Management of Energy Technology for Sustainability: How to Fund Energy Technology Research and Development

Operations management methods have been applied profitably to a wide range of technology portfolio management problems, but have been slow to be adopted by governments and policy makers. We develop a framework that allows us to apply such techniques to a large and important public policy problem: energy technology R&D portfolio management under climate change. We apply a multi‐model approach, implementing probabilistic data derived from expert elicitations into a novel stochastic programming version of a dynamic integrated assessment model. We note that while the unifying framework we present can be applied to a range of models and data sets, the specific results depend on the data and assumptions used and therefore may not be generalizable. Nevertheless, the results are suggestive, and we find that the optimal technology portfolio for the set of projects considered is fairly robust to different specifications of climate uncertainty, to different policy environments, and to assumptions about the opportunity cost of investing. We also conclude that policy makers would do better to over‐invest in R&D rather than under‐invest. Finally, we show that R&D can play different roles in different types of policy environments, sometimes leading primarily to cost reduction, other times leading to better environmental outcomes.     

Supplier Selection for Framework Agreements in Humanitarian Relief

In this study, we consider the supplier selection problem of a relief organization that wants to establish framework agreements (FAs) with a number of suppliers to ensure quick and cost‐effective procurement of relief supplies in responding to sudden‐onset disasters. Motivated by the FAs in relief practice, we focus on a quantity flexibility contract in which the relief organization commits to purchase a minimum total quantity from each framework supplier over a fixed agreement horizon, and, in return, the suppliers reserve capacity for the organization and promise to deliver items according to pre‐specified agreement terms. Due to the uncertainties in demand locations and amounts, it may be challenging for relief organizations to assess candidate suppliers and the offered agreement terms. We use a scenario‐based approach to represent demand uncertainty and develop a stochastic programming model that selects framework suppliers to minimize expected procurement and agreement costs while meeting service requirements. We perform numerical experiments to understand the implications of agreement terms in different settings. The results show that supplier selection decisions and costs are generally more sensitive to the changes in agreement terms in settings with high‐impact disasters. Finally, we illustrate the applicability of our model on a case study.     

An evaluation of the performance of kernel estimators for graduating mortality data

In the graduation of the age-specific mortality pattern, recent emphasis has been placed on the use of kernel regression estimators. Three such estimators are the Nadaraya-Watson, Gasser-Muller and kernel weighted local linear estimators. This paper discusses the theoretical background of each estimator and evaluates their accuracy in graduating age-specific mortality using data for France, Japan and Sweden. For comparison, we also fit the Heligman-Pollard model and its nine-parameter variant by Kostaki. The Gasser-Muller estimator is found to be superior to the two other kernel estimators in that it is both more stable and not influenced by boundary effects. Furthermore, compared with the two parametrric models, the Gasser-Muller estimator provides a more satisfactory graduation, especially at older adult ages, in terms both of smoothness and of fidelity between the observed and graduated rates.     

Technological change and sociocultural models in China: A case study of train commuters in Beijing

ABSTRACT

China’s mobility turn has created the world’s largest public rail system, contributing extensively to citizens’ economic, social, and spatial mobility. Concurrently, this technological transformation has introduced many opportunities for individuation, which could potentially challenge the social, collectivistic, and Confucian foundations of China’s sociocultural and political ideology. While the notion that ‘mobility produces culture’ is readily accepted, research on train mobility in China is rare. In this study, we use Albert Bandura’s Model of Triadic Reciprocal Causation to conceptualize mobility as agency. We employ Hermeneutic Content Analysis, a mixed methods framework, to study how this rapidly evolving mobility environment connects to the lives of 31 regular train users living in Beijing. Studying agency in China enables us to systematize the sociocultural models within which mobility practices are embedded and how they manifest. We find that our interviewees embed agentive practices in a cultural model that is intertwined with collectivistic aspirations of the country. Technological developments are thus integrated into existing sociocultural models and political expectations, contradicting existing debates on the fracturing impact of disruptive technologies.     

