An empirical investigation of director selection in movie preproduction: A two-sided matching approach

This paper examines how movie producers recruit directors in the preproduction phase as mutual choices in a two-sided matching model. It conceptualizes that movie attributes and filmmaker characteristics determine the matching outcomes (“who directed which movie”) and in turn indirectly affect movie box office. We exploit a dataset of 4,807 feature films from 1990 to 2010 to examine empirically the complementarities between the movie/producer side and the director side in terms of movie budget, filmmaker track records and social relations. A series of simulations suggest that social relations facilitate positive assortative matching. Further simulation analyses are conducted to quantify the financial implications of movie–director mismatches, as well as the indirect effects of production budget and producer characteristics. The simulation results show that: a) the financial implications of having a mismatched director can be substantial; and b) the indirect effect of production budget and producer characteristics affect movie box office in an interactive manner. These findings can help filmmakers to better understand the financial impacts of movie–director choices and make more informed decisions at the early phase of preproduction.     

Exploring the core factors of online purchase decisions by building an E-Commerce network evolution model

With the continuous development of the Internet and information technology, online shopping has become a popular purchase mode. The in-depth analysis of consumer decision-making in online shopping is an important issue. Our purpose is to study how the factors of the shopping web pages corporately affect online purchase decisions and determine which are the core factors that affect consumer purchase decisions. We screen the influencing factors on the shopping webpage and deploy e-commerce network evolution based on various weight combinations of these factors to generate sales distributions of online products. By comparing these simulated sales distributions to the real data, the optimal weight of each factor is obtained. The results show that sales volume and the number of high-quality negative comments are the most important factors influencing consumers' decision-making, the number of comments and the number of comments with pictures are relatively minor factors, store type and video presentation of the products have the least impact. The optimal simulated sales distribution is very close to the real case and verifies that the introduced network evolution technology is applicable. The proposed model can be used as a uniform evaluation platform for correlational study, which is an important link in the purchase research chain.     

再制造逆向物流网络设计的多目标优化模型

逆向物流是物流领域的新视野,它不仅强调对废旧品的回收利用,更强调实现节约资源、保护环境和增强竞争力等目标.针对再制造逆向物流网络设计问题,在考虑废旧产品回收数量不确定的情况下,基于混合整数规划方法,建立了一个多目标的再制造逆向物流网络优化设计模型.模型以最小化网络设施总建设费用和最小化所建设施对居民产生的负效用为目标,...     

Modeling approaches for the design of resilient supply networks under disruptions

This paper studies various modeling approaches to design resilient supply networks (SN) for the location-transportation problem under uncertainty. The future environment of the SN is shaped by random demands, and by disruptions perturbing depots capacity and ship-to-point demand processes. The paper proposes several stochastic programming models incorporating alternative resilience seeking formulations. A generic approach to model SN disruptions, and to elaborate and evaluate SN designs is also proposed. Experiments are made to compare the SN design models formulated, and recommendations are drawn on the approach to use to design effective and robust supply networks.     

理实一体化在网络互联教学中的应用

本文阐述了理实一体化教学，并对其在网络互联教学中（包括课程标准、教学内容、教学实施、教学方法）的应用进行了深入的探索，最后对其在教学实践中收到的良好效果给予了肯定。     

基于Crystal Ball的PERT网络计划项目工期风险分析

文章介绍了网络计划技术,对PERT网络计划项目各活动持续时间的确定进行了分析,总结了使用Crystal Ball进行风险分析的步骤,构建了某PERT网络计划项目各活动的时间参数的Excel模型。在此基础上,使用Crystal Ball建立该项目的工期风险分析模型,并对该模型进行风险分析,获得有效的分析结果。     

Evaluating the multi-period efficiency of East Asia airport companies

The aim of this study is to analyze how internal operating sub-processes and annual operations of airport companies influence the overall efficiency. The multi-period Network Data Envelopment Analysis is used to evaluate the efficiencies and the efficiency changes for East Asia airport companies. The results indicate that the overall efficiencies of airport companies during a specified period of time are affected by the system efficiency and the sub-processes’ efficiencies in individual periods. Furthermore, the overall efficiency change is determined by the sub-processes’ efficiency changes. According to the operating decision analysis matrix, managers can discover the inefficient sub-processes and formulate the improvement countermeasures.     

Merger and acquisitions in South African banking: A network DEA model

Banking in South Africa is known for its small number of companies that operate as an oligopoly. This paper presents a strategic fit assessment of mergers and acquisitions (M&A) in South African banks. A network DEA (Data Envelopment Analysis) approach is adopted to compute the impact of contextual variables on several types of efficiency scores of the resulting virtual merged banks: global (merger), technical (learning), harmony (scope), and scale (size) efficiencies. The impact of contextual variables related to the origin of the bank and its type is tested by means of a set of several robust regressions to handle dependent variables bounded in 0 and 1: Tobit, Simplex, and Beta. The results reveal that bank type and origin impact virtual efficiency levels. However, the findings also show that harmony and scale effects are negligible due to the oligopolistic structure of banking in South Africa.     

WHICH INDUSTRIES TO BAIL OUT FIRST IN ECONOMIC RECESSION? RANKING US INDUSTRIAL SECTORS BY THE POWER-OF-PULL

There have been intense debates regarding which industrial sectors should be prioritized for receiving bailout in economic recessions. This paper takes a network perspective to rank sectors according to the Power-of-Pull (PoP), i.e. a sector's power to pull the overall economy. An eigenvector method is employed to assess the PoP of sectors in the USA, using input–output data from 1998 to 2010. The results support bailout to the motor vehicle sector, but argue against bailout to public infrastructure, health care and information technologies design and service sectors, and also reveal the continual decline of PoP ranking of computer and electronics manufacturing sector over time. These results confirm some but also show little support to some other economic revival policies of the Obama Administration in the USA.