Two-stage financial risk tolerance assessment using data envelopment analysis

Typical questionnaires administered by financial advisors to assess financial risk tolerance mostly contain stereotypes of people, have seemingly unscientific scoring approaches and often treat risk as a one-dimensional concept. In this work, a mathematical tool was developed to assess relative risk tolerance using Data Envelopment Analysis (DEA). At its core, it is a novel questionnaire that characterizes risk by its four distinct elements: propensity, attitude, capacity, and knowledge. Over 180 individuals were surveyed and their responses were analyzed using the Slacks-based measure type of DEA efficiency model. Results show that the multidimensionality of risk must be considered for complete assessment of risk tolerance. This approach also provides insight into the relationship between risk, its elements and other variables. Specifically, the perception of risk varies by gender as men are generally less risk averse than women. In fact, risk attitude and knowledge scores are consistently lower for women, while there is no statistical difference in their risk capacity and propensity compared to men. The tool can also serve as a “risk calculator” for an appropriate and defensible method to meet legal compliance requirements, known as the “Know Your Client” rule, that exist for Canadian financial institutions and their advisors.     

Adjusting a railway timetable in case of partial or complete blockades

Unexpected events, such as accidents or track damages, can have a significant impact on the railway system so that trains need to be canceled and delayed. In case of a disruption it is important that dispatchers quickly present a good solution in order to minimize the nuisance for the passengers. In this paper, we focus on adjusting the timetable of a passenger railway operator in case of major disruptions. Both a partial and a complete blockade of a railway line are considered. Given a disrupted infrastructure situation and a forecast of the characteristics of the disruption, our goal is to determine a disposition timetable, specifying which trains will still be operated during the disruption and determining the timetable of these trains. Without explicitly taking the rolling stock rescheduling problem into account, we develop our models such that the probability that feasible solutions to this problem exist, is high. The main objective is to maximize the service level offered to the passengers. We present integer programming formulations and test our models using instances from Netherlands Railways.     

A 4D-sequencing approach for air traffic management

The current air traffic system is forecasted to face strong challenges due to the continuous increase in air traffic demand. Hence, there is a need for new types of organization permitting a more efficient air traffic management, with both a high capacity and a high level of safety, and possibly with a reduced environmental impact. In this article, we study a holistic approach, consisting in designing across Europe a very organized air traffic system, as opposed to free flight, to reduce costs while maintaining safety.     

Computing approximate Nash equilibria in general network revenue management games

Computing optimal capacity allocations in network revenue management is computationally hard. The problem of computing exact Nash equilibria in non-zero-sum games is computationally hard, too. We present a fast heuristic that, in case it cannot converge to an exact Nash equilibrium, computes an approximation to it in general network revenue management problems under competition. We also investigate the question whether it is worth taking competition into account when making (network) capacity allocation decisions. Computational results show that the payoffs in the approximate equilibria are very close to those in exact ones. Taking competition into account never leads to a lower revenue than ignoring competition, no matter what the competitor does. Since we apply linear continuous models, computation time is very short.     

Optimal credit period and lot size for deteriorating items with expiration dates under two-level trade credit financing

In a supplier-retailer-buyer supply chain, the supplier frequently offers the retailer a trade credit of S periods, and the retailer in turn provides a trade credit of R periods to her/his buyer to stimulate sales and reduce inventory. From the seller’s perspective, granting trade credit increases sales and revenue but also increases opportunity cost (i.e., the capital opportunity loss during credit period) and default risk (i.e., the percentage that the buyer will not be able to pay off her/his debt obligations). Hence, how to determine credit period is increasingly recognized as an important strategy to increase seller’s profitability. Also, many products such as fruits, vegetables, high-tech products, pharmaceuticals, and volatile liquids not only deteriorate continuously due to evaporation, obsolescence and spoilage but also have their expiration dates. However, only a few researchers take the expiration date of a deteriorating item into consideration. This paper proposes an economic order quantity model for the retailer where: (a) the supplier provides an up-stream trade credit and the retailer also offers a down-stream trade credit, (b) the retailer’s down-stream trade credit to the buyer not only increases sales and revenue but also opportunity cost and default risk, and (c) deteriorating items not only deteriorate continuously but also have their expiration dates. We then show that the retailer’s optimal credit period and cycle time not only exist but also are unique. Furthermore, we discuss several special cases including for non-deteriorating items. Finally, we run some numerical examples to illustrate the problem and provide managerial insights.     

