神经经济学和神经管理学的前沿

认知神经科学是一门阐明心理活动的脑基础,以揭示心理与脑的关系的科学。近年来,它与经济学、管理学等学科的交叉与融合,使得神经经济学、神经管理学等交叉学科进入人们的视野,并随之不断发展壮大。神经经济学与神经管理学的产生与发展给传统的经济学和管理学带来了极大的挑战,也出现了不少创新,在一定程度上促进了经济学和管理学的发展。

交通安全管理预案研究

在我国当前交通安全形势日趋严重的情况下 ,建立适合我国国情的交通安全管理体系具有重大的意义。本文的研究直接面向交通安全管理实践 ,以系统论、行为科学、管理决策学为理论基础 ,提出交通安全管理预案的概念 ,分析了它的功能与特性 ,探讨了交通安全管理预案的形成。

Application of a mixed DEA model to evaluate relative efficiency validity

Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.

Market Share Model of Price and Advertising Combined Game in Duopoly

The marketing share model of price and advertising in a duopoly market was studied in this paper. Market response curves of price and advertising were presented to calculate the reasonable range based on the market forecast results. The interaction effect of price and advertising was considered,and the game theory was applied to a two-stage price and advertising competition which involved the market share model. A marketing decision support system (MDSS) was developed and simulation data was provided to give the solutions. The operation results show that the leading enterprise makes higher price,spends more on advertising,and earns more profit,while the small-scale enterprise has to lower the price,spend less on advertising,and has slightly higher profit rate. The system is shown to be adaptable to a wide variety of realistic situations.

Multi-criteria decision-making selection model with application to chemical engineering management decisions

Chemical industry project management involves complex decision making situations that require discerning abilities and methods to make sound decisions. Chemical engineers as project managers are faced with decision environments and problems in chemical industry projects that are complex. Multiple-criteria decision making （MCDM） approaches are major parts of decision theory and analysis. This paper presents all of MCDM approaches for use in chemical engineering management decisions. In this work, case study is Research and Development （R＆D） project selection in chemical industry. The ability to make sound decisions is very important to success of R＆D projects. It is hoped that this work will provide a ready reference on MCDM and this will encourage the application of the MCDM in chemical engineering management.

Arrival Pattern Recognition and Prediction Based on Machine Learning

A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction,two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft,just like real ATCOs do. Therefore,the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally,a case study is carried out and demonstrates that the convolutional neural network(CNN)-based predictor performs better than the radom forest(RF)-based one.

Investment control in whole process of engineering construction project

in recent years, as the project of our country is increasing, investment growth, put forward new challenges to investment in construction projects. Research from the research status of investment in construction, the implementation process in accordance with the construction project, followed by analysis of the construction project investment the currently existing problems, and puts forward the implementation of the project the whole process as the main line, to scientific decision-making, rational design, bidding, construction control standard and completion of review strategies as the core.

Decision support for integrated river basin management—Scientific research challenges

Integrated River Basin Management(IRBM)has been a long discussed way to sustainably manage water and land resources;yet,very few examples of effective IRBM are found because there is a lack of sufficient scientific support,as well as institutional accommodation,to successfully implement it.This paper overviews the major challenges with IRBM,the promising scientific approaches for the implementation of IRBM,and the areas of needed research,with considerable issues and experiences from China.It is expected that novel research will draw together disparate disciplines into an integrated scientific framework,upon which better modeling tools,stakeholder involvement,and decision-making support can be built.Cutting-edge new technologies will bring ideas of IRBM forward to theory and finally to practice.The paper will prompt scientists to undertake research to fill in the gaps in the current IRBM knowledge base and provide practitioners guidance on how to incorporate scientifically based information within the IRBM decision process.

Using the movement patterns of reintroduced animals to improve reintroduction success

Despite their importance to conservation, reintroductions are still a risky endeavor and tend to fail, highlighting the need for more efficient post-release monitoring techniques. Reintroduced animals are released into unfamiliar novel environ ments and must explore their surroundings to gain knowledge in order to survive. According to theory, knowledge gain should be followed by subsequent changes to the animal＇s movement behavior, making movement behavior an excellent indicator of reintroduction progress. We aim to conceptually describe a logical process that will enable the inclusion of behavior （in particular, movement behavior） in management decision-making post-reintroductions, and to do so, we provide four basic components that a manager should look for in the behaviors of released animals. The suggested components are release-site fidelity, recurring locations, proximity to other individuals, and individual variation in movement behavior. These components are by no means the only possible ones available to a manager, but they provide an efficient tool to understanding animals＇ decision-making based on ecological theory; namely, the exploration-exploitation trade-off that released animals go through, and which underlies their behavior. We demonstrate our conceptual approach using data from two ungulate species reintroduced in Israel： the Persian fallow deer Dama mesopotamica and the Arabian oryx Oryx leucoryx [Current Zoology 60 （4）： 515-526, 2014] .