A decomposition technique for quantifying real process performance

A decomposition technique for quantifying the impacts of changes in product mix and process performance on aggregate process-related indicators is presented. Through application of the technique, the real performance of a process can be quantified. Changes in real performance over time can be monitored to provide useful information for process evaluation and production planning. Two case studies, one related to the aggregate defective rate for an assembly line of an integrated circuit fabrication plant and the other to the aggregate inventory turnover for a tyre distribution company, are presented to illustrate the application of the technique.     

Wird die Relevanz von Ertragsteuern für die Unternehmensrechnung nach rechtlichen oder ökonomischen Kriterien beurteilt?

Textbooks in the areas of Management Accounting, Finance and Valuation treat taxes very differently. Finance and Valuation increasingly consider tax effects. Management Accounting considers taxes only if they meet certain legal “cost” criteria. These criteria follow tax law rules, but not economic rules and primarily consider tax effects of the local business tax only. This view is also reflected in recent cost accounting regulations. We present evidence from a survey of managers and chambers of commerce, according to which practitioners’ views of whether the local business tax is a cost are heterogeneous. The majority of managers do not consider the local business tax as a cost and do not pass it on to customers. The chambers of commerce however still consider the local business tax as a cost.     

利益相关者影响企业财务绩效的理论分析与实证研究

本文从利益相关者视角出发,综合价值链理论、契约理论和期望理论,分析了利益相关者影响企业财务绩效的机理,指出利益相关者满足是影响企业财务绩效的关键因素,并在理论上分析了实现企业财务绩效最大化的条件.在此基础上,采用面板数据模型对中国上市公司数据进行了实证分析.研究表明:利益相关者满足与企业财务绩效之间存在着显著的相关性,β值的分析显示中国上市公司对不同利益相关者的满足水平并不合理,公司可按照β值对不同利益相关者的投入产出效率进行调整,从而提升其财务绩效.     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.     

Calibration estimation in dual-frame surveys

Survey statisticians make use of auxiliary information to improve estimates. One important example is calibration estimation, which constructs new weights that match benchmark constraints on auxiliary variables while remaining “close” to the design weights. Multiple-frame surveys are increasingly used by statistical agencies and private organizations to reduce sampling costs and/or avoid frame undercoverage errors. Several ways of combining estimates derived from such frames have been proposed elsewhere; in this paper, we extend the calibration paradigm, previously used for single-frame surveys, to calculate the total value of a variable of interest in a dual-frame survey. Calibration is a general tool that allows to include auxiliary information from two frames. It also incorporates, as a special case, certain dual-frame estimators that have been proposed previously. The theoretical properties of our class of estimators are derived and discussed, and simulation studies conducted to compare the efficiency of the procedure, using different sets of auxiliary variables. Finally, the proposed methodology is applied to real data obtained from the Barometer of Culture of Andalusia survey.     

A NOTE ON A MULTIVARIATE GENERALIZATION OF THE KRUSKAL-WALLIS TEST

Marketers are often interested in testing whether the mean vectors of multivariate distributions are equal. The test usually applied, one-way MANOVA, assumes the distributions are multinormal. Unfortunately, this assumption is not supported in many studies. As an alternative, a nonparametric multivariate one-way analysis of variance procedure is presented.     

EXPLORING MARKET PRICING STRATEGIES VIA DYNAMIC PROGRAMMING

Price determinants as well as strategies can be studies by use of simulation, particularly if cost and price relationships can be related to market activity [1] [9] [11]. But, through the use of dynamic programming, given the market conditions, one can extend the analysis to include an optimal strategy. This paper describes a dynamic programming approach to studying price strategy. A model is developed to show that in a market characterized by cost/volume and price/volume relationships, profitability can be extended beyond that resulting from a dominant market strategy to an optimal maximizing strategy. Extension of the model is suggested for studying (a) sensitivity of a strategy (solution) to price level and cost changes, (b) optimal timing of withdrawal, and (c) present value analysis.     

SENSITIVITY ANALYSIS WITH INTERACTION EFFECTS

The purpose of this paper is to extend the sensitivity analysis methodology as it applies to linear programming. The methodology developed herein is concerned with those changes in a technological coefficient that cause simultaneous changes in the relevant cost coefficients of the objective function. By proceeding from the definitions of feasibility and optimality, the authors develop formulas for determining bounds on the extent to which a technological coefficient, which has a predetermined effect on the corresponding cost coefficient, can vary without changing the optimal set of activities. After the formulas are developed, their use is demonstrated on a product-mix problem. This technique is of interest because changes in the rate at which an input is utilized can be expected to change the cost per unit of a resulting product. This interdependence should be recognized whenever a sensitivity analysis is performed on a technological coefficient of either a cost minimization or a contribution margin maximization problem.