Kwantificering in de sociologie

Ensuing the recognition of indirect measurement of so-called non-measurable data in sociological research, many kinds of indices and scales have been constructed in order to grasp the essence of complex reality. Especially in the realm of attitude research the use of e.g. the GUTTMAN scale has been fruitful. Notwithstanding many critical remarks, new developments in scaling theory and scaling techniques warrant an optimistic view of sociology as an exact empirical science. More than up to now statistical thinking and methods will have to play a part in this development.     

INNOVATIVE ATTITUDES, VALUES, AND INTENTIONS IN ORGANIZATIONS [1]

In this paper we explore the relationships between some of the various concepts and scales that have been used to characterize innovative attitudes and behaviours. A sample (N = 123) of undergraduate and graduate business students with full-time jobs or the equivalent provided questionnaire data to test two initial hypotheses. It was found that four attitude-value scales which have been used to measure change values, innovation orientation, readiness for change, and innovativenesss, are intercorrelated significantly when no distinction is made between the respondents’intentions to be innovative and respondents’actual innovative behaviour. Innovative and change attitudes, as measured by these same four scales, do consistently predict multiple innovative intentions and behaviours but not, as expected, single behaviours or single intentions. The single best predictor in a multiple regression of the combined multiple innovative intention-behaviour measure was found to be a creative scale (R²= 0.43, p < 0.01). The innovative behaviour scale was tentatively called attitude toward being innovative. A factor analysis of this scale revealed dimensions related to innovative behaviour in organizations: the innovator, the preserver of the status quo, and the unchallenged, dissatisfied person. Two other hypotheses were also tested. The first was that the perceived organization risk-taking climate would moderate the relationship between these attitude measures. This hypothesis was not supported by the overall results. However, moderate support was found for the hypothesis that the more formal authority a person has in an organization, the greater the consistency between change attitudes and innovative behaviours as measured by self-report methods.     

Covariance functions that are stationary or nonstationary in space and stationary in time

There is a great demand for statistical modelling of phenomena that evolve in both space and time, and thus, there is a growing literature on covariance function models for spatio-temporal processes. Although several nonseparable space–time covariance models are available in the literature, very few of them can be used for spatially anisotropic data. In this paper, we propose a new class of stationary nonseparable covariance functions that can be used for both geometrically and zonally anistropic data. In addition, we show some desirable mathematical features of this class. Another important aspect, only partially covered by the literature, is that of spatial nonstationarity. We show a very simple criteria allowing for the construction of space–time covariance functions that are nonseparable, nonstationary in space and stationary in time. Part of the theoretical results proposed in the paper will then be used for the analysis of Irish wind speed data as in HASLETT and RAFTERY ( Applied Statistics , 38 , 1989, 1).     

Mapping the criterion space for expatriate success: task- and relationship-based performance,effort and adaptation

The paper presents an explicit consideration of the criterion space for expatriate success. Expatriate performance is conceptualized in terms of task completion, relationship building and overall performance. These three dimensions are determined by various features of effort regulation: the amount and pattern of personal resources the expatriate spends on behaviours that constitute his or her position. Drawing upon work motivation and withdrawal literatures, we assess effort in terms of withdrawal cognitions, passive task neglect, active task avoidance, time to proficiency and leader-team exchanges. Effort regulation, in turn, is proposed to be a function of three forms of adjustment (cultural, interaction and work) – which have been the default criterion in past expatriate research. Our model is tested using multi-source data from expatriates, their spouses and their work colleagues. Support for the proposed mapping of successive linkages between adjustment, effort (including the often-studied assignment withdrawal) and performance dimensions provides a more comprehensive perspective of the expatriate criterion space.     

