Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

The effect of external supply knowledge acquisition,development activities and organizational status on the supply performance of SMEs

Given the increasingly strategic role of external resources, acquiring knowledge about current suppliers and the broader supply market is an important and demanding task for the purchasing and supply management (PSM) function of a firm. Performance-improvement-oriented application of external supply knowledge present further challenges for the function. To examine this, we draw on the knowledge-based view and develop a hypothesized model in which supply knowledge acquisition drives PSM exploration and exploitation orientations which in turn mediate the organizational status of PSM function in terms of supply performance. We test the model on an SME-focused and survey-based dataset, using structural equation modelling. Our results indicate that an exploitative orientation is associated with knowledge gained from the supply base, whereas an explorative orientation is predominantly associated with supply market knowledge and less with supply base knowledge, suggesting natural pairings. The findings also show how an exploitative development orientation mediates the positive association of the PSM function's organizational status with supply performance. Driven by supply base knowledge, a status-empowered exploitative PSM orientation may suppress supply market based explorative orientation in resource-scarce SMEs, thus appearing to serve as the sole path to supply performance. Our research contributes by pointing out the significance of the knowledge-resource, and the knowledge-based view, in understanding performance in PSM.     

辐射迁移方程--一个K-辛空间上的正则方程

说明了均匀、轴对称、无源介质是一个K-辛空间上的Hamilton系统，Hamilton函数是系统的守恒量；数值计算辐射强度角分布的合理途径是将辐射迁移方程离散成以离散Hamilton函数为守恒量的有限维K-辛空间上的正则方程，并采用保离散Hamilton函数守恒的K-辛算法数值求解．     

对计算企业经营活动现金流量的一点思考——从基本会计等式出发

本文旨在通过对基本会计等式的运用,揭示用间接法将净收益调节为经营活动现金流量的内在逻辑性。先对基本会计等式进行逐步的分析,推导出现金流量的计算步骤。在这一过程中,可以清楚的反映出会计报表之间的明晰性。     

A new bivariate distribution in natural exponential family

We propose a new bivariate distribution following a GLM form i.e., natural exponential family given the constantly correlated covariance matrix. The proposed distribution can represent an independent bivariate gamma distribution as a special case. In order to derive the distribution we utilize an integrating factor method to satisfy the integrability condition of the quasi-score function. The derived distribution becomes a mixture of discrete and absolute continuous distributions. The proposal of our new bivariate distribution will make it possible to develop some bivariate generalized linear models. Further the discrete correlated bivariate distribution will also arise from an independent bivariate Poisson mass function by compounding our proposed distribution (Iwasaki and Tsubaki, 2002).Received March 2003     

Blocked-Error-R 2: A Conceptually Improved Definition of the Proportion of Explained Variance in Models Containing Loops or Correlated Residuals

Bentler and Raykov (2000, Journal of Applied Psychology 85: 125–131), and Jöreskog (1999a, http://www.ssicentral.com/lisrel/column3.htm, 1999b http://www.ssicentral. com/lisrel/column5.htm) proposed procedures for calculating R ² for dependent variables involved in loops or possessing correlated errors. This article demonstrates that Bentler and Raykov’s procedure can not be routinely interpreted as a “proportion” of explained variance, while Jöreskog’s reduced-form calculation is unnecessarily restrictive. The new blocked-error-R ² (beR ²) uses a minimal hypothetical causal intervention to resolve the variance-partitioning ambiguities created by loops and correlated errors. Hayduk (1996) discussed how stabilising feedback models – models capable of counteracting external perturbations – can result in an acceptable error variance which exceeds the variance of the dependent variable to which that error is attached. For variables included within loops, whether stabilising or not, beR ² provides the same value as Hayduk’s (1996) loop-adjusted-R ². For variables not involved in loops and not displaying correlated residuals, beR ² reports the same value as the traditional regression R ². Thus, beR ² provides a conceptualisation of the proportion of explained variance that spans both recursive and nonrecursive structural equation models. A procedure for calculating beR ² in any SEM program is provided.     

A graduates ’ satisfaction index for the evaluation of the university overall quality

In the higher educational setting, students provide a relevant contribution to the quality of educational services. In such a context, the measurement of the perceived quality and related satisfaction for the university experience are of primary interest to evaluate the efficiency and efficacy of the learning processes. In this contribution, we aim at assessing the overall quality of the graduates’ university experience in terms of internal and external efficacy by applying the ECSI (European Customer Satisfaction Index) methodology, based on structural equation models and primarily developed in the context of customer satisfaction. For this aim, we propose a modified ECSI model tailored for the higher educational setting, explicitly taking into account the differences among groups of degree program. The study is carried out on data collected by the AlmaLaurea surveys at the University of Florence (Italy) in the period 2014–2017 and concerns a sample of more than 2,000 graduates. We find out eight latent variables that contribute to define the overall quality of university experience. These variables are differently affected by the type of degree program, with the highest levels of external efficacy observed for degree programs belonging to the educational, health, and engineering groups. It also turns out that interventions on the internal efficacy (i.e., quality of hardware and quality of humanware) have a direct positive effect on the university (i.e., loyalty) and an indirect positive effect on the society (i.e., external efficacy).