The pre-acquisition evaluation of target firms and cross border acquisition performance

The paper investigates the impact of the pre-acquisition evaluation of target firms on the performance of cross border acquisitions using data from a sample of acquisitions made by UK firms. The findings provide reasonable support for organizational learning theory, suggesting that the more the acquiring firm learns about the target firm then the better will be the acquisition performance. Specifically, we find support for the hypothesis that thorough evaluation of the strategic and cultural fit positively influences cross border acquisition success. Further, the analysis reveals that detailed evaluation of the target firm's employee and business capability improves acquisition performance. The managerial implications of the findings and directions for future research are also discussed.     

How Effective Is Foreign Aid at Improving Health Outcomes in Recipient Countries?

Since the United Nations’ establishment of the Millennium Development Goals (MDGs) in 2000 the world has observed an increasing trend in foreign aid provided by more affluent countries to developing nations. This paper examined whether foreign aid (total foreign aid and health sector aid) has been effective in improving the health of citizens in recipient nations since establishment of the MDGs. Five facets of population health were examined: infant mortality, life expectancy, the annual death rate, and immunizations against measles and diphtheria. Using a panel data set covering 90 developing countries, observed annually over 2001–2015, fixed-effects multivariate regressions with alternative specifications were estimated for each of these measures. The findings reveal that foreign aid has had little to no effect on population health since 2000. We found some evidence that foreign aid has improved life expectancy in developing countries, however, the effect is very small. In light of these findings, continued monitoring of the relationship between foreign aid and health outcomes would be both valuable and prudent.

     

从发展差距角度看民族地区建设小康社会的艰巨性——以新疆为例

全面建设小康社会,区域难点在民族地区,城乡难点在农村。少数民族地区的农牧区处于此二者的交汇处,属我国全面建设小康社会的难中之难。全面建设小康社会这一宏伟目标能否顺利实现,关键在于民族地区农牧区居民收入与生活水平是否能达到小康标准。从民族地区农村居民收入的增长趋势看,现阶段很难达到目标。因此,未来的关键是下大力气增加农牧民收入,并加快增长速度。     

Application of ANFIS to exchange rate forecasting

The need of exchange rate forecasting in order to preventing its disruptive movements has engrossed many policy-makers and economists for many years. The determinants of exchange rate have grown manifold making its behavior complex, nonlinear and volatile so that nonlinear models have better performance for its forecasting. In this study the accuracy of ANFIS as the nonlinear model and ARIMA as the linear models for forecasting 2, 4 and 8 days ahead of daily Iran Rial/∈ and Rial/US$ was compared. Using forecast evaluation criteria we found that nonlinear model outperforms linear model in all three horizons.     

TD-LTE抢占无线全新商机

如今,为了努力满足用户对移动数据日益增长的需求,大部分运营商的网络和频段都在满负荷运行。据相关数据显示,2010年用户每月使用的数据流量已经超过了5GB。由于数据增长的关键驱动因素——smartphone的普及率在全球仍低于20%,运营商预计用户每月使用的数据流量仍将继续增长。因此,如何充分利用自身的频谱资源、开发包括TD-LTE在内的不同技术选择的潜力,就成为运营商极为关注的重要课题。     

A gossip based information fusion protocol for distributed frequent itemset mining

The computational complexity, huge memory space requirement, and time-consuming nature of frequent pattern mining process are the most important motivations for distribution and parallelization of this mining process. On the other hand, the emergence of distributed computational and operational environments, which causes the production and maintenance of data on different distributed data sources, makes the parallelization and distribution of the knowledge discovery process inevitable. In this paper, a gossip based distributed itemset mining (GDIM) algorithm is proposed to extract frequent itemsets, which are special types of frequent patterns, in a wireless sensor network environment. In this algorithm, local frequent itemsets of each sensor are extracted using a bit-wise horizontal approach (LHPM) from the nodes which are clustered using a leach-based protocol. Heads of clusters exploit a gossip based protocol in order to communicate each other to find the patterns which their global support is equal to or more than the specified support threshold. Experimental results show that the proposed algorithm outperforms the best existing gossip based algorithm in term of execution time.     

Empirical Bayes analysis of log-linear models for a generalized finite stationary Markov chain

This article presents the empirical Bayes method for estimation of the transition probabilities of a generalized finite stationary Markov chain whose ith state is a multi-way contingency table. We use a log-linear model to describe the relationship between factors in each state. The prior knowledge about the main effects and interactions will be described by a conjugate prior. Following the Bayesian paradigm, the Bayes and empirical Bayes estimators relative to various loss functions are obtained. These procedures are illustrated by a real example. Finally, asymptotic normality of the empirical Bayes estimators are established.     

AN APPLICATION OF ACTIVITY BASED COSTING IN THE AIR CONDITIONER MANUFACTURING INDUSTRY

AIRCO is a manufacturer of industrial air conditioner units whose management is concerned that their current traditional cost accounting (TCA) system is not accurately representing their product cost behavior. Under certain operating conditions, an activity based costing (ABC) system can provide relevant and accurate indirect cost information that assists in making customer, product, and process improvement decisions. An ABC system was successfully developed for AIRCO that indicated that their products do not consume overhead costs on a volume basis as represented by their current TCA system. Valuable product and process information were obtained. This case study details the development process that was used and the results that were obtained during the ABC analysis.     

Credit constraints and smallholder dairy production in the East African highlands: application of a switching regression model

Accurate assessment of farmers' credit constraint condition is important in order to understand the circumstances under which credit would have its greatest impact. In this study a switching regression model was used to determine the impact of credit on smallholder dairy farms in the East African highlands using farm level data from Ethiopia and Kenya. Farmers were classified as credit constrained or credit non-constrained based on their responses from the farm level surveys. No consistent relationship was found between farmers' credit constraint condition and their borrowing status. Most of the variation in milk output per farm was explained by the number of crossbred milking cows in the dairy herd. As credit is likely to facilitate investment in crossbred dairy cows it will have substantial impacts on smallholder dairy farms especially if it is targeted to credit constrained farms.