Corbelled Domes in Two and Three Dimensions: The Treasury of Atreus

Before the development of the true dome, many ancient cultures used the technique of corbelling to roof spaces. Recently, a series of related statistical models have been proposed in the literature for explaining how corbelled domes might have been constructed. The most sophisticated of these models is based on a piecewise linear structure, with an unknown number of changepoints, to guide the building process. This model is analyzed by the reversible jump Markov Chain Monte Carlo (MCMC) technique. All models considered to date have been two-dimensional, that is, they have taken a single cross section through the dome; even when more extensive data, in the form of measurements on multiple slices through the dome, have been available, these have been averaged together for the purposes of analysis. In this paper, we extend the two-dimensional analysis to a three-dimensional analysis, that takes full advantage of the data collected by the archaeologists and of the rotational symmetries inherent in the structure.We also explore ways of graphically presenting the results from a complex, reversible jump MCMC implementation, in order to check convergence, good mixing, and appropriate exploration of the (high dimensional and varying dimension) parameter space. The model and the graphical techniques are demonstrated on the Treasury of Atreus in Mycenae, Greece, one of the finest extant examples of the corbelling method.     

A new measurement procedure for attitudinal research. Analysis of its psychometric and informational properties

Since measurement errors have strong effects in all relationships (statistical or otherwise) studied, there is an increasing interest in the data quality, which is the major justification for this research. This paper aims to present a new measurement procedure, the letter scale, which avoids many of the problems connected with the response modalities traditionally used in attitudinal research, especially the ordinal categorical scales. This paper analyzes the error composition of the scores obtained with this new measurement procedure. The validity of the procedure is also analyzed and the observed variance is assessed to determine which part of the observed variance is “valid”, which part is random error (attenuating relationships) and which is correlated error (magnifying relationships). Structural equation models will be used to provide estimates of the measurement quality: (i) Reliability, (ii) Construct validity, method effect and residual variance. In addition, this letter scale is evaluated under another different perspective, Information Theory measures are also used to assess the amount of information transmitted. The relative merits of this new measurement procedure as opposed to other common response modalities will be discussed in both cases.     

A classification of response scale characteristics that affect data quality: a literature review

Quite a lot of research is available on the relationships between survey response scales’ characteristics and the quality of responses. However, it is often difficult to extract practical rules for questionnaire design from the wide and often mixed amount of empirical evidence. The aim of this study is to provide first a classification of the characteristics of response scales, mentioned in the literature, that should be considered when developing a scale, and second a summary of the main conclusions extracted from the literature regarding the impact these characteristics have on data quality. Thus, this paper provides an updated and detailed classification of the design decisions that matter in questionnaire development, and a summary of what is said in the literature about their impact on data quality. It distinguishes between characteristics that have been demonstrated to have an impact, characteristics for which the impact has not been found, and characteristics for which research is still needed to make a conclusion.     

An Application of Principal Component Analysis on Multivariate Time-stationary Spatio-temporal Data

Abstract

Principal component analysis (PCA) denotes a popular algorithmic technique to dimension reduction and factor extraction. Spatial variants have been proposed to account for the particularities of spatial data, namely spatial heterogeneity and spatial autocorrelation, and we present a novel approach which transfers PCA into the spatio-temporal realm. Our approach, named spatio-temporal principal component analysis (stPCA), allows for dimension reduction in the attribute space while striving to preserve much of the data's variance and maintaining the data's original structure in the spatio-temporal domain. Additionally to spatial autocorrelation stPCA exploits any serial correlation present in the data and consequently takes advantage of all particular features of spatial-temporal data. A simulation study underlines the superior performance of stPCA if compared to the original PCA or its spatial variants and an application on indicators of economic deprivation and urbanism demonstrates its suitability for practical use.     

Combining common-weights DEA window with the Malmquist index: A case of China’s iron and steel industry

In the conventional data envelopment analysis (DEA) window analysis, a decision-making unit (DMU) in each window is treated as different units in each period so that the evaluation for one unit is performed on different scales over time. This paper proposes a novel window analysis based on common weight across time (CWAT), which evaluates each unit in each window by its common scale independent of time. The model for obtaining common weights is described as linear programming. And the paper suggests the Malmquist productivity index (MPI) on CWAT, CWAT MPI, to analyze productivity change by inheriting the result of window analysis. The numerical experiments are illustrated to examine the validity of CWAT and MPI, and the result shows that the proposed method provides a new evaluation scale compared to previous studies. The proposed model is applied to evaluate the performance of China 45 iron and steel enterprises during 2009–2017. The energy and environmental efficiency are calculated using CWAT, and CWAT MPI analyzes the productivity change.     

