apply the technology in all the different stages of SDM. There are many factors affecting the utilization of IT in supporting effective SDM. These factors range from the systems themselves, the organizations that use the systems, the decision-makers and the overall environment. Yet, recent studies of technology acceptance and usage have only been concentrated in the technologically developed world. Certainly, of the large number of IT acceptance and usage studies covered in recent literature reviews, few if any took place in the developing world (Rose and Straub, 1998; Thompson and Rose, 1994). The developing countries clearly have their own unique characteristics; research in these countries is indeed required to enhance our understanding of DSS acceptance and usage and this will enable us to identify the steps required for a more sustainable approach to the implementation and use of this technology.

This research study examines and defines the factors that influence DSS usage in making strategic decisions in local governments in Egypt. By understanding these factors, managers can develop strategies to increase the utilization of the DSS. The research is of value to local authorities in Egypt for four main reasons:

• Understanding the factors affecting user acceptance of DSS: knowledge of the factors affecting user acceptance of DSS, how they can be measured, and how they relate to each other is crucial in the development, implementation, and successful management of DSS. With this knowledge, interventions during implementation (such as training or involving user in development) can be used to increase user acceptance and usage.

• Prediction of user acceptance of DSS: before investing a large amount of money in technology, an organization must be able to predict whether the investment will be accepted and used.

• Selection of alternatives: relative measures of user acceptance can be used to choose between alternative technologies.

• Guiding development: measurement of specific aspects or elements of a technology which affect user acceptance can be used to provide guidance to system/software developers as to which of these aspects or elements are important to the decision maker or need to be improved to use the system effectively. This knowledge can also be used in the early stages of software development to identify potential problems before they occur or sort them out easily.