A Three-State Markov Model of Choice Behavior within Spatial Structures

This paper derives a simple mathematical model of spatial learning and choice by integrating several psychological theories, whose features accord with the results of empirical investigation in a previous paper [2]. A sample of homogeneous decision-makers are assumed to make a succession of selections from a given set of initially unknown spatial alternatives (for example, a set of shopping places for a good). The decision-makers pass through two states of “recognition” and “discrimination” learning, before reaching an equilibrium state. In the equilibrium state, decision-makers have sufficiently learned the attributes of the alternatives so that satisfactory choices are always made. These assumptions permit the derivation of mathematical expressions to answer two questions: first, what proportion of decision-makers will be in the equilibrium state after any given time interval, and second, what proportion of decision-makers will choose any designated spatial alternative after the same time interval. In the second case, the proportion of decision-makers choosing an alternative is predicted from the individuals' perceptions of the attributes of the alternatives. The paper concludes with an evaluation of the model and suggestions for its testing and further development.     

Truncated Decision Making and Deliberative Implementation: A Time-Based Policy Process Model for Transitional China

The time dimension has not attracted enough attention in policy process research in China, yet speed is the most distinctive feature of China’s recent development. This article, based on observations of China’s policy practices, proposes a new research perspective for understanding how the Chinese government has been able to address policy challenges in an era of rapid transition. The approach adopted by the government allows decision makers to respond quickly to serious problems with a truncated decision-making process, and then implement the decisions through a more gradual deliberative process. The article examines China’s coal-mining industry reform as an empirical case to illustrate how this governance approach has been used to achieve major policy reform, namely property rights reform for coal mines, while simultaneously maintaining stability, regulating production safety, and stimulating industrial development. The article concludes with a discussion of the broad implications of this pattern for improving the effectiveness of public policy both in and outside China.     

A Note on the Mixed Geographically Weighted Regression Model*

Abstract. A mixed, geographically weighted regression (GWR) model is useful in the situation where certain explanatory variables influencing the response are global while others are local. Undoubtedly, how to identify these two types of the explanatory variables is essential for building such a model. Nevertheless, It seems that there has not been a formal way to achieve this task. Based on some work on the GWR technique and the distribution theory of quadratic forms in normal variables, a statistical test approach is suggested here to identify a mixed GWR model. Then, this note mainly focuses on simulation studies to examine the performance of the test and to provide some guidelines for performing the test in practice. The simulation studies demonstrate that the test works quite well and provides a feasible way to choose an appropriate mixed GWR model for a given data set.     

Empirical Evaluation of Alternative Model Specifications to Predict Commuting Flows

This study is devoted to empirical and modeling aspects on how characteristics of spatial structure influence commuting flows. Within a doubly-constrained framework, results from a competing-destinations formulation are evaluated and compared to results from the traditional gravity model. The evaluation depends critically upon the specification of within-zone journeys-to-work. Specific labor-market characteristics are found to be significant to explain how workers are absorbed in diagonal elements of the trip-distribution matrix. We also find that the parametric specification of the accessibility measure is important, and that the competing-destinations formulation is superior to the traditional gravity model.     

旅行社共创O2O模式的互补性资源投入决策研究

旅游运营商与在线旅行社通过合作发挥资源互补优势实现双方的O2O模式,但互补性资源的投入会产生机会主义风险,协调成本会使资源遭受效率损失.本文综合考虑资源投入的收益与效率损失构建了合作收益模型,运用Stackelberg博弈分析了双方互补性资源的最优投入策略,并通过算例和案例对模型主要部分结论进行了验证.结果表明:合作主导者收益达到其阀值时,双方才能达成合作;资源之间存在不完全互补关系,资源与合作努力之间存在替代关系;双方可调整资源与合作努力投入比例,控制资源效率损失;双方互补性资源投入和合作努力投入比例与其在共创O2O模式中的成本收益比相一致.     

A Flexible Mathematical Programming Model to Estimate Interregional Input–Output Accounts*

Abstract. This study implements and tests a mathematical programming model to estimate interregional, interindustry transaction flows in a national system of economic regions based on an interregional accounting framework and initial information of interregional shipments. A national input–output (IO) table, regional data on gross output, value‐added, exports, imports, and final demand at sector level are used as inputs to generate an interregional IO account that reconciles regional economic statistics and interregional transaction data. The model is tested using data from a multiregional global IO database and shows remarkable capacity to discover true interregional trade patterns from highly distorted initial estimates.     

Neural Network Modeling of Constrained Spatial Interaction Flows: Design, Estimation, and Performance Issues

In this paper a novel modular product unit neural network architecture is presented to model singly constrained spatial interaction flows. The efficacy of the model approach is demonstrated for the origin constrained case of spatial interaction using Austrian interregional telecommunication traffic data. The model requires a global search procedure for parameter estimation, such as the Alopex procedure. A benchmark comparison against the standard origin constrained gravity model and the two–stage neural network approach, suggested by Openshaw (1998), illustrates the superiority of the proposed model in terms of the generalization performance measured by ARV and SRMSE.