Agent‐based model for economic impact of free software

This article describes the potential impact that free (i.e., open source) software can have on an existing commercial software market. A model for the software market is constructed in terms of autonomous agents, which represent the users, the companies, and the free software providers. The model specifies a reservation price for each user agent and develops a gradient learning strategy for revenue‐maximizing company agents. Simulations explore parameters such as the demand distribution, and the relative importance of market share, advertising and random effects in product visibility. Results from the case without free software show a prevalence of monopolies, which is consistent with other studies of high‐technology market economics. The effects of free software are not uniform, but are highly parameter dependent. A “capture region” is found in which free software eventually dominates the market. © 2003 Wiley Periodicals, Inc.     

Optimal ordering and pricing policy for an inventory system with trial periods

It is a business practice that home shopping companies offer a free trial period for their products with a goal of increasing sales. Under this policy, if for any reason customers are not satisfied with the purchase, they can return the product for a refund within the trial period. To develop inventory strategies in such environment, home shopping companies should take the return phenomenon into account so as to increase their profit. This paper considers this phenomenon and develops a seasonal inventory model to deal with the problem. Two scenarios are analyzed. In the first scenario, demand is assumed to be linearly price-dependent while in the second one, it is assumed to be exponentially price-dependent. The purpose of this research is to maximize the total profit over a given planning period by determining the optimal ordering quantity and price. The analytical results demonstrate that the optimal ordering quantity and prices are obtained using closed-form formulas.     

考虑云安全风险的个人云存储服务最优定价策略

针对现有个人云存储服务纷纷关闭的现象,如何根据不同市场时期和云用户特征,制定合理的定价策略已成为个人云存储服务商面临的挑战性问题。本文在考虑云安全风险,云用户感知价值及弹性成本对个人云存储服务定价的影响,建立了基于云安全风险的两阶段定价模型,给出了免费试用时长确定下的最优决策及免费试用时长不确定下的最优免费试用时长及最优价格。借助数值分析,进一步研究了云安全风险系数,云用户感知价值,云安全运营成本系数对最优免费时长,最优利润的影响,结果表明,当云安全风险系数适中时,个人云存储供应商(PCSP)采取两阶段定价策略。另外,最优利润随着云安全风险系数,免费试用时长,单位安全运营成本的增加先增加后减少。     

考虑地位效应时炫耀性虚拟商品的最优定价与普及版本化

考虑地位效应的影响,针对炫耀性虚拟商品,决策最优定价和普及版本化。建立了单标准版策略、双版本免费普及策略和双版本销售策略等三种模型,求解得到企业在对应策略下对单版本或双版本的炫耀性虚拟商品的最优定价,在此基础上分析得到地位效应对虚拟商品价格、企业利润和最优普及版本化策略的影响。研究发现地位效应是导致标准版炫耀性虚拟商品价格和企业利润提升的因素;当存在地位效应时,双版本销售策略是炫耀性虚拟商品的最优普及版本化策略;但双版本销售策略相比于单标准版策略的优势在一定条件下因网络外部性增强而削弱。     

Stabilization of the trial method for the Bernoulli problem in case of prescribed Dirichlet data

We apply the trial method for the solution of Bernoulli's free boundary problem when the Dirichlet boundary condition is imposed for the solution of the underlying Laplace equation, and the free boundary is updated according to the Neumann boundary condition. The Dirichlet boundary value problem for the Laplacian is solved by an exponentially convergent boundary element method. The update rule for the free boundary is derived from the linearization of the Neumann data around the actual free boundary. With the help of shape sensitivity analysis and Banach's fixed‐point theorem, we shed light on the convergence of the respective trial method. Especially, we derive a stabilized version of this trial method. Numerical examples validate the theoretical findings.Copyright © 2014 John Wiley & Sons, Ltd.     

