Study On Collaborative Work Mechanism Of E-commerce Based On Integrated Simulation

Enterprises can integrate resources, reduce costs and improve performance through collaborative work. This paper employ integrated agent-based simulation and other simulation methods to explore the competitive and the collaborative work mechanism of e-commerce service chains, the collaborative management mechanism of e-commerce service provider coalitions, and collaborative affair work mechanism inside an e-commerce enterprise.The necessity and implementation how-toes of integrated simulation for collaborative work mechanism among e-commerce enterprises are described. By analyzing collaborative work process of intra-enterprise and inter-enterprise, we explain necessity of integrated simulation for special application. After concluding the general simulation methods, we present integrated simulation principles for collaborative work mechanisms of e-commerce enterprises. And then, implementation method of integrated simulation models in this paper are put forward and compared with common implementation platforms concerning agent-based simulation. The implementation uses Java to program the simulation models based on Repast. We also discuss how to verify the model by debugging and how to carry out qualitative and quantitative validation.The integrated simulation for e-commerce service chain's competitive and collaborative mechanisms is proposed based on multi-agents and optimal algorithm. The main idea of the proposed approach is based on a multi-agent system with optimal profit of the pull, push, and collaborative models among the portal access service provider (PASP), the product service provider (PSP), and the mobile service provider (MSP). To resolve all these modes, the agent evolution algorithm (AEA) is proposed based on traditional genetic algorithm. Furthermore, on basis of these, we design an integrated system framework with multi-agents and AEA. To examine the feasibility of the framework, a prototype system is implemented. As for simulation data, we try to mine there for an appropriate decision for each entity with regards to variety pricing strategies and risk preferences from game theoretic perspective. It is found that in the situation where a collaborative mechanism is applied rationally, the profit of players is higher as compared to the other two situations where a competitive mechanism is employed. If some constraints are applied, the collaborative state will exist and be stable, and the risk will be kept at a low level.The integrated simulation for collaborative management mechanism of e-commerce service provider coalition is studied based on cellular automata and evolutionary game. By assigning payoff matrix with fixed cost and punishment, we apply the dynamic equation to analyze for an evolutionary stable strategy for the group in coalition. By setting evolution learning rules including historical information and neighbor characters and considering personal decisional characteristic, the simulation system is implemented. Simulation results show that the different coalition scale have minor effect on macro trend of group behavior, and different individual distributions as well as different communication modes and punishment parameters have varying effect on group behavior.The integrated simulation for collaborative management mechanism of e-commerce service provider coalition is researched based on complex network and evolutionary game. By designing payoff matrix with payoff-shared and punishment-shared, we model replicate the dynamic equation to analysis evolutionary stable strategy of the group in coalition. By applying evolution learning rules including historical information and neighbor decision characters, the simulation system is implemented. Simulation results indicate that the scale of coalition have minor effect on cooperation trend and major effect on cooperation frequency of group, the different parameters of payoff matrix, the different group that are made up of individuals with variety decision-making characteristic, and the work difficulty have varying effect on group behavior.The integrated simulation with agent-based simulation and discrete simulation is applied to explore how collaborative work behavior interacts with dynamic tasks under collaborative work environment. An agent-based assessment model for matching between employees and tasks is presented, and two algorithms to allocate tasks to employees, namely, the minimal matching and the greedy matching algorithm, are designed. The two algorithms are then translated into the multi-agent simulation system. The simulation experiment results showed that minimal matching is better than greedy matching for rapid task allocation. Moreover, with the minimal matching algorithm, the different preference of manager has a rarer impact on completion effect of tasks than on the increase of individual capability; the following effects are evident:the different percentage of generalists and specialists have a distinct effect on task completion; the higher rate of individual capability is positively correlated with collaborative learning rate; and the different dynamic of tasks have different degree impact on the average rate of increase of capability of employees.