后现代主义教育视野下的师生观

后现代主义(postmodernism)是20世纪后半叶在西方社会流行的一种哲学、文化思潮。它脱胎于信息化后工业社会。后现代教育思想作为整个后现代思潮的一部分,它强调个人选择和参与,崇尚创造性、差异性、多样性、不确定性和建构性,主张教师与学生之间应建立一种平等的对话关系。这对我国当前的教育研究及教育改革,尤其是课堂教学改革具有一定的指导意义。     

Cost/quality tradeoffs for control procedures in information systems

An analytical framework is presented to study the cost/benefit tradeoffs of alternative internal control scenarios designed to ensure quality of outputs from information systems. A mathematical model is used to evaluate the impact that various alternatives have on system performance and cost. The model can be used to compare the benefits gained from enhanced processing with those arising from more effective internal control procedures. Model variables under the control of system designers include placement and effectiveness of internal control procedures, cost and quality of processing activities, both manual and computerized, and cost and quality of correction procedures. The model incorporates a penalty cost incurred by failure to detect and correct errors. The analytical process is illustrated through application to a specific information system.     

盈余重述归因分析——资产负债表膨胀的角度

针对国内外学者对财务重述原因的争议,在借鉴已有研究成果的基础上,本文从资产负债表膨胀的角度对盈余重述进行了归因分析。以高报盈余的重述公司为对象,利用多元回归分析等方法实证后发现,与非重述公司相比,高报盈余的重述公司在财务报告发生错误的年度资产负债表膨胀水平较高,说明公司被重述期正向调整了盈余,重述归因于公司之前年度有意的盈余管理;违规公司被重述期期初的资产负债表膨胀度显著高于非违规公司,证明公司违规主要是由于会计准则弹性范围内调整盈余的机会受限。     

Selections from Sinet – the Social Indicators Network News

Social Indicators Research -     

A new heteroscedastic regression to analyze mass loss of wood in civil construction in Brazil

A heteroscedastic regression based on the odd log-logistic Marshall–Olkin normal (OLLMON) distribution is defined by extending previous models. Some structural properties of this distribution are presented. The estimation of the parameters is addressed by maximum likelihood. For different parameter settings, sample sizes and some scenarios, various simulations investigate the performance of the heteroscedastic OLLMON regression. We use residual analysis to detect influential observations and to check the model assumptions. The new regression explains the mass loss of different wood species in civil construction in Brazil.     

AN INDEX FOR THE MEASUREMENT OF CONSUMER LOYALTY*

The concept of consumer “loyalty” (i.e., preference for a particular store or brand) is intriguing to marketing scholars and practitioners. Research in this area would be enhanced by the acceptance of an operational measure of consumer loyalty. Loyalty appears to be a tri-dimensional concept; per cent of budget, allocated to the store or brand, amount of switching, and number of alternatives explored have been used to measure loyalty. Consequently, the authors propose a “loyalty index” which combines these three measures. An empirical test of the proposed index showed that the index did discriminate among degrees of consumer loyalty, and was related to consumer psychological characteristics in a manner similar to that of the generally used single measures of consumer loyalty.     

APPLICATIONS OF SPECTRAL ANALYSIS

The basic concepts and application of spectral analysis are explained. Stationary time series and autocorrelation are first defined. Autocorrelation is related to the familiar concepts of variance and covariance. The use of autocorrelation analysis is explained in estimating the interdependent relationship of a time series over discrete time lags. In order to measure the behavior of the time series using autocorrelation, it would be necessary to examine a very large number of autocorrelation lags. Alternatively, the technique of Fourier analysis can be used to transform the autocorrelation function of the time series into a continuous function, termed a spectrum. The spectrum has a one to one correspondence to the autocorrelation for the time series and has the advantage of representing all possible autocorrelations over the discrete time lags. The spectrum can then be examined as a measure of the behavior of the time series. Spectral analysis indicates the reliability of the analysis of autocorrelated variables when familiar statistical techniques such as sample means and variances are used. The application of spectral analysis to management science problems in three general areas is illustrated: (1) inventory demand, (2) transportation simulation, and (3) stock market price behavior. Spectral analysis was used to detect cycles and trends in the data. Analyses were focused on the spectrum which provides a measure of the relative contribution of cycles in a band of frequencies to the total variance of the data.     

USING DUMMY VARIABLES TO CHECK FOR ROUNDING ERROR IN COMPUTERIZED REGRESSION PROGRAMS*

After a brief review of the role of dummy variables in regression analysis and the current state-of-the art in rounding/truncation error detection in computerized least squares programs, this paper presents a theorem that can be used to detect this type of error whenever an analyst is running a regression program that has one (or more) dummy variables as independent variables.     

DETERMINING OPTIMAL SHIFT SCHEDULES FOR TELEPHONE TRAFFIC EXCHANGE OPERATORS

A branch and bound algorithm is presented for determining the minimum number of telephone operators, and their shift schedules, required to meet demand that varies over a 24 hour operating period. An integer linear programming formulation is used, and the algorithm is described in terms of its separation, relaxation, fathoming, and branching procedures. Computational results are provided, using actual operating data. The results indicate that practical sized problems can be solved by the algorithm, involving as many as 100 different shift type variables and demand profiles typical of those encountered in many telephone traffic exchanges.