Positioning terrorism in management and marketing: Research propositions

Terrorism poses both direct and indirect threats to the operations of the firm. It represents a market imperfection that increases transaction costs and creates barriers to the free flow of goods, affecting potential gains that would occur in the presence of unhindered exchange. Terrorism reflects the risk or actual encounter of violent acts, whose goal is to engender fear, coercion, or intimidation. We investigate terrorism and its association with marketing strategy and operations. Key concepts on terrorism are reviewed and a collection of propositions is offered. We highlight the pivotal roles of sourcing, production, distribution, pricing, communications, and general business strategy as functions influenced by, or capable of influencing, terrorism. Lastly, we offer managerial implications, as well as directions and guidelines for future research.     

A Generalization of Geometric Brownian Motion with Applications

Although geometric Brownian motion has a great variety of applications, it can not cover all the random phenomena. The purpose of this article is to propose a model that generalizes geometric Brownian motion. We present some interesting applications of this model in financial engineering and statistical inferences for the unknown parameters.     

上证50ETF隐含高阶矩风险对股票收益的预测研究

高阶矩是刻画资产收益涨跌非对称和“尖峰厚尾”现象中不可忽略的系统性风险。本文基于我国上证50ETF期权数据采用无模型方法估计隐含波动率、隐含偏度和隐含峰度,通过自回归滑动平均模型提取期权隐含高阶矩新息(Innovations),将它们作为高阶矩风险的度量,探讨其对股票收益的预测作用。研究表明:①在控制换手率和股息率等变量后,隐含波动率对于上证50指数和市场未来4周的超额收益有显著负向的预测作用;②隐含偏度新息越低,上证50指数和市场的超额收益越高,这种预测能力在未来1周和未来4周均显著,但随着时间的推移,隐含偏度新息的预测能力逐渐下降;③隐含偏度风险对于我国股市横截面收益也有显著的解释能力,投资组合在隐含偏度风险因子上的风险暴露越大即因子载荷值越大,则未来的收益会越低;④隐含峰度新息总体上与股票收益负相关。     

Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights

Integrating retail decisions on such aspects as assortment, pricing, and inventory greatly improves profitability. We examine a multi-period selling horizon where a retailer jointly optimizes assortment planning, pricing, and inventory decisions for a product line of substitutable products, in a market with multiple customer segments. Focusing on fast-moving retail products, the problem is modeled as a mixed-integer nonlinear program where demand is driven by exogenous consumer reservation prices and endogenous assortment and pricing decisions. A mixed-integer linear reformulation is developed, which enables an exact solution to large problem instances (with up to a hundred products) in manageable times. Empirical evidence is provided in support of a classical deterministic maximum-surplus consumer choice model. Computational results and managerial insights are discussed. We find that the optimal assortment and pricing decisions do not exhibit a simple, intuitive structure that could be analytically characterized, which reflects the usefulness of optimization approaches to numerically identify attractive trade-offs for the decision-maker. We also observe that suboptimal inventory policies significantly decrease profitability, which highlights the importance of integrated decision-making. Finally, we find that the seasonality of consumer preferences and supply costs present an opportunity for boosting the profit via higher inventory levels and wider assortments.     

Optimal pricing for group buying with network effects

In this paper, we analyze online group-pricing mechanisms for sellers and compare them with the option of selling only to individuals. We formulate the demand for group buying and individual buying (GB and IB, respectively) based on the utility a consumer attains from each environment considering two specific types of externalities unique to our problem. First, we assume that consumers receive positive “network effects” from GB, i.e., they obtain utility from shopping with others because of information exchange and collective support. Second, they encounter a negative externality of group buying because of inconvenience costs and delays in receiving the products. The two types of externalities lead to distorted demand, which in turn affects prices and profits. We analyze the optimal and equilibrium strategies for a seller operating in monopoly, duopoly, and multiple-firm competition. We derive the equilibrium strategies and show the existence of a Nash Equilibrium under competition of multiple firms. In addition, we show that positive network effects from group buying often outweigh the negative externalities arising from costs.     

Viability of Auction‐Based Revenue Management in Sequential Markets

The Internet is providing an opportunity to revenue management practitioners to exploit the potential of auctions as a new price distribution channel. We develop a stochastic model for a high‐level abstraction of a revenue management system (RMS) that allows us to understand the potential of incorporating auctions in revenue management in the presence of forecast errors associated with key parameters. Our abstraction is for an environment where two market segments book in sequence and revenue management approaches consider auctions in none, one, or both segments. Key insights from our robust results are (i) limited auctions are best employed closest to the final sale date, (ii) counterbalancing forecast errors associated with overall traffic intensity and the proportion of customer arrivals in a segment is more important if an auction is adopted in that segment, and (iii) it is critically important not to err on the side of overestimating market willingness to pay.     

我国新股发行定价的市场化改革的政策效应

随着我国新股发行定价市场化改革的推进,新股发行市盈率和价格有所提高,然而一、二级市场的巨大价差并未得以缩小,反而有所提高,这是与缩小一、二级市场价差的改革初衷相违背的。同时,市场化改革还导致企业超额募集资金,并且出现流通股比例最小化的趋向,因而必须采取相应措施来进一步提高新股发行定价市场化改革的政策效应。     

Optimal Policy for a Reseller When the Supplier Offers a Temporary Reduction in Price*

A common practice in product distribution is the case in which the supplier offers a temporary reduction in price. It is suggested in the literature that in such situations, the reseller may engage in forward buying (i.e., purchasing additional stock at the reduced price offered by the supplier for later sale at the regular selling price). In this paper, a model is formulated of the reseller's response when the supplier offers a temporary reduction in price. It is assumed that the market demand for the product is elastic with respect to the selling price the reseller sets. A procedure for determining the optimal response of the reseller is developed. The model presented in this paper can easily be adapted to the case in which the reseller faces a permanent increase in the price charged by the supplier.     

Marketing Category Forecasting: An Alternative of BVAR‐Artificial Neural Networks*

Analyzing scanner data in brand management activities presents unique difficulties due to the vast quantity of the data. Time series methods that are able to handle the volume effectively often are inappropriate due to the violation of many statistical assumptions in the data characteristics. We examine scanner data sets for three brand categories and examine properties associated with many time series forecasting methods. Many violations are found with respect to linearity, normality, autocorrelation, and heteroscedasticity. With this in mind we compare the forecasting ability of neural networks that require no assumptions to two of the more robust time series techniques. Neural networks provide similar forecasts to Bayesian vector autoregression (BVAR), and both outperform generalized autoregressive conditional herteroscedasticty (GARCH) models.     

基于关系型贷款的城市商业银行小企业贷款定价研究

城市商业银行与小企业有着天然的、共生共荣的联系。如何制定一个科学合理的小企业贷款利率定价机制,是城市商业银行经营决策中的重要课题。通过对某城市商业银行的小企业贷款定价现状进行的实证分析,发现银行主要侧重于风险的考虑,忽略了银企之间的“关系”因素,没有借助“关系”收集并利用“软”信息进行准确定价。在此基础上,以关系型贷款作为小企业贷款定价的指导思想,研究设计了基于关系型贷款的定价思路。