This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of unc...This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of uncertainty, irreversibility and choice of timing, which suggests that we can appraise KM investment by real options theory. Second, the paper analyses corresponding states of real options in KM and finance options. Then, this paper sheds light on the way to the application of binomial pricing method to KM investment model, which includes modeling and conducting KM options. Finally, different results are shown of using DCF method and binomial model of option evaluation via a case.展开更多
The container sea-rail multimodal transport system faces complex challenges with de- mand uncertainties for joint slot allocation and dynamic pricing. The challenge is formulated as a two-stage optimal model based on ...The container sea-rail multimodal transport system faces complex challenges with de- mand uncertainties for joint slot allocation and dynamic pricing. The challenge is formulated as a two-stage optimal model based on revenue management （RM） as actual slots sale of multi-node container sea-rail multimodal transport usually includes contract sale to large shippers and free sale to scattered shippers. First stage in the model utilizes an origin-destination control approach, formulated as a stochastic integer programming equation, to settle long-term slot allocation in the contract market and empty container allocation. Second stage in the model is formulated as a stochastic nonlinear programming equation to solve a multiproduct joint dynamic pricing and inventory control problem for price settling and slot allocation in each period of free market. Considering the random nature of demand, the methods of chance constrained programming and robust optimi- zation are utilized to transform stochastic models into deterministic models. A numerical experiment is presented to verify the availability of models and solving methods. Results of considering uncertain/certain demand are compared, which show that the two-stage optimal strategy integrating slot allocation with dynamic pricing considering random de- mand is revealed to increase the revenue for multimodal transport operators （MTO） while concurrently satisfying shippers＇ demand. Research resulting from this paper will contribute to the theory and practice of container sea-rail multimodal transport revenue management and provide a scientific decision-making tool for MTO.展开更多
基金This paper is supported by National Natural Science Foundation of China （NSFC） and Ph.D. Research Fund.
文摘This paper views knowledge management （KM） investment from the angle of real options, and demonstrates the utility of the real options approach to KM investment analysis. First, KM project has characteristics of uncertainty, irreversibility and choice of timing, which suggests that we can appraise KM investment by real options theory. Second, the paper analyses corresponding states of real options in KM and finance options. Then, this paper sheds light on the way to the application of binomial pricing method to KM investment model, which includes modeling and conducting KM options. Finally, different results are shown of using DCF method and binomial model of option evaluation via a case.
基金supported by the National Natural Science Foundation of China(No.71372088)the scientific research fund of Education Department of Liaoning Province (No.L2014179,L2013207)
文摘The container sea-rail multimodal transport system faces complex challenges with de- mand uncertainties for joint slot allocation and dynamic pricing. The challenge is formulated as a two-stage optimal model based on revenue management （RM） as actual slots sale of multi-node container sea-rail multimodal transport usually includes contract sale to large shippers and free sale to scattered shippers. First stage in the model utilizes an origin-destination control approach, formulated as a stochastic integer programming equation, to settle long-term slot allocation in the contract market and empty container allocation. Second stage in the model is formulated as a stochastic nonlinear programming equation to solve a multiproduct joint dynamic pricing and inventory control problem for price settling and slot allocation in each period of free market. Considering the random nature of demand, the methods of chance constrained programming and robust optimi- zation are utilized to transform stochastic models into deterministic models. A numerical experiment is presented to verify the availability of models and solving methods. Results of considering uncertain/certain demand are compared, which show that the two-stage optimal strategy integrating slot allocation with dynamic pricing considering random de- mand is revealed to increase the revenue for multimodal transport operators （MTO） while concurrently satisfying shippers＇ demand. Research resulting from this paper will contribute to the theory and practice of container sea-rail multimodal transport revenue management and provide a scientific decision-making tool for MTO.