考虑在线评论的产品免费试用策略

商家提供产品免费试用,要求试用者对产品质量进行在线评论,消费者基于在线评论进行购买决策。免费试用者数量越多,在线评论数量越多,消费者对在线评论越信任。考虑在线评论和产品生产成本,研究商家的产品免费试用策略及其对利润的影响。研究发现,虽然商家承受免费试用的产品生产成本损失,但是免费试用产生的在线评论可以使商家更好地按照产品质量制定价格,因此当产品生产成本较低时,提供免费试用可以提高商家利润。产品生产成本提高,商家的最优免费试用数量减少。产品质量不确定性越大或失配距离单位成本越低,免费试用给商家带来的收益越高。     

基于Hotelling模型的双寡头免费增值策略竞争分析

软件产品的经验性和强网络效应使得企业往往依靠免费的基础产品积聚人气,再通过收费的增值产品或服务来盈利。现有免费增值策略相关研究多局限于垄断情况,对多个企业之间的竞争交互鲜有探讨。基于产品网络效应和消费者偏好差异,本文构建Hotelling模型研究了双寡头企业免费增值策略博弈均衡及其影响因素。结果表明:若网络效应相对较强,企业都应采用免费增值策略;若网络效应相对较弱,都不采用;若网络效应相对处于中等水平,存在“都不采用”和“都采用”两种可能的均衡结果,但前者情况下双方企业都能获得更大利润。另外,消费者对企业之间的水平差异越敏感,对免费版本的质量要求越高,企业采用免费增值策略的动力越弱,“都不采用”区域扩大,而“都采用”区域缩小。     

KamiWaAI – interactive 3D sketching with Java based on Cl(4, 1) conformal model of Euclidean space

This paper introduces the new interactive Java sketching software KamiWaAi, recently developed at the University of Fukui. Its graphical user interface enables the user without any knowledge of both mathematics or computer science, to do full three dimensional “drawings” on the screen. The resulting constructions can be reshaped interactively by dragging its points over the screen. The programming approach is new. KamiWaAi implements geometric objects like points, lines, circles, spheres, etc. directly as software objects (Java classes) of the same name. These software objects are geometric entities mathematically defined and manipulated in a conformal geometric algebra, combining the five dimensions of origin, three space and infinity. Simple geometric products in this algebra represent geometric unions, intersections, arbitrary rotations and translations, projections, distance, etc. To ease the coordinate free and matrix free implementation of this fundamental geometric product, a new algebraic three level approach is presented. Finally details about the Java classes of the new GeometricAlgebra software package and their associated methods are given. KamiWaAi is available for free internet download.     

融合两阶段过程模型和改进Bass模型的网络社交平台上产品信息扩散研究

提出并验证了融合两阶段过程模型和改进Bass模型的网络社交平台上产品信息扩散模型。考虑用户转发动机构建产品信息扩散两阶段过程模型;考虑用户兴趣衰减效应改进Bass模型;融合这两个模型,考虑产品信息发布者明星效应、产品信息质量对产品信息扩散的影响,提出了产品信息扩散模型。以2019年11～12月新浪电影发布的电影预告片转发数据验证了所提模型,并与Bass模型进行了比较。结果表明,用户转发动机和用户兴趣衰减效应对产品信息扩散均有显著影响,所提模型的预测精度和拟合效果均优于Bass模型。所提模型可用于存在不同转发动机及具有衰减效应的其他信息转发量预测,尤其适合于在产品信息投放前期和早期对转发量的预测,是对信息扩散模型的补充。     

融合情感评论倾向与均衡长尾物品的推荐方法

推荐领域中已有研究较多的考虑属性维度在评分-物品上来提高算法的准确性,对于用户对产品的真实态度判断不够。论文利用LSTM神经网络模型将用户评论情感得分和用户评分进行融合分析,来计算用户对物品真正的兴趣度;运用向量空间对用户情感进行三分类,借鉴经济学中基尼系数的思想,引入惩罚因子通过对热门物品进行调节,发挥系统的长尾能力从而增加推荐结果的覆盖率,从而实现对热门物品和冷门物品被推荐程度的均衡优化。最后,对情感系数和惩罚系数参数的取值进行实验,得出最优模型参数组合,结果表明,评论的情感因素和惩罚系数对于构建性能更优的推荐模型效果明显,该模型在推荐的准确率和覆盖率上相较其他主流模型更加符合用户需求。     

