试论从项目决策及设计阶段加强投资管理

文章试图结合作者所参与项目得到的体会 ,阐述加强项目前期投资管理的必要性和重要性 ,以及如何加强项目前期投资管理。项目投资管理只有从项目前期抓起、优化工程设计 ,加强项目各阶段的审查 ,从源头上控制项目投资 ,才能有效而合理控制整个项目投资。     

Contracts,Negotiation, and Learning: An Examination of Termination Provisions

Taking a temporal view of learning in partnerships, we argue that learning to contract from prior relationships can be manifested not only in an increase in the level of contractual detail but also in a decrease in negotiation time for a given level of contractual detail. We analyse the influence that the length of prior relationships and the detail of termination provisions have on negotiation time, or the time period that it takes for partners to reach a mutually acceptable agreement. We find that: (1) the length of prior relationships has a curvilinear, U‐shaped effect on negotiation time, suggesting the possibility of diverse learning mechanisms as the relationship unfolds; (2) the impact of the detail of termination provisions on negotiation time varies across different types of termination provisions; and (3) it takes a shorter time to negotiate certain types of termination provisions when partners have longer prior relationships. Beyond suggesting the need to investigate the consequences of contractual provisions for collaborators, our study proposes negotiation time as an additional indicator of a learning‐to‐contract effect that complements existing ones.     

Improvised internationalization in new ventures: The role of prior knowledge and networks

How do entrepreneurs identify foreign market opportunities and how do they identify foreign market(s) and customers? We draw on the concepts of effectuation, improvisation, prior knowledge and networks to study the early internationalization of new ventures operating in the Irish Shellfish sector. We argue that the internationalization process was strongly influenced by two ‘resources to hand’: the entrepreneurs’ idiosyncratic prior knowledge and their prior social and business ties. We observe an effectuation logic and extensive improvisation in the internationalization process of these new ventures.     

A simple method for estimating preference parameters for individuals

This paper demonstrates a method for estimating logit choice models for small sample data, including single individuals, that is computationally simpler and relies on weaker prior distributional assumptions compared to hierarchical Bayes estimation. Using Monte Carlo simulations and online discrete choice experiments, we show how this method is particularly well suited to estimating values of choice model parameters from small sample choice data, thus opening this area to the application of choice modeling. For larger sample sizes of approximately 100–200 respondents, preference distribution recovery is similar to hierarchical Bayes estimation of mixed logit models for the examples we demonstrate. We discuss three approaches for specifying the conjugate priors required for the method: specifying priors based on existing or projected market shares of products, specifying a flat prior on the choice alternatives in a discrete choice experiment, or adopting an empirical Bayes approach where the prior choice probabilities are taken to be the average choice probabilities observed in a discrete choice experiment. We show that for small sample data, the relative weighting of the prior during estimation is an important consideration, and we present an automated method for selecting the weight based on a predictive scoring rule.     

单位球上调和Dirichlet空间上的分式线性复合算子

研究了单位球上调和Dirichlet空间上的分式线性复合算子的伴随表示,并在此基础上讨论了空间■h(BN)和■h0(BN)上的分式线性复合算子的正常性与本性正常性.     

Hidden group patterns in democracy developments: Bayesian inference for grouped heterogeneity

We propose a nonparametric Bayesian approach to estimate time‐varying grouped patterns of heterogeneity in linear panel data models. Unlike the classical approach in Bonhomme and Manresa (Econometrica, 2015, 83, 1147–1184), our approach can accommodate selection of the optimal number of groups and model estimation jointly, and also be readily extended to quantify uncertainties in the estimated group structure. Our proposed approach performs well in Monte Carlo simulations. Using our approach, we successfully replicate the estimated relationship between income and democracy in Bonhomme and Manresa and the group characteristics when we use the same number of groups. Furthermore, we find that the optimal number of groups could depend on model specifications on heteroskedasticity and discuss ways to choose models in practice.     

Innovation shock,outsourcing strategy,and environmental performance: The roles of prior green innovation experience and knowledge inheritance

To investigate under what conditions an outsourcing strategy can show superior environmental performance, one stream of scholars has underscored the importance of prior green innovation experience, and another stream of scholars has underscored the importance of the in‐house possession of outsourced component knowledge. However, the empirical findings regarding the positive role of both scholarly streams when studied separately are mixed and sometimes contradictory. This study bridges these two distinct but related streams and suggests that prior green innovation experience and in‐house knowledge regarding outsourced components play a complementary role in enhancing environmental performance. The U.S. hybrid electric vehicle market lends support to the argument of this study. In so doing, this study increases our understanding of the role of prior green innovation experience and outsourced component knowledge on environmental performance while pursuing an outsourcing strategy. This study also provides guidance for managers and policymakers on how to achieve superior environmental performance in outsourcing.     

Mean squared error of ridge estimators in logistic regression

It is well known that the maximum likelihood estimator (MLE) is inadmissible when estimating the multidimensional Gaussian location parameter. We show that the verdict is much more subtle for the binary location parameter. We consider this problem in a regression framework by considering a ridge logistic regression (RR) with three alternative ways of shrinking the estimates of the event probabilities. While it is shown that all three variants reduce the mean squared error (MSE) of the MLE, there is at the same time, for every amount of shrinkage, a true value of the location parameter for which we are overshrinking, thus implying the minimaxity of the MLE in this family of estimators. Little shrinkage also always reduces the MSE of individual predictions for all three RR estimators; however, only the naive estimator that shrinks toward 1/2 retains this property for any generalized MSE (GMSE). In contrast, for the two RR estimators that shrink toward the common mean probability, there is always a GMSE for which even a minute amount of shrinkage increases the error. These theoretical results are illustrated on a numerical example. The estimators are also applied to a real data set, and practical implications of our results are discussed.     

SPLIT–PLOT DESIGN: MODEL AND ANALYSIS FOR COUNT DATA

The analysis of count response data from designed experiments is well–known for independent response variables having the Poisson distribution. For experimental designs where responses are dependent, no general results seem to be available. An example of this type of design is the split–plot design, where sub–plot responses are essentially dependent within whole plots.
In this paper, a model will be proposed for split–plot count data and a separate analysis for whole plot and sub–plot data will be presented. It is interesting to note, that the same model is used in the quite different context of consumer buying behaviour. It is derived by Goodhardt, Ehrenberg and Chatfield and it was called the 'Dirichlet model', as the Dirichlet multinomial distribution, together with the negative binomial distribution, build up the model.     

BAYESIAN ESTIMATION OF T–G RIDGE MODEL

Ridge type analysis of the Theil–Goldberger mixed model, considered earlier by Saxena and Bhatta–charya (1983) for the non–Bayesian set–up, is discussed from the Bayesian view–point when a has a closed prior and the loss–function being squared error.