Make-or-buy service capacity decision in a supply chain providing after-sales service

We consider a supply chain comprising a manufacturer and a retailer. The manufacturer supplies a product to the retailer, while the retailer sells the product bundled with after-sales service to consumers in a fully competitive market. The sales volume is affected by the retailer’s service-level commitment. The retailer can build service capacity in-house at a deterministic price before service demand is realized, or buy the service from an outsourcing market at an uncertain price after service demand realization. We find that the outsourcing market encourages the retailer to make a higher level of service commitment, while prompting the manufacturer to reduce the wholesale price, resulting in more demand realization. We analyze how the expected cost of the service in the outsourcing market and the retailer’s risk attitude affect the decisions of both parties. We derive the conditions under which the retailer is willing to build service capacity in-house and under which it will buy the service from the outsourcing market. Moreover, we find that the manufacturer’s sharing with the retailer the cost to build service capacity improves the profits of both parties.     

More than a second channel? Supply chain strategies in B2B spot markets

The emergence of B2B spot markets has greatly facilitated spot trading and impacted supply chain structures as well as the way commercial transactions take place between firms in many industries. While providing new opportunities, the B2B spot market also exposes participants to a price risk. This new business landscape raises some important questions on how the supplier and manufacturer should change their sales channel and procurement strategies and tailor their decisions to this changing environment. In this paper, we study the channel-choice, pricing and ordering/production decisions of the risk-averse supplier and manufacturer in a two-tier supply chain with a B2B spot market. Our analysis shows that, to benefit from the B2B spot market and control the risk exposure, the upstream supplier should develop an integrated channel-choice and pricing strategy. When the supplier adopts a dual-channel strategy, the equilibrium contract price decreases in the supplier’s risk attitude, but increases in the demand uncertainty. However, it first decreases and then increases in the manufacturer’s risk attitude and spot price volatility. We conclude that rather than simply being a second channel, the B2B spot market provides a strategic tool to supply chain members to achieve an advantageous position in their contract trading.     

A note on “Seller’s optimal credit period and cycle time in a supply chain for deteriorating items with maximum lifetime”

In 2014, Wang et al. (2014) extended the model of Lou and Wang (2012) to incorporate the credit period dependent demand and default risk for deteriorating items with maximum lifetime. However, the rates of demand, default risk and deterioration in the model of Wang et al. (2014) are assumed to be specific functions of credit period which limits the contributions. In this note, we first generalize the theoretical results of Wang et al. (2014) under some certain conditions. Furthermore, we also present some structural results instead of a numerical analysis on variation of optimal replenishment and trade credit strategies with respect to key parameters.     

基于泛函分析的高校虚拟科研团队距离管理研究

随着通信和互联网技术的高速发展,在面对科研目标越来越复杂,学科划分越来越精细的背景下,组建跨时空、跨专业的虚拟科研团队将成为未来高校科研方式的主要发展方向.以某高校A虚拟科研团队为例,从行为距离这一新的视角分析虚拟科研团队管理中的行为难题,构建了虚拟科研团队的行为距离综合评价指标体系,采用了模糊评价原理来对行为距离进行度量.最后根据度量结果,提出了解决高校虚拟科研团队的距离难题的基本思路.     

大规模伤亡事件应对流程的前摄性调度优化

以死亡人数最少化为目标,研究大规模伤亡事件应对流程的前摄性调度优化问题。首先,使用伤情等级和伤情随机转化的马尔可夫链,建立伤员死亡概率与伤员处置时间的函数关系。随后,将研究问题转化为柔性作业车间静态调度问题,并设计遗传算法求解。最后用一个随机算例对算法进行仿真,结果表明：该算法可行有效;与现有研究中救援时间最短化的调度方法相比,伴随着可接受的救援时间跨度增加,该方法可大幅降低救援过程中的死亡人数。本文研究有助于决策者优化应急救援过程,有效减少死亡人员数量。