理性看待中国的“世界工厂”地位

中国制造业的高速发展和迅速崛起,为中国赢得了"世界工厂"的称号,而近年来频频爆发的"质量门"事件和全球贸易摩擦却使中国制造业危机重重。中国制造业"大而不强",在效率、效益、技术、品牌、成本等方面面临严重的发展瓶颈,离真正的"世界工厂"还相距甚远。为实现从制造大国向制造强国的转变,必须以国际金融危机的倒逼压力为契机,加速中国制造业的结构调整和转型升级,变"中国制造"为"中国创造"。     

竞合关系、组织惯例更新与突破式创新——环境不确定性的调节作用

突破式创新是创新驱动发展的重要形式，而以竞合关系促进协同创新已成为企业常态。基于动态能力理论与资源基础理论，探讨竞合关系、组织惯例更新和环境不确定性对突破式创新的交互作用机制。通过对298家企业问卷调研数据的分析，结果表明：竞争与合作均对突破式创新产生积极影响，竞合平衡对突破式创新产生消极影响；组织惯例更新分别在合作、竞合平衡与突破式创新关系中起中介作用；技术不确定性分别调节竞争、合作与突破式创新关系，市场不确定性分别调节合作、竞合平衡与突破式创新关系。该结论丰富了企业竞合与突破式创新关系研究，为企业管理利用竞合关系促进突破式创新提供了理论参考。     

An Algorithm for Balancing Commodity-flow Systems

In many cases there is a need to balance commodity-flow system data quickly and with limited resources. In order to compile new supply and use tables and investment matrices consistent with revised national accounts data, it can be necessary to apply some sort of automatic balancing technique. The paper proposes an algorithm that, contrary to RAS, can balance a commodity-flow system with unequal net row and column sums. The algorithm is applied to a recent revision of Danish capital stock estimates.     

Updating Input–Output Tables with Benchmark Table Series

Numerous methods have been proposed to update input–output (I–O) tables. They rely on the assumption that the economic structure will not change significantly during the interpolation period. However, this assumption may not always hold, particularly for countries experiencing rapid development. This study attempts to combine forecasting with a matrix transformation technique (MTT) to provide a new perspective on updating I–O tables. Under the assumption that changes in the trend of an economic structure are statistically significant, the method extrapolates I–O tables by combining time series models with an MTT and proceeds with only the total value added during the target years. A simulation study and empirical analysis are conducted to compare the forecasting performance of the MTT to the Generalized RAS (GRAS) and Kuroda methods. The results show that the comprehensive performance of the MTT is better than the performance of the GRAS and Kuroda methods, as measured by the Standardized Total Percentage Error, Theil's U and Mean Absolute Percentage Error indices.     

组织惯例更新触发因素与影响效应——基于先动型市场导向和可持续竞争优势视角

组织惯例更新是企业进行组织优化和迭代以适应外部动态环境的重要途径,基于组织学习理论和动态能力理论,构建先动型市场导向—组织学习—组织惯例更新—动态能力—可持续竞争优势研究框架,探讨组织惯例更新触发因素与影响效应。通过对191家科技型企业进行问卷调研发现：①先动型市场导向显著正向影响组织惯例更新,组织学习在先动型市场导向与组织惯例更新之间起部分中介作用;②组织惯例更新显著正向影响企业可持续竞争优势,动态能力在组织惯例更新与可持续竞争优势之间发挥完全中介作用。研究结论有助于厘清组织惯例更新触发因素、丰富组织惯例更新结果研究,并对企业建立可持续竞争优势具有一定指导意义。     

Reviewing and improving performance measurement systems: An action research

Reviewing and updating performance measurement systems (PMS) based on internal and external environmental changes are as important as developing and implementing them. The results of an action research study carried out to improve the PMS of an energy company's maritime transportation area are presented. The findings of this longitudinal study illustrate the difficulty and complexity of reviewing and updating an energy company's PMS for its maritime transportation area. This difficulty is due to the involvement of PMS users, the assessment of performance measures, the establishment of targets, and data availability. The complexity is related to the changes in information technology when implementing changes in procedures for computing performance measures. This article contributes to a better understanding of the process of reviewing and updating a company's existing PMS.     

Update rules for convex risk measures

In the first part of the paper we investigate the properties that describe the intertemporal structure of dynamic convex risk measures. The usual backward approach to dynamic risk assessment leads to strong and weak versions of time consistency. As an alternative, we introduce a forward approach of consecutivity. In the second part we discuss the problem of how to update a convex risk measure when new information arrives. We analyse to what extent the above properties are appropriate update criteria.     

Out-of-sample tests of forecasting accuracy: an analysis and review

In evaluations of forecasting accuracy, including forecasting competitions, researchers have paid attention to the selection of time series and to the appropriateness of forecast-error measures. However, they have not formally analyzed choices in the implementation of out-of-sample tests, making it difficult to replicate and compare forecasting accuracy studies. In this paper, I (1) explain the structure of out-of-sample tests, (2) provide guidelines for implementing these tests, and (3) evaluate the adequacy of out-of-sample tests in forecasting software. The issues examined include series-splitting rules, fixed versus rolling origins, updating versus recalibration of model coefficients, fixed versus rolling windows, single versus multiple test periods, diversification through multiple time series, and design characteristics of forecasting competitions. For individual time series, the efficiency and reliability of out-of-sample tests can be improved by employing rolling-origin evaluations, recalibrating coefficients, and using multiple test periods. The results of forecasting competitions would be more generalizable if based upon precisely described groups of time series, in which the series are homogeneous within group and heterogeneous between groups. Few forecasting software programs adequately implement out-of-sample evaluations, especially general statistical packages and spreadsheet add-ins.     

Sampling and Estimation Issues for Annual and Sub-annual Canadian Business Surveys

A typical Business Register (BR) is mainly based on administrative data files provided by organisations that produce them as a by-product of their function. Such files do not necessarily yield a perfect Business Register. A good BR should have the following characteristics: (1) It should reflect the complex structures of businesses with multiple activities, in multiple locations or with multiple legal entities; (2) It should be free of duplication, extraneous or missing units; (3) It should be properly classified in terms of key stratification variables, including size, geography and industry; (4) It should be easily updateable to represent the newer business picture, and not lag too much behind it. In reality, not all these desirable features are fully satisfied, resulting in a universe that has missing units, inaccurate structures, as well as improper contact information, to name a few defects.
These defects can be compensated by using sampling and estimation procedures. For example, coverage can be improved using multiple frame techniques, and the sample size can be increased to account for misclassification of units and deaths on the register. At the time of estimation, auxiliary information can be used in a variety of ways. It can be used to impute missing variables, to treat outliers, or to create synthetic variables obtained via modelling. Furthermore, time lags between the birth of units and the time that they are included on the register can be accounted for appropriately inflating the design-based estimates.     

Input Coefficient Change Using Biproportional Econometric Adjustment Functions

This paper deals with the issue of updating input-output (I-O) coefficients within a large-scale disaggregated econometric macro-model of the Austrian economy. Capturing the changes in input coefficients over time is an important issue in I-O modelling due to a lack of recent benchmark I-O tables in most countries. Different approaches for updating these coefficients can be found in the literature, such as adjusting input coefficients 'along the row' and variable input coefficients 'along the column' stemming from factor input equations derived from production or cost functions. This paper combines these two approaches, yielding a biproportional method. For the adjustment, 'along the column' econometric factor input functions are used to derive a sum of non-energy intermediate inputs. For the adjustment 'along the row' the starting point is a set of adjustment functions described in the literature: special emphasis is placed on econometric specification and 'cointegration accounting'.