Direct Estimation of Equivalence Scales and More Evidence on Independence of Base

We explore a direct approach to estimating household equivalence scales from income satisfaction data. Our method differs from previous approaches to using satisfaction data for this purpose in that it can be used to directly fit and evaluate closed‐form and non‐parametric equivalence scales of any desired form. Its flexibility makes it easy to consider specific aspects such as income dependence or more specific information on household composition (such as whether household members live in a partner relationship). We estimate and evaluate a number of scales used in the literature. If the equivalence scale is assumed to be independent of income and to depend only on household size, we do not reject the validity of the widely used square‐root scale at conventional significance levels. We also test GESE and GAESE restrictions (Donaldson and Pendakur, 2003, 2006) and investigate in detail to what extent household economies of scale depend on income. Our results suggest that the income dependence differs fundamentally across household types (rising economies of scale for ‘family’ households, falling economies of scale for multi‐adult households without children and no income dependence for other households).     

On possibilities and limitations of using self-anchoring scales in web surveys

Self-anchoring scales were first mentioned by Kilpatrick and Cantril (J Indiv Psychol 16:158–170, 1960) and Cantril (The pattern of human concerns, 1965) as rating instruments in which the end anchors are defined by the respondent himself, basing on his own assumptions, perceptions, goals and values. The uses of these scales are legion and they have shown to be very useful in reducing measurement bias in cross-cultural research (Cantril, The pattern of human concerns, 1965; Bernheim et al. J. Happiness Stud. 7:227–250, 2006). The first part of the current study investigates whether context effects can be lessened or eliminated by using self-anchoring scales. For this purpose, an experiment similar to the ones by Couper et al. (Public Opin Q 71:623–634, 2004, Public Opin Q 68:255–266, 2007), in which they manipulated images that figured in a web survey, was conducted. The hypothesis that self-anchoring scales can reduce contextual bias, is not supported by our data. The second part of the study investigates if and how self-anchoring scales affect drop-out during the filling-out of questionnaires. It is found that, compared to a regular rating scale, a larger proportion of respondents drop-out. Moreover, subjective preferences for the one or the other scale do not seem to differ.     

Multiscale features of extreme risk spillover networks among global stock markets

This paper studies the multiscale features of extreme risk spillover among global stock markets over various time–frequency horizons. We propose multiscale risk spillover indexes based on GARCH-EVT-VaR, maximal overlap discrete wavelet transform method, and forecast-error-variance decompositions. We further construct multiscale risk spillover networks to visualize risk spillovers at different scales. Our findings show that the US and the UK are detected as the centers of risk spillovers, while Asian stock markets are mainly at the edge of the risk spillover network. The topological properties are unevenly spread over each time scale. The network tends to be closer not only at the short-term scale but also during the financial crisis. For individual features, the US and the UK are super-spreaders of risk spillover at each time scale, while most developing markets mainly act as absorbers. The role of European stock markets is complex at different scales.     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Misspecification and Expectations Correction in New Keynesian DSGE Models

This paper focuses on the dynamic misspecification that characterizes the class of small‐scale New Keynesian models currently used in monetary and business cycle analysis, and provides a remedy for the typical difficulties these models have in accounting for the rich contemporaneous and dynamic correlation structure of the data. We suggest using a statistical model for the data as a device through which it is possible to adapt the econometric specification of the New Keynesian model such that the risk of omitting important propagation mechanisms is kept under control. A pseudo‐structural form is built from the baseline system of Euler equations by forcing the state vector of the system to have the same dimension as the state vector characterizing the statistical model. The pseudo‐structural form gives rise to a set of cross‐equation restrictions that do not penalize the autocorrelation structure and persistence of the data. Standard estimation and evaluation methods can be used. We provide an empirical illustration based on USA quarterly data and a small‐scale monetary New Keynesian model.     

Cluster Analysis for mixed data: An application to credit risk evaluation

Credit risk is one of the main risks faced by a bank to provide financial products and services to clients. To evaluate the financial performance of clients, several scoring methodologies have been proposed, which are based mostly on quantitative indicators. This paper highlights the relevance of both quantitative and qualitative features of applicants and proposes a new methodology based on mixed data clustering techniques. Indeed, cluster analysis may prove particularly useful in the estimation of credit risk. Traditionally, clustering concentrates only on quantitative or qualitative data at a time; however, since credit applicants are characterized by mixed personal features, a cluster analysis specific for mixed data can lead to discover particularly informative patterns, estimating the risk associated with credit granting.     