Stochastic optimization on social networks with application to service pricing

In this paper we develop a combined simulation and optimization approach for solving difficult decision problems on complex dynamic networks. For a specific reference problem we consider a telecommunication service provider who offers a telecommunication service to a market with network effects. More particularly, the service consumption of an individual user depends on both idiosyncratic characteristics and the popularity of this service among the customer’s immediate neighborhood. Both the social network and the individual user preferences are largely heterogeneous and changing over time. In addition the service provider’s decisions are made in absence of perfect knowledge about user preferences. The service provider pursues the strategy of stimulating the demand by offering differentiated prices to the customers. For finding the optimal pricing we apply a stochastic quasi-gradient algorithm that is integrated with a simulation model that drives the evolution of the network and user preferences over time. We show that exploiting the social network structure and implementing differentiated pricing can substantially increase the revenues of a service provider operating on a social network. More generally, we show that stochastic gradient methods represent a powerful methodology for the optimization of decisions in social networks.     

Technology choice and timing with positive network effects

When two competing and incompatible products coexist in a market, potential users face a choice between the two products and the alternative of deferring the decision. This paper examines the choice between the two substitutes, where each one is subject to a positive network effect. That is, a user of one of the products experiences an increase in the value for each additional person using the same product. We examine this buy or wait problem, either for an individual or a manager making the investment on behalf of a firm, by formulating and analyzing a decision-theoretic model. To model the stochastic evolution of market share, we build on the generalized Polya urn of Arthur et al. [Arthur, W.B., Ermoliev, Y.M., Kaniovski, Y.M., 1987. Path-dependent processes and the emergence of macro-structure. European Journal Of Operational Research 30 (3), 294–303], allowing for composition of the market to affect not just the relative market shares but also the absolute growth rate of the market. We show that the optimal strategy is defined by a pair of market penetration thresholds that depend on the market composition. Looking at the effect of the network effects on the optimal strategy, we find that more pronounced network effects can either raise or lower the penetration thresholds.     

移动学习软件打卡返现的免费增值策略研究

考虑网络外部性因素,研究移动学习软件打卡返现的免费增值策略。分别构建企业在垄断市场和竞争市场下的数学模型,得到不同市场结构下企业最优的产品价格、需求及利润,并通过均衡结果分析企业的策略选择。研究表明：(1)在垄断市场中,企业应当选择打卡返现策略,此时产品定价较高,付费市场需求较低。(2)在竞争市场中,对于企业2(劣势企业)而言,无论企业1(优势企业)采取何种策略,均不应选择打卡返现策略;对于企业1(优势企业)而言,只有当两家企业产品差异程度较大时,才应选择打卡返现策略。     

Minimizing the maximum network flow: models and algorithms with resource synergy considerations

In this paper, we model and solve the network interdiction problem of minimizing the maximum flow through a network from a given source node to a terminus node, while incorporating different forms of superadditive synergy effects of the resources applied to the arcs in the network. Within this context, we examine linear, concave, and convex–concave synergy relationships, illustrate their relative effect on optimal solution characteristics, and accordingly develop and test effective solution procedures for the underlying problems. For a concave synergy relationship, which yields a convex programme, we propose an inner-linearization procedure that significantly outperforms the competitive commercial solver SBB by improving the quality of solutions found by the latter by 6.2% (within a time limit of 1800 CPU?s), while saving 84.5% of the required computational effort. For general non-concave synergy relationships, we develop an outer-approximation-based heuristic that achieves solutions of objective value 0.20% better than the commercial global optimization software BARON, with a 99.3% reduction in computational effort for the subset of test problems for which BARON could identify a feasible solution within the set time limit.     

Wireless network capacity management: A real options approach

This paper applies financial option valuation methods to new wireless network capacity investment decision timing. In particular, we consider the case of network capacity for cellular telephone service. Given a cluster of base stations (with a certain traffic capacity per base station), we determine when it is optimal to increase capacity for each of the base stations contained in the cluster. We express this in terms of the fraction of total cluster capacity in use, i.e. we calculate the optimal time to upgrade in terms of the ratio of observed usage to existing capacity. We study the optimal decision problem of adding new capacity in the presence of stochastic wireless demand for services. A four factor algorithm is developed, based on a real options formulation. Numerical examples are provided to illustrate various aspects of the model.     

