Research On Schedulinging Model Of Online Customer Service From The Perspective Of Service Profit Chain

With the advance of information technology, the competitive advantage ofnetwork comes from the ability to attract and keep customers, the high quality ofonline customer service on the network platform is an important means to establish agood cooperation relationship between organizations and customers. Customers arethe subject of business activities and the source of profits, who have self-determationespecially when engaged in trading activities. If there is no scientific and reasonableonline service mechanism, it will influence customer satisfaction seriously. Inaddition, the traditional FCFS service rule has been unable to create reasonablesatisfaction for all customers and results in widespread loss of customers leading tothe failure of economic revenue maximization ultimately. Based on this background,online service platform must take a decision-making method to response to customers’service requests, then generates customer service scheduling scheme fastly in order togive guidances on the management of online customer service and improve customersatisfaction. Therefore, this thesis combines mathematical model and artificialintelligence optimization algorithm to solve the scheduling problem of onlinecustomer service.Firstly, the thesis introduces the concept of customer service value and builds ascheduling model of online service based on the the service value equation from theperspective of the service profit chain. Then we select some variables and parameterswhich objectively describe each element of model and are established a equivalentrelationship as a goal to maximize all customers’ service value. Secondly, the thesisput forword a optimization strategy based on the service value for the online servicescheduling problem from the point of view of the service profit chain and give detailsof the specific ideas and processes of QPSO algorithm used in this research. Finally,the thesis uses Matlab language to program the model and QPSO algorithm, after thatwe do some numerical examples of different data scale to generate both the solutionsof model and the best scheduling scheme. Meanwhile, the QPSO algorithm’sefficiency and convergence effect are analyzed according to the data results.In this thesis, the numerical examples’ results prove that the model is feasibleand valid. Besides, QPSO algorithm can generate the optimal online servicescheduling schemes under a variety of data scale fastly. These tasks verify the excellent performance of QPSO algorithm, it suggests that QPSO algorithm can besuccessfully applied to solve the scheduling model and provides a new idea andmethod for the online customer service scheduling problem.