Community-Based Tradable Permits for Localized Pollution

This paper considers the assignment of tradable permits—representing property rights of an environmental good—to community members who are harmed by pollution generated by firms. These community members can in turn sell permits to polluters according to their personal preferences. For a special case with a sole household, market transactions between the household and polluters achieve an efficient pollution level. However, for a group of households, the decentralized market solution fails to yield social efficiency because of competitive consumption of the environmental goods. We design a revenue-sharing mechanism akin to unitization, under which market transactions also achieve efficient resource allocation. Importantly, in some cases, efficiency can be achieved even when regulators are ignorant of the private valuation of the environmental good.     

BidPacket: trading bandwidth in public spaces

Smart devices such as smartphones and tablets are used extensively in public spaces for the transmission and reception of content in the form of text, photos and streaming videos. Since the bandwidth provided for wireless access is limited in public areas, it becomes an issue for users to gain access to the bandwidth they need at the right times. While an omniscient controller could assign bandwidth to each device on the basis of their needs and overall availability, imperfect information about the instantaneous state of the wifi access patterns and needs of users make for a very inefficient allocation of such bandwidth. This paper provides a solution for bandwidth allocation by creating a market among users of smart devices so that they can bid for extra bandwidth when they need it and sell it when they don’t. They do so by using a virtual currency that is conserved so that each device owner maximizes his own utility. This utility function is composed of both the benefit accrued from accessing bandwidth and the loss of the currency incurred in bidding for such bandwidth. Extensive simulations show that this market-based method outperforms an omniscient model when demand is uncertain, while minimizing bandwidth consumption.     

Short-term scheduling of crude oil operations in refinery with high-fusion-point oil and two transportation pipelines

In some refineries, storage tanks are located at two different sites, one for low-fusion-point crude oil and the other for high one. Two pipelines are used to transport different oil types. Due to the constraints resulting from the high-fusion-point oil transportation, it is challenging to schedule such a system. This work studies the scheduling problem from a control-theoretic perspective. It proposes to use a hybrid Petri net method to model the system. It then finds the schedulability conditions by analysing the dynamic behaviour of the net model. Next, it proposes an efficient scheduling method to minimize the cost of high-fusion-point oil transportation. Finally, it gives a complex industrial case study to show its application.     

Managing security risks for inter-organisational information systems: a multiagent collaborative model

Information sharing across organisations is critical to effectively managing the security risks of inter-organisational information systems. Nevertheless, few previous studies on information systems security have focused on inter-organisational information sharing, and none have studied the sharing of inferred beliefs versus factual observations. In this article, a multiagent collaborative model (MACM) is proposed as a practical solution to assess the risk level of each allied organisation’s information system and support proactive security treatment by sharing beliefs on event probabilities as well as factual observations. In MACM, for each allied organisation’s information system, we design four types of agents: inspection agent, analysis agent, control agent, and communication agent. By sharing soft findings (beliefs) in addition to hard findings (factual observations) among the organisations, each organisation’s analysis agent is capable of dynamically predicting its security risk level using a Bayesian network. A real-world implementation illustrates how our model can be used to manage security risks in distributed information systems and that sharing soft findings leads to lower expected loss from security risks.     

基于红外图像的林火识别方法及实现

森林火灾是一种突发性强、破坏性大且处置救助较为困难的自然灾害,会对森林、森林生态系统和人类带来一定危害和损失。早期的林火判别多基于温度、烟雾以及24小时图像监测实现,主观性强,标准单一,且误报率高。如何快速发现林火目标并及时报警扑灭,已经成为国内外学者研究的热点之一。文章基于红外热像仪,对大量森林背景及模拟林火状态进行了图像和温度数据的采集,首次提出了基于温度标准差方法进行热源识别的概念,得出了不同地点、不同时间段森林背景的温度标准差分布,以及明火温度在各阶段的波动范围,为林火的预防和监测提供了重要依据。同时,通过对干扰源进入前后的红外图像进行预处理和分析,对比目标热源的像素面积变化率及其圆形度,即可准确实现部分干扰热源的排除。实验结果证明,将此基于红外图像的热源初判原则与干扰源排除的规律应用于林火监测,方法简单有效,准确率高,对降低森林火灾的发生率,提高社会经济效益有着重要的作用。     

Two-stage DEA: <Emphasis Type="Italic">caveat emptor</Emphasis>

This paper examines the wide-spread practice where data envelopment analysis (DEA) efficiency estimates are regressed on some environmental variables in a second-stage analysis. In the literature, only two statistical models have been proposed in which second-stage regressions are well-defined and meaningful. In the model considered by Simar and Wilson (J Prod Anal 13:49–78, 2007), truncated regression provides consistent estimation in the second stage, where as in the model proposed by Banker and Natarajan (Oper Res 56: 48–58, 2008a), ordinary least squares (OLS) provides consistent estimation. This paper examines, compares, and contrasts the very different assumptions underlying these two models, and makes clear that second-stage OLS estimation is consistent only under very peculiar and unusual assumptions on the data-generating process that limit its applicability. In addition, we show that in either case, bootstrap methods provide the only feasible means for inference in the second stage. We also comment on ad hoc specifications of second-stage regression equations that ignore the part of the data-generating process that yields data used to obtain the initial DEA estimates.     

A proposal for a more objective measure of de facto constitutional constraints

In this paper we propose two new indicators of de facto constitutional constraints. The indicators are based on the presence or the absence of easily observable political events. This makes the proposed measures relatively objective and easy to verify relative to the most widely used indicators of de jure and de facto constitutions. This paper describes the indicators and demonstrates their usefulness for research on economic development.     

The joint effects of social identity and institutional pressures on audit quality: The case of the Chinese Audit Industry

This article examines how social identity links institutional pressures and audit quality. Combining institutional theory and social identity theory, we theoretically argue that the interaction between social and institutional forces shapes audit quality. Through an analysis of Chinese audit firms from 2000 to 2007, we show that isomorphic imitation has a more significant effect on firms belonging to the same-identity group than firms across cross-identity groups; foreign-affiliated audit firms are more willing to conform to normative pressure from professional networks than local firms; and foreign-affiliated firms are coerced to adapt to the local government’s expectation, particularly when they have a geographically concentrated customer base. We further reveal that a larger customer base attenuates within-identity group imitation but strengthens cross-identity group imitation. The results shed light on the role of social identity in shaping conformity in the audit industry, thus contributing to international convergence–divergence literature and institutional theory.     

Richard H. Thaler — Wirtschaftsnobelpreisträger 2017

Richard H. Thaler was awarded this year’s Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel “for his contributions to behavioural economics”. He studied systematic departures of human behaviour from the standard “homo oeconomicus” assumption. His famous work on boundedly rational behaviour considers both cognitive limitations and limited self-control. The cognitive limitations he studied are in particular the endowment effect, i.e. the observation that individuals assign a higher value to an object if they possess it, and mental accounting, a collection of theories regarding how individuals think about money. Furthermore, he provided path-breaking evidence on the nature of social preferences, which laid the groundwork for the development of several widely used economic theories incorporating altruism, fairness and reciprocity.