Hybrid decision model for information project selection

Information project selection is an important and recurring activity in many organizations. Establishing a systematic project selection model thus is important for organizations. However, information system project selection is made difficult by the need to consider numerous quantitative and qualitative factors, such as business goals, benefits, project risks and limitations in available resources. This study proposes a hybrid measurement model for evaluating the overall effects of information projects. The selection model generates critical, quantitative and qualitative indicators to help managers realize the advantages/disadvantages of operational conditions. This hybrid selection model not only accelerates project evaluation and selection, but also helps organizations optimize project selection and thus achieve sustainable development.     

高职院校科研选题策略

科研选题是高职院校科研工作的起点,是高职课题研究迈出的第一步。文章对目前我国高职院校科研选题存在现象进行了分析,提出了在高职科研选题过程需要结合一定的选题原则,在掌握必要的选题方法和明确的目的前提下进行选择。     

Binary response panel data models with sample selection and self‐selection

We consider estimating binary response models on an unbalanced panel, where the outcome of the dependent variable may be missing due to nonrandom selection, or there is self‐selection into a treatment. In the present paper, we first consider estimation of sample selection models and treatment effects using a fully parametric approach, where the error distribution is assumed to be normal in both primary and selection equations. Arbitrary time dependence in errors is permitted. Estimation of both coefficients and partial effects, as well as tests for selection bias, are discussed. Furthermore, we consider a semiparametric estimator of binary response panel data models with sample selection that is robust to a variety of error distributions. The estimator employs a control function approach to account for endogenous selection and permits consistent estimation of scaled coefficients and relative effects.     

基于模糊物元分析的航材仓库选址决策

在分析空军航材仓库选址影响因素的基础上,基于模糊物元分析原理,建立了航材仓库选址决策的模糊物元分析法。模糊物元分析法可对航材仓库选址决策进行定量分析,从而确定各选址方案的排序。最后,结合实例进行了应用分析,获得了满意的结果。航材仓库选址决策的模糊物元分析法,为空军航材仓库选址决策提供了一种更为科学、有效的方法。     

Practice and promise of formal supplier selection: a study of four empirical cases

In this paper an experimental study of formal decision-making models for supplier selection is described. Attention is paid to all phases of the supplier selection process: the recognition of the need for a new supplier, the formulation of decision criteria, the qualification of suitable candidates and final selection. It appears from the experiments that formal decision models may prove to be useful in various ways throughout the whole supplier selection process and in different purchasing situations.     

改进的TOPSIS法在ERP软件选型中的应用

ERP软件选型是企业在实施ERP过程中的重要内容。文章通过对ERP软件选型的影响因素分析,建立了ERP软件选型评价指标体系,并尝试利用逼近理想解的排序法(TOPSIS法)进行评价。由于人们对ERP软件选型的认识处于一种灰色的状态,故在求解过程中用灰色关联度来确定各指标的权重,以使得ERP软件选型更客观合理。     

What is required for greener supplier selection? A literature review and conceptual model development

This paper examines the existing literature on green supplier selection. In total, 60 articles are reviewed, all published in peer-reviewed journals between 1991 and 2011. The articles are analyzed in terms of several general variables such as type of research and theoretical viewpoint, as well as more specific variables such as the supply chain position considered, stages of the supplier selection process studied, and the perspective taken on environmental criteria. The main findings are threefold. First, analytical research, focusing on developing normative decision models for the final stage in green supplier selection is clearly most dominant, employing a wide range of techniques. Second, empirical research is less prominent and generally lacks a clear theoretical background. Third, very little conceptual research has been done linking green supplier selection to an organization's strategy. Research on green supplier selection is highly fragmented and in danger of overemphasizing the technical aspects of supplier selection. Based on this review of the articles, a conceptual model of green supplier selection is presented, aimed at integrating the different dimensions of green supplier selection and identifying directions for future research.     