Randomized Response, Statistical Disclosure Control and Misclassificatio: a Review

This paper discusses analysis of categorical data which have been misclassified and where misclassification probabilities are known. Fields where this kind of misclassification occurs are randomized response, statistical disclosure control, and classification with known sensitivity and specificity. Estimates of true frequencies are given, and adjustments to the odds ratio are discussed. Moment estimates and maximum Likelihood estimates are compared and it is proved that they are the same in the interior of the parameter space. Since moment estimators are regularly outside the parameter space, special attention is paid to the possibility of boundary solutions. An example is given.     

Quantile functions for multivariate analysis: approaches and applications

Despite the absence of a natural ordering of Euclidean space for dimensions greater than one, the effort to define vector-valued quantile functions for multivariate distributions has generated several approaches. To support greater discrimination in comparing, selecting and using such functions, we introduce relevant criteria, including a notion of "medianoriented quantile function". On this basis we compare recent quantile approaches and several multivariate versions of trimmed mean and interquartile range. We also discuss a univariate "generalized quantile" approach that enables particular features of multivariate distributions, for example scale and kurtosis, to be studied by two-dimensional plots. Methods based on statistical depth functions are found to be especially attractive for quantile-based multivariate inference.     

Combining quality and quantity. A psychometric evaluation of the self-anchoring scale

In this study a psychometric comparison is made between a category rating scale with fixed anchors and a self-anchoring category rating scale where respondents themselves define the end anchors by referring to their personal experiences with the construct being measured. A student-satisfaction questionnaire was administered to 301 undergraduate students on two test moments separated by a 1-month period. Both types of category rating scales were crossed with both test moments according to a 2 ×  2 mixed factorial design. Our results show that respondents perceive the construct being measured in the same way with both rating scales. A comparison concerning different indicators of reliability, i.e. test–retest reliability, internal consistency and the error variances associated with each item, also failed to find a difference between both rating scales. In a last analysis it is demonstrated that using a self-anchoring rating scale or a rating scale with fixed anchors has a small but significant effect on the ratings of the respondents. In conclusion, a self anchoring scale may be the scale of choice if additional qualitative information from the anchors is warranted, but when quantitative comparisons between groups are required, rating scales with fixed anchors are preferable thanks to their ease of use.     

大型钢铁企业组织结构的规模效率分析

首先,分析了我国钢铁行业发展的特点,认为产品结构不够完善、行业集中度较低以及企业规模偏小是我国钢铁企业面临的主要问题,而规模是造成上述现状的根本原因;国际钢铁业已进入由大企业集团主宰的国际市场化阶段,我国钢铁企业需要扩大规模,增加在国际竞争中的话语权。其次。围绕企业的规模运作,运用经济学模型对产业链的大规模企业生产模式进行了分析,从理论视角论证了企业扩大规模的动机以及规模优势产生的机制和所需条件。大型组织结构优势产生的机制在于,通过生产及运营要素的优化整合实现合理分工协作,从而降低运营成本,提高企业的竞争力。此外,对钢铁企业采用的组织结构特点和运营模式进行了探讨,一元式的组织结构能够发挥职能分工所带来的效率,然而高度的集权特征不适用于超大规模企业的管理决策。控股公司和事业部结构体现了规模化后组织结构由集权向分权转化的趋势,但在运行中面临的效率障碍在于无法消除部门机会主义．分权后权威统筹机构的缺位以及传统的规模企业应当分权的逻辑需要企业重新思考。在上述分析基础上提出．钢铁企业在实现形式上的规模化后,需要考虑技术任务特征、信息处理以及权力的分化整合之间的平衡,构造合理的控制机制以保证规模优势的实现。     

常州市物流园区科学建设对策思考

随着常州经济的快速发展,物流园区建设势在必行,建设定位准确、规模适当的物流园区,是常州经济发展中面临的一项重要课题。作者从常州经济发展的实际情况出发,在深入调查研究、查阅相关数据资料的基础上,对常州建设物流园区的必要性、可行性进行了分析,并提出了常州科学建设物流园区的对策。