Can piracy lead to higher prices in the music and motion picture industries?

Piracy of copyrighted goods has received increased attention in the literature. Much of this research has focused on pricing policies, protection against piracy, and governmental policies in the software industries. In this paper, we focus on pricing policies of producers in the music and motion picture industries. Exact analytical results are difficult to obtain; therefore, we develop an approximating function of the cumulative demand. This enables us to obtain closed-form expressions for the optimal price. Our results show that the existence of piracy in these industries and the lack of positive network externalities may cause monopolists to charge higher prices to optimize profits. These prices increase with increases in the speed of piracy and longer product lifecycles. We demonstrate the accuracy of our demand approximation function using a numerical experiment. We show how a two-price strategy and dual distribution channels may help in reducing the negative effects of piracy. We perform some numerical sensitivity analysis and provide managerial insights.     

Algorithms and software for total variation image reconstruction via first-order methods

This paper describes new algorithms and related software for total variation (TV) image reconstruction, more specifically: denoising, inpainting, and deblurring. The algorithms are based on one of Nesterov’s first-order methods, tailored to the image processing applications in such a way that, except for the mandatory regularization parameter, the user needs not specify any parameters in the algorithms. The software is written in C with interface to Matlab (version 7.5 or later), and we demonstrate its performance and use with examples.     

计及网络效应的共享电动汽车租赁网络扩张特征分析与布局算法构建

共享租赁网络规划的合理性是共享电动汽车得以顺利发展的基础。为此,本文以共享租赁网络的合理布局作为主题,对共享电动汽车租赁网络的扩展特征进行建模分析,并据此提出相应的布局算法。研究发现:正负网络效应的综合影响使各类网点呈现出不同的利润特征,而对不同类型网点布局的先后顺序,将对整个网络的利润产生影响;基于此,本文提出两步聚类萤火虫算法,该算法不仅能提高前期搜索的效率和精度,同时通过对各候选网点的归类,可便捷地识别各候选网点的布局顺序。最后,通过算例分析进一步论证了所提算法的适用性。     

Flow-level performance and capacity of wireless networks with user mobility

The performance evaluation of wireless networks is severely complicated by the specific features of radio communication, such as highly variable channel conditions, interference issues, and possible hand-offs among base stations. The latter elements have no natural counterparts in wireline scenarios, and create a need for novel performance models that account for the impact of these characteristics on the service rates of users. Motivated by the above issues, we review several models for characterizing the capacity and evaluating the flow-level performance of wireless networks carrying elastic data transfers. We first examine the flow-level performance and stability of a wide family of so-called α-fair channel-aware scheduling strategies. We establish that these disciplines provide maximum stability, and describe how the special case of the Proportional Fair policy gives rise to a Processor-Sharing model with a state-dependent service rate. Next we turn attention to a network of several base stations with inter-cell interference. We derive both necessary and sufficient stability conditions and construct lower and upper bounds for the flow-level performance measures. Lastly we investigate the impact of user mobility that occurs on a slow timescale and causes possible hand-offs of active sessions. We show that the mobility tends to increase the capacity region, both in the case of globally optimal scheduling and local α-fair scheduling. It is additionally demonstrated that the capacity and user throughput improve with lower values of the fairness index α.     

Improved trial methods for a class of generalized Bernoulli problems

The aim of this article is to develop improved trial methods for the solution of a generalized exterior Bernoulli free boundary problem. At the free boundary, we prescribe the Neumann boundary condition and update the free boundary with the help of the remaining Dirichlet boundary condition. Appropriate update rules are obtained by expanding the state's Dirichlet data at the actual boundary via a Taylor expansion of first and second order. The resulting trial methods converge linearly for both cases, although the trial method based on the second order Taylor expansion is much more robust. Nevertheless, via results of shape sensitivity analysis, we are able to modify the update rules such that their convergence is improved. The feasibility of the proposed trial methods and their performance is demonstrated by numerical results.