GMADM-based attributes selection method in developing prediction model

Attribute Selection is an important issue for developing a prediction model, however, how to determine an effective attribute selection algorithm is an important but difficult issue. Attribute selection can effectively delete the irrelevant and redundant attributes to increase the prediction accuracy, and evaluating attribute selection methods usually need to consider several criteria such as accuracy, type I error, and type II error. In this paper, the selected attribute process is modeled as a group multiple attributes decision making (GMADM) problem. In evaluating different GMACD methods, the most results usually are consistently, But there are some situations where the evaluated outcomes have different results. The GMADM method is useful tool for evaluating attribute selection algorithms, and the TOPSIS is capable of identifying a compromised solution when different GMADM method result in conflicting rankings. Therefore, this paper proposes an objective (persuasive) GMADM-based attributes selection method to solve this disagreement and help decision makers pick the most suitable method. After verification, the proposed model is more persuasive to evaluate the attributes selection methods for developing prediction model.     

Sample selection bias with multiple selection rules: An application to student aid grants

This paper extends the sample selection bias correction procedure, developed by James J. Heckman, to the case of multiple selection rules. Estimators are presented for independent selection rules and a consistent estimator for the variance-covariance matrix is derived. The methodology is applied to the problem of estimating the financial aid available to U.S. highschool students for college education. In order to be observed in receipt of financial aid, a student has to be both enrolled in college and to have had an expected value of aid in excess of the costs of applying. Both of these sources of selection bias were found to be important.     

Impact of culture on ‘partner selection criteria’ in East Asian international joint ventures

Selecting the right partner is important for the success of alliances and joint ventures. For international joint ventures (IJVs) from diverse cultures the partner selection process can become complicated. Prior studies have investigated the alliances and joint ventures to develop a set of objective criteria for evaluating potential partners. This paper reports the study of IJVs formed by Singapore firms in Peoples Republic of China and India. The intent was to develop a methodology for identifying partner selection criteria in a cross-cultural setting. The findings reveal that the partner selection process follows a different logic in Confucian societies. Trust has been established to be essential for developing enduring co-operative relationships. The paper explores the concept of trust in relation to commitment and control in the context of the Confucian culture. We discover that trust is critical to partner selection. Cultural differences do not significantly alter the partner selection criteria for Singapore firms. Results support the view that while Chinese may depend on networks for social solidarity, social trust does extends beyond the family and is necessary for harmonious and successful joint ventures.     

Incorporating support vector machines with multiple criteria decision making for financial crisis analysis

Feature selection is an essential pre-processing technique in data mining that eliminates redundant or unrepresentative attributes and improves the performance of classifiers. However, a classifier with different feature selection approaches results in diverse outcomes. Thus, determining how to integrate feature selection methods and yield an appropriate feature set is an issue worth further study. Based on ensemble learning, this investigation develops a SVMMCDM (support vector machines with multiple criteria decision making) model that employs various feature selection techniques as data preprocessing schemes and then uses SVM for financial crisis prediction. The study uses MCDM to determine the most suitable feature selection mechanism when many performance criteria are considered. After the feature selection mechanism has been determined, the study decomposes the SVM to obtain support vectors and predicted labels which are then fed into a decision tree to generate rules. The numerical results for the ex-ante and ex-post periods relative to the financial tsunami show that the proposed SVMMCDM model is an effective way to predict a financial crisis and can provide useful rules for decision makers.     

浅议制造型企业如何选择供应商

在供应链管理环境下,供应商的选择对制造型企业是非常重要的。为了让制造型企业的供应商选择工作更加高效且成本更低,文章在已有供应商选择理论的基础上,针对制造型企业,首先分析了供应商的分类,然后建立了一个制造型企业选择供应商的指标体系,给出了制造型企业选择供应商的基本流程。     

浅谈结构选型与建筑使用功能、经济造价的关系

结构选型与建筑使用功能、经济造价有很大的关系,有时结构选型受建筑使用功能的影响,有时结构选型决定经济造价。在业主对建筑使用功能的要求下进行结构选型,经济造价提高是解决不了的矛盾,最优的结构型选及其设计应是结构设计人员必上的一课。     

