This paper is based on four in-depth case studies on the information and communication technology (ICT) evolution of Chinese tobacco companies. The ICT transformation processes of these companies are introduced briefly. A strategic grid model was used, which shows that depending on a company's strategic grid cell, different behavior patterns can be observed, in terms of Nolan's stage model. The analysis shows that companies allocated in the "turnaround" and "strategic" cell do not behave accordingly to Nolan's stage model. A few years after China first application for a World Trade Organization (WTO) membership renewal in 1986, observed companies skipped some of Nolan's stages to achieve an accelerated ICT transformation. Therefore, a fast transformation of ICT plays a major role for Chinese tobacco companies to face the challenges entailed by an open door policy and the WTO entry. This conclusion is limited to companies that are allocated either in the "transformation" cell or the "strategic" cell.
Topology design of artificial neural networks （ANNs） is an important problem for large scale applications. This paper describes a new efficient pruning method, the multi-weight optimal brain surgeon （MWOBS） method, to optimize neural network topologies. The advantages and disadvantages of the OBS and unit-OBS were analyzed to develop the method. Actually, optimized topologies are difficult to get within reasonable times for complex problems. Motivating by the mechanism of natural neurons, the MW-OBS method balances the accuracy and the time complexity to achieve better neural network performance. The method will delete multiple connections among neurons according to the second derivative of the error function, so the arithmetic converges rapidly while the accuracy of the neural network remains high. The stability and generalization ability of the method are illustrated in a Java program. The results show that the MWOBS method has the same accuracy as OBS, but time is similar to that of unit-OBS. Therefore, the MWOBS method can be used to efficiently optimize structures of neural networks for large scale applications.
Retailing is an important component of every country’s economic system. The current status and developments in the informization of Chinese retail industry were investigated by using questionnaires and interviews to survey 139 retailers throughout China. The investigation shows that Chinese retailers are in the initial informization stage, and can be classified into different types with corresponding informization characteristics. In addition, the survey identified the key problems faced by retailers in the initial stage. Developments in the information technology field were analyzed to identify the key technologies that Chinese retailers should focus on during the informization process. The investigation also shows that the retailers have not arrived at a consensus about information technology adoption, and thus hesitate to use new information technologies, such as the radio frequency identification.