Dynamics of age- and size-structured populations in fluctuating environments: Applications of stochastic matrix models to natural populations

Recent developments of the theory of stochastic matrix modeling have made it possible to estimate general properties of age- and size-structured populations in fluctuating environments. However, applications of the theory to natural populations are still few. The empirical studies which have used stochastic matrix models are reviewed here to examine whether predictions made by the theory can be generally found in wild populations. The organisms studied include terrestrial grasses and herbs, a seaweed, a fish, a reptile, a deer and some marine invertebrates. In all the studies, the stochastic population growth rate (ln λ _s ) was no greater than the deterministic population growth rate determined using average vital rates, suggesting that the model based only on average vital rates may overestimate growth rates of populations in fluctuating environments. Factors affecting ln λ _s include the magnitude of variation in vital rates, probability distribution of random environments, fluctuation in different types of vital rates, covariances between vital rates, and autocorrelation between successive environments. However, comprehensive rules were hardly found through the comparisons of the empirical studies. Based on shortcomings of previous studies, I address some important subjects which should be examined in future studies.     

Dynamic Mechanism Design: A Myersonian Approach

We study mechanism design in dynamic quasilinear environments where private information arrives over time and decisions are made over multiple periods. We make three contributions. First, we provide a necessary condition for incentive compatibility that takes the form of an envelope formula for the derivative of an agent's equilibrium expected payoff with respect to his current type. It combines the familiar marginal effect of types on payoffs with novel marginal effects of the current type on future ones that are captured by “impulse response functions.” The formula yields an expression for dynamic virtual surplus that is instrumental to the design of optimal mechanisms and to the study of distortions under such mechanisms. Second, we characterize the transfers that satisfy the envelope formula and establish a sense in which they are pinned down by the allocation rule (“revenue equivalence”). Third, we characterize perfect Bayesian equilibrium‐implementable allocation rules in Markov environments, which yields tractable sufficient conditions that facilitate novel applications. We illustrate the results by applying them to the design of optimal mechanisms for the sale of experience goods (“bandit auctions”).     

办学要素的生态型混合：高职院校混合所有制改革的系统化建构

混合所有制改革是激发高职院校办学活力的重要方略。高职院校混合所有制改革过程中面临着办学要素离散的困境,主要体现为目标理念不明晰、改革策略措施单一化、支持环境不健全等。破解之道是形成办学要素的生态型混合,促进混合所有制生成的内部要素与外部支持条件的系统化重建,推进高职院校混合所有制的科学建构与可持续发展。     

论刘少奇新民主主义经济建设思想的理论价值和现实意义

在建国前后的几年中,刘少奇对新民主主义经济建设进行了深入的探索,提出了许多具有一定独创性的见解,为马克思主义的政治经济学、为毛泽东思想的理论均增添了许多新的内容。刘少奇关于新民主主义经济建设的理论和实践,在很大程度上推动了建国前后中国经济的恢复与发展,为邓小平创立中国特色的社会主义理论奠定了一定的思想理论基础,并且对当前的现代化建设也有许多可以借鉴之处,因此,进一步研究刘少奇的新民主主义经济建设思想具有重要的理论价值和现实意义。     

刘文淇《左传》研究思想探析

仪征刘氏家族是清代扬州学派的重要代表,其学术研究以《左传》名家。从刘文淇开始,历经三代,共同编著《春秋左传旧注疏证》。该书蕴含着作者非常丰富的《左传》研究思想,集中体现其研究特点,是清儒《左传》注疏研究的整理和总结之作。在分析该书内容的基础上,概括其《左传》研究思想为三个方面,即“释《春秋》必以《周礼》明之”,《公羊》、《毂梁》之义理不能尽信,《左传》之褒贬存于贾逵旧注。     

双重信息不对称下销售渠道双目标混合激励模型

销售渠道在企业与消费者之间扮演着重要的桥梁作用,销售人员的销售能力和销售努力等信息均为其私有而不为企业所共知时,企业如何甄别其真实能力信息并对其销售努力实施有效激励是个重要问题.针对上述问题,给出了基于线性合约的双目标混合激励模型,通过模型求解得到并刻画了最优合约的3个特征.首先,为辨别高能力类型与普通能力类型这两种不...