| With the development of economy and technology,the competition in the market is becoming fiercer.Due to the stochastic,diversity characteristics of customer demand,the competition among the enterprises gradually turns products to services.Modern call center is taken as the main link between service provider and customers,so it is the focus of manager and academic as well that how to improve the quality of service by using advanced technology and management mode.Currently,call center with delay information has been widely applied,and delay information is that call center provides customers information about anticipated delays,so waiting customers can get delay information as the visible queue,and then decide their behavior subsequently.Managers effectively make use of this mode to modulate the demand and control the congestion of system.However,incorporated with delay information,human resource management method has not been been proposed.Since delay information has a great impact on call center performace,old staffing method can result in the loss of revenues and profits.In view of this,this dissertation designs queueing systems of call centers with delay announcements and proposes the effective staffing method with the combination of customer patience.This work is a a constituent part of the National Nature Science Foundation under Grant(71271052)and the National Science Fund for Innovative Research Groups under Grant(71021061).Based on the development project of the Liao Ning Mobile Company in China,with the characteristics of single skill and multi-server queue,from the perspective of psychology in queue,this dissertation designs the queueing system with delay information and takes its staffing,establishes the mathematical model with delay information,and develops the solution algorithms for different objections and takes the analysis of queueing theory,and makes use of simulation technology to verify the validity and the effectiveness of approximation method and solution algorithm.To sum up,this dissertation focuses on the five key problems:(1)The decision model of announcement coverage with customer updated patence is provided.From the perspective of psychology in queue and considering the impact of queue length on customer patience,the queueing system with delay information and updated patence is designed.Two types of the decision model of announcement coverage are established from two aspects of perspective.One is for the maximum utility of call center,the influence of delay information on the customer's patience and balking and reneging behavior is addressed,and the chaotic search algorithm is developed for the optimal announcement coverage.The other is for the two maximum utilities of call center and customers,a non-cooperative game model is formulated with delay information and customer patience,and the optimal announcement coverage and the utility under different operation regimes change the rules.(2)A state-dependent Markovian approximation for call center with delay information is provided.Motivated by real call center data with a Voice Response Unit,the patience distribution and updated scenario are studied.According to the fit and analysis of real call center data,a queueing sytem with hyperexponential patience distribution is established.Based on a state-dependent Markovian approximation,a method for estimating virtual delays is proposed and all performances are soloved,and then the delay announcement is incorporated in the system with hyperexponential patience distribution.For demonstrating the effectiveness of Markovian approximation for the call center with delay information,a simulation model is established by general programming language(c++)using discrete event-based scheduling method,and then the queueing system with delay information by analytic method is compared with simulation model.(3)Staffing call centers with delay information is provided.From different objective and performance-constraints,two kinds of models with staffing are established.One is taking call center with delay information as the focus,given that delay information has the influence on system performance,a staffing model with balking and reneging contraints is established,and some related performances are derived by applying queuing theory for steady state probability,and the fixed point algorithm and bisection method are designed for the optimal staffing level.The other is from the perspective of a customer satisfaction segmentation,customer satisfactions with delay information,short abandonment and quick answer are described.For the maximum revenues of call center,a staffing model with multi performance-constraints is established.(4)Staffing call centers with customer satisfaction is provided.Specifically,it mainly concludes the following two aspects.One is taking call center without delay information as the focus,the link between customer satisfaction with waiting experences and repeated behavior is addressed.For the maximum revenues of call center,a staffing model using queueing theory is established.The other is taking call center with delay information as the focus,customer satisfaction with delay information and repeated behavior are structured.For the maximum utilities of call center,the decision model with staffing and announcement coverage is established.(5)Staffing call centers with a deterministic fluid approximation is provided.Considering the impacts of retrial and abandonment on call center performance,a call center with delay information is established by a deterministic fluid approximation,and some related performances are derived for steady state probability.Through the comparison with two kinds of approximation,the effectiveness and the accuracy of the deterministic fluid approximation are demonstrated,including the comparison between the fluid approximation and Markovian method for the stochastic system with delay information,and the comparison between the fluid approximation and simulation mehod with C++ for the system with delay information and retrial.And then demand forecasting and staffing under retrial are analyzed by the fluid approximation. |
PDF Full Text Request