Model selection in univariate time series forecasting using discriminant analysis

When a large number of time series are to be forecast on a regular basis, as in large scale inventory management or production control, the appropriate choice of a forecast model is important as it has the potential for large cost savings through improved accuracy. A possible solution to this problem is to select one best forecast model for all the series in the dataset. Alternatively one may develop a rule that will select the best model for each series. Fildes (1989) calls the former an aggregate selection rule and the latter an individual selection rule. In this paper we develop an individual selection rule using discriminant analysis and compare its performance to aggregate selection for the quarterly series of the M-Competition data. A number of forecast accuracy measures are used for the evaluation and confidence intervals for them are constructed using bootstrapping. The results indicate that the individual selection rule based on discriminant scores is more accurate, and sometimes significantly so, than any aggregate selection method.     

基于层次模糊评价法的供应商选择

供应商选择是供应链管理的重要内吝之一。文章在分析供应商选择评价指标体系的前提下,建立了基于层次分析法和模糊评价法的层次模糊评价法。该方法避免了不确定性对供应商选择结果的影响,为供应商的选择提供了一个更为科学、合理的方法。     

Deriving target selection rules from endogenously selected samples

The selection of the most profitable customers in a customer database for targeted activities is often done based on observed behaviour in the past. Consequently, databases arising from the responses to, for example, direct mailings in the past are not random samples. When not all heterogeneity across customers is observed, target selection will be based on unobserved heterogeneity and hence it is endogenous. We develop a method to adjust the likelihood function of latent class models to correct for this endogenous sampling process. We apply this technique to the selection of mail targets for a Dutch charity. Based on a joint model for the response rate and the amount donated, we create a target selection rule that maximizes expected revenues. Copyright © 2006 John Wiley & Sons, Ltd.     

装备维修方法最优化选择探析

针对装备维修方法选择需要考虑的实际问题,以定期维修、事后维修和基于状态的维修为选择对象,总结不同维修方法的比较原则,构建维修方法的选择标准,在此基础上设计维修方法的选择流程,为装备维修方法的最优化选择提供参考。     

Simply the best? The case for using ‘threshold selection’ in hiring decisions

This paper argues the case for a more progressive approach to diversity and inclusion that incorporates a form of positive discrimination in the selection process: ‘threshold selection’. It outlines the distinctive features of threshold selection and argues that it is an approach that resolves the tension between suitability and acceptability criteria, relies on high formalisation and transparency, can mitigate some of the self‐serving bias among selectors and ties the selection needs to the goals of the organisation. In these respects, although controversial, threshold selection offers a thorough and systematic approach that is entirely consistent with the general tendency towards greater professionalisation of HRM.     

On a criterion for the selection of models for stationary time series

Summary A general approach to model selection is described and a criterion for the selection of parametric models for stationary Gaussian time series is derived. A corresponding approximate test is also given and experiences in applying the criterion are reported.     

Estimating panel data models in the presence of endogeneity and selection

We consider estimation of panel data models with sample selection when the equation of interest contains endogenous explanatory variables as well as unobserved heterogeneity. Assuming that appropriate instruments are available, we propose several tests for selection bias and two estimation procedures that correct for selection in the presence of endogenous regressors. The tests are based on the fixed effects two-stage least squares estimator, thereby permitting arbitrary correlation between unobserved heterogeneity and explanatory variables. The first correction procedure is parametric and is valid under the assumption that the errors in the selection equation are normally distributed. The second procedure estimates the model parameters semiparametrically using series estimators. In the proposed testing and correction procedures, the error terms may be heterogeneously distributed and serially dependent in both selection and primary equations. Because these methods allow for a rather flexible structure of the error variance and do not impose any nonstandard assumptions on the conditional distributions of explanatory variables, they provide a useful alternative to the existing approaches presented in the literature.