公共设施分布公平性问题初探

不管规划范围内居民的社会经济状况、意愿、人口分布是否相同,都应该得到公共设施服务。公共设施由于其自身的独特性质、普遍的“市场失灵”、政府行政的干预和社会群体的分层等原因,存在配置的公平性问题。从公共设施配置中的投资建设方面来说,需重视对市场运作的积极引导、改善政府介入的方式,促进公众参与机制的形成。     

When and how authoritarian leadership and leader renqing orientation influence tacit knowledge sharing intentions

In this study of tacit knowledge-sharing intentions in China, we examine the roles of authoritarian leadership and fairness with respect to the way managers make decisions and treat their subordinates. In particular, we examine the role of leader renqing orientation, i.e., the way leaders distribute favors and emotional concern to their subordinates, as a moderating factor. We draw on the research literature in the domains of knowledge management and cross-cultural Psychology to identify constructs that we then test with a survey of 309 Chinese employees. Our findings are counter-intuitive and are discussed in detail before we conclude with implications for research and practice.     

The impacts of speed cameras on road accidents: An application of propensity score matching methods

This paper aims to evaluate the impacts of speed limit enforcement cameras on reducing road accidents in the UK by accounting for both confounding factors and the selection of proper reference groups. The propensity score matching (PSM) method is employed to do this. A naïve before and after approach and the empirical Bayes (EB) method are compared with the PSM method. A total of 771 sites and 4787 sites for the treatment and the potential reference groups respectively are observed for a period of 9 years in England. Both the PSM and the EB methods show similar results that there are significant reductions in the number of accidents of all severities at speed camera sites. It is suggested that the propensity score can be used as the criteria for selecting the reference group in before-after control studies. Speed cameras were found to be most effective in reducing accidents up to 200 meters from camera sites and no evidence of accident migration was found.     

＂哲匠＂与＂塞米丝＂的结合——浅谈城市规划职业制度困境以及对律师制度借鉴的可能性

城市规划学科职业实践中的困境越来越受到社会的关注,而社会对其的看法也莫衷一是。而这个困境需要在什么方面寻求突破？本文立足于城市规划职业实践的困境以及职业制度的不足：工作内容缺失、权威性缺失、公平性、正义职责履行不足以及公众参与落实难,对比分析了城市规划职业制度与律师职业制度以及国外相关探索,建议规划职业制度的完善可以借...     

Toward an understanding of the impact of production pressure on safety performance in construction operations

It is not unusual to observe that actual schedule and quality performances are different from planned performances (e.g., schedule delay and rework) during a construction project. Such differences often result in production pressure (e.g., being pressed to work faster). Previous studies demonstrated that such production pressure negatively affects safety performance. However, the process by which production pressure influences safety performance, and to what extent, has not been fully investigated. As a result, the impact of production pressure has not been incorporated much into safety management in practice. In an effort to address this issue, this paper examines how production pressure relates to safety performance over time by identifying their feedback processes. A conceptual causal loop diagram is created to identify the relationship between schedule and quality performances (e.g., schedule delays and rework) and the components related to a safety program (e.g., workers’ perceptions of safety, safety training, safety supervision, and crew size). A case study is then experimentally undertaken to investigate this relationship with accident occurrence with the use of data collected from a construction site; the case study is used to build a System Dynamics (SD) model. The SD model, then, is validated through inequality statistics analysis. Sensitivity analysis and statistical screening techniques further permit an evaluation of the impact of the managerial components on accident occurrence. The results of the case study indicate that schedule delays and rework are the critical factors affecting accident occurrence for the monitored project.     

An empirical study of transaction throughput thrashing across multiple relational DBMSes

Modern DBMSes are designed to support many transactions running simultaneously. DBMS thrashing is indicated by the existence of a sharp drop in transaction throughput. Thrashing behavior in DBMSes is a serious concern to database administrators (DBAs) as well as to DBMS implementers. From an engineering perspective, therefore, it is of critical importance to understand the causal factors of DBMS thrashing. However, understanding the origin of thrashing in modern DBMSes is challenging, due to many factors that may interact with each other.This article aims to better understand the thrashing phenomenon across multiple DBMSes. We identify some of the underlying causes of DBMS thrashing. We then propose a novel structural causal model to explicate the relationships between various factors contributing to DBMS thrashing. Our model derives a number of specific hypotheses to be subsequently tested across DBMSes, providing empirical support for this model as well as important engineering implications for improvements in transaction processing.     

Solving House Allocation Problems with Risk-Averse Agents

This paper solves the fair and optimal house allocation problem (Sun and Yang, Econ Lett 81:73–79, 2003) when the agents preferences are represented by nonlinear utility functions using techniques for global mixed integer nonlinear optimization. A small simulation study indicates that if quasi-linear specifications are adopted as approximations to nonlinear utility functions and if the fair and optimal allocation is identified based on this approximation, then the prices are typically higher on average and the resulting allocation is typically non-fair.     

An Artificial Network Simulating Cause-to-Effect Reasoning: Cancellation Interactions and Numerical Studies

During the last few decades, a variety of models have been proposed to address causal reasoning (known also as abduction); most of these dealt with a probabilistic or a logical framework. Recently, a few models have been proposed within a neural framework. The investigation of neural approaches is mainly motivated by the computational burden of the causal reasoning task and by the satisfactory results given by neural networks in solving hard problems in general. A particular class of causal reasoning that raises several difficulties is the cancellation class. From an abstract point of view, cancellation occurs when two causes (hypotheses) cancel each other's explanation capabilities with respect to a given effect (observation). The present work is twofold. First, we extend an existing neural model to handle cancellation interactions. Second, we test the model on a large database and propose objective criteria to quantitatively evaluate the scenarios (explanations) produced. Simulation results show good performance and stability of the model. Received 17 November 1999 / Revised 12 May 2000 / Accepted in revised form 16 June 2000     

Data-driven causal inference based on a modified transfer entropy

Causality inference and root cause analysis are important for fault diagnosis in the chemical industry. Due to the increasing scale and complexity of chemical processes, data-driven methods become indispensable in causality inference. This paper proposes an approach based on the concept of transfer entropy which was presented by Schreiber in 2000 to generate a causal map. To get a better performance in estimating the time delay of causal relations, a modified form of the transfer entropy is presented in this paper. Case studies on two simulated chemical processes, including the benchmark Tennessee Eastman process are performed to illustrate the effectiveness of this approach.