Business Models,Operation Models and Service Development of IPTV

IPTV,as a newborn service,is restricted on market operation by multiple factors. Therefore,exploration is required in respect of its business,operations and service provision models. First,an IPTV industry value chain can be formed by integrating the advantages of the existing business models of telecommunication,broadcasting and TV,and Internet industries,which helps realize win-win cooperation of all the parties on the chain. Second,plans for technology implementation and network deployment should be made after comprehensive consideration according to various development stages of the IPTV. Third,a reasonable profit allocation model may promote the growth of IPTV services. Last,market competitiveness will be improved by services bundling. Generally,IPTV will become a breakthrough point for the strategic transformation of telecom operators and meet their innovation demands. Therefore,IPTV is expected to be a promising technology helping telecom operators find more growth space in the information communication market.

The role of bias correction on subseasonal prediction of Arctic sea ice during summer 2018

Subseasonal Arctic sea ice prediction is highly needed for practical services including icebreakers and commercial ships,while limited by the capability of climate models.A bias correction methodology in this study was proposed and performed on raw products from two climate models,the First Institute Oceanography Earth System Model(FIOESM)and the National Centers for Environmental Prediction(NCEP)Climate Forecast System(CFS),to improve 60 days predictions for Arctic sea ice.Both models were initialized on July 1,August 1,and September 1 in 2018.A 60-day forecast was conducted as a part of the official sea ice service,especially for the ninth Chinese National Arctic Research Expedition(CHINARE)and the China Ocean Shipping(Group)Company(COSCO)Northeast Passage voyages during the summer of 2018.The results indicated that raw products from FIOESM underestimated sea ice concentration(SIC)overall,with a mean bias of SIC up to 30%.Bias correction resulted in a 27%improvement in the Root Mean Square Error(RMSE)of SIC and a 10%improvement in the Integrated Ice Edge Error(IIEE)of sea ice edge(SIE).For the CFS,the SIE overestimation in the marginal ice zone was the dominant features of raw products.Bias correction provided a 7%reduction in the RMSE of SIC and a 17%reduction in the IIEE of SIE.In terms of sea ice extent,FIOESM projected a reasonable minimum time and amount in mid-September;however,CFS failed to project both.Additional comparison with subseasonal to seasonal(S2S)models suggested that the bias correction methodology used in this study was more effective when predictions had larger biases.

Service Mechanism and Pricing Based on Fairness Preference of Customers in Queuing System

Service providers often adopt the mechanism of customer classification due to the heterogeneity of customer waiting cost. However, the classification service may cause unfairness feeling of regular customers, then affect the revenue and social welfare. This paper provides the first exact analysis about the situation that service providers offer two classes of non-preemptive priority service when customer fairness perception is explicitly modeled. We model customer fairness perception as a negative utility on regular customers that’s proportional to the waiting time difference between the two queues. By analyzing a stylized M/M/1 queue in monopoly service system, we can derive important results some of which reaffirm existed research results. First, from the perspective of revenue maximization, service providers should adopt the mechanism of customer classification and set up the two kinds of customers where they can see each other. Next, considering customer utility maximization,service providers should cancel the mechanism of customer classification, and keep one queue(regular customers) only. Then, from the perspective of social welfare maximization, service providers shouldalso adopt the mechanism of customer classification but set up the two kinds of customers where they cannot feel each other. Finally, this paper concludes the optimal pricing based on customer classification in the above three different perspectives. This research shows important reference value and practical significance for service providers who adopt the mechanism of classification service.

ESTIMATING CROSS-TRAINING CALL CENTER CAPACITY THROUGH SIMULATION

Call centers have grown world-wide during the past decade. One of the most important aspects considered by call center managers is the optimization of its operators, which implies covering the highly variable demand and f＇mding an efficient way to assign people to certain shifts in order to achieve a desirable service level and abandonment rate. Another challenge is determining which system setup is appropriate for the specific call center. Should we have a single-skill call center or multi-skill call center？ If we do have the latter, how many multi-skill agents should we have on staff？. In this case study, we generate and analyze discrete-event systems simulation-optimization models to test the behavior of a real-world call center under the actual configuration and under different levels of cross-training. The model results help call center managers by： 1） determining the optimal number of operators needed for different staff configtmations in order to achieve the targets for service level and abandonment; 2） providing information about the trade-off between the key measurements in the call center; and 3） providing useful information about the number of operators needed and used for each hour of operation to estimate the number of four-hour shifts required to achieve the performance targets. Our experimental f＇mdings from this case study suggest that a bi-skill call center is economically better in the long-rtm compared to a full-skill or single-skill call center. This case study augments the call center body of knowledge by providing additional managerial insights for the operations management community.

Flexibility in matching

We examine a service system that matches jobs and candidates with different ability levels.A candidate’s ability will affect the possibility of obtaining a high return on a job assignment.Based on the property that the jobs to be assigned to a candidate are substituted in an assignment problem,we propose a novel random parameter generating process to demonstrate that the expected reward increases with the ability level of a candidate at a diminishing rate.This observation is consistent with the classic result in process flexibility literature that a little flexibility(i.e.,ability level)can capture the most benefit.Our observations can help a company decide the proper level of ability.

Advances in Ecological Applications of Fengyun Satellite Data

In recent years,the remote sensing based on meteorological satellite observations has become an important tool for assessing global ecological conditions.Since the early 2000,Fengyun(FY)satellite data have been widely used to derive the key parameters of ecological environment in China.An integrated earth-observation system has been developed in China through using FY satellite data,including retrievals the key ecological parameters as well as to constructions of long-term data records of vegetation index,land surface temperature,net primary production,vegetation health index,and so on.Considerable progress has thus been made in the application and service for prevention of air pollution,management and control of ecological redline,ecological monitoring for the Belt and Road Initiative,and assessment of ecological environment for human settlement.In order to monitor the ecological parameters in real time and with a full dynamic coverage,it is necessary to improve the technology in application of ecological remote sensing from meteorological satellites,and further enhance the ecological meteorological service.