In the context of globalization, the requirements on transport logistics continuously rise. Often goods travel through many different countries, using several transport modes and involving a number of different actors. Implementing some level of intelligence on the goods, which provide them with the capabilities to assist in the logistical activities, is one of the instruments that can be used to improve control and efficiency in transports and goods-handling. The concept of intelligent goods both opens up for new types of services and may be used to improve currently available services. The research is mainly focused on the characteristics, possible architectures, and applications of intelligent goods systems. In this context, an intelligent goods system refers to a number of interacting components, e.g. on-board units, servers, and RFID tags, which together provide intelligent goods services. Intelligent goods refer to goods with a higher degree of intelligence than just providing the ID of the goods, and generally the concept involve information processing and/or storage on or close to the goods, acting on behalf of the goods throughout the whole transport. The purpose of the studies is to investigate how intelligent goods can be used to improve goods transports in terms of more efficient goods-handling as well as better control of the goods and the transportation process, but also in terms of more efficient information sharing, e.g. between different actors. This may in turn provide reduced costs, environmental impact and usage of infrastructure. The research is concentrated on the communication and processing of information before, during and after transport. Most of the research results are applicable to ii goods transport by any mode, whereas some of the research has an emphasis on road transport. A framework is presented which can be used to describe intelligent goods systems, including the capabilities of the goods, necessary information entities related to the goods, as well as a number of primitive services that can be used as building blocks when creating more advanced intelligent goods services. Furthermore, a new approach to service description is proposed, which can be used to, amongst others, define an intelligent goods service and to perform architecture analyses. By identifying architectures corresponding to different service solutions, intelligent goods can be compared with other types of solutions, for instance more centralized approaches. In particular, different situations and services put different requirements on a system and the benefits of using intelligent goods vary. In order to investigate how intelligent goods may be applied in practice, two services have been examined in more detail: a dynamic shelf- life prediction service, and a consignment-level emission allocation service. These studies involve field tests, interviews and simulations. Finally, an investigation of how intelligent goods systems can be modelled as multi-agent systems is also included.