Stakeholder Performance Measurement in Nonprofit Organizations

According to recent findings, nonprofit organizations should address the relationships of nonprofit service quality, satisfaction, loyalty, and organizational identification when planning and evaluating donor surveys. This article presents a donor satisfaction barometer that can be used to gain insights into the strength of these key relationships and thereby establish a basis for calculated relevant indices. With such indices, nonprofit organizations can compare stakeholder performance over time and benchmark themselves against other organizations. Data from 2,599 blood donors to one section of the German Red Cross, collected through the proposed donor satisfaction barometer, show that service quality drives satisfaction, and donor satisfaction and organizational identification both exert significant positive effects on donor loyalty. Therefore, nonprofit organizations should use a combined strategic approach that improves both donor satisfaction and organizational identification to increase donor loyalty. The successful application of the donor satisfaction barometer also suggests its value for other nonprofit industries and offers important insights for managers.     

Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error

In this paper, we develop modified versions of the likelihood ratio test for multivariate heteroskedastic errors-in-variables regression models. The error terms are allowed to follow a multivariate distribution in the elliptical class of distributions, which has the normal distribution as a special case. We derive the Skovgaard-adjusted likelihood ratio statistics, which follow a chi-squared distribution with a high degree of accuracy. We conduct a simulation study and show that the proposed tests display superior finite sample behaviour as compared to the standard likelihood ratio test. We illustrate the usefulness of our results in applied settings using a data set from the WHO MONICA Project on cardiovascular disease.     

微信公众号影响力指数建构与量化评估

作为被广泛使用的社交媒体，微信已经成为热点事件和网络舆情的重要策源地，科学准确评估微信公众号的影响力对于明晰微信信息传播特点，深入挖掘微信传播潜力，进一步规范和指导微信平台的传播行为具有较大的理论和实践意义。在对既有关于微信公众号影响力研究进行梳理和评价的基础上，基于传播效果测量的设计，坚持以受众为中心、由浅入深多层次考察准则，运用德尔菲法和层次分析法建构一套微信公众号影响力指标体系。该指标体系由4个一级指标和9个二级指标构成，并运用线性合成法合成微信公众号影响力指数。     

Making Professional Decisions in Research: Measurement and Key Predictors

The professional decision-making in research (PDR) measure was administered to 400 National Institutes of Health (NIH)-funded and industry-funded investigators, along with measures of cynicism, moral disengagement, compliance disengagement, impulsivity, work stressors, knowledge of responsible conduct of research (RCR), and socially desirable response tendencies. Negative associations were found for the PDR and measures of cynicism, moral disengagement, and compliance disengagement, while positive associations were found for the PDR and RCR knowledge and positive urgency, an impulsivity subscale. PDR scores were not related to socially desirable responding, or to measures of work stressors and the remaining impulsivity subscales. In a multivariate logistic regression analysis, lower moral disengagement scores, higher RCR knowledge, and identifying the United States as one’s nation of origin emerged as key predictors of stronger performance on the PDR. The implications of these findings for understanding the measurement of decision-making in research and future directions for research and RCR education are discussed.     

Measuring operational excellence: an operational excellence profitability (OEP) approach

The pursuit of operational excellence in the manufacturing industry is at rise but its measurement still lacks of appropriate indicators to determine its financial benefits. The ambiguity is due to the impact arisen from manufacturing fluctuations such as price and cost, production mix and direct and indirect parameters variations. Manufacturing fluctuations distort the cost benefit of operational excellence. This paper, therefore, proposes the OEP (Operational Excellence Profitability) indicators to isolate the impact of manufacturing fluctuation and distinctly identify the payback of operational excellence strategies and initiatives through cost benefits of achieving higher efficiency and yield. The paper presents the conceptual and mathematical development of the proposed OEP indicators and the formulas used for their calculation. Hypothetical and industrial-based investigations and applications of the OEP indicators are conducted for their validation. The results obtained from the hypothetical exercise and industrial case suggest that OEP indicators can provide an effective cost-benefit analysis of operational excellence. This would contribute in providing manufacturing organizations with more complete information regarding the performance of their processes, which will allow their directors and managers to take better decisions related to the management and improvement of their processes.     

属性集容量确定的夹挤式测度模式及其推算模型

迄今，为解决多属性偏好关联决策属性集容量判断指数复杂性难题所提出的λ模糊测度模式与k-可加模糊测度模式，以及建构在它们之上的属性集容量确定的推算模型，尚存在着适用性差的技术不足。为此，以平衡容量判断的可操作性和容量推算的准确性为视角，提出了一种新容量测度模式，即关于容量判断与推算的夹挤式测度模式，并在此基础上通过引入决策者较易判断给出的容量序信息构建了相应的容量推算模型。基于数值模拟的对比分析表明：新模式不仅在应用可行性上高于k-可加模糊测度模式，而且从容量推算的准确性上看也明显优于λ模糊测度模式和k-可加模糊测度模式，因而对实际决策具有更强的适用性。     

Simultaneous edit-imputation and disclosure limitation for business establishment data

Business establishment microdata typically are required to satisfy agency-specified edit rules, such as balance equations and linear inequalities. Inevitably some establishments' reported data violate the edit rules. Statistical agencies correct faulty values using a process known as edit-imputation. Business establishment data also must be heavily redacted before being shared with the public; indeed, confidentiality concerns lead many agencies not to share establishment microdata as unrestricted access files. When microdata must be heavily redacted, one approach is to create synthetic data, as done in the U.S. Longitudinal Business Database and the German IAB Establishment Panel. This article presents the first implementation of a fully integrated approach to edit-imputation and data synthesis. We illustrate the approach on data from the U.S. Census of Manufactures and present a variety of evaluations of the utility of the synthetic data. The paper also presents assessments of disclosure risks for several intruder attacks. We find that the synthetic data preserve important distributional features from the post-editing confidential microdata, and have low risks for the various attacks.     

Was Cicourel’s critique in Methods and Measurement in Sociology too radical?

This article is a contribution to a mini symposium on the 50th anniversary of the publication of A V Cicourel’s Method and Measurement in Sociology (1964). The central theme of the book is reviewed – the problem of the relationship between everyday language and cultural meanings, and the language of measurement in social research – and the lack of an adequate ontology of social actors is identified as being the cause of the problem. The solution offered by Alfred Schütz – that social scientific language should be derived from everyday language – is discussed and it is argued that this was probably too radical at the time the book was published, and is still generally neglected in the social sciences.     

后金融危机时期完善公允价值计量的探索

在2008年的金融风暴中,公允价值计量虽然暴露出其固有缺陷,但目前仍不失为一种面对市场的、动态反映产权价值运动的最佳计量模式。在后金融危机时期,我们需要通过建立健全市场机制、降低公允价值计量的实际操作难度、完善估值技术等手段进一步修改与完善公允价值计量模式,助推经济复苏与调整。     

Mean shift and influence measures in linear measurement error models with stochastic linear restrictions

We present influence diagnostics for linear measurement error models with stochastic linear restrictions using the corrected likelihood of Nakamura in 1990. The case deletion and mean shift outlier models are developed to identify outlying and influential observations. We derive a corrected score test statistic for outlier detection based on mean shift outlier models. The analogs of Cook's distance and likelihood distance are proposed to determine influential observations based on case deletion models. A parametric bootstrap procedure is used to obtain empirical distributions of the test statistics and a simulation study has been used to evaluate the performance of the proposed estimators based on the mean squares error criterion and the score test statistic. Finally, a numerical example is given to illustrate the theoretical results.