AN EMPIRICAL EXAMINATION OF RELATIONSHIP MAGNITUDE

Based upon a review of the extant literature, it is proposed that the structure of an interorganizational relationship is composed of relationship type and the under‐researched construct of relationship magnitude. Specifically, it is hypothesized that relationship magnitude, a second order construct composed of trust, commitment, and dependence, affects relationship type, which affects the perception of value of the relationship. The results of a survey analyzed through structural equation modeling support these hypotheses.     

THE EFFECT OF INVESTMENT IN INTERORGANIZATIONAL INFORMATION TECHNOLOGY IN A RETAIL SUPPLY CHAIN

The primary purpose of this research was to investigate the effect of investment in information technology in a supply chain. The results of that investigation are presented by focusing on an empirically tested supply chain relationship model containing both behavioral and operational constructs. The four behavioral constructs represented in the model are relationship trust, relationship commitment, relationship dependence, and long‐term relationship orientation. The four operational constructs represented in the model are retailer investment in interorganizational information technology, perceived supplier investment in interorganizational information technology, logistics efficiency, and logistics effectiveness. Among other findings, the results of the investigation found that perceived supplier investment in interorganizational information technology has a significant and positive effect on logistics efficiency.     

增加值率下降意味着什么

增加值率是从总体上度量一个经济体投入产出效益的综合指标。中国的增加值率一直在下降,表明中国经济增长的质量在下降。本文定义了中间投入贡献系数,给出其与增加值率的关系,通过分析中间投入贡献系数的变化本文得出,新增加中间投入品的贡献系数下降是造成总体中间投入贡献系数进而增加值率下降的原因。接着本文利用变参数经济计量模型,测算了改革开放以来国内中间投入和进口中间投入的贡献系数的数值和变化情况,并就提高增加值率的可能方面进行了探讨。     

Technological change in energy systems: Learning curves, logistic curves and input-output coefficients

Learning curves have recently been widely adopted in climate-economy models to incorporate endogenous change of energy technologies, replacing the conventional assumption of an autonomous energy efficiency improvement. However, there has been little consideration of the credibility of the learning curve. The current trend that many important energy and climate change policy analyses rely on the learning curve means that it is of great importance to critically examine the basis for learning curves. Here, we analyse the use of learning curves in energy technology, usually implemented as a simple power function. We find that the learning curve cannot separate the effects of price and technological change, cannot reflect continuous and qualitative change of both conventional and emerging energy technologies, cannot help to determine the time paths of technological investment, and misses the central role of R&D activity in driving technological change. We argue that a logistic curve of improving performance modified to include R&D activity as a driving variable can better describe the cost reductions in energy technologies. Furthermore, we demonstrate that the top-down Leontief technology can incorporate the bottom-up technologies that improve along either the learning curve or the logistic curve, through changing input-output coefficients. An application to UK wind power illustrates that the logistic curve fits the observed data better and implies greater potential for cost reduction than the learning curve does.     

Thermodynamics and process analysis for future economic scenarios

Economists are increasingly interested in forecasting future costs and benefits of policies for dealing with materials/energy fluxes, polluting emissions and environmental impacts on various scales, from sectoral to global. Computable general equilibrium (CGE) models are currently popular because they project demand and industrial structure into the future, along an equilibrium path. But they are applicable only to the extent that structural changes occur in or near equilibrium, independent of radical technological (or social) change. The alternative tool for analyzing economic implications of scenario assumptions is to use Leontief-type Input-Output (I-O) models. I-O models are unable to endogenize structural shifts (changing I-O coefficients). However, this can be a virtue when considering radical rather than incremental shifts. Postulated I-O tables can be used independently to check the internal consistency of scenarios. Or I-O models can be used to generate scenarios by linking them to econometric macro-drivers (which can, in principle, be CGE models). Explicit process analysis can be integrated, in principle, with I-O models. This hybrid scheme provides a natural means of satisfying physical constraints, especially the first and second laws of thermodynamics. This is important, to avoid constructing scenarios based on physically impossible processes. Process analysis is really the only available tool for constructing physically plausible alternative future I-O tables, and generating materials/energy and waste emissions coefficients. Explicit process analysis also helps avoid several problems characteristic of pure CGE or I-O models, viz. (1) aggregation errors (2) inability to handle arbitrary combinations of co-product and co-input relationships and (3) inability to reflect certain non-linearities such as internal feedback loops.     

Assessment of regional trade and virtual water flows in China

The success of China's economic development has left deep marks on resource availability and quality. Some regions in China are relatively poor with regards to water resources. This problem is exacerbated by economic growth. Flourishing trade activities on both domestic and international levels have resulted in significant amounts of water withdrawal and water pollution. Hence the goal of this paper is to evaluate the current inter-regional trade structure and its effects on water consumption and pollution via ‘virtual water flows’. Virtual water is the water embedded in products and used in the whole production chain, and that is traded between regions or exported to other countries. For this assessment of trade flows and effects on water resources, we have developed an extended regional input-output model for eight hydro-economic regions in China to account for virtual water flows between North and South China. The findings show that the current trade structure in China is not very favorable with regards to water resource allocation and efficiency. North China as a water scarce region virtually exports about 5% of its total available freshwater resources while accepting large amounts of wastewater for other regions' consumption. By contrast, South China a region with abundant water resources is virtually importing water from other regions while their imports are creating waste water polluting other regions' hydro-ecosystems.     

“互联网+创业”服务平台用户使用意愿影响机理研究——基于D & M模型和计划行为理论视角

针对互联网创业服务特点，基于计划行为理论信息系统成功模型构建新的理论模型，使用结构方程模型进行数据分析，以解释互联网创业服务平台用户持续使用意愿。通过模型分析发现，兼容性和线上线下互动通过知觉行为控制正向显著影响用户满意度和用户使用意愿，信息品质直接影响用户对互联网创业服务平台的使用意愿，而用户满意度在平台信息品质、系统品质、服务品质与使用意愿之间具有中介效应。基于此，提出完善互联网创业服务平台和提升用户使用意愿的对策建议。     

Analysis of interregional industry linkage and economic distance in China: evidence from the mining industry

The mining industry is an important sector of the national economy, which provides essential support for energy and other resources for economic development. Industrial linkage and economic distance are two different concepts in measuring the correlationship of different industries, in this article, we apply the model that combines both of them to analyse the industries significantly influence the mining industry. We find that electricity and heating industry, and the mining industry itself from forward linkages have greatly influenced the mining industry, and the industries from backward linkages affect mining industry are changing with industrial economic transformation. We also find resources can flow across several regions only after 2007, which means the role of geographical factors limiting long-range transportation of resources is weakening after 2007. And we explain how resources flow among various regions during 1997 ~ 2007. Based on the findings above, policy implications from the empirical results obtained are discussed.     

“一带一路”沿线国家与中国的贸易发展状况研究

研究目标：探索构建灯光数据对贸易研究的可行性。研究方法：运用1995~2012年“一带一路”沿线国家的面板数据，采用普通最小二乘法、泊松伪最大似然估计方法及工具变量法，以灯光数据作为GDP的替代量，通过传统引力模型搭建桥梁。研究发现：地理距离、边界及区域协定对中国与“一带一路”沿线国家之间贸易的显著影响表明灯光数据对贸易研究的有效性；同时，对1996~2012年贸易趋势的预测与实际贸易的对比结果显示，以灯光数据预测的“一带一路”贸易趋势与实际贸易基本吻合。研究创新：首次将夜间灯光数据应用于引力模型研究，对中国与“一带一路”沿线国家的贸易发展状况进行分析。研究价值：开拓夜间灯光数据研究贸易的先河，并结合引力模型的最新发展及微观基础思考拓展性的相关研究。     

An options pricing approach to ramping rate restrictions at hydro power plants

This paper investigates the impact of ramping rate restrictions imposed on hydro operations to protect aquatic ecosystems. The optimal ramping decision is specified as an optimal control problem which results in a Hamilton Jacobi Bellman (HJB) equation. Electricity prices are modelled as a regime switching stochastic process. The optimal control is determined by solving the HJB equation numerically using a fully implicit finite difference approach with semi-Lagrangian time stepping. The paper focuses on the effect of ramping restrictions on a hydro plant׳s value and optimal operations, and provides an analysis of which factors cause ramping restrictions to have a greater or lesser impact on profitability. It is shown that hydro plant value is negatively affected by ramping restrictions, but the extent of the impact depends on key parameters which determine the desirability of frequent changes in water release rates. Interestingly for the case considered, value is not sensitive to ramping restrictions over a large range of restrictions. The results point to the importance of accurately modelling electricity prices in gauging the trade offs involved in imposing restrictions on hydro operators which may hinder their ability to respond to volatile electricity prices and meet peak demands.