Research On Pricing Methods Of Commercial Remote Sensing Satellite Image Data Products In Fuzzy Environments

Satellite remote sensing technology concentrates the latest research achievements in space,optics,electronics,earth science and computer communication.Its applications reflect the level of scientific and technological development of a country to a great extent.Remote sensing satellite image data products are one of the most important application achievements.They are pictures or videos taken remotely from satellites.To date,the global high resolution remote sensing satellite has gradually realized marketization,commercialization and industrialization.As commercial products,the pricing of commercial remote sensing satellite image data products is an important decision for enterprises to realize profits.Therefore,this paper aims to solve the pricing problem of commercial remote sensing satellite image data products under fuzzy environment.By comprehensively applying the latest theoretical achievements of fuzzy set theory,product pricing theory and game theory,several novel fuzzy pricing methods are proposed in this paper.The main research contents are as follows:(1)A new concept,neutrosophic fuzzy variable,is put forward,and its special case(triangular neutrosophic fuzzy variable)is studied.Then,the truth membership function,indeterminacy membership function and falsity membership function are defined.Furtheermore,the concrete calculation formulas of the expected value,optimistic value and pessimistic value are provided.(2)A game pricing method considering market structures is proposed.According to the different game scenarios between providers,a Bertrand game pricing model and a Stackelberg game pricing model are respectively established based on the game theory in neutrosophic fuzzy environments.Afterwards,by means of the expected value function of neutrosophic fuzzy variable,the fuzzy pricing models are transformed and solved.As a result,the equilibrium prices of commercial remote sensing satellite image data products can be obtained in neutrosophic fuzzy environments.Finally,the feasibility of the proposed methods is illustrated through a case study.Sensitivity analyses of the key problem parameters and weight coefficients in the models are also conducted.(3)A game pricing method considering risk preferences is proposed.Based on the hypothesis of providers’ limited rationality,a Bertrand game pricing model and a Stackelberg game pricing model considering risk preferences are respectively established according to different market power structures in neutrosophic fuzzy environments.By means of the optimistic value criterion of neutrosophic fuzzy variable,the fuzzy pricing models are transformed and solved.Consequently,the equilibrium pricing formulas of commercial remote sensing satellite image data products considering risk preference can be obtained in neutrosophic fuzzy environments.Then,a case study is used to illustrate the feasibility of the proposed methods.Last,sensitivity analyses of key problem parameters and confidence level in the models are made to illustrate the impact of participants’ risk aversion behavior on pricing decisions.(4)A pricing method based on multi-criteria decision-making is proposed.According to the product selection behavior of end-consumers,main criteria affecting the evaluation of commercial remote sensing satellite image data products are identified.Moreover,dissimilar types of fuzzy numbers are adopted to express different evaluation criteria based on their distinctive characteristics.Subsequently,the traditional Artificial Fish Swarm Algorithm(AFSA)is modified to calculate creitria weights.Then,the traditional Multi-attribute Border Approximation Area Comparison(MABAC)method is improved to select the optimal products.Finally,a case study is provided to illustrate the decision-making process of the hybrid AFSA-MABAC method.The feasibility and effectiveness of the proposed method are systematically analyzed as well.(5)A pricing method based on multilevel programming is proposed.According to the cooperation and reciprocity between providers and consumers,interactive multi-level programming models are established in neutrosophic environments.The membership functions of neutrosophic set are defined,and multiple conflicting objective functions are converted into a single fuzzy objective function from different angles.Interactive multilevel programming methods based on the scoring function,the Technique based on Similarity to an Ideal Solution(TOPSIS)and Multi-objective Optimization by Ratio Analysis(MOORA)are proposed,respectively.Therefore,a pricing that both suppliers and consumers are satisfied with can be obtianed.Last,the model construction and solution process are illustrated through a case study.Sensitivity analysis and comparative analysis of different methods are also conducted.(6)A pricing method based on evolutionalry game is proposed.Focusing on the evolutionary process of providers and consumers,the strategy combinations of groups are identified based on the hypothesis of limited rationality of providers and consumers.Then,a payment matrix and an evolutionary game model are constructed.Afterwards,the variation tendency of providers and consumers is analyzed in the dynamic environment,and evolutionary stability strategies are obtained through replication dynamic equations of providers and consumers.Furthermore,equilibrium analyses of evolution paths under different circumstances are carried out.Finally,the feasibility of the proposed method is verified by example illustration and sensitivity analysis.As a resut,guidances and management implications can be provided for providers to make pricing decisions.