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.     

ANALYZING GEOGRAPHICALLY DISCRETE WAREHOUSING NETWORKS BY COMPUTER SIMULATION*

This paper describes a comprehensive simulation modeling approach to the problem of locating warehousing facilities in a fashion that minimizes the cost associated with operating a multi-product, multi-source, multi-destination distribution system. The digital simulation model presented in the study is derived within an “industrial dynamics” framework, utilizes input from an existing management information system, and employs a number of relatively simple heuristic procedures to analyze various alternative warehousing networks. Simulation results, in terms of the distribution costs associated with various warehouse locations, are presented for cases involving the effect of provision of a 100% service level, the effect of constraining product availability and/or inventory capacities at various warehouses, and the effect of deleting various warehouses from the existing warehouse network.     

莫斯科的国际中心城市地位研究

20世纪90年代,莫斯科的政治、经济和社会结构经历了重大变革,改变了莫斯科的国家地位和国际排名。本文研究莫斯科在俄罗斯国内和在欧洲城市中的地位。毫无疑问,莫斯科的发展特点是：在逐渐脱离国家城市体系的同时,也逐渐朝着国际方向发展。以经济指标来衡量,莫斯科在国内找不到竞争对手。它远远领先于国内其他城市,因为这些城市正快速融入国内和区域经济的潮流,只在很小的程度上参与经济全球化。相反,莫斯科越来越多地争取融入跨国公司和国际经济体系的行列。虽然莫斯科作为一个国际性城市的概念往往只是城市的政治工具,但事实上,如果俄罗斯的首都想要融入世界,其资本是有限的。从中欧的角度来看,目前莫斯科最重要的功能,是连结中欧、西欧和俄罗斯。但现实是,莫斯科与俄罗斯其他城市之间的差距将会继续扩大。     

Building a Values‐Informed Mental Model for New Orleans Climate Risk Management

Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals’ values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a “Values‐informed Mental Model” research approach, or ViMM, to elicit individuals’ values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans’ unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision‐support processes and may encourage adoption of CRM strategies more in line with stakeholders’ values.     

Predicting the Risk of Biological Invasions Using Environmental Similarity and Transport Network Connectedness

Understanding the risk of biological invasions associated with particular transport pathways and source regions is critical for implementing effective biosecurity management. This may require both a model for physical connectedness between regions, and a measure of environmental similarity, so as to quantify the potential for a species to be transported from a given region and to survive at a destination region. We present an analysis of integrated biosecurity risk into Australia, based on flights and shipping data from each global geopolitical region, and an adaptation of the “range bagging” method to determine environmental matching between regions. Here, we describe global patterns of environmental matching and highlight those regions with many physical connections. We classify patterns of global invasion risk (high to low) into Australian states and territories. We validate our analysis by comparison with global presence data for 844 phytophagous insect pest species, and produce a list of high‐risk species not previously known to be present in Australia. We determined that, of the insect pest species used for validation, the species most likely to be present in Australia were those also present in geopolitical regions with high transport connectivity to Australia, and those regions that were geographically close, and had similar environments.