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 appli-cations. This paper describes a new efficient pruning method, the multi-weight optimal brain surgeon (MW-OBS) 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 rea-sonable 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 func-tion, 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 MW-OBS method has the same accuracy as OBS, but time is similar to that of unit-OBS. Therefore, the MW-OBS method can be used to efficiently optimize structures of neural networks for large scale applications.
eCRM ties customer relationship management with e-business. Very often, eCRM is interfaced with other information systems to form a seamless integration and interchange of information both inside and outside an organization—a work flow management system. This integration of business partners, sup- pliers, and customers is essential in this global competitive market environment. An effective infrastructure and hence an appropriate framework are required to provide the information exchange and data analysis between eCRM and work flow management. This paper proposes a functional framework of eCRM based on customer value to realize the win-win strategy for both the companies and their customers. Moreover, a workflow management system also forms an integral part of this total solution to facilitate the implementa- tion of a supply chain or extended enterprise.
It is becoming increasingly evident that in the future the Internet will host large numbers of software agents that aid or even act on behalf of companies and consumers to make decisions and carry out transactions. In this paper, we develop different pricing and ordering strategies with limited information requirements for e-retailers under the electronic business environment, and study the dynamics and performance of these strategies through multi-agent simulation. The results not only reproduce some phenomena in former literature, such as the "tacit collusion" and the cyclical price wars,but also generate new findings, for example, the "tacit collusion" does not always exist among hill-climbing e-retailers, and the cyclical price wars will be suppressed when e-retailers consider their competitors'strategies. The results show that in electronic business environments, to test different strategies and evaluate their performance by simulation before they are employed into practice is